Sample records for conformation ensemble generator
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Bioactive focus in conformational ensembles: a pluralistic approach
NASA Astrophysics Data System (ADS)
Habgood, Matthew
2017-12-01
Computational generation of conformational ensembles is key to contemporary drug design. Selecting the members of the ensemble that will approximate the conformation most likely to bind to a desired target (the bioactive conformation) is difficult, given that the potential energy usually used to generate and rank the ensemble is a notoriously poor discriminator between bioactive and non-bioactive conformations. In this study an approach to generating a focused ensemble is proposed in which each conformation is assigned multiple rankings based not just on potential energy but also on solvation energy, hydrophobic or hydrophilic interaction energy, radius of gyration, and on a statistical potential derived from Cambridge Structural Database data. The best ranked structures derived from each system are then assembled into a new ensemble that is shown to be better focused on bioactive conformations. This pluralistic approach is tested on ensembles generated by the Molecular Operating Environment's Low Mode Molecular Dynamics module, and by the Cambridge Crystallographic Data Centre's conformation generator software.
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Monte Carlo replica-exchange based ensemble docking of protein conformations.
Zhang, Zhe; Ehmann, Uwe; Zacharias, Martin
2017-05-01
A replica-exchange Monte Carlo (REMC) ensemble docking approach has been developed that allows efficient exploration of protein-protein docking geometries. In addition to Monte Carlo steps in translation and orientation of binding partners, possible conformational changes upon binding are included based on Monte Carlo selection of protein conformations stored as ordered pregenerated conformational ensembles. The conformational ensembles of each binding partner protein were generated by three different approaches starting from the unbound partner protein structure with a range spanning a root mean square deviation of 1-2.5 Å with respect to the unbound structure. Because MC sampling is performed to select appropriate partner conformations on the fly the approach is not limited by the number of conformations in the ensemble compared to ensemble docking of each conformer pair in ensemble cross docking. Although only a fraction of generated conformers was in closer agreement with the bound structure the REMC ensemble docking approach achieved improved docking results compared to REMC docking with only the unbound partner structures or using docking energy minimization methods. The approach has significant potential for further improvement in combination with more realistic structural ensembles and better docking scoring functions. Proteins 2017; 85:924-937. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
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Benchmarking Commercial Conformer Ensemble Generators.
Friedrich, Nils-Ole; de Bruyn Kops, Christina; Flachsenberg, Florian; Sommer, Kai; Rarey, Matthias; Kirchmair, Johannes
2017-11-27
We assess and compare the performance of eight commercial conformer ensemble generators (ConfGen, ConfGenX, cxcalc, iCon, MOE LowModeMD, MOE Stochastic, MOE Conformation Import, and OMEGA) and one leading free algorithm, the distance geometry algorithm implemented in RDKit. The comparative study is based on a new version of the Platinum Diverse Dataset, a high-quality benchmarking dataset of 2859 protein-bound ligand conformations extracted from the PDB. Differences in the performance of commercial algorithms are much smaller than those observed for free algorithms in our previous study (J. Chem. Inf. 2017, 57, 529-539). For commercial algorithms, the median minimum root-mean-square deviations measured between protein-bound ligand conformations and ensembles of a maximum of 250 conformers are between 0.46 and 0.61 Å. Commercial conformer ensemble generators are characterized by their high robustness, with at least 99% of all input molecules successfully processed and few or even no substantial geometrical errors detectable in their output conformations. The RDKit distance geometry algorithm (with minimization enabled) appears to be a good free alternative since its performance is comparable to that of the midranked commercial algorithms. Based on a statistical analysis, we elaborate on which algorithms to use and how to parametrize them for best performance in different application scenarios.
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Uehara, Shota; Tanaka, Shigenori
2017-04-24
Protein flexibility is a major hurdle in current structure-based virtual screening (VS). In spite of the recent advances in high-performance computing, protein-ligand docking methods still demand tremendous computational cost to take into account the full degree of protein flexibility. In this context, ensemble docking has proven its utility and efficiency for VS studies, but it still needs a rational and efficient method to select and/or generate multiple protein conformations. Molecular dynamics (MD) simulations are useful to produce distinct protein conformations without abundant experimental structures. In this study, we present a novel strategy that makes use of cosolvent-based molecular dynamics (CMD) simulations for ensemble docking. By mixing small organic molecules into a solvent, CMD can stimulate dynamic protein motions and induce partial conformational changes of binding pocket residues appropriate for the binding of diverse ligands. The present method has been applied to six diverse target proteins and assessed by VS experiments using many actives and decoys of DEKOIS 2.0. The simulation results have revealed that the CMD is beneficial for ensemble docking. Utilizing cosolvent simulation allows the generation of druggable protein conformations, improving the VS performance compared with the use of a single experimental structure or ensemble docking by standard MD with pure water as the solvent.
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NASA Astrophysics Data System (ADS)
Yongye, Austin B.; Bender, Andreas; Martínez-Mayorga, Karina
2010-08-01
Representing the 3D structures of ligands in virtual screenings via multi-conformer ensembles can be computationally intensive, especially for compounds with a large number of rotatable bonds. Thus, reducing the size of multi-conformer databases and the number of query conformers, while simultaneously reproducing the bioactive conformer with good accuracy, is of crucial interest. While clustering and RMSD filtering methods are employed in existing conformer generators, the novelty of this work is the inclusion of a clustering scheme (NMRCLUST) that does not require a user-defined cut-off value. This algorithm simultaneously optimizes the number and the average spread of the clusters. Here we describe and test four inter-dependent approaches for selecting computer-generated conformers, namely: OMEGA, NMRCLUST, RMS filtering and averaged- RMS filtering. The bioactive conformations of 65 selected ligands were extracted from the corresponding protein:ligand complexes from the Protein Data Bank, including eight ligands that adopted dissimilar bound conformations within different receptors. We show that NMRCLUST can be employed to further filter OMEGA-generated conformers while maintaining biological relevance of the ensemble. It was observed that NMRCLUST (containing on average 10 times fewer conformers per compound) performed nearly as well as OMEGA, and both outperformed RMS filtering and averaged- RMS filtering in terms of identifying the bioactive conformations with excellent and good matches (0.5 < RMSD < 1.0 Å). Furthermore, we propose thresholds for OMEGA root-mean square filtering depending on the number of rotors in a compound: 0.8, 1.0 and 1.4 for structures with low (1-4), medium (5-9) and high (10-15) numbers of rotatable bonds, respectively. The protocol employed is general and can be applied to reduce the number of conformers in multi-conformer compound collections and alleviate the complexity of downstream data processing in virtual screening experiments.
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Unbiased, scalable sampling of protein loop conformations from probabilistic priors.
Zhang, Yajia; Hauser, Kris
2013-01-01
Protein loops are flexible structures that are intimately tied to function, but understanding loop motion and generating loop conformation ensembles remain significant computational challenges. Discrete search techniques scale poorly to large loops, optimization and molecular dynamics techniques are prone to local minima, and inverse kinematics techniques can only incorporate structural preferences in adhoc fashion. This paper presents Sub-Loop Inverse Kinematics Monte Carlo (SLIKMC), a new Markov chain Monte Carlo algorithm for generating conformations of closed loops according to experimentally available, heterogeneous structural preferences. Our simulation experiments demonstrate that the method computes high-scoring conformations of large loops (>10 residues) orders of magnitude faster than standard Monte Carlo and discrete search techniques. Two new developments contribute to the scalability of the new method. First, structural preferences are specified via a probabilistic graphical model (PGM) that links conformation variables, spatial variables (e.g., atom positions), constraints and prior information in a unified framework. The method uses a sparse PGM that exploits locality of interactions between atoms and residues. Second, a novel method for sampling sub-loops is developed to generate statistically unbiased samples of probability densities restricted by loop-closure constraints. Numerical experiments confirm that SLIKMC generates conformation ensembles that are statistically consistent with specified structural preferences. Protein conformations with 100+ residues are sampled on standard PC hardware in seconds. Application to proteins involved in ion-binding demonstrate its potential as a tool for loop ensemble generation and missing structure completion.
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Unbiased, scalable sampling of protein loop conformations from probabilistic priors
2013-01-01
Background Protein loops are flexible structures that are intimately tied to function, but understanding loop motion and generating loop conformation ensembles remain significant computational challenges. Discrete search techniques scale poorly to large loops, optimization and molecular dynamics techniques are prone to local minima, and inverse kinematics techniques can only incorporate structural preferences in adhoc fashion. This paper presents Sub-Loop Inverse Kinematics Monte Carlo (SLIKMC), a new Markov chain Monte Carlo algorithm for generating conformations of closed loops according to experimentally available, heterogeneous structural preferences. Results Our simulation experiments demonstrate that the method computes high-scoring conformations of large loops (>10 residues) orders of magnitude faster than standard Monte Carlo and discrete search techniques. Two new developments contribute to the scalability of the new method. First, structural preferences are specified via a probabilistic graphical model (PGM) that links conformation variables, spatial variables (e.g., atom positions), constraints and prior information in a unified framework. The method uses a sparse PGM that exploits locality of interactions between atoms and residues. Second, a novel method for sampling sub-loops is developed to generate statistically unbiased samples of probability densities restricted by loop-closure constraints. Conclusion Numerical experiments confirm that SLIKMC generates conformation ensembles that are statistically consistent with specified structural preferences. Protein conformations with 100+ residues are sampled on standard PC hardware in seconds. Application to proteins involved in ion-binding demonstrate its potential as a tool for loop ensemble generation and missing structure completion. PMID:24565175
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Peptidic Macrocycles - Conformational Sampling and Thermodynamic Characterization
2018-01-01
Macrocycles are of considerable interest as highly specific drug candidates, yet they challenge standard conformer generators with their large number of rotatable bonds and conformational restrictions. Here, we present a molecular dynamics-based routine that bypasses current limitations in conformational sampling and extensively profiles the free energy landscape of peptidic macrocycles in solution. We perform accelerated molecular dynamics simulations to capture a diverse conformational ensemble. By applying an energetic cutoff, followed by geometric clustering, we demonstrate the striking robustness and efficiency of the approach in identifying highly populated conformational states of cyclic peptides. The resulting structural and thermodynamic information is benchmarked against interproton distances from NMR experiments and conformational states identified by X-ray crystallography. Using three different model systems of varying size and flexibility, we show that the method reliably reproduces experimentally determined structural ensembles and is capable of identifying key conformational states that include the bioactive conformation. Thus, the described approach is a robust method to generate conformations of peptidic macrocycles and holds promise for structure-based drug design. PMID:29652495
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Peptidic Macrocycles - Conformational Sampling and Thermodynamic Characterization.
Kamenik, Anna S; Lessel, Uta; Fuchs, Julian E; Fox, Thomas; Liedl, Klaus R
2018-05-29
Macrocycles are of considerable interest as highly specific drug candidates, yet they challenge standard conformer generators with their large number of rotatable bonds and conformational restrictions. Here, we present a molecular dynamics-based routine that bypasses current limitations in conformational sampling and extensively profiles the free energy landscape of peptidic macrocycles in solution. We perform accelerated molecular dynamics simulations to capture a diverse conformational ensemble. By applying an energetic cutoff, followed by geometric clustering, we demonstrate the striking robustness and efficiency of the approach in identifying highly populated conformational states of cyclic peptides. The resulting structural and thermodynamic information is benchmarked against interproton distances from NMR experiments and conformational states identified by X-ray crystallography. Using three different model systems of varying size and flexibility, we show that the method reliably reproduces experimentally determined structural ensembles and is capable of identifying key conformational states that include the bioactive conformation. Thus, the described approach is a robust method to generate conformations of peptidic macrocycles and holds promise for structure-based drug design.
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Yongye, Austin B.; Bender, Andreas
2010-01-01
Representing the 3D structures of ligands in virtual screenings via multi-conformer ensembles can be computationally intensive, especially for compounds with a large number of rotatable bonds. Thus, reducing the size of multi-conformer databases and the number of query conformers, while simultaneously reproducing the bioactive conformer with good accuracy, is of crucial interest. While clustering and RMSD filtering methods are employed in existing conformer generators, the novelty of this work is the inclusion of a clustering scheme (NMRCLUST) that does not require a user-defined cut-off value. This algorithm simultaneously optimizes the number and the average spread of the clusters. Here we describe and test four inter-dependent approaches for selecting computer-generated conformers, namely: OMEGA, NMRCLUST, RMS filtering and averaged-RMS filtering. The bioactive conformations of 65 selected ligands were extracted from the corresponding protein:ligand complexes from the Protein Data Bank, including eight ligands that adopted dissimilar bound conformations within different receptors. We show that NMRCLUST can be employed to further filter OMEGA-generated conformers while maintaining biological relevance of the ensemble. It was observed that NMRCLUST (containing on average 10 times fewer conformers per compound) performed nearly as well as OMEGA, and both outperformed RMS filtering and averaged-RMS filtering in terms of identifying the bioactive conformations with excellent and good matches (0.5 < RMSD < 1.0 Å). Furthermore, we propose thresholds for OMEGA root-mean square filtering depending on the number of rotors in a compound: 0.8, 1.0 and 1.4 for structures with low (1–4), medium (5–9) and high (10–15) numbers of rotatable bonds, respectively. The protocol employed is general and can be applied to reduce the number of conformers in multi-conformer compound collections and alleviate the complexity of downstream data processing in virtual screening experiments. Electronic supplementary material The online version of this article (doi:10.1007/s10822-010-9365-1) contains supplementary material, which is available to authorized users. PMID:20499135
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Using simulation to interpret experimental data in terms of protein conformational ensembles.
Allison, Jane R
2017-04-01
In their biological environment, proteins are dynamic molecules, necessitating an ensemble structural description. Molecular dynamics simulations and solution-state experiments provide complimentary information in the form of atomically detailed coordinates and averaged or distributions of structural properties or related quantities. Recently, increases in the temporal and spatial scale of conformational sampling and comparison of the more diverse conformational ensembles thus generated have revealed the importance of sampling rare events. Excitingly, new methods based on maximum entropy and Bayesian inference are promising to provide a statistically sound mechanism for combining experimental data with molecular dynamics simulations. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Conformational Heterogeneity of Unbound Proteins Enhances Recognition in Protein-Protein Encounters.
Pallara, Chiara; Rueda, Manuel; Abagyan, Ruben; Fernández-Recio, Juan
2016-07-12
To understand cellular processes at the molecular level we need to improve our knowledge of protein-protein interactions, from a structural, mechanistic, and energetic point of view. Current theoretical studies and computational docking simulations show that protein dynamics plays a key role in protein association and support the need for including protein flexibility in modeling protein interactions. Assuming the conformational selection binding mechanism, in which the unbound state can sample bound conformers, one possible strategy to include flexibility in docking predictions would be the use of conformational ensembles originated from unbound protein structures. Here we present an exhaustive computational study about the use of precomputed unbound ensembles in the context of protein docking, performed on a set of 124 cases of the Protein-Protein Docking Benchmark 3.0. Conformational ensembles were generated by conformational optimization and refinement with MODELLER and by short molecular dynamics trajectories with AMBER. We identified those conformers providing optimal binding and investigated the role of protein conformational heterogeneity in protein-protein recognition. Our results show that a restricted conformational refinement can generate conformers with better binding properties and improve docking encounters in medium-flexible cases. For more flexible cases, a more extended conformational sampling based on Normal Mode Analysis was proven helpful. We found that successful conformers provide better energetic complementarity to the docking partners, which is compatible with recent views of binding association. In addition to the mechanistic considerations, these findings could be exploited for practical docking predictions of improved efficiency.
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Monitoring of the Conformational Space of Dipeptides by Generative Topographic Mapping.
Horvath, Dragos; Marcou, Gilles; Varnek, Alexandre
2018-01-01
This work describes a procedure to build generative topographic maps (GTM) as 2D representation of the conformational space (CS) of dipeptides. GTMs with excellent propensities to support highly predictive landscapes of various conformational properties were reported for three dipeptides (AA, KE and KR). CS monitoring via GTMproceeds through the projection of conformer ensembles on the map, producing cumulated responsibility (CR) vectors characteristic of the CS areas covered by the ensemble. Overlap of the CS areas visited by two distinct simulations can be expressed by the Tanimoto coefficient Tc of the associated CRs. This idea was used to monitor the reproducibility of the stochastic evolutionary conformer generation process implemented in S4MPLE. It could be shown that conformers produced by <500 S4MPLE runs reproducibly cover the relevant CS zone at given setup of the driving force field. The propensity of a simulation to visit the native CS zone can thus be quantitatively estimated, as the Tc score with respect to the "native" CR, as defined by the ensemble of dipeptide geometries extracted from PDB proteins. It could be shown that low-energy CS regions were indeed found to fall within the native zone. The Tc overlap score behaved as a smooth function of force field parameters. This opens the perspective of a novel force field parameter tuning procedure, bound to simultaneously optimize the behavior of the in Silico simulations for every possible dipeptide. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Ensemble models of proteins and protein domains based on distance distribution restraints.
Jeschke, Gunnar
2016-04-01
Conformational ensembles of intrinsically disordered peptide chains are not fully determined by experimental observations. Uncertainty due to lack of experimental restraints and due to intrinsic disorder can be distinguished if distance distributions restraints are available. Such restraints can be obtained from pulsed dipolar electron paramagnetic resonance (EPR) spectroscopy applied to pairs of spin labels. Here, we introduce a Monte Carlo approach for generating conformational ensembles that are consistent with a set of distance distribution restraints, backbone dihedral angle statistics in known protein structures, and optionally, secondary structure propensities or membrane immersion depths. The approach is tested with simulated restraints for a terminal and an internal loop and for a protein with 69 residues by using sets of sparse restraints for underlying well-defined conformations and for published ensembles of a premolten globule-like and a coil-like intrinsically disordered protein. © 2016 Wiley Periodicals, Inc.
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Conformational and functional analysis of molecular dynamics trajectories by Self-Organising Maps
2011-01-01
Background Molecular dynamics (MD) simulations are powerful tools to investigate the conformational dynamics of proteins that is often a critical element of their function. Identification of functionally relevant conformations is generally done clustering the large ensemble of structures that are generated. Recently, Self-Organising Maps (SOMs) were reported performing more accurately and providing more consistent results than traditional clustering algorithms in various data mining problems. We present a novel strategy to analyse and compare conformational ensembles of protein domains using a two-level approach that combines SOMs and hierarchical clustering. Results The conformational dynamics of the α-spectrin SH3 protein domain and six single mutants were analysed by MD simulations. The Cα's Cartesian coordinates of conformations sampled in the essential space were used as input data vectors for SOM training, then complete linkage clustering was performed on the SOM prototype vectors. A specific protocol to optimize a SOM for structural ensembles was proposed: the optimal SOM was selected by means of a Taguchi experimental design plan applied to different data sets, and the optimal sampling rate of the MD trajectory was selected. The proposed two-level approach was applied to single trajectories of the SH3 domain independently as well as to groups of them at the same time. The results demonstrated the potential of this approach in the analysis of large ensembles of molecular structures: the possibility of producing a topological mapping of the conformational space in a simple 2D visualisation, as well as of effectively highlighting differences in the conformational dynamics directly related to biological functions. Conclusions The use of a two-level approach combining SOMs and hierarchical clustering for conformational analysis of structural ensembles of proteins was proposed. It can easily be extended to other study cases and to conformational ensembles from other sources. PMID:21569575
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Johnson, David K.; Karanicolas, John
2015-01-01
Small-molecules that inhibit interactions between specific pairs of proteins have long represented a promising avenue for therapeutic intervention in a variety of settings. Structural studies have shown that in many cases, the inhibitor-bound protein adopts a conformation that is distinct from its unbound and its protein-bound conformations. This plasticity of the protein surface presents a major challenge in predicting which members of a protein family will be inhibited by a given ligand. Here, we use biased simulations of Bcl-2-family proteins to generate ensembles of low-energy conformations that contain surface pockets suitable for small molecule binding. We find that the resulting conformational ensembles include surface pockets that mimic those observed in inhibitor-bound crystal structures. Next, we find that the ensembles generated using different members of this protein family are overlapping but distinct, and that the activity of a given compound against a particular family member (ligand selectivity) can be predicted from whether the corresponding ensemble samples a complementary surface pocket. Finally, we find that each ensemble includes certain surface pockets that are not shared by any other family member: while no inhibitors have yet been identified to take advantage of these pockets, we expect that chemical scaffolds complementing these “distinct” pockets will prove highly selective for their targets. The opportunity to achieve target selectivity within a protein family by exploiting differences in surface fluctuations represents a new paradigm that may facilitate design of family-selective small-molecule inhibitors of protein-protein interactions. PMID:25706586
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Predicting bioactive conformations and binding modes of macrocycles
NASA Astrophysics Data System (ADS)
Anighoro, Andrew; de la Vega de León, Antonio; Bajorath, Jürgen
2016-10-01
Macrocyclic compounds experience increasing interest in drug discovery. It is often thought that these large and chemically complex molecules provide promising candidates to address difficult targets and interfere with protein-protein interactions. From a computational viewpoint, these molecules are difficult to treat. For example, flexible docking of macrocyclic compounds is hindered by the limited ability of current docking approaches to optimize conformations of extended ring systems for pose prediction. Herein, we report predictions of bioactive conformations of macrocycles using conformational search and binding modes using docking. Conformational ensembles generated using specialized search technique of about 70 % of the tested macrocycles contained accurate bioactive conformations. However, these conformations were difficult to identify on the basis of conformational energies. Moreover, docking calculations with limited ligand flexibility starting from individual low energy conformations rarely yielded highly accurate binding modes. In about 40 % of the test cases, binding modes were approximated with reasonable accuracy. However, when conformational ensembles were subjected to rigid body docking, an increase in meaningful binding mode predictions to more than 50 % of the test cases was observed. Electrostatic effects did not contribute to these predictions in a positive or negative manner. Rather, achieving shape complementarity at macrocycle-target interfaces was a decisive factor. In summary, a combined computational protocol using pre-computed conformational ensembles of macrocycles as a starting point for docking shows promise in modeling binding modes of macrocyclic compounds.
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ClustENM: ENM-Based Sampling of Essential Conformational Space at Full Atomic Resolution
Kurkcuoglu, Zeynep; Bahar, Ivet; Doruker, Pemra
2016-01-01
Accurate sampling of conformational space and, in particular, the transitions between functional substates has been a challenge in molecular dynamic (MD) simulations of large biomolecular systems. We developed an Elastic Network Model (ENM)-based computational method, ClustENM, for sampling large conformational changes of biomolecules with various sizes and oligomerization states. ClustENM is an iterative method that combines ENM with energy minimization and clustering steps. It is an unbiased technique, which requires only an initial structure as input, and no information about the target conformation. To test the performance of ClustENM, we applied it to six biomolecular systems: adenylate kinase (AK), calmodulin, p38 MAP kinase, HIV-1 reverse transcriptase (RT), triosephosphate isomerase (TIM), and the 70S ribosomal complex. The generated ensembles of conformers determined at atomic resolution show good agreement with experimental data (979 structures resolved by X-ray and/or NMR) and encompass the subspaces covered in independent MD simulations for TIM, p38, and RT. ClustENM emerges as a computationally efficient tool for characterizing the conformational space of large systems at atomic detail, in addition to generating a representative ensemble of conformers that can be advantageously used in simulating substrate/ligand-binding events. PMID:27494296
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Kim, Hyoungrae; Jang, Cheongyun; Yadav, Dharmendra K; Kim, Mi-Hyun
2017-03-23
The accuracy of any 3D-QSAR, Pharmacophore and 3D-similarity based chemometric target fishing models are highly dependent on a reasonable sample of active conformations. Since a number of diverse conformational sampling algorithm exist, which exhaustively generate enough conformers, however model building methods relies on explicit number of common conformers. In this work, we have attempted to make clustering algorithms, which could find reasonable number of representative conformer ensembles automatically with asymmetric dissimilarity matrix generated from openeye tool kit. RMSD was the important descriptor (variable) of each column of the N × N matrix considered as N variables describing the relationship (network) between the conformer (in a row) and the other N conformers. This approach used to evaluate the performance of the well-known clustering algorithms by comparison in terms of generating representative conformer ensembles and test them over different matrix transformation functions considering the stability. In the network, the representative conformer group could be resampled for four kinds of algorithms with implicit parameters. The directed dissimilarity matrix becomes the only input to the clustering algorithms. Dunn index, Davies-Bouldin index, Eta-squared values and omega-squared values were used to evaluate the clustering algorithms with respect to the compactness and the explanatory power. The evaluation includes the reduction (abstraction) rate of the data, correlation between the sizes of the population and the samples, the computational complexity and the memory usage as well. Every algorithm could find representative conformers automatically without any user intervention, and they reduced the data to 14-19% of the original values within 1.13 s per sample at the most. The clustering methods are simple and practical as they are fast and do not ask for any explicit parameters. RCDTC presented the maximum Dunn and omega-squared values of the four algorithms in addition to consistent reduction rate between the population size and the sample size. The performance of the clustering algorithms was consistent over different transformation functions. Moreover, the clustering method can also be applied to molecular dynamics sampling simulation results.
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Constrained proper sampling of conformations of transition state ensemble of protein folding
Lin, Ming; Zhang, Jian; Lu, Hsiao-Mei; Chen, Rong; Liang, Jie
2011-01-01
Characterizing the conformations of protein in the transition state ensemble (TSE) is important for studying protein folding. A promising approach pioneered by Vendruscolo [Nature (London) 409, 641 (2001)] to study TSE is to generate conformations that satisfy all constraints imposed by the experimentally measured ϕ values that provide information about the native likeness of the transition states. Faísca [J. Chem. Phys. 129, 095108 (2008)] generated conformations of TSE based on the criterion that, starting from a TS conformation, the probabilities of folding and unfolding are about equal through Markov Chain Monte Carlo (MCMC) simulations. In this study, we use the technique of constrained sequential Monte Carlo method [Lin , J. Chem. Phys. 129, 094101 (2008); Zhang Proteins 66, 61 (2007)] to generate TSE conformations of acylphosphatase of 98 residues that satisfy the ϕ-value constraints, as well as the criterion that each conformation has a folding probability of 0.5 by Monte Carlo simulations. We adopt a two stage process and first generate 5000 contact maps satisfying the ϕ-value constraints. Each contact map is then used to generate 1000 properly weighted conformations. After clustering similar conformations, we obtain a set of properly weighted samples of 4185 candidate clusters. Representative conformation of each of these cluster is then selected and 50 runs of Markov chain Monte Carlo (MCMC) simulation are carried using a regrowth move set. We then select a subset of 1501 conformations that have equal probabilities to fold and to unfold as the set of TSE. These 1501 samples characterize well the distribution of transition state ensemble conformations of acylphosphatase. Compared with previous studies, our approach can access much wider conformational space and can objectively generate conformations that satisfy the ϕ-value constraints and the criterion of 0.5 folding probability without bias. In contrast to previous studies, our results show that transition state conformations are very diverse and are far from nativelike when measured in cartesian root-mean-square deviation (cRMSD): the average cRMSD between TSE conformations and the native structure is 9.4 Å for this short protein, instead of 6 Å reported in previous studies. In addition, we found that the average fraction of native contacts in the TSE is 0.37, with enrichment in native-like β-sheets and a shortage of long range contacts, suggesting such contacts form at a later stage of folding. We further calculate the first passage time of folding of TSE conformations through calculation of physical time associated with the regrowth moves in MCMC simulation through mapping such moves to a Markovian state model, whose transition time was obtained by Langevin dynamics simulations. Our results indicate that despite the large structural diversity of the TSE, they are characterized by similar folding time. Our approach is general and can be used to study TSE in other macromolecules. PMID:21341875
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NASA Astrophysics Data System (ADS)
Beckman, Robert A.; Moreland, David; Louise-May, Shirley; Humblet, Christine
2006-05-01
Nuclear magnetic resonance (NMR) provides structural and dynamic information reflecting an average, often non-linear, of multiple solution-state conformations. Therefore, a single optimized structure derived from NMR refinement may be misleading if the NMR data actually result from averaging of distinct conformers. It is hypothesized that a conformational ensemble generated by a valid molecular dynamics (MD) simulation should be able to improve agreement with the NMR data set compared with the single optimized starting structure. Using a model system consisting of two sequence-related self-complementary ribonucleotide octamers for which NMR data was available, 0.3 ns particle mesh Ewald MD simulations were performed in the AMBER force field in the presence of explicit water and counterions. Agreement of the averaged properties of the molecular dynamics ensembles with NMR data such as homonuclear proton nuclear Overhauser effect (NOE)-based distance constraints, homonuclear proton and heteronuclear 1H-31P coupling constant ( J) data, and qualitative NMR information on hydrogen bond occupancy, was systematically assessed. Despite the short length of the simulation, the ensemble generated from it agreed with the NMR experimental constraints more completely than the single optimized NMR structure. This suggests that short unrestrained MD simulations may be of utility in interpreting NMR results. As expected, a 0.5 ns simulation utilizing a distance dependent dielectric did not improve agreement with the NMR data, consistent with its inferior exploration of conformational space as assessed by 2-D RMSD plots. Thus, ability to rapidly improve agreement with NMR constraints may be a sensitive diagnostic of the MD methods themselves.
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Advanced ensemble modelling of flexible macromolecules using X-ray solution scattering.
Tria, Giancarlo; Mertens, Haydyn D T; Kachala, Michael; Svergun, Dmitri I
2015-03-01
Dynamic ensembles of macromolecules mediate essential processes in biology. Understanding the mechanisms driving the function and molecular interactions of 'unstructured' and flexible molecules requires alternative approaches to those traditionally employed in structural biology. Small-angle X-ray scattering (SAXS) is an established method for structural characterization of biological macromolecules in solution, and is directly applicable to the study of flexible systems such as intrinsically disordered proteins and multi-domain proteins with unstructured regions. The Ensemble Optimization Method (EOM) [Bernadó et al. (2007 ▶). J. Am. Chem. Soc. 129, 5656-5664] was the first approach introducing the concept of ensemble fitting of the SAXS data from flexible systems. In this approach, a large pool of macromolecules covering the available conformational space is generated and a sub-ensemble of conformers coexisting in solution is selected guided by the fit to the experimental SAXS data. This paper presents a series of new developments and advancements to the method, including significantly enhanced functionality and also quantitative metrics for the characterization of the results. Building on the original concept of ensemble optimization, the algorithms for pool generation have been redesigned to allow for the construction of partially or completely symmetric oligomeric models, and the selection procedure was improved to refine the size of the ensemble. Quantitative measures of the flexibility of the system studied, based on the characteristic integral parameters of the selected ensemble, are introduced. These improvements are implemented in the new EOM version 2.0, and the capabilities as well as inherent limitations of the ensemble approach in SAXS, and of EOM 2.0 in particular, are discussed.
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PubChem3D: Conformer generation
2011-01-01
Background PubChem, an open archive for the biological activities of small molecules, provides search and analysis tools to assist users in locating desired information. Many of these tools focus on the notion of chemical structure similarity at some level. PubChem3D enables similarity of chemical structure 3-D conformers to augment the existing similarity of 2-D chemical structure graphs. It is also desirable to relate theoretical 3-D descriptions of chemical structures to experimental biological activity. As such, it is important to be assured that the theoretical conformer models can reproduce experimentally determined bioactive conformations. In the present study, we investigate the effects of three primary conformer generation parameters (the fragment sampling rate, the energy window size, and force field variant) upon the accuracy of theoretical conformer models, and determined optimal settings for PubChem3D conformer model generation and conformer sampling. Results Using the software package OMEGA from OpenEye Scientific Software, Inc., theoretical 3-D conformer models were generated for 25,972 small-molecule ligands, whose 3-D structures were experimentally determined. Different values for primary conformer generation parameters were systematically tested to find optimal settings. Employing a greater fragment sampling rate than the default did not improve the accuracy of the theoretical conformer model ensembles. An ever increasing energy window did increase the overall average accuracy, with rapid convergence observed at 10 kcal/mol and 15 kcal/mol for model building and torsion search, respectively; however, subsequent study showed that an energy threshold of 25 kcal/mol for torsion search resulted in slightly improved results for larger and more flexible structures. Exclusion of coulomb terms from the 94s variant of the Merck molecular force field (MMFF94s) in the torsion search stage gave more accurate conformer models at lower energy windows. Overall average accuracy of reproduction of bioactive conformations was remarkably linear with respect to both non-hydrogen atom count ("size") and effective rotor count ("flexibility"). Using these as independent variables, a regression equation was developed to predict the RMSD accuracy of a theoretical ensemble to reproduce bioactive conformations. The equation was modified to give a minimum RMSD conformer sampling value to help ensure that 90% of the sampled theoretical models should contain at least one conformer within the RMSD sampling value to a "bioactive" conformation. Conclusion Optimal parameters for conformer generation using OMEGA were explored and determined. An equation was developed that provides an RMSD sampling value to use that is based on the relative accuracy to reproduce bioactive conformations. The optimal conformer generation parameters and RMSD sampling values determined are used by the PubChem3D project to generate theoretical conformer models. PMID:21272340
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Nguyen, Q Nhu N; Schwochert, Joshua; Tantillo, Dean J; Lokey, R Scott
2018-05-10
Solving conformations of cyclic peptides can provide insight into structure-activity and structure-property relationships, which can help in the design of compounds with improved bioactivity and/or ADME characteristics. The most common approaches for determining the structures of cyclic peptides are based on NMR-derived distance restraints obtained from NOESY or ROESY cross-peak intensities, and 3J-based dihedral restraints using the Karplus relationship. Unfortunately, these observables are often too weak, sparse, or degenerate to provide unequivocal, high-confidence solution structures, prompting us to investigate an alternative approach that relies only on 1H and 13C chemical shifts as experimental observables. This method, which we call conformational analysis from NMR and density-functional prediction of low-energy ensembles (CANDLE), uses molecular dynamics (MD) simulations to generate conformer families and density functional theory (DFT) calculations to predict their 1H and 13C chemical shifts. Iterative conformer searches and DFT energy calculations on a cyclic peptide-peptoid hybrid yielded Boltzmann ensembles whose predicted chemical shifts matched the experimental values better than any single conformer. For these compounds, CANDLE outperformed the classic NOE- and 3J-coupling-based approach by disambiguating similar β-turn types and also enabled the structural elucidation of the minor conformer. Through the use of chemical shifts, in conjunction with DFT and MD calculations, CANDLE can help illuminate conformational ensembles of cyclic peptides in solution.
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Salmon, Loïc; Giambaşu, George M; Nikolova, Evgenia N; Petzold, Katja; Bhattacharya, Akash; Case, David A; Al-Hashimi, Hashim M
2015-10-14
Approaches that combine experimental data and computational molecular dynamics (MD) to determine atomic resolution ensembles of biomolecules require the measurement of abundant experimental data. NMR residual dipolar couplings (RDCs) carry rich dynamics information, however, difficulties in modulating overall alignment of nucleic acids have limited the ability to fully extract this information. We present a strategy for modulating RNA alignment that is based on introducing variable dynamic kinks in terminal helices. With this strategy, we measured seven sets of RDCs in a cUUCGg apical loop and used this rich data set to test the accuracy of an 0.8 μs MD simulation computed using the Amber ff10 force field as well as to determine an atomic resolution ensemble. The MD-generated ensemble quantitatively reproduces the measured RDCs, but selection of a sub-ensemble was required to satisfy the RDCs within error. The largest discrepancies between the RDC-selected and MD-generated ensembles are observed for the most flexible loop residues and backbone angles connecting the loop to the helix, with the RDC-selected ensemble resulting in more uniform dynamics. Comparison of the RDC-selected ensemble with NMR spin relaxation data suggests that the dynamics occurs on the ps-ns time scales as verified by measurements of R(1ρ) relaxation-dispersion data. The RDC-satisfying ensemble samples many conformations adopted by the hairpin in crystal structures indicating that intrinsic plasticity may play important roles in conformational adaptation. The approach presented here can be applied to test nucleic acid force fields and to characterize dynamics in diverse RNA motifs at atomic resolution.
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Henriksen, Niel M.; Roe, Daniel R.; Cheatham, Thomas E.
2013-01-01
Molecular dynamics force field development and assessment requires a reliable means for obtaining a well-converged conformational ensemble of a molecule in both a time-efficient and cost-effective manner. This remains a challenge for RNA because its rugged energy landscape results in slow conformational sampling and accurate results typically require explicit solvent which increases computational cost. To address this, we performed both traditional and modified replica exchange molecular dynamics simulations on a test system (alanine dipeptide) and an RNA tetramer known to populate A-form-like conformations in solution (single-stranded rGACC). A key focus is on providing the means to demonstrate that convergence is obtained, for example by investigating replica RMSD profiles and/or detailed ensemble analysis through clustering. We found that traditional replica exchange simulations still require prohibitive time and resource expenditures, even when using GPU accelerated hardware, and our results are not well converged even at 2 microseconds of simulation time per replica. In contrast, a modified version of replica exchange, reservoir replica exchange in explicit solvent, showed much better convergence and proved to be both a cost-effective and reliable alternative to the traditional approach. We expect this method will be attractive for future research that requires quantitative conformational analysis from explicitly solvated simulations. PMID:23477537
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Henriksen, Niel M; Roe, Daniel R; Cheatham, Thomas E
2013-04-18
Molecular dynamics force field development and assessment requires a reliable means for obtaining a well-converged conformational ensemble of a molecule in both a time-efficient and cost-effective manner. This remains a challenge for RNA because its rugged energy landscape results in slow conformational sampling and accurate results typically require explicit solvent which increases computational cost. To address this, we performed both traditional and modified replica exchange molecular dynamics simulations on a test system (alanine dipeptide) and an RNA tetramer known to populate A-form-like conformations in solution (single-stranded rGACC). A key focus is on providing the means to demonstrate that convergence is obtained, for example, by investigating replica RMSD profiles and/or detailed ensemble analysis through clustering. We found that traditional replica exchange simulations still require prohibitive time and resource expenditures, even when using GPU accelerated hardware, and our results are not well converged even at 2 μs of simulation time per replica. In contrast, a modified version of replica exchange, reservoir replica exchange in explicit solvent, showed much better convergence and proved to be both a cost-effective and reliable alternative to the traditional approach. We expect this method will be attractive for future research that requires quantitative conformational analysis from explicitly solvated simulations.
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Similarity Measures for Protein Ensembles
Lindorff-Larsen, Kresten; Ferkinghoff-Borg, Jesper
2009-01-01
Analyses of similarities and changes in protein conformation can provide important information regarding protein function and evolution. Many scores, including the commonly used root mean square deviation, have therefore been developed to quantify the similarities of different protein conformations. However, instead of examining individual conformations it is in many cases more relevant to analyse ensembles of conformations that have been obtained either through experiments or from methods such as molecular dynamics simulations. We here present three approaches that can be used to compare conformational ensembles in the same way as the root mean square deviation is used to compare individual pairs of structures. The methods are based on the estimation of the probability distributions underlying the ensembles and subsequent comparison of these distributions. We first validate the methods using a synthetic example from molecular dynamics simulations. We then apply the algorithms to revisit the problem of ensemble averaging during structure determination of proteins, and find that an ensemble refinement method is able to recover the correct distribution of conformations better than standard single-molecule refinement. PMID:19145244
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Mixture models for protein structure ensembles.
Hirsch, Michael; Habeck, Michael
2008-10-01
Protein structure ensembles provide important insight into the dynamics and function of a protein and contain information that is not captured with a single static structure. However, it is not clear a priori to what extent the variability within an ensemble is caused by internal structural changes. Additional variability results from overall translations and rotations of the molecule. And most experimental data do not provide information to relate the structures to a common reference frame. To report meaningful values of intrinsic dynamics, structural precision, conformational entropy, etc., it is therefore important to disentangle local from global conformational heterogeneity. We consider the task of disentangling local from global heterogeneity as an inference problem. We use probabilistic methods to infer from the protein ensemble missing information on reference frames and stable conformational sub-states. To this end, we model a protein ensemble as a mixture of Gaussian probability distributions of either entire conformations or structural segments. We learn these models from a protein ensemble using the expectation-maximization algorithm. Our first model can be used to find multiple conformers in a structure ensemble. The second model partitions the protein chain into locally stable structural segments or core elements and less structured regions typically found in loops. Both models are simple to implement and contain only a single free parameter: the number of conformers or structural segments. Our models can be used to analyse experimental ensembles, molecular dynamics trajectories and conformational change in proteins. The Python source code for protein ensemble analysis is available from the authors upon request.
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Enhanced conformational sampling to visualize a free-energy landscape of protein complex formation
Iida, Shinji; Nakamura, Haruki; Higo, Junichi
2016-01-01
We introduce various, recently developed, generalized ensemble methods, which are useful to sample various molecular configurations emerging in the process of protein–protein or protein–ligand binding. The methods introduced here are those that have been or will be applied to biomolecular binding, where the biomolecules are treated as flexible molecules expressed by an all-atom model in an explicit solvent. Sampling produces an ensemble of conformations (snapshots) that are thermodynamically probable at room temperature. Then, projection of those conformations to an abstract low-dimensional space generates a free-energy landscape. As an example, we show a landscape of homo-dimer formation of an endothelin-1-like molecule computed using a generalized ensemble method. The lowest free-energy cluster at room temperature coincided precisely with the experimentally determined complex structure. Two minor clusters were also found in the landscape, which were largely different from the native complex form. Although those clusters were isolated at room temperature, with rising temperature a pathway emerged linking the lowest and second-lowest free-energy clusters, and a further temperature increment connected all the clusters. This exemplifies that the generalized ensemble method is a powerful tool for computing the free-energy landscape, by which one can discuss the thermodynamic stability of clusters and the temperature dependence of the cluster networks. PMID:27288028
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Ruiz, Duncan D. A.; Norberto de Souza, Osmar
2015-01-01
Protein receptor conformations, obtained from molecular dynamics (MD) simulations, have become a promising treatment of its explicit flexibility in molecular docking experiments applied to drug discovery and development. However, incorporating the entire ensemble of MD conformations in docking experiments to screen large candidate compound libraries is currently an unfeasible task. Clustering algorithms have been widely used as a means to reduce such ensembles to a manageable size. Most studies investigate different algorithms using pairwise Root-Mean Square Deviation (RMSD) values for all, or part of the MD conformations. Nevertheless, the RMSD only may not be the most appropriate gauge to cluster conformations when the target receptor has a plastic active site, since they are influenced by changes that occur on other parts of the structure. Hence, we have applied two partitioning methods (k-means and k-medoids) and four agglomerative hierarchical methods (Complete linkage, Ward’s, Unweighted Pair Group Method and Weighted Pair Group Method) to analyze and compare the quality of partitions between a data set composed of properties from an enzyme receptor substrate-binding cavity and two data sets created using different RMSD approaches. Ensembles of representative MD conformations were generated by selecting a medoid of each group from all partitions analyzed. We investigated the performance of our new method for evaluating binding conformation of drug candidates to the InhA enzyme, which were performed by cross-docking experiments between a 20 ns MD trajectory and 20 different ligands. Statistical analyses showed that the novel ensemble, which is represented by only 0.48% of the MD conformations, was able to reproduce 75% of all dynamic behaviors within the binding cavity for the docking experiments performed. Moreover, this new approach not only outperforms the other two RMSD-clustering solutions, but it also shows to be a promising strategy to distill biologically relevant information from MD trajectories, especially for docking purposes. PMID:26218832
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De Paris, Renata; Quevedo, Christian V; Ruiz, Duncan D A; Norberto de Souza, Osmar
2015-01-01
Protein receptor conformations, obtained from molecular dynamics (MD) simulations, have become a promising treatment of its explicit flexibility in molecular docking experiments applied to drug discovery and development. However, incorporating the entire ensemble of MD conformations in docking experiments to screen large candidate compound libraries is currently an unfeasible task. Clustering algorithms have been widely used as a means to reduce such ensembles to a manageable size. Most studies investigate different algorithms using pairwise Root-Mean Square Deviation (RMSD) values for all, or part of the MD conformations. Nevertheless, the RMSD only may not be the most appropriate gauge to cluster conformations when the target receptor has a plastic active site, since they are influenced by changes that occur on other parts of the structure. Hence, we have applied two partitioning methods (k-means and k-medoids) and four agglomerative hierarchical methods (Complete linkage, Ward's, Unweighted Pair Group Method and Weighted Pair Group Method) to analyze and compare the quality of partitions between a data set composed of properties from an enzyme receptor substrate-binding cavity and two data sets created using different RMSD approaches. Ensembles of representative MD conformations were generated by selecting a medoid of each group from all partitions analyzed. We investigated the performance of our new method for evaluating binding conformation of drug candidates to the InhA enzyme, which were performed by cross-docking experiments between a 20 ns MD trajectory and 20 different ligands. Statistical analyses showed that the novel ensemble, which is represented by only 0.48% of the MD conformations, was able to reproduce 75% of all dynamic behaviors within the binding cavity for the docking experiments performed. Moreover, this new approach not only outperforms the other two RMSD-clustering solutions, but it also shows to be a promising strategy to distill biologically relevant information from MD trajectories, especially for docking purposes.
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Toward canonical ensemble distribution from self-guided Langevin dynamics simulation
NASA Astrophysics Data System (ADS)
Wu, Xiongwu; Brooks, Bernard R.
2011-04-01
This work derives a quantitative description of the conformational distribution in self-guided Langevin dynamics (SGLD) simulations. SGLD simulations employ guiding forces calculated from local average momentums to enhance low-frequency motion. This enhancement in low-frequency motion dramatically accelerates conformational search efficiency, but also induces certain perturbations in conformational distribution. Through the local averaging, we separate properties of molecular systems into low-frequency and high-frequency portions. The guiding force effect on the conformational distribution is quantitatively described using these low-frequency and high-frequency properties. This quantitative relation provides a way to convert between a canonical ensemble and a self-guided ensemble. Using example systems, we demonstrated how to utilize the relation to obtain canonical ensemble properties and conformational distributions from SGLD simulations. This development makes SGLD not only an efficient approach for conformational searching, but also an accurate means for conformational sampling.
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From a structural average to the conformational ensemble of a DNA bulge
Shi, Xuesong; Beauchamp, Kyle A.; Harbury, Pehr B.; Herschlag, Daniel
2014-01-01
Direct experimental measurements of conformational ensembles are critical for understanding macromolecular function, but traditional biophysical methods do not directly report the solution ensemble of a macromolecule. Small-angle X-ray scattering interferometry has the potential to overcome this limitation by providing the instantaneous distance distribution between pairs of gold-nanocrystal probes conjugated to a macromolecule in solution. Our X-ray interferometry experiments reveal an increasing bend angle of DNA duplexes with bulges of one, three, and five adenosine residues, consistent with previous FRET measurements, and further reveal an increasingly broad conformational ensemble with increasing bulge length. The distance distributions for the AAA bulge duplex (3A-DNA) with six different Au-Au pairs provide strong evidence against a simple elastic model in which fluctuations occur about a single conformational state. Instead, the measured distance distributions suggest a 3A-DNA ensemble with multiple conformational states predominantly across a region of conformational space with bend angles between 24 and 85 degrees and characteristic bend directions and helical twists and displacements. Additional X-ray interferometry experiments revealed perturbations to the ensemble from changes in ionic conditions and the bulge sequence, effects that can be understood in terms of electrostatic and stacking contributions to the ensemble and that demonstrate the sensitivity of X-ray interferometry. Combining X-ray interferometry ensemble data with molecular dynamics simulations gave atomic-level models of representative conformational states and of the molecular interactions that may shape the ensemble, and fluorescence measurements with 2-aminopurine-substituted 3A-DNA provided initial tests of these atomistic models. More generally, X-ray interferometry will provide powerful benchmarks for testing and developing computational methods. PMID:24706812
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NASA Astrophysics Data System (ADS)
Botlani, Mohsen; Siddiqui, Ahnaf; Varma, Sameer
2018-06-01
Many proteins are regulated by dynamic allostery wherein regulator-induced changes in structure are comparable with thermal fluctuations. Consequently, understanding their mechanisms requires assessment of relationships between and within conformational ensembles of different states. Here we show how machine learning based approaches can be used to simplify this high-dimensional data mining task and also obtain mechanistic insight. In particular, we use these approaches to investigate two fundamental questions in dynamic allostery. First, how do regulators modify inter-site correlations in conformational fluctuations (Cij)? Second, how are regulator-induced shifts in conformational ensembles at two different sites in a protein related to each other? We address these questions in the context of the human protein tyrosine phosphatase 1E's PDZ2 domain, which is a model protein for studying dynamic allostery. We use molecular dynamics to generate conformational ensembles of the PDZ2 domain in both the regulator-bound and regulator-free states. The employed protocol reproduces methyl deuterium order parameters from NMR. Results from unsupervised clustering of Cij combined with flow analyses of weighted graphs of Cij show that regulator binding significantly alters the global signaling network in the protein; however, not by altering the spatial arrangement of strongly interacting amino acid clusters but by modifying the connectivity between clusters. Additionally, we find that regulator-induced shifts in conformational ensembles, which we evaluate by repartitioning ensembles using supervised learning, are, in fact, correlated. This correlation Δij is less extensive compared to Cij, but in contrast to Cij, Δij depends inversely on the distance from the regulator binding site. Assuming that Δij is an indicator of the transduction of the regulatory signal leads to the conclusion that the regulatory signal weakens with distance from the regulatory site. Overall, this work provides new approaches to analyze high-dimensional molecular simulation data and also presents applications that yield new insight into dynamic allostery.
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Determination of the conformational ensemble of the TAR RNA by X-ray scattering interferometry
Walker, Peter
2017-01-01
Abstract The conformational ensembles of structured RNA's are crucial for biological function, but they remain difficult to elucidate experimentally. We demonstrate with HIV-1 TAR RNA that X-ray scattering interferometry (XSI) can be used to determine RNA conformational ensembles. X-ray scattering interferometry (XSI) is based on site-specifically labeling RNA with pairs of heavy atom probes, and precisely measuring the distribution of inter-probe distances that arise from a heterogeneous mixture of RNA solution structures. We show that the XSI-based model of the TAR RNA ensemble closely resembles an independent model derived from NMR-RDC data. Further, we show how the TAR RNA ensemble changes shape at different salt concentrations. Finally, we demonstrate that a single hybrid model of the TAR RNA ensemble simultaneously fits both the XSI and NMR-RDC data set and show that XSI can be combined with NMR-RDC to further improve the quality of the determined ensemble. The results suggest that XSI-RNA will be a powerful approach for characterizing the solution conformational ensembles of RNAs and RNA-protein complexes under diverse solution conditions. PMID:28108663
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Metadynamic metainference: Enhanced sampling of the metainference ensemble using metadynamics
Bonomi, Massimiliano; Camilloni, Carlo; Vendruscolo, Michele
2016-01-01
Accurate and precise structural ensembles of proteins and macromolecular complexes can be obtained with metainference, a recently proposed Bayesian inference method that integrates experimental information with prior knowledge and deals with all sources of errors in the data as well as with sample heterogeneity. The study of complex macromolecular systems, however, requires an extensive conformational sampling, which represents a separate challenge. To address such challenge and to exhaustively and efficiently generate structural ensembles we combine metainference with metadynamics and illustrate its application to the calculation of the free energy landscape of the alanine dipeptide. PMID:27561930
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A New Method for Determining Structure Ensemble: Application to a RNA Binding Di-Domain Protein.
Liu, Wei; Zhang, Jingfeng; Fan, Jing-Song; Tria, Giancarlo; Grüber, Gerhard; Yang, Daiwen
2016-05-10
Structure ensemble determination is the basis of understanding the structure-function relationship of a multidomain protein with weak domain-domain interactions. Paramagnetic relaxation enhancement has been proven a powerful tool in the study of structure ensembles, but there exist a number of challenges such as spin-label flexibility, domain dynamics, and overfitting. Here we propose a new (to our knowledge) method to describe structure ensembles using a minimal number of conformers. In this method, individual domains are considered rigid; the position of each spin-label conformer and the structure of each protein conformer are defined by three and six orthogonal parameters, respectively. First, the spin-label ensemble is determined by optimizing the positions and populations of spin-label conformers against intradomain paramagnetic relaxation enhancements with a genetic algorithm. Subsequently, the protein structure ensemble is optimized using a more efficient genetic algorithm-based approach and an overfitting indicator, both of which were established in this work. The method was validated using a reference ensemble with a set of conformers whose populations and structures are known. This method was also applied to study the structure ensemble of the tandem di-domain of a poly (U) binding protein. The determined ensemble was supported by small-angle x-ray scattering and nuclear magnetic resonance relaxation data. The ensemble obtained suggests an induced fit mechanism for recognition of target RNA by the protein. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.
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Mizwicki, Mathew T.; Bula, Craig M.; Bishop, June E.; Norman, Anthony W.
2007-01-01
Recently, we have developed a vitamin D sterol (VDS)-VDR conformational ensemble model. This model can be broken down into three individual, yet interlinked parts: a) the conformationally flexible VDS, b) the apo/holo-VDR helix-12 (H12) conformational ensemble, and c) the presence of two VDR ligand binding pockets (LBPs); one thermodynamically favored (the genomic pocket, G-pocket) and the other kinetically favored by VDSs (the alternative pocket, A-pocket). One focus of this study is to use directed VDR mutagenesis to 1) demonstrate H12 is stabilized in the transcriptionally active closed conformation (hVDR-c1) by three salt-bridges that span the length of H12 (cationic residues R154, K264 and R402), 2) to elucidate the VDR trypsin sites [R173 (hVDR-c1), K413 (hVDR-c2) and R402 (hVDR-c3)] and 3) demonstrate the apo-VDR H12 equilibrium can be shifted. The other focus of this study is to apply the model to generate a mechanistic understanding to discrepancies observed in structure-function data obtained with a variety of 1α,25(OH)2-vitamin D3 (1,25D) A-ring and side-chain analogs, and side-chain metabolites. We will demonstrate that these structure-function conundrums can be rationalized, for the most part by focusing on alterations in the VDS conformational flexibility and the elementary interaction between the VDS and the VDR A- and G-pockets, relative to the control, 1,25D. PMID:17368177
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Enhanced conformational sampling to visualize a free-energy landscape of protein complex formation.
Iida, Shinji; Nakamura, Haruki; Higo, Junichi
2016-06-15
We introduce various, recently developed, generalized ensemble methods, which are useful to sample various molecular configurations emerging in the process of protein-protein or protein-ligand binding. The methods introduced here are those that have been or will be applied to biomolecular binding, where the biomolecules are treated as flexible molecules expressed by an all-atom model in an explicit solvent. Sampling produces an ensemble of conformations (snapshots) that are thermodynamically probable at room temperature. Then, projection of those conformations to an abstract low-dimensional space generates a free-energy landscape. As an example, we show a landscape of homo-dimer formation of an endothelin-1-like molecule computed using a generalized ensemble method. The lowest free-energy cluster at room temperature coincided precisely with the experimentally determined complex structure. Two minor clusters were also found in the landscape, which were largely different from the native complex form. Although those clusters were isolated at room temperature, with rising temperature a pathway emerged linking the lowest and second-lowest free-energy clusters, and a further temperature increment connected all the clusters. This exemplifies that the generalized ensemble method is a powerful tool for computing the free-energy landscape, by which one can discuss the thermodynamic stability of clusters and the temperature dependence of the cluster networks. © 2016 The Author(s).
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Automated use of mutagenesis data in structure prediction.
Nanda, Vikas; DeGrado, William F
2005-05-15
In the absence of experimental structural determination, numerous methods are available to indirectly predict or probe the structure of a target molecule. Genetic modification of a protein sequence is a powerful tool for identifying key residues involved in binding reactions or protein stability. Mutagenesis data is usually incorporated into the modeling process either through manual inspection of model compatibility with empirical data, or through the generation of geometric constraints linking sensitive residues to a binding interface. We present an approach derived from statistical studies of lattice models for introducing mutation information directly into the fitness score. The approach takes into account the phenotype of mutation (neutral or disruptive) and calculates the energy for a given structure over an ensemble of sequences. The structure prediction procedure searches for the optimal conformation where neutral sequences either have no impact or improve stability and disruptive sequences reduce stability relative to wild type. We examine three types of sequence ensembles: information from saturation mutagenesis, scanning mutagenesis, and homologous proteins. Incorporating multiple sequences into a statistical ensemble serves to energetically separate the native state and misfolded structures. As a result, the prediction of structure with a poor force field is sufficiently enhanced by mutational information to improve accuracy. Furthermore, by separating misfolded conformations from the target score, the ensemble energy serves to speed up conformational search algorithms such as Monte Carlo-based methods. Copyright 2005 Wiley-Liss, Inc.
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Efficient generation of low-energy folded states of a model protein
NASA Astrophysics Data System (ADS)
Gordon, Heather L.; Kwan, Wai Kei; Gong, Chunhang; Larrass, Stefan; Rothstein, Stuart M.
2003-01-01
A number of short simulated annealing runs are performed on a highly-frustrated 46-"residue" off-lattice model protein. We perform, in an iterative fashion, a principal component analysis of the 946 nonbonded interbead distances, followed by two varieties of cluster analyses: hierarchical and k-means clustering. We identify several distinct sets of conformations with reasonably consistent cluster membership. Nonbonded distance constraints are derived for each cluster and are employed within a distance geometry approach to generate many new conformations, previously unidentified by the simulated annealing experiments. Subsequent analyses suggest that these new conformations are members of the parent clusters from which they were generated. Furthermore, several novel, previously unobserved structures with low energy were uncovered, augmenting the ensemble of simulated annealing results, and providing a complete distribution of low-energy states. The computational cost of this approach to generating low-energy conformations is small when compared to the expense of further Monte Carlo simulated annealing runs.
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Determination of the conformational ensemble of the TAR RNA by X-ray scattering interferometry.
Shi, Xuesong; Walker, Peter; Harbury, Pehr B; Herschlag, Daniel
2017-05-05
The conformational ensembles of structured RNA's are crucial for biological function, but they remain difficult to elucidate experimentally. We demonstrate with HIV-1 TAR RNA that X-ray scattering interferometry (XSI) can be used to determine RNA conformational ensembles. X-ray scattering interferometry (XSI) is based on site-specifically labeling RNA with pairs of heavy atom probes, and precisely measuring the distribution of inter-probe distances that arise from a heterogeneous mixture of RNA solution structures. We show that the XSI-based model of the TAR RNA ensemble closely resembles an independent model derived from NMR-RDC data. Further, we show how the TAR RNA ensemble changes shape at different salt concentrations. Finally, we demonstrate that a single hybrid model of the TAR RNA ensemble simultaneously fits both the XSI and NMR-RDC data set and show that XSI can be combined with NMR-RDC to further improve the quality of the determined ensemble. The results suggest that XSI-RNA will be a powerful approach for characterizing the solution conformational ensembles of RNAs and RNA-protein complexes under diverse solution conditions. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
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Sanchez-Martinez, M; Crehuet, R
2014-12-21
We present a method based on the maximum entropy principle that can re-weight an ensemble of protein structures based on data from residual dipolar couplings (RDCs). The RDCs of intrinsically disordered proteins (IDPs) provide information on the secondary structure elements present in an ensemble; however even two sets of RDCs are not enough to fully determine the distribution of conformations, and the force field used to generate the structures has a pervasive influence on the refined ensemble. Two physics-based coarse-grained force fields, Profasi and Campari, are able to predict the secondary structure elements present in an IDP, but even after including the RDC data, the re-weighted ensembles differ between both force fields. Thus the spread of IDP ensembles highlights the need for better force fields. We distribute our algorithm in an open-source Python code.
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Characterizing RNA ensembles from NMR data with kinematic models
Fonseca, Rasmus; Pachov, Dimitar V.; Bernauer, Julie; van den Bedem, Henry
2014-01-01
Functional mechanisms of biomolecules often manifest themselves precisely in transient conformational substates. Researchers have long sought to structurally characterize dynamic processes in non-coding RNA, combining experimental data with computer algorithms. However, adequate exploration of conformational space for these highly dynamic molecules, starting from static crystal structures, remains challenging. Here, we report a new conformational sampling procedure, KGSrna, which can efficiently probe the native ensemble of RNA molecules in solution. We found that KGSrna ensembles accurately represent the conformational landscapes of 3D RNA encoded by NMR proton chemical shifts. KGSrna resolves motionally averaged NMR data into structural contributions; when coupled with residual dipolar coupling data, a KGSrna ensemble revealed a previously uncharacterized transient excited state of the HIV-1 trans-activation response element stem–loop. Ensemble-based interpretations of averaged data can aid in formulating and testing dynamic, motion-based hypotheses of functional mechanisms in RNAs with broad implications for RNA engineering and therapeutic intervention. PMID:25114056
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Yang, Shan; Al-Hashimi, Hashim M.
2016-01-01
A growing number of studies employ time-averaged experimental data to determine dynamic ensembles of biomolecules. While it is well known that different ensembles can satisfy experimental data to within error, the extent and nature of these degeneracies, and their impact on the accuracy of the ensemble determination remains poorly understood. Here, we use simulations and a recently introduced metric for assessing ensemble similarity to explore degeneracies in determining ensembles using NMR residual dipolar couplings (RDCs) with specific application to A-form helices in RNA. Various target ensembles were constructed representing different domain-domain orientational distributions that are confined to a topologically restricted (<10%) conformational space. Five independent sets of ensemble averaged RDCs were then computed for each target ensemble and a ‘sample and select’ scheme used to identify degenerate ensembles that satisfy RDCs to within experimental uncertainty. We find that ensembles with different ensemble sizes and that can differ significantly from the target ensemble (by as much as ΣΩ ~ 0.4 where ΣΩ varies between 0 and 1 for maximum and minimum ensemble similarity, respectively) can satisfy the ensemble averaged RDCs. These deviations increase with the number of unique conformers and breadth of the target distribution, and result in significant uncertainty in determining conformational entropy (as large as 5 kcal/mol at T = 298 K). Nevertheless, the RDC-degenerate ensembles are biased towards populated regions of the target ensemble, and capture other essential features of the distribution, including the shape. Our results identify ensemble size as a major source of uncertainty in determining ensembles and suggest that NMR interactions such as RDCs and spin relaxation, on their own, do not carry the necessary information needed to determine conformational entropy at a useful level of precision. The framework introduced here provides a general approach for exploring degeneracies in ensemble determination for different types of experimental data. PMID:26131693
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Quantifying polypeptide conformational space: sensitivity to conformation and ensemble definition.
Sullivan, David C; Lim, Carmay
2006-08-24
Quantifying the density of conformations over phase space (the conformational distribution) is needed to model important macromolecular processes such as protein folding. In this work, we quantify the conformational distribution for a simple polypeptide (N-mer polyalanine) using the cumulative distribution function (CDF), which gives the probability that two randomly selected conformations are separated by less than a "conformational" distance and whose inverse gives conformation counts as a function of conformational radius. An important finding is that the conformation counts obtained by the CDF inverse depend critically on the assignment of a conformation's distance span and the ensemble (e.g., unfolded state model): varying ensemble and conformation definition (1 --> 2 A) varies the CDF-based conformation counts for Ala(50) from 10(11) to 10(69). In particular, relatively short molecular dynamics (MD) relaxation of Ala(50)'s random-walk ensemble reduces the number of conformers from 10(55) to 10(14) (using a 1 A root-mean-square-deviation radius conformation definition) pointing to potential disconnections in comparing the results from simplified models of unfolded proteins with those from all-atom MD simulations. Explicit waters are found to roughen the landscape considerably. Under some common conformation definitions, the results herein provide (i) an upper limit to the number of accessible conformations that compose unfolded states of proteins, (ii) the optimal clustering radius/conformation radius for counting conformations for a given energy and solvent model, (iii) a means of comparing various studies, and (iv) an assessment of the applicability of random search in protein folding.
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Keedy, Daniel A.; Kenner, Lillian R.; Warkentin, Matthew; ...
2015-09-30
Determining the interconverting conformations of dynamic proteins in atomic detail is a major challenge for structural biology. Conformational heterogeneity in the active site of the dynamic enzyme cyclophilin A (CypA) has been previously linked to its catalytic function, but the extent to which the different conformations of these residues are correlated is unclear. Here we compare the conformational ensembles of CypA by multitemperature synchrotron crystallography and fixed-target X-ray free-electron laser (XFEL) crystallography. The diffraction-before-destruction nature of XFEL experiments provides a radiation-damage-free view of the functionally important alternative conformations of CypA, confirming earlier synchrotron-based results. We monitored the temperature dependences ofmore » these alternative conformations with eight synchrotron datasets spanning 100-310 K. Multiconformer models show that many alternative conformations in CypA are populated only at 240 K and above, yet others remain populated or become populated at 180 K and below. These results point to a complex evolution of conformational heterogeneity between 180-–240 K that involves both thermal deactivation and solvent-driven arrest of protein motions in the crystal. The lack of a single shared conformational response to temperature within the dynamic active-site network provides evidence for a conformation shuffling model, in which exchange between rotamer states of a large aromatic ring in the middle of the network shifts the conformational ensemble for the other residues in the network. Altogether, our multitemperature analyses and XFEL data motivate a new generation of temperature- and time-resolved experiments to structurally characterize the dynamic underpinnings of protein function.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Keedy, Daniel A.; Kenner, Lillian R.; Warkentin, Matthew
Determining the interconverting conformations of dynamic proteins in atomic detail is a major challenge for structural biology. Conformational heterogeneity in the active site of the dynamic enzyme cyclophilin A (CypA) has been previously linked to its catalytic function, but the extent to which the different conformations of these residues are correlated is unclear. Here we compare the conformational ensembles of CypA by multitemperature synchrotron crystallography and fixed-target X-ray free-electron laser (XFEL) crystallography. The diffraction-before-destruction nature of XFEL experiments provides a radiation-damage-free view of the functionally important alternative conformations of CypA, confirming earlier synchrotron-based results. We monitored the temperature dependences ofmore » these alternative conformations with eight synchrotron datasets spanning 100-310 K. Multiconformer models show that many alternative conformations in CypA are populated only at 240 K and above, yet others remain populated or become populated at 180 K and below. These results point to a complex evolution of conformational heterogeneity between 180-–240 K that involves both thermal deactivation and solvent-driven arrest of protein motions in the crystal. The lack of a single shared conformational response to temperature within the dynamic active-site network provides evidence for a conformation shuffling model, in which exchange between rotamer states of a large aromatic ring in the middle of the network shifts the conformational ensemble for the other residues in the network. Together, our multitemperature analyses and XFEL data motivate a new generation of temperature- and time-resolved experiments to structurally characterize the dynamic underpinnings of protein function.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Keedy, Daniel A.; Kenner, Lillian R.; Warkentin, Matthew
Determining the interconverting conformations of dynamic proteins in atomic detail is a major challenge for structural biology. Conformational heterogeneity in the active site of the dynamic enzyme cyclophilin A (CypA) has been previously linked to its catalytic function, but the extent to which the different conformations of these residues are correlated is unclear. Here we compare the conformational ensembles of CypA by multitemperature synchrotron crystallography and fixed-target X-ray free-electron laser (XFEL) crystallography. The diffraction-before-destruction nature of XFEL experiments provides a radiation-damage-free view of the functionally important alternative conformations of CypA, confirming earlier synchrotron-based results. We monitored the temperature dependences ofmore » these alternative conformations with eight synchrotron datasets spanning 100-310 K. Multiconformer models show that many alternative conformations in CypA are populated only at 240 K and above, yet others remain populated or become populated at 180 K and below. These results point to a complex evolution of conformational heterogeneity between 180-–240 K that involves both thermal deactivation and solvent-driven arrest of protein motions in the crystal. The lack of a single shared conformational response to temperature within the dynamic active-site network provides evidence for a conformation shuffling model, in which exchange between rotamer states of a large aromatic ring in the middle of the network shifts the conformational ensemble for the other residues in the network. Altogether, our multitemperature analyses and XFEL data motivate a new generation of temperature- and time-resolved experiments to structurally characterize the dynamic underpinnings of protein function.« less
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Fast de novo discovery of low-energy protein loop conformations.
Wong, Samuel W K; Liu, Jun S; Kou, S C
2017-08-01
In the prediction of protein structure from amino acid sequence, loops are challenging regions for computational methods. Since loops are often located on the protein surface, they can have significant roles in determining protein functions and binding properties. Loop prediction without the aid of a structural template requires extensive conformational sampling and energy minimization, which are computationally difficult. In this article we present a new de novo loop sampling method, the Parallely filtered Energy Targeted All-atom Loop Sampler (PETALS) to rapidly locate low energy conformations. PETALS explores both backbone and side-chain positions of the loop region simultaneously according to the energy function selected by the user, and constructs a nonredundant ensemble of low energy loop conformations using filtering criteria. The method is illustrated with the DFIRE potential and DiSGro energy function for loops, and shown to be highly effective at discovering conformations with near-native (or better) energy. Using the same energy function as the DiSGro algorithm, PETALS samples conformations with both lower RMSDs and lower energies. PETALS is also useful for assessing the accuracy of different energy functions. PETALS runs rapidly, requiring an average time cost of 10 minutes for a length 12 loop on a single 3.2 GHz processor core, comparable to the fastest existing de novo methods for generating an ensemble of conformations. Proteins 2017; 85:1402-1412. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
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NASA Astrophysics Data System (ADS)
Wu, Xiongwu; Brooks, Bernard R.
2011-11-01
The self-guided Langevin dynamics (SGLD) is a method to accelerate conformational searching. This method is unique in the way that it selectively enhances and suppresses molecular motions based on their frequency to accelerate conformational searching without modifying energy surfaces or raising temperatures. It has been applied to studies of many long time scale events, such as protein folding. Recent progress in the understanding of the conformational distribution in SGLD simulations makes SGLD also an accurate method for quantitative studies. The SGLD partition function provides a way to convert the SGLD conformational distribution to the canonical ensemble distribution and to calculate ensemble average properties through reweighting. Based on the SGLD partition function, this work presents a force-momentum-based self-guided Langevin dynamics (SGLDfp) simulation method to directly sample the canonical ensemble. This method includes interaction forces in its guiding force to compensate the perturbation caused by the momentum-based guiding force so that it can approximately sample the canonical ensemble. Using several example systems, we demonstrate that SGLDfp simulations can approximately maintain the canonical ensemble distribution and significantly accelerate conformational searching. With optimal parameters, SGLDfp and SGLD simulations can cross energy barriers of more than 15 kT and 20 kT, respectively, at similar rates for LD simulations to cross energy barriers of 10 kT. The SGLDfp method is size extensive and works well for large systems. For studies where preserving accessible conformational space is critical, such as free energy calculations and protein folding studies, SGLDfp is an efficient approach to search and sample the conformational space.
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Vorontsov, Ivan I; Miyashita, Osamu
2011-04-30
Complexes of two Cyanovirin-N (CVN) mutants, m4-CVN and P51G-m4-CVN, with deoxy di-mannose analogs were employed as models to generate conformational ensembles using explicit water Molecular Dynamics (MD) simulations in solution and in crystal environment. The results were utilized for evaluation of binding free energies with the molecular mechanics Poisson-Boltzmann (or Generalized Born) surface area, MM/PB(GB)SA, methods. The calculations provided the ranking of deoxy di-mannose ligands affinity in agreement with available qualitative experimental evidences. This confirms the importance of the hydrogen-bond network between di-mannose 3'- and 4'-hydroxyl groups and the protein binding site B(M) as a basis of the CVN activity as an effective HIV fusion inhibitor. Comparison of binding free energies averaged over snapshots from the solution and crystal simulations showed high promises in the use of the crystal matrix for acceleration of the conformational ensemble generation, the most time consuming step in MM/PB(GB)SA approach. Correlation between energy values based on solution versus crystal ensembles is 0.95 for both MM/PBSA and MM/GBSA methods. Copyright © 2010 Wiley Periodicals, Inc.
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Kaji, Takahiro; Ito, Syoji; Iwai, Shigenori; Miyasaka, Hiroshi
2009-10-22
Single-molecule and ensemble time-resolved fluorescence measurements were applied for the investigation of the conformational dynamics of single-stranded DNA, ssDNA, connected with a fluorescein dye by a C6 linker, where the motions both of DNA and the C6 linker affect the geometry of the system. From the ensemble measurement of the fluorescence quenching via photoinduced electron transfer with a guanine base in the DNA sequence, three main conformations were found in aqueous solution: a conformation unaffected by the guanine base in the excited state lifetime of fluorescein, a conformation in which the fluorescence is dynamically quenched in the excited-state lifetime, and a conformation leading to rapid quenching via nonfluorescent complex. The analysis by using the parameters acquired from the ensemble measurements for interphoton time distribution histograms and FCS autocorrelations by the single-molecule measurement revealed that interconversion in these three conformations took place with two characteristic time constants of several hundreds of nanoseconds and tens of microseconds. The advantage of the combination use of the ensemble measurements with the single-molecule detections for rather complex dynamic motions is discussed by integrating the experimental results with those obtained by molecular dynamics simulation.
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Knowledge-Based Methods To Train and Optimize Virtual Screening Ensembles
2016-01-01
Ensemble docking can be a successful virtual screening technique that addresses the innate conformational heterogeneity of macromolecular drug targets. Yet, lacking a method to identify a subset of conformational states that effectively segregates active and inactive small molecules, ensemble docking may result in the recommendation of a large number of false positives. Here, three knowledge-based methods that construct structural ensembles for virtual screening are presented. Each method selects ensembles by optimizing an objective function calculated using the receiver operating characteristic (ROC) curve: either the area under the ROC curve (AUC) or a ROC enrichment factor (EF). As the number of receptor conformations, N, becomes large, the methods differ in their asymptotic scaling. Given a set of small molecules with known activities and a collection of target conformations, the most resource intense method is guaranteed to find the optimal ensemble but scales as O(2N). A recursive approximation to the optimal solution scales as O(N2), and a more severe approximation leads to a faster method that scales linearly, O(N). The techniques are generally applicable to any system, and we demonstrate their effectiveness on the androgen nuclear hormone receptor (AR), cyclin-dependent kinase 2 (CDK2), and the peroxisome proliferator-activated receptor δ (PPAR-δ) drug targets. Conformations that consisted of a crystal structure and molecular dynamics simulation cluster centroids were used to form AR and CDK2 ensembles. Multiple available crystal structures were used to form PPAR-δ ensembles. For each target, we show that the three methods perform similarly to one another on both the training and test sets. PMID:27097522
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A Maximum-Likelihood Approach to Force-Field Calibration.
Zaborowski, Bartłomiej; Jagieła, Dawid; Czaplewski, Cezary; Hałabis, Anna; Lewandowska, Agnieszka; Żmudzińska, Wioletta; Ołdziej, Stanisław; Karczyńska, Agnieszka; Omieczynski, Christian; Wirecki, Tomasz; Liwo, Adam
2015-09-28
A new approach to the calibration of the force fields is proposed, in which the force-field parameters are obtained by maximum-likelihood fitting of the calculated conformational ensembles to the experimental ensembles of training system(s). The maximum-likelihood function is composed of logarithms of the Boltzmann probabilities of the experimental conformations, calculated with the current energy function. Because the theoretical distribution is given in the form of the simulated conformations only, the contributions from all of the simulated conformations, with Gaussian weights in the distances from a given experimental conformation, are added to give the contribution to the target function from this conformation. In contrast to earlier methods for force-field calibration, the approach does not suffer from the arbitrariness of dividing the decoy set into native-like and non-native structures; however, if such a division is made instead of using Gaussian weights, application of the maximum-likelihood method results in the well-known energy-gap maximization. The computational procedure consists of cycles of decoy generation and maximum-likelihood-function optimization, which are iterated until convergence is reached. The method was tested with Gaussian distributions and then applied to the physics-based coarse-grained UNRES force field for proteins. The NMR structures of the tryptophan cage, a small α-helical protein, determined at three temperatures (T = 280, 305, and 313 K) by Hałabis et al. ( J. Phys. Chem. B 2012 , 116 , 6898 - 6907 ), were used. Multiplexed replica-exchange molecular dynamics was used to generate the decoys. The iterative procedure exhibited steady convergence. Three variants of optimization were tried: optimization of the energy-term weights alone and use of the experimental ensemble of the folded protein only at T = 280 K (run 1); optimization of the energy-term weights and use of experimental ensembles at all three temperatures (run 2); and optimization of the energy-term weights and the coefficients of the torsional and multibody energy terms and use of experimental ensembles at all three temperatures (run 3). The force fields were subsequently tested with a set of 14 α-helical and two α + β proteins. Optimization run 1 resulted in better agreement with the experimental ensemble at T = 280 K compared with optimization run 2 and in comparable performance on the test set but poorer agreement of the calculated folding temperature with the experimental folding temperature. Optimization run 3 resulted in the best fit of the calculated ensembles to the experimental ones for the tryptophan cage but in much poorer performance on the training set, suggesting that use of a small α-helical protein for extensive force-field calibration resulted in overfitting of the data for this protein at the expense of transferability. The optimized force field resulting from run 2 was found to fold 13 of the 14 tested α-helical proteins and one small α + β protein with the correct topologies; the average structures of 10 of them were predicted with accuracies of about 5 Å C(α) root-mean-square deviation or better. Test simulations with an additional set of 12 α-helical proteins demonstrated that this force field performed better on α-helical proteins than the previous parametrizations of UNRES. The proposed approach is applicable to any problem of maximum-likelihood parameter estimation when the contributions to the maximum-likelihood function cannot be evaluated at the experimental points and the dimension of the configurational space is too high to construct histograms of the experimental distributions.
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Chakravorty, Arghya; Jia, Zhe; Li, Lin; Zhao, Shan; Alexov, Emil
2018-02-13
Typically, the ensemble average polar component of solvation energy (ΔG polar solv ) of a macromolecule is computed using molecular dynamics (MD) or Monte Carlo (MC) simulations to generate conformational ensemble and then single/rigid conformation solvation energy calculation is performed on each snapshot. The primary objective of this work is to demonstrate that Poisson-Boltzmann (PB)-based approach using a Gaussian-based smooth dielectric function for macromolecular modeling previously developed by us (Li et al. J. Chem. Theory Comput. 2013, 9 (4), 2126-2136) can reproduce that ensemble average (ΔG polar solv ) of a protein from a single structure. We show that the Gaussian-based dielectric model reproduces the ensemble average ΔG polar solv (⟨ΔG polar solv ⟩) from an energy-minimized structure of a protein regardless of the minimization environment (structure minimized in vacuo, implicit or explicit waters, or crystal structure); the best case, however, is when it is paired with an in vacuo-minimized structure. In other minimization environments (implicit or explicit waters or crystal structure), the traditional two-dielectric model can still be selected with which the model produces correct solvation energies. Our observations from this work reflect how the ability to appropriately mimic the motion of residues, especially the salt bridge residues, influences a dielectric model's ability to reproduce the ensemble average value of polar solvation free energy from a single in vacuo-minimized structure.
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Tian, Sheng; Sun, Huiyong; Pan, Peichen; Li, Dan; Zhen, Xuechu; Li, Youyong; Hou, Tingjun
2014-10-27
In this study, to accommodate receptor flexibility, based on multiple receptor conformations, a novel ensemble docking protocol was developed by using the naïve Bayesian classification technique, and it was evaluated in terms of the prediction accuracy of docking-based virtual screening (VS) of three important targets in the kinase family: ALK, CDK2, and VEGFR2. First, for each target, the representative crystal structures were selected by structural clustering, and the capability of molecular docking based on each representative structure to discriminate inhibitors from non-inhibitors was examined. Then, for each target, 50 ns molecular dynamics (MD) simulations were carried out to generate an ensemble of the conformations, and multiple representative structures/snapshots were extracted from each MD trajectory by structural clustering. On average, the representative crystal structures outperform the representative structures extracted from MD simulations in terms of the capabilities to separate inhibitors from non-inhibitors. Finally, by using the naïve Bayesian classification technique, an integrated VS strategy was developed to combine the prediction results of molecular docking based on different representative conformations chosen from crystal structures and MD trajectories. It was encouraging to observe that the integrated VS strategy yields better performance than the docking-based VS based on any single rigid conformation. This novel protocol may provide an improvement over existing strategies to search for more diverse and promising active compounds for a target of interest.
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Keedy, Daniel A; Kenner, Lillian R; Warkentin, Matthew; Woldeyes, Rahel A; Hopkins, Jesse B; Thompson, Michael C; Brewster, Aaron S; Van Benschoten, Andrew H; Baxter, Elizabeth L; Uervirojnangkoorn, Monarin; McPhillips, Scott E; Song, Jinhu; Alonso-Mori, Roberto; Holton, James M; Weis, William I; Brunger, Axel T; Soltis, S Michael; Lemke, Henrik; Gonzalez, Ana; Sauter, Nicholas K; Cohen, Aina E; van den Bedem, Henry; Thorne, Robert E; Fraser, James S
2015-01-01
Determining the interconverting conformations of dynamic proteins in atomic detail is a major challenge for structural biology. Conformational heterogeneity in the active site of the dynamic enzyme cyclophilin A (CypA) has been previously linked to its catalytic function, but the extent to which the different conformations of these residues are correlated is unclear. Here we compare the conformational ensembles of CypA by multitemperature synchrotron crystallography and fixed-target X-ray free-electron laser (XFEL) crystallography. The diffraction-before-destruction nature of XFEL experiments provides a radiation-damage-free view of the functionally important alternative conformations of CypA, confirming earlier synchrotron-based results. We monitored the temperature dependences of these alternative conformations with eight synchrotron datasets spanning 100-310 K. Multiconformer models show that many alternative conformations in CypA are populated only at 240 K and above, yet others remain populated or become populated at 180 K and below. These results point to a complex evolution of conformational heterogeneity between 180-–240 K that involves both thermal deactivation and solvent-driven arrest of protein motions in the crystal. The lack of a single shared conformational response to temperature within the dynamic active-site network provides evidence for a conformation shuffling model, in which exchange between rotamer states of a large aromatic ring in the middle of the network shifts the conformational ensemble for the other residues in the network. Together, our multitemperature analyses and XFEL data motivate a new generation of temperature- and time-resolved experiments to structurally characterize the dynamic underpinnings of protein function. DOI: http://dx.doi.org/10.7554/eLife.07574.001 PMID:26422513
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Enzymatic Detoxication, Conformational Selection, and the Role of Molten Globule Active Sites*
Honaker, Matthew T.; Acchione, Mauro; Zhang, Wei; Mannervik, Bengt; Atkins, William M.
2013-01-01
The role of conformational ensembles in enzymatic reactions remains unclear. Discussion concerning “induced fit” versus “conformational selection” has, however, ignored detoxication enzymes, which exhibit catalytic promiscuity. These enzymes dominate drug metabolism and determine drug-drug interactions. The detoxication enzyme glutathione transferase A1–1 (GSTA1–1), exploits a molten globule-like active site to achieve remarkable catalytic promiscuity wherein the substrate-free conformational ensemble is broad with barrierless transitions between states. A quantitative index of catalytic promiscuity is used to compare engineered variants of GSTA1–1 and the catalytic promiscuity correlates strongly with characteristics of the thermodynamic partition function, for the substrate-free enzymes. Access to chemically disparate transition states is encoded by the substrate-free conformational ensemble. Pre-steady state catalytic data confirm an extension of the conformational selection model, wherein different substrates select different starting conformations. The kinetic liability of the conformational breadth is minimized by a smooth landscape. We propose that “local” molten globule behavior optimizes detoxication enzymes. PMID:23649628
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Probing RNA Native Conformational Ensembles with Structural Constraints.
Fonseca, Rasmus; van den Bedem, Henry; Bernauer, Julie
2016-05-01
Noncoding ribonucleic acids (RNA) play a critical role in a wide variety of cellular processes, ranging from regulating gene expression to post-translational modification and protein synthesis. Their activity is modulated by highly dynamic exchanges between three-dimensional conformational substates, which are difficult to characterize experimentally and computationally. Here, we present an innovative, entirely kinematic computational procedure to efficiently explore the native ensemble of RNA molecules. Our procedure projects degrees of freedom onto a subspace of conformation space defined by distance constraints in the tertiary structure. The dimensionality reduction enables efficient exploration of conformational space. We show that the conformational distributions obtained with our method broadly sample the conformational landscape observed in NMR experiments. Compared to normal mode analysis-based exploration, our procedure diffuses faster through the experimental ensemble while also accessing conformational substates to greater precision. Our results suggest that conformational sampling with a highly reduced but fully atomistic representation of noncoding RNA expresses key features of their dynamic nature.
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A flexible docking scheme to explore the binding selectivity of PDZ domains.
Gerek, Z Nevin; Ozkan, S Banu
2010-05-01
Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using ROSETTALIGAND, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 A. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately.
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A flexible docking scheme to explore the binding selectivity of PDZ domains
Gerek, Z Nevin; Ozkan, S Banu
2010-01-01
Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using RosettaLigand, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 Å. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately. PMID:20196074
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Johnson, David K; Karanicolas, John
2013-01-01
Despite intense interest and considerable effort via high-throughput screening, there are few examples of small molecules that directly inhibit protein-protein interactions. This suggests that many protein interaction surfaces may not be intrinsically "druggable" by small molecules, and elevates in importance the few successful examples as model systems for improving our fundamental understanding of druggability. Here we describe an approach for exploring protein fluctuations enriched in conformations containing surface pockets suitable for small molecule binding. Starting from a set of seven unbound protein structures, we find that the presence of low-energy pocket-containing conformations is indeed a signature of druggable protein interaction sites and that analogous surface pockets are not formed elsewhere on the protein. We further find that ensembles of conformations generated with this biased approach structurally resemble known inhibitor-bound structures more closely than equivalent ensembles of unbiased conformations. Collectively these results suggest that "druggability" is a property encoded on a protein surface through its propensity to form pockets, and inspire a model in which the crude features of the predisposed pocket(s) restrict the range of complementary ligands; additional smaller conformational changes then respond to details of a particular ligand. We anticipate that the insights described here will prove useful in selecting protein targets for therapeutic intervention.
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Is the Conformational Ensemble of Alzheimer’s Aβ10-40 Peptide Force Field Dependent?
Siwy, Christopher M.
2017-01-01
By applying REMD simulations we have performed comparative analysis of the conformational ensembles of amino-truncated Aβ10-40 peptide produced with five force fields, which combine four protein parameterizations (CHARMM36, CHARMM22*, CHARMM22/cmap, and OPLS-AA) and two water models (standard and modified TIP3P). Aβ10-40 conformations were analyzed by computing secondary structure, backbone fluctuations, tertiary interactions, and radius of gyration. We have also calculated Aβ10-40 3JHNHα-coupling and RDC constants and compared them with their experimental counterparts obtained for the full-length Aβ1-40 peptide. Our study led us to several conclusions. First, all force fields predict that Aβ adopts unfolded structure dominated by turn and random coil conformations. Second, specific TIP3P water model does not dramatically affect secondary or tertiary Aβ10-40 structure, albeit standard TIP3P model favors slightly more compact states. Third, although the secondary structures observed in CHARMM36 and CHARMM22/cmap simulations are qualitatively similar, their tertiary interactions show little consistency. Fourth, two force fields, OPLS-AA and CHARMM22* have unique features setting them apart from CHARMM36 or CHARMM22/cmap. OPLS-AA reveals moderate β-structure propensity coupled with extensive, but weak long-range tertiary interactions leading to Aβ collapsed conformations. CHARMM22* exhibits moderate helix propensity and generates multiple exceptionally stable long- and short-range interactions. Our investigation suggests that among all force fields CHARMM22* differs the most from CHARMM36. Fifth, the analysis of 3JHNHα-coupling and RDC constants based on CHARMM36 force field with standard TIP3P model led us to an unexpected finding that in silico Aβ10-40 and experimental Aβ1-40 constants are generally in better agreement than these quantities computed and measured for identical peptides, such as Aβ1-40 or Aβ1-42. This observation suggests that the differences in the conformational ensembles of Aβ10-40 and Aβ1-40 are small and the former can be used as proxy of the full-length peptide. Based on this argument, we concluded that CHARMM36 force field with standard TIP3P model produces the most accurate representation of Aβ10-40 conformational ensemble. PMID:28085875
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Fuchs, Julian E; Waldner, Birgit J; Huber, Roland G; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R
2015-03-10
Conformational dynamics are central for understanding biomolecular structure and function, since biological macromolecules are inherently flexible at room temperature and in solution. Computational methods are nowadays capable of providing valuable information on the conformational ensembles of biomolecules. However, analysis tools and intuitive metrics that capture dynamic information from in silico generated structural ensembles are limited. In standard work-flows, flexibility in a conformational ensemble is represented through residue-wise root-mean-square fluctuations or B-factors following a global alignment. Consequently, these approaches relying on global alignments discard valuable information on local dynamics. Results inherently depend on global flexibility, residue size, and connectivity. In this study we present a novel approach for capturing positional fluctuations based on multiple local alignments instead of one single global alignment. The method captures local dynamics within a structural ensemble independent of residue type by splitting individual local and global degrees of freedom of protein backbone and side-chains. Dependence on residue type and size in the side-chains is removed via normalization with the B-factors of the isolated residue. As a test case, we demonstrate its application to a molecular dynamics simulation of bovine pancreatic trypsin inhibitor (BPTI) on the millisecond time scale. This allows for illustrating different time scales of backbone and side-chain flexibility. Additionally, we demonstrate the effects of ligand binding on side-chain flexibility of three serine proteases. We expect our new methodology for quantifying local flexibility to be helpful in unraveling local changes in biomolecular dynamics.
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Davey, James A; Chica, Roberto A
2014-05-01
Multistate computational protein design (MSD) with backbone ensembles approximating conformational flexibility can predict higher quality sequences than single-state design with a single fixed backbone. However, it is currently unclear what characteristics of backbone ensembles are required for the accurate prediction of protein sequence stability. In this study, we aimed to improve the accuracy of protein stability predictions made with MSD by using a variety of backbone ensembles to recapitulate the experimentally measured stability of 85 Streptococcal protein G domain β1 sequences. Ensembles tested here include an NMR ensemble as well as those generated by molecular dynamics (MD) simulations, by Backrub motions, and by PertMin, a new method that we developed involving the perturbation of atomic coordinates followed by energy minimization. MSD with the PertMin ensembles resulted in the most accurate predictions by providing the highest number of stable sequences in the top 25, and by correctly binning sequences as stable or unstable with the highest success rate (≈90%) and the lowest number of false positives. The performance of PertMin ensembles is due to the fact that their members closely resemble the input crystal structure and have low potential energy. Conversely, the NMR ensemble as well as those generated by MD simulations at 500 or 1000 K reduced prediction accuracy due to their low structural similarity to the crystal structure. The ensembles tested herein thus represent on- or off-target models of the native protein fold and could be used in future studies to design for desired properties other than stability. Copyright © 2013 Wiley Periodicals, Inc.
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NMR Studies of Dynamic Biomolecular Conformational Ensembles
Torchia, Dennis A.
2015-01-01
Multidimensional heteronuclear NMR approaches can provide nearly complete sequential signal assignments of isotopically enriched biomolecules. The availability of assignments together with measurements of spin relaxation rates, residual spin interactions, J-couplings and chemical shifts provides information at atomic resolution about internal dynamics on timescales ranging from ps to ms, both in solution and in the solid state. However, due to the complexity of biomolecules, it is not possible to extract a unique atomic-resolution description of biomolecular motions even from extensive NMR data when many conformations are sampled on multiple timescales. For this reason, powerful computational approaches are increasingly applied to large NMR data sets to elucidate conformational ensembles sampled by biomolecules. In the past decade, considerable attention has been directed at an important class of biomolecules that function by binding to a wide variety of target molecules. Questions of current interest are: “Does the free biomolecule sample a conformational ensemble that encompasses the conformations found when it binds to various targets; and if so, on what time scale is the ensemble sampled?” This article reviews recent efforts to answer these questions, with a focus on comparing ensembles obtained for the same biomolecules by different investigators. A detailed comparison of results obtained is provided for three biomolecules: ubiquitin, calmodulin and the HIV-1 trans-activation response RNA. PMID:25669739
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Lee, Kuo Hao; Chen, Jianhan
2017-06-15
Accurate treatment of solvent environment is critical for reliable simulations of protein conformational equilibria. Implicit treatment of solvation, such as using the generalized Born (GB) class of models arguably provides an optimal balance between computational efficiency and physical accuracy. Yet, GB models are frequently plagued by a tendency to generate overly compact structures. The physical origins of this drawback are relatively well understood, and the key to a balanced implicit solvent protein force field is careful optimization of physical parameters to achieve a sufficient level of cancellation of errors. The latter has been hampered by the difficulty of generating converged conformational ensembles of non-trivial model proteins using the popular replica exchange sampling technique. Here, we leverage improved sampling efficiency of a newly developed multi-scale enhanced sampling technique to re-optimize the generalized-Born with molecular volume (GBMV2) implicit solvent model with the CHARMM36 protein force field. Recursive optimization of key GBMV2 parameters (such as input radii) and protein torsion profiles (via the CMAP torsion cross terms) has led to a more balanced GBMV2 protein force field that recapitulates the structures and stabilities of both helical and β-hairpin model peptides. Importantly, this force field appears to be free of the over-compaction bias, and can generate structural ensembles of several intrinsically disordered proteins of various lengths that seem highly consistent with available experimental data. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
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Ligand-biased ensemble receptor docking (LigBEnD): a hybrid ligand/receptor structure-based approach
NASA Astrophysics Data System (ADS)
Lam, Polo C.-H.; Abagyan, Ruben; Totrov, Maxim
2018-01-01
Ligand docking to flexible protein molecules can be efficiently carried out through ensemble docking to multiple protein conformations, either from experimental X-ray structures or from in silico simulations. The success of ensemble docking often requires the careful selection of complementary protein conformations, through docking and scoring of known co-crystallized ligands. False positives, in which a ligand in a wrong pose achieves a better docking score than that of native pose, arise as additional protein conformations are added. In the current study, we developed a new ligand-biased ensemble receptor docking method and composite scoring function which combine the use of ligand-based atomic property field (APF) method with receptor structure-based docking. This method helps us to correctly dock 30 out of 36 ligands presented by the D3R docking challenge. For the six mis-docked ligands, the cognate receptor structures prove to be too different from the 40 available experimental Pocketome conformations used for docking and could be identified only by receptor sampling beyond experimentally explored conformational subspace.
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2013-01-01
Background Many problems in protein modeling require obtaining a discrete representation of the protein conformational space as an ensemble of conformations. In ab-initio structure prediction, in particular, where the goal is to predict the native structure of a protein chain given its amino-acid sequence, the ensemble needs to satisfy energetic constraints. Given the thermodynamic hypothesis, an effective ensemble contains low-energy conformations which are similar to the native structure. The high-dimensionality of the conformational space and the ruggedness of the underlying energy surface currently make it very difficult to obtain such an ensemble. Recent studies have proposed that Basin Hopping is a promising probabilistic search framework to obtain a discrete representation of the protein energy surface in terms of local minima. Basin Hopping performs a series of structural perturbations followed by energy minimizations with the goal of hopping between nearby energy minima. This approach has been shown to be effective in obtaining conformations near the native structure for small systems. Recent work by us has extended this framework to larger systems through employment of the molecular fragment replacement technique, resulting in rapid sampling of large ensembles. Methods This paper investigates the algorithmic components in Basin Hopping to both understand and control their effect on the sampling of near-native minima. Realizing that such an ensemble is reduced before further refinement in full ab-initio protocols, we take an additional step and analyze the quality of the ensemble retained by ensemble reduction techniques. We propose a novel multi-objective technique based on the Pareto front to filter the ensemble of sampled local minima. Results and conclusions We show that controlling the magnitude of the perturbation allows directly controlling the distance between consecutively-sampled local minima and, in turn, steering the exploration towards conformations near the native structure. For the minimization step, we show that the addition of Metropolis Monte Carlo-based minimization is no more effective than a simple greedy search. Finally, we show that the size of the ensemble of sampled local minima can be effectively and efficiently reduced by a multi-objective filter to obtain a simpler representation of the probed energy surface. PMID:24564970
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Bazeley, Peter S; Prithivi, Sridevi; Struble, Craig A; Povinelli, Richard J; Sem, Daniel S
2006-01-01
Cytochrome P450 2D6 (CYP2D6) is used to develop an approach for predicting affinity and relevant binding conformation(s) for highly flexible binding sites. The approach combines the use of docking scores and compound properties as attributes in building a neural network (NN) model. It begins by identifying segments of CYP2D6 that are important for binding specificity, based on structural variability among diverse CYP enzymes. A family of distinct, low-energy conformations of CYP2D6 are generated using simulated annealing (SA) and a collection of 82 compounds with known CYP2D6 affinities are docked. Interestingly, docking poses are observed on the backside of the heme as well as in the known active site. Docking scores for the active site binders, along with compound-specific attributes, are used to train a neural network model to properly bin compounds as strong binders, moderate binders, or nonbinders. Attribute selection is used to preselect the most important scores and compound-specific attributes for the model. A prediction accuracy of 85+/-6% is achieved. Dominant attributes include docking scores for three of the 20 conformations in the ensemble as well as the compound's formal charge, number of aromatic rings, and AlogP. Although compound properties were highly predictive attributes (12% improvement over baseline) in the NN-based prediction of CYP2D6 binders, their combined use with docking score attributes is synergistic (net increase of 23% above baseline). Beyond prediction of affinity, attribute selection provides a way to identify the most relevant protein conformation(s), in terms of binding competence. In the case of CYP2D6, three out of the ensemble of 20 SA-generated structures are found to be the most predictive for binding.
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Free-energy landscape of the villin headpiece in an all-atom force field.
Herges, Thomas; Wenzel, Wolfgang
2005-04-01
We investigate the landscape of the internal free-energy of the 36 amino acid villin headpiece with a modified basin hopping method in the all-atom force field PFF01, which was previously used to predictively fold several helical proteins with atomic resolution. We identify near native conformations of the protein as the global optimum of the force field. More than half of the twenty best simulations started from random initial conditions converge to the folding funnel of the native conformation, but several competing low-energy metastable conformations were observed. From 76,000 independently generated conformations we derived a decoy tree which illustrates the topological structure of the entire low-energy part of the free-energy landscape and characterizes the ensemble of metastable conformations. These emerge as similar in secondary content, but differ in tertiary arrangement.
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Johnson, David K.; Karanicolas, John
2013-01-01
Despite intense interest and considerable effort via high-throughput screening, there are few examples of small molecules that directly inhibit protein-protein interactions. This suggests that many protein interaction surfaces may not be intrinsically “druggable” by small molecules, and elevates in importance the few successful examples as model systems for improving our fundamental understanding of druggability. Here we describe an approach for exploring protein fluctuations enriched in conformations containing surface pockets suitable for small molecule binding. Starting from a set of seven unbound protein structures, we find that the presence of low-energy pocket-containing conformations is indeed a signature of druggable protein interaction sites and that analogous surface pockets are not formed elsewhere on the protein. We further find that ensembles of conformations generated with this biased approach structurally resemble known inhibitor-bound structures more closely than equivalent ensembles of unbiased conformations. Collectively these results suggest that “druggability” is a property encoded on a protein surface through its propensity to form pockets, and inspire a model in which the crude features of the predisposed pocket(s) restrict the range of complementary ligands; additional smaller conformational changes then respond to details of a particular ligand. We anticipate that the insights described here will prove useful in selecting protein targets for therapeutic intervention. PMID:23505360
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Barman, Arghya; Hamelberg, Donald
2015-03-01
Self-association of proteins can be triggered by a change in the distribution of the conformational ensemble. Posttranslational modification, such as phosphorylation, can induce a shift in the ensemble of conformations. In the brain of Alzheimer's disease patients, the formation of intra-cellular neurofibrillary tangles deposition is a result of self-aggregation of hyper-phosphorylated tau protein. Biochemical and NMR studies suggest that the cis peptidyl prolyl conformation of a phosphorylated threonine-proline motif in the tau protein renders tau more prone to aggregation than the trans isomer. However, little is known about the role of peptidyl prolyl cis/trans isomerization in tau aggregation. Here, we show that intra-molecular electrostatic interactions are better formed in the trans isomer. We explore the conformational landscape of the tau segment containing the phosphorylated-Thr(231)-Pro(232) motif using accelerated molecular dynamics and show that intra-molecular electrostatic interactions are coupled to the isomeric state of the peptidyl prolyl bond. Our results suggest that the loss of intra-molecular interactions and the more restricted conformational ensemble of the cis isomer could favor self-aggregation. The results are consistent with experiments, providing valuable complementary atomistic insights and a hypothetical model for isomer specific aggregation of the tau protein. © 2014 Wiley Periodicals, Inc.
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Zhu, Guanhua; Liu, Wei; Bao, Chenglong; Tong, Dudu; Ji, Hui; Shen, Zuowei; Yang, Daiwen; Lu, Lanyuan
2018-05-01
The structural variations of multidomain proteins with flexible parts mediate many biological processes, and a structure ensemble can be determined by selecting a weighted combination of representative structures from a simulated structure pool, producing the best fit to experimental constraints such as interatomic distance. In this study, a hybrid structure-based and physics-based atomistic force field with an efficient sampling strategy is adopted to simulate a model di-domain protein against experimental paramagnetic relaxation enhancement (PRE) data that correspond to distance constraints. The molecular dynamics simulations produce a wide range of conformations depicted on a protein energy landscape. Subsequently, a conformational ensemble recovered with low-energy structures and the minimum-size restraint is identified in good agreement with experimental PRE rates, and the result is also supported by chemical shift perturbations and small-angle X-ray scattering data. It is illustrated that the regularizations of energy and ensemble-size prevent an arbitrary interpretation of protein conformations. Moreover, energy is found to serve as a critical control to refine the structure pool and prevent data overfitting, because the absence of energy regularization exposes ensemble construction to the noise from high-energy structures and causes a more ambiguous representation of protein conformations. Finally, we perform structure-ensemble optimizations with a topology-based structure pool, to enhance the understanding on the ensemble results from different sources of pool candidates. © 2018 Wiley Periodicals, Inc.
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NASA Astrophysics Data System (ADS)
Natalello, Antonino; Santambrogio, Carlo; Grandori, Rita
2017-01-01
Native mass spectrometry (MS) has become a central tool of structural proteomics, but its applicability to the peculiar class of intrinsically disordered proteins (IDPs) is still object of debate. IDPs lack an ordered tridimensional structure and are characterized by high conformational plasticity. Since they represent valuable targets for cancer and neurodegeneration research, there is an urgent need of methodological advances for description of the conformational ensembles populated by these proteins in solution. However, structural rearrangements during electrospray-ionization (ESI) or after the transfer to the gas phase could affect data obtained by native ESI-MS. In particular, charge-state distributions (CSDs) are affected by protein conformation inside ESI droplets, while ion mobility (IM) reflects protein conformation in the gas phase. This review focuses on the available evidence relating IDP solution ensembles with CSDs, trying to summarize cases of apparent consistency or discrepancy. The protein-specificity of ionization patterns and their responses to ligands and buffer conditions suggests that CSDs are imprinted to protein structural features also in the case of IDPs. Nevertheless, it seems that these proteins are more easily affected by electrospray conditions, leading in some cases to rearrangements of the conformational ensembles.
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Natalello, Antonino; Santambrogio, Carlo; Grandori, Rita
2017-01-01
Native mass spectrometry (MS) has become a central tool of structural proteomics, but its applicability to the peculiar class of intrinsically disordered proteins (IDPs) is still object of debate. IDPs lack an ordered tridimensional structure and are characterized by high conformational plasticity. Since they represent valuable targets for cancer and neurodegeneration research, there is an urgent need of methodological advances for description of the conformational ensembles populated by these proteins in solution. However, structural rearrangements during electrospray-ionization (ESI) or after the transfer to the gas phase could affect data obtained by native ESI-MS. In particular, charge-state distributions (CSDs) are affected by protein conformation inside ESI droplets, while ion mobility (IM) reflects protein conformation in the gas phase. This review focuses on the available evidence relating IDP solution ensembles with CSDs, trying to summarize cases of apparent consistency or discrepancy. The protein-specificity of ionization patterns and their responses to ligands and buffer conditions suggests that CSDs are imprinted to protein structural features also in the case of IDPs. Nevertheless, it seems that these proteins are more easily affected by electrospray conditions, leading in some cases to rearrangements of the conformational ensembles. Graphical Abstract ᅟ.
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Bootstrapping on Undirected Binary Networks Via Statistical Mechanics
NASA Astrophysics Data System (ADS)
Fushing, Hsieh; Chen, Chen; Liu, Shan-Yu; Koehl, Patrice
2014-09-01
We propose a new method inspired from statistical mechanics for extracting geometric information from undirected binary networks and generating random networks that conform to this geometry. In this method an undirected binary network is perceived as a thermodynamic system with a collection of permuted adjacency matrices as its states. The task of extracting information from the network is then reformulated as a discrete combinatorial optimization problem of searching for its ground state. To solve this problem, we apply multiple ensembles of temperature regulated Markov chains to establish an ultrametric geometry on the network. This geometry is equipped with a tree hierarchy that captures the multiscale community structure of the network. We translate this geometry into a Parisi adjacency matrix, which has a relative low energy level and is in the vicinity of the ground state. The Parisi adjacency matrix is then further optimized by making block permutations subject to the ultrametric geometry. The optimal matrix corresponds to the macrostate of the original network. An ensemble of random networks is then generated such that each of these networks conforms to this macrostate; the corresponding algorithm also provides an estimate of the size of this ensemble. By repeating this procedure at different scales of the ultrametric geometry of the network, it is possible to compute its evolution entropy, i.e. to estimate the evolution of its complexity as we move from a coarse to a fine description of its geometric structure. We demonstrate the performance of this method on simulated as well as real data networks.
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NASA Astrophysics Data System (ADS)
Oda, Akifumi; Fukuyoshi, Shuichi
2015-06-01
The GADV hypothesis is a form of the protein world hypothesis, which suggests that life originated from proteins (Lacey et al. 1999; Ikehara 2002; Andras 2006). In the GADV hypothesis, life is thought to have originated from primitive proteins constructed of only glycine, alanine, aspartic acid, and valine ([GADV]-proteins). In this study, the three-dimensional (3D) conformations of randomly generated short [GADV]-peptides were computationally investigated using replica-exchange molecular dynamics (REMD) simulations (Sugita and Okamoto 1999). Because the peptides used in this study consisted of only 20 residues each, they could not form certain 3D structures. However, the conformational tendencies of the peptides were elucidated by analyzing the conformational ensembles generated by REMD simulations. The results indicate that secondary structures can be formed in several randomly generated [GADV]-peptides. A long helical structure was found in one of the hydrophobic peptides, supporting the conjecture of the GADV hypothesis that many peptides aggregated to form peptide multimers with enzymatic activity in the primordial soup. In addition, these results indicate that REMD simulations can be used for the structural investigation of short peptides.
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Hernández, Griselda; Anderson, Janet S.; LeMaster, David M.
2012-01-01
The acute sensitivity to conformation exhibited by amide hydrogen exchange reactivity provides a valuable test for the physical accuracy of model ensembles developed to represent the Boltzmann distribution of the protein native state. A number of molecular dynamics studies of ubiquitin have predicted a well-populated transition in the tight turn immediately preceding the primary site of proteasome-directed polyubiquitylation Lys 48. Amide exchange reactivity analysis demonstrates that this transition is 103-fold rarer than these predictions. More strikingly, for the most populated novel conformational basin predicted from a recent 1 ms MD simulation of bovine pancreatic trypsin inhibitor (at 13% of total), experimental hydrogen exchange data indicates a population below 10−6. The most sophisticated efforts to directly incorporate experimental constraints into the derivation of model protein ensembles have been applied to ubiquitin, as illustrated by three recently deposited studies (PDB codes 2NR2, 2K39 and 2KOX). Utilizing the extensive set of experimental NOE constraints, each of these three ensembles yields a modestly more accurate prediction of the exchange rates for the highly exposed amides than does a standard unconstrained molecular simulation. However, for the less frequently exposed amide hydrogens, the 2NR2 ensemble offers no improvement in rate predictions as compared to the unconstrained MD ensemble. The other two NMR-constrained ensembles performed markedly worse, either underestimating (2KOX) or overestimating (2K39) the extent of conformational diversity. PMID:22425325
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NASA Astrophysics Data System (ADS)
Orellana, Laura; Yoluk, Ozge; Carrillo, Oliver; Orozco, Modesto; Lindahl, Erik
2016-08-01
Protein conformational changes are at the heart of cell functions, from signalling to ion transport. However, the transient nature of the intermediates along transition pathways hampers their experimental detection, making the underlying mechanisms elusive. Here we retrieve dynamic information on the actual transition routes from principal component analysis (PCA) of structurally-rich ensembles and, in combination with coarse-grained simulations, explore the conformational landscapes of five well-studied proteins. Modelling them as elastic networks in a hybrid elastic-network Brownian dynamics simulation (eBDIMS), we generate trajectories connecting stable end-states that spontaneously sample the crystallographic motions, predicting the structures of known intermediates along the paths. We also show that the explored non-linear routes can delimit the lowest energy passages between end-states sampled by atomistic molecular dynamics. The integrative methodology presented here provides a powerful framework to extract and expand dynamic pathway information from the Protein Data Bank, as well as to validate sampling methods in general.
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Estimation of Uncertainties in the Global Distance Test (GDT_TS) for CASP Models.
Li, Wenlin; Schaeffer, R Dustin; Otwinowski, Zbyszek; Grishin, Nick V
2016-01-01
The Critical Assessment of techniques for protein Structure Prediction (or CASP) is a community-wide blind test experiment to reveal the best accomplishments of structure modeling. Assessors have been using the Global Distance Test (GDT_TS) measure to quantify prediction performance since CASP3 in 1998. However, identifying significant score differences between close models is difficult because of the lack of uncertainty estimations for this measure. Here, we utilized the atomic fluctuations caused by structure flexibility to estimate the uncertainty of GDT_TS scores. Structures determined by nuclear magnetic resonance are deposited as ensembles of alternative conformers that reflect the structural flexibility, whereas standard X-ray refinement produces the static structure averaged over time and space for the dynamic ensembles. To recapitulate the structural heterogeneous ensemble in the crystal lattice, we performed time-averaged refinement for X-ray datasets to generate structural ensembles for our GDT_TS uncertainty analysis. Using those generated ensembles, our study demonstrates that the time-averaged refinements produced structure ensembles with better agreement with the experimental datasets than the averaged X-ray structures with B-factors. The uncertainty of the GDT_TS scores, quantified by their standard deviations (SDs), increases for scores lower than 50 and 70, with maximum SDs of 0.3 and 1.23 for X-ray and NMR structures, respectively. We also applied our procedure to the high accuracy version of GDT-based score and produced similar results with slightly higher SDs. To facilitate score comparisons by the community, we developed a user-friendly web server that produces structure ensembles for NMR and X-ray structures and is accessible at http://prodata.swmed.edu/SEnCS. Our work helps to identify the significance of GDT_TS score differences, as well as to provide structure ensembles for estimating SDs of any scores.
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Physical–chemical determinants of coil conformations in globular proteins
Perskie, Lauren L; Rose, George D
2010-01-01
We present a method with the potential to generate a library of coil segments from first principles. Proteins are built from α-helices and/or β-strands interconnected by these coil segments. Here, we investigate the conformational determinants of short coil segments, with particular emphasis on chain turns. Toward this goal, we extracted a comprehensive set of two-, three-, and four-residue turns from X-ray–elucidated proteins and classified them by conformation. A remarkably small number of unique conformers account for most of this experimentally determined set, whereas remaining members span a large number of rare conformers, many occurring only once in the entire protein database. Factors determining conformation were identified via Metropolis Monte Carlo simulations devised to test the effectiveness of various energy terms. Simulated structures were validated by comparison to experimental counterparts. After filtering rare conformers, we found that 98% of the remaining experimentally determined turn population could be reproduced by applying a hydrogen bond energy term to an exhaustively generated ensemble of clash-free conformers in which no backbone polar group lacks a hydrogen-bond partner. Further, at least 90% of longer coil segments, ranging from 5- to 20 residues, were found to be structural composites of these shorter primitives. These results are pertinent to protein structure prediction, where approaches can be divided into either empirical or ab initio methods. Empirical methods use database-derived information; ab initio methods rely on physical–chemical principles exclusively. Replacing the database-derived coil library with one generated from first principles would transform any empirically based method into its corresponding ab initio homologue. PMID:20512968
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pE-DB: a database of structural ensembles of intrinsically disordered and of unfolded proteins.
Varadi, Mihaly; Kosol, Simone; Lebrun, Pierre; Valentini, Erica; Blackledge, Martin; Dunker, A Keith; Felli, Isabella C; Forman-Kay, Julie D; Kriwacki, Richard W; Pierattelli, Roberta; Sussman, Joel; Svergun, Dmitri I; Uversky, Vladimir N; Vendruscolo, Michele; Wishart, David; Wright, Peter E; Tompa, Peter
2014-01-01
The goal of pE-DB (http://pedb.vib.be) is to serve as an openly accessible database for the deposition of structural ensembles of intrinsically disordered proteins (IDPs) and of denatured proteins based on nuclear magnetic resonance spectroscopy, small-angle X-ray scattering and other data measured in solution. Owing to the inherent flexibility of IDPs, solution techniques are particularly appropriate for characterizing their biophysical properties, and structural ensembles in agreement with these data provide a convenient tool for describing the underlying conformational sampling. Database entries consist of (i) primary experimental data with descriptions of the acquisition methods and algorithms used for the ensemble calculations, and (ii) the structural ensembles consistent with these data, provided as a set of models in a Protein Data Bank format. PE-DB is open for submissions from the community, and is intended as a forum for disseminating the structural ensembles and the methodologies used to generate them. While the need to represent the IDP structures is clear, methods for determining and evaluating the structural ensembles are still evolving. The availability of the pE-DB database is expected to promote the development of new modeling methods and leads to a better understanding of how function arises from disordered states.
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Conformational equilibria of light-activated rhodopsin in nanodiscs
Van Eps, Ned; Caro, Lydia N.; Morizumi, Takefumi; Kusnetzow, Ana Karin; Szczepek, Michal; Hofmann, Klaus Peter; Bayburt, Timothy H.; Sligar, Stephen G.; Ernst, Oliver P.; Hubbell, Wayne L.
2017-01-01
Conformational equilibria of G-protein–coupled receptors (GPCRs) are intimately involved in intracellular signaling. Here conformational substates of the GPCR rhodopsin are investigated in micelles of dodecyl maltoside (DDM) and in phospholipid nanodiscs by monitoring the spatial positions of transmembrane helices 6 and 7 at the cytoplasmic surface using site-directed spin labeling and double electron–electron resonance spectroscopy. The photoactivated receptor in DDM is dominated by one conformation with weak pH dependence. In nanodiscs, however, an ensemble of pH-dependent conformational substates is observed, even at pH 6.0 where the MIIbH+ form defined by proton uptake and optical spectroscopic methods is reported to be the sole species present in native disk membranes. In nanodiscs, the ensemble of substates in the photoactivated receptor spontaneously decays to that characteristic of the inactive state with a lifetime of ∼16 min at 20 °C. Importantly, transducin binding to the activated receptor selects a subset of the ensemble in which multiple substates are apparently retained. The results indicate that in a native-like lipid environment rhodopsin activation is not analogous to a simple binary switch between two defined conformations, but the activated receptor is in equilibrium between multiple conformers that in principle could recognize different binding partners. PMID:28373559
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Ahlstrom, Logan S.; Vorontsov, Ivan I.; Shi, Jun; Miyashita, Osamu
2017-01-01
Side chains in protein crystal structures are essential for understanding biochemical processes such as catalysis and molecular recognition. However, crystal packing could influence side-chain conformation and dynamics, thus complicating functional interpretations of available experimental structures. Here we investigate the effect of crystal packing on side-chain conformational dynamics with crystal and solution molecular dynamics simulations using Cyanovirin-N as a model system. Side-chain ensembles for solvent-exposed residues obtained from simulation largely reflect the conformations observed in the X-ray structure. This agreement is most striking for crystal-contacting residues during crystal simulation. Given the high level of correspondence between our simulations and the X-ray data, we compare side-chain ensembles in solution and crystal simulations. We observe large decreases in conformational entropy in the crystal for several long, polar and contacting residues on the protein surface. Such cases agree well with the average loss in conformational entropy per residue upon protein folding and are accompanied by a change in side-chain conformation. This finding supports the application of surface engineering to facilitate crystallization. Our simulation-based approach demonstrated here with Cyanovirin-N establishes a framework for quantitatively comparing side-chain ensembles in solution and in the crystal across a larger set of proteins to elucidate the effect of the crystal environment on protein conformations. PMID:28107510
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Ahlstrom, Logan S; Vorontsov, Ivan I; Shi, Jun; Miyashita, Osamu
2017-01-01
Side chains in protein crystal structures are essential for understanding biochemical processes such as catalysis and molecular recognition. However, crystal packing could influence side-chain conformation and dynamics, thus complicating functional interpretations of available experimental structures. Here we investigate the effect of crystal packing on side-chain conformational dynamics with crystal and solution molecular dynamics simulations using Cyanovirin-N as a model system. Side-chain ensembles for solvent-exposed residues obtained from simulation largely reflect the conformations observed in the X-ray structure. This agreement is most striking for crystal-contacting residues during crystal simulation. Given the high level of correspondence between our simulations and the X-ray data, we compare side-chain ensembles in solution and crystal simulations. We observe large decreases in conformational entropy in the crystal for several long, polar and contacting residues on the protein surface. Such cases agree well with the average loss in conformational entropy per residue upon protein folding and are accompanied by a change in side-chain conformation. This finding supports the application of surface engineering to facilitate crystallization. Our simulation-based approach demonstrated here with Cyanovirin-N establishes a framework for quantitatively comparing side-chain ensembles in solution and in the crystal across a larger set of proteins to elucidate the effect of the crystal environment on protein conformations.
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Chirikjian, Gregory S.
2011-01-01
Proteins fold from a highly disordered state into a highly ordered one. Traditionally, the folding problem has been stated as one of predicting ‘the’ tertiary structure from sequential information. However, new evidence suggests that the ensemble of unfolded forms may not be as disordered as once believed, and that the native form of many proteins may not be described by a single conformation, but rather an ensemble of its own. Quantifying the relative disorder in the folded and unfolded ensembles as an entropy difference may therefore shed light on the folding process. One issue that clouds discussions of ‘entropy’ is that many different kinds of entropy can be defined: entropy associated with overall translational and rotational Brownian motion, configurational entropy, vibrational entropy, conformational entropy computed in internal or Cartesian coordinates (which can even be different from each other), conformational entropy computed on a lattice; each of the above with different solvation and solvent models; thermodynamic entropy measured experimentally, etc. The focus of this work is the conformational entropy of coil/loop regions in proteins. New mathematical modeling tools for the approximation of changes in conformational entropy during transition from unfolded to folded ensembles are introduced. In particular, models for computing lower and upper bounds on entropy for polymer models of polypeptide coils both with and without end constraints are presented. The methods reviewed here include kinematics (the mathematics of rigid-body motions), classical statistical mechanics and information theory. PMID:21187223
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Kukic, Predrag; Lundström, Patrik; Camilloni, Carlo; Evenäs, Johan; Akke, Mikael; Vendruscolo, Michele
2016-01-12
Calmodulin is a two-domain signaling protein that becomes activated upon binding cooperatively two pairs of calcium ions, leading to large-scale conformational changes that expose its binding site. Despite significant advances in understanding the structural biology of calmodulin functions, the mechanistic details of the conformational transition between closed and open states have remained unclear. To investigate this transition, we used a combination of molecular dynamics simulations and nuclear magnetic resonance (NMR) experiments on the Ca(2+)-saturated E140Q C-terminal domain variant. Using chemical shift restraints in replica-averaged metadynamics simulations, we obtained a high-resolution structural ensemble consisting of two conformational states and validated such an ensemble against three independent experimental data sets, namely, interproton nuclear Overhauser enhancements, (15)N order parameters, and chemical shift differences between the exchanging states. Through a detailed analysis of this structural ensemble and of the corresponding statistical weights, we characterized a calcium-mediated conformational transition whereby the coordination of Ca(2+) by just one oxygen of the bidentate ligand E140 triggers a concerted movement of the two EF-hands that exposes the target binding site. This analysis provides atomistic insights into a possible Ca(2+)-mediated activation mechanism of calmodulin that cannot be achieved from static structures alone or from ensemble NMR measurements of the transition between conformations.
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Pandini, Alessandro; Fraccalvieri, Domenico; Bonati, Laura
2013-01-01
The biological function of proteins is strictly related to their molecular flexibility and dynamics: enzymatic activity, protein-protein interactions, ligand binding and allosteric regulation are important mechanisms involving protein motions. Computational approaches, such as Molecular Dynamics (MD) simulations, are now routinely used to study the intrinsic dynamics of target proteins as well as to complement molecular docking approaches. These methods have also successfully supported the process of rational design and discovery of new drugs. Identification of functionally relevant conformations is a key step in these studies. This is generally done by cluster analysis of the ensemble of structures in the MD trajectory. Recently Artificial Neural Network (ANN) approaches, in particular methods based on Self-Organising Maps (SOMs), have been reported performing more accurately and providing more consistent results than traditional clustering algorithms in various data-mining problems. In the specific case of conformational analysis, SOMs have been successfully used to compare multiple ensembles of protein conformations demonstrating a potential in efficiently detecting the dynamic signatures central to biological function. Moreover, examples of the use of SOMs to address problems relevant to other stages of the drug-design process, including clustering of docking poses, have been reported. In this contribution we review recent applications of ANN algorithms in analysing conformational and structural ensembles and we discuss their potential in computer-based approaches for medicinal chemistry.
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Di Pierro, Michele; Cheng, Ryan R; Lieberman Aiden, Erez; Wolynes, Peter G; Onuchic, José N
2017-11-14
Inside the cell nucleus, genomes fold into organized structures that are characteristic of cell type. Here, we show that this chromatin architecture can be predicted de novo using epigenetic data derived from chromatin immunoprecipitation-sequencing (ChIP-Seq). We exploit the idea that chromosomes encode a 1D sequence of chromatin structural types. Interactions between these chromatin types determine the 3D structural ensemble of chromosomes through a process similar to phase separation. First, a neural network is used to infer the relation between the epigenetic marks present at a locus, as assayed by ChIP-Seq, and the genomic compartment in which those loci reside, as measured by DNA-DNA proximity ligation (Hi-C). Next, types inferred from this neural network are used as an input to an energy landscape model for chromatin organization [Minimal Chromatin Model (MiChroM)] to generate an ensemble of 3D chromosome conformations at a resolution of 50 kilobases (kb). After training the model, dubbed Maximum Entropy Genomic Annotation from Biomarkers Associated to Structural Ensembles (MEGABASE), on odd-numbered chromosomes, we predict the sequences of chromatin types and the subsequent 3D conformational ensembles for the even chromosomes. We validate these structural ensembles by using ChIP-Seq tracks alone to predict Hi-C maps, as well as distances measured using 3D fluorescence in situ hybridization (FISH) experiments. Both sets of experiments support the hypothesis of phase separation being the driving process behind compartmentalization. These findings strongly suggest that epigenetic marking patterns encode sufficient information to determine the global architecture of chromosomes and that de novo structure prediction for whole genomes may be increasingly possible. Copyright © 2017 the Author(s). Published by PNAS.
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Ovchinnikov, Victor; Karplus, Martin
2012-07-26
The popular targeted molecular dynamics (TMD) method for generating transition paths in complex biomolecular systems is revisited. In a typical TMD transition path, the large-scale changes occur early and the small-scale changes tend to occur later. As a result, the order of events in the computed paths depends on the direction in which the simulations are performed. To identify the origin of this bias, and to propose a method in which the bias is absent, variants of TMD in the restraint formulation are introduced and applied to the complex open ↔ closed transition in the protein calmodulin. Due to the global best-fit rotation that is typically part of the TMD method, the simulated system is guided implicitly along the lowest-frequency normal modes, until the large spatial scales associated with these modes are near the target conformation. The remaining portion of the transition is described progressively by higher-frequency modes, which correspond to smaller-scale rearrangements. A straightforward modification of TMD that avoids the global best-fit rotation is the locally restrained TMD (LRTMD) method, in which the biasing potential is constructed from a number of TMD potentials, each acting on a small connected portion of the protein sequence. With a uniform distribution of these elements, transition paths that lack the length-scale bias are obtained. Trajectories generated by steered MD in dihedral angle space (DSMD), a method that avoids best-fit rotations altogether, also lack the length-scale bias. To examine the importance of the paths generated by TMD, LRTMD, and DSMD in the actual transition, we use the finite-temperature string method to compute the free energy profile associated with a transition tube around a path generated by each algorithm. The free energy barriers associated with the paths are comparable, suggesting that transitions can occur along each route with similar probabilities. This result indicates that a broad ensemble of paths needs to be calculated to obtain a full description of conformational changes in biomolecules. The breadth of the contributing ensemble suggests that energetic barriers for conformational transitions in proteins are offset by entropic contributions that arise from a large number of possible paths.
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Nullspace Sampling with Holonomic Constraints Reveals Molecular Mechanisms of Protein Gαs.
Pachov, Dimitar V; van den Bedem, Henry
2015-07-01
Proteins perform their function or interact with partners by exchanging between conformational substates on a wide range of spatiotemporal scales. Structurally characterizing these exchanges is challenging, both experimentally and computationally. Large, diffusional motions are often on timescales that are difficult to access with molecular dynamics simulations, especially for large proteins and their complexes. The low frequency modes of normal mode analysis (NMA) report on molecular fluctuations associated with biological activity. However, NMA is limited to a second order expansion about a minimum of the potential energy function, which limits opportunities to observe diffusional motions. By contrast, kino-geometric conformational sampling (KGS) permits large perturbations while maintaining the exact geometry of explicit conformational constraints, such as hydrogen bonds. Here, we extend KGS and show that a conformational ensemble of the α subunit Gαs of heterotrimeric stimulatory protein Gs exhibits structural features implicated in its activation pathway. Activation of protein Gs by G protein-coupled receptors (GPCRs) is associated with GDP release and large conformational changes of its α-helical domain. Our method reveals a coupled α-helical domain opening motion while, simultaneously, Gαs helix α5 samples an activated conformation. These motions are moderated in the activated state. The motion centers on a dynamic hub near the nucleotide-binding site of Gαs, and radiates to helix α4. We find that comparative NMA-based ensembles underestimate the amplitudes of the motion. Additionally, the ensembles fall short in predicting the accepted direction of the full activation pathway. Taken together, our findings suggest that nullspace sampling with explicit, holonomic constraints yields ensembles that illuminate molecular mechanisms involved in GDP release and protein Gs activation, and further establish conformational coupling between key structural elements of Gαs.
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Nullspace Sampling with Holonomic Constraints Reveals Molecular Mechanisms of Protein Gαs
Pachov, Dimitar V.; van den Bedem, Henry
2015-01-01
Proteins perform their function or interact with partners by exchanging between conformational substates on a wide range of spatiotemporal scales. Structurally characterizing these exchanges is challenging, both experimentally and computationally. Large, diffusional motions are often on timescales that are difficult to access with molecular dynamics simulations, especially for large proteins and their complexes. The low frequency modes of normal mode analysis (NMA) report on molecular fluctuations associated with biological activity. However, NMA is limited to a second order expansion about a minimum of the potential energy function, which limits opportunities to observe diffusional motions. By contrast, kino-geometric conformational sampling (KGS) permits large perturbations while maintaining the exact geometry of explicit conformational constraints, such as hydrogen bonds. Here, we extend KGS and show that a conformational ensemble of the α subunit Gαs of heterotrimeric stimulatory protein Gs exhibits structural features implicated in its activation pathway. Activation of protein Gs by G protein-coupled receptors (GPCRs) is associated with GDP release and large conformational changes of its α-helical domain. Our method reveals a coupled α-helical domain opening motion while, simultaneously, Gαs helix α5 samples an activated conformation. These motions are moderated in the activated state. The motion centers on a dynamic hub near the nucleotide-binding site of Gαs, and radiates to helix α4. We find that comparative NMA-based ensembles underestimate the amplitudes of the motion. Additionally, the ensembles fall short in predicting the accepted direction of the full activation pathway. Taken together, our findings suggest that nullspace sampling with explicit, holonomic constraints yields ensembles that illuminate molecular mechanisms involved in GDP release and protein Gs activation, and further establish conformational coupling between key structural elements of Gαs. PMID:26218073
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A Unified Conformational Selection and Induced Fit Approach to Protein-Peptide Docking
Trellet, Mikael; Melquiond, Adrien S. J.; Bonvin, Alexandre M. J. J.
2013-01-01
Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking. PMID:23516555
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A unified conformational selection and induced fit approach to protein-peptide docking.
Trellet, Mikael; Melquiond, Adrien S J; Bonvin, Alexandre M J J
2013-01-01
Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking.
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Rozentur-Shkop, Eva; Goobes, Gil; Chill, Jordan H
2016-12-01
Intrinsically disordered proteins (IDPs) are multi-conformational polypeptides that lack a single stable three-dimensional structure. It has become increasingly clear that the versatile IDPs play key roles in a multitude of biological processes, and, given their flexible nature, NMR is a leading method to investigate IDP behavior on the molecular level. Here we present an IDP-tailored J-modulated experiment designed to monitor changes in the conformational ensemble characteristic of IDPs by accurately measuring backbone one- and two-bond J( 15 N, 13 Cα) couplings. This concept was realized using a unidirectional (H)NCO 13 C-detected experiment suitable for poor spectral dispersion and optimized for maximum coverage of amino acid types. To demonstrate the utility of this approach we applied it to the disordered actin-binding N-terminal domain of WASp interacting protein (WIP), a ubiquitous key modulator of cytoskeletal changes in a range of biological systems. One- and two-bond J( 15 N, 13 Cα) couplings were acquired for WIP residues 2-65 at various temperatures, and in denaturing and crowding environments. Under native conditions fitted J-couplings identified in the WIP conformational ensemble a propensity for extended conformation at residues 16-23 and 45-60, and a helical tendency at residues 28-42. These findings are consistent with a previous study of the based upon chemical shift and RDC data and confirm that the WIP 2-65 conformational ensemble is biased towards the structure assumed by this fragment in its actin-bound form. The effects of environmental changes upon this ensemble were readily apparent in the J-coupling data, which reflected a significant decrease in structural propensity at higher temperatures, in the presence of 8 M urea, and under the influence of a bacterial cell lysate. The latter suggests that crowding can cause protein unfolding through protein-protein interactions that stabilize the unfolded state. We conclude that J-couplings are a useful measureable in characterizing structural ensembles in IDPs, and that the proposed experiment provides a practical method for accurately performing such measurements, once again emphasizing the power of NMR in studying IDP behavior.
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Conformational ensembles of RNA oligonucleotides from integrating NMR and molecular simulations.
Bottaro, Sandro; Bussi, Giovanni; Kennedy, Scott D; Turner, Douglas H; Lindorff-Larsen, Kresten
2018-05-01
RNA molecules are key players in numerous cellular processes and are characterized by a complex relationship between structure, dynamics, and function. Despite their apparent simplicity, RNA oligonucleotides are very flexible molecules, and understanding their internal dynamics is particularly challenging using experimental data alone. We show how to reconstruct the conformational ensemble of four RNA tetranucleotides by combining atomistic molecular dynamics simulations with nuclear magnetic resonance spectroscopy data. The goal is achieved by reweighting simulations using a maximum entropy/Bayesian approach. In this way, we overcome problems of current simulation methods, as well as in interpreting ensemble- and time-averaged experimental data. We determine the populations of different conformational states by considering several nuclear magnetic resonance parameters and point toward properties that are not captured by state-of-the-art molecular force fields. Although our approach is applied on a set of model systems, it is fully general and may be used to study the conformational dynamics of flexible biomolecules and to detect inaccuracies in molecular dynamics force fields.
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Turney, Toby; Pan, Qingfeng; Sernau, Luke; Carmichael, Ian; Zhang, Wenhui; Wang, Xiaocong; Woods, Robert J; Serianni, Anthony S
2017-01-12
α- and β-d-glucopyranose monoacetates 1-3 were prepared with selective 13 C enrichment in the O-acetyl side-chain, and ensembles of 13 C- 1 H and 13 C- 13 C NMR spin-couplings (J-couplings) were measured involving the labeled carbons. Density functional theory (DFT) was applied to a set of model structures to determine which J-couplings are sensitive to rotation of the ester bond θ. Eight J-couplings ( 1 J CC , 2 J CH , 2 J CC , 3 J CH , and 3 J CC ) were found to be sensitive to θ, and four equations were parametrized to allow quantitative interpretations of experimental J-values. Inspection of J-coupling ensembles in 1-3 showed that O-acetyl side-chain conformation depends on molecular context, with flanking groups playing a dominant role in determining the properties of θ in solution. To quantify these effects, ensembles of J-couplings containing four values were used to determine the precision and accuracy of several 2-parameter statistical models of rotamer distributions across θ in 1-3. The statistical method used to generate these models has been encoded in a newly developed program, MA'AT, which is available for public use. These models were compared to O-acetyl side-chain behavior observed in a representative sample of crystal structures, and in molecular dynamics (MD) simulations of O-acetylated model structures. While the functional form of the model had little effect on the precision of the calculated mean of θ in 1-3, platykurtic models were found to give more precise estimates of the width of the distribution about the mean (expressed as circular standard deviations). Validation of these 2-parameter models to interpret ensembles of redundant J-couplings using the O-acetyl system as a test case enables future extension of the approach to other flexible elements in saccharides, such as glycosidic linkage conformation.
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Maciag, Joseph J.; Mackenzie, Sarah H.; Tucker, Matthew B.; Schipper, Joshua L.; Swartz, Paul; Clark, A. Clay
2016-01-01
The native ensemble of caspases is described globally by a complex energy landscape where the binding of substrate selects for the active conformation, whereas targeting an allosteric site in the dimer interface selects an inactive conformation that contains disordered active-site loops. Mutations and posttranslational modifications stabilize high-energy inactive conformations, with mostly formed, but distorted, active sites. To examine the interconversion of active and inactive states in the ensemble, we used detection of related solvent positions to analyze 4,995 waters in 15 high-resolution (<2.0 Å) structures of wild-type caspase-3, resulting in 450 clusters with the most highly conserved set containing 145 water molecules. The data show that regions of the protein that contact the conserved waters also correspond to sites of posttranslational modifications, suggesting that the conserved waters are an integral part of allosteric mechanisms. To test this hypothesis, we created a library of 19 caspase-3 variants through saturation mutagenesis in a single position of the allosteric site of the dimer interface, and we show that the enzyme activity varies by more than four orders of magnitude. Altogether, our database consists of 37 high-resolution structures of caspase-3 variants, and we demonstrate that the decrease in activity correlates with a loss of conserved water molecules. The data show that the activity of caspase-3 can be fine-tuned through globally desolvating the active conformation within the native ensemble, providing a mechanism for cells to repartition the ensemble and thus fine-tune activity through conformational selection. PMID:27681633
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Maciag, Joseph J; Mackenzie, Sarah H; Tucker, Matthew B; Schipper, Joshua L; Swartz, Paul; Clark, A Clay
2016-10-11
The native ensemble of caspases is described globally by a complex energy landscape where the binding of substrate selects for the active conformation, whereas targeting an allosteric site in the dimer interface selects an inactive conformation that contains disordered active-site loops. Mutations and posttranslational modifications stabilize high-energy inactive conformations, with mostly formed, but distorted, active sites. To examine the interconversion of active and inactive states in the ensemble, we used detection of related solvent positions to analyze 4,995 waters in 15 high-resolution (<2.0 Å) structures of wild-type caspase-3, resulting in 450 clusters with the most highly conserved set containing 145 water molecules. The data show that regions of the protein that contact the conserved waters also correspond to sites of posttranslational modifications, suggesting that the conserved waters are an integral part of allosteric mechanisms. To test this hypothesis, we created a library of 19 caspase-3 variants through saturation mutagenesis in a single position of the allosteric site of the dimer interface, and we show that the enzyme activity varies by more than four orders of magnitude. Altogether, our database consists of 37 high-resolution structures of caspase-3 variants, and we demonstrate that the decrease in activity correlates with a loss of conserved water molecules. The data show that the activity of caspase-3 can be fine-tuned through globally desolvating the active conformation within the native ensemble, providing a mechanism for cells to repartition the ensemble and thus fine-tune activity through conformational selection.
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Bhattacharyya, Moitrayee; Vishveshwara, Saraswathi
2011-07-01
In this article, we present a novel application of a quantum clustering (QC) technique to objectively cluster the conformations, sampled by molecular dynamics simulations performed on different ligand bound structures of the protein. We further portray each conformational population in terms of dynamically stable network parameters which beautifully capture the ligand induced variations in the ensemble in atomistic detail. The conformational populations thus identified by the QC method and verified by network parameters are evaluated for different ligand bound states of the protein pyrrolysyl-tRNA synthetase (DhPylRS) from D. hafniense. The ligand/environment induced re-distribution of protein conformational ensembles forms the basis for understanding several important biological phenomena such as allostery and enzyme catalysis. The atomistic level characterization of each population in the conformational ensemble in terms of the re-orchestrated networks of amino acids is a challenging problem, especially when the changes are minimal at the backbone level. Here we demonstrate that the QC method is sensitive to such subtle changes and is able to cluster MD snapshots which are similar at the side-chain interaction level. Although we have applied these methods on simulation trajectories of a modest time scale (20 ns each), we emphasize that our methodology provides a general approach towards an objective clustering of large-scale MD simulation data and may be applied to probe multistate equilibria at higher time scales, and to problems related to protein folding for any protein or protein-protein/RNA/DNA complex of interest with a known structure.
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Design of protein switches based on an ensemble model of allostery.
Choi, Jay H; Laurent, Abigail H; Hilser, Vincent J; Ostermeier, Marc
2015-04-22
Switchable proteins that can be regulated through exogenous or endogenous inputs have a broad range of biotechnological and biomedical applications. Here we describe the design of switchable enzymes based on an ensemble allosteric model. First, we insert an enzyme domain into an effector-binding domain such that both domains remain functionally intact. Second, we induce the fusion to behave as a switch through the introduction of conditional conformational flexibility designed to increase the conformational entropy of the enzyme domain in a temperature- or pH-dependent fashion. We confirm the switching behaviour in vitro and in vivo. Structural and thermodynamic studies support the hypothesis that switching result from an increase in conformational entropy of the enzyme domain in the absence of effector. These results support the ensemble model of allostery and embody a strategy for the design of protein switches.
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Zheng, Lianqing; Chen, Mengen; Yang, Wei
2009-06-21
To overcome the pseudoergodicity problem, conformational sampling can be accelerated via generalized ensemble methods, e.g., through the realization of random walks along prechosen collective variables, such as spatial order parameters, energy scaling parameters, or even system temperatures or pressures, etc. As usually observed, in generalized ensemble simulations, hidden barriers are likely to exist in the space perpendicular to the collective variable direction and these residual free energy barriers could greatly abolish the sampling efficiency. This sampling issue is particularly severe when the collective variable is defined in a low-dimension subset of the target system; then the "Hamiltonian lagging" problem, which reveals the fact that necessary structural relaxation falls behind the move of the collective variable, may be likely to occur. To overcome this problem in equilibrium conformational sampling, we adopted the orthogonal space random walk (OSRW) strategy, which was originally developed in the context of free energy simulation [L. Zheng, M. Chen, and W. Yang, Proc. Natl. Acad. Sci. U.S.A. 105, 20227 (2008)]. Thereby, generalized ensemble simulations can simultaneously escape both the explicit barriers along the collective variable direction and the hidden barriers that are strongly coupled with the collective variable move. As demonstrated in our model studies, the present OSRW based generalized ensemble treatments show improved sampling capability over the corresponding classical generalized ensemble treatments.
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Moustafa, Ibrahim M; Gohara, David W; Uchida, Akira; Yennawar, Neela; Cameron, Craig E
2015-11-23
The genomes of RNA viruses are relatively small. To overcome the small-size limitation, RNA viruses assign distinct functions to the processed viral proteins and their precursors. This is exemplified by poliovirus 3CD protein. 3C protein is a protease and RNA-binding protein. 3D protein is an RNA-dependent RNA polymerase (RdRp). 3CD exhibits unique protease and RNA-binding activities relative to 3C and is devoid of RdRp activity. The origin of these differences is unclear, since crystal structure of 3CD revealed "beads-on-a-string" structure with no significant structural differences compared to the fully processed proteins. We performed molecular dynamics (MD) simulations on 3CD to investigate its conformational dynamics. A compact conformation of 3CD was observed that was substantially different from that shown crystallographically. This new conformation explained the unique properties of 3CD relative to the individual proteins. Interestingly, simulations of mutant 3CD showed altered interface. Additionally, accelerated MD simulations uncovered a conformational ensemble of 3CD. When we elucidated the 3CD conformations in solution using small-angle X-ray scattering (SAXS) experiments a range of conformations from extended to compact was revealed, validating the MD simulations. The existence of conformational ensemble of 3CD could be viewed as a way to expand the poliovirus proteome, an observation that may extend to other viruses.
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Expected distributions of root-mean-square positional deviations in proteins.
Pitera, Jed W
2014-06-19
The atom positional root-mean-square deviation (RMSD) is a standard tool for comparing the similarity of two molecular structures. It is used to characterize the quality of biomolecular simulations, to cluster conformations, and as a reaction coordinate for conformational changes. This work presents an approximate analytic form for the expected distribution of RMSD values for a protein or polymer fluctuating about a stable native structure. The mean and maximum of the expected distribution are independent of chain length for long chains and linearly proportional to the average atom positional root-mean-square fluctuations (RMSF). To approximate the RMSD distribution for random-coil or unfolded ensembles, numerical distributions of RMSD were generated for ensembles of self-avoiding and non-self-avoiding random walks. In both cases, for all reference structures tested for chains more than three monomers long, the distributions have a maximum distant from the origin with a power-law dependence on chain length. The purely entropic nature of this result implies that care must be taken when interpreting stable high-RMSD regions of the free-energy landscape as "intermediates" or well-defined stable states.
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Perroud, Thomas D.; Bokoch, Michael P.; Zare, Richard N.
2005-01-01
We apply the photon counting histogram (PCH) model, a fluorescence technique with single-molecule sensitivity, to study pH-induced conformational changes of cytochrome c. PCH is able to distinguish different protein conformations based on the brightness of a fluorophore sensitive to its local environment. We label cytochrome c through its single free cysteine with tetramethylrhodamine-5-maleimide (TMR), a fluorophore with specific brightnesses that we associate with specific protein conformations. Ensemble measurements demonstrate two different fluorescence responses with increasing pH: (i) a decrease in fluorescence intensity caused by the alkaline transition of cytochrome c (pH 7.0–9.5), and (ii) an increase in intensity when the protein unfolds (pH 9.5–10.8). The magnitudes of these two responses depend strongly on the molar ratio of TMR used to label cytochrome c. Using PCH we determine that this effect arises from the proportion of a nonfunctional conformation in the sample, which can be differentiated from the functional conformation. We further determine the causes of each ensemble fluorescence response: (i) during the alkaline transition, the fluorophore enters a dark state and discrete conformations are observed, and (ii) as cytochrome c unfolds, the fluorophore incrementally brightens, but discrete conformations are no longer resolved. Moreover, we also show that functional TMR-cytochrome c undergoes a response of identical magnitude regardless of the proportion of nonfunctional protein in the sample. As expected for a technique with single-molecule sensitivity, we demonstrate that PCH can directly observe the most relevant conformation, unlike ensemble fluorometry. PMID:16314563
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NASA Astrophysics Data System (ADS)
Akasaka, Kazuyuki
2010-12-01
NMR experiments at variable pressure reveal a wide range of conformation of a globular protein spanning from within the folded ensemble to the fully unfolded ensemble, herewith collectively called "high-energy conformers". The observation of "high-energy conformers" in a wide variety of globular proteins has led to the "volume theorem": the partial molar volume of a protein decreases with the decrease in its conformational order. Since "high-energy conformers" are intrinsically more reactive than the basic folded conformer, they could play decisive roles in all phenomena of proteins, namely function, environmental adaptation and misfolding. Based on the information on high-energy conformers and the rules on their partial volume in its monomeric state and amyloidosis, one may have a general view on what is happening on proteins under pressure. Moreover, one may even choose a high-energy conformer of a protein with pressure as variable for a particular purpose. Bridging "high-energy conformers" to macroscopic pressure effects could be a key to success in pressure application to biology, medicine, food technology and industry in the near future.
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Dasgupta, Amrita; Udgaonkar, Jayant B; Das, Payel
2014-06-19
The unfolding of the SH3 domain of the PI3 kinase in aqueous urea has been studied using a synergistic experiment-simulation approach. The experimental observation of a transient wet molten globule intermediate, IU, with an unusual non-native burial of the sole Trp residue, W53, provides the benchmark for the unfolding simulations performed (eight in total, each at least 0.5 μs long). The simulations reveal that the partially unfolded IU ensemble is preceded by an early native-like molten globule intermediate ensemble I*. In the very initial stage of unfolding, dry globule conformations with the protein core filled with urea instead of water are transiently observed within the I* ensemble. Water penetration into the urea-filled core of dry globule conformations is frequently accompanied by very transient burial of W53. Later during gradual unfolding, W53 is seen to again become transiently buried in the IU ensemble for a much longer time. In the structurally heterogeneous IU ensemble, conformational flexibility of the C-terminal β-strands enables W53 burial by the formation of non-native, tertiary contacts with hydrophobic residues, which could serve to protect the protein from aggregation during unfolding.
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Conformational Fluctuations in G-Protein-Coupled Receptors
NASA Astrophysics Data System (ADS)
Brown, Michael F.
2014-03-01
G-protein-coupled receptors (GPCRs) comprise almost 50% of pharmaceutical drug targets, where rhodopsin is an important prototype and occurs naturally in a lipid membrane. Rhodopsin photoactivation entails 11-cis to all-trans isomerization of the retinal cofactor, yielding an equilibrium between inactive Meta-I and active Meta-II states. Two important questions are: (1) Is rhodopsin is a simple two-state switch? Or (2) does isomerization of retinal unlock an activated conformational ensemble? For an ensemble-based activation mechanism (EAM) a role for conformational fluctuations is clearly indicated. Solid-state NMR data together with theoretical molecular dynamics (MD) simulations detect increased local mobility of retinal after light activation. Resultant changes in local dynamics of the cofactor initiate large-scale fluctuations of transmembrane helices that expose recognition sites for the signal-transducing G-protein. Time-resolved FTIR studies and electronic spectroscopy further show the conformational ensemble is strongly biased by the membrane lipid composition, as well as pH and osmotic pressure. A new flexible surface model (FSM) describes how the curvature stress field of the membrane governs the energetics of active rhodopsin, due to the spontaneous monolayer curvature of the lipids. Furthermore, influences of osmotic pressure dictate that a large number of bulk water molecules are implicated in rhodopsin activation. Around 60 bulk water molecules activate rhodopsin, which is much larger than the number of structural waters seen in X-ray crystallography, or inferred from studies of bulk hydrostatic pressure. Conformational selection and promoting vibrational motions of rhodopsin lead to activation of the G-protein (transducin). Our biophysical data give a paradigm shift in understanding GPCR activation. The new view is: dynamics and conformational fluctuations involve an ensemble of substates that activate the cognate G-protein in the amplified visual response.
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Jou, Jonathan D; Jain, Swati; Georgiev, Ivelin S; Donald, Bruce R
2016-06-01
Sparse energy functions that ignore long range interactions between residue pairs are frequently used by protein design algorithms to reduce computational cost. Current dynamic programming algorithms that fully exploit the optimal substructure produced by these energy functions only compute the GMEC. This disproportionately favors the sequence of a single, static conformation and overlooks better binding sequences with multiple low-energy conformations. Provable, ensemble-based algorithms such as A* avoid this problem, but A* cannot guarantee better performance than exhaustive enumeration. We propose a novel, provable, dynamic programming algorithm called Branch-Width Minimization* (BWM*) to enumerate a gap-free ensemble of conformations in order of increasing energy. Given a branch-decomposition of branch-width w for an n-residue protein design with at most q discrete side-chain conformations per residue, BWM* returns the sparse GMEC in O([Formula: see text]) time and enumerates each additional conformation in merely O([Formula: see text]) time. We define a new measure, Total Effective Search Space (TESS), which can be computed efficiently a priori before BWM* or A* is run. We ran BWM* on 67 protein design problems and found that TESS discriminated between BWM*-efficient and A*-efficient cases with 100% accuracy. As predicted by TESS and validated experimentally, BWM* outperforms A* in 73% of the cases and computes the full ensemble or a close approximation faster than A*, enumerating each additional conformation in milliseconds. Unlike A*, the performance of BWM* can be predicted in polynomial time before running the algorithm, which gives protein designers the power to choose the most efficient algorithm for their particular design problem.
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NASA Astrophysics Data System (ADS)
Matsunaga, Y.; Sugita, Y.
2018-06-01
A data-driven modeling scheme is proposed for conformational dynamics of biomolecules based on molecular dynamics (MD) simulations and experimental measurements. In this scheme, an initial Markov State Model (MSM) is constructed from MD simulation trajectories, and then, the MSM parameters are refined using experimental measurements through machine learning techniques. The second step can reduce the bias of MD simulation results due to inaccurate force-field parameters. Either time-series trajectories or ensemble-averaged data are available as a training data set in the scheme. Using a coarse-grained model of a dye-labeled polyproline-20, we compare the performance of machine learning estimations from the two types of training data sets. Machine learning from time-series data could provide the equilibrium populations of conformational states as well as their transition probabilities. It estimates hidden conformational states in more robust ways compared to that from ensemble-averaged data although there are limitations in estimating the transition probabilities between minor states. We discuss how to use the machine learning scheme for various experimental measurements including single-molecule time-series trajectories.
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Analysis of the interface variability in NMR structure ensembles of protein-protein complexes.
Calvanese, Luisa; D'Auria, Gabriella; Vangone, Anna; Falcigno, Lucia; Oliva, Romina
2016-06-01
NMR structures consist in ensembles of conformers, all satisfying the experimental restraints, which exhibit a certain degree of structural variability. We analyzed here the interface in NMR ensembles of protein-protein heterodimeric complexes and found it to span a wide range of different conservations. The different exhibited conservations do not simply correlate with the size of the systems/interfaces, and are most probably the result of an interplay between different factors, including the quality of experimental data and the intrinsic complex flexibility. In any case, this information is not to be missed when NMR structures of protein-protein complexes are analyzed; especially considering that, as we also show here, the first NMR conformer is usually not the one which best reflects the overall interface. To quantify the interface conservation and to analyze it, we used an approach originally conceived for the analysis and ranking of ensembles of docking models, which has now been extended to directly deal with NMR ensembles. We propose this approach, based on the conservation of the inter-residue contacts at the interface, both for the analysis of the interface in whole ensembles of NMR complexes and for the possible selection of a single conformer as the best representative of the overall interface. In order to make the analyses automatic and fast, we made the protocol available as a web tool at: https://www.molnac.unisa.it/BioTools/consrank/consrank-nmr.html. Copyright © 2016 Elsevier Inc. All rights reserved.
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Tran, Hoang T.; Pappu, Rohit V.
2006-01-01
Our focus is on an appropriate theoretical framework for describing highly denatured proteins. In high concentrations of denaturants, proteins behave like polymers in a good solvent and ensembles for denatured proteins can be modeled by ignoring all interactions except excluded volume (EV) effects. To assay conformational preferences of highly denatured proteins, we quantify a variety of properties for EV-limit ensembles of 23 two-state proteins. We find that modeled denatured proteins can be best described as follows. Average shapes are consistent with prolate ellipsoids. Ensembles are characterized by large correlated fluctuations. Sequence-specific conformational preferences are restricted to local length scales that span five to nine residues. Beyond local length scales, chain properties follow well-defined power laws that are expected for generic polymers in the EV limit. The average available volume is filled inefficiently, and cavities of all sizes are found within the interiors of denatured proteins. All properties characterized from simulated ensembles match predictions from rigorous field theories. We use our results to resolve between conflicting proposals for structure in ensembles for highly denatured states. PMID:16766618
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Lin, Yao; Ying, Yi-Lun; Gao, Rui; Long, Yi-Tao
2018-03-25
The nanopore can generate an electrochemical confinement for single-molecule sensing that help understand the fundamental chemical principle in nanoscale dimensions. By observing the generated ionic current, individual bond-making and bond-breaking steps, single biomolecule dynamic conformational changes and electron transfer processes that occur within pore can be monitored with high temporal and current resolution. These single-molecule studies in nanopore confinement are revealing information about the fundamental chemical and biological processes that cannot be extracted from ensemble measurements. In this Concept article, we introduce and discuss the electrochemical confinement effects on single-molecule covalent reactions, conformational dynamics of individual molecules and host-guest interactions in protein nanopores. Then, we extend the concept of nanopore confinement effects to confine electrochemical redox reactions in solid-state nanopores for developing new sensing mechanisms. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
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PubChem3D: conformer ensemble accuracy
2013-01-01
Background PubChem is a free and publicly available resource containing substance descriptions and their associated biological activity information. PubChem3D is an extension to PubChem containing computationally-derived three-dimensional (3-D) structures of small molecules. All the tools and services that are a part of PubChem3D rely upon the quality of the 3-D conformer models. Construction of the conformer models currently available in PubChem3D involves a clustering stage to sample the conformational space spanned by the molecule. While this stage allows one to downsize the conformer models to more manageable size, it may result in a loss of the ability to reproduce experimentally determined “bioactive” conformations, for example, found for PDB ligands. This study examines the extent of this accuracy loss and considers its effect on the 3-D similarity analysis of molecules. Results The conformer models consisting of up to 100,000 conformers per compound were generated for 47,123 small molecules whose structures were experimentally determined, and the conformers in each conformer model were clustered to reduce the size of the conformer model to a maximum of 500 conformers per molecule. The accuracy of the conformer models before and after clustering was evaluated using five different measures: root-mean-square distance (RMSD), shape-optimized shape-Tanimoto (STST-opt) and combo-Tanimoto (ComboTST-opt), and color-optimized color-Tanimoto (CTCT-opt) and combo-Tanimoto (ComboTCT-opt). On average, the effect of clustering decreased the conformer model accuracy, increasing the conformer ensemble’s RMSD to the bioactive conformer (by 0.18 ± 0.12 Å), and decreasing the STST-opt, ComboTST-opt, CTCT-opt, and ComboTCT-opt scores (by 0.04 ± 0.03, 0.16 ± 0.09, 0.09 ± 0.05, and 0.15 ± 0.09, respectively). Conclusion This study shows the RMSD accuracy performance of the PubChem3D conformer models is operating as designed. In addition, the effect of PubChem3D sampling on 3-D similarity measures shows that there is a linear degradation of average accuracy with respect to molecular size and flexibility. Generally speaking, one can likely expect the worst-case minimum accuracy of 90% or more of the PubChem3D ensembles to be 0.75, 1.09, 0.43, and 1.13, in terms of STST-opt, ComboTST-opt, CTCT-opt, and ComboTCT-opt, respectively. This expected accuracy improves linearly as the molecule becomes smaller or less flexible. PMID:23289532
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What induces pocket openings on protein surface patches involved in protein-protein interactions?
Eyrisch, Susanne; Helms, Volkhard
2009-02-01
We previously showed for the proteins BCL-X(L), IL-2, and MDM2 that transient pockets at their protein-protein binding interfaces can be identified by applying the PASS algorithm to molecular dynamics (MD) snapshots. We now investigated which aspects of the natural conformational dynamics of proteins induce the formation of such pockets. The pocket detection protocol was applied to three different conformational ensembles for the same proteins that were extracted from MD simulations of the inhibitor bound crystal conformation in water and the free crystal/NMR structure in water and in methanol. Additional MD simulations studied the impact of backbone mobility. The more efficient CONCOORD or normal mode analysis (NMA) techniques gave significantly smaller pockets than MD simulations, whereas tCONCOORD generated pockets comparable to those observed in MD simulations for two of the three systems. Our findings emphasize the influence of solvent polarity and backbone rearrangements on the formation of pockets on protein surfaces and should be helpful in future generation of transient pockets as putative ligand binding sites at protein-protein interfaces.
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What induces pocket openings on protein surface patches involved in protein-protein interactions?
NASA Astrophysics Data System (ADS)
Eyrisch, Susanne; Helms, Volkhard
2009-02-01
We previously showed for the proteins BCL-XL, IL-2, and MDM2 that transient pockets at their protein-protein binding interfaces can be identified by applying the PASS algorithm to molecular dynamics (MD) snapshots. We now investigated which aspects of the natural conformational dynamics of proteins induce the formation of such pockets. The pocket detection protocol was applied to three different conformational ensembles for the same proteins that were extracted from MD simulations of the inhibitor bound crystal conformation in water and the free crystal/NMR structure in water and in methanol. Additional MD simulations studied the impact of backbone mobility. The more efficient CONCOORD or normal mode analysis (NMA) techniques gave significantly smaller pockets than MD simulations, whereas tCONCOORD generated pockets comparable to those observed in MD simulations for two of the three systems. Our findings emphasize the influence of solvent polarity and backbone rearrangements on the formation of pockets on protein surfaces and should be helpful in future generation of transient pockets as putative ligand binding sites at protein-protein interfaces.
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Budday, Dominik; Leyendecker, Sigrid; van den Bedem, Henry
2015-01-01
Proteins operate and interact with partners by dynamically exchanging between functional substates of a conformational ensemble on a rugged free energy landscape. Understanding how these substates are linked by coordinated, collective motions requires exploring a high-dimensional space, which remains a tremendous challenge. While molecular dynamics simulations can provide atomically detailed insight into the dynamics, computational demands to adequately sample conformational ensembles of large biomolecules and their complexes often require tremendous resources. Kinematic models can provide high-level insights into conformational ensembles and molecular rigidity beyond the reach of molecular dynamics by reducing the dimensionality of the search space. Here, we model a protein as a kinematic linkage and present a new geometric method to characterize molecular rigidity from the constraint manifold Q and its tangent space Q at the current configuration q. In contrast to methods based on combinatorial constraint counting, our method is valid for both generic and non-generic, e.g., singular configurations. Importantly, our geometric approach provides an explicit basis for collective motions along floppy modes, resulting in an efficient procedure to probe conformational space. An atomically detailed structural characterization of coordinated, collective motions would allow us to engineer or allosterically modulate biomolecules by selectively stabilizing conformations that enhance or inhibit function with broad implications for human health. PMID:26213417
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NASA Astrophysics Data System (ADS)
Budday, Dominik; Leyendecker, Sigrid; van den Bedem, Henry
2015-10-01
Proteins operate and interact with partners by dynamically exchanging between functional substates of a conformational ensemble on a rugged free energy landscape. Understanding how these substates are linked by coordinated, collective motions requires exploring a high-dimensional space, which remains a tremendous challenge. While molecular dynamics simulations can provide atomically detailed insight into the dynamics, computational demands to adequately sample conformational ensembles of large biomolecules and their complexes often require tremendous resources. Kinematic models can provide high-level insights into conformational ensembles and molecular rigidity beyond the reach of molecular dynamics by reducing the dimensionality of the search space. Here, we model a protein as a kinematic linkage and present a new geometric method to characterize molecular rigidity from the constraint manifold Q and its tangent space Tq Q at the current configuration q. In contrast to methods based on combinatorial constraint counting, our method is valid for both generic and non-generic, e.g., singular configurations. Importantly, our geometric approach provides an explicit basis for collective motions along floppy modes, resulting in an efficient procedure to probe conformational space. An atomically detailed structural characterization of coordinated, collective motions would allow us to engineer or allosterically modulate biomolecules by selectively stabilizing conformations that enhance or inhibit function with broad implications for human health.
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2013-01-01
Background Elucidating the native structure of a protein molecule from its sequence of amino acids, a problem known as de novo structure prediction, is a long standing challenge in computational structural biology. Difficulties in silico arise due to the high dimensionality of the protein conformational space and the ruggedness of the associated energy surface. The issue of multiple minima is a particularly troublesome hallmark of energy surfaces probed with current energy functions. In contrast to the true energy surface, these surfaces are weakly-funneled and rich in comparably deep minima populated by non-native structures. For this reason, many algorithms seek to be inclusive and obtain a broad view of the low-energy regions through an ensemble of low-energy (decoy) conformations. Conformational diversity in this ensemble is key to increasing the likelihood that the native structure has been captured. Methods We propose an evolutionary search approach to address the multiple-minima problem in decoy sampling for de novo structure prediction. Two population-based evolutionary search algorithms are presented that follow the basic approach of treating conformations as individuals in an evolving population. Coarse graining and molecular fragment replacement are used to efficiently obtain protein-like child conformations from parents. Potential energy is used both to bias parent selection and determine which subset of parents and children will be retained in the evolving population. The effect on the decoy ensemble of sampling minima directly is measured by additionally mapping a conformation to its nearest local minimum before considering it for retainment. The resulting memetic algorithm thus evolves not just a population of conformations but a population of local minima. Results and conclusions Results show that both algorithms are effective in terms of sampling conformations in proximity of the known native structure. The additional minimization is shown to be key to enhancing sampling capability and obtaining a diverse ensemble of decoy conformations, circumventing premature convergence to sub-optimal regions in the conformational space, and approaching the native structure with proximity that is comparable to state-of-the-art decoy sampling methods. The results are shown to be robust and valid when using two representative state-of-the-art coarse-grained energy functions. PMID:24565020
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Olson, Mark A
2018-01-22
Intrinsically disordered proteins are characterized by their large manifold of thermally accessible conformations and their related statistical weights, making them an interesting target of simulation studies. To assess the development of a computational framework for modeling this distinct class of proteins, this work examines temperature-based replica-exchange simulations to generate a conformational ensemble of a 28-residue peptide from the Ebola virus protein VP35. Starting from a prefolded helix-β-turn-helix topology observed in a crystallographic assembly, the simulation strategy tested is the recently refined CHARMM36m force field combined with a generalized Born solvent model. A comparison of two replica-exchange methods is provided, where one is a traditional approach with a fixed set of temperatures and the other is an adaptive scheme in which the thermal windows are allowed to move in temperature space. The assessment is further extended to include a comparison with equivalent CHARMM22 simulation data sets. The analysis finds CHARMM36m to shift the minimum in the potential of mean force (PMF) to a lower fractional helicity compared with CHARMM22, while the latter showed greater conformational plasticity along the helix-forming reaction coordinate. Among the simulation models, only the adaptive tempering method with CHARMM36m found an ensemble of conformational heterogeneity consisting of transitions between α-helix-β-hairpin folds and unstructured states that produced a PMF of fractional fold propensity in qualitative agreement with circular dichroism experiments reporting a disordered peptide.
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2013-01-01
The ability to interact with different partners is one of the most important features in proteins. Proteins that bind a large number of partners (hubs) have been often associated with intrinsic disorder. However, many examples exist of hubs with an ordered structure, and evidence of a general mechanism promoting promiscuity in ordered proteins is still elusive. An intriguing hypothesis is that promiscuous binding sites have specific dynamical properties, distinct from the rest of the interface and pre-existing in the protein isolated state. Here, we present the first comprehensive study of the intrinsic dynamics of promiscuous residues in a large protein data set. Different computational methods, from coarse-grained elastic models to geometry-based sampling methods and to full-atom Molecular Dynamics simulations, were used to generate conformational ensembles for the isolated proteins. The flexibility and dynamic correlations of interface residues with a different degree of binding promiscuity were calculated and compared considering side chain and backbone motions, the latter both on a local and on a global scale. The study revealed that (a) promiscuous residues tend to be more flexible than nonpromiscuous ones, (b) this additional flexibility has a higher degree of organization, and (c) evolutionary conservation and binding promiscuity have opposite effects on intrinsic dynamics. Findings on simulated ensembles were also validated on ensembles of experimental structures extracted from the Protein Data Bank (PDB). Additionally, the low occurrence of single nucleotide polymorphisms observed for promiscuous residues indicated a tendency to preserve binding diversity at these positions. A case study on two ubiquitin-like proteins exemplifies how binding promiscuity in evolutionary related proteins can be modulated by the fine-tuning of the interface dynamics. The interplay between promiscuity and flexibility highlighted here can inspire new directions in protein–protein interaction prediction and design methods. PMID:24250278
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Multi-Conformer Ensemble Docking to Difficult Protein Targets
Ellingson, Sally R.; Miao, Yinglong; Baudry, Jerome; ...
2014-09-08
We investigate large-scale ensemble docking using five proteins from the Directory of Useful Decoys (DUD, dud.docking.org) for which docking to crystal structures has proven difficult. Molecular dynamics trajectories are produced for each protein and an ensemble of representative conformational structures extracted from the trajectories. Docking calculations are performed on these selected simulation structures and ensemble-based enrichment factors compared with those obtained using docking in crystal structures of the same protein targets or random selection of compounds. We also found simulation-derived snapshots with improved enrichment factors that increased the chemical diversity of docking hits for four of the five selected proteins.more » A combination of all the docking results obtained from molecular dynamics simulation followed by selection of top-ranking compounds appears to be an effective strategy for increasing the number and diversity of hits when using docking to screen large libraries of chemicals against difficult protein targets.« less
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Jiang, Xukai; Wang, Yuying; Xu, Limei; Chen, Guanjun; Wang, Lushan
2017-09-09
The role of protein dynamics in enzyme catalysis is one of the most active areas in current enzymological research. Here, using endoglucanase Cel5A from Thermobifida fusca (TfCel5A) as a model, we applied molecular dynamics simulations to explore the dynamic behavior of the enzyme upon substrate binding. The collective motions of the active site revealed that the mechanism of TfCel5A substrate binding can likely be described by the conformational-selection model; however, we observed that the conformations of active site residues changed differently along with substrate binding. Although most active site residues retained their native conformational ensemble, some (Tyr163 and Glu355) generated newly induced conformations, whereas others (Phe162 and Tyr189) exhibited shifts in the equilibration of their conformational distributions. These results showed that TfCel5A substrate binding relied on a hybrid mechanism involving induced fit and conformational selection. Interestingly, we found that TfCel5A active site could only partly rebalance its conformational dynamics upon substrate dissociation within the same simulation time, which implies that the conformational rebalance upon substrate dissociation is likely more difficult than the conformational selection upon substrate binding at least in the view of the time required. Our findings offer new insight into enzyme catalysis and potential applications for future protein engineering. Copyright © 2017 Elsevier Inc. All rights reserved.
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Observing the conformation of individual SNARE proteins inside live cells
NASA Astrophysics Data System (ADS)
Weninger, Keith
2010-10-01
Protein conformational dynamics are directly linked to function in many instances. Within living cells, protein dynamics are rarely synchronized so observing ensemble-averaged behaviors can hide details of signaling pathways. Here we present an approach using single molecule fluorescence resonance energy transfer (FRET) to observe the conformation of individual SNARE proteins as they fold to enter the SNARE complex in living cells. Proteins were recombinantly expressed, labeled with small-molecule fluorescent dyes and microinjected for in vivo imaging and tracking using total internal reflection microscopy. Observing single molecules avoids the difficulties of averaging over unsynchronized ensembles. Our approach is easily generalized to a wide variety of proteins in many cellular signaling pathways.
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Bayesian energy landscape tilting: towards concordant models of molecular ensembles.
Beauchamp, Kyle A; Pande, Vijay S; Das, Rhiju
2014-03-18
Predicting biological structure has remained challenging for systems such as disordered proteins that take on myriad conformations. Hybrid simulation/experiment strategies have been undermined by difficulties in evaluating errors from computational model inaccuracies and data uncertainties. Building on recent proposals from maximum entropy theory and nonequilibrium thermodynamics, we address these issues through a Bayesian energy landscape tilting (BELT) scheme for computing Bayesian hyperensembles over conformational ensembles. BELT uses Markov chain Monte Carlo to directly sample maximum-entropy conformational ensembles consistent with a set of input experimental observables. To test this framework, we apply BELT to model trialanine, starting from disagreeing simulations with the force fields ff96, ff99, ff99sbnmr-ildn, CHARMM27, and OPLS-AA. BELT incorporation of limited chemical shift and (3)J measurements gives convergent values of the peptide's α, β, and PPII conformational populations in all cases. As a test of predictive power, all five BELT hyperensembles recover set-aside measurements not used in the fitting and report accurate errors, even when starting from highly inaccurate simulations. BELT's principled framework thus enables practical predictions for complex biomolecular systems from discordant simulations and sparse data. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.
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- CONUS Double Resolution (Lambert Conformal - 40km) NEMS Non-hydrostatic Multiscale Model on the B grid AWIPS grid 212 Regional - CONUS Double Resolution (Lambert Conformal - 40km) NEMS Non-hydrostatic 132 - Double Resolution (Lambert Conformal - 16km) NEMS Non-hydrostatic Multiscale Model on the B grid
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Highly Disordered Amyloid-β Monomer Probed by Single-Molecule FRET and MD Simulation.
Meng, Fanjie; Bellaiche, Mathias M J; Kim, Jae-Yeol; Zerze, Gül H; Best, Robert B; Chung, Hoi Sung
2018-02-27
Monomers of amyloid-β (Aβ) protein are known to be disordered, but there is considerable controversy over the existence of residual or transient conformations that can potentially promote oligomerization and fibril formation. We employed single-molecule Förster resonance energy transfer (FRET) spectroscopy with site-specific dye labeling using an unnatural amino acid and molecular dynamics simulations to investigate conformations and dynamics of Aβ isoforms with 40 (Aβ40) and 42 residues (Aβ42). The FRET efficiency distributions of both proteins measured in phosphate-buffered saline at room temperature show a single peak with very similar FRET efficiencies, indicating there is apparently only one state. 2D FRET efficiency-donor lifetime analysis reveals, however, that there is a broad distribution of rapidly interconverting conformations. Using nanosecond fluorescence correlation spectroscopy, we measured the timescale of the fluctuations between these conformations to be ∼35 ns, similar to that of disordered proteins. These results suggest that both Aβ40 and Aβ42 populate an ensemble of rapidly reconfiguring unfolded states, with no long-lived conformational state distinguishable from that of the disordered ensemble. To gain molecular-level insights into these observations, we performed molecular dynamics simulations with a force field optimized to describe disordered proteins. We find, as in experiments, that both peptides populate configurations consistent with random polymer chains, with the vast majority of conformations lacking significant secondary structure, giving rise to very similar ensemble-averaged FRET efficiencies. Published by Elsevier Inc.
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NASA Astrophysics Data System (ADS)
Qiao, Qin; Zhang, Hou-Dao; Huang, Xuhui
2016-04-01
Simulated tempering (ST) is a widely used enhancing sampling method for Molecular Dynamics simulations. As one expanded ensemble method, ST is a combination of canonical ensembles at different temperatures and the acceptance probability of cross-temperature transitions is determined by both the temperature difference and the weights of each temperature. One popular way to obtain the weights is to adopt the free energy of each canonical ensemble, which achieves uniform sampling among temperature space. However, this uniform distribution in temperature space may not be optimal since high temperatures do not always speed up the conformational transitions of interest, as anti-Arrhenius kinetics are prevalent in protein and RNA folding. Here, we propose a new method: Enhancing Pairwise State-transition Weights (EPSW), to obtain the optimal weights by minimizing the round-trip time for transitions among different metastable states at the temperature of interest in ST. The novelty of the EPSW algorithm lies in explicitly considering the kinetics of conformation transitions when optimizing the weights of different temperatures. We further demonstrate the power of EPSW in three different systems: a simple two-temperature model, a two-dimensional model for protein folding with anti-Arrhenius kinetics, and the alanine dipeptide. The results from these three systems showed that the new algorithm can substantially accelerate the transitions between conformational states of interest in the ST expanded ensemble and further facilitate the convergence of thermodynamics compared to the widely used free energy weights. We anticipate that this algorithm is particularly useful for studying functional conformational changes of biological systems where the initial and final states are often known from structural biology experiments.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Qiao, Qin, E-mail: qqiao@ust.hk; Zhang, Hou-Dao; Huang, Xuhui, E-mail: xuhuihuang@ust.hk
2016-04-21
Simulated tempering (ST) is a widely used enhancing sampling method for Molecular Dynamics simulations. As one expanded ensemble method, ST is a combination of canonical ensembles at different temperatures and the acceptance probability of cross-temperature transitions is determined by both the temperature difference and the weights of each temperature. One popular way to obtain the weights is to adopt the free energy of each canonical ensemble, which achieves uniform sampling among temperature space. However, this uniform distribution in temperature space may not be optimal since high temperatures do not always speed up the conformational transitions of interest, as anti-Arrhenius kineticsmore » are prevalent in protein and RNA folding. Here, we propose a new method: Enhancing Pairwise State-transition Weights (EPSW), to obtain the optimal weights by minimizing the round-trip time for transitions among different metastable states at the temperature of interest in ST. The novelty of the EPSW algorithm lies in explicitly considering the kinetics of conformation transitions when optimizing the weights of different temperatures. We further demonstrate the power of EPSW in three different systems: a simple two-temperature model, a two-dimensional model for protein folding with anti-Arrhenius kinetics, and the alanine dipeptide. The results from these three systems showed that the new algorithm can substantially accelerate the transitions between conformational states of interest in the ST expanded ensemble and further facilitate the convergence of thermodynamics compared to the widely used free energy weights. We anticipate that this algorithm is particularly useful for studying functional conformational changes of biological systems where the initial and final states are often known from structural biology experiments.« less
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El-Turk, Farah; Newby, Francisco N; De Genst, Erwin; Guilliams, Tim; Sprules, Tara; Mittermaier, Anthony; Dobson, Christopher M; Vendruscolo, Michele
2016-06-07
α-Synuclein is an intrinsically disordered protein whose aggregation is associated with Parkinson's disease and other related neurodegenerative disorders. Recently, two single-domain camelid antibodies (nanobodies) were shown to bind α-synuclein with high affinity. Herein, we investigated how these two nanobodies (NbSyn2 and NbSyn87), which are directed to two distinct epitopes within the C-terminal domain of α-synuclein, affect the conformational properties of this protein. Our results suggest that nanobody NbSyn2, which binds to the five C-terminal residues of α-synuclein (residues 136-140), does not disrupt the transient long-range interactions that generate a degree of compaction within the native structural ensemble of α-synuclein. In contrast, the data that we report indicate that NbSyn87, which targets a central region within the C-terminal domain (residues 118-128), has more substantial effects on the fluctuating secondary and tertiary structure of the protein. These results are consistent with the different effects that the two nanobodies have on the aggregation behavior of α-synuclein in vitro. Our findings thus provide new insights into the type of effects that nanobodies can have on the conformational ensemble of α-synuclein.
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Parish, Carol A; Yarger, Matthew; Sinclair, Kent; Dure, Myrianne; Goldberg, Alla
2004-09-23
The conformational flexibility of a series of diastereomeric cyclic urea HIV-1 protease inhibitors has been examined using the Low Mode:Monte Carlo conformational search method. Force fields were validated by a comparison of the energetic ordering of the minimum energy structures on the AMBER/GBSA(water), OPLSAA/GBSA(water) and HF/6-311G/SCRF(water) surfaces. The energetic ordering of the minima on the OPLSAA /GBSA(water) surface was in better agreement with the quantum calculations than the ordering on the AMBER/GBSA(water) surface. An ensemble of low energy structures was generated using OPLSAA/GBSA(water) and used to compare the molecular shape and flexibility of each diastereomer to the experimentally determined binding affinities and crystal structures of closely related systems. The results indicate that diastereomeric solution-phase energetic stability, conformational rigidity and ability to adopt a chair conformation correlate strongly with experimental binding affinities. Rigid body docking suggests that all of the diastereomers adopt solution-phase conformations suitable for alignment with the HIV-1 protease; however, these results indicate that the binding affinities are dependent upon subtle differences in the P1/P1' and P2/P2' substituent orientations.
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Protein-protein structure prediction by scoring molecular dynamics trajectories of putative poses.
Sarti, Edoardo; Gladich, Ivan; Zamuner, Stefano; Correia, Bruno E; Laio, Alessandro
2016-09-01
The prediction of protein-protein interactions and their structural configuration remains a largely unsolved problem. Most of the algorithms aimed at finding the native conformation of a protein complex starting from the structure of its monomers are based on searching the structure corresponding to the global minimum of a suitable scoring function. However, protein complexes are often highly flexible, with mobile side chains and transient contacts due to thermal fluctuations. Flexibility can be neglected if one aims at finding quickly the approximate structure of the native complex, but may play a role in structure refinement, and in discriminating solutions characterized by similar scores. We here benchmark the capability of some state-of-the-art scoring functions (BACH-SixthSense, PIE/PISA and Rosetta) in discriminating finite-temperature ensembles of structures corresponding to the native state and to non-native configurations. We produce the ensembles by running thousands of molecular dynamics simulations in explicit solvent starting from poses generated by rigid docking and optimized in vacuum. We find that while Rosetta outperformed the other two scoring functions in scoring the structures in vacuum, BACH-SixthSense and PIE/PISA perform better in distinguishing near-native ensembles of structures generated by molecular dynamics in explicit solvent. Proteins 2016; 84:1312-1320. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
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Chodera, John D; Shirts, Michael R
2011-11-21
The widespread popularity of replica exchange and expanded ensemble algorithms for simulating complex molecular systems in chemistry and biophysics has generated much interest in discovering new ways to enhance the phase space mixing of these protocols in order to improve sampling of uncorrelated configurations. Here, we demonstrate how both of these classes of algorithms can be considered as special cases of Gibbs sampling within a Markov chain Monte Carlo framework. Gibbs sampling is a well-studied scheme in the field of statistical inference in which different random variables are alternately updated from conditional distributions. While the update of the conformational degrees of freedom by Metropolis Monte Carlo or molecular dynamics unavoidably generates correlated samples, we show how judicious updating of the thermodynamic state indices--corresponding to thermodynamic parameters such as temperature or alchemical coupling variables--can substantially increase mixing while still sampling from the desired distributions. We show how state update methods in common use can lead to suboptimal mixing, and present some simple, inexpensive alternatives that can increase mixing of the overall Markov chain, reducing simulation times necessary to obtain estimates of the desired precision. These improved schemes are demonstrated for several common applications, including an alchemical expanded ensemble simulation, parallel tempering, and multidimensional replica exchange umbrella sampling.
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Black hole evaporation in conformal gravity
NASA Astrophysics Data System (ADS)
Bambi, Cosimo; Modesto, Leonardo; Porey, Shiladitya; Rachwał, Lesław
2017-09-01
We study the formation and the evaporation of a spherically symmetric black hole in conformal gravity. From the collapse of a spherically symmetric thin shell of radiation, we find a singularity-free non-rotating black hole. This black hole has the same Hawking temperature as a Schwarzschild black hole with the same mass, and it completely evaporates either in a finite or in an infinite time, depending on the ensemble. We consider the analysis both in the canonical and in the micro-canonical statistical ensembles. Last, we discuss the corresponding Penrose diagram of this physical process.
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Black hole evaporation in conformal gravity
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bambi, Cosimo; Rachwał, Lesław; Modesto, Leonardo
We study the formation and the evaporation of a spherically symmetric black hole in conformal gravity. From the collapse of a spherically symmetric thin shell of radiation, we find a singularity-free non-rotating black hole. This black hole has the same Hawking temperature as a Schwarzschild black hole with the same mass, and it completely evaporates either in a finite or in an infinite time, depending on the ensemble. We consider the analysis both in the canonical and in the micro-canonical statistical ensembles. Last, we discuss the corresponding Penrose diagram of this physical process.
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Mercadante, Davide; Milles, Sigrid; Fuertes, Gustavo; Svergun, Dmitri I; Lemke, Edward A; Gräter, Frauke
2015-06-25
Understanding the function of intrinsically disordered proteins is intimately related to our capacity to correctly sample their conformational dynamics. So far, a gap between experimentally and computationally derived ensembles exists, as simulations show overcompacted conformers. Increasing evidence suggests that the solvent plays a crucial role in shaping the ensembles of intrinsically disordered proteins and has led to several attempts to modify water parameters and thereby favor protein-water over protein-protein interactions. This study tackles the problem from a different perspective, which is the use of the Kirkwood-Buff theory of solutions to reproduce the correct conformational ensemble of intrinsically disordered proteins (IDPs). A protein force field recently developed on such a basis was found to be highly effective in reproducing ensembles for a fragment from the FG-rich nucleoporin 153, with dimensions matching experimental values obtained from small-angle X-ray scattering and single molecule FRET experiments. Kirkwood-Buff theory presents a complementary and fundamentally different approach to the recently developed four-site TIP4P-D water model, both of which can rescue the overcollapse observed in IDPs with canonical protein force fields. As such, our study provides a new route for tackling the deficiencies of current protein force fields in describing protein solvation.
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NASA Astrophysics Data System (ADS)
Thorne, Robert; Keedy, Daniel; Warkentin, Matthew; Fraser, James; Moreau, David; Atakisi, Hakan; Rau, Peter
Proteins populate complex, temperature-dependent ensembles of conformations that enable their function. Yet in X-ray crystallographic studies, roughly 98% of structures have been determined at 100 K, and most refined to only a single conformation. A combination of experimental methods enabled by studies of ice formation and computational methods for mining low-density features in electron density maps have been applied to determine the evolution of the conformational landscapes of the enzymes cyclophilin A and urease between 300 K and 100 K. Minority conformations of most side chains depopulate on cooling from 300 to ~200 K, below which subsequent conformational evolution is quenched. The characteristic temperatures for this depopulation are highly heterogeneous throughout each enzyme. The temperature-dependent ensemble of the active site flap in urease has also been mapped. These all-atom, site-resolved measurements and analyses rule out one interpretation of the protein-solvent glass transition, and give an alternative interpretation of a dynamical transition identified in site-averaged experiments. They demonstrate a powerful approach to structural characterization of the dynamic underpinnings of protein function. Supported by NSF MCB-1330685.
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Dietschreit, Johannes C B; Diestler, Dennis J; Knapp, Ernst W
2016-05-10
To speed up the generation of an ensemble of poly(ethylene oxide) (PEO) polymer chains in solution, a tetrahedral lattice model possessing the appropriate bond angles is used. The distance between noncovalently bonded atoms is maintained at realistic values by generating chains with an enhanced degree of self-avoidance by a very efficient Monte Carlo (MC) algorithm. Potential energy parameters characterizing this lattice model are adjusted so as to mimic realistic PEO polymer chains in water simulated by molecular dynamics (MD), which serves as a benchmark. The MD data show that PEO chains have a fractal dimension of about two, in contrast to self-avoiding walk lattice models, which exhibit the fractal dimension of 1.7. The potential energy accounts for a mild hydrophobic effect (HYEF) of PEO and for a proper setting of the distribution between trans and gauche conformers. The potential energy parameters are determined by matching the Flory radius, the radius of gyration, and the fraction of trans torsion angles in the chain. A gratifying result is the excellent agreement of the pair distribution function and the angular correlation for the lattice model with the benchmark distribution. The lattice model allows for the precise computation of the torsional entropy of the chain. The generation of polymer conformations of the adjusted lattice model is at least 2 orders of magnitude more efficient than MD simulations of the PEO chain in explicit water. This method of generating chain conformations on a tetrahedral lattice can also be applied to other types of polymers with appropriate adjustment of the potential energy function. The efficient MC algorithm for generating chain conformations on a tetrahedral lattice is available for download at https://github.com/Roulattice/Roulattice .
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Microsecond protein dynamics observed at the single-molecule level
NASA Astrophysics Data System (ADS)
Otosu, Takuhiro; Ishii, Kunihiko; Tahara, Tahei
2015-07-01
How polypeptide chains acquire specific conformations to realize unique biological functions is a central problem of protein science. Single-molecule spectroscopy, combined with fluorescence resonance energy transfer, is utilized to study the conformational heterogeneity and the state-to-state transition dynamics of proteins on the submillisecond to second timescales. However, observation of the dynamics on the microsecond timescale is still very challenging. This timescale is important because the elementary processes of protein dynamics take place and direct comparison between experiment and simulation is possible. Here we report a new single-molecule technique to reveal the microsecond structural dynamics of proteins through correlation of the fluorescence lifetime. This method, two-dimensional fluorescence lifetime correlation spectroscopy, is applied to clarify the conformational dynamics of cytochrome c. Three conformational ensembles and the microsecond transitions in each ensemble are indicated from the correlation signal, demonstrating the importance of quantifying microsecond dynamics of proteins on the folding free energy landscape.
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Microsecond protein dynamics observed at the single-molecule level
Otosu, Takuhiro; Ishii, Kunihiko; Tahara, Tahei
2015-01-01
How polypeptide chains acquire specific conformations to realize unique biological functions is a central problem of protein science. Single-molecule spectroscopy, combined with fluorescence resonance energy transfer, is utilized to study the conformational heterogeneity and the state-to-state transition dynamics of proteins on the submillisecond to second timescales. However, observation of the dynamics on the microsecond timescale is still very challenging. This timescale is important because the elementary processes of protein dynamics take place and direct comparison between experiment and simulation is possible. Here we report a new single-molecule technique to reveal the microsecond structural dynamics of proteins through correlation of the fluorescence lifetime. This method, two-dimensional fluorescence lifetime correlation spectroscopy, is applied to clarify the conformational dynamics of cytochrome c. Three conformational ensembles and the microsecond transitions in each ensemble are indicated from the correlation signal, demonstrating the importance of quantifying microsecond dynamics of proteins on the folding free energy landscape. PMID:26151767
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SQUEEZE-E: The Optimal Solution for Molecular Simulations with Periodic Boundary Conditions.
Wassenaar, Tsjerk A; de Vries, Sjoerd; Bonvin, Alexandre M J J; Bekker, Henk
2012-10-09
In molecular simulations of macromolecules, it is desirable to limit the amount of solvent in the system to avoid spending computational resources on uninteresting solvent-solvent interactions. As a consequence, periodic boundary conditions are commonly used, with a simulation box chosen as small as possible, for a given minimal distance between images. Here, we describe how such a simulation cell can be set up for ensembles, taking into account a priori available or estimable information regarding conformational flexibility. Doing so ensures that any conformation present in the input ensemble will satisfy the distance criterion during the simulation. This helps avoid periodicity artifacts due to conformational changes. The method introduces three new approaches in computational geometry: (1) The first is the derivation of an optimal packing of ensembles, for which the mathematical framework is described. (2) A new method for approximating the α-hull and the contact body for single bodies and ensembles is presented, which is orders of magnitude faster than existing routines, allowing the calculation of packings of large ensembles and/or large bodies. 3. A routine is described for searching a combination of three vectors on a discretized contact body forming a reduced base for a lattice with minimal cell volume. The new algorithms reduce the time required to calculate packings of single bodies from minutes or hours to seconds. The use and efficacy of the method is demonstrated for ensembles obtained from NMR, MD simulations, and elastic network modeling. An implementation of the method has been made available online at http://haddock.chem.uu.nl/services/SQUEEZE/ and has been made available as an option for running simulations through the weNMR GRID MD server at http://haddock.science.uu.nl/enmr/services/GROMACS/main.php .
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Conformational Entropy of Intrinsically Disordered Proteins from Amino Acid Triads
Baruah, Anupaul; Rani, Pooja; Biswas, Parbati
2015-01-01
This work quantitatively characterizes intrinsic disorder in proteins in terms of sequence composition and backbone conformational entropy. Analysis of the normalized relative composition of the amino acid triads highlights a distinct boundary between globular and disordered proteins. The conformational entropy is calculated from the dihedral angles of the middle amino acid in the amino acid triad for the conformational ensemble of the globular, partially and completely disordered proteins relative to the non-redundant database. Both Monte Carlo (MC) and Molecular Dynamics (MD) simulations are used to characterize the conformational ensemble of the representative proteins of each group. The results show that the globular proteins span approximately half of the allowed conformational states in the Ramachandran space, while the amino acid triads in disordered proteins sample the entire range of the allowed dihedral angle space following Flory’s isolated-pair hypothesis. Therefore, only the sequence information in terms of the relative amino acid triad composition may be sufficient to predict protein disorder and the backbone conformational entropy, even in the absence of well-defined structure. The predicted entropies are found to agree with those calculated using mutual information expansion and the histogram method. PMID:26138206
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NASA Astrophysics Data System (ADS)
Pachov, Dimitar V.
Biomolecules are dynamic in nature and visit a number of states while performing their biological function. However, understanding how they interconvert between functional substates is a challenging task. In this thesis, we employ enhanced computational strategies to reveal in atomistic resolution transition states and molecular mechanism along conformational pathways of the signaling protein Nitrogen Regulatory Protein C (NtrC) and the enzyme Adenylate Kinase (Adk). Targeted Molecular Dynamics (TMD) simulations and NMR experiments have previously found the active/inactive interconversion of NtrC is stabilized by non-native transient contacts. To find where along the conformational pathway they lie and probe the existence of multiple intermediates, a beyond 8mus-extensive mapping of the conformational landscape was performed by a multitude of straightforward MD simulations relaxed from the biased TMD pathway. A number of metastable states stabilized by local interactions was found to underline the conformational pathway of NtrC. Two spontaneous transitions of the last stage of the active-to-inactive conversion were identified and used in path sampling procedures to generate an ensemble of truly dynamic reactive pathways. The transition state ensemble (TSE) and mechanistic descriptors of this transition were revealed in atomic detail and verified by committor analysis. By analyzing how pressure affects the dynamics and function of two homologous Adk proteins - the P.Profundum Adk surviving at 700atm pressure in the deep sea, and the E. coli Adk that lives at ambient pressures - we indirectly obtained atomic information about the TSE of the large-amplitude rate-limiting conformational opening of the Adk lids. Guided by NMR experiments showing significantly decreased activation volumes of the piezophile compared to its mesophilic counterpart, TMD simulations revealed the formation of an extended hydrogen-bonded water network in the transition state of the piezophile that can explain the experimentally measured activation volume differences. The transition state of the conformational change was proposed to lie close to the closed state. Additionally, a number of descriptors were used to characterize the free energy landscape of the mesophile. It was found that the features of landscape are highly sensitive to the binding of different ligands, their protonation states and the presence of magnesium.
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Discrete Molecular Dynamics Can Predict Helical Prestructured Motifs in Disordered Proteins
Han, Kyou-Hoon; Dokholyan, Nikolay V.; Tompa, Péter; Kalmár, Lajos; Hegedűs, Tamás
2014-01-01
Intrinsically disordered proteins (IDPs) lack a stable tertiary structure, but their short binding regions termed Pre-Structured Motifs (PreSMo) can form transient secondary structure elements in solution. Although disordered proteins are crucial in many biological processes and designing strategies to modulate their function is highly important, both experimental and computational tools to describe their conformational ensembles and the initial steps of folding are sparse. Here we report that discrete molecular dynamics (DMD) simulations combined with replica exchange (RX) method efficiently samples the conformational space and detects regions populating α-helical conformational states in disordered protein regions. While the available computational methods predict secondary structural propensities in IDPs based on the observation of protein-protein interactions, our ab initio method rests on physical principles of protein folding and dynamics. We show that RX-DMD predicts α-PreSMos with high confidence confirmed by comparison to experimental NMR data. Moreover, the method also can dissect α-PreSMos in close vicinity to each other and indicate helix stability. Importantly, simulations with disordered regions forming helices in X-ray structures of complexes indicate that a preformed helix is frequently the binding element itself, while in other cases it may have a role in initiating the binding process. Our results indicate that RX-DMD provides a breakthrough in the structural and dynamical characterization of disordered proteins by generating the structural ensembles of IDPs even when experimental data are not available. PMID:24763499
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Determination of ensemble-average pairwise root mean-square deviation from experimental B-factors.
Kuzmanic, Antonija; Zagrovic, Bojan
2010-03-03
Root mean-square deviation (RMSD) after roto-translational least-squares fitting is a measure of global structural similarity of macromolecules used commonly. On the other hand, experimental x-ray B-factors are used frequently to study local structural heterogeneity and dynamics in macromolecules by providing direct information about root mean-square fluctuations (RMSF) that can also be calculated from molecular dynamics simulations. We provide a mathematical derivation showing that, given a set of conservative assumptions, a root mean-square ensemble-average of an all-against-all distribution of pairwise RMSD for a single molecular species,
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Determination of Ensemble-Average Pairwise Root Mean-Square Deviation from Experimental B-Factors
Kuzmanic, Antonija; Zagrovic, Bojan
2010-01-01
Abstract Root mean-square deviation (RMSD) after roto-translational least-squares fitting is a measure of global structural similarity of macromolecules used commonly. On the other hand, experimental x-ray B-factors are used frequently to study local structural heterogeneity and dynamics in macromolecules by providing direct information about root mean-square fluctuations (RMSF) that can also be calculated from molecular dynamics simulations. We provide a mathematical derivation showing that, given a set of conservative assumptions, a root mean-square ensemble-average of an all-against-all distribution of pairwise RMSD for a single molecular species,
1/2, is directly related to average B-factors () and 1/2. We show this relationship and explore its limits of validity on a heterogeneous ensemble of structures taken from molecular dynamics simulations of villin headpiece generated using distributed-computing techniques and the Folding@Home cluster. Our results provide a basis for quantifying global structural diversity of macromolecules in crystals directly from x-ray experiments, and we show this on a large set of structures taken from the Protein Data Bank. In particular, we show that the ensemble-average pairwise backbone RMSD for a microscopic ensemble underlying a typical protein x-ray structure is ∼1.1 Å, under the assumption that the principal contribution to experimental B-factors is conformational variability. PMID:20197040 -
Keinan, Shahar; Nocek, Judith M; Hoffman, Brian M; Beratan, David N
2012-10-28
Formation of a transient [myoglobin (Mb), cytochrome b(5) (cyt b(5))] complex is required for the reductive repair of inactive ferri-Mb to its functional ferro-Mb state. The [Mb, cyt b(5)] complex exhibits dynamic docking (DD), with its cyt b(5) partner in rapid exchange at multiple sites on the Mb surface. A triple mutant (Mb(3M)) was designed as part of efforts to shift the electron-transfer process to the simple docking (SD) regime, in which reactive binding occurs at a restricted, reactive region on the Mb surface that dominates the docked ensemble. An electrostatically-guided brownian dynamics (BD) docking protocol was used to generate an initial ensemble of reactive configurations of the complex between unrelaxed partners. This ensemble samples a broad and diverse array of heme-heme distances and orientations. These configurations seeded all-atom constrained molecular dynamics simulations (MD) to generate relaxed complexes for the calculation of electron tunneling matrix elements (T(DA)) through tunneling-pathway analysis. This procedure for generating an ensemble of relaxed complexes combines the ability of BD calculations to sample the large variety of available conformations and interprotein distances, with the ability of MD to generate the atomic level information, especially regarding the structure of water molecules at the protein-protein interface, that defines electron-tunneling pathways. We used the calculated T(DA) values to compute ET rates for the [Mb(wt), cyt b(5)] complex and for the complex with a mutant that has a binding free energy strengthened by three D/E → K charge-reversal mutations, [Mb(3M), cyt b(5)]. The calculated rate constants are in agreement with the measured values, and the mutant complex ensemble has many more geometries with higher T(DA) values than does the wild-type Mb complex. Interestingly, water plays a double role in this electron-transfer system, lowering the tunneling barrier as well as inducing protein interface remodeling that screens the repulsion between the negatively-charged propionates of the two hemes.
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Ensembler: Enabling High-Throughput Molecular Simulations at the Superfamily Scale.
Parton, Daniel L; Grinaway, Patrick B; Hanson, Sonya M; Beauchamp, Kyle A; Chodera, John D
2016-06-01
The rapidly expanding body of available genomic and protein structural data provides a rich resource for understanding protein dynamics with biomolecular simulation. While computational infrastructure has grown rapidly, simulations on an omics scale are not yet widespread, primarily because software infrastructure to enable simulations at this scale has not kept pace. It should now be possible to study protein dynamics across entire (super)families, exploiting both available structural biology data and conformational similarities across homologous proteins. Here, we present a new tool for enabling high-throughput simulation in the genomics era. Ensembler takes any set of sequences-from a single sequence to an entire superfamily-and shepherds them through various stages of modeling and refinement to produce simulation-ready structures. This includes comparative modeling to all relevant PDB structures (which may span multiple conformational states of interest), reconstruction of missing loops, addition of missing atoms, culling of nearly identical structures, assignment of appropriate protonation states, solvation in explicit solvent, and refinement and filtering with molecular simulation to ensure stable simulation. The output of this pipeline is an ensemble of structures ready for subsequent molecular simulations using computer clusters, supercomputers, or distributed computing projects like Folding@home. Ensembler thus automates much of the time-consuming process of preparing protein models suitable for simulation, while allowing scalability up to entire superfamilies. A particular advantage of this approach can be found in the construction of kinetic models of conformational dynamics-such as Markov state models (MSMs)-which benefit from a diverse array of initial configurations that span the accessible conformational states to aid sampling. We demonstrate the power of this approach by constructing models for all catalytic domains in the human tyrosine kinase family, using all available kinase catalytic domain structures from any organism as structural templates. Ensembler is free and open source software licensed under the GNU General Public License (GPL) v2. It is compatible with Linux and OS X. The latest release can be installed via the conda package manager, and the latest source can be downloaded from https://github.com/choderalab/ensembler.
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Accessing protein conformational ensembles using room-temperature X-ray crystallography
Fraser, James S.; van den Bedem, Henry; Samelson, Avi J.; Lang, P. Therese; Holton, James M.; Echols, Nathaniel; Alber, Tom
2011-01-01
Modern protein crystal structures are based nearly exclusively on X-ray data collected at cryogenic temperatures (generally 100 K). The cooling process is thought to introduce little bias in the functional interpretation of structural results, because cryogenic temperatures minimally perturb the overall protein backbone fold. In contrast, here we show that flash cooling biases previously hidden structural ensembles in protein crystals. By analyzing available data for 30 different proteins using new computational tools for electron-density sampling, model refinement, and molecular packing analysis, we found that crystal cryocooling remodels the conformational distributions of more than 35% of side chains and eliminates packing defects necessary for functional motions. In the signaling switch protein, H-Ras, an allosteric network consistent with fluctuations detected in solution by NMR was uncovered in the room-temperature, but not the cryogenic, electron-density maps. These results expose a bias in structural databases toward smaller, overpacked, and unrealistically unique models. Monitoring room-temperature conformational ensembles by X-ray crystallography can reveal motions crucial for catalysis, ligand binding, and allosteric regulation. PMID:21918110
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Single-molecule studies of the Im7 folding landscape.
Pugh, Sara D; Gell, Christopher; Smith, D Alastair; Radford, Sheena E; Brockwell, David J
2010-04-23
Under appropriate conditions, the four-helical Im7 (immunity protein 7) folds from an ensemble of unfolded conformers to a highly compact native state via an on-pathway intermediate. Here, we investigate the unfolded, intermediate, and native states populated during folding using diffusion single-pair fluorescence resonance energy transfer by measuring the efficiency of energy transfer (or proximity or P ratio) between pairs of fluorophores introduced into the side chains of cysteine residues placed in the center of helices 1 and 4, 1 and 3, or 2 and 4. We show that while the native states of each variant give rise to a single narrow distribution with high P values, the distributions of the intermediates trapped at equilibrium (denoted I(eqm)) are fitted by two Gaussian distributions. Modulation of the folding conditions from those that stabilize the intermediate to those that destabilize the intermediate enabled the distribution of lower P value to be assigned to the population of the unfolded ensemble in equilibrium with the intermediate state. The reduced stability of the I(eqm) variants allowed analysis of the effect of denaturant concentration on the compaction and breadth of the unfolded state ensemble to be quantified from 0 to 6 M urea. Significant compaction is observed as the concentration of urea is decreased in both the presence and absence of sodium sulfate, as previously reported for a variety of proteins. In the presence of Na(2)SO(4) in 0 M urea, the P value of the unfolded state ensemble approaches that of the native state. Concurrent with compaction, the ensemble displays increased peak width of P values, possibly reflecting a reduction in the rate of conformational exchange among iso-energetic unfolded, but compact conformations. The results provide new insights into the initial stages of folding of Im7 and suggest that the unfolded state is highly conformationally constrained at the outset of folding. (c) 2010 Elsevier Ltd. All rights reserved.
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Single-Molecule Studies of the Im7 Folding Landscape
Pugh, Sara D.; Gell, Christopher; Smith, D. Alastair; Radford, Sheena E.; Brockwell, David J.
2010-01-01
Under appropriate conditions, the four-helical Im7 (immunity protein 7) folds from an ensemble of unfolded conformers to a highly compact native state via an on-pathway intermediate. Here, we investigate the unfolded, intermediate, and native states populated during folding using diffusion single-pair fluorescence resonance energy transfer by measuring the efficiency of energy transfer (or proximity or P ratio) between pairs of fluorophores introduced into the side chains of cysteine residues placed in the center of helices 1 and 4, 1 and 3, or 2 and 4. We show that while the native states of each variant give rise to a single narrow distribution with high P values, the distributions of the intermediates trapped at equilibrium (denoted Ieqm) are fitted by two Gaussian distributions. Modulation of the folding conditions from those that stabilize the intermediate to those that destabilize the intermediate enabled the distribution of lower P value to be assigned to the population of the unfolded ensemble in equilibrium with the intermediate state. The reduced stability of the Ieqm variants allowed analysis of the effect of denaturant concentration on the compaction and breadth of the unfolded state ensemble to be quantified from 0 to 6 M urea. Significant compaction is observed as the concentration of urea is decreased in both the presence and absence of sodium sulfate, as previously reported for a variety of proteins. In the presence of Na2SO4 in 0 M urea, the P value of the unfolded state ensemble approaches that of the native state. Concurrent with compaction, the ensemble displays increased peak width of P values, possibly reflecting a reduction in the rate of conformational exchange among iso-energetic unfolded, but compact conformations. The results provide new insights into the initial stages of folding of Im7 and suggest that the unfolded state is highly conformationally constrained at the outset of folding. PMID:20211187
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Quantifying Nucleic Acid Ensembles with X-ray Scattering Interferometry.
Shi, Xuesong; Bonilla, Steve; Herschlag, Daniel; Harbury, Pehr
2015-01-01
The conformational ensemble of a macromolecule is the complete description of the macromolecule's solution structures and can reveal important aspects of macromolecular folding, recognition, and function. However, most experimental approaches determine an average or predominant structure, or follow transitions between states that each can only be described by an average structure. Ensembles have been extremely difficult to experimentally characterize. We present the unique advantages and capabilities of a new biophysical technique, X-ray scattering interferometry (XSI), for probing and quantifying structural ensembles. XSI measures the interference of scattered waves from two heavy metal probes attached site specifically to a macromolecule. A Fourier transform of the interference pattern gives the fractional abundance of different probe separations directly representing the multiple conformation states populated by the macromolecule. These probe-probe distance distributions can then be used to define the structural ensemble of the macromolecule. XSI provides accurate, calibrated distance in a model-independent fashion with angstrom scale sensitivity in distances. XSI data can be compared in a straightforward manner to atomic coordinates determined experimentally or predicted by molecular dynamics simulations. We describe the conceptual framework for XSI and provide a detailed protocol for carrying out an XSI experiment. © 2015 Elsevier Inc. All rights reserved.
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Chowdhury, Saikat Dutta; Sarkar, Aditya K; Lahiri, Ansuman
2016-07-25
As part of their basal immune mechanism against insect/herbivore attacks, plants have evolved systemic response mechanisms. Such a systemic wound response in tomato was found to involve an 18 amino acid polypeptide called systemin, the first polypeptide hormone to be discovered in plants. Systematic alanine scanning and deletion studies showed differential modulation in its activity, particularly a major loss of function due to alanine substitution at positions 13 and 17 and less extentive loss of function due to substitution at position 12. We have studied the conformational ensembles of wild-type systemin along with its 17 variants by carrying out a total of 5.76 μs of replica-exchange molecular dynamics simulation in an implicit solvent environment. In our simulations, wild-type systemin showed a lack of α-helical and β-sheet structures, in conformity with earlier circular dichroism and NMR data. On the other hand, two regions containing diproline segments showed a tendency to adopt polyproline II structures. Examination of conformational ensembles of the 17 variants revealed a change in the population distributions, suggesting a less flexible structure for alanine substitutions at positions 12 and 13 but not for position 17. Combined with the experimental observations that positions 1-14 of systemin are important for the formation of the peptide-receptor complex, this leads to the hypothesis that loss of conformational flexibility may play a role in the loss of activity of systemin due to the P12A and P13A substitutions, while T17A deactivation probably occurs for a different reason, most likely the loss of the threonine phosphorylation site. We also indicate possible structural reasons why the substitution of the prolines at positions 12 and 13 leads to a loss of conformational freedom in the peptide.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
van der Graaf, M.; van Mierlo, C.P.M.; Hemminga, M.A.
1991-06-11
The first 25 amino acids of the coat protein of cowpea chlorotic mottle virus are essential for binding the encapsidated RNA. Although an {alpha}-helical conformation has been predicted for this highly positively charged N-terminal region. No experimental evidence for this conformation has been presented so far. In this study, two-dimensional proton NMR experiments were performed on a chemically synthesized pentacosapeptide containing the first 25 amino acids of this coat protein. All resonances could be assigned by a combined use of two-dimensional correlated spectroscopy and nuclear Overhauser enhancement spectroscopy carried out at four different temperatures. Various NMR parameters indicate the presencemore » of a conformational ensemble consisting of helical structures rapidly converting into more extended states. Differences in chemical shifts and nuclear Overhauser effects indicate that lowering the temperature induces a shift of the dynamic equilibrium toward more helical structures. At 10{degrees}C, a perceptible fraction of the conformational ensemble consists of structures with an {alpha}-helical conformation between residues 9 and 17, likely starting with a turnlike structure around Thr9 and Arg10. Both the conformation and the position of this helical region agree well with the secondary structure predictions mentioned above.« less
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Mapping Conformational Dynamics of Proteins Using Torsional Dynamics Simulations
Gangupomu, Vamshi K.; Wagner, Jeffrey R.; Park, In-Hee; Jain, Abhinandan; Vaidehi, Nagarajan
2013-01-01
All-atom molecular dynamics simulations are widely used to study the flexibility of protein conformations. However, enhanced sampling techniques are required for simulating protein dynamics that occur on the millisecond timescale. In this work, we show that torsional molecular dynamics simulations enhance protein conformational sampling by performing conformational search in the low-frequency torsional degrees of freedom. In this article, we use our recently developed torsional-dynamics method called Generalized Newton-Euler Inverse Mass Operator (GNEIMO) to study the conformational dynamics of four proteins. We investigate the use of the GNEIMO method in simulations of the conformationally flexible proteins fasciculin and calmodulin, as well as the less flexible crambin and bovine pancreatic trypsin inhibitor. For the latter two proteins, the GNEIMO simulations with an implicit-solvent model reproduced the average protein structural fluctuations and sample conformations similar to those from Cartesian simulations with explicit solvent. The application of GNEIMO with replica exchange to the study of fasciculin conformational dynamics produced sampling of two of this protein’s experimentally established conformational substates. Conformational transition of calmodulin from the Ca2+-bound to the Ca2+-free conformation occurred readily with GNEIMO simulations. Moreover, the GNEIMO method generated an ensemble of conformations that satisfy about half of both short- and long-range interresidue distances obtained from NMR structures of holo to apo transitions in calmodulin. Although unconstrained all-atom Cartesian simulations have failed to sample transitions between the substates of fasciculin and calmodulin, GNEIMO simulations show the transitions in both systems. The relatively short simulation times required to capture these long-timescale conformational dynamics indicate that GNEIMO is a promising molecular-dynamics technique for studying domain motion in proteins. PMID:23663843
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Mapping conformational dynamics of proteins using torsional dynamics simulations.
Gangupomu, Vamshi K; Wagner, Jeffrey R; Park, In-Hee; Jain, Abhinandan; Vaidehi, Nagarajan
2013-05-07
All-atom molecular dynamics simulations are widely used to study the flexibility of protein conformations. However, enhanced sampling techniques are required for simulating protein dynamics that occur on the millisecond timescale. In this work, we show that torsional molecular dynamics simulations enhance protein conformational sampling by performing conformational search in the low-frequency torsional degrees of freedom. In this article, we use our recently developed torsional-dynamics method called Generalized Newton-Euler Inverse Mass Operator (GNEIMO) to study the conformational dynamics of four proteins. We investigate the use of the GNEIMO method in simulations of the conformationally flexible proteins fasciculin and calmodulin, as well as the less flexible crambin and bovine pancreatic trypsin inhibitor. For the latter two proteins, the GNEIMO simulations with an implicit-solvent model reproduced the average protein structural fluctuations and sample conformations similar to those from Cartesian simulations with explicit solvent. The application of GNEIMO with replica exchange to the study of fasciculin conformational dynamics produced sampling of two of this protein's experimentally established conformational substates. Conformational transition of calmodulin from the Ca(2+)-bound to the Ca(2+)-free conformation occurred readily with GNEIMO simulations. Moreover, the GNEIMO method generated an ensemble of conformations that satisfy about half of both short- and long-range interresidue distances obtained from NMR structures of holo to apo transitions in calmodulin. Although unconstrained all-atom Cartesian simulations have failed to sample transitions between the substates of fasciculin and calmodulin, GNEIMO simulations show the transitions in both systems. The relatively short simulation times required to capture these long-timescale conformational dynamics indicate that GNEIMO is a promising molecular-dynamics technique for studying domain motion in proteins. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.
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Radhakrishnan, Aditya; Vitalis, Andreas; Mao, Albert H.; Steffen, Adam T.; Pappu, Rohit V.
2012-01-01
Poly-L-proline (PLP) polymers are useful mimics of biologically relevant proline-rich sequences. Biophysical and computational studies of PLP polymers in aqueous solutions are challenging because of the diversity of length scales and the slow time scales for conformational conversions. We describe an atomistic simulation approach that combines an improved ABSINTH implicit solvation model, with conformational sampling based on standard and novel Metropolis Monte Carlo moves. Refinements to forcefield parameters were guided by published experimental data for proline-rich systems. We assessed the validity of our simulation results through quantitative comparisons to experimental data that were not used in refining the forcefield parameters. Our analysis shows that PLP polymers form heterogeneous ensembles of conformations characterized by semi-rigid, rod-like segments interrupted by kinks, which result from a combination of internal cis peptide bonds, flexible backbone ψ-angles, and the coupling between ring puckering and backbone degrees of freedom. PMID:22329658
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simulation of the DNA force-extension curve
NASA Astrophysics Data System (ADS)
Shinaberry, Gregory; Mikhaylov, Ivan; Balaeff, Alexander
A molecular dynamics simulation study of the force-extension curve of double-stranded DNA is presented. Extended simulations of the DNA at multiple points along the force-extension curve are conducted with DNA end-to-end length constrained at each point. The calculated force-extension curve qualitatively reproduces the experimental one. The DNA conformational ensemble at each extension shows that the famous plateau of the force-extension curve results from B-DNA melting, whereas the formation of the earlier-predicted novel DNA conformation called 'zip-DNA' takes place at extensions past the plateau. An extensive analysis of the DNA conformational ensemble in terms of base configuration, backbone configuration, solvent interaction energy, etc., is conducted in order to elucidate the physical origin of DNA elasticity and the main interactions responsible for the shape of the force-extension curve.
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NASA Astrophysics Data System (ADS)
Ezerski, Jacob; Cheung, Margaret
CaM forms distinct conformation states through modifications in its charge distribution upon binding to Ca2+ ions. The occurrence of protein structural change resulting from an altered charge distribution is paramount in the scheme of cellular signaling. Not only is charge induced structural change observed in CaM, it is also seen in an essential binding target: calmodulin-depended protein kinase II (CaMKII). In order to investigate the mechanism of selectivity in relation to changes in secondary structure, the CaM binding domain of CaMKII is isolated. Experimentally, charged residues of the CaMKII peptide are systematically mutated to alanine, resulting in altered binding kinetics between the peptide and the Ca2+ saturated state of CaM. We perform an all atom simulation of the wildtype (RRK) and mutated (AAA) CaMKII peptides and generate structures from the trajectory. We analyze RRK and AAA using DSSP and find significant structural differences due to the mutation. Structures from the RRK and AAA ensembles are then selected and docked onto the crystal structure of Ca2+ saturated CaM. We observe that RRK binds to CaM at the C-terminus, whereas the 3-residue mutation, AAA, shows increased patterns of binding to the N-terminus and linker regions of CaM. Due to the conformational change of the peptide ensemble from charged residue mutation, a distinct change in the binding site can be seen, which offers an explanation to experimentally observed changes in kinetic binding rates
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Prediction of conformationally dependent atomic multipole moments in carbohydrates
Cardamone, Salvatore
2015-01-01
The conformational flexibility of carbohydrates is challenging within the field of computational chemistry. This flexibility causes the electron density to change, which leads to fluctuating atomic multipole moments. Quantum Chemical Topology (QCT) allows for the partitioning of an “atom in a molecule,” thus localizing electron density to finite atomic domains, which permits the unambiguous evaluation of atomic multipole moments. By selecting an ensemble of physically realistic conformers of a chemical system, one evaluates the various multipole moments at defined points in configuration space. The subsequent implementation of the machine learning method kriging delivers the evaluation of an analytical function, which smoothly interpolates between these points. This allows for the prediction of atomic multipole moments at new points in conformational space, not trained for but within prediction range. In this work, we demonstrate that the carbohydrates erythrose and threose are amenable to the above methodology. We investigate how kriging models respond when the training ensemble incorporating multiple energy minima and their environment in conformational space. Additionally, we evaluate the gains in predictive capacity of our models as the size of the training ensemble increases. We believe this approach to be entirely novel within the field of carbohydrates. For a modest training set size of 600, more than 90% of the external test configurations have an error in the total (predicted) electrostatic energy (relative to ab initio) of maximum 1 kJ mol−1 for open chains and just over 90% an error of maximum 4 kJ mol−1 for rings. © 2015 Wiley Periodicals, Inc. PMID:26547500
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Prediction of conformationally dependent atomic multipole moments in carbohydrates.
Cardamone, Salvatore; Popelier, Paul L A
2015-12-15
The conformational flexibility of carbohydrates is challenging within the field of computational chemistry. This flexibility causes the electron density to change, which leads to fluctuating atomic multipole moments. Quantum Chemical Topology (QCT) allows for the partitioning of an "atom in a molecule," thus localizing electron density to finite atomic domains, which permits the unambiguous evaluation of atomic multipole moments. By selecting an ensemble of physically realistic conformers of a chemical system, one evaluates the various multipole moments at defined points in configuration space. The subsequent implementation of the machine learning method kriging delivers the evaluation of an analytical function, which smoothly interpolates between these points. This allows for the prediction of atomic multipole moments at new points in conformational space, not trained for but within prediction range. In this work, we demonstrate that the carbohydrates erythrose and threose are amenable to the above methodology. We investigate how kriging models respond when the training ensemble incorporating multiple energy minima and their environment in conformational space. Additionally, we evaluate the gains in predictive capacity of our models as the size of the training ensemble increases. We believe this approach to be entirely novel within the field of carbohydrates. For a modest training set size of 600, more than 90% of the external test configurations have an error in the total (predicted) electrostatic energy (relative to ab initio) of maximum 1 kJ mol(-1) for open chains and just over 90% an error of maximum 4 kJ mol(-1) for rings. © 2015 Wiley Periodicals, Inc.
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NASA Astrophysics Data System (ADS)
Zhang, Chuan-Biao; Ming, Li; Xin, Zhou
2015-12-01
Ensemble simulations, which use multiple short independent trajectories from dispersive initial conformations, rather than a single long trajectory as used in traditional simulations, are expected to sample complex systems such as biomolecules much more efficiently. The re-weighted ensemble dynamics (RED) is designed to combine these short trajectories to reconstruct the global equilibrium distribution. In the RED, a number of conformational functions, named as basis functions, are applied to relate these trajectories to each other, then a detailed-balance-based linear equation is built, whose solution provides the weights of these trajectories in equilibrium distribution. Thus, the sufficient and efficient selection of basis functions is critical to the practical application of RED. Here, we review and present a few possible ways to generally construct basis functions for applying the RED in complex molecular systems. Especially, for systems with less priori knowledge, we could generally use the root mean squared deviation (RMSD) among conformations to split the whole conformational space into a set of cells, then use the RMSD-based-cell functions as basis functions. We demonstrate the application of the RED in typical systems, including a two-dimensional toy model, the lattice Potts model, and a short peptide system. The results indicate that the RED with the constructions of basis functions not only more efficiently sample the complex systems, but also provide a general way to understand the metastable structure of conformational space. Project supported by the National Natural Science Foundation of China (Grant No. 11175250).
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NASA Astrophysics Data System (ADS)
Verkhivker, Gennady M.; Rejto, Paul A.; Bouzida, Djamal; Arthurs, Sandra; Colson, Anthony B.; Freer, Stephan T.; Gehlhaar, Daniel K.; Larson, Veda; Luty, Brock A.; Marrone, Tami; Rose, Peter W.
2001-03-01
Thermodynamic and kinetic aspects of ligand-protein binding are studied for the methotrexate-dihydrofolate reductase system from the binding free energy profile constructed as a function of the order parameter. Thermodynamic stability of the native complex and a cooperative transition to the unique native structure suggest the nucleation kinetic mechanism at the equilibrium transition temperature. Structural properties of the transition state ensemble and the ensemble of nucleation conformations are determined by kinetic simulations of the transmission coefficient and ligand-protein association pathways. Structural analysis of the transition states and the nucleation conformations reconciles different views on the nucleation mechanism in protein folding.
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Baxa, Michael C.; Haddadian, Esmael J.; Jumper, John M.; Freed, Karl F.; Sosnick, Tobin R.
2014-01-01
The loss of conformational entropy is a major contribution in the thermodynamics of protein folding. However, accurate determination of the quantity has proven challenging. We calculate this loss using molecular dynamic simulations of both the native protein and a realistic denatured state ensemble. For ubiquitin, the total change in entropy is TΔSTotal = 1.4 kcal⋅mol−1 per residue at 300 K with only 20% from the loss of side-chain entropy. Our analysis exhibits mixed agreement with prior studies because of the use of more accurate ensembles and contributions from correlated motions. Buried side chains lose only a factor of 1.4 in the number of conformations available per rotamer upon folding (ΩU/ΩN). The entropy loss for helical and sheet residues differs due to the smaller motions of helical residues (TΔShelix−sheet = 0.5 kcal⋅mol−1), a property not fully reflected in the amide N-H and carbonyl C=O bond NMR order parameters. The results have implications for the thermodynamics of folding and binding, including estimates of solvent ordering and microscopic entropies obtained from NMR. PMID:25313044
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Svensson, Fredrik; Aniceto, Natalia; Norinder, Ulf; Cortes-Ciriano, Isidro; Spjuth, Ola; Carlsson, Lars; Bender, Andreas
2018-05-29
Making predictions with an associated confidence is highly desirable as it facilitates decision making and resource prioritization. Conformal regression is a machine learning framework that allows the user to define the required confidence and delivers predictions that are guaranteed to be correct to the selected extent. In this study, we apply conformal regression to model molecular properties and bioactivity values and investigate different ways to scale the resultant prediction intervals to create as efficient (i.e., narrow) regressors as possible. Different algorithms to estimate the prediction uncertainty were used to normalize the prediction ranges, and the different approaches were evaluated on 29 publicly available data sets. Our results show that the most efficient conformal regressors are obtained when using the natural exponential of the ensemble standard deviation from the underlying random forest to scale the prediction intervals, but other approaches were almost as efficient. This approach afforded an average prediction range of 1.65 pIC50 units at the 80% confidence level when applied to bioactivity modeling. The choice of nonconformity function has a pronounced impact on the average prediction range with a difference of close to one log unit in bioactivity between the tightest and widest prediction range. Overall, conformal regression is a robust approach to generate bioactivity predictions with associated confidence.
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Dynamic Conformations of Nucleosome Arrays in Solution from Small-Angle X-ray Scattering
NASA Astrophysics Data System (ADS)
Howell, Steven C.
Chromatin conformation and dynamics remains unsolved despite the critical role of the chromatin in fundamental genetic functions such as transcription, replication, and repair. At the molecular level, chromatin can be viewed as a linear array of nucleosomes, each consisting of 147 base pairs (bp) of double-stranded DNA (dsDNA) wrapped around a protein core and connected by 10 to 90 bp of linker dsDNA. Using small-angle X-ray scattering (SAXS), we investigated how the conformations of model nucleosome arrays in solution are modulated by ionic condition as well as the effect of linker histone proteins. To facilitate ensemble modeling of these SAXS measurements, we developed a simulation method that treats coarse-grained DNA as a Markov chain, then explores possible DNA conformations using Metropolis Monte Carlo (MC) sampling. This algorithm extends the functionality of SASSIE, a program used to model intrinsically disordered biological molecules, adding to the previous methods for simulating protein, carbohydrates, and single-stranded DNA. Our SAXS measurements of various nucleosome arrays together with the MC generated models provide valuable solution structure information identifying specific differences from the structure of crystallized arrays.
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Developing hybrid approaches to predict pKa values of ionizable groups
Witham, Shawn; Talley, Kemper; Wang, Lin; Zhang, Zhe; Sarkar, Subhra; Gao, Daquan; Yang, Wei
2011-01-01
Accurate predictions of pKa values of titratable groups require taking into account all relevant processes associated with the ionization/deionization. Frequently, however, the ionization does not involve significant structural changes and the dominating effects are purely electrostatic in origin allowing accurate predictions to be made based on the electrostatic energy difference between ionized and neutral forms alone using a static structure. On another hand, if the change of the charge state is accompanied by a structural reorganization of the target protein, then the relevant conformational changes have to be taken into account in the pKa calculations. Here we report a hybrid approach that first predicts the titratable groups, which ionization is expected to cause conformational changes, termed “problematic” residues, then applies a special protocol on them, while the rest of the pKa’s are predicted with rigid backbone approach as implemented in multi-conformation continuum electrostatics (MCCE) method. The backbone representative conformations for “problematic” groups are generated with either molecular dynamics simulations with charged and uncharged amino acid or with ab-initio local segment modeling. The corresponding ensembles are then used to calculate the pKa of the “problematic” residues and then the results are averaged. PMID:21744395
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Sparse networks of directly coupled, polymorphic, and functional side chains in allosteric proteins.
Soltan Ghoraie, Laleh; Burkowski, Forbes; Zhu, Mu
2015-03-01
Recent studies have highlighted the role of coupled side-chain fluctuations alone in the allosteric behavior of proteins. Moreover, examination of X-ray crystallography data has recently revealed new information about the prevalence of alternate side-chain conformations (conformational polymorphism), and attempts have been made to uncover the hidden alternate conformations from X-ray data. Hence, new computational approaches are required that consider the polymorphic nature of the side chains, and incorporate the effects of this phenomenon in the study of information transmission and functional interactions of residues in a molecule. These studies can provide a more accurate understanding of the allosteric behavior. In this article, we first present a novel approach to generate an ensemble of conformations and an efficient computational method to extract direct couplings of side chains in allosteric proteins, and provide sparse network representations of the couplings. We take the side-chain conformational polymorphism into account, and show that by studying the intrinsic dynamics of an inactive structure, we are able to construct a network of functionally crucial residues. Second, we show that the proposed method is capable of providing a magnified view of the coupled and conformationally polymorphic residues. This model reveals couplings between the alternate conformations of a coupled residue pair. To the best of our knowledge, this is the first computational method for extracting networks of side chains' alternate conformations. Such networks help in providing a detailed image of side-chain dynamics in functionally important and conformationally polymorphic sites, such as binding and/or allosteric sites. © 2014 Wiley Periodicals, Inc.
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NASA Astrophysics Data System (ADS)
Mo, Yuxiang; Lei, Jiangtao; Sun, Yunxiang; Zhang, Qingwen; Wei, Guanghong
2016-09-01
Small oligomers formed early along human islet amyloid polypeptide (hIAPP) aggregation is responsible for the cell death in Type II diabetes. The epigallocatechin gallate (EGCG), a green tea extract, was found to inhibit hIAPP fibrillation. However, the inhibition mechanism and the conformational distribution of the smallest hIAPP oligomer - dimer are mostly unknown. Herein, we performed extensive replica exchange molecular dynamic simulations on hIAPP dimer with and without EGCG molecules. Extended hIAPP dimer conformations, with a collision cross section value similar to that observed by ion mobility-mass spectrometry, were observed in our simulations. Notably, these dimers adopt a three-stranded antiparallel β-sheet and contain the previously reported β-hairpin amyloidogenic precursor. We find that EGCG binding strongly blocks both the inter-peptide hydrophobic and aromatic-stacking interactions responsible for inter-peptide β-sheet formation and intra-peptide interaction crucial for β-hairpin formation, thus abolishes the three-stranded β-sheet structures and leads to the formation of coil-rich conformations. Hydrophobic, aromatic-stacking, cation-π and hydrogen-bonding interactions jointly contribute to the EGCG-induced conformational shift. This study provides, on atomic level, the conformational ensemble of hIAPP dimer and the molecular mechanism by which EGCG inhibits hIAPP aggregation.
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Yokom, Adam L; Morishima, Yoshihiro; Lau, Miranda; Su, Min; Glukhova, Alisa; Osawa, Yoichi; Southworth, Daniel R
2014-06-13
Nitric-oxide synthase (NOS) is required in mammals to generate NO for regulating blood pressure, synaptic response, and immune defense. NOS is a large homodimer with well characterized reductase and oxygenase domains that coordinate a multistep, interdomain electron transfer mechanism to oxidize l-arginine and generate NO. Ca(2+)-calmodulin (CaM) binds between the reductase and oxygenase domains to activate NO synthesis. Although NOS has long been proposed to adopt distinct conformations that alternate between interflavin and FMN-heme electron transfer steps, structures of the holoenzyme have remained elusive and the CaM-bound arrangement is unknown. Here we have applied single particle electron microscopy (EM) methods to characterize the full-length of the neuronal isoform (nNOS) complex and determine the structural mechanism of CaM activation. We have identified that nNOS adopts an ensemble of open and closed conformational states and that CaM binding induces a dramatic rearrangement of the reductase domain. Our three-dimensional reconstruction of the intact nNOS-CaM complex reveals a closed conformation and a cross-monomer arrangement with the FMN domain rotated away from the NADPH-FAD center, toward the oxygenase dimer. This work captures, for the first time, the reductase-oxygenase structural arrangement and the CaM-dependent release of the FMN domain that coordinates to drive electron transfer across the domains during catalysis. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.
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NASA Astrophysics Data System (ADS)
Santos-Filho, Osvaldo Andrade; Hopfinger, Anton J.
2001-01-01
A set of 18 structurally diverse antifolates including pyrimethamine, cycloguanil, methotrexate, aminopterin and trimethoprim, and 13 pyrrolo[2,3-d]pyrimidines were studied using four-dimensional quantitative structure-activity relationship (4D-QSAR) analysis. The corresponding biological activities of these compounds include IC50 inhibition constants for both the wild type, and a specific mutant type of Plasmodium falciparum dihydrofolate reductase (DHFR). Two thousand conformations of each analog were sampled to generate a conformational ensemble profile (CEP) from a molecular dynamics simulation (MDS) of 100,000 conformer trajectory states. Each sampled conformation was placed in a 1 Å cubic grid cell lattice for each of five trial alignments. The frequency of occupation of each grid cell was computed for each of six types of pharmacophore groups of atoms of each compound. These grid cell occupancy descriptors (GCODs) were then used as a descriptor pool to construct 4D-QSAR models. Models for inhibition of both the `wild' type and the mutant enzyme were generated which provide detailed spatial pharmacophore requirements for inhibition in terms of atom types and their corresponding relative locations in space. The 4D-QSAR models indicate some structural features perhaps relevant to the mechanism of resistance of the Plasmodium falciparum DHFR to current antimalarials. One feature identified is a slightly different binding alignment of the ligands to the mutant form of the enzyme as compared to the wild type.
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Estrada, T; Zhang, B; Cicotti, P; Armen, R S; Taufer, M
2012-07-01
We present a scalable and accurate method for classifying protein-ligand binding geometries in molecular docking. Our method is a three-step process: the first step encodes the geometry of a three-dimensional (3D) ligand conformation into a single 3D point in the space; the second step builds an octree by assigning an octant identifier to every single point in the space under consideration; and the third step performs an octree-based clustering on the reduced conformation space and identifies the most dense octant. We adapt our method for MapReduce and implement it in Hadoop. The load-balancing, fault-tolerance, and scalability in MapReduce allow screening of very large conformation spaces not approachable with traditional clustering methods. We analyze results for docking trials for 23 protein-ligand complexes for HIV protease, 21 protein-ligand complexes for Trypsin, and 12 protein-ligand complexes for P38alpha kinase. We also analyze cross docking trials for 24 ligands, each docking into 24 protein conformations of the HIV protease, and receptor ensemble docking trials for 24 ligands, each docking in a pool of HIV protease receptors. Our method demonstrates significant improvement over energy-only scoring for the accurate identification of native ligand geometries in all these docking assessments. The advantages of our clustering approach make it attractive for complex applications in real-world drug design efforts. We demonstrate that our method is particularly useful for clustering docking results using a minimal ensemble of representative protein conformational states (receptor ensemble docking), which is now a common strategy to address protein flexibility in molecular docking. Copyright © 2012 Elsevier Ltd. All rights reserved.
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Haspel, Nurit; Geisbrecht, Brian V; Lambris, John; Kavraki, Lydia
2010-03-01
We present a novel multi-level methodology to explore and characterize the low energy landscape and the thermodynamics of proteins. Traditional conformational search methods typically explore only a small portion of the conformational space of proteins and are hard to apply to large proteins due to the large amount of calculations required. In our multi-scale approach, we first provide an initial characterization of the equilibrium state ensemble of a protein using an efficient computational conformational sampling method. We then enrich the obtained ensemble by performing short Molecular Dynamics (MD) simulations on selected conformations from the ensembles as starting points. To facilitate the analysis of the results, we project the resulting conformations on a low-dimensional landscape to efficiently focus on important interactions and examine low energy regions. This methodology provides a more extensive sampling of the low energy landscape than an MD simulation starting from a single crystal structure as it explores multiple trajectories of the protein. This enables us to obtain a broader view of the dynamics of proteins and it can help in understanding complex binding, improving docking results and more. In this work, we apply the methodology to provide an extensive characterization of the bound complexes of the C3d fragment of human Complement component C3 and one of its powerful bacterial inhibitors, the inhibitory domain of Staphylococcus aureus extra-cellular fibrinogen-binding domain (Efb-C) and two of its mutants. We characterize several important interactions along the binding interface and define low free energy regions in the three complexes. Proteins 2010. (c) 2009 Wiley-Liss, Inc.
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Kinetic rate constant prediction supports the conformational selection mechanism of protein binding.
Moal, Iain H; Bates, Paul A
2012-01-01
The prediction of protein-protein kinetic rate constants provides a fundamental test of our understanding of molecular recognition, and will play an important role in the modeling of complex biological systems. In this paper, a feature selection and regression algorithm is applied to mine a large set of molecular descriptors and construct simple models for association and dissociation rate constants using empirical data. Using separate test data for validation, the predicted rate constants can be combined to calculate binding affinity with accuracy matching that of state of the art empirical free energy functions. The models show that the rate of association is linearly related to the proportion of unbound proteins in the bound conformational ensemble relative to the unbound conformational ensemble, indicating that the binding partners must adopt a geometry near to that of the bound prior to binding. Mirroring the conformational selection and population shift mechanism of protein binding, the models provide a strong separate line of evidence for the preponderance of this mechanism in protein-protein binding, complementing structural and theoretical studies.
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Transition-State Ensembles Navigate the Pathways of Enzyme Catalysis.
Mickert, Matthias J; Gorris, Hans H
2018-06-07
Transition-state theory (TST) provides an important framework for analyzing and explaining the reaction rates of enzymes. TST, however, needs to account for protein dynamic effects and heterogeneities in enzyme catalysis. We have analyzed the reaction rates of β-galactosidase and β-glucuronidase at the single molecule level by using large arrays of femtoliter-sized chambers. Heterogeneities in individual reaction rates yield information on the intrinsic distribution of the free energy of activation (Δ G ‡ ) in an enzyme ensemble. The broader distribution of Δ G ‡ in β-galactosidase compared to β-glucuronidase is attributed to β-galactosidase's multiple catalytic functions as a hydrolase and a transglycosylase. Based on the catalytic mechanism of β-galactosidase, we show that transition-state ensembles do not only contribute to enzyme catalysis but can also channel the catalytic pathway to the formation of different products. We conclude that β-galactosidase is an example of natural evolution, where a new catalytic pathway branches off from an established enzyme function. The functional division of work between enzymatic substates explains why the conformational space represented by the enzyme ensemble is larger than the conformational space that can be sampled by any given enzyme molecule during catalysis.
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Helmholtz and Gibbs ensembles, thermodynamic limit and bistability in polymer lattice models
NASA Astrophysics Data System (ADS)
Giordano, Stefano
2017-12-01
Representing polymers by random walks on a lattice is a fruitful approach largely exploited to study configurational statistics of polymer chains and to develop efficient Monte Carlo algorithms. Nevertheless, the stretching and the folding/unfolding of polymer chains within the Gibbs (isotensional) and the Helmholtz (isometric) ensembles of the statistical mechanics have not been yet thoroughly analysed by means of the lattice methodology. This topic, motivated by the recent introduction of several single-molecule force spectroscopy techniques, is investigated in the present paper. In particular, we analyse the force-extension curves under the Gibbs and Helmholtz conditions and we give a proof of the ensembles equivalence in the thermodynamic limit for polymers represented by a standard random walk on a lattice. Then, we generalize these concepts for lattice polymers that can undergo conformational transitions or, equivalently, for chains composed of bistable or two-state elements (that can be either folded or unfolded). In this case, the isotensional condition leads to a plateau-like force-extension response, whereas the isometric condition causes a sawtooth-like force-extension curve, as predicted by numerous experiments. The equivalence of the ensembles is finally proved also for lattice polymer systems exhibiting conformational transitions.
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Effects of Catalytic Action and Ligand Binding on Conformational Ensembles of Adenylate Kinase.
Onuk, Emre; Badger, John; Wang, Yu Jing; Bardhan, Jaydeep; Chishti, Yasmin; Akcakaya, Murat; Brooks, Dana H; Erdogmus, Deniz; Minh, David D L; Makowski, Lee
2017-08-29
Crystal structures of adenylate kinase (AdK) from Escherichia coli capture two states: an "open" conformation (apo) obtained in the absence of ligands and a "closed" conformation in which ligands are bound. Other AdK crystal structures suggest intermediate conformations that may lie on the transition pathway between these two states. To characterize the transition from open to closed states in solution, X-ray solution scattering data were collected from AdK in the apo form and with progressively increasing concentrations of five different ligands. Scattering data from apo AdK are consistent with scattering predicted from the crystal structure of AdK in the open conformation. In contrast, data from AdK samples saturated with Ap5A do not agree with that calculated from AdK in the closed conformation. Using cluster analysis of available structures, we selected representative structures in five conformational states: open, partially open, intermediate, partially closed, and closed. We used these structures to estimate the relative abundances of these states for each experimental condition. X-ray solution scattering data obtained from AdK with AMP are dominated by scattering from AdK in the open conformation. For AdK in the presence of high concentrations of ATP and ADP, the conformational ensemble shifts to a mixture of partially open and closed states. Even when AdK is saturated with Ap5A, a significant proportion of AdK remains in a partially open conformation. These results are consistent with an induced-fit model in which the transition of AdK from an open state to a closed state is initiated by ATP binding.
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Molecular dynamics simulations using temperature-enhanced essential dynamics replica exchange.
Kubitzki, Marcus B; de Groot, Bert L
2007-06-15
Today's standard molecular dynamics simulations of moderately sized biomolecular systems at full atomic resolution are typically limited to the nanosecond timescale and therefore suffer from limited conformational sampling. Efficient ensemble-preserving algorithms like replica exchange (REX) may alleviate this problem somewhat but are still computationally prohibitive due to the large number of degrees of freedom involved. Aiming at increased sampling efficiency, we present a novel simulation method combining the ideas of essential dynamics and REX. Unlike standard REX, in each replica only a selection of essential collective modes of a subsystem of interest (essential subspace) is coupled to a higher temperature, with the remainder of the system staying at a reference temperature, T(0). This selective excitation along with the replica framework permits efficient approximate ensemble-preserving conformational sampling and allows much larger temperature differences between replicas, thereby considerably enhancing sampling efficiency. Ensemble properties and sampling performance of the method are discussed using dialanine and guanylin test systems, with multi-microsecond molecular dynamics simulations of these test systems serving as references.
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Remarks on thermalization in 2D CFT
NASA Astrophysics Data System (ADS)
de Boer, Jan; Engelhardt, Dalit
2016-12-01
We revisit certain aspects of thermalization in 2D conformal field theory (CFT). In particular, we consider similarities and differences between the time dependence of correlation functions in various states in rational and non-rational CFTs. We also consider the distinction between global and local thermalization and explain how states obtained by acting with a diffeomorphism on the ground state can appear locally thermal, and we review why the time-dependent expectation value of the energy-momentum tensor is generally a poor diagnostic of global thermalization. Since all 2D CFTs have an infinite set of commuting conserved charges, generic initial states might be expected to give rise to a generalized Gibbs ensemble rather than a pure thermal ensemble at late times. We construct the holographic dual of the generalized Gibbs ensemble and show that, to leading order, it is still described by a Banados-Teitelboim-Zanelli black hole. The extra conserved charges, while rendering c <1 theories essentially integrable, therefore seem to have little effect on large-c conformal field theories.
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Conformation switching of AIM2 PYD domain revealed by NMR relaxation and MD simulation.
Wang, Haobo; Yang, Lijiang; Niu, Xiaogang
2016-04-29
Protein absent in melanoma 2 (AIM2) is a double-strand DNA (ds DNA) sensor mainly located in cytoplasm of cell. It includes one N terminal PYD domain and one C terminal HIN domain. When the ds DNA such as DNA viruses and bacteria entered cytoplasm, the HIN domain of AIM2 will recognize and bind to DNA, and the PYD domain will bind to ASC protein which will result in the formation of AIM2 inflammasome. Three AIM2 PYD domain structures have been solved, but every structure yields a unique conformation around the α3 helix region. To understand why different AIM2 PYD structures show different conformations in this region, we use NMR relaxation techniques to study the backbone dynamics of mouse AIM2 PYD domain and perform molecular dynamics (MD) simulations on both mouse and human AIM2 PYD structures. Our results indicate that this region is highly flexible in both mouse and human AIM2 PYD domains, and the PYD domain may exist as a conformation ensemble in solution. Different environment makes the population vary among pre-existing conformational substrates of the ensemble, which may be the reason why different AIM2 PYD structures were observed under different conditions. Further docking analysis reveals that the conformation switching may be important for the autoinhibition of the AIM2 protein. Copyright © 2016 Elsevier Inc. All rights reserved.
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NASA Astrophysics Data System (ADS)
Toal, Siobhan; Schweitzer-Stenner, Reinhard; Rybka, Karin; Schwalbe, Hardol
2013-03-01
In order to enable structural predictions of intrinsically disordered proteins (IDPs) the intrinsic conformational propensities of amino acids must be complimented by information on nearest-neighbor interactions. To explore the influence of nearest-neighbors on conformational distributions, we preformed a joint vibrational (Infrared, Vibrational Circular Dichroism (VCD), polarized Raman) and 2D-NMR study of selected GxyG host-guest peptides: GDyG, GSyG, GxLG, GxVG, where x/y ={A,K,LV}. D and S (L and V) were chosen at the x (y) position due to their observance to drastically change the distribution of alanine in xAy tripeptide sequences in truncated coil libraries. The conformationally sensitive amide' profiles of the respective spectra were analyzed in terms of a statistical ensemble described as a superposition of 2D-Gaussian functions in Ramachandran space representing sub-ensembles of pPII-, β-strand-, helical-, and turn-like conformations. Our analysis and simulation of the amide I' band profiles exploits excitonic coupling between the local amide I' vibrational modes in the tetra-peptides. The resulting distributions reveal that D and S, which themselves have high propensities for turn-structures, strongly affect the conformational distribution of their downstream neighbor. Taken together, our results indicate that Dx and Sx motifs might act as conformational randomizers in proteins, attenuating intrinsic propensities of neighboring residues. Overall, our results show that nearest neighbor interactions contribute significantly to the Gibbs energy landscape of disordered peptides and proteins.
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Kasahara, Kota; Ma, Benson; Goto, Kota; Dasgupta, Bhaskar; Higo, Junichi; Fukuda, Ikuo; Mashimo, Tadaaki; Akiyama, Yutaka; Nakamura, Haruki
2016-01-01
Molecular dynamics (MD) is a promising computational approach to investigate dynamical behavior of molecular systems at the atomic level. Here, we present a new MD simulation engine named "myPresto/omegagene" that is tailored for enhanced conformational sampling methods with a non-Ewald electrostatic potential scheme. Our enhanced conformational sampling methods, e.g. , the virtual-system-coupled multi-canonical MD (V-McMD) method, replace a multi-process parallelized run with multiple independent runs to avoid inter-node communication overhead. In addition, adopting the non-Ewald-based zero-multipole summation method (ZMM) makes it possible to eliminate the Fourier space calculations altogether. The combination of these state-of-the-art techniques realizes efficient and accurate calculations of the conformational ensemble at an equilibrium state. By taking these advantages, myPresto/omegagene is specialized for the single process execution with Graphics Processing Unit (GPU). We performed benchmark simulations for the 20-mer peptide, Trp-cage, with explicit solvent. One of the most thermodynamically stable conformations generated by the V-McMD simulation is very similar to an experimentally solved native conformation. Furthermore, the computation speed is four-times faster than that of our previous simulation engine, myPresto/psygene-G. The new simulator, myPresto/omegagene, is freely available at the following URLs: http://www.protein.osaka-u.ac.jp/rcsfp/pi/omegagene/ and http://presto.protein.osaka-u.ac.jp/myPresto4/.
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Ashford, Paul; Moss, David S; Alex, Alexander; Yeap, Siew K; Povia, Alice; Nobeli, Irene; Williams, Mark A
2012-03-14
Protein structures provide a valuable resource for rational drug design. For a protein with no known ligand, computational tools can predict surface pockets that are of suitable size and shape to accommodate a complementary small-molecule drug. However, pocket prediction against single static structures may miss features of pockets that arise from proteins' dynamic behaviour. In particular, ligand-binding conformations can be observed as transiently populated states of the apo protein, so it is possible to gain insight into ligand-bound forms by considering conformational variation in apo proteins. This variation can be explored by considering sets of related structures: computationally generated conformers, solution NMR ensembles, multiple crystal structures, homologues or homology models. It is non-trivial to compare pockets, either from different programs or across sets of structures. For a single structure, difficulties arise in defining particular pocket's boundaries. For a set of conformationally distinct structures the challenge is how to make reasonable comparisons between them given that a perfect structural alignment is not possible. We have developed a computational method, Provar, that provides a consistent representation of predicted binding pockets across sets of related protein structures. The outputs are probabilities that each atom or residue of the protein borders a predicted pocket. These probabilities can be readily visualised on a protein using existing molecular graphics software. We show how Provar simplifies comparison of the outputs of different pocket prediction algorithms, of pockets across multiple simulated conformations and between homologous structures. We demonstrate the benefits of use of multiple structures for protein-ligand and protein-protein interface analysis on a set of complexes and consider three case studies in detail: i) analysis of a kinase superfamily highlights the conserved occurrence of surface pockets at the active and regulatory sites; ii) a simulated ensemble of unliganded Bcl2 structures reveals extensions of a known ligand-binding pocket not apparent in the apo crystal structure; iii) visualisations of interleukin-2 and its homologues highlight conserved pockets at the known receptor interfaces and regions whose conformation is known to change on inhibitor binding. Through post-processing of the output of a variety of pocket prediction software, Provar provides a flexible approach to the analysis and visualization of the persistence or variability of pockets in sets of related protein structures.
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Typical event horizons in AdS/CFT
NASA Astrophysics Data System (ADS)
Avery, Steven G.; Lowe, David A.
2016-01-01
We consider the construction of local bulk operators in a black hole background dual to a pure state in conformal field theory. The properties of these operators in a microcanonical ensemble are studied. It has been argued in the literature that typical states in such an ensemble contain firewalls, or otherwise singular horizons. We argue this conclusion can be avoided with a proper definition of the interior operators.
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Peters, Jan H; de Groot, Bert L
2012-01-01
Protein-protein interactions play an important role in all biological processes. However, the principles underlying these interactions are only beginning to be understood. Ubiquitin is a small signalling protein that is covalently attached to different proteins to mark them for degradation, regulate transport and other functions. As such, it interacts with and is recognised by a multitude of other proteins. We have conducted molecular dynamics simulations of ubiquitin in complex with 11 different binding partners on a microsecond timescale and compared them with ensembles of unbound ubiquitin to investigate the principles of their interaction and determine the influence of complex formation on the dynamic properties of this protein. Along the main mode of fluctuation of ubiquitin, binding in most cases reduces the conformational space available to ubiquitin to a subspace of that covered by unbound ubiquitin. This behaviour can be well explained using the model of conformational selection. For lower amplitude collective modes, a spectrum of zero to almost complete coverage of bound by unbound ensembles was observed. The significant differences between bound and unbound structures are exclusively situated at the binding interface. Overall, the findings correspond neither to a complete conformational selection nor induced fit scenario. Instead, we introduce a model of conformational restriction, extension and shift, which describes the full range of observed effects.
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Differential Enzyme Flexibility Probed Using Solid-State Nanopores.
Hu, Rui; Rodrigues, João V; Waduge, Pradeep; Yamazaki, Hirohito; Cressiot, Benjamin; Chishti, Yasmin; Makowski, Lee; Yu, Dapeng; Shakhnovich, Eugene; Zhao, Qing; Wanunu, Meni
2018-05-22
Enzymes and motor proteins are dynamic macromolecules that coexist in a number of conformations of similar energies. Protein function is usually accompanied by a change in structure and flexibility, often induced upon binding to ligands. However, while measuring protein flexibility changes between active and resting states is of therapeutic significance, it remains a challenge. Recently, our group has demonstrated that breadth of signal amplitudes in measured electrical signatures as an ensemble of individual protein molecules is driven through solid-state nanopores and correlates with protein conformational dynamics. Here, we extend our study to resolve subtle flexibility variation in dihydrofolate reductase mutants from unlabeled single molecules in solution. We first demonstrate using a canonical protein system, adenylate kinase, that both size and flexibility changes can be observed upon binding to a substrate that locks the protein in a closed conformation. Next, we investigate the influence of voltage bias and pore geometry on the measured electrical pulse statistics during protein transport. Finally, using the optimal experimental conditions, we systematically study a series of wild-type and mutant dihydrofolate reductase proteins, finding a good correlation between nanopore-measured protein conformational dynamics and equilibrium bulk fluorescence probe measurements. Our results unequivocally demonstrate that nanopore-based measurements reliably probe conformational diversity in native protein ensembles.
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Infinitely dilute partial molar properties of proteins from computer simulation.
Ploetz, Elizabeth A; Smith, Paul E
2014-11-13
A detailed understanding of temperature and pressure effects on an infinitely dilute protein's conformational equilibrium requires knowledge of the corresponding infinitely dilute partial molar properties. Established molecular dynamics methodologies generally have not provided a way to calculate these properties without either a loss of thermodynamic rigor, the introduction of nonunique parameters, or a loss of information about which solute conformations specifically contributed to the output values. Here we implement a simple method that is thermodynamically rigorous and possesses none of the above disadvantages, and we report on the method's feasibility and computational demands. We calculate infinitely dilute partial molar properties for two proteins and attempt to distinguish the thermodynamic differences between a native and a denatured conformation of a designed miniprotein. We conclude that simple ensemble average properties can be calculated with very reasonable amounts of computational power. In contrast, properties corresponding to fluctuating quantities are computationally demanding to calculate precisely, although they can be obtained more easily by following the temperature and/or pressure dependence of the corresponding ensemble averages.
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Vincenzi, Marian; Costantini, Susan; Scala, Stefania; Tesauro, Diego; Accardo, Antonella; Leone, Marilisa; Colonna, Giovanni; Guillon, Jean; Portella, Luigi; Trotta, Anna Maria; Ronga, Luisa; Rossi, Filomena
2015-01-01
This work reports on the design and the synthesis of two short linear peptides both containing a few amino acids with disorder propensity and an allylic ester group at the C-terminal end. Their structural properties were firstly analyzed by means of experimental techniques in solution such as CD and NMR methods that highlighted peptide flexibility. These results were further confirmed by MD simulations that demonstrated the ability of the peptides to assume conformational ensembles. They revealed a network of transient and dynamic H-bonds and interactions with water molecules. Binding assays with a well-known drug-target, i.e., the CXCR4 receptor, were also carried out in an attempt to verify their biological function and the possibility to use the assays to develop new specific targets for CXCR4. Moreover, our data indicate that these peptides represent useful tools for molecular recognition processes in which a flexible conformation is required in order to obtain an interaction with a specific target. PMID:26030674
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Action-FRET of a Gaseous Protein
NASA Astrophysics Data System (ADS)
Daly, Steven; Knight, Geoffrey; Halim, Mohamed Abdul; Kulesza, Alexander; Choi, Chang Min; Chirot, Fabien; MacAleese, Luke; Antoine, Rodolphe; Dugourd, Philippe
2017-01-01
Mass spectrometry is an extremely powerful technique for analysis of biological molecules, in particular proteins. One aspect that has been contentious is how much native solution-phase structure is preserved upon transposition to the gas phase by soft ionization methods such as electrospray ionization. To address this question—and thus further develop mass spectrometry as a tool for structural biology—structure-sensitive techniques must be developed to probe the gas-phase conformations of proteins. Here, we report Förster resonance energy transfer (FRET) measurements on a ubiquitin mutant using specific photofragmentation as a reporter of the FRET efficiency. The FRET data is interpreted in the context of circular dichroism, molecular dynamics simulation, and ion mobility data. Both the dependence of the FRET efficiency on the charge state—where a systematic decrease is observed—and on methanol concentration are considered. In the latter case, a decrease in FRET efficiency with methanol concentration is taken as evidence that the conformational ensemble of gaseous protein cations retains a memory of the solution phase conformational ensemble upon electrospray ionization.
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Differences in β-strand Populations of Monomeric Aβ40 and Aβ42
Ball, K. Aurelia; Phillips, Aaron H.; Wemmer, David E.; Head-Gordon, Teresa
2013-01-01
Using homonuclear 1H NOESY spectra, with chemical shifts, 3JHNHα scalar couplings, residual dipolar couplings, and 1H-15N NOEs, we have optimized and validated the conformational ensembles of the amyloid-β 1–40 (Aβ40) and amyloid-β 1–42 (Aβ42) peptides generated by molecular dynamics simulations. We find that both peptides have a diverse set of secondary structure elements including turns, helices, and antiparallel and parallel β-strands. The most significant difference in the structural ensembles of the two peptides is the type of β-hairpins and β-strands they populate. We find that Aβ42 forms a major antiparallel β-hairpin involving the central hydrophobic cluster residues (16–21) with residues 29–36, compatible with known amyloid fibril forming regions, whereas Aβ40 forms an alternative but less populated antiparallel β-hairpin between the central hydrophobic cluster and residues 9–13, that sometimes forms a β-sheet by association with residues 35–37. Furthermore, we show that the two additional C-terminal residues of Aβ42, in particular Ile-41, directly control the differences in the β-strand content found between the Aβ40 and Aβ42 structural ensembles. Integrating the experimental and theoretical evidence accumulated over the last decade, it is now possible to present monomeric structural ensembles of Aβ40 and Aβ42 consistent with available information that produce a plausible molecular basis for why Aβ42 exhibits greater fibrillization rates than Aβ40. PMID:23790380
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Producing genome structure populations with the dynamic and automated PGS software.
Hua, Nan; Tjong, Harianto; Shin, Hanjun; Gong, Ke; Zhou, Xianghong Jasmine; Alber, Frank
2018-05-01
Chromosome conformation capture technologies such as Hi-C are widely used to investigate the spatial organization of genomes. Because genome structures can vary considerably between individual cells of a population, interpreting ensemble-averaged Hi-C data can be challenging, in particular for long-range and interchromosomal interactions. We pioneered a probabilistic approach for the generation of a population of distinct diploid 3D genome structures consistent with all the chromatin-chromatin interaction probabilities from Hi-C experiments. Each structure in the population is a physical model of the genome in 3D. Analysis of these models yields new insights into the causes and the functional properties of the genome's organization in space and time. We provide a user-friendly software package, called PGS, which runs on local machines (for practice runs) and high-performance computing platforms. PGS takes a genome-wide Hi-C contact frequency matrix, along with information about genome segmentation, and produces an ensemble of 3D genome structures entirely consistent with the input. The software automatically generates an analysis report, and provides tools to extract and analyze the 3D coordinates of specific domains. Basic Linux command-line knowledge is sufficient for using this software. A typical running time of the pipeline is ∼3 d with 300 cores on a computer cluster to generate a population of 1,000 diploid genome structures at topological-associated domain (TAD)-level resolution.
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Interaction of dihydrofolate reductase with methotrexate: Ensemble and single-molecule kinetics
NASA Astrophysics Data System (ADS)
Rajagopalan, P. T. Ravi; Zhang, Zhiquan; McCourt, Lynn; Dwyer, Mary; Benkovic, Stephen J.; Hammes, Gordon G.
2002-10-01
The thermodynamics and kinetics of the interaction of dihydrofolate reductase (DHFR) with methotrexate have been studied by using fluorescence, stopped-flow, and single-molecule methods. DHFR was modified to permit the covalent addition of a fluorescent molecule, Alexa 488, and a biotin at the N terminus of the molecule. The fluorescent molecule was placed on a protein loop that closes over methotrexate when binding occurs, thus causing a quenching of the fluorescence. The biotin was used to attach the enzyme in an active form to a glass surface for single-molecule studies. The equilibrium dissociation constant for the binding of methotrexate to the enzyme is 9.5 nM. The stopped-flow studies revealed that methotrexate binds to two different conformations of the enzyme, and the association and dissociation rate constants were determined. The single-molecule investigation revealed a conformational change in the enzyme-methotrexate complex that was not observed in the stopped-flow studies. The ensemble averaged rate constants for this conformation change in both directions is about 2-4 s1 and is attributed to the opening and closing of the enzyme loop over the bound methotrexate. Thus the mechanism of methotrexate binding to DHFR involves multiple steps and protein conformational changes.
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Combining Rosetta with molecular dynamics (MD): A benchmark of the MD-based ensemble protein design.
Ludwiczak, Jan; Jarmula, Adam; Dunin-Horkawicz, Stanislaw
2018-07-01
Computational protein design is a set of procedures for computing amino acid sequences that will fold into a specified structure. Rosetta Design, a commonly used software for protein design, allows for the effective identification of sequences compatible with a given backbone structure, while molecular dynamics (MD) simulations can thoroughly sample near-native conformations. We benchmarked a procedure in which Rosetta design is started on MD-derived structural ensembles and showed that such a combined approach generates 20-30% more diverse sequences than currently available methods with only a slight increase in computation time. Importantly, the increase in diversity is achieved without a loss in the quality of the designed sequences assessed by their resemblance to natural sequences. We demonstrate that the MD-based procedure is also applicable to de novo design tasks started from backbone structures without any sequence information. In addition, we implemented a protocol that can be used to assess the stability of designed models and to select the best candidates for experimental validation. In sum our results demonstrate that the MD ensemble-based flexible backbone design can be a viable method for protein design, especially for tasks that require a large pool of diverse sequences. Copyright © 2018 Elsevier Inc. All rights reserved.
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Typical event horizons in AdS/CFT
Avery, Steven G.; Lowe, David A.
2016-01-14
We consider the construction of local bulk operators in a black hole background dual to a pure state in conformal field theory. The properties of these operators in a microcanonical ensemble are studied. It has been argued in the literature that typical states in such an ensemble contain firewalls, or otherwise singular horizons. Here, we argue this conclusion can be avoided with a proper definition of the interior operators.
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Calculating ensemble averaged descriptions of protein rigidity without sampling.
González, Luis C; Wang, Hui; Livesay, Dennis R; Jacobs, Donald J
2012-01-01
Previous works have demonstrated that protein rigidity is related to thermodynamic stability, especially under conditions that favor formation of native structure. Mechanical network rigidity properties of a single conformation are efficiently calculated using the integer body-bar Pebble Game (PG) algorithm. However, thermodynamic properties require averaging over many samples from the ensemble of accessible conformations to accurately account for fluctuations in network topology. We have developed a mean field Virtual Pebble Game (VPG) that represents the ensemble of networks by a single effective network. That is, all possible number of distance constraints (or bars) that can form between a pair of rigid bodies is replaced by the average number. The resulting effective network is viewed as having weighted edges, where the weight of an edge quantifies its capacity to absorb degrees of freedom. The VPG is interpreted as a flow problem on this effective network, which eliminates the need to sample. Across a nonredundant dataset of 272 protein structures, we apply the VPG to proteins for the first time. Our results show numerically and visually that the rigidity characterizations of the VPG accurately reflect the ensemble averaged [Formula: see text] properties. This result positions the VPG as an efficient alternative to understand the mechanical role that chemical interactions play in maintaining protein stability.
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Elucidation of Ligand-Dependent Modulation of Disorder-Order Transitions in the Oncoprotein MDM2.
Bueren-Calabuig, Juan A; Michel, Julien
2015-06-01
Numerous biomolecular interactions involve unstructured protein regions, but how to exploit such interactions to enhance the affinity of a lead molecule in the context of rational drug design remains uncertain. Here clarification was sought for cases where interactions of different ligands with the same disordered protein region yield qualitatively different results. Specifically, conformational ensembles for the disordered lid region of the N-terminal domain of the oncoprotein MDM2 in the presence of different ligands were computed by means of a novel combination of accelerated molecular dynamics, umbrella sampling, and variational free energy profile methodologies. The resulting conformational ensembles for MDM2, free and bound to p53 TAD (17-29) peptide identify lid states compatible with previous NMR measurements. Remarkably, the MDM2 lid region is shown to adopt distinct conformational states in the presence of different small-molecule ligands. Detailed analyses of small-molecule bound ensembles reveal that the ca. 25-fold affinity improvement of the piperidinone family of inhibitors for MDM2 constructs that include the full lid correlates with interactions between ligand hydrophobic groups and the C-terminal lid region that is already partially ordered in apo MDM2. By contrast, Nutlin or benzodiazepinedione inhibitors, that bind with similar affinity to full lid and lid-truncated MDM2 constructs, interact additionally through their solubilizing groups with N-terminal lid residues that are more disordered in apo MDM2.
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Tran, Hai L; Lexa, Katrina W; Julien, Olivier; Young, Travis S; Walsh, Christopher T; Jacobson, Matthew P; Wells, James A
2017-02-22
Macrocycles are appealing drug candidates due to their high affinity, specificity, and favorable pharmacological properties. In this study, we explored the effects of chemical modifications to a natural product macrocycle upon its activity, 3D geometry, and conformational entropy. We chose thiocillin as a model system, a thiopeptide in the ribosomally encoded family of natural products that exhibits potent antimicrobial effects against Gram-positive bacteria. Since thiocillin is derived from a genetically encoded peptide scaffold, site-directed mutagenesis allows for rapid generation of analogues. To understand thiocillin's structure-activity relationship, we generated a site-saturation mutagenesis library covering each position along thiocillin's macrocyclic ring. We report the identification of eight unique compounds more potent than wild-type thiocillin, the best having an 8-fold improvement in potency. Computational modeling of thiocillin's macrocyclic structure revealed a striking requirement for a low-entropy macrocycle for activity. The populated ensembles of the active mutants showed a rigid structure with few adoptable conformations while inactive mutants showed a more flexible macrocycle which is unfavorable for binding. This finding highlights the importance of macrocyclization in combination with rigidifying post-translational modifications to achieve high-potency binding.
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Yamaguchi, Takumi; Sakae, Yoshitake; Zhang, Ying; Yamamoto, Sayoko; Okamoto, Yuko; Kato, Koichi
2014-10-06
Exploration of the conformational spaces of flexible biomacromolecules is essential for quantitatively understanding the energetics of their molecular recognition processes. We employed stable isotope- and lanthanide-assisted NMR approaches in conjunction with replica-exchange molecular dynamics (REMD) simulations to obtain atomic descriptions of the conformational dynamics of high-mannose-type oligosaccharides, which harbor intracellular glycoprotein-fate determinants in their triantennary structures. The experimentally validated REMD simulation provided quantitative views of the dynamic conformational ensembles of the complicated, branched oligosaccharides, and indicated significant expansion of the conformational space upon removal of a terminal mannose residue during the functional glycan-processing pathway. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Order–Disorder Transitions Govern Kinetic Cooperativity and Allostery of Monomeric Human Glucokinase
Bruschweiler-Li, Lei; Miller, Brian G.; Brüschweiler, Rafael
2012-01-01
Glucokinase (GCK) catalyzes the rate-limiting step of glucose catabolism in the pancreas, where it functions as the body's principal glucose sensor. GCK dysfunction leads to several potentially fatal diseases including maturity–onset diabetes of the young type II (MODY-II) and persistent hypoglycemic hyperinsulinemia of infancy (PHHI). GCK maintains glucose homeostasis by displaying a sigmoidal kinetic response to increasing blood glucose levels. This positive cooperativity is unique because the enzyme functions exclusively as a monomer and possesses only a single glucose binding site. Despite nearly a half century of research, the mechanistic basis for GCK's homotropic allostery remains unresolved. Here we explain GCK cooperativity in terms of large-scale, glucose-mediated disorder–order transitions using 17 isotopically labeled isoleucine methyl groups and three tryptophan side chains as sensitive nuclear magnetic resonance (NMR) probes. We find that the small domain of unliganded GCK is intrinsically disordered and samples a broad conformational ensemble. We also demonstrate that small-molecule diabetes therapeutic agents and hyperinsulinemia-associated GCK mutations share a strikingly similar activation mechanism, characterized by a population shift toward a more narrow, well-ordered ensemble resembling the glucose-bound conformation. Our results support a model in which GCK generates its cooperative kinetic response at low glucose concentrations by using a millisecond disorder–order cycle of the small domain as a “time-delay loop,” which is bypassed at high glucose concentrations, providing a unique mechanism to allosterically regulate the activity of human GCK under physiological conditions. PMID:23271955
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Harkness, Robert W; Mittermaier, Anthony K
2017-11-01
G-quadruplexes (GQs) are four-stranded nucleic acid secondary structures formed by guanosine (G)-rich DNA and RNA sequences. It is becoming increasingly clear that cellular processes including gene expression and mRNA translation are regulated by GQs. GQ structures have been extensively characterized, however little attention to date has been paid to their conformational dynamics, despite the fact that many biological GQ sequences populate multiple structures of similar free energies, leading to an ensemble of exchanging conformations. The impact of these dynamics on biological function is currently not well understood. Recently, structural dynamics have been demonstrated to entropically stabilize GQ ensembles, potentially modulating gene expression. Transient, low-populated states in GQ ensembles may additionally regulate nucleic acid interactions and function. This review will underscore the interplay of GQ dynamics and biological function, focusing on several dynamic processes for biological GQs and the characterization of GQ dynamics by nuclear magnetic resonance (NMR) spectroscopy in conjunction with other biophysical techniques. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman. Copyright © 2017 Elsevier B.V. All rights reserved.
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Rosenzweig, Rina; Sekhar, Ashok; Nagesh, Jayashree; Kay, Lewis E
2017-01-01
The Hsp70 chaperone system is integrated into a myriad of biochemical processes that are critical for cellular proteostasis. Although detailed pictures of Hsp70 bound with peptides have emerged, correspondingly detailed structural information on complexes with folding-competent substrates remains lacking. Here we report a methyl-TROSY based solution NMR study showing that the Escherichia coli version of Hsp70, DnaK, binds to as many as four distinct sites on a small 53-residue client protein, hTRF1. A fraction of hTRF1 chains are also bound to two DnaK molecules simultaneously, resulting in a mixture of DnaK-substrate sub-ensembles that are structurally heterogeneous. The interactions of Hsp70 with a client protein at different sites results in a fuzzy chaperone-substrate ensemble and suggests a mechanism for Hsp70 function whereby the structural heterogeneity of released substrate molecules enables them to circumvent kinetic traps in their conformational free energy landscape and fold efficiently to the native state. DOI: http://dx.doi.org/10.7554/eLife.28030.001 PMID:28708484
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Capturing Three-Dimensional Genome Organization in Individual Cells by Single-Cell Hi-C.
Nagano, Takashi; Wingett, Steven W; Fraser, Peter
2017-01-01
Hi-C is a powerful method to investigate genome-wide, higher-order chromatin and chromosome conformations averaged from a population of cells. To expand the potential of Hi-C for single-cell analysis, we developed single-cell Hi-C. Similar to the existing "ensemble" Hi-C method, single-cell Hi-C detects proximity-dependent ligation events between cross-linked and restriction-digested chromatin fragments in cells. A major difference between the single-cell Hi-C and ensemble Hi-C protocol is that the proximity-dependent ligation is carried out in the nucleus. This allows the isolation of individual cells in which nearly the entire Hi-C procedure has been carried out, enabling the production of a Hi-C library and data from individual cells. With this new method, we studied genome conformations and found evidence for conserved topological domain organization from cell to cell, but highly variable interdomain contacts and chromosome folding genome wide. In addition, we found that the single-cell Hi-C protocol provided cleaner results with less technical noise suggesting it could be used to improve the ensemble Hi-C technique.
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Rosen, Laura E.; Connell, Katelyn B.; Marqusee, Susan
2014-01-01
The molten globule, a conformational ensemble with significant secondary structure but only loosely packed tertiary structure, has been suggested to be a ubiquitous intermediate in protein folding. However, it is difficult to assess the tertiary packing of transiently populated species to evaluate this hypothesis. Escherichia coli RNase H is known to populate an intermediate before the rate-limiting barrier to folding that has long been thought to be a molten globule. We investigated this hypothesis by making mimics of the intermediate that are the ground-state conformation at equilibrium, using two approaches: a truncation to generate a fragment mimic of the intermediate, and selective destabilization of the native state using point mutations. Spectroscopic characterization and the response of the mimics to further mutation are consistent with studies on the transient kinetic intermediate, indicating that they model the early intermediate. Both mimics fold cooperatively and exhibit NMR spectra indicative of a closely packed conformation, in contrast to the hypothesis of molten tertiary packing. This result is important for understanding the nature of the subsequent rate-limiting barrier to folding and has implications for the assumption that many other proteins populate molten globule folding intermediates. PMID:25258414
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Rosen, Laura E; Connell, Katelyn B; Marqusee, Susan
2014-10-14
The molten globule, a conformational ensemble with significant secondary structure but only loosely packed tertiary structure, has been suggested to be a ubiquitous intermediate in protein folding. However, it is difficult to assess the tertiary packing of transiently populated species to evaluate this hypothesis. Escherichia coli RNase H is known to populate an intermediate before the rate-limiting barrier to folding that has long been thought to be a molten globule. We investigated this hypothesis by making mimics of the intermediate that are the ground-state conformation at equilibrium, using two approaches: a truncation to generate a fragment mimic of the intermediate, and selective destabilization of the native state using point mutations. Spectroscopic characterization and the response of the mimics to further mutation are consistent with studies on the transient kinetic intermediate, indicating that they model the early intermediate. Both mimics fold cooperatively and exhibit NMR spectra indicative of a closely packed conformation, in contrast to the hypothesis of molten tertiary packing. This result is important for understanding the nature of the subsequent rate-limiting barrier to folding and has implications for the assumption that many other proteins populate molten globule folding intermediates.
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Relationship between ion pair geometries and electrostatic strengths in proteins.
Kumar, Sandeep; Nussinov, Ruth
2002-01-01
The electrostatic free energy contribution of an ion pair in a protein depends on two factors, geometrical orientation of the side-chain charged groups with respect to each other and the structural context of the ion pair in the protein. Conformers in NMR ensembles enable studies of the relationship between geometry and electrostatic strengths of ion pairs, because the protein structural contexts are highly similar across different conformers. We have studied this relationship using a dataset of 22 unique ion pairs in 14 NMR conformer ensembles for 11 nonhomologous proteins. In different NMR conformers, the ion pairs are classified as salt bridges, nitrogen-oxygen (N-O) bridges and longer-range ion pairs on the basis of geometrical criteria. In salt bridges, centroids of the side-chain charged groups and at least a pair of side-chain nitrogen and oxygen atoms of the ion-pairing residues are within a 4 A distance. In N-O bridges, at least a pair of the side-chain nitrogen and oxygen atoms of the ion-pairing residues are within 4 A distance, but the distance between the side-chain charged group centroids is greater than 4 A. In the longer-range ion pairs, the side-chain charged group centroids as well as the side-chain nitrogen and oxygen atoms are more than 4 A apart. Continuum electrostatic calculations indicate that most of the ion pairs have stabilizing electrostatic contributions when their side-chain charged group centroids are within 5 A distance. Hence, most (approximately 92%) of the salt bridges and a majority (68%) of the N-O bridges are stabilizing. Most (approximately 89%) of the destabilizing ion pairs are the longer-range ion pairs. In the NMR conformer ensembles, the electrostatic interaction between side-chain charged groups of the ion-pairing residues is the strongest for salt bridges, considerably weaker for N-O bridges, and the weakest for longer-range ion pairs. These results suggest empirical rules for stabilizing electrostatic interactions in proteins. PMID:12202384
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Woods, Kristina N; Pfeffer, Juergen
2016-01-01
It is now widely accepted that protein function is intimately tied with the navigation of energy landscapes. In this framework, a protein sequence is not described by a distinct structure but rather by an ensemble of conformations. And it is through this ensemble that evolution is able to modify a protein's function by altering its landscape. Hence, the evolution of protein functions involves selective pressures that adjust the sampling of the conformational states. In this work, we focus on elucidating the evolutionary pathway that shaped the function of individual proteins that make-up the mammalian c-type lysozyme subfamily. Using both experimental and computational methods, we map out specific intermolecular interactions that direct the sampling of conformational states and accordingly, also underlie shifts in the landscape that are directly connected with the formation of novel protein functions. By contrasting three representative proteins in the family we identify molecular mechanisms that are associated with the selectivity of enhanced antimicrobial properties and consequently, divergent protein function. Namely, we link the extent of localized fluctuations involving the loop separating helices A and B with shifts in the equilibrium of the ensemble of conformational states that mediate interdomain coupling and concurrently moderate substrate binding affinity. This work reveals unique insights into the molecular level mechanisms that promote the progression of interactions that connect the immune response to infection with the nutritional properties of lactation, while also providing a deeper understanding about how evolving energy landscapes may define present-day protein function. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
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A collaborative filtering approach for protein-protein docking scoring functions.
Bourquard, Thomas; Bernauer, Julie; Azé, Jérôme; Poupon, Anne
2011-04-22
A protein-protein docking procedure traditionally consists in two successive tasks: a search algorithm generates a large number of candidate conformations mimicking the complex existing in vivo between two proteins, and a scoring function is used to rank them in order to extract a native-like one. We have already shown that using Voronoi constructions and a well chosen set of parameters, an accurate scoring function could be designed and optimized. However to be able to perform large-scale in silico exploration of the interactome, a near-native solution has to be found in the ten best-ranked solutions. This cannot yet be guaranteed by any of the existing scoring functions. In this work, we introduce a new procedure for conformation ranking. We previously developed a set of scoring functions where learning was performed using a genetic algorithm. These functions were used to assign a rank to each possible conformation. We now have a refined rank using different classifiers (decision trees, rules and support vector machines) in a collaborative filtering scheme. The scoring function newly obtained is evaluated using 10 fold cross-validation, and compared to the functions obtained using either genetic algorithms or collaborative filtering taken separately. This new approach was successfully applied to the CAPRI scoring ensembles. We show that for 10 targets out of 12, we are able to find a near-native conformation in the 10 best ranked solutions. Moreover, for 6 of them, the near-native conformation selected is of high accuracy. Finally, we show that this function dramatically enriches the 100 best-ranking conformations in near-native structures.
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A Collaborative Filtering Approach for Protein-Protein Docking Scoring Functions
Bourquard, Thomas; Bernauer, Julie; Azé, Jérôme; Poupon, Anne
2011-01-01
A protein-protein docking procedure traditionally consists in two successive tasks: a search algorithm generates a large number of candidate conformations mimicking the complex existing in vivo between two proteins, and a scoring function is used to rank them in order to extract a native-like one. We have already shown that using Voronoi constructions and a well chosen set of parameters, an accurate scoring function could be designed and optimized. However to be able to perform large-scale in silico exploration of the interactome, a near-native solution has to be found in the ten best-ranked solutions. This cannot yet be guaranteed by any of the existing scoring functions. In this work, we introduce a new procedure for conformation ranking. We previously developed a set of scoring functions where learning was performed using a genetic algorithm. These functions were used to assign a rank to each possible conformation. We now have a refined rank using different classifiers (decision trees, rules and support vector machines) in a collaborative filtering scheme. The scoring function newly obtained is evaluated using 10 fold cross-validation, and compared to the functions obtained using either genetic algorithms or collaborative filtering taken separately. This new approach was successfully applied to the CAPRI scoring ensembles. We show that for 10 targets out of 12, we are able to find a near-native conformation in the 10 best ranked solutions. Moreover, for 6 of them, the near-native conformation selected is of high accuracy. Finally, we show that this function dramatically enriches the 100 best-ranking conformations in near-native structures. PMID:21526112
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Zacarías-Lara, Oscar J; Correa-Basurto, José; Bello, Martiniano
2016-07-01
B-cell lymphoma (Bcl-2) is commonly associated with the progression and preservation of cancer and certain lymphomas; therefore, it is considered as a biological target against cancer. Nevertheless, evidence of all its structural binding sites has been hidden because of the lack of a complete Bcl-2 model, given the presence of a flexible loop domain (FLD), which is responsible for its complex behavior. FLD region has been implicated in phosphorylation, homotrimerization, and heterodimerization associated with Bcl-2 antiapoptotic function. In this contribution, homology modeling, molecular dynamics (MD) simulations in the microsecond (µs) time-scale and docking calculations were combined to explore the conformational complexity of unphosphorylated/phosphorylated monomeric and trimeric Bcl-2 systems. Conformational ensembles generated through MD simulations allowed for identifying the most populated unphosphorylated/phosphorylated monomeric conformations, which were used as starting models to obtain trimeric complexes through protein-protein docking calculations, also submitted to µs MD simulations. Principal component analysis showed that FLD represents the main contributor to total Bcl-2 mobility, and is affected by phosphorylation and oligomerization. Subsequently, based on the most representative unphosphorylated/phosphorylated monomeric and trimeric Bcl-2 conformations, docking studies were initiated to identify the ligand binding site of several known Bcl-2 inhibitors to explain their influence in homo-complex formation and phosphorylation. Docking studies showed that the different conformational states experienced by FLD, such as phosphorylation and oligomerization, play an essential role in the ability to make homo and hetero-complexes. © 2016 Wiley Periodicals, Inc. Biopolymers 105: 393-413, 2016. © 2016 Wiley Periodicals, Inc.
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Olson, Mark A; Feig, Michael; Brooks, Charles L
2008-04-15
This article examines ab initio methods for the prediction of protein loops by a computational strategy of multiscale conformational sampling and physical energy scoring functions. Our approach consists of initial sampling of loop conformations from lattice-based low-resolution models followed by refinement using all-atom simulations. To allow enhanced conformational sampling, the replica exchange method was implemented. Physical energy functions based on CHARMM19 and CHARMM22 parameterizations with generalized Born (GB) solvent models were applied in scoring loop conformations extracted from the lattice simulations and, in the case of all-atom simulations, the ensemble of conformations were generated and scored with these models. Predictions are reported for 25 loop segments, each eight residues long and taken from a diverse set of 22 protein structures. We find that the simulations generally sampled conformations with low global root-mean-square-deviation (RMSD) for loop backbone coordinates from the known structures, whereas clustering conformations in RMSD space and scoring detected less favorable loop structures. Specifically, the lattice simulations sampled basins that exhibited an average global RMSD of 2.21 +/- 1.42 A, whereas clustering and scoring the loop conformations determined an RMSD of 3.72 +/- 1.91 A. Using CHARMM19/GB to refine the lattice conformations improved the sampling RMSD to 1.57 +/- 0.98 A and detection to 2.58 +/- 1.48 A. We found that further improvement could be gained from extending the upper temperature in the all-atom refinement from 400 to 800 K, where the results typically yield a reduction of approximately 1 A or greater in the RMSD of the detected loop. Overall, CHARMM19 with a simple pairwise GB solvent model is more efficient at sampling low-RMSD loop basins than CHARMM22 with a higher-resolution modified analytical GB model; however, the latter simulation method provides a more accurate description of the all-atom energy surface, yet demands a much greater computational cost. (c) 2007 Wiley Periodicals, Inc.
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2015-01-01
Complex RNA structures are constructed from helical segments connected by flexible loops that move spontaneously and in response to binding of small molecule ligands and proteins. Understanding the conformational variability of RNA requires the characterization of the coupled time evolution of interconnected flexible domains. To elucidate the collective molecular motions and explore the conformational landscape of the HIV-1 TAR RNA, we describe a new methodology that utilizes energy-minimized structures generated by the program “Fragment Assembly of RNA with Full-Atom Refinement (FARFAR)”. We apply structural filters in the form of experimental residual dipolar couplings (RDCs) to select a subset of discrete energy-minimized conformers and carry out principal component analyses (PCA) to corroborate the choice of the filtered subset. We use this subset of structures to calculate solution T1 and T1ρ relaxation times for 13C spins in multiple residues in different domains of the molecule using two simulation protocols that we previously published. We match the experimental T1 times to within 2% and the T1ρ times to within less than 10% for helical residues. These results introduce a protocol to construct viable dynamic trajectories for RNA molecules that accord well with experimental NMR data and support the notion that the motions of the helical portions of this small RNA can be described by a relatively small number of discrete conformations exchanging over time scales longer than 1 μs. PMID:24479561
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Bolia, Ashini; Gerek, Z. Nevin; Ozkan, S. Banu
2016-01-01
Molecular docking serves as an important tool in modeling protein–ligand interactions. However, it is still challenging to incorporate overall receptor flexibility, especially backbone flexibility, in docking due to the large conformational space that needs to be sampled. To overcome this problem, we developed a novel flexible docking approach, BP-Dock (Backbone Perturbation-Dock) that can integrate both backbone and side chain conformational changes induced by ligand binding through a multi-scale approach. In the BP-Dock method, we mimic the nature of binding-induced events as a first-order approximation by perturbing the residues along the protein chain with a small Brownian kick one at a time. The response fluctuation profile of the chain upon these perturbations is computed using the perturbation response scanning method. These response fluctuation profiles are then used to generate binding-induced multiple receptor conformations for ensemble docking. To evaluate the performance of BP-Dock, we applied our approach on a large and diverse data set using unbound structures as receptors. We also compared the BP-Dock results with bound and unbound docking, where overall receptor flexibility was not taken into account. Our results highlight the importance of modeling backbone flexibility in docking for recapitulating the experimental binding affinities, especially when an unbound structure is used. With BP-Dock, we can generate a wide range of binding site conformations realized in nature even in the absence of a ligand that can help us to improve the accuracy of unbound docking. We expect that our fast and efficient flexible docking approach may further aid in our understanding of protein–ligand interactions as well as virtual screening of novel targets for rational drug design. PMID:24380381
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Rethinking the Default Construction of Multimodel Climate Ensembles
Rauser, Florian; Gleckler, Peter; Marotzke, Jochem
2015-07-21
Here, we discuss the current code of practice in the climate sciences to routinely create climate model ensembles as ensembles of opportunity from the newest phase of the Coupled Model Intercomparison Project (CMIP). We give a two-step argument to rethink this process. First, the differences between generations of ensembles corresponding to different CMIP phases in key climate quantities are not large enough to warrant an automatic separation into generational ensembles for CMIP3 and CMIP5. Second, we suggest that climate model ensembles cannot continue to be mere ensembles of opportunity but should always be based on a transparent scientific decision process.more » If ensembles can be constrained by observation, then they should be constructed as target ensembles that are specifically tailored to a physical question. If model ensembles cannot be constrained by observation, then they should be constructed as cross-generational ensembles, including all available model data to enhance structural model diversity and to better sample the underlying uncertainties. To facilitate this, CMIP should guide the necessarily ongoing process of updating experimental protocols for the evaluation and documentation of coupled models. Finally, with an emphasis on easy access to model data and facilitating the filtering of climate model data across all CMIP generations and experiments, our community could return to the underlying idea of using model data ensembles to improve uncertainty quantification, evaluation, and cross-institutional exchange.« less
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Padula, Daniele; Pescitelli, Gennaro
2018-01-09
Chiroptical spectra such as electronic circular dichroism (ECD) are said to be much more sensitive to conformation than their non-chiroptical counterparts, however, it is difficult to demonstrate such a common notion in a clear-cut way. We run DFT and TDDFT calculations on two closely related 1,1-diarylmethanols which show mirror-image ECD spectra for the same absolute configuration. We demonstrate that the main reason for the different chiroptical response of the two compounds lies in different conformational ensembles, caused by a single hydrogen-to-methyl substitution. We conclude that two compounds, having the same configuration but different conformation, may exhibit mirror-image ECD signals, stressing the importance and impact of conformational factors on ECD spectra.
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Infinitely Dilute Partial Molar Properties of Proteins from Computer Simulation
2015-01-01
A detailed understanding of temperature and pressure effects on an infinitely dilute protein’s conformational equilibrium requires knowledge of the corresponding infinitely dilute partial molar properties. Established molecular dynamics methodologies generally have not provided a way to calculate these properties without either a loss of thermodynamic rigor, the introduction of nonunique parameters, or a loss of information about which solute conformations specifically contributed to the output values. Here we implement a simple method that is thermodynamically rigorous and possesses none of the above disadvantages, and we report on the method’s feasibility and computational demands. We calculate infinitely dilute partial molar properties for two proteins and attempt to distinguish the thermodynamic differences between a native and a denatured conformation of a designed miniprotein. We conclude that simple ensemble average properties can be calculated with very reasonable amounts of computational power. In contrast, properties corresponding to fluctuating quantities are computationally demanding to calculate precisely, although they can be obtained more easily by following the temperature and/or pressure dependence of the corresponding ensemble averages. PMID:25325571
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Vassall, Kenrick A; Jenkins, Andrew D; Bamm, Vladimir V; Harauz, George
2015-05-22
The intrinsically disordered, 18.5-kDa isoform of myelin basic protein (MBP) is a peripheral membrane protein that is essential to proper myelin formation in the central nervous system. MBP acts in oligodendrocytes both to adjoin membrane leaflets to each other in forming myelin and as a hub in numerous protein-protein and protein-membrane interaction networks. Like many intrinsically disordered proteins (IDPs), MBP multifunctionality arises from its high conformational plasticity and its ability to undergo reversible disorder-to-order transitions. One such transition is the disorder-to-α-helical conformational change that is induced upon MBP-membrane binding. Here, we have investigated the disorder-to-α-helical transition of MBP-derived α-peptides and the full-length 18.5-kDa protein. This transition was induced through titration of the membrane-mimetic solvent trifluoroethanol into both protein and peptide solutions, and conformational change was monitored using circular dichroism spectroscopy, 1-anilinonaphthalene-8-sulfonic acid binding, tryptophan fluorescence quenching, and Förster (fluorescence) resonance energy transfer measurements. The data suggest that the disorder-to-α-helical transition of MBP follows a 3-state model: disordered↔intermediate↔α-helical, with each of the identified equilibrium states likely representing a conformational ensemble. The disordered state is characterized by slight compaction with little regular secondary structure, whereas the intermediate is also disordered but globally more compact. Surprisingly, the α-helical conformation is less compact than the intermediate. This study suggests that multifunctionality in MBP could arise from differences in the population of energetically distinct ensembles under different conditions and also provides an example of an IDP that undergoes cooperative global conformation change. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Leong, Max K.; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng
2017-01-01
The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r2 = 0.928–0.988, = 0.894–0.954, RMSE = 0.002–0.412, s = 0.001–0.214), and the predicted pKi values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r2 = 0.967, = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q2 = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery. PMID:28059133
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Leong, Max K; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng
2017-01-06
The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r 2 = 0.928-0.988, = 0.894-0.954, RMSE = 0.002-0.412, s = 0.001-0.214), and the predicted pK i values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r 2 = 0.967, = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q 2 = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery.
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NASA Astrophysics Data System (ADS)
Leong, Max K.; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng
2017-01-01
The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r2 = 0.928-0.988, = 0.894-0.954, RMSE = 0.002-0.412, s = 0.001-0.214), and the predicted pKi values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r2 = 0.967, = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q2 = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery.
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MSEBAG: a dynamic classifier ensemble generation based on `minimum-sufficient ensemble' and bagging
NASA Astrophysics Data System (ADS)
Chen, Lei; Kamel, Mohamed S.
2016-01-01
In this paper, we propose a dynamic classifier system, MSEBAG, which is characterised by searching for the 'minimum-sufficient ensemble' and bagging at the ensemble level. It adopts an 'over-generation and selection' strategy and aims to achieve a good bias-variance trade-off. In the training phase, MSEBAG first searches for the 'minimum-sufficient ensemble', which maximises the in-sample fitness with the minimal number of base classifiers. Then, starting from the 'minimum-sufficient ensemble', a backward stepwise algorithm is employed to generate a collection of ensembles. The objective is to create a collection of ensembles with a descending fitness on the data, as well as a descending complexity in the structure. MSEBAG dynamically selects the ensembles from the collection for the decision aggregation. The extended adaptive aggregation (EAA) approach, a bagging-style algorithm performed at the ensemble level, is employed for this task. EAA searches for the competent ensembles using a score function, which takes into consideration both the in-sample fitness and the confidence of the statistical inference, and averages the decisions of the selected ensembles to label the test pattern. The experimental results show that the proposed MSEBAG outperforms the benchmarks on average.
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Generating intrinsically disordered protein conformational ensembles from a Markov chain
NASA Astrophysics Data System (ADS)
Cukier, Robert I.
2018-03-01
Intrinsically disordered proteins (IDPs) sample a diverse conformational space. They are important to signaling and regulatory pathways in cells. An entropy penalty must be payed when an IDP becomes ordered upon interaction with another protein or a ligand. Thus, the degree of conformational disorder of an IDP is of interest. We create a dichotomic Markov model that can explore entropic features of an IDP. The Markov condition introduces local (neighbor residues in a protein sequence) rotamer dependences that arise from van der Waals and other chemical constraints. A protein sequence of length N is characterized by its (information) entropy and mutual information, MIMC, the latter providing a measure of the dependence among the random variables describing the rotamer probabilities of the residues that comprise the sequence. For a Markov chain, the MIMC is proportional to the pair mutual information MI which depends on the singlet and pair probabilities of neighbor residue rotamer sampling. All 2N sequence states are generated, along with their probabilities, and contrasted with the probabilities under the assumption of independent residues. An efficient method to generate realizations of the chain is also provided. The chain entropy, MIMC, and state probabilities provide the ingredients to distinguish different scenarios using the terminologies: MoRF (molecular recognition feature), not-MoRF, and not-IDP. A MoRF corresponds to large entropy and large MIMC (strong dependence among the residues' rotamer sampling), a not-MoRF corresponds to large entropy but small MIMC, and not-IDP corresponds to low entropy irrespective of the MIMC. We show that MorFs are most appropriate as descriptors of IDPs. They provide a reasonable number of high-population states that reflect the dependences between neighbor residues, thus classifying them as IDPs, yet without very large entropy that might lead to a too high entropy penalty.
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Role of conformational dynamics in the evolution of novel enzyme function.
Maria-Solano, Miguel A; Serrano-Hervás, Eila; Romero-Rivera, Adrian; Iglesias-Fernández, Javier; Osuna, Sílvia
2018-05-21
The free energy landscape concept that describes enzymes as an ensemble of differently populated conformational sub-states in dynamic equilibrium is key for evaluating enzyme activity, enantioselectivity, and specificity. Mutations introduced in the enzyme sequence can alter the populations of the pre-existing conformational states, thus strongly modifying the enzyme ability to accommodate alternative substrates, revert its enantiopreferences, and even increase the activity for some residual promiscuous reactions. In this feature article, we present an overview of the current experimental and computational strategies to explore the conformational free energy landscape of enzymes. We provide a series of recent publications that highlight the key role of conformational dynamics for the enzyme evolution towards new functions and substrates, and provide some perspectives on how conformational dynamism should be considered in future computational enzyme design protocols.
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Abramyan, Tigran M.; Hyde-Volpe, David L.; Stuart, Steven J.; Latour, Robert A.
2017-01-01
The use of standard molecular dynamics simulation methods to predict the interactions of a protein with a material surface have the inherent limitations of lacking the ability to determine the most likely conformations and orientations of the adsorbed protein on the surface and to determine the level of convergence attained by the simulation. In addition, standard mixing rules are typically applied to combine the nonbonded force field parameters of the solution and solid phases the system to represent interfacial behavior without validation. As a means to circumvent these problems, the authors demonstrate the application of an efficient advanced sampling method (TIGER2A) for the simulation of the adsorption of hen egg-white lysozyme on a crystalline (110) high-density polyethylene surface plane. Simulations are conducted to generate a Boltzmann-weighted ensemble of sampled states using force field parameters that were validated to represent interfacial behavior for this system. The resulting ensembles of sampled states were then analyzed using an in-house-developed cluster analysis method to predict the most probable orientations and conformations of the protein on the surface based on the amount of sampling performed, from which free energy differences between the adsorbed states were able to be calculated. In addition, by conducting two independent sets of TIGER2A simulations combined with cluster analyses, the authors demonstrate a method to estimate the degree of convergence achieved for a given amount of sampling. The results from these simulations demonstrate that these methods enable the most probable orientations and conformations of an adsorbed protein to be predicted and that the use of our validated interfacial force field parameter set provides closer agreement to available experimental results compared to using standard CHARMM force field parameterization to represent molecular behavior at the interface. PMID:28514864
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Conformational diversity and computational enzyme design
Lassila, Jonathan K.
2010-01-01
The application of computational protein design methods to the design of enzyme active sites offers potential routes to new catalysts and new reaction specificities. Computational design methods have typically treated the protein backbone as a rigid structure for the sake of computational tractability. However, this fixed-backbone approximation introduces its own special challenges for enzyme design and it contrasts with an emerging picture of natural enzymes as dynamic ensembles with multiple conformations and motions throughout a reaction cycle. This review considers the impact of conformational variation and dynamics on computational enzyme design and it highlights new approaches to addressing protein conformational diversity in enzyme design including recent advances in multistate design, backbone flexibility, and computational library design. PMID:20829099
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Polyphony: superposition independent methods for ensemble-based drug discovery.
Pitt, William R; Montalvão, Rinaldo W; Blundell, Tom L
2014-09-30
Structure-based drug design is an iterative process, following cycles of structural biology, computer-aided design, synthetic chemistry and bioassay. In favorable circumstances, this process can lead to the structures of hundreds of protein-ligand crystal structures. In addition, molecular dynamics simulations are increasingly being used to further explore the conformational landscape of these complexes. Currently, methods capable of the analysis of ensembles of crystal structures and MD trajectories are limited and usually rely upon least squares superposition of coordinates. Novel methodologies are described for the analysis of multiple structures of a protein. Statistical approaches that rely upon residue equivalence, but not superposition, are developed. Tasks that can be performed include the identification of hinge regions, allosteric conformational changes and transient binding sites. The approaches are tested on crystal structures of CDK2 and other CMGC protein kinases and a simulation of p38α. Known interaction - conformational change relationships are highlighted but also new ones are revealed. A transient but druggable allosteric pocket in CDK2 is predicted to occur under the CMGC insert. Furthermore, an evolutionarily-conserved conformational link from the location of this pocket, via the αEF-αF loop, to phosphorylation sites on the activation loop is discovered. New methodologies are described and validated for the superimposition independent conformational analysis of large collections of structures or simulation snapshots of the same protein. The methodologies are encoded in a Python package called Polyphony, which is released as open source to accompany this paper [http://wrpitt.bitbucket.org/polyphony/].
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NASA Astrophysics Data System (ADS)
Reppert, Michael; Tokmakoff, Andrei
The structural characterization of intrinsically disordered peptides (IDPs) presents a challenging biophysical problem. Extreme heterogeneity and rapid conformational interconversion make traditional methods difficult to interpret. Due to its ultrafast (ps) shutter speed, Amide I vibrational spectroscopy has received considerable interest as a novel technique to probe IDP structure and dynamics. Historically, Amide I spectroscopy has been limited to delivering global secondary structural information. More recently, however, the method has been adapted to study structure at the local level through incorporation of isotope labels into the protein backbone at specific amide bonds. Thanks to the acute sensitivity of Amide I frequencies to local electrostatic interactions-particularly hydrogen bonds-spectroscopic data on isotope labeled residues directly reports on local peptide conformation. Quantitative information can be extracted using electrostatic frequency maps which translate molecular dynamics trajectories into Amide I spectra for comparison with experiment. Here we present our recent efforts in the development of a rigorous approach to incorporating Amide I spectroscopic restraints into refined molecular dynamics structural ensembles using maximum entropy and related approaches. By combining force field predictions with experimental spectroscopic data, we construct refined structural ensembles for a family of short, strongly disordered, elastin-like peptides in aqueous solution.
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Blacklock, Kristin; Verkhivker, Gennady M.
2014-01-01
A fundamental role of the Hsp90 chaperone in regulating functional activity of diverse protein clients is essential for the integrity of signaling networks. In this work we have combined biophysical simulations of the Hsp90 crystal structures with the protein structure network analysis to characterize the statistical ensemble of allosteric interaction networks and communication pathways in the Hsp90 chaperones. We have found that principal structurally stable communities could be preserved during dynamic changes in the conformational ensemble. The dominant contribution of the inter-domain rigidity to the interaction networks has emerged as a common factor responsible for the thermodynamic stability of the active chaperone form during the ATPase cycle. Structural stability analysis using force constant profiling of the inter-residue fluctuation distances has identified a network of conserved structurally rigid residues that could serve as global mediating sites of allosteric communication. Mapping of the conformational landscape with the network centrality parameters has demonstrated that stable communities and mediating residues may act concertedly with the shifts in the conformational equilibrium and could describe the majority of functionally significant chaperone residues. The network analysis has revealed a relationship between structural stability, global centrality and functional significance of hotspot residues involved in chaperone regulation. We have found that allosteric interactions in the Hsp90 chaperone may be mediated by modules of structurally stable residues that display high betweenness in the global interaction network. The results of this study have suggested that allosteric interactions in the Hsp90 chaperone may operate via a mechanism that combines rapid and efficient communication by a single optimal pathway of structurally rigid residues and more robust signal transmission using an ensemble of suboptimal multiple communication routes. This may be a universal requirement encoded in protein structures to balance the inherent tension between resilience and efficiency of the residue interaction networks. PMID:24922508
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Blacklock, Kristin; Verkhivker, Gennady M
2014-06-01
A fundamental role of the Hsp90 chaperone in regulating functional activity of diverse protein clients is essential for the integrity of signaling networks. In this work we have combined biophysical simulations of the Hsp90 crystal structures with the protein structure network analysis to characterize the statistical ensemble of allosteric interaction networks and communication pathways in the Hsp90 chaperones. We have found that principal structurally stable communities could be preserved during dynamic changes in the conformational ensemble. The dominant contribution of the inter-domain rigidity to the interaction networks has emerged as a common factor responsible for the thermodynamic stability of the active chaperone form during the ATPase cycle. Structural stability analysis using force constant profiling of the inter-residue fluctuation distances has identified a network of conserved structurally rigid residues that could serve as global mediating sites of allosteric communication. Mapping of the conformational landscape with the network centrality parameters has demonstrated that stable communities and mediating residues may act concertedly with the shifts in the conformational equilibrium and could describe the majority of functionally significant chaperone residues. The network analysis has revealed a relationship between structural stability, global centrality and functional significance of hotspot residues involved in chaperone regulation. We have found that allosteric interactions in the Hsp90 chaperone may be mediated by modules of structurally stable residues that display high betweenness in the global interaction network. The results of this study have suggested that allosteric interactions in the Hsp90 chaperone may operate via a mechanism that combines rapid and efficient communication by a single optimal pathway of structurally rigid residues and more robust signal transmission using an ensemble of suboptimal multiple communication routes. This may be a universal requirement encoded in protein structures to balance the inherent tension between resilience and efficiency of the residue interaction networks.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Horowitz, Scott; Salmon, Loïc; Koldewey, Philipp
We present that challenges in determining the structures of heterogeneous and dynamic protein complexes have greatly hampered past efforts to obtain a mechanistic understanding of many important biological processes. One such process is chaperone-assisted protein folding. Obtaining structural ensembles of chaperone–substrate complexes would ultimately reveal how chaperones help proteins fold into their native state. To address this problem, we devised a new structural biology approach based on X-ray crystallography, termed residual electron and anomalous density (READ). READ enabled us to visualize even sparsely populated conformations of the substrate protein immunity protein 7 (Im7) in complex with the Escherichia coli chaperonemore » Spy, and to capture a series of snapshots depicting the various folding states of Im7 bound to Spy. The ensemble shows that Spy-associated Im7 samples conformations ranging from unfolded to partially folded to native-like states and reveals how a substrate can explore its folding landscape while being bound to a chaperone.« less
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Improving database enrichment through ensemble docking
NASA Astrophysics Data System (ADS)
Rao, Shashidhar; Sanschagrin, Paul C.; Greenwood, Jeremy R.; Repasky, Matthew P.; Sherman, Woody; Farid, Ramy
2008-09-01
While it may seem intuitive that using an ensemble of multiple conformations of a receptor in structure-based virtual screening experiments would necessarily yield improved enrichment of actives relative to using just a single receptor, it turns out that at least in the p38 MAP kinase model system studied here, a very large majority of all possible ensembles do not yield improved enrichment of actives. However, there are combinations of receptor structures that do lead to improved enrichment results. We present here a method to select the ensembles that produce the best enrichments that does not rely on knowledge of active compounds or sophisticated analyses of the 3D receptor structures. In the system studied here, the small fraction of ensembles of up to 3 receptors that do yield good enrichments of actives were identified by selecting ensembles that have the best mean GlideScore for the top 1% of the docked ligands in a database screen of actives and drug-like "decoy" ligands. Ensembles of two receptors identified using this mean GlideScore metric generally outperform single receptors, while ensembles of three receptors identified using this metric consistently give optimal enrichment factors in which, for example, 40% of the known actives outrank all the other ligands in the database.
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Molecular Simulation Uncovers the Conformational Space of the λ Cro Dimer in Solution
Ahlstrom, Logan S.; Miyashita, Osamu
2011-01-01
The significant variation among solved structures of the λ Cro dimer suggests its flexibility. However, contacts in the crystal lattice could have stabilized a conformation which is unrepresentative of its dominant solution form. Here we report on the conformational space of the Cro dimer in solution using replica exchange molecular dynamics in explicit solvent. The simulated ensemble shows remarkable correlation with available x-ray structures. Network analysis and a free energy surface reveal the predominance of closed and semi-open dimers, with a modest barrier separating these two states. The fully open conformation lies higher in free energy, indicating that it requires stabilization by DNA or crystal contacts. Most NMR models are found to be unstable conformations in solution. Intersubunit salt bridging between Arg4 and Glu53 during simulation stabilizes closed conformations. Because a semi-open state is among the low-energy conformations sampled in simulation, we propose that Cro-DNA binding may not entail a large conformational change relative to the dominant dimer forms in solution. PMID:22098751
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The "Tse Tsa Watle" Speaker Series: An Example of Ensemble Leadership and Generative Adult Learning
ERIC Educational Resources Information Center
McKendry, Virginia
2017-01-01
This chapter examines an Indigenous speaker series formed to foster intercultural partnerships at a Canadian university. Using ensemble leadership and generative learning theories to make sense of the project, the author argues that ensemble leadership is key to designing the generative learning adult learners need in an era of ambiguity.
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A probabilistic model for detecting rigid domains in protein structures.
Nguyen, Thach; Habeck, Michael
2016-09-01
Large-scale conformational changes in proteins are implicated in many important biological functions. These structural transitions can often be rationalized in terms of relative movements of rigid domains. There is a need for objective and automated methods that identify rigid domains in sets of protein structures showing alternative conformational states. We present a probabilistic model for detecting rigid-body movements in protein structures. Our model aims to approximate alternative conformational states by a few structural parts that are rigidly transformed under the action of a rotation and a translation. By using Bayesian inference and Markov chain Monte Carlo sampling, we estimate all parameters of the model, including a segmentation of the protein into rigid domains, the structures of the domains themselves, and the rigid transformations that generate the observed structures. We find that our Gibbs sampling algorithm can also estimate the optimal number of rigid domains with high efficiency and accuracy. We assess the power of our method on several thousand entries of the DynDom database and discuss applications to various complex biomolecular systems. The Python source code for protein ensemble analysis is available at: https://github.com/thachnguyen/motion_detection : mhabeck@gwdg.de. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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The Role of Large-Scale Motions in Catalysis by Dihydrofolate Reductase
2011-01-01
Dihydrofolate reductase has long been used as a model system to study the coupling of protein motions to enzymatic hydride transfer. By studying environmental effects on hydride transfer in dihydrofolate reductase (DHFR) from the cold-adapted bacterium Moritella profunda (MpDHFR) and comparing the flexibility of this enzyme to that of DHFR from Escherichia coli (EcDHFR), we demonstrate that factors that affect large-scale (i.e., long-range, but not necessarily large amplitude) protein motions have no effect on the kinetic isotope effect on hydride transfer or its temperature dependence, although the rates of the catalyzed reaction are affected. Hydrogen/deuterium exchange studies by NMR-spectroscopy show that MpDHFR is a more flexible enzyme than EcDHFR. NMR experiments with EcDHFR in the presence of cosolvents suggest differences in the conformational ensemble of the enzyme. The fact that enzymes from different environmental niches and with different flexibilities display the same behavior of the kinetic isotope effect on hydride transfer strongly suggests that, while protein motions are important to generate the reaction ready conformation, an optimal conformation with the correct electrostatics and geometry for the reaction to occur, they do not influence the nature of the chemical step itself; large-scale motions do not couple directly to hydride transfer proper in DHFR. PMID:22060818
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Force generation by titin folding.
Mártonfalvi, Zsolt; Bianco, Pasquale; Naftz, Katalin; Ferenczy, György G; Kellermayer, Miklós
2017-07-01
Titin is a giant protein that provides elasticity to muscle. As the sarcomere is stretched, titin extends hierarchically according to the mechanics of its segments. Whether titin's globular domains unfold during this process and how such unfolded domains might contribute to muscle contractility are strongly debated. To explore the force-dependent folding mechanisms, here we manipulated skeletal-muscle titin molecules with high-resolution optical tweezers. In force-clamp mode, after quenching the force (<10 pN), extension fluctuated without resolvable discrete events. In position-clamp experiments, the time-dependent force trace contained rapid fluctuations and a gradual increase of average force, indicating that titin can develop force via dynamic transitions between its structural states en route to the native conformation. In 4 M urea, which destabilizes H-bonds hence the consolidated native domain structure, the net force increase disappeared but the fluctuations persisted. Thus, whereas net force generation is caused by the ensemble folding of the elastically-coupled domains, force fluctuations arise due to a dynamic equilibrium between unfolded and molten-globule states. Monte-Carlo simulations incorporating a compact molten-globule intermediate in the folding landscape recovered all features of our nanomechanics results. The ensemble molten-globule dynamics delivers significant added contractility that may assist sarcomere mechanics, and it may reduce the dissipative energy loss associated with titin unfolding/refolding during muscle contraction/relaxation cycles. © 2017 The Protein Society.
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Ligand and receptor dynamics contribute to the mechanism of graded PPARγ agonism
Hughes, Travis S.; Chalmers, Michael J.; Novick, Scott; Kuruvilla, Dana S.; Chang, Mi Ra; Kamenecka, Theodore M.; Rance, Mark; Johnson, Bruce A.; Burris, Thomas P.; Griffin, Patrick R.; Kojetin, Douglas J.
2011-01-01
SUMMARY Ligand binding to proteins is not a static process, but rather involves a number of complex dynamic transitions. A flexible ligand can change conformation upon binding its target. The conformation and dynamics of a protein can change to facilitate ligand binding. The conformation of the ligand, however, is generally presumed to have one primary binding mode, shifting the protein conformational ensemble from one state to another. We report solution NMR studies that reveal peroxisome proliferator-activated receptor γ (PPARγ) modulators can sample multiple binding modes manifesting in multiple receptor conformations in slow conformational exchange. Our NMR, hydrogen/deuterium exchange and docking studies reveal that ligand-induced receptor stabilization and binding mode occupancy correlate with the graded agonist response of the ligand. Our results suggest that ligand and receptor dynamics affect the graded transcriptional output of PPARγ modulators. PMID:22244763
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Latypov, Ramil F.; Liu, Dingjiang; Jacob, Jaby
2010-01-12
Conformational properties of the folded and unfolded ensembles of human interleukin-1 receptor antagonist (IL-1ra) are strongly denaturant-dependent as evidenced by high-resolution two-dimensional nuclear magnetic resonance (NMR), limited proteolysis, and small-angle X-ray scattering (SAXS). The folded ensemble was characterized in detail in the presence of different urea concentrations by 1H-15N HSQC NMR. The {beta}-trefoil fold characteristic of native IL-1ra was preserved until the unfolding transition region beginning at 4 M urea. At the same time, a subset of native resonances disappeared gradually starting at low denaturant concentrations, indicating noncooperative changes in the folded state. Additional evidence of structural perturbations came frommore » the chemical shift analysis, nonuniform and bell-shaped peak intensity profiles, and limited proteolysis. In particular, the following nearby regions of the tertiary structure became progressively destabilized with increasing urea concentrations: the {beta}-hairpin interface of trefoils 1 and 2 and the H2a-H2 helical region. These regions underwent small-scale perturbations within the native baseline region in the absence of populated molten globule-like states. Similar regions were affected by elevated temperatures known to induce irreversible aggregation of IL-1ra. Further evidence of structural transitions invoking near-native conformations came from an optical spectroscopy analysis of its single-tryptophan variant W17A. The increase in the radius of gyration was associated with a single equilibrium unfolding transition in the case of two different denaturants, urea and guanidine hydrochloride (GuHCl). However, the compactness of urea- and GuHCl-unfolded molecules was comparable only at high denaturant concentrations and deviated under less denaturing conditions. Our results identified the role of conformational flexibility in IL-1ra aggregation and shed light on the nature of structural transitions within the folded ensembles of other {beta}-trefoil proteins, such as IL-1{beta} and hFGF-1.« less
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Equilibrium sampling by reweighting nonequilibrium simulation trajectories
NASA Astrophysics Data System (ADS)
Yang, Cheng; Wan, Biao; Xu, Shun; Wang, Yanting; Zhou, Xin
2016-03-01
Based on equilibrium molecular simulations, it is usually difficult to efficiently visit the whole conformational space of complex systems, which are separated into some metastable regions by high free energy barriers. Nonequilibrium simulations could enhance transitions among these metastable regions and then be applied to sample equilibrium distributions in complex systems, since the associated nonequilibrium effects can be removed by employing the Jarzynski equality (JE). Here we present such a systematical method, named reweighted nonequilibrium ensemble dynamics (RNED), to efficiently sample equilibrium conformations. The RNED is a combination of the JE and our previous reweighted ensemble dynamics (RED) method. The original JE reproduces equilibrium from lots of nonequilibrium trajectories but requires that the initial distribution of these trajectories is equilibrium. The RED reweights many equilibrium trajectories from an arbitrary initial distribution to get the equilibrium distribution, whereas the RNED has both advantages of the two methods, reproducing equilibrium from lots of nonequilibrium simulation trajectories with an arbitrary initial conformational distribution. We illustrated the application of the RNED in a toy model and in a Lennard-Jones fluid to detect its liquid-solid phase coexistence. The results indicate that the RNED sufficiently extends the application of both the original JE and the RED in equilibrium sampling of complex systems.
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Equilibrium sampling by reweighting nonequilibrium simulation trajectories.
Yang, Cheng; Wan, Biao; Xu, Shun; Wang, Yanting; Zhou, Xin
2016-03-01
Based on equilibrium molecular simulations, it is usually difficult to efficiently visit the whole conformational space of complex systems, which are separated into some metastable regions by high free energy barriers. Nonequilibrium simulations could enhance transitions among these metastable regions and then be applied to sample equilibrium distributions in complex systems, since the associated nonequilibrium effects can be removed by employing the Jarzynski equality (JE). Here we present such a systematical method, named reweighted nonequilibrium ensemble dynamics (RNED), to efficiently sample equilibrium conformations. The RNED is a combination of the JE and our previous reweighted ensemble dynamics (RED) method. The original JE reproduces equilibrium from lots of nonequilibrium trajectories but requires that the initial distribution of these trajectories is equilibrium. The RED reweights many equilibrium trajectories from an arbitrary initial distribution to get the equilibrium distribution, whereas the RNED has both advantages of the two methods, reproducing equilibrium from lots of nonequilibrium simulation trajectories with an arbitrary initial conformational distribution. We illustrated the application of the RNED in a toy model and in a Lennard-Jones fluid to detect its liquid-solid phase coexistence. The results indicate that the RNED sufficiently extends the application of both the original JE and the RED in equilibrium sampling of complex systems.
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Determination of helix orientations in a flexible DNA by multi-frequency EPR spectroscopy.
Grytz, C M; Kazemi, S; Marko, A; Cekan, P; Güntert, P; Sigurdsson, S Th; Prisner, T F
2017-11-15
Distance measurements are performed between a pair of spin labels attached to nucleic acids using Pulsed Electron-Electron Double Resonance (PELDOR, also called DEER) spectroscopy which is a complementary tool to other structure determination methods in structural biology. The rigid spin label Ç, when incorporated pairwise into two helical parts of a nucleic acid molecule, allows the determination of both the mutual orientation and the distance between those labels, since Ç moves rigidly with the helix to which it is attached. We have developed a two-step protocol to investigate the conformational flexibility of flexible nucleic acid molecules by multi-frequency PELDOR. In the first step, a library with a broad collection of conformers, which are in agreement with topological constraints, NMR restraints and distances derived from PELDOR, was created. In the second step, a weighted structural ensemble of these conformers was chosen, such that it fits the multi-frequency PELDOR time traces of all doubly Ç-labelled samples simultaneously. This ensemble reflects the global structure and the conformational flexibility of the two-way DNA junction. We demonstrate this approach on a flexible bent DNA molecule, consisting of two short helical parts with a five adenine bulge at the center. The kink and twist motions between both helical parts were quantitatively determined and showed high flexibility, in agreement with a Förster Resonance Energy Transfer (FRET) study on a similar bent DNA motif. The approach presented here should be useful to describe the relative orientation of helical motifs and the conformational flexibility of nucleic acid structures, both alone and in complexes with proteins and other molecules.
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Aoki, Yoshiaki; Matsuki, Nobuo; Mori, Tadashi; Ikeda, Hiroshi; Inoue, Yoshihisa
2014-09-19
Solvent, temperature, and excitation wavelength significantly affected the photochemical outcomes of a naphthalene-dicyanoethene system tethered by different number (n) of methylene groups (1-3). The effect of irradiation wavelength was almost negligible for 2a but pronounced for 3a. The temperature dependence and theoretical calculations indicated the diversity of exciplex conformations, an ensemble of which can be effectively altered by changing excitation wavelength to eventually switch the regioselectivity of photoreactions.
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Molecular dynamics simulations: advances and applications
Hospital, Adam; Goñi, Josep Ramon; Orozco, Modesto; Gelpí, Josep L
2015-01-01
Molecular dynamics simulations have evolved into a mature technique that can be used effectively to understand macromolecular structure-to-function relationships. Present simulation times are close to biologically relevant ones. Information gathered about the dynamic properties of macromolecules is rich enough to shift the usual paradigm of structural bioinformatics from studying single structures to analyze conformational ensembles. Here, we describe the foundations of molecular dynamics and the improvements made in the direction of getting such ensemble. Specific application of the technique to three main issues (allosteric regulation, docking, and structure refinement) is discussed. PMID:26604800
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Ollikainen, Noah; Smith, Colin A.; Fraser, James S.; Kortemme, Tanja
2013-01-01
Sampling alternative conformations is key to understanding how proteins work and engineering them for new functions. However, accurately characterizing and modeling protein conformational ensembles remains experimentally and computationally challenging. These challenges must be met before protein conformational heterogeneity can be exploited in protein engineering and design. Here, as a stepping stone, we describe methods to detect alternative conformations in proteins and strategies to model these near-native conformational changes based on backrub-type Monte Carlo moves in Rosetta. We illustrate how Rosetta simulations that apply backrub moves improve modeling of point mutant side chain conformations, native side chain conformational heterogeneity, functional conformational changes, tolerated sequence space, protein interaction specificity, and amino acid co-variation across protein-protein interfaces. We include relevant Rosetta command lines and RosettaScripts to encourage the application of these types of simulations to other systems. Our work highlights that critical scoring and sampling improvements will be necessary to approximate conformational landscapes. Challenges for the future development of these methods include modeling conformational changes that propagate away from designed mutation sites and modulating backbone flexibility to predictively design functionally important conformational heterogeneity. PMID:23422426
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Bayesian refinement of protein structures and ensembles against SAXS data using molecular dynamics
Shevchuk, Roman; Hub, Jochen S.
2017-01-01
Small-angle X-ray scattering is an increasingly popular technique used to detect protein structures and ensembles in solution. However, the refinement of structures and ensembles against SAXS data is often ambiguous due to the low information content of SAXS data, unknown systematic errors, and unknown scattering contributions from the solvent. We offer a solution to such problems by combining Bayesian inference with all-atom molecular dynamics simulations and explicit-solvent SAXS calculations. The Bayesian formulation correctly weights the SAXS data versus prior physical knowledge, it quantifies the precision or ambiguity of fitted structures and ensembles, and it accounts for unknown systematic errors due to poor buffer matching. The method further provides a probabilistic criterion for identifying the number of states required to explain the SAXS data. The method is validated by refining ensembles of a periplasmic binding protein against calculated SAXS curves. Subsequently, we derive the solution ensembles of the eukaryotic chaperone heat shock protein 90 (Hsp90) against experimental SAXS data. We find that the SAXS data of the apo state of Hsp90 is compatible with a single wide-open conformation, whereas the SAXS data of Hsp90 bound to ATP or to an ATP-analogue strongly suggest heterogenous ensembles of a closed and a wide-open state. PMID:29045407
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Watts, Charles R; Gregory, Andrew; Frisbie, Cole; Lovas, Sándor
2018-03-01
The conformational space and structural ensembles of amyloid beta (Aβ) peptides and their oligomers in solution are inherently disordered and proven to be challenging to study. Optimum force field selection for molecular dynamics (MD) simulations and the biophysical relevance of results are still unknown. We compared the conformational space of the Aβ(1-40) dimers by 300 ns replica exchange MD simulations at physiological temperature (310 K) using: the AMBER-ff99sb-ILDN, AMBER-ff99sb*-ILDN, AMBER-ff99sb-NMR, and CHARMM22* force fields. Statistical comparisons of simulation results to experimental data and previously published simulations utilizing the CHARMM22* and CHARMM36 force fields were performed. All force fields yield sampled ensembles of conformations with collision cross sectional areas for the dimer that are statistically significantly larger than experimental results. All force fields, with the exception of AMBER-ff99sb-ILDN (8.8 ± 6.4%) and CHARMM36 (2.7 ± 4.2%), tend to overestimate the α-helical content compared to experimental CD (5.3 ± 5.2%). Using the AMBER-ff99sb-NMR force field resulted in the greatest degree of variance (41.3 ± 12.9%). Except for the AMBER-ff99sb-NMR force field, the others tended to under estimate the expected amount of β-sheet and over estimate the amount of turn/bend/random coil conformations. All force fields, with the exception AMBER-ff99sb-NMR, reproduce a theoretically expected β-sheet-turn-β-sheet conformational motif, however, only the CHARMM22* and CHARMM36 force fields yield results compatible with collapse of the central and C-terminal hydrophobic cores from residues 17-21 and 30-36. Although analyses of essential subspace sampling showed only minor variations between force fields, secondary structures of lowest energy conformers are different. © 2017 Wiley Periodicals, Inc.
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Zhang, Jian; Zhao, Xiaowei; Sun, Pingping; Gao, Bo; Ma, Zhiqiang
2014-01-01
B-cell epitopes are regions of the antigen surface which can be recognized by certain antibodies and elicit the immune response. Identification of epitopes for a given antigen chain finds vital applications in vaccine and drug research. Experimental prediction of B-cell epitopes is time-consuming and resource intensive, which may benefit from the computational approaches to identify B-cell epitopes. In this paper, a novel cost-sensitive ensemble algorithm is proposed for predicting the antigenic determinant residues and then a spatial clustering algorithm is adopted to identify the potential epitopes. Firstly, we explore various discriminative features from primary sequences. Secondly, cost-sensitive ensemble scheme is introduced to deal with imbalanced learning problem. Thirdly, we adopt spatial algorithm to tell which residues may potentially form the epitopes. Based on the strategies mentioned above, a new predictor, called CBEP (conformational B-cell epitopes prediction), is proposed in this study. CBEP achieves good prediction performance with the mean AUC scores (AUCs) of 0.721 and 0.703 on two benchmark datasets (bound and unbound) using the leave-one-out cross-validation (LOOCV). When compared with previous prediction tools, CBEP produces higher sensitivity and comparable specificity values. A web server named CBEP which implements the proposed method is available for academic use.
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Andrabi, Munazah; Hutchins, Andrew Paul; Miranda-Saavedra, Diego; Kono, Hidetoshi; Nussinov, Ruth; Mizuguchi, Kenji; Ahmad, Shandar
2017-06-22
DNA shape is emerging as an important determinant of transcription factor binding beyond just the DNA sequence. The only tool for large scale DNA shape estimates, DNAshape was derived from Monte-Carlo simulations and predicts four broad and static DNA shape features, Propeller twist, Helical twist, Minor groove width and Roll. The contributions of other shape features e.g. Shift, Slide and Opening cannot be evaluated using DNAshape. Here, we report a novel method DynaSeq, which predicts molecular dynamics-derived ensembles of a more exhaustive set of DNA shape features. We compared the DNAshape and DynaSeq predictions for the common features and applied both to predict the genome-wide binding sites of 1312 TFs available from protein interaction quantification (PIQ) data. The results indicate a good agreement between the two methods for the common shape features and point to advantages in using DynaSeq. Predictive models employing ensembles from individual conformational parameters revealed that base-pair opening - known to be important in strand separation - was the best predictor of transcription factor-binding sites (TFBS) followed by features employed by DNAshape. Of note, TFBS could be predicted not only from the features at the target motif sites, but also from those as far as 200 nucleotides away from the motif.
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Deshmukh, Lalit; Schwieters, Charles D; Grishaev, Alexander; Clore, G Marius
2016-06-03
Nucleic-acid-related events in the HIV-1 replication cycle are mediated by nucleocapsid, a small protein comprising two zinc knuckles connected by a short flexible linker and flanked by disordered termini. Combining experimental NMR residual dipolar couplings, solution X-ray scattering and protein engineering with ensemble simulated annealing, we obtain a quantitative description of the configurational space sampled by the two zinc knuckles, the linker and disordered termini in the absence of nucleic acids. We first compute the conformational ensemble (with an optimal size of three members) of an engineered nucleocapsid construct lacking the N- and C-termini that satisfies the experimental restraints, and then validate this ensemble, as well as characterize the disordered termini, using the experimental data from the full-length nucleocapsid construct. The experimental and computational strategy is generally applicable to multidomain proteins. Differential flexibility within the linker results in asymmetric motion of the zinc knuckles which may explain their functionally distinct roles despite high sequence identity. One of the configurations (populated at a level of ≈40 %) closely resembles that observed in various ligand-bound forms, providing evidence for conformational selection and a mechanistic link between protein dynamics and function. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Camilloni, Carlo; Robustelli, Paul; De Simone, Alfonso; Cavalli, Andrea; Vendruscolo, Michele
2012-03-07
Following the recognition that NMR chemical shifts can be used for protein structure determination, rapid advances have recently been made in methods for extending this strategy for proteins and protein complexes of increasing size and complexity. A remaining major challenge is to develop approaches to exploit the information contained in the chemical shifts about conformational fluctuations in native states of proteins. In this work we show that it is possible to determine an ensemble of conformations representing the free energy surface of RNase A using chemical shifts as replica-averaged restraints in molecular dynamics simulations. Analysis of this surface indicates that chemical shifts can be used to characterize the conformational equilibrium between the two major substates of this protein. © 2012 American Chemical Society
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NASA Astrophysics Data System (ADS)
Xu, Xianjin; Yan, Chengfei; Zou, Xiaoqin
2017-08-01
The growing number of protein-ligand complex structures, particularly the structures of proteins co-bound with different ligands, in the Protein Data Bank helps us tackle two major challenges in molecular docking studies: the protein flexibility and the scoring function. Here, we introduced a systematic strategy by using the information embedded in the known protein-ligand complex structures to improve both binding mode and binding affinity predictions. Specifically, a ligand similarity calculation method was employed to search a receptor structure with a bound ligand sharing high similarity with the query ligand for the docking use. The strategy was applied to the two datasets (HSP90 and MAP4K4) in recent D3R Grand Challenge 2015. In addition, for the HSP90 dataset, a system-specific scoring function (ITScore2_hsp90) was generated by recalibrating our statistical potential-based scoring function (ITScore2) using the known protein-ligand complex structures and the statistical mechanics-based iterative method. For the HSP90 dataset, better performances were achieved for both binding mode and binding affinity predictions comparing with the original ITScore2 and with ensemble docking. For the MAP4K4 dataset, although there were only eight known protein-ligand complex structures, our docking strategy achieved a comparable performance with ensemble docking. Our method for receptor conformational selection and iterative method for the development of system-specific statistical potential-based scoring functions can be easily applied to other protein targets that have a number of protein-ligand complex structures available to improve predictions on binding.
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Ensemble-based characterization of unbound and bound states on protein energy landscape
Ruvinsky, Anatoly M; Kirys, Tatsiana; Tuzikov, Alexander V; Vakser, Ilya A
2013-01-01
Physicochemical description of numerous cell processes is fundamentally based on the energy landscapes of protein molecules involved. Although the whole energy landscape is difficult to reconstruct, increased attention to particular targets has provided enough structures for mapping functionally important subspaces associated with the unbound and bound protein structures. The subspace mapping produces a discrete representation of the landscape, further called energy spectrum. We compiled and characterized ensembles of bound and unbound conformations of six small proteins and explored their spectra in implicit solvent. First, the analysis of the unbound-to-bound changes points to conformational selection as the binding mechanism for four proteins. Second, results show that bound and unbound spectra often significantly overlap. Moreover, the larger the overlap the smaller the root mean square deviation (RMSD) between the bound and unbound conformational ensembles. Third, the center of the unbound spectrum has a higher energy than the center of the corresponding bound spectrum of the dimeric and multimeric states for most of the proteins. This suggests that the unbound states often have larger entropy than the bound states. Fourth, the exhaustively long minimization, making small intrarotamer adjustments (all-atom RMSD ≤ 0.7 Å), dramatically reduces the distance between the centers of the bound and unbound spectra as well as the spectra extent. It condenses unbound and bound energy levels into a thin layer at the bottom of the energy landscape with the energy spacing that varies between 0.8–4.6 and 3.5–10.5 kcal/mol for the unbound and bound states correspondingly. Finally, the analysis of protein energy fluctuations showed that protein vibrations itself can excite the interstate transitions, including the unbound-to-bound ones. PMID:23526684
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Weighted Ensemble Simulation: Review of Methodology, Applications, and Software
Zuckerman, Daniel M.; Chong, Lillian T.
2018-01-01
The weighted ensemble (WE) methodology orchestrates quasi-independent parallel simulations run with intermittent communication that can enhance sampling of rare events such as protein conformational changes, folding, and binding. The WE strategy can achieve superlinear scaling—the unbiased estimation of key observables such as rate constants and equilibrium state populations to greater precision than would be possible with ordinary parallel simulation. WE software can be used to control any dynamics engine, such as standard molecular dynamics and cell-modeling packages. This article reviews the theoretical basis of WE and goes on to describe successful applications to a number of complex biological processes—protein conformational transitions, (un)binding, and assembly processes, as well as cell-scale processes in systems biology. We furthermore discuss the challenges that need to be overcome in the next phase of WE methodological development. Overall, the combined advances in WE methodology and software have enabled the simulation of long-timescale processes that would otherwise not be practical on typical computing resources using standard simulation. PMID:28301772
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Karp, Jerome M; Eryilmaz, Ertan; Erylimaz, Ertan; Cowburn, David
2015-01-01
There has been a longstanding interest in being able to accurately predict NMR chemical shifts from structural data. Recent studies have focused on using molecular dynamics (MD) simulation data as input for improved prediction. Here we examine the accuracy of chemical shift prediction for intein systems, which have regions of intrinsic disorder. We find that using MD simulation data as input for chemical shift prediction does not consistently improve prediction accuracy over use of a static X-ray crystal structure. This appears to result from the complex conformational ensemble of the disordered protein segments. We show that using accelerated molecular dynamics (aMD) simulations improves chemical shift prediction, suggesting that methods which better sample the conformational ensemble like aMD are more appropriate tools for use in chemical shift prediction for proteins with disordered regions. Moreover, our study suggests that data accurately reflecting protein dynamics must be used as input for chemical shift prediction in order to correctly predict chemical shifts in systems with disorder.
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Visualizing chaperone-assisted protein folding
Horowitz, Scott; Salmon, Loïc; Koldewey, Philipp; ...
2016-05-30
We present that challenges in determining the structures of heterogeneous and dynamic protein complexes have greatly hampered past efforts to obtain a mechanistic understanding of many important biological processes. One such process is chaperone-assisted protein folding. Obtaining structural ensembles of chaperone–substrate complexes would ultimately reveal how chaperones help proteins fold into their native state. To address this problem, we devised a new structural biology approach based on X-ray crystallography, termed residual electron and anomalous density (READ). READ enabled us to visualize even sparsely populated conformations of the substrate protein immunity protein 7 (Im7) in complex with the Escherichia coli chaperonemore » Spy, and to capture a series of snapshots depicting the various folding states of Im7 bound to Spy. The ensemble shows that Spy-associated Im7 samples conformations ranging from unfolded to partially folded to native-like states and reveals how a substrate can explore its folding landscape while being bound to a chaperone.« less
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Weighted Ensemble Simulation: Review of Methodology, Applications, and Software.
Zuckerman, Daniel M; Chong, Lillian T
2017-05-22
The weighted ensemble (WE) methodology orchestrates quasi-independent parallel simulations run with intermittent communication that can enhance sampling of rare events such as protein conformational changes, folding, and binding. The WE strategy can achieve superlinear scaling-the unbiased estimation of key observables such as rate constants and equilibrium state populations to greater precision than would be possible with ordinary parallel simulation. WE software can be used to control any dynamics engine, such as standard molecular dynamics and cell-modeling packages. This article reviews the theoretical basis of WE and goes on to describe successful applications to a number of complex biological processes-protein conformational transitions, (un)binding, and assembly processes, as well as cell-scale processes in systems biology. We furthermore discuss the challenges that need to be overcome in the next phase of WE methodological development. Overall, the combined advances in WE methodology and software have enabled the simulation of long-timescale processes that would otherwise not be practical on typical computing resources using standard simulation.
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Residue-Specific Side-Chain Polymorphisms via Particle Belief Propagation.
Ghoraie, Laleh Soltan; Burkowski, Forbes; Li, Shuai Cheng; Zhu, Mu
2014-01-01
Protein side chains populate diverse conformational ensembles in crystals. Despite much evidence that there is widespread conformational polymorphism in protein side chains, most of the X-ray crystallography data are modeled by single conformations in the Protein Data Bank. The ability to extract or to predict these conformational polymorphisms is of crucial importance, as it facilitates deeper understanding of protein dynamics and functionality. In this paper, we describe a computational strategy capable of predicting side-chain polymorphisms. Our approach extends a particular class of algorithms for side-chain prediction by modeling the side-chain dihedral angles more appropriately as continuous rather than discrete variables. Employing a new inferential technique known as particle belief propagation, we predict residue-specific distributions that encode information about side-chain polymorphisms. Our predicted polymorphisms are in relatively close agreement with results from a state-of-the-art approach based on X-ray crystallography data, which characterizes the conformational polymorphisms of side chains using electron density information, and has successfully discovered previously unmodeled conformations.
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UNICON: A Powerful and Easy-to-Use Compound Library Converter.
Sommer, Kai; Friedrich, Nils-Ole; Bietz, Stefan; Hilbig, Matthias; Inhester, Therese; Rarey, Matthias
2016-06-27
The accurate handling of different chemical file formats and the consistent conversion between them play important roles for calculations in complex cheminformatics workflows. Working with different cheminformatic tools often makes the conversion between file formats a mandatory step. Such a conversion might become a difficult task in cases where the information content substantially differs. This paper describes UNICON, an easy-to-use software tool for this task. The functionality of UNICON ranges from file conversion between standard formats SDF, MOL2, SMILES, PDB, and PDBx/mmCIF via the generation of 2D structure coordinates and 3D structures to the enumeration of tautomeric forms, protonation states, and conformer ensembles. For this purpose, UNICON bundles the key elements of the previously described NAOMI library in a single, easy-to-use command line tool.
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Conformational dynamics of amyloid proteins at the aqueous interface
NASA Astrophysics Data System (ADS)
Armbruster, Matthew; Horst, Nathan; Aoki, Brendy; Malik, Saad; Soto, Patricia
2013-03-01
Amyloid proteins is a class of proteins that exhibit distinct monomeric and oligomeric conformational states hallmark of deleterious neurological diseases for which there are not yet cures. Our goal is to examine the extent of which the aqueous/membrane interface modulates the folding energy landscape of amyloid proteins. To this end, we probe the dynamic conformational ensemble of amyloids (monomer prion protein and Alzheimer's Ab protofilaments) interacting with model bilayers. We will present the results of our coarse grain molecular modeling study in terms of the existence of preferential binding spots of the amyloid to the bilayer and the response of the bilayer to the interaction with the amyloid. NSF Nebraska EPSCoR First Award
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The interaction with gold suppresses fiber-like conformations of the amyloid β (16-22) peptide
NASA Astrophysics Data System (ADS)
Bellucci, Luca; Ardèvol, Albert; Parrinello, Michele; Lutz, Helmut; Lu, Hao; Weidner, Tobias; Corni, Stefano
2016-04-01
Inorganic surfaces and nanoparticles can accelerate or inhibit the fibrillation process of proteins and peptides, including the biomedically relevant amyloid β peptide. However, the microscopic mechanisms that determine such an effect are still poorly understood. By means of large-scale, state-of-the-art enhanced sampling molecular dynamics simulations, here we identify an interaction mechanism between the segments 16-22 of the amyloid β peptide, known to be fibrillogenic by itself, and the Au(111) surface in water that leads to the suppression of fiber-like conformations from the peptide conformational ensemble. Moreover, thanks to advanced simulation analysis techniques, we characterize the conformational selection vs. induced fit nature of the gold effect. Our results disclose an inhibition mechanism that is rooted in the details of the microscopic peptide-surface interaction rather than in general phenomena such as peptide sequestration from the solution.Inorganic surfaces and nanoparticles can accelerate or inhibit the fibrillation process of proteins and peptides, including the biomedically relevant amyloid β peptide. However, the microscopic mechanisms that determine such an effect are still poorly understood. By means of large-scale, state-of-the-art enhanced sampling molecular dynamics simulations, here we identify an interaction mechanism between the segments 16-22 of the amyloid β peptide, known to be fibrillogenic by itself, and the Au(111) surface in water that leads to the suppression of fiber-like conformations from the peptide conformational ensemble. Moreover, thanks to advanced simulation analysis techniques, we characterize the conformational selection vs. induced fit nature of the gold effect. Our results disclose an inhibition mechanism that is rooted in the details of the microscopic peptide-surface interaction rather than in general phenomena such as peptide sequestration from the solution. Electronic supplementary information (ESI) available: Representative structures for the most populated conformational structures of Aβ16-22 on bulk and on the metal surface. Normalized distribution of the variable s defined as the sum of internal dihedral angles of the peptide in solution and at the gold/water interface. See DOI: 10.1039/C6NR01539E
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Lim, Hojun; Abdeljawad, Fadi; Owen, Steven J.
Here, the mechanical properties of materials systems are highly influenced by various features at the microstructural level. The ability to capture these heterogeneities and incorporate them into continuum-scale frameworks of the deformation behavior is considered a key step in the development of complex non-local models of failure. In this study, we present a modeling framework that incorporates physically-based realizations of polycrystalline aggregates from a phase field (PF) model into a crystal plasticity finite element (CP-FE) framework. Simulated annealing via the PF model yields ensembles of materials microstructures with various grain sizes and shapes. With the aid of a novel FEmore » meshing technique, FE discretizations of these microstructures are generated, where several key features, such as conformity to interfaces, and triple junction angles, are preserved. The discretizations are then used in the CP-FE framework to simulate the mechanical response of polycrystalline α-iron. It is shown that the conformal discretization across interfaces reduces artificial stress localization commonly observed in non-conformal FE discretizations. The work presented herein is a first step towards incorporating physically-based microstructures in lieu of the overly simplified representations that are commonly used. In broader terms, the proposed framework provides future avenues to explore bridging models of materials processes, e.g. additive manufacturing and microstructure evolution of multi-phase multi-component systems, into continuum-scale frameworks of the mechanical properties.« less
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Lim, Hojun; Abdeljawad, Fadi; Owen, Steven J.; ...
2016-04-25
Here, the mechanical properties of materials systems are highly influenced by various features at the microstructural level. The ability to capture these heterogeneities and incorporate them into continuum-scale frameworks of the deformation behavior is considered a key step in the development of complex non-local models of failure. In this study, we present a modeling framework that incorporates physically-based realizations of polycrystalline aggregates from a phase field (PF) model into a crystal plasticity finite element (CP-FE) framework. Simulated annealing via the PF model yields ensembles of materials microstructures with various grain sizes and shapes. With the aid of a novel FEmore » meshing technique, FE discretizations of these microstructures are generated, where several key features, such as conformity to interfaces, and triple junction angles, are preserved. The discretizations are then used in the CP-FE framework to simulate the mechanical response of polycrystalline α-iron. It is shown that the conformal discretization across interfaces reduces artificial stress localization commonly observed in non-conformal FE discretizations. The work presented herein is a first step towards incorporating physically-based microstructures in lieu of the overly simplified representations that are commonly used. In broader terms, the proposed framework provides future avenues to explore bridging models of materials processes, e.g. additive manufacturing and microstructure evolution of multi-phase multi-component systems, into continuum-scale frameworks of the mechanical properties.« less
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Beckstein, Oliver; Denning, Elizabeth J.; Perilla, Juan R.; Woolf, Thomas B.
2009-01-01
Adenylate kinase (AdK), a phosphotransferase enzyme, plays an important role in cellular energy homeostasis. It undergoes a large conformational change between an open and a closed state, even in the absence of substrate. We investigate the apo-AdK transition at the atomic level both with free energy calculations and our new dynamic importance sampling (DIMS) molecular dynamics (MD) method. DIMS is shown to sample biologically relevant conformations as verified by comparing an ensemble of hundreds of DIMS transitions to AdK crystal structure intermediates. The simulations reveal in atomic detail how hinge regions partially and intermittently unfold during the transition. Conserved salt bridges are seen to have important structural and dynamic roles; in particular four ionic bonds are identified that open in a sequential, zipper-like fashion and thus dominate the free energy landscape of the transition. Transitions between the closed and open conformations only have to overcome moderate free energy barriers. Unexpectedly, the closed and open state encompass broad free energy basins that contain conformations differing in domain hinge motions by up to 40°. The significance of these extended states is discussed in relation to recent experimental FRET measurements. Taken together, these results demonstrate how a small number of cooperative key interactions can shape the overall dynamics of an enzyme and suggest an “all-or-nothing” mechanism for the opening and closing of AdK. Our efficient DIMS-MD computer simulation approach can provide a detailed picture of a functionally important macromolecular transition and thus help to interpret and suggest experiments to probe the conformational landscape of dynamic proteins such as AdK. PMID:19751742
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A critical analysis of computational protein design with sparse residue interaction graphs
Georgiev, Ivelin S.
2017-01-01
Protein design algorithms enumerate a combinatorial number of candidate structures to compute the Global Minimum Energy Conformation (GMEC). To efficiently find the GMEC, protein design algorithms must methodically reduce the conformational search space. By applying distance and energy cutoffs, the protein system to be designed can thus be represented using a sparse residue interaction graph, where the number of interacting residue pairs is less than all pairs of mutable residues, and the corresponding GMEC is called the sparse GMEC. However, ignoring some pairwise residue interactions can lead to a change in the energy, conformation, or sequence of the sparse GMEC vs. the original or the full GMEC. Despite the widespread use of sparse residue interaction graphs in protein design, the above mentioned effects of their use have not been previously analyzed. To analyze the costs and benefits of designing with sparse residue interaction graphs, we computed the GMECs for 136 different protein design problems both with and without distance and energy cutoffs, and compared their energies, conformations, and sequences. Our analysis shows that the differences between the GMECs depend critically on whether or not the design includes core, boundary, or surface residues. Moreover, neglecting long-range interactions can alter local interactions and introduce large sequence differences, both of which can result in significant structural and functional changes. Designs on proteins with experimentally measured thermostability show it is beneficial to compute both the full and the sparse GMEC accurately and efficiently. To this end, we show that a provable, ensemble-based algorithm can efficiently compute both GMECs by enumerating a small number of conformations, usually fewer than 1000. This provides a novel way to combine sparse residue interaction graphs with provable, ensemble-based algorithms to reap the benefits of sparse residue interaction graphs while avoiding their potential inaccuracies. PMID:28358804
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Gomes, Gregory-Neal; Gradinaru, Claudiu C
2017-11-01
Most proteins are not static structures, but many of them are found in a dynamic state, exchanging conformations on various time scales as a key aspect of their biological function. An entire spectrum of structural disorder exists in proteins and obtaining a satisfactory quantitative description of these states remains a challenge. Single-molecule fluorescence spectroscopy techniques are uniquely suited for this task, by measuring conformations without ensemble averaging and kinetics without interference from asynchronous processes. In this paper we review some of the recent successes in applying single-molecule fluorescence to different disordered protein systems, including interactions with their cellular targets and self-aggregation processes. We also discuss the implementation of computational methods and polymer physics models that are essential for inferring global dimension parameters for these proteins from smFRET data. Regarding future directions; 3- or 4-color FRET methods can provide multiple distances within a disordered ensemble simultaneously. In addition, integrating complementary experimental data from smFRET, NMR and SAXS will provide meaningful constraints for molecular simulations and will lead to more accurate structural representations of disordered proteins. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman. Copyright © 2017 Elsevier B.V. All rights reserved.
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The role of protein homochirality in shaping the energy landscape of folding
Nanda, Vikas; Andrianarijaona, Aina; Narayanan, Chitra
2007-01-01
The homochirality, or isotacticity, of the natural amino acids facilitates the formation of regular secondary structures such as α-helices and β-sheets. However, many examples exist in nature where novel polypeptide topologies use both l- and d-amino acids. In this study, we explore how stereochemistry of the polypeptide backbone influences basic properties such as compactness and the size of fold space by simulating both lattice and all-atom polypeptide chains. We formulate a rectangular lattice chain model in both two and three dimensions, where monomers are chiral, having the effect of restricting local conformation. Syndiotactic chains with alternating chirality of adjacent monomers have a very large ensemble of accessible conformations characterized predominantly by extended structures. Isotactic chains on the other hand, have far fewer possible conformations and a significant fraction of these are compact. Syndiotactic chains are often unable to access maximally compact states available to their isotactic counterparts of the same length. Similar features are observed in all-atom models of isotactic versus syndiotactic polyalanine. Our results suggest that protein isotacticity has evolved to increase the enthalpy of chain collapse by facilitating compact helical states and to reduce the entropic cost of folding by restricting the size of the unfolded ensemble of competing states. PMID:17600146
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Bhatt, Divesh; Zuckerman, Daniel M.
2010-01-01
We performed “weighted ensemble” path–sampling simulations of adenylate kinase, using several semi–atomistic protein models. The models have an all–atom backbone with various levels of residue interactions. The primary result is that full statistically rigorous path sampling required only a few weeks of single–processor computing time with these models, indicating the addition of further chemical detail should be readily feasible. Our semi–atomistic path ensembles are consistent with previous biophysical findings: the presence of two distinct pathways, identification of intermediates, and symmetry of forward and reverse pathways. PMID:21660120
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Yonezawa, Yasushige
2014-05-01
The carboxyl-terminal domain (CTD) of RNA polymerase II in eukaryotes regulates mRNA processing processes by recruiting various regulation factors. A main function of the CTD relies on the heptad consensus sequence (YSPTSPS). The CTD dynamically changes its conformational state to recognize and bind different regulation factors. The dynamical conformation changes are caused by modifications, mainly phosphorylation and dephosphorylation, to the serine residues. In this study, we investigate the conformational states of the unit consensus CTD peptide with various phosphorylation patterns of the serine residues by extended ensemble simulations. The results show that the CTD without phosphorylation has a flexible disordered structure distributed between twisted and extended states, but phosphorylation tends to reduce the conformational space. It was found that phosphorylation induces a β-turn around the phosphorylated serine residue and the cis conformation of the proline residue significantly inhibits the β-turn formation. The β-turn should contribute to specific CTD binding of the different regulation factors by changing the conformation propensity combined with induced fit.
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Sekhar, Ashok; Kay, Lewis E
2013-08-06
The importance of dynamics to biomolecular function is becoming increasingly clear. A description of the structure-function relationship must, therefore, include the role of motion, requiring a shift in paradigm from focus on a single static 3D picture to one where a given biomolecule is considered in terms of an ensemble of interconverting conformers, each with potentially diverse activities. In this Perspective, we describe how recent developments in solution NMR spectroscopy facilitate atomic resolution studies of sparsely populated, transiently formed biomolecular conformations that exchange with the native state. Examples of how this methodology is applied to protein folding and misfolding, ligand binding, and molecular recognition are provided as a means of illustrating both the power of the new techniques and the significant roles that conformationally excited protein states play in biology.
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Entanglement between two spatially separated atomic modes
NASA Astrophysics Data System (ADS)
Lange, Karsten; Peise, Jan; Lücke, Bernd; Kruse, Ilka; Vitagliano, Giuseppe; Apellaniz, Iagoba; Kleinmann, Matthias; Tóth, Géza; Klempt, Carsten
2018-04-01
Modern quantum technologies in the fields of quantum computing, quantum simulation, and quantum metrology require the creation and control of large ensembles of entangled particles. In ultracold ensembles of neutral atoms, nonclassical states have been generated with mutual entanglement among thousands of particles. The entanglement generation relies on the fundamental particle-exchange symmetry in ensembles of identical particles, which lacks the standard notion of entanglement between clearly definable subsystems. Here, we present the generation of entanglement between two spatially separated clouds by splitting an ensemble of ultracold identical particles prepared in a twin Fock state. Because the clouds can be addressed individually, our experiments open a path to exploit the available entangled states of indistinguishable particles for quantum information applications.
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NASA Astrophysics Data System (ADS)
Shen, Feifei; Xu, Dongmei; Xue, Ming; Min, Jinzhong
2017-07-01
This study examines the impacts of assimilating radar radial velocity (Vr) data for the simulation of hurricane Ike (2008) with two different ensemble generation techniques in the framework of the hybrid ensemble-variational (EnVar) data assimilation system of Weather Research and Forecasting model. For the generation of ensemble perturbations we apply two techniques, the ensemble transform Kalman filter (ETKF) and the ensemble of data assimilation (EDA). For the ETKF-EnVar, the forecast ensemble perturbations are updated by the ETKF, while for the EDA-EnVar, the hybrid is employed to update each ensemble member with perturbed observations. The ensemble mean is analyzed by the hybrid method with flow-dependent ensemble covariance for both EnVar. The sensitivity of analyses and forecasts to the two applied ensemble generation techniques is investigated in our current study. It is found that the EnVar system is rather stable with different ensemble update techniques in terms of its skill on improving the analyses and forecasts. The EDA-EnVar-based ensemble perturbations are likely to include slightly less organized spatial structures than those in ETKF-EnVar, and the perturbations of the latter are constructed more dynamically. Detailed diagnostics reveal that both of the EnVar schemes not only produce positive temperature increments around the hurricane center but also systematically adjust the hurricane location with the hurricane-specific error covariance. On average, the analysis and forecast from the ETKF-EnVar have slightly smaller errors than that from the EDA-EnVar in terms of track, intensity, and precipitation forecast. Moreover, ETKF-EnVar yields better forecasts when verified against conventional observations.
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Gantner, Melisa E; Peroni, Roxana N; Morales, Juan F; Villalba, María L; Ruiz, María E; Talevi, Alan
2017-08-28
Breast Cancer Resistance Protein (BCRP) is an ATP-dependent efflux transporter linked to the multidrug resistance phenomenon in many diseases such as epilepsy and cancer and a potential source of drug interactions. For these reasons, the early identification of substrates and nonsubstrates of this transporter during the drug discovery stage is of great interest. We have developed a computational nonlinear model ensemble based on conformational independent molecular descriptors using a combined strategy of genetic algorithms, J48 decision tree classifiers, and data fusion. The best model ensemble consists in averaging the ranking of the 12 decision trees that showed the best performance on the training set, which also demonstrated a good performance for the test set. It was experimentally validated using the ex vivo everted rat intestinal sac model. Five anticonvulsant drugs classified as nonsubstrates for BRCP by the model ensemble were experimentally evaluated, and none of them proved to be a BCRP substrate under the experimental conditions used, thus confirming the predictive ability of the model ensemble. The model ensemble reported here is a potentially valuable tool to be used as an in silico ADME filter in computer-aided drug discovery campaigns intended to overcome BCRP-mediated multidrug resistance issues and to prevent drug-drug interactions.
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Nekouzadeh, Ali; Rudy, Yoram
2016-01-01
Ion channels are the "building blocks" of the excitation process in excitable tissues. Despite advances in determining their molecular structure, understanding the relationship between channel protein structure and electrical excitation remains a challenge. The Kv7.1 potassium channel is an important determinant of the cardiac action potential and its adaptation to rate changes. It is subject to beta adrenergic regulation, and many mutations in the channel protein are associated with the arrhythmic long QT syndrome. In this theoretical study, we use a novel computational approach to simulate the conformational changes that Kv7.1 undergoes during activation gating and compute the resulting electrophysiologic function in terms of single-channel and macroscopic currents. We generated all possible conformations of the S4-S5 linker that couples the S3-S4 complex (voltage sensor domain, VSD) to the pore, and all associated conformations of VSD and the pore (S6). Analysis of these conformations revealed that VSD-to-pore mechanical coupling during activation gating involves outward translation of the voltage sensor, accompanied by a translation away from the pore and clockwise twist. These motions cause pore opening by moving the S4-S5 linker upward and away from the pore, providing space for the S6 tails to move away from each other. Single channel records, computed from the simulated motion trajectories during gating, have stochastic properties similar to experimentally recorded traces. Macroscopic current through an ensemble of channels displays two key properties of Kv7.1: an initial delay of activation and fast inactivation. The simulations suggest a molecular mechanism for fast inactivation; a large twist of the VSD following its outward translation results in movement of the base of the S4-S5 linker toward the pore, eliminating open pore conformations to cause inactivation. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
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Warfield, Becka M.
2017-01-01
RNA aptamers are oligonucleotides that bind with high specificity and affinity to target ligands. In the absence of bound ligand, secondary structures of RNA aptamers are generally stable, but single-stranded and loop regions, including ligand binding sites, lack defined structures and exist as ensembles of conformations. For example, the well-characterized theophylline-binding aptamer forms a highly stable binding site when bound to theophylline, but the binding site is unstable and disordered when theophylline is absent. Experimental methods have not revealed at atomic resolution the conformations that the theophylline aptamer explores in its unbound state. Consequently, in the present study we applied 21 microseconds of molecular dynamics simulations to structurally characterize the ensemble of conformations that the aptamer adopts in the absence of theophylline. Moreover, we apply Markov state modeling to predict the kinetics of transitions between unbound conformational states. Our simulation results agree with experimental observations that the theophylline binding site is found in many distinct binding-incompetent states and show that these states lack a binding pocket that can accommodate theophylline. The binding-incompetent states interconvert with binding-competent states through structural rearrangement of the binding site on the nanosecond to microsecond timescale. Moreover, we have simulated the complete theophylline binding pathway. Our binding simulations supplement prior experimental observations of slow theophylline binding kinetics by showing that the binding site must undergo a large conformational rearrangement after the aptamer and theophylline form an initial complex, most notably, a major rearrangement of the C27 base from a buried to solvent-exposed orientation. Theophylline appears to bind by a combination of conformational selection and induced fit mechanisms. Finally, our modeling indicates that when Mg2+ ions are present the population of binding-competent aptamer states increases more than twofold. This population change, rather than direct interactions between Mg2+ and theophylline, accounts for altered theophylline binding kinetics. PMID:28437473
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Argumentation Based Joint Learning: A Novel Ensemble Learning Approach
Xu, Junyi; Yao, Li; Li, Le
2015-01-01
Recently, ensemble learning methods have been widely used to improve classification performance in machine learning. In this paper, we present a novel ensemble learning method: argumentation based multi-agent joint learning (AMAJL), which integrates ideas from multi-agent argumentation, ensemble learning, and association rule mining. In AMAJL, argumentation technology is introduced as an ensemble strategy to integrate multiple base classifiers and generate a high performance ensemble classifier. We design an argumentation framework named Arena as a communication platform for knowledge integration. Through argumentation based joint learning, high quality individual knowledge can be extracted, and thus a refined global knowledge base can be generated and used independently for classification. We perform numerous experiments on multiple public datasets using AMAJL and other benchmark methods. The results demonstrate that our method can effectively extract high quality knowledge for ensemble classifier and improve the performance of classification. PMID:25966359
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On the generation of climate model ensembles
NASA Astrophysics Data System (ADS)
Haughton, Ned; Abramowitz, Gab; Pitman, Andy; Phipps, Steven J.
2014-10-01
Climate model ensembles are used to estimate uncertainty in future projections, typically by interpreting the ensemble distribution for a particular variable probabilistically. There are, however, different ways to produce climate model ensembles that yield different results, and therefore different probabilities for a future change in a variable. Perhaps equally importantly, there are different approaches to interpreting the ensemble distribution that lead to different conclusions. Here we use a reduced-resolution climate system model to compare three common ways to generate ensembles: initial conditions perturbation, physical parameter perturbation, and structural changes. Despite these three approaches conceptually representing very different categories of uncertainty within a modelling system, when comparing simulations to observations of surface air temperature they can be very difficult to separate. Using the twentieth century CMIP5 ensemble for comparison, we show that initial conditions ensembles, in theory representing internal variability, significantly underestimate observed variance. Structural ensembles, perhaps less surprisingly, exhibit over-dispersion in simulated variance. We argue that future climate model ensembles may need to include parameter or structural perturbation members in addition to perturbed initial conditions members to ensure that they sample uncertainty due to internal variability more completely. We note that where ensembles are over- or under-dispersive, such as for the CMIP5 ensemble, estimates of uncertainty need to be treated with care.
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Discretized torsional dynamics and the folding of an RNA chain.
Fernández, A; Salthú, R; Cendra, H
1999-08-01
The aim of this work is to implement a discrete coarse codification of local torsional states of the RNA chain backbone in order to explore the long-time limit dynamics and ultimately obtain a coarse solution to the RNA folding problem. A discrete representation of the soft-mode dynamics is turned into an algorithm for a rough structure prediction. The algorithm itself is inherently parallel, as it evaluates concurrent folding possibilities by pattern recognition, but it may be implemented in a personal computer as a chain of perturbation-translation-renormalization cycles performed on a binary matrix of local topological constraints. This requires suitable representational tools and a periodic quenching of the dynamics for system renormalization. A binary coding of local topological constraints associated with each structural motif is introduced, with each local topological constraint corresponding to a local torsional state. This treatment enables us to adopt a computation time step far larger than hydrodynamic drag time scales. Accordingly, the solvent is no longer treated as a hydrodynamic drag medium. Instead we incorporate its capacity for forming local conformation-dependent dielectric domains. Each translation of the matrix of local topological constraints (LTM's) depends on the conformation-dependent local dielectric created by a confined solvent. Folding pathways are resolved as transitions between patterns of locally encoded structural signals which change within the 1 ns-100 ms time scale range. These coarse folding pathways are generated by a search at regular intervals for structural patterns in the LTM. Each pattern is recorded as a base-pairing pattern (BPP) matrix, a consensus-evaluation operation subject to a renormalization feedback loop. Since several mutually conflicting consensus evaluations might occur at a given time, the need arises for a probabilistic approach appropriate for an ensemble of RNA molecules. Thus, a statistical dynamics of consensus formation is determined by the time evolution of the base pairing probability matrix. These dynamics are generated for a functional RNA molecule, a representative of the so-called group I ribozymes, in order to test the model. The resulting ensemble of conformations is sharply peaked and the most probable structure features the predominance of all phylogenetically conserved intrachain helices tantamount to ribozyme function. Furthermore, the magnesium-aided cooperativity that leads to the shaping of the catalytic core is elucidated. Once the predictive folding algorithm has been implemented, the validity of the so-called "adiabatic approximation" is tested. This approximation requires that conformational microstates be lumped up into BPP's which are treated as quasiequilibrium states, while folding pathways are coarsely represented as sequences of BPP transitions. To test the validity of this adiabatic ansatz, a computation of the coarse Shannon information entropy sigma associated to the specific partition of conformation space into BPP's is performed taking into account the LTM evolution and contrasted with the adiabatic computation. The results reveal a subordination of torsional microstate dynamics to BPP transitions within time scales relevant to folding. This adiabatic entrainment in the long-time limit is thus identified as responsible for the expediency of the folding process.
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Single-Molecule Spectroscopy and Imaging Studies of Protein Dynamics
NASA Astrophysics Data System (ADS)
Lu, H. Peter
2012-04-01
Enzymatic reactions and protein-protein interactions are traditionally studied at the ensemble level, despite significant static and dynamic inhomogeneities. Subtle conformational changes play a crucial role in protein functions, and these protein conformations are highly dynamic rather than being static. We applied AFM-enhanced single-molecule spectroscopy to study the mechanisms and dynamics of enzymatic reactions involved with kinase and lysozyme proteins. Enzymatic reaction turnovers and the associated structure changes of individual protein molecules were observed simultaneously in real-time by single-molecule FRET detections. Our single-molecule spectroscopy measurements of T4 lysozyme and HPPK enzymatic conformational dynamics have revealed time bunching effect and intermittent coherence in conformational state change dynamics involving in enzymatic reaction cycles. The coherent conformational state dynamics suggests that the enzymatic catalysis involves a multi-step conformational motion along the coordinates of substrate-enzyme complex formation and product releasing, presenting as an extreme dynamic behavior intrinsically related to the time bunching effect that we have reported previously. Our results of HPPK interaction with substrate support a multiple-conformational state model, being consistent with a complementary conformation selection and induced-fit enzymatic loop-gated conformational change mechanism in substrate-enzyme active complex formation. Our new approach is applicable to a wide range of single-molecule FRET measurements for protein conformational changes under enzymatic reactions.
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Multi-model analysis in hydrological prediction
NASA Astrophysics Data System (ADS)
Lanthier, M.; Arsenault, R.; Brissette, F.
2017-12-01
Hydrologic modelling, by nature, is a simplification of the real-world hydrologic system. Therefore ensemble hydrological predictions thus obtained do not present the full range of possible streamflow outcomes, thereby producing ensembles which demonstrate errors in variance such as under-dispersion. Past studies show that lumped models used in prediction mode can return satisfactory results, especially when there is not enough information available on the watershed to run a distributed model. But all lumped models greatly simplify the complex processes of the hydrologic cycle. To generate more spread in the hydrologic ensemble predictions, multi-model ensembles have been considered. In this study, the aim is to propose and analyse a method that gives an ensemble streamflow prediction that properly represents the forecast probabilities and reduced ensemble bias. To achieve this, three simple lumped models are used to generate an ensemble. These will also be combined using multi-model averaging techniques, which generally generate a more accurate hydrogram than the best of the individual models in simulation mode. This new predictive combined hydrogram is added to the ensemble, thus creating a large ensemble which may improve the variability while also improving the ensemble mean bias. The quality of the predictions is then assessed on different periods: 2 weeks, 1 month, 3 months and 6 months using a PIT Histogram of the percentiles of the real observation volumes with respect to the volumes of the ensemble members. Initially, the models were run using historical weather data to generate synthetic flows. This worked for individual models, but not for the multi-model and for the large ensemble. Consequently, by performing data assimilation at each prediction period and thus adjusting the initial states of the models, the PIT Histogram could be constructed using the observed flows while allowing the use of the multi-model predictions. The under-dispersion has been largely corrected on short-term predictions. For the longer term, the addition of the multi-model member has been beneficial to the quality of the predictions, although it is too early to determine whether the gain is related to the addition of a member or if multi-model member has plus-value itself.
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Computational prediction of atomic structures of helical membrane proteins aided by EM maps.
Kovacs, Julio A; Yeager, Mark; Abagyan, Ruben
2007-09-15
Integral membrane proteins pose a major challenge for protein-structure prediction because only approximately 100 high-resolution structures are available currently, thereby impeding the development of rules or empirical potentials to predict the packing of transmembrane alpha-helices. However, when an intermediate-resolution electron microscopy (EM) map is available, it can be used to provide restraints which, in combination with a suitable computational protocol, make structure prediction feasible. In this work we present such a protocol, which proceeds in three stages: 1), generation of an ensemble of alpha-helices by flexible fitting into each of the density rods in the low-resolution EM map, spanning a range of rotational angles around the main helical axes and translational shifts along the density rods; 2), fast optimization of side chains and scoring of the resulting conformations; and 3), refinement of the lowest-scoring conformations with internal coordinate mechanics, by optimizing the van der Waals, electrostatics, hydrogen bonding, torsional, and solvation energy contributions. In addition, our method implements a penalty term through a so-called tethering map, derived from the EM map, which restrains the positions of the alpha-helices. The protocol was validated on three test cases: GpA, KcsA, and MscL.
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Solution structural ensembles of substrate-free cytochrome P450(cam).
Asciutto, Eliana K; Young, Matthew J; Madura, Jeffry; Pochapsky, Susan Sondej; Pochapsky, Thomas C
2012-04-24
Removal of substrate (+)-camphor from the active site of cytochrome P450(cam) (CYP101A1) results in nuclear magnetic resonance-detected perturbations in multiple regions of the enzyme. The (1)H-(15)N correlation map of substrate-free diamagnetic Fe(II) CO-bound CYP101A permits these perturbations to be mapped onto the solution structure of the enzyme. Residual dipolar couplings (RDCs) were measured for (15)N-(1)H amide pairs in two independent alignment media for the substrate-free enzyme and used as restraints in solvated molecular dynamics (MD) simulations to generate an ensemble of best-fit structures of the substrate-free enzyme in solution. Nuclear magnetic resonance-detected chemical shift perturbations reflect changes in the electronic environment of the NH pairs, such as hydrogen bonding and ring current shifts, and are observed for residues in the active site as well as in hinge regions between secondary structural features. RDCs provide information about relative orientations of secondary structures, and RDC-restrained MD simulations indicate that portions of a β-rich region adjacent to the active site shift so as to partially occupy the vacancy left by removal of the substrate. The accessible volume of the active site is reduced in the substrate-free enzyme relative to the substrate-bound structure calculated using the same methods. Both symmetric and asymmetric broadening of multiple resonances observed upon substrate removal as well as localized increased errors in RDC fits suggest that an ensemble of enzyme conformations are present in the substrate-free form.
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NASA Astrophysics Data System (ADS)
Ou, Jiemei; Yang, Yuzhao; Lin, Wensheng; Yuan, Zhongke; Gan, Lin; Lin, Xiaofeng; Chen, Xudong; Chen, Yujie
2015-03-01
We investigated the transitions of conformations and their effects on emission properties of poly[2-methoxy-5-(2'-ethyl-hexyloxy)-1,4-phenylene vinylene] (MEH-PPV) single molecules in PMMA matrix during thermal annealing process. Total internal reflection fluorescence microscopy measurements reveal the transformation from collapsed conformations to extended, highly ordered rod-like structures of MEH-PPV single molecules during thermal annealing. The blue shifts in the ensemble single molecule PL spectra support our hypnosis. The transition occurs as the annealing temperature exceeds 100 °C, implying that an annealing temperature near the glass transition temperature Tg of matrix is ideal for the control and optimization of blend polymer films.
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Correlation in photon pairs generated using four-wave mixing in a cold atomic ensemble
NASA Astrophysics Data System (ADS)
Ferdinand, Andrew Richard; Manjavacas, Alejandro; Becerra, Francisco Elohim
2017-04-01
Spontaneous four-wave mixing (FWM) in atomic ensembles can be used to generate narrowband entangled photon pairs at or near atomic resonances. While extensive research has been done to investigate the quantum correlations in the time and polarization of such photon pairs, the study and control of high dimensional quantum correlations contained in their spatial degrees of freedom has not been fully explored. In our work we experimentally investigate the generation of correlated light from FWM in a cold ensemble of cesium atoms as a function of the frequencies of the pump fields in the FWM process. In addition, we theoretically study the spatial correlations of the photon pairs generated in the FWM process, specifically the joint distribution of their orbital angular momentum (OAM). We investigate the width of the distribution of the OAM modes, known as the spiral bandwidth, and the purity of OAM correlations as a function of the properties of the pump fields, collected photons, and the atomic ensemble. These studies will guide experiments involving high dimensional entanglement of photons generated from this FWM process and OAM-based quantum communication with atomic ensembles. This work is supported by AFORS Grant FA9550-14-1-0300.
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Model Independence in Downscaled Climate Projections: a Case Study in the Southeast United States
NASA Astrophysics Data System (ADS)
Gray, G. M. E.; Boyles, R.
2016-12-01
Downscaled climate projections are used to deduce how the climate will change in future decades at local and regional scales. It is important to use multiple models to characterize part of the future uncertainty given the impact on adaptation decision making. This is traditionally employed through an equally-weighted ensemble of multiple GCMs downscaled using one technique. Newer practices include several downscaling techniques in an effort to increase the ensemble's representation of future uncertainty. However, this practice may be adding statistically dependent models to the ensemble. Previous research has shown a dependence problem in the GCM ensemble in multiple generations, but has not been shown in the downscaled ensemble. In this case study, seven downscaled climate projections on the daily time scale are considered: CLAREnCE10, SERAP, BCCA (CMIP5 and CMIP3 versions), Hostetler, CCR, and MACA-LIVNEH. These data represent 83 ensemble members, 44 GCMs, and two generations of GCMs. Baseline periods are compared against the University of Idaho's METDATA gridded observation dataset. Hierarchical agglomerative clustering is applied to the correlated errors to determine dependent clusters. Redundant GCMs across different downscaling techniques show the most dependence, while smaller dependence signals are detected within downscaling datasets and across generations of GCMs. These results indicate that using additional downscaled projections to increase the ensemble size must be done with care to avoid redundant GCMs and the process of downscaling may increase the dependence of those downscaled GCMs. Climate model generation does not appear dissimilar enough to be treated as two separate statistical populations for ensemble building at the local and regional scales.
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Residue-level global and local ensemble-ensemble comparisons of protein domains.
Clark, Sarah A; Tronrud, Dale E; Karplus, P Andrew
2015-09-01
Many methods of protein structure generation such as NMR-based solution structure determination and template-based modeling do not produce a single model, but an ensemble of models consistent with the available information. Current strategies for comparing ensembles lose information because they use only a single representative structure. Here, we describe the ENSEMBLATOR and its novel strategy to directly compare two ensembles containing the same atoms to identify significant global and local backbone differences between them on per-atom and per-residue levels, respectively. The ENSEMBLATOR has four components: eePREP (ee for ensemble-ensemble), which selects atoms common to all models; eeCORE, which identifies atoms belonging to a cutoff-distance dependent common core; eeGLOBAL, which globally superimposes all models using the defined core atoms and calculates for each atom the two intraensemble variations, the interensemble variation, and the closest approach of members of the two ensembles; and eeLOCAL, which performs a local overlay of each dipeptide and, using a novel measure of local backbone similarity, reports the same four variations as eeGLOBAL. The combination of eeGLOBAL and eeLOCAL analyses identifies the most significant differences between ensembles. We illustrate the ENSEMBLATOR's capabilities by showing how using it to analyze NMR ensembles and to compare NMR ensembles with crystal structures provides novel insights compared to published studies. One of these studies leads us to suggest that a "consistency check" of NMR-derived ensembles may be a useful analysis step for NMR-based structure determinations in general. The ENSEMBLATOR 1.0 is available as a first generation tool to carry out ensemble-ensemble comparisons. © 2015 The Protein Society.
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Residue-level global and local ensemble-ensemble comparisons of protein domains
Clark, Sarah A; Tronrud, Dale E; Andrew Karplus, P
2015-01-01
Many methods of protein structure generation such as NMR-based solution structure determination and template-based modeling do not produce a single model, but an ensemble of models consistent with the available information. Current strategies for comparing ensembles lose information because they use only a single representative structure. Here, we describe the ENSEMBLATOR and its novel strategy to directly compare two ensembles containing the same atoms to identify significant global and local backbone differences between them on per-atom and per-residue levels, respectively. The ENSEMBLATOR has four components: eePREP (ee for ensemble-ensemble), which selects atoms common to all models; eeCORE, which identifies atoms belonging to a cutoff-distance dependent common core; eeGLOBAL, which globally superimposes all models using the defined core atoms and calculates for each atom the two intraensemble variations, the interensemble variation, and the closest approach of members of the two ensembles; and eeLOCAL, which performs a local overlay of each dipeptide and, using a novel measure of local backbone similarity, reports the same four variations as eeGLOBAL. The combination of eeGLOBAL and eeLOCAL analyses identifies the most significant differences between ensembles. We illustrate the ENSEMBLATOR's capabilities by showing how using it to analyze NMR ensembles and to compare NMR ensembles with crystal structures provides novel insights compared to published studies. One of these studies leads us to suggest that a “consistency check” of NMR-derived ensembles may be a useful analysis step for NMR-based structure determinations in general. The ENSEMBLATOR 1.0 is available as a first generation tool to carry out ensemble-ensemble comparisons. PMID:26032515
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Kingsley, Laura J.; Lill, Markus A.
2014-01-01
Computational prediction of ligand entry and egress paths in proteins has become an emerging topic in computational biology and has proven useful in fields such as protein engineering and drug design. Geometric tunnel prediction programs, such as Caver3.0 and MolAxis, are computationally efficient methods to identify potential ligand entry and egress routes in proteins. Although many geometric tunnel programs are designed to accommodate a single input structure, the increasingly recognized importance of protein flexibility in tunnel formation and behavior has led to the more widespread use of protein ensembles in tunnel prediction. However, there has not yet been an attempt to directly investigate the influence of ensemble size and composition on geometric tunnel prediction. In this study, we compared tunnels found in a single crystal structure to ensembles of various sizes generated using different methods on both the apo and holo forms of cytochrome P450 enzymes CYP119, CYP2C9, and CYP3A4. Several protein structure clustering methods were tested in an attempt to generate smaller ensembles that were capable of reproducing the data from larger ensembles. Ultimately, we found that by including members from both the apo and holo data sets, we could produce ensembles containing less than 15 members that were comparable to apo or holo ensembles containing over 100 members. Furthermore, we found that, in the absence of either apo or holo crystal structure data, pseudo-apo or –holo ensembles (e.g. adding ligand to apo protein throughout MD simulations) could be used to resemble the structural ensembles of the corresponding apo and holo ensembles, respectively. Our findings not only further highlight the importance of including protein flexibility in geometric tunnel prediction, but also suggest that smaller ensembles can be as capable as larger ensembles at capturing many of the protein motions important for tunnel prediction at a lower computational cost. PMID:24956479
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Carlacci, Louis; Millard, Charles B; Olson, Mark A
2004-10-01
The X-ray crystal structure of the reaction product of acetylcholinesterase (AChE) with the inhibitor diisopropylphosphorofluoridate (DFP) showed significant structural displacement in a loop segment of residues 287-290. To understand this conformational selection, a Monte Carlo (MC) simulation study was performed of the energy landscape for the loop segment. A computational strategy was applied by using a combined simulated annealing and room temperature Metropolis sampling approach with solvent polarization modeled by a generalized Born (GB) approximation. Results from thermal annealing reveal a landscape topology of broader basin opening and greater distribution of energies for the displaced loop conformation, while the ensemble average of conformations at 298 K favored a shift in populations toward the native by a free-energy difference in good agreement with the estimated experimental value. Residue motions along a reaction profile of loop conformational reorganization are proposed where Arg-289 is critical in determining electrostatic effects of solvent interaction versus Coulombic charging.
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Xia, Junchao; Case, David A.
2012-01-01
We report 100 ns molecular dynamics simulations, at various temperatures, of sucrose in water (with concentrations of sucrose ranging from 0.02 to 4 M), and in a 7:3 water-DMSO mixture. Convergence of the resulting conformational ensembles was checked using adaptive-biased simulations along the glycosidic φ and ψ torsion angles. NMR relaxation parameters, including longitudinal (R1) and transverse (R2) relaxation rates, nuclear Overhauser enhancements (NOE), and generalized order parameter (S2) were computed from the resulting time-correlation functions. The amplitude and time scales of molecular motions change with temperature and concentration in ways that track closely with experimental results, and are consistent with a model in which sucrose conformational fluctuations are limited (with 80–90% of the conformations having φ – ψ values within 20° of an average conformation), but with some important differences in conformation between pure water and DMSO-water mixtures. PMID:22058066
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Efficient Simulation of Explicitly Solvated Proteins in the Well-Tempered Ensemble.
Deighan, Michael; Bonomi, Massimiliano; Pfaendtner, Jim
2012-07-10
Herein, we report significant reduction in the cost of combined parallel tempering and metadynamics simulations (PTMetaD). The efficiency boost is achieved using the recently proposed well-tempered ensemble (WTE) algorithm. We studied the convergence of PTMetaD-WTE conformational sampling and free energy reconstruction of an explicitly solvated 20-residue tryptophan-cage protein (trp-cage). A set of PTMetaD-WTE simulations was compared to a corresponding standard PTMetaD simulation. The properties of PTMetaD-WTE and the convergence of the calculations were compared. The roles of the number of replicas, total simulation time, and adjustable WTE parameter γ were studied.
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NASA Astrophysics Data System (ADS)
Yin, Dong-shan; Gao, Yu-ping; Zhao, Shu-hong
2017-07-01
Millisecond pulsars can generate another type of time scale that is totally independent of the atomic time scale, because the physical mechanisms of the pulsar time scale and the atomic time scale are quite different from each other. Usually the pulsar timing observations are not evenly sampled, and the internals between two data points range from several hours to more than half a month. Further more, these data sets are sparse. All this makes it difficult to generate an ensemble pulsar time scale. Hence, a new algorithm to calculate the ensemble pulsar time scale is proposed. Firstly, a cubic spline interpolation is used to densify the data set, and make the intervals between data points uniform. Then, the Vondrak filter is employed to smooth the data set, and get rid of the high-frequency noises, and finally the weighted average method is adopted to generate the ensemble pulsar time scale. The newly released NANOGRAV (North American Nanohertz Observatory for Gravitational Waves) 9-year data set is used to generate the ensemble pulsar time scale. This data set includes the 9-year observational data of 37 millisecond pulsars observed by the 100-meter Green Bank telescope and the 305-meter Arecibo telescope. It is found that the algorithm used in this paper can reduce effectively the influence caused by the noises in pulsar timing residuals, and improve the long-term stability of the ensemble pulsar time scale. Results indicate that the long-term (> 1 yr) stability of the ensemble pulsar time scale is better than 3.4 × 10-15.
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Elucidating Ligand-Modulated Conformational Landscape of GPCRs Using Cloud-Computing Approaches.
Shukla, Diwakar; Lawrenz, Morgan; Pande, Vijay S
2015-01-01
G-protein-coupled receptors (GPCRs) are a versatile family of membrane-bound signaling proteins. Despite the recent successes in obtaining crystal structures of GPCRs, much needs to be learned about the conformational changes associated with their activation. Furthermore, the mechanism by which ligands modulate the activation of GPCRs has remained elusive. Molecular simulations provide a way of obtaining detailed an atomistic description of GPCR activation dynamics. However, simulating GPCR activation is challenging due to the long timescales involved and the associated challenge of gaining insights from the "Big" simulation datasets. Here, we demonstrate how cloud-computing approaches have been used to tackle these challenges and obtain insights into the activation mechanism of GPCRs. In particular, we review the use of Markov state model (MSM)-based sampling algorithms for sampling milliseconds of dynamics of a major drug target, the G-protein-coupled receptor β2-AR. MSMs of agonist and inverse agonist-bound β2-AR reveal multiple activation pathways and how ligands function via modulation of the ensemble of activation pathways. We target this ensemble of conformations with computer-aided drug design approaches, with the goal of designing drugs that interact more closely with diverse receptor states, for overall increased efficacy and specificity. We conclude by discussing how cloud-based approaches present a powerful and broadly available tool for studying the complex biological systems routinely. © 2015 Elsevier Inc. All rights reserved.
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Chakraborty, Sandipan; Ramachandran, Balaji; Basu, Soumalee
2014-10-01
Mimicking receptor flexibility during receptor-ligand binding is a challenging task in computational drug design since it is associated with a large increase in the conformational search space. In the present study, we have devised an in silico design strategy incorporating receptor flexibility in virtual screening to identify potential lead compounds as inhibitors for flexible proteins. We have considered BACE1 (β-secretase), a key target protease from a therapeutic perspective for Alzheimer's disease, as the highly flexible receptor. The protein undergoes significant conformational transitions from open to closed form upon ligand binding, which makes it a difficult target for inhibitor design. We have designed a hybrid structure-activity model containing both ligand based descriptors and energetic descriptors obtained from molecular docking based on a dataset of structurally diverse BACE1 inhibitors. An ensemble of receptor conformations have been used in the docking study, further improving the prediction ability of the model. The designed model that shows significant prediction ability judged by several statistical parameters has been used to screen an in house developed 3-D structural library of 731 phytochemicals. 24 highly potent, novel BACE1 inhibitors with predicted activity (Ki) ≤ 50 nM have been identified. Detailed analysis reveals pharmacophoric features of these novel inhibitors required to inhibit BACE1.
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Joseph, Prem Raj B.; Sawant, Kirti V.; Isley, Angela; Pedroza, Mesias; Garofalo, Roberto P.; Richardson, Ricardo M.; Rajarathnam, Krishna
2014-01-01
Chemokines mediate diverse functions from organogenesis to mobilizing leucocytes, and are unusual agonists for class-A GPCRs (G-protein-coupled receptors) because of their large size and multi-domain structure. The current model for receptor activation, which involves interactions between chemokine N-loop and receptor N-terminal residues (Site-I) and between chemokine N-terminal and receptor extracellular loop/transmembrane residues (Site-II), fails to describe differences in ligand/receptor selectivity and the activation of multiple signalling pathways. In the present study, we show in neutrophil-activating chemokine CXCL8 that the highly conserved GP (glycine-proline) motif located distal to both N-terminal and N-loop residues couples Site-I and Site-II interactions. Mutations in the GP motif caused various differences from native-like function to complete loss of activity that could not be correlated with the specific mutation, receptor affinity or subtype, or a specific signalling pathway. NMR studies indicated that the GP motif does not influence Site-I interactions, but molecular dynamics simulations suggested that this motif dictates substates of the CXCL8 conformational ensemble. We conclude that the GP motif enables diverse receptor functions by controlling cross-talk between Site-I and Site-II, and further propose that the repertoire of chemokine functions is best described by a conformational ensemble model in which a network of long-range coupled indirect interactions mediate receptor activity. PMID:24032673
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Gestalt Effects in Visual Working Memory.
Kałamała, Patrycja; Sadowska, Aleksandra; Ordziniak, Wawrzyniec; Chuderski, Adam
2017-01-01
Four experiments investigated whether conforming to Gestalt principles, well known to drive visual perception, also facilitates the active maintenance of information in visual working memory (VWM). We used the change detection task, which required the memorization of visual patterns composed of several shapes. We observed no effects of symmetry of visual patterns on VWM performance. However, there was a moderate positive effect when a particular shape that was probed matched the shape of the whole pattern (the whole-part similarity effect). Data support the models assuming that VWM encodes not only particular objects of the perceptual scene but also the spatial relations between them (the ensemble representation). The ensemble representation may prime objects similar to its shape and thereby boost access to them. In contrast, the null effect of symmetry relates the fact that this very feature of an ensemble does not yield any useful additional information for VWM.
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ERIC Educational Resources Information Center
Lawrence, Sarah H.; Jaffe, Eileen K.
2008-01-01
A morpheein is a homo-oligomeric protein that can exist as an ensemble of physiologically significant and functionally distinct alternate quaternary assemblies. Morpheeins exist in nature and use conformational equilibria between different tertiary structures to form distinct oligomers as a means of regulating their function. Notably, alternate…
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Pettersson, John R; Lanni, Frederick; Rule, Gordon S
2017-08-08
Single-molecule fluorescence techniques were used to characterize the binding of products and inhibitors to human glutathione S-transferase A1-1 (hGSTA1-1). The identification of at least two different bound states for the wild-type enzyme suggests that there are at least two conformations of the protein, consistent with the model that ligand binding promotes closure of the carboxy-terminal helix over the active site. Ligand induced changes in ensemble fluorescence energy transfer support this proposed structural change. The more predominant state in the ensemble of single molecules shows a significantly faster off-rate, suggesting that the carboxy-terminal helix is delocalized in this state, permitting faster exit of the bound ligand. A point mutation (I219A), which is known to interfere with the association of the carboxy-terminal helix with the enzyme, shows increased rates of interconversion between the open and closed state. Kinematic traces of fluorescence from single molecules show that a single molecule readily samples a number of different conformations, each with a characteristic off-rate.
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Hyde, Eva I; Callow, Philip; Rajasekar, Karthik V; Timmins, Peter; Patel, Trushar R; Siligardi, Giuliano; Hussain, Rohanah; White, Scott A; Thomas, Christopher M; Scott, David J
2017-08-30
The ParB protein, KorB, from the RK2 plasmid is required for DNA partitioning and transcriptional repression. It acts co-operatively with other proteins, including the repressor KorA. Like many multifunctional proteins, KorB contains regions of intrinsically disordered structure, existing in a large ensemble of interconverting conformations. Using NMR spectroscopy, circular dichroism and small-angle neutron scattering, we studied KorB selectively within its binary complexes with KorA and DNA, and within the ternary KorA/KorB/DNA complex. The bound KorB protein remains disordered with a mobile C-terminal domain and no changes in the secondary structure, but increases in the radius of gyration on complex formation. Comparison of wild-type KorB with an N-terminal deletion mutant allows a model of the ensemble average distances between the domains when bound to DNA. We propose that the positive co-operativity between KorB, KorA and DNA results from conformational restriction of KorB on binding each partner, while maintaining disorder. © 2017 The Author(s).
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Improving RNA nearest neighbor parameters for helices by going beyond the two-state model.
Spasic, Aleksandar; Berger, Kyle D; Chen, Jonathan L; Seetin, Matthew G; Turner, Douglas H; Mathews, David H
2018-06-01
RNA folding free energy change nearest neighbor parameters are widely used to predict folding stabilities of secondary structures. They were determined by linear regression to datasets of optical melting experiments on small model systems. Traditionally, the optical melting experiments are analyzed assuming a two-state model, i.e. a structure is either complete or denatured. Experimental evidence, however, shows that structures exist in an ensemble of conformations. Partition functions calculated with existing nearest neighbor parameters predict that secondary structures can be partially denatured, which also directly conflicts with the two-state model. Here, a new approach for determining RNA nearest neighbor parameters is presented. Available optical melting data for 34 Watson-Crick helices were fit directly to a partition function model that allows an ensemble of conformations. Fitting parameters were the enthalpy and entropy changes for helix initiation, terminal AU pairs, stacks of Watson-Crick pairs and disordered internal loops. The resulting set of nearest neighbor parameters shows a 38.5% improvement in the sum of residuals in fitting the experimental melting curves compared to the current literature set.
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Heisel, Kurt A.; Krishnan, V. V.
2014-01-01
The conformational preference of a peptide with three phenylalanine-glycine (FG) repeats from the intrinsically disordered domain of nucleoporin 159 (nup159) from the yeast nucleopore complex (NPC) is studied. Conformational states of this FG-peptide in dimethyl sulfoxide (DMSO), a non-native solvent are first studied. A solvent exchange scheme is designed and performed to understand how the conformational preferences of the peptide are altered as the solvent shifts from DMSO to water. An ensemble of structures of a 19-residue peptide is determined based on 13Cα, 1Hα, and 1HN chemical shifts and with inter-proton distances. An experimental model is then presented where chemical shifts and amide-proton temperature dependence is probed at changing DMSO to water ratios. These co-solvent experiments provide evidence of a conformational change as the fraction of water increases by the stark change in the behavior of amide protons under varied temperature. This investigation provides a NMR based experimental method in the field of intrinsically disordered proteins to realize conformational transitions from a non-native set of structures (in DMSO) to a native set of disordered conformers (in water). PMID:24037535
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Structural alphabets derived from attractors in conformational space
2010-01-01
Background The hierarchical and partially redundant nature of protein structures justifies the definition of frequently occurring conformations of short fragments as 'states'. Collections of selected representatives for these states define Structural Alphabets, describing the most typical local conformations within protein structures. These alphabets form a bridge between the string-oriented methods of sequence analysis and the coordinate-oriented methods of protein structure analysis. Results A Structural Alphabet has been derived by clustering all four-residue fragments of a high-resolution subset of the protein data bank and extracting the high-density states as representative conformational states. Each fragment is uniquely defined by a set of three independent angles corresponding to its degrees of freedom, capturing in simple and intuitive terms the properties of the conformational space. The fragments of the Structural Alphabet are equivalent to the conformational attractors and therefore yield a most informative encoding of proteins. Proteins can be reconstructed within the experimental uncertainty in structure determination and ensembles of structures can be encoded with accuracy and robustness. Conclusions The density-based Structural Alphabet provides a novel tool to describe local conformations and it is specifically suitable for application in studies of protein dynamics. PMID:20170534
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Reid, Korey M; Sunanda, Punnepalli; Raghothama, S; Krishnan, V V
2017-11-01
Intrinsically disordered proteins (IDP) lack a well-defined 3D-structure under physiological conditions, yet, the inherent disorder represented by an ensemble of conformation plays a critical role in many cellular and regulatory processes. Nucleoporins, or Nups, are the proteins found in the nuclear pore complex (NPC). The central pore of the NPC is occupied by Nups, which have phenylalanine-glycine domain repeats and are intrinsically disordered, and therefore are termed FG-Nups. These FG-domain repeats exhibit differing cohesiveness character and differ from least (FG) to most (GLFG) cohesive. The designed FG-Nup is a 25 AA model peptide containing a noncohesive FG-motif flanked by two cohesive GLFG-motifs (WT peptide). Complete NMR-based ensemble characterization of this peptide along with a control peptide with an F>A substitution (MU peptide) are discussed. Ensemble characterization of the NMR-determined models suggests that both the peptides do not have consistent secondary structures and continue to be disordered. Nonetheless, the role of cohesive elements mediated by the GLFG motifs is evident in the WT ensemble of structures that are more compact than the MU peptide. The approach presented here allows an alternate way to investigate the specific roles of distinct amino acid motifs that translate into the long-range organization of the ensemble of structures and in general on the nature of IDPs. © 2017 Wiley Periodicals, Inc.
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NASA Astrophysics Data System (ADS)
Khajehei, Sepideh; Moradkhani, Hamid
2015-04-01
Producing reliable and accurate hydrologic ensemble forecasts are subject to various sources of uncertainty, including meteorological forcing, initial conditions, model structure, and model parameters. Producing reliable and skillful precipitation ensemble forecasts is one approach to reduce the total uncertainty in hydrological applications. Currently, National Weather Prediction (NWP) models are developing ensemble forecasts for various temporal ranges. It is proven that raw products from NWP models are biased in mean and spread. Given the above state, there is a need for methods that are able to generate reliable ensemble forecasts for hydrological applications. One of the common techniques is to apply statistical procedures in order to generate ensemble forecast from NWP-generated single-value forecasts. The procedure is based on the bivariate probability distribution between the observation and single-value precipitation forecast. However, one of the assumptions of the current method is fitting Gaussian distribution to the marginal distributions of observed and modeled climate variable. Here, we have described and evaluated a Bayesian approach based on Copula functions to develop an ensemble precipitation forecast from the conditional distribution of single-value precipitation forecasts. Copula functions are known as the multivariate joint distribution of univariate marginal distributions, which are presented as an alternative procedure in capturing the uncertainties related to meteorological forcing. Copulas are capable of modeling the joint distribution of two variables with any level of correlation and dependency. This study is conducted over a sub-basin in the Columbia River Basin in USA using the monthly precipitation forecasts from Climate Forecast System (CFS) with 0.5x0.5 Deg. spatial resolution to reproduce the observations. The verification is conducted on a different period and the superiority of the procedure is compared with Ensemble Pre-Processor approach currently used by National Weather Service River Forecast Centers in USA.
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Multi-objective optimization for generating a weighted multi-model ensemble
NASA Astrophysics Data System (ADS)
Lee, H.
2017-12-01
Many studies have demonstrated that multi-model ensembles generally show better skill than each ensemble member. When generating weighted multi-model ensembles, the first step is measuring the performance of individual model simulations using observations. There is a consensus on the assignment of weighting factors based on a single evaluation metric. When considering only one evaluation metric, the weighting factor for each model is proportional to a performance score or inversely proportional to an error for the model. While this conventional approach can provide appropriate combinations of multiple models, the approach confronts a big challenge when there are multiple metrics under consideration. When considering multiple evaluation metrics, it is obvious that a simple averaging of multiple performance scores or model ranks does not address the trade-off problem between conflicting metrics. So far, there seems to be no best method to generate weighted multi-model ensembles based on multiple performance metrics. The current study applies the multi-objective optimization, a mathematical process that provides a set of optimal trade-off solutions based on a range of evaluation metrics, to combining multiple performance metrics for the global climate models and their dynamically downscaled regional climate simulations over North America and generating a weighted multi-model ensemble. NASA satellite data and the Regional Climate Model Evaluation System (RCMES) software toolkit are used for assessment of the climate simulations. Overall, the performance of each model differs markedly with strong seasonal dependence. Because of the considerable variability across the climate simulations, it is important to evaluate models systematically and make future projections by assigning optimized weighting factors to the models with relatively good performance. Our results indicate that the optimally weighted multi-model ensemble always shows better performance than an arithmetic ensemble mean and may provide reliable future projections.
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CABS-flex predictions of protein flexibility compared with NMR ensembles
Jamroz, Michal; Kolinski, Andrzej; Kmiecik, Sebastian
2014-01-01
Motivation: Identification of flexible regions of protein structures is important for understanding of their biological functions. Recently, we have developed a fast approach for predicting protein structure fluctuations from a single protein model: the CABS-flex. CABS-flex was shown to be an efficient alternative to conventional all-atom molecular dynamics (MD). In this work, we evaluate CABS-flex and MD predictions by comparison with protein structural variations within NMR ensembles. Results: Based on a benchmark set of 140 proteins, we show that the relative fluctuations of protein residues obtained from CABS-flex are well correlated to those of NMR ensembles. On average, this correlation is stronger than that between MD and NMR ensembles. In conclusion, CABS-flex is useful and complementary to MD in predicting protein regions that undergo conformational changes as well as the extent of such changes. Availability and implementation: The CABS-flex is freely available to all users at http://biocomp.chem.uw.edu.pl/CABSflex. Contact: sekmi@chem.uw.edu.pl Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24735558
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CABS-flex predictions of protein flexibility compared with NMR ensembles.
Jamroz, Michal; Kolinski, Andrzej; Kmiecik, Sebastian
2014-08-01
Identification of flexible regions of protein structures is important for understanding of their biological functions. Recently, we have developed a fast approach for predicting protein structure fluctuations from a single protein model: the CABS-flex. CABS-flex was shown to be an efficient alternative to conventional all-atom molecular dynamics (MD). In this work, we evaluate CABS-flex and MD predictions by comparison with protein structural variations within NMR ensembles. Based on a benchmark set of 140 proteins, we show that the relative fluctuations of protein residues obtained from CABS-flex are well correlated to those of NMR ensembles. On average, this correlation is stronger than that between MD and NMR ensembles. In conclusion, CABS-flex is useful and complementary to MD in predicting protein regions that undergo conformational changes as well as the extent of such changes. The CABS-flex is freely available to all users at http://biocomp.chem.uw.edu.pl/CABSflex. sekmi@chem.uw.edu.pl Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.
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Funar-Timofei, Simona; Borota, Ana; Crisan, Luminita
2017-05-01
Cinnoline, pyridine, pyrimidine, and triazine herbicides were found be inhibitors of the D1 protein in photosystem II (D1 PSII) electron transport of plants. The photosystem II inhibitory activity of these herbicides, expressed by experimental [Formula: see text] values, was modeled by a docking and quantitative structure-activity relationships study. A conformer ensemble for each of the herbicide structure was generated using the MMFF94s force field. These conformers were further employed in a docking approach, which provided new information about the rational "active conformations" and various interaction patterns of the herbicide derivatives with D1 PSII. The most "active conformers" from the docking study were used to calculate structural descriptors, which were further related to the inhibitory experimental [Formula: see text] values by multiple linear regression (MLR). The dataset was divided into training and test sets according to the partition around medoids approach, taking 27% of the compounds from the entire series for the test set. Variable selection was performed using the genetic algorithm, and several criteria were checked for model performance. WHIM and GETAWAY geometrical descriptors (position of substituents and moieties in the molecular space) were found to contribute to the herbicidal activity. The derived MLR model is statistically significant, shows very good stability and was used to predict the herbicidal activity of new derivatives having cinnoline, indeno[1.2-c]cinnoline-ll-one, triazolo[1,5-a] pyridine, imidazo[1,2-a]pyridine, triazine and triazolo[1,5-a] pyrimidine scaffolds whose experimental inhibitory activity against D1 PSII had not been determined up to now.
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Uchikoga, Nobuyuki; Hirokawa, Takatsugu
2010-05-11
Protein-protein docking for proteins with large conformational changes was analyzed by using interaction fingerprints, one of the scales for measuring similarities among complex structures, utilized especially for searching near-native protein-ligand or protein-protein complex structures. Here, we have proposed a combined method for analyzing protein-protein docking by taking large conformational changes into consideration. This combined method consists of ensemble soft docking with multiple protein structures, refinement of complexes, and cluster analysis using interaction fingerprints and energy profiles. To test for the applicability of this combined method, various CaM-ligand complexes were reconstructed from the NMR structures of unbound CaM. For the purpose of reconstruction, we used three known CaM-ligands, namely, the CaM-binding peptides of cyclic nucleotide gateway (CNG), CaM kinase kinase (CaMKK) and the plasma membrane Ca2+ ATPase pump (PMCA), and thirty-one structurally diverse CaM conformations. For each ligand, 62000 CaM-ligand complexes were generated in the docking step and the relationship between their energy profiles and structural similarities to the native complex were analyzed using interaction fingerprint and RMSD. Near-native clusters were obtained in the case of CNG and CaMKK. The interaction fingerprint method discriminated near-native structures better than the RMSD method in cluster analysis. We showed that a combined method that includes the interaction fingerprint is very useful for protein-protein docking analysis of certain cases.
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Towards an improved ensemble precipitation forecast: A probabilistic post-processing approach
NASA Astrophysics Data System (ADS)
Khajehei, Sepideh; Moradkhani, Hamid
2017-03-01
Recently, ensemble post-processing (EPP) has become a commonly used approach for reducing the uncertainty in forcing data and hence hydrologic simulation. The procedure was introduced to build ensemble precipitation forecasts based on the statistical relationship between observations and forecasts. More specifically, the approach relies on a transfer function that is developed based on a bivariate joint distribution between the observations and the simulations in the historical period. The transfer function is used to post-process the forecast. In this study, we propose a Bayesian EPP approach based on copula functions (COP-EPP) to improve the reliability of the precipitation ensemble forecast. Evaluation of the copula-based method is carried out by comparing the performance of the generated ensemble precipitation with the outputs from an existing procedure, i.e. mixed type meta-Gaussian distribution. Monthly precipitation from Climate Forecast System Reanalysis (CFS) and gridded observation from Parameter-Elevation Relationships on Independent Slopes Model (PRISM) have been employed to generate the post-processed ensemble precipitation. Deterministic and probabilistic verification frameworks are utilized in order to evaluate the outputs from the proposed technique. Distribution of seasonal precipitation for the generated ensemble from the copula-based technique is compared to the observation and raw forecasts for three sub-basins located in the Western United States. Results show that both techniques are successful in producing reliable and unbiased ensemble forecast, however, the COP-EPP demonstrates considerable improvement in the ensemble forecast in both deterministic and probabilistic verification, in particular in characterizing the extreme events in wet seasons.
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Hybrid fuzzy cluster ensemble framework for tumor clustering from biomolecular data.
Yu, Zhiwen; Chen, Hantao; You, Jane; Han, Guoqiang; Li, Le
2013-01-01
Cancer class discovery using biomolecular data is one of the most important tasks for cancer diagnosis and treatment. Tumor clustering from gene expression data provides a new way to perform cancer class discovery. Most of the existing research works adopt single-clustering algorithms to perform tumor clustering is from biomolecular data that lack robustness, stability, and accuracy. To further improve the performance of tumor clustering from biomolecular data, we introduce the fuzzy theory into the cluster ensemble framework for tumor clustering from biomolecular data, and propose four kinds of hybrid fuzzy cluster ensemble frameworks (HFCEF), named as HFCEF-I, HFCEF-II, HFCEF-III, and HFCEF-IV, respectively, to identify samples that belong to different types of cancers. The difference between HFCEF-I and HFCEF-II is that they adopt different ensemble generator approaches to generate a set of fuzzy matrices in the ensemble. Specifically, HFCEF-I applies the affinity propagation algorithm (AP) to perform clustering on the sample dimension and generates a set of fuzzy matrices in the ensemble based on the fuzzy membership function and base samples selected by AP. HFCEF-II adopts AP to perform clustering on the attribute dimension, generates a set of subspaces, and obtains a set of fuzzy matrices in the ensemble by performing fuzzy c-means on subspaces. Compared with HFCEF-I and HFCEF-II, HFCEF-III and HFCEF-IV consider the characteristics of HFCEF-I and HFCEF-II. HFCEF-III combines HFCEF-I and HFCEF-II in a serial way, while HFCEF-IV integrates HFCEF-I and HFCEF-II in a concurrent way. HFCEFs adopt suitable consensus functions, such as the fuzzy c-means algorithm or the normalized cut algorithm (Ncut), to summarize generated fuzzy matrices, and obtain the final results. The experiments on real data sets from UCI machine learning repository and cancer gene expression profiles illustrate that 1) the proposed hybrid fuzzy cluster ensemble frameworks work well on real data sets, especially biomolecular data, and 2) the proposed approaches are able to provide more robust, stable, and accurate results when compared with the state-of-the-art single clustering algorithms and traditional cluster ensemble approaches.
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Design of an Evolutionary Approach for Intrusion Detection
2013-01-01
A novel evolutionary approach is proposed for effective intrusion detection based on benchmark datasets. The proposed approach can generate a pool of noninferior individual solutions and ensemble solutions thereof. The generated ensembles can be used to detect the intrusions accurately. For intrusion detection problem, the proposed approach could consider conflicting objectives simultaneously like detection rate of each attack class, error rate, accuracy, diversity, and so forth. The proposed approach can generate a pool of noninferior solutions and ensembles thereof having optimized trade-offs values of multiple conflicting objectives. In this paper, a three-phase, approach is proposed to generate solutions to a simple chromosome design in the first phase. In the first phase, a Pareto front of noninferior individual solutions is approximated. In the second phase of the proposed approach, the entire solution set is further refined to determine effective ensemble solutions considering solution interaction. In this phase, another improved Pareto front of ensemble solutions over that of individual solutions is approximated. The ensemble solutions in improved Pareto front reported improved detection results based on benchmark datasets for intrusion detection. In the third phase, a combination method like majority voting method is used to fuse the predictions of individual solutions for determining prediction of ensemble solution. Benchmark datasets, namely, KDD cup 1999 and ISCX 2012 dataset, are used to demonstrate and validate the performance of the proposed approach for intrusion detection. The proposed approach can discover individual solutions and ensemble solutions thereof with a good support and a detection rate from benchmark datasets (in comparison with well-known ensemble methods like bagging and boosting). In addition, the proposed approach is a generalized classification approach that is applicable to the problem of any field having multiple conflicting objectives, and a dataset can be represented in the form of labelled instances in terms of its features. PMID:24376390
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Keedy, Daniel A.; Fraser, James S.; van den Bedem, Henry
Proteins must move between different conformations of their native ensemble to perform their functions. Crystal structures obtained from high-resolution X-ray diffraction data reflect this heterogeneity as a spatial and temporal conformational average. Although movement between natively populated alternative conformations can be critical for characterizing molecular mechanisms, it is challenging to identify these conformations within electron density maps. Alternative side chain conformations are generally well separated into distinct rotameric conformations, but alternative backbone conformations can overlap at several atomic positions. Our model building program qFit uses mixed integer quadratic programming (MIQP) to evaluate an extremely large number of combinations of sidechainmore » conformers and backbone fragments to locally explain the electron density. Here, we describe two major modeling enhancements to qFit: peptide flips and alternative glycine conformations. We find that peptide flips fall into four stereotypical clusters and are enriched in glycine residues at the n+1 position. The potential for insights uncovered by new peptide flips and glycine conformations is exemplified by HIV protease, where different inhibitors are associated with peptide flips in the “flap” regions adjacent to the inhibitor binding site. Our results paint a picture of peptide flips as conformational switches, often enabled by glycine flexibility, that result in dramatic local rearrangements. Our results furthermore demonstrate the power of large-scale computational analysis to provide new insights into conformational heterogeneity. Furthermore, improved modeling of backbone heterogeneity with high-resolution X-ray data will connect dynamics to the structure-function relationship and help drive new design strategies for inhibitors of biomedically important systems.« less
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Oliveira, Roberta B; Pereira, Aledir S; Tavares, João Manuel R S
2017-10-01
The number of deaths worldwide due to melanoma has risen in recent times, in part because melanoma is the most aggressive type of skin cancer. Computational systems have been developed to assist dermatologists in early diagnosis of skin cancer, or even to monitor skin lesions. However, there still remains a challenge to improve classifiers for the diagnosis of such skin lesions. The main objective of this article is to evaluate different ensemble classification models based on input feature manipulation to diagnose skin lesions. Input feature manipulation processes are based on feature subset selections from shape properties, colour variation and texture analysis to generate diversity for the ensemble models. Three subset selection models are presented here: (1) a subset selection model based on specific feature groups, (2) a correlation-based subset selection model, and (3) a subset selection model based on feature selection algorithms. Each ensemble classification model is generated using an optimum-path forest classifier and integrated with a majority voting strategy. The proposed models were applied on a set of 1104 dermoscopic images using a cross-validation procedure. The best results were obtained by the first ensemble classification model that generates a feature subset ensemble based on specific feature groups. The skin lesion diagnosis computational system achieved 94.3% accuracy, 91.8% sensitivity and 96.7% specificity. The input feature manipulation process based on specific feature subsets generated the greatest diversity for the ensemble classification model with very promising results. Copyright © 2017 Elsevier B.V. All rights reserved.
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Ensemble Bayesian forecasting system Part I: Theory and algorithms
NASA Astrophysics Data System (ADS)
Herr, Henry D.; Krzysztofowicz, Roman
2015-05-01
The ensemble Bayesian forecasting system (EBFS), whose theory was published in 2001, is developed for the purpose of quantifying the total uncertainty about a discrete-time, continuous-state, non-stationary stochastic process such as a time series of stages, discharges, or volumes at a river gauge. The EBFS is built of three components: an input ensemble forecaster (IEF), which simulates the uncertainty associated with random inputs; a deterministic hydrologic model (of any complexity), which simulates physical processes within a river basin; and a hydrologic uncertainty processor (HUP), which simulates the hydrologic uncertainty (an aggregate of all uncertainties except input). It works as a Monte Carlo simulator: an ensemble of time series of inputs (e.g., precipitation amounts) generated by the IEF is transformed deterministically through a hydrologic model into an ensemble of time series of outputs, which is next transformed stochastically by the HUP into an ensemble of time series of predictands (e.g., river stages). Previous research indicated that in order to attain an acceptable sampling error, the ensemble size must be on the order of hundreds (for probabilistic river stage forecasts and probabilistic flood forecasts) or even thousands (for probabilistic stage transition forecasts). The computing time needed to run the hydrologic model this many times renders the straightforward simulations operationally infeasible. This motivates the development of the ensemble Bayesian forecasting system with randomization (EBFSR), which takes full advantage of the analytic meta-Gaussian HUP and generates multiple ensemble members after each run of the hydrologic model; this auxiliary randomization reduces the required size of the meteorological input ensemble and makes it operationally feasible to generate a Bayesian ensemble forecast of large size. Such a forecast quantifies the total uncertainty, is well calibrated against the prior (climatic) distribution of predictand, possesses a Bayesian coherence property, constitutes a random sample of the predictand, and has an acceptable sampling error-which makes it suitable for rational decision making under uncertainty.
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NASA Astrophysics Data System (ADS)
Reyers, Mark; Moemken, Julia; Pinto, Joaquim; Feldmann, Hendrik; Kottmeier, Christoph; MiKlip Module-C Team
2017-04-01
Decadal climate predictions can provide a useful basis for decision making support systems for the public and private sectors. Several generations of decadal hindcasts and predictions have been generated throughout the German research program MiKlip. Together with the global climate predictions computed with MPI-ESM, the regional climate model (RCM) COSMO-CLM is used for regional downscaling by MiKlip Module-C. The RCMs provide climate information on spatial and temporal scales closer to the needs of potential users. In this study, two downscaled hindcast generations are analysed (named b0 and b1). The respective global generations are both initialized by nudging them towards different reanalysis anomaly fields. An ensemble of five starting years (1961, 1971, 1981, 1991, and 2001), each comprising ten ensemble members, is used for both generations in order to quantify the regional decadal prediction skill for precipitation and near-surface temperature and wind speed over Europe. All datasets (including hindcasts, observations, reanalysis, and historical MPI-ESM runs) are pre-processed in an analogue manner by (i) removing the long-term trend and (ii) re-gridding to a common grid. Our analysis shows that there is potential for skillful decadal predictions over Europe in the regional MiKlip ensemble, but the skill is not systematic and depends on the PRUDENCE region and the variable. Further, the differences between the two hindcast generations are mostly small. As we used detrended time series, the predictive skill found in our study can probably attributed to reasonable predictions of anomalies which are associated with the natural climate variability. In a sensitivity study, it is shown that the results may strongly change when the long-term trend is kept in the datasets, as here the skill of predicting the long-term trend (e.g. for temperature) also plays a major role. The regionalization of the global ensemble provides an added value for decadal predictions for some complex regions like the Mediterranean and Iberian Peninsula, while for other regions no systematic improvement is found. A clear dependence of the performance of the regional MiKlip system on the ensemble size is detected. For all variables in both hindcast generations, the skill increases when the ensemble is enlarged. The results indicate that a number of ten members is an appropriate ensemble size for decadal predictions over Europe.
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Sugimoto, Toshikazu; Habuchi, Satoshi; Ogino, Kenji; Vacha, Martin
2009-09-10
We study conformation-dependent photophysical properties of polythiophene (PT) by molecular dynamics simulations and by ensemble and single-molecule optical experiments. We use a graft copolymer consisting of a polythiophene backbone and long polystyrene branches and compare its properties with those obtained on the same polythiophene derivative without the side chains. Coarse-grain molecular dynamics simulations show that in a poor solvent, the PT without the side chains (PT-R) forms a globulelike conformation in which distances between any two conjugated segments on the chain are within the Forster radius for efficient energy transfer. In the PT with the polystyrene branches (PT-PS), the polymer main PT chain retains an extended coillike conformation, even in a poor solvent, and the calculated distances between conjugated segments favor energy transfer only between a few neighboring chromophores. The theoretical predictions are confirmed by measurements of fluorescence anisotropy and fluorescence blinking of the polymers' single chains. High anisotropy ratios and two-state blinking in PT-R are due to localization of the exciton on a single conjugated segment. These signatures of exciton localization are absent in single chains of PT-PS. Electric-field-induced quenching measured as a function of concentration of PT dispersed in an inert matrix showed that in well-isolated chains of PT-PS, the exciton dissociation is an intrachain process and that aggregation of the PT-R chains causes an increase in quenching due to the onset of interchain interactions. Measurements of the field-induced quenching on single chains indicate that in PT-R, the exciton dissociation is a slower process that takes place only after the exciton is localized on one conjugated segment.
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Fluctuating observation time ensembles in the thermodynamics of trajectories
NASA Astrophysics Data System (ADS)
Budini, Adrián A.; Turner, Robert M.; Garrahan, Juan P.
2014-03-01
The dynamics of stochastic systems, both classical and quantum, can be studied by analysing the statistical properties of dynamical trajectories. The properties of ensembles of such trajectories for long, but fixed, times are described by large-deviation (LD) rate functions. These LD functions play the role of dynamical free energies: they are cumulant generating functions for time-integrated observables, and their analytic structure encodes dynamical phase behaviour. This ‘thermodynamics of trajectories’ approach is to trajectories and dynamics what the equilibrium ensemble method of statistical mechanics is to configurations and statics. Here we show that, just like in the static case, there are a variety of alternative ensembles of trajectories, each defined by their global constraints, with that of trajectories of fixed total time being just one of these. We show how the LD functions that describe an ensemble of trajectories where some time-extensive quantity is constant (and large) but where total observation time fluctuates can be mapped to those of the fixed-time ensemble. We discuss how the correspondence between generalized ensembles can be exploited in path sampling schemes for generating rare dynamical trajectories.
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Exposing hidden alternative backbone conformations in X-ray crystallography using qFit
Keedy, Daniel A.; Fraser, James S.; van den Bedem, Henry; ...
2015-10-27
Proteins must move between different conformations of their native ensemble to perform their functions. Crystal structures obtained from high-resolution X-ray diffraction data reflect this heterogeneity as a spatial and temporal conformational average. Although movement between natively populated alternative conformations can be critical for characterizing molecular mechanisms, it is challenging to identify these conformations within electron density maps. Alternative side chain conformations are generally well separated into distinct rotameric conformations, but alternative backbone conformations can overlap at several atomic positions. Our model building program qFit uses mixed integer quadratic programming (MIQP) to evaluate an extremely large number of combinations of sidechainmore » conformers and backbone fragments to locally explain the electron density. Here, we describe two major modeling enhancements to qFit: peptide flips and alternative glycine conformations. We find that peptide flips fall into four stereotypical clusters and are enriched in glycine residues at the n+1 position. The potential for insights uncovered by new peptide flips and glycine conformations is exemplified by HIV protease, where different inhibitors are associated with peptide flips in the “flap” regions adjacent to the inhibitor binding site. Our results paint a picture of peptide flips as conformational switches, often enabled by glycine flexibility, that result in dramatic local rearrangements. Our results furthermore demonstrate the power of large-scale computational analysis to provide new insights into conformational heterogeneity. Furthermore, improved modeling of backbone heterogeneity with high-resolution X-ray data will connect dynamics to the structure-function relationship and help drive new design strategies for inhibitors of biomedically important systems.« less
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End-to-end distance and contour length distribution functions of DNA helices
NASA Astrophysics Data System (ADS)
Zoli, Marco
2018-06-01
I present a computational method to evaluate the end-to-end and the contour length distribution functions of short DNA molecules described by a mesoscopic Hamiltonian. The method generates a large statistical ensemble of possible configurations for each dimer in the sequence, selects the global equilibrium twist conformation for the molecule, and determines the average base pair distances along the molecule backbone. Integrating over the base pair radial and angular fluctuations, I derive the room temperature distribution functions as a function of the sequence length. The obtained values for the most probable end-to-end distance and contour length distance, providing a measure of the global molecule size, are used to examine the DNA flexibility at short length scales. It is found that, also in molecules with less than ˜60 base pairs, coiled configurations maintain a large statistical weight and, consistently, the persistence lengths may be much smaller than in kilo-base DNA.
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A universal pathway for kinesin stepping.
Clancy, Bason E; Behnke-Parks, William M; Andreasson, Johan O L; Rosenfeld, Steven S; Block, Steven M
2011-08-14
Kinesin-1 is an ATP-driven, processive motor that transports cargo along microtubules in a tightly regulated stepping cycle. Efficient gating mechanisms ensure that the sequence of kinetic events proceeds in the proper order, generating a large number of successive reaction cycles. To study gating, we created two mutant constructs with extended neck-linkers and measured their properties using single-molecule optical trapping and ensemble fluorescence techniques. Owing to a reduction in the inter-head tension, the constructs access an otherwise rarely populated conformational state in which both motor heads remain bound to the microtubule. ATP-dependent, processive backstepping and futile hydrolysis were observed under moderate hindering loads. On the basis of measurements, we formulated a comprehensive model for kinesin motion that incorporates reaction pathways for both forward and backward stepping. In addition to inter-head tension, we found that neck-linker orientation is also responsible for ensuring gating in kinesin.
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Theory of Stochastic Laplacian Growth
NASA Astrophysics Data System (ADS)
Alekseev, Oleg; Mineev-Weinstein, Mark
2017-07-01
We generalize the diffusion-limited aggregation by issuing many randomly-walking particles, which stick to a cluster at the discrete time unit providing its growth. Using simple combinatorial arguments we determine probabilities of different growth scenarios and prove that the most probable evolution is governed by the deterministic Laplacian growth equation. A potential-theoretical analysis of the growth probabilities reveals connections with the tau-function of the integrable dispersionless limit of the two-dimensional Toda hierarchy, normal matrix ensembles, and the two-dimensional Dyson gas confined in a non-uniform magnetic field. We introduce the time-dependent Hamiltonian, which generates transitions between different classes of equivalence of closed curves, and prove the Hamiltonian structure of the interface dynamics. Finally, we propose a relation between probabilities of growth scenarios and the semi-classical limit of certain correlation functions of "light" exponential operators in the Liouville conformal field theory on a pseudosphere.
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MovieMaker: a web server for rapid rendering of protein motions and interactions
Maiti, Rajarshi; Van Domselaar, Gary H.; Wishart, David S.
2005-01-01
MovieMaker is a web server that allows short (∼10 s), downloadable movies of protein motions to be generated. It accepts PDB files or PDB accession numbers as input and automatically calculates, renders and merges the necessary image files to create colourful animations covering a wide range of protein motions and other dynamic processes. Users have the option of animating (i) simple rotation, (ii) morphing between two end-state conformers, (iii) short-scale, picosecond vibrations, (iv) ligand docking, (v) protein oligomerization, (vi) mid-scale nanosecond (ensemble) motions and (vii) protein folding/unfolding. MovieMaker does not perform molecular dynamics calculations. Instead it is an animation tool that uses a sophisticated superpositioning algorithm in conjunction with Cartesian coordinate interpolation to rapidly and automatically calculate the intermediate structures needed for many of its animations. Users have extensive control over the rendering style, structure colour, animation quality, background and other image features. MovieMaker is intended to be a general-purpose server that allows both experts and non-experts to easily generate useful, informative protein animations for educational and illustrative purposes. MovieMaker is accessible at . PMID:15980488
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Analysis of the bacterial luciferase mobile loop by replica-exchange molecular dynamics.
Campbell, Zachary T; Baldwin, Thomas O; Miyashita, Osamu
2010-12-15
Bacterial luciferase contains an extended 29-residue mobile loop. Movements of this loop are governed by binding of either flavin mononucleotide (FMNH2) or polyvalent anions. To understand this process, loop dynamics were investigated using replica-exchange molecular dynamics that yielded conformational ensembles in either the presence or absence of FMNH2. The resulting data were analyzed using clustering and network analysis. We observed the closed conformations that are visited only in the simulations with the ligand. Yet the mobile loop is intrinsically flexible, and FMNH2 binding modifies the relative populations of conformations. This model provides unique information regarding the function of a crystallographically disordered segment of the loop near the binding site. Structures at or near the fringe of this network were compatible with flavin binding or release. Finally, we demonstrate that the crystallographically observed conformation of the mobile loop bound to oxidized flavin was influenced by crystal packing. Thus, our study has revealed what we believe are novel conformations of the mobile loop and additional context for experimentally determined structures. Copyright © 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.
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Marzinek, Jan K.; Lakshminarayanan, Rajamani; Goh, Eunice; Huber, Roland G.; Panzade, Sadhana; Verma, Chandra; Bond, Peter J.
2016-01-01
Conformational changes in the envelope proteins of flaviviruses help to expose the highly conserved fusion peptide (FP), a region which is critical to membrane fusion and host cell infection, and which represents a significant target for antiviral drugs and antibodies. In principle, extended timescale atomic-resolution simulations may be used to characterize the dynamics of such peptides. However, the resultant accuracy is critically dependent upon both the underlying force field and sufficient conformational sampling. In the present study, we report a comprehensive comparison of three simulation methods and four force fields comprising a total of more than 40 μs of sampling. Additionally, we describe the conformational landscape of the FP fold across all flavivirus family members. All investigated methods sampled conformations close to available X-ray structures, but exhibited differently populated ensembles. The best force field / sampling combination was sufficiently accurate to predict that the solvated peptide fold is less ordered than in the crystallographic state, which was subsequently confirmed via circular dichroism and spectrofluorometric measurements. Finally, the conformational landscape of a mutant incapable of membrane fusion was significantly shallower than wild-type variants, suggesting that dynamics should be considered when therapeutically targeting FP epitopes. PMID:26785994
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Novel layered clustering-based approach for generating ensemble of classifiers.
Rahman, Ashfaqur; Verma, Brijesh
2011-05-01
This paper introduces a novel concept for creating an ensemble of classifiers. The concept is based on generating an ensemble of classifiers through clustering of data at multiple layers. The ensemble classifier model generates a set of alternative clustering of a dataset at different layers by randomly initializing the clustering parameters and trains a set of base classifiers on the patterns at different clusters in different layers. A test pattern is classified by first finding the appropriate cluster at each layer and then using the corresponding base classifier. The decisions obtained at different layers are fused into a final verdict using majority voting. As the base classifiers are trained on overlapping patterns at different layers, the proposed approach achieves diversity among the individual classifiers. Identification of difficult-to-classify patterns through clustering as well as achievement of diversity through layering leads to better classification results as evidenced from the experimental results.
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Single-cell epigenomics: techniques and emerging applications.
Schwartzman, Omer; Tanay, Amos
2015-12-01
Epigenomics is the study of the physical modifications, associations and conformations of genomic DNA sequences, with the aim of linking these with epigenetic memory, cellular identity and tissue-specific functions. While current techniques in the field are characterizing the average epigenomic features across large cell ensembles, the increasing interest in the epigenetics within complex and heterogeneous tissues is driving the development of single-cell epigenomics. We review emerging single-cell methods for capturing DNA methylation, chromatin accessibility, histone modifications, chromosome conformation and replication dynamics. Together, these techniques are rapidly becoming a powerful tool in studies of cellular plasticity and diversity, as seen in stem cells and cancer.
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Entropic Elasticity in the Giant Muscle Protein Titin
NASA Astrophysics Data System (ADS)
Morgan, Ian; Saleh, Omar
Intrinsically disordered proteins (IDPs) are a large and functionally important class of proteins that lack a fixed three-dimensional structure. Instead, they adopt a conformational ensemble of states which facilitates their biological function as molecular linkers, springs, and switches. Due to their conformational flexibility, it can be difficult to study IDPs using typical experimental methods. To overcome this challenge, we use a high-resolution single-molecule magnetic stretching technique to quantify IDP flexibility. We apply this technique to the giant muscle protein titin, measuring its elastic response at low forces. We present results demonstrating that titin's native elastic response derives from the combined entropic elasticity of its ordered and disordered domains.
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Liu, Xiaofeng; Bai, Fang; Ouyang, Sisheng; Wang, Xicheng; Li, Honglin; Jiang, Hualiang
2009-03-31
Conformation generation is a ubiquitous problem in molecule modelling. Many applications require sampling the broad molecular conformational space or perceiving the bioactive conformers to ensure success. Numerous in silico methods have been proposed in an attempt to resolve the problem, ranging from deterministic to non-deterministic and systemic to stochastic ones. In this work, we described an efficient conformation sampling method named Cyndi, which is based on multi-objective evolution algorithm. The conformational perturbation is subjected to evolutionary operation on the genome encoded with dihedral torsions. Various objectives are designated to render the generated Pareto optimal conformers to be energy-favoured as well as evenly scattered across the conformational space. An optional objective concerning the degree of molecular extension is added to achieve geometrically extended or compact conformations which have been observed to impact the molecular bioactivity (J Comput -Aided Mol Des 2002, 16: 105-112). Testing the performance of Cyndi against a test set consisting of 329 small molecules reveals an average minimum RMSD of 0.864 A to corresponding bioactive conformations, indicating Cyndi is highly competitive against other conformation generation methods. Meanwhile, the high-speed performance (0.49 +/- 0.18 seconds per molecule) renders Cyndi to be a practical toolkit for conformational database preparation and facilitates subsequent pharmacophore mapping or rigid docking. The copy of precompiled executable of Cyndi and the test set molecules in mol2 format are accessible in Additional file 1. On the basis of MOEA algorithm, we present a new, highly efficient conformation generation method, Cyndi, and report the results of validation and performance studies comparing with other four methods. The results reveal that Cyndi is capable of generating geometrically diverse conformers and outperforms other four multiple conformer generators in the case of reproducing the bioactive conformations against 329 structures. The speed advantage indicates Cyndi is a powerful alternative method for extensive conformational sampling and large-scale conformer database preparation.
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Niesen, Michiel J M; Bhattacharya, Supriyo; Grisshammer, Reinhard; Tate, Christopher G; Vaidehi, Nagarajan
2013-06-20
The dynamic nature of GPCRs is a major hurdle in their purification and crystallization. Thermostabilization can facilitate GPCR structure determination, as has been shown by the structure of the thermostabilized β1-adrenergic receptor (β1AR) mutant, m23-β1AR, which has been thermostabilized in the inactive state. However, it is unclear from the structure how the six thermostabilizing mutations in m23-β1AR affect receptor dynamics. We have used molecular dynamics simulations in explicit solvent to compare the conformational ensembles for both wild type β1AR (wt-β1AR) and m23-β1AR. Thermostabilization results in an increase in the number of accessible microscopic conformational states within the inactive state ensemble, effectively increasing the side chain entropy of the inactive state at room temperature, while suppressing large-scale main chain conformational changes that lead to activation. We identified several diverse mechanisms of thermostabilization upon mutation. These include decrease of long-range correlated movement between residues in the G-protein coupling site to the extracellular region (Y227A(5.58), F338M(7.48)), formation of new hydrogen bonds (R68S), and reduction of local stress (Y227(5.58), F327(7.37), and F338(7.48)). This study provides insights into microscopic mechanisms underlying thermostability that leads to an understanding of the effect of these mutations on the structure of the receptor.
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Mode localization in the cooperative dynamics of protein recognition
NASA Astrophysics Data System (ADS)
Copperman, J.; Guenza, M. G.
2016-07-01
The biological function of proteins is encoded in their structure and expressed through the mediation of their dynamics. This paper presents a study on the correlation between local fluctuations, binding, and biological function for two sample proteins, starting from the Langevin Equation for Protein Dynamics (LE4PD). The LE4PD is a microscopic and residue-specific coarse-grained approach to protein dynamics, which starts from the static structural ensemble of a protein and predicts the dynamics analytically. It has been shown to be accurate in its prediction of NMR relaxation experiments and Debye-Waller factors. The LE4PD is solved in a set of diffusive modes which span a vast range of time scales of the protein dynamics, and provides a detailed picture of the mode-dependent localization of the fluctuation as a function of the primary structure of the protein. To investigate the dynamics of protein complexes, the theory is implemented here to treat the coarse-grained dynamics of interacting macromolecules. As an example, calculations of the dynamics of monomeric and dimerized HIV protease and the free Insulin Growth Factor II Receptor (IGF2R) domain 11 and its IGF2R:IGF2 complex are presented. Either simulation-derived or experimentally measured NMR conformers are used as input structural ensembles to the theory. The picture that emerges suggests a dynamical heterogeneous protein where biologically active regions provide energetically comparable conformational states that are trapped by a reacting partner in agreement with the conformation-selection mechanism of binding.
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Nguyen, Phuong H; Tarus, Bogdan; Derreumaux, Philippe
2014-01-16
The self-assembly of the amyloid-β (Aβ) peptide of 39-43 amino acids into senile plaques is one hallmark of Alzheimer's disease (AD) pathology. While A2 V carriers remain healthy in the heterozygous state, they suffer from early onset AD in the homozygous state. As a first toward understanding the impact of A2 V on Aβ at its earlier stage, we characterized the equilibrium ensemble of the Aβ1-28 wild type and Aβ1-28 A2 V monomers by means of extensive atomistic replica exchange molecular dynamics simulations. While global conformational properties such as the radius of gyration and the average secondary structure content of the whole peptides are very similar, the population of β-hairpins is increased by a factor of 4 in A2 V, and this may explain the enhanced Aβ1-40 A2 V aggregation kinetics with respect to Aβ1-40 wild type. Both peptides display a non-negligible population of extended metastable conformations differing however in their atomic details that represent ideal seeds for polymerization. Remarkably, upon A2 V mutation, the intrinsic disorder of Aβ1-28 monomer is reduced by a factor of 2, and the free energy landscape is completely different. This difference in the conformational ensembles of the two peptides may explain in part why the mixture of the Aβ40 WT and A2 V peptides protects against AD.
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HPEPDOCK: a web server for blind peptide-protein docking based on a hierarchical algorithm.
Zhou, Pei; Jin, Bowen; Li, Hao; Huang, Sheng-You
2018-05-09
Protein-peptide interactions are crucial in many cellular functions. Therefore, determining the structure of protein-peptide complexes is important for understanding the molecular mechanism of related biological processes and developing peptide drugs. HPEPDOCK is a novel web server for blind protein-peptide docking through a hierarchical algorithm. Instead of running lengthy simulations to refine peptide conformations, HPEPDOCK considers the peptide flexibility through an ensemble of peptide conformations generated by our MODPEP program. For blind global peptide docking, HPEPDOCK obtained a success rate of 33.3% in binding mode prediction on a benchmark of 57 unbound cases when the top 10 models were considered, compared to 21.1% for pepATTRACT server. HPEPDOCK also performed well in docking against homology models and obtained a success rate of 29.8% within top 10 predictions. For local peptide docking, HPEPDOCK achieved a high success rate of 72.6% on a benchmark of 62 unbound cases within top 10 predictions, compared to 45.2% for HADDOCK peptide protocol. Our HPEPDOCK server is computationally efficient and consumed an average of 29.8 mins for a global peptide docking job and 14.2 mins for a local peptide docking job. The HPEPDOCK web server is available at http://huanglab.phys.hust.edu.cn/hpepdock/.
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Computational Prediction of Atomic Structures of Helical Membrane Proteins Aided by EM Maps
Kovacs, Julio A.; Yeager, Mark; Abagyan, Ruben
2007-01-01
Integral membrane proteins pose a major challenge for protein-structure prediction because only ≈100 high-resolution structures are available currently, thereby impeding the development of rules or empirical potentials to predict the packing of transmembrane α-helices. However, when an intermediate-resolution electron microscopy (EM) map is available, it can be used to provide restraints which, in combination with a suitable computational protocol, make structure prediction feasible. In this work we present such a protocol, which proceeds in three stages: 1), generation of an ensemble of α-helices by flexible fitting into each of the density rods in the low-resolution EM map, spanning a range of rotational angles around the main helical axes and translational shifts along the density rods; 2), fast optimization of side chains and scoring of the resulting conformations; and 3), refinement of the lowest-scoring conformations with internal coordinate mechanics, by optimizing the van der Waals, electrostatics, hydrogen bonding, torsional, and solvation energy contributions. In addition, our method implements a penalty term through a so-called tethering map, derived from the EM map, which restrains the positions of the α-helices. The protocol was validated on three test cases: GpA, KcsA, and MscL. PMID:17496035
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Hansen, Halvor S; Daura, Xavier; Hünenberger, Philippe H
2010-09-14
A new method, fragment-based local elevation umbrella sampling (FB-LEUS), is proposed to enhance the conformational sampling in explicit-solvent molecular dynamics (MD) simulations of solvated polymers. The method is derived from the local elevation umbrella sampling (LEUS) method [ Hansen and Hünenberger , J. Comput. Chem. 2010 , 31 , 1 - 23 ], which combines the local elevation (LE) conformational searching and the umbrella sampling (US) conformational sampling approaches into a single scheme. In LEUS, an initial (relatively short) LE build-up (searching) phase is used to construct an optimized (grid-based) biasing potential within a subspace of conformationally relevant degrees of freedom, which is then frozen and used in a (comparatively longer) US sampling phase. This combination dramatically enhances the sampling power of MD simulations but, due to computational and memory costs, is only applicable to relevant subspaces of low dimensionalities. As an attempt to expand the scope of the LEUS approach to solvated polymers with more than a few relevant degrees of freedom, the FB-LEUS scheme involves an US sampling phase that relies on a superposition of low-dimensionality biasing potentials optimized using LEUS at the fragment level. The feasibility of this approach is tested using polyalanine (poly-Ala) and polyvaline (poly-Val) oligopeptides. Two-dimensional biasing potentials are preoptimized at the monopeptide level, and subsequently applied to all dihedral-angle pairs within oligopeptides of 4, 6, 8, or 10 residues. Two types of fragment-based biasing potentials are distinguished: (i) the basin-filling (BF) potentials act so as to "fill" free-energy basins up to a prescribed free-energy level above the global minimum; (ii) the valley-digging (VD) potentials act so as to "dig" valleys between the (four) free-energy minima of the two-dimensional maps, preserving barriers (relative to linearly interpolated free-energy changes) of a prescribed magnitude. The application of these biasing potentials may lead to an impressive enhancement of the searching power (volume of conformational space visited in a given amount of simulation time). However, this increase is largely offset by a deterioration of the statistical efficiency (representativeness of the biased ensemble in terms of the conformational distribution appropriate for the physical ensemble). As a result, it appears difficult to engineer FB-LEUS schemes representing a significant improvement over plain MD, at least for the systems considered here.
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Electrostatic mechanism of nucleosomal array folding revealed by computer simulation
Sun, Jian; Zhang, Qing; Schlick, Tamar
2005-01-01
Although numerous experiments indicate that the chromatin fiber displays salt-dependent conformations, the associated molecular mechanism remains unclear. Here, we apply an irregular Discrete Surface Charge Optimization (DiSCO) model of the nucleosome with all histone tails incorporated to describe by Monte Carlo simulations salt-dependent rearrangements of a nucleosomal array with 12 nucleosomes. The ensemble of nucleosomal array conformations display salt-dependent condensation in good agreement with hydrodynamic measurements and suggest that the array adopts highly irregular 3D zig-zag conformations at high (physiological) salt concentrations and transitions into the extended “beads-on-a-string” conformation at low salt. Energy analyses indicate that the repulsion among linker DNA leads to this extended form, whereas internucleosome attraction drives the folding at high salt. The balance between these two contributions determines the salt-dependent condensation. Importantly, the internucleosome and linker DNA–nucleosome attractions require histone tails; we find that the H3 tails, in particular, are crucial for stabilizing the moderately folded fiber at physiological monovalent salt. PMID:15919827
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Structural Landscape of the Proline-Rich Domain of Sos1 Nucleotide Exchange Factor
McDonald, Caleb B.; Bhat, Vikas; Kurouski, Dmitry; Mikles, David C.; Deegan, Brian J.; Seldeen, Kenneth L.; Lednev, Igor K.; Farooq, Amjad
2013-01-01
Despite its key role in mediating a plethora of cellular signaling cascades pertinent to health and disease, little is known about the structural landscape of the proline-rich (PR) domain of Sos1 guanine nucleotide exchange factor. Herein, using a battery of biophysical tools, we provide evidence that the PR domain of Sos1 is structurally disordered and adopts an extended random coil-like conformation in solution. Of particular interest is the observation that while chemical denaturation of PR domain results in the formation of a significant amount of polyproline II (PPII) helices, it has little or negligible effect on its overall size as measured by its hydrodynamic radius. Our data also show that the PR domain displays a highly dynamic conformational basin in agreement with the knowledge that the intrinsically unstructured proteins rapidly interconvert between an ensemble of conformations. Collectively, our study provides new insights into the conformational equilibrium of a key signaling molecule with important consequences on its physiological function. PMID:23528987
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Toulmin, Anita; Baltierra-Jasso, Laura E; Morten, Michael J; Sabir, Tara; McGlynn, Peter; Schröder, Gunnar F; Smith, Brian O; Magennis, Steven W
2017-09-19
DNA three-way junctions (3WJs) are branched structures that serve as important biological intermediates and as components in DNA nanostructures. We recently derived the global structure of a fully complementary 3WJ and found that it contained unpaired bases at the branchpoint, which is consistent with previous observations of branch flexibility and branchpoint reactivity. By combining high-resolution single-molecule Förster resonance energy transfer, molecular modeling, time-resolved ensemble fluorescence spectroscopy, and the first 19 F nuclear magnetic resonance observations of fully complementary 3WJs, we now show that the 3WJ structure can adopt multiple distinct conformations depending upon the sequence at the branchpoint. A 3WJ with a GC-rich branchpoint adopts an open conformation with unpaired bases at the branch and at least one additional conformation with an increased number of base interactions at the branchpoint. This structural diversity has implications for branch interactions and processing in vivo and for technological applications.
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Electrostatic mechanism of nucleosomal array folding revealed by computer simulation.
Sun, Jian; Zhang, Qing; Schlick, Tamar
2005-06-07
Although numerous experiments indicate that the chromatin fiber displays salt-dependent conformations, the associated molecular mechanism remains unclear. Here, we apply an irregular Discrete Surface Charge Optimization (DiSCO) model of the nucleosome with all histone tails incorporated to describe by Monte Carlo simulations salt-dependent rearrangements of a nucleosomal array with 12 nucleosomes. The ensemble of nucleosomal array conformations display salt-dependent condensation in good agreement with hydrodynamic measurements and suggest that the array adopts highly irregular 3D zig-zag conformations at high (physiological) salt concentrations and transitions into the extended "beads-on-a-string" conformation at low salt. Energy analyses indicate that the repulsion among linker DNA leads to this extended form, whereas internucleosome attraction drives the folding at high salt. The balance between these two contributions determines the salt-dependent condensation. Importantly, the internucleosome and linker DNA-nucleosome attractions require histone tails; we find that the H3 tails, in particular, are crucial for stabilizing the moderately folded fiber at physiological monovalent salt.
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Crystal cryocooling distorts conformational heterogeneity in a model Michaelis complex of DHFR
Keedy, Daniel A.; van den Bedem, Henry; Sivak, David A.; Petsko, Gregory A.; Ringe, Dagmar; Wilson, Mark A.; Fraser, James S.
2014-01-01
Summary Most macromolecular X-ray structures are determined from cryocooled crystals, but it is unclear whether cryocooling distorts functionally relevant flexibility. Here we compare independently acquired pairs of high-resolution datasets of a model Michaelis complex of dihydrofolate reductase (DHFR), collected by separate groups at both room and cryogenic temperatures. These datasets allow us to isolate the differences between experimental procedures and between temperatures. Our analyses of multiconformer models and time-averaged ensembles suggest that cryocooling suppresses and otherwise modifies sidechain and mainchain conformational heterogeneity, quenching dynamic contact networks. Despite some idiosyncratic differences, most changes from room temperature to cryogenic temperature are conserved, and likely reflect temperature-dependent solvent remodeling. Both cryogenic datasets point to additional conformations not evident in the corresponding room-temperature datasets, suggesting that cryocooling does not merely trap pre-existing conformational heterogeneity. Our results demonstrate that crystal cryocooling consistently distorts the energy landscape of DHFR, a paragon for understanding functional protein dynamics. PMID:24882744
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A comparison of breeding and ensemble transform vectors for global ensemble generation
NASA Astrophysics Data System (ADS)
Deng, Guo; Tian, Hua; Li, Xiaoli; Chen, Jing; Gong, Jiandong; Jiao, Meiyan
2012-02-01
To compare the initial perturbation techniques using breeding vectors and ensemble transform vectors, three ensemble prediction systems using both initial perturbation methods but with different ensemble member sizes based on the spectral model T213/L31 are constructed at the National Meteorological Center, China Meteorological Administration (NMC/CMA). A series of ensemble verification scores such as forecast skill of the ensemble mean, ensemble resolution, and ensemble reliability are introduced to identify the most important attributes of ensemble forecast systems. The results indicate that the ensemble transform technique is superior to the breeding vector method in light of the evaluation of anomaly correlation coefficient (ACC), which is a deterministic character of the ensemble mean, the root-mean-square error (RMSE) and spread, which are of probabilistic attributes, and the continuous ranked probability score (CRPS) and its decomposition. The advantage of the ensemble transform approach is attributed to its orthogonality among ensemble perturbations as well as its consistence with the data assimilation system. Therefore, this study may serve as a reference for configuration of the best ensemble prediction system to be used in operation.
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Molecular Dynamics Simulation of Membranes and a Transmembrane Helix
NASA Astrophysics Data System (ADS)
Duong, Tap Ha; Mehler, Ernest L.; Weinstein, Harel
1999-05-01
Three molecular dynamics (MD) simulations of 1.5-ns length were carried out on fully hydrated patches of dimyristoyl phosphatidylcholine (DMPC) bilayers in the liquid-crystalline phase. The simulations were performed using different ensembles and electrostatic conditions: a microcanonical ensemble or constant pressure-temperature ensemble, with or without truncated electrostatic interactions. Calculated properties of the membrane patches from the three different protocols were compared to available data from experiments. These data include the resulting overall geometrical dimensions, the order characteristics of the lipid hydrocarbon chains, as well as various measures of the conformations of the polar head groups. The comparisons indicate that the simulation carried out within the microcanonical ensemble with truncated electrostatic interactions yielded results closest to the experimental data, provided that the initial equilibration phase preceding the production run was sufficiently long. The effects of embedding a non-ideal helical protein domain in the membrane patch were studied with the same MD protocols. This simulation was carried out for 2.5 ns. The protein domain corresponds to the seventh transmembrane segment (TMS7) of the human serotonin 5HT 2Areceptor. The peptide is composed of two α-helical segments linked by a hinge domain around a perturbing Asn-Pro motif that produces at the end of the simulation a kink angle of nearly 80° between the two helices. Several aspects of the TMS7 structure, such as the bending angle, backbone Φ and Ψ torsion angles, the intramolecular hydrogen bonds, and the overall conformation, were found to be very similar to those determined by NMR for the corresponding transmembrane segment of the tachykinin NK-1 receptor. In general, the simulations were found to yield structural and dynamic characteristics that are in good agreement with experiment. These findings support the application of simulation methods to the study of the complex biomolecular systems at the membrane interface of cells.
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NASA Astrophysics Data System (ADS)
Lee, H. S.; Liu, Y.; Ward, J.; Brown, J.; Maestre, A.; Herr, H.; Fresch, M. A.; Wells, E.; Reed, S. M.; Jones, E.
2017-12-01
The National Weather Service's (NWS) Office of Water Prediction (OWP) recently launched a nationwide effort to verify streamflow forecasts from the Hydrologic Ensemble Forecast Service (HEFS) for a majority of forecast locations across the 13 River Forecast Centers (RFCs). Known as the HEFS Baseline Validation (BV), the project involves a joint effort between the OWP and the RFCs. It aims to provide a geographically consistent, statistically robust validation, and a benchmark to guide the operational implementation of the HEFS, inform practical applications, such as impact-based decision support services, and to provide an objective framework for evaluating strategic investments in the HEFS. For the BV, HEFS hindcasts are issued once per day on a 12Z cycle for the period of 1985-2015 with a forecast horizon of 30 days. For the first two weeks, the hindcasts are forced with precipitation and temperature ensemble forecasts from the Global Ensemble Forecast System of the National Centers for Environmental Prediction, and by resampled climatology for the remaining period. The HEFS-generated ensemble streamflow hindcasts are verified using the Ensemble Verification System. Skill is assessed relative to streamflow hindcasts generated from NWS' current operational system, namely climatology-based Ensemble Streamflow Prediction. In this presentation, we summarize the results and findings to date.
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Manoharan, Prabu; Chennoju, Kiranmai; Ghoshal, Nanda
2015-07-01
BACE1 is an attractive target in Alzheimer's disease (AD) treatment. A rational drug design effort for the inhibition of BACE1 is actively pursued by researchers in both academic and pharmaceutical industries. This continued effort led to the steady accumulation of BACE1 crystal structures, co-complexed with different classes of inhibitors. This wealth of information is used in this study to develop target specific proteochemometric models and these models are exploited for predicting the prospective BACE1 inhibitors. The models developed in this study have performed excellently in predicting the computationally generated poses, separately obtained from single and ensemble docking approaches. The simple protein-ligand contact (SPLC) model outperforms other sophisticated high end models, in virtual screening performance, developed during this study. In an attempt to account for BACE1 protein active site flexibility information in predictive models, we included the change in the area of solvent accessible surface and the change in the volume of solvent accessible surface in our models. The ensemble and single receptor docking results obtained from this study indicate that the structural water mediated interactions improve the virtual screening results. Also, these waters are essential for recapitulating bioactive conformation during docking study. The proteochemometric models developed in this study can be used for the prediction of BACE1 inhibitors, during the early stage of AD drug discovery.
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USDA-ARS?s Scientific Manuscript database
Molecular dynamics simulations using AMB06C, an in-house carbohydrate force field, (NPT ensembles, 1atm) were carried out on a periodic cell that contained a cyclic-DP-240 amylose fragment and TIP3P water molecules. Molecular conformation and movement of the amylose fragment and water molecules at ...
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Anandapadamanaban, Madhanagopal; Pilstål, Robert; Andresen, Cecilia; Trewhella, Jill; Moche, Martin; Wallner, Björn; Sunnerhagen, Maria
2016-08-02
MexR is a repressor of the MexAB-OprM multidrug efflux pump operon of Pseudomonas aeruginosa, where DNA-binding impairing mutations lead to multidrug resistance (MDR). Surprisingly, the crystal structure of an MDR-conferring MexR mutant R21W (2.19 Å) presented here is closely similar to wild-type MexR. However, our extended analysis, by molecular dynamics and small-angle X-ray scattering, reveals that the mutation stabilizes a ground state that is deficient of DNA binding and is shared by both mutant and wild-type MexR, whereas the DNA-binding state is only transiently reached by the more flexible wild-type MexR. This population shift in the conformational ensemble is effected by mutation-induced allosteric coupling of contact networks that are independent in the wild-type protein. We propose that the MexR-R21W mutant mimics derepression by small-molecule binding to MarR proteins, and that the described allosteric model based on population shifts may also apply to other MarR family members. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Hidden Structural Codes in Protein Intrinsic Disorder.
Borkosky, Silvia S; Camporeale, Gabriela; Chemes, Lucía B; Risso, Marikena; Noval, María Gabriela; Sánchez, Ignacio E; Alonso, Leonardo G; de Prat Gay, Gonzalo
2017-10-17
Intrinsic disorder is a major structural category in biology, accounting for more than 30% of coding regions across the domains of life, yet consists of conformational ensembles in equilibrium, a major challenge in protein chemistry. Anciently evolved papillomavirus genomes constitute an unparalleled case for sequence to structure-function correlation in cases in which there are no folded structures. E7, the major transforming oncoprotein of human papillomaviruses, is a paradigmatic example among the intrinsically disordered proteins. Analysis of a large number of sequences of the same viral protein allowed for the identification of a handful of residues with absolute conservation, scattered along the sequence of its N-terminal intrinsically disordered domain, which intriguingly are mostly leucine residues. Mutation of these led to a pronounced increase in both α-helix and β-sheet structural content, reflected by drastic effects on equilibrium propensities and oligomerization kinetics, and uncovers the existence of local structural elements that oppose canonical folding. These folding relays suggest the existence of yet undefined hidden structural codes behind intrinsic disorder in this model protein. Thus, evolution pinpoints conformational hot spots that could have not been identified by direct experimental methods for analyzing or perturbing the equilibrium of an intrinsically disordered protein ensemble.
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Cembran, Alessandro; Kim, Jonggul; Gao, Jiali; Veglia, Gianluigi
2014-01-01
Proteins exist as an ensemble of conformers that are distributed on free energy landscapes resembling folding funnels. While the most stable conformers populate low energy basins, protein function is often carried out through low-populated conformational states that occupy high energy basins. Ligand binding shifts the populations of these states, changing the distribution of these conformers. Understanding how the equilibrium among the states is altered upon ligand binding, interaction with other binding partners, and/or mutations and post-translational modifications is of critical importance for explaining allosteric signaling in proteins. Here, we propose a statistical analysis of the chemical shifts (CONCISE, COordiNated ChemIcal Shifts bEhavior) for the interpretation of protein conformational equilibria following linear trajectories of NMR chemical shifts. CONCISE enables one to quantitatively measure the population shifts associated with ligand titrations and estimate the degree of collectiveness of the protein residues’ response to ligand binding, giving a concise view of the structural transitions. The combination of CONCISE with thermocalorimetric and kinetic data allows one to depict a protein’s approximate conformational energy landscape. We tested this method with the catalytic subunit of cAMP-dependent protein kinase A, a ubiquitous enzyme that undergoes conformational transitions upon both nucleotide and pseudo-substrate binding. When complemented with chemical shift covariance analysis (CHESCA), this new method offers both collective response and residue-specific correlations for ligand binding to proteins. PMID:24604024
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Fast, clash-free RNA conformational morphing using molecular junctions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Heliou, Amelie; Budday, Dominik; Fonseca, Rasmus
Non-coding ribonucleic acids (ncRNA) are functional RNA molecules that are not translated into protein. They are extremely dynamic, adopting diverse conformational substates, which enables them to modulate their interaction with a large number of other molecules. The flexibility of ncRNA provides a challenge for probing their complex 3D conformational landscape, both experimentally and computationally. As a result, despite their conformational diversity, ncRNAs mostly preserve their secondary structure throughout the dynamic ensemble. Here we present a kinematics-based procedure to morph an RNA molecule between conformational substates, while avoiding inter-atomic clashes. We represent an RNA as a kinematic linkage, with fixed groupsmore » of atoms as rigid bodies and rotatable bonds as degrees of freedom. Our procedure maintains RNA secondary structure by treating hydrogen bonds between base pairs as constraints. The constraints define a lower-dimensional, secondary-structure constraint manifold in conformation space, where motions are largely governed by molecular junctions of unpaired nucleotides. On a large benchmark set, we show that our morphing procedure compares favorably to peer algorithms, and can approach goal conformations to within a low all-atom RMSD by directing fewer than 1% of its atoms. Furthermore, our results suggest that molecular junctions can modulate 3D structural rearrangements, while secondary structure elements guide large parts of the molecule along the transition to the correct final conformation.« less
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Fast, clash-free RNA conformational morphing using molecular junctions
Heliou, Amelie; Budday, Dominik; Fonseca, Rasmus; ...
2017-03-13
Non-coding ribonucleic acids (ncRNA) are functional RNA molecules that are not translated into protein. They are extremely dynamic, adopting diverse conformational substates, which enables them to modulate their interaction with a large number of other molecules. The flexibility of ncRNA provides a challenge for probing their complex 3D conformational landscape, both experimentally and computationally. As a result, despite their conformational diversity, ncRNAs mostly preserve their secondary structure throughout the dynamic ensemble. Here we present a kinematics-based procedure to morph an RNA molecule between conformational substates, while avoiding inter-atomic clashes. We represent an RNA as a kinematic linkage, with fixed groupsmore » of atoms as rigid bodies and rotatable bonds as degrees of freedom. Our procedure maintains RNA secondary structure by treating hydrogen bonds between base pairs as constraints. The constraints define a lower-dimensional, secondary-structure constraint manifold in conformation space, where motions are largely governed by molecular junctions of unpaired nucleotides. On a large benchmark set, we show that our morphing procedure compares favorably to peer algorithms, and can approach goal conformations to within a low all-atom RMSD by directing fewer than 1% of its atoms. Furthermore, our results suggest that molecular junctions can modulate 3D structural rearrangements, while secondary structure elements guide large parts of the molecule along the transition to the correct final conformation.« less
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Mori, Takaharu; Jung, Jaewoon; Sugita, Yuji
2013-12-10
Conformational sampling is fundamentally important for simulating complex biomolecular systems. The generalized-ensemble algorithm, especially the temperature replica-exchange molecular dynamics method (T-REMD), is one of the most powerful methods to explore structures of biomolecules such as proteins, nucleic acids, carbohydrates, and also of lipid membranes. T-REMD simulations have focused on soluble proteins rather than membrane proteins or lipid bilayers, because explicit membranes do not keep their structural integrity at high temperature. Here, we propose a new generalized-ensemble algorithm for membrane systems, which we call the surface-tension REMD method. Each replica is simulated in the NPγT ensemble, and surface tensions in a pair of replicas are exchanged at certain intervals to enhance conformational sampling of the target membrane system. We test the method on two biological membrane systems: a fully hydrated DPPC (1,2-dipalmitoyl-sn-glycero-3-phosphatidylcholine) lipid bilayer and a WALP23-POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) membrane system. During these simulations, a random walk in surface tension space is realized. Large-scale lateral deformation (shrinking and stretching) of the membranes takes place in all of the replicas without collapse of the lipid bilayer structure. There is accelerated lateral diffusion of DPPC lipid molecules compared with conventional MD simulation, and a much wider range of tilt angle of the WALP23 peptide is sampled due to large deformation of the POPC lipid bilayer and through peptide-lipid interactions. Our method could be applicable to a wide variety of biological membrane systems.
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Comparing pharmacophore models derived from crystallography and NMR ensembles
NASA Astrophysics Data System (ADS)
Ghanakota, Phani; Carlson, Heather A.
2017-11-01
NMR and X-ray crystallography are the two most widely used methods for determining protein structures. Our previous study examining NMR versus X-Ray sources of protein conformations showed improved performance with NMR structures when used in our Multiple Protein Structures (MPS) method for receptor-based pharmacophores (Damm, Carlson, J Am Chem Soc 129:8225-8235, 2007). However, that work was based on a single test case, HIV-1 protease, because of the rich data available for that system. New data for more systems are available now, which calls for further examination of the effect of different sources of protein conformations. The MPS technique was applied to Growth factor receptor bound protein 2 (Grb2), Src SH2 homology domain (Src-SH2), FK506-binding protein 1A (FKBP12), and Peroxisome proliferator-activated receptor-γ (PPAR-γ). Pharmacophore models from both crystal and NMR ensembles were able to discriminate between high-affinity, low-affinity, and decoy molecules. As we found in our original study, NMR models showed optimal performance when all elements were used. The crystal models had more pharmacophore elements compared to their NMR counterparts. The crystal-based models exhibited optimum performance only when pharmacophore elements were dropped. This supports our assertion that the higher flexibility in NMR ensembles helps focus the models on the most essential interactions with the protein. Our studies suggest that the "extra" pharmacophore elements seen at the periphery in X-ray models arise as a result of decreased protein flexibility and make very little contribution to model performance.
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Frank, Joachim; Gonzalez, Ruben L.
2015-01-01
At equilibrium, thermodynamic and kinetic information can be extracted from biomolecular energy landscapes by many techniques. However, while static, ensemble techniques yield thermodynamic data, often only dynamic, single-molecule techniques can yield the kinetic data that describes transition-state energy barriers. Here we present a generalized framework based upon dwell-time distributions that can be used to connect such static, ensemble techniques with dynamic, single-molecule techniques, and thus characterize energy landscapes to greater resolutions. We demonstrate the utility of this framework by applying it to cryogenic electron microscopy and single-molecule fluorescence resonance energy transfer studies of the bacterial ribosomal pretranslocation complex. Among other benefits, application of this framework to these data explains why two transient, intermediate conformations of the pretranslocation complex, which are observed in a cryogenic electron microscopy study, may not be observed in several single-molecule fluorescence resonance energy transfer studies. PMID:25785884
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Thompson, Colin D Kinz; Sharma, Ajeet K; Frank, Joachim; Gonzalez, Ruben L; Chowdhury, Debashish
2015-08-27
At equilibrium, thermodynamic and kinetic information can be extracted from biomolecular energy landscapes by many techniques. However, while static, ensemble techniques yield thermodynamic data, often only dynamic, single-molecule techniques can yield the kinetic data that describe transition-state energy barriers. Here we present a generalized framework based upon dwell-time distributions that can be used to connect such static, ensemble techniques with dynamic, single-molecule techniques, and thus characterize energy landscapes to greater resolutions. We demonstrate the utility of this framework by applying it to cryogenic electron microscopy (cryo-EM) and single-molecule fluorescence resonance energy transfer (smFRET) studies of the bacterial ribosomal pre-translocation complex. Among other benefits, application of this framework to these data explains why two transient, intermediate conformations of the pre-translocation complex, which are observed in a cryo-EM study, may not be observed in several smFRET studies.
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Ghasemi, Jahan B; Safavi-Sohi, Reihaneh; Barbosa, Euzébio G
2012-02-01
A quasi 4D-QSAR has been carried out on a series of potent Gram-negative LpxC inhibitors. This approach makes use of the molecular dynamics (MD) trajectories and topology information retrieved from the GROMACS package. This new methodology is based on the generation of a conformational ensemble profile, CEP, for each compound instead of only one conformation, followed by the calculation intermolecular interaction energies at each grid point considering probes and all aligned conformations resulting from MD simulations. These interaction energies are independent variables employed in a QSAR analysis. The comparison of the proposed methodology to comparative molecular field analysis (CoMFA) formalism was performed. This methodology explores jointly the main features of CoMFA and 4D-QSAR models. Step-wise multiple linear regression was used for the selection of the most informative variables. After variable selection, multiple linear regression (MLR) and partial least squares (PLS) methods used for building the regression models. Leave-N-out cross-validation (LNO), and Y-randomization were performed in order to confirm the robustness of the model in addition to analysis of the independent test set. Best models provided the following statistics: [Formula in text] (PLS) and [Formula in text] (MLR). Docking study was applied to investigate the major interactions in protein-ligand complex with CDOCKER algorithm. Visualization of the descriptors of the best model helps us to interpret the model from the chemical point of view, supporting the applicability of this new approach in rational drug design.
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SwiSpot: modeling riboswitches by spotting out switching sequences.
Barsacchi, Marco; Novoa, Eva Maria; Kellis, Manolis; Bechini, Alessio
2016-11-01
Riboswitches are cis-regulatory elements in mRNA, mostly found in Bacteria, which exhibit two main secondary structure conformations. Although one of them prevents the gene from being expressed, the other conformation allows its expression, and this switching process is typically driven by the presence of a specific ligand. Although there are a handful of known riboswitches, our knowledge in this field has been greatly limited due to our inability to identify their alternate structures from their sequences. Indeed, current methods are not able to predict the presence of the two functionally distinct conformations just from the knowledge of the plain RNA nucleotide sequence. Whether this would be possible, for which cases, and what prediction accuracy can be achieved, are currently open questions. Here we show that the two alternate secondary structures of riboswitches can be accurately predicted once the 'switching sequence' of the riboswitch has been properly identified. The proposed SwiSpot approach is capable of identifying the switching sequence inside a putative, complete riboswitch sequence, on the basis of pairing behaviors, which are evaluated on proper sets of configurations. Moreover, it is able to model the switching behavior of riboswitches whose generated ensemble covers both alternate configurations. Beyond structural predictions, the approach can also be paired to homology-based riboswitch searches. SwiSpot software, along with the reference dataset files, is available at: http://www.iet.unipi.it/a.bechini/swispot/Supplementary information: Supplementary data are available at Bioinformatics online. a.bechini@ing.unipi.it. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Balu, Rajkamal; Knott, Robert; Cowieson, Nathan P.; Elvin, Christopher M.; Hill, Anita J.; Choudhury, Namita R.; Dutta, Naba K.
2015-01-01
Rec1-resilin is the first recombinant resilin-mimetic protein polymer, synthesized from exon-1 of the Drosophila melanogaster gene CG15920 that has demonstrated unusual multi-stimuli responsiveness in aqueous solution. Crosslinked hydrogels of Rec1-resilin have also displayed remarkable mechanical properties including near-perfect rubber-like elasticity. The structural basis of these extraordinary properties is not clearly understood. Here we combine a computational and experimental investigation to examine structural ensembles of Rec1-resilin in aqueous solution. The structure of Rec1-resilin in aqueous solutions is investigated experimentally using circular dichroism (CD) spectroscopy and small angle X-ray scattering (SAXS). Both bench-top and synchrotron SAXS are employed to extract structural data sets of Rec1-resilin and to confirm their validity. Computational approaches have been applied to these experimental data sets in order to extract quantitative information about structural ensembles including radius of gyration, pair-distance distribution function, and the fractal dimension. The present work confirms that Rec1-resilin is an intrinsically disordered protein (IDP) that displays equilibrium structural qualities between those of a structured globular protein and a denatured protein. The ensemble optimization method (EOM) analysis reveals a single conformational population with partial compactness. This work provides new insight into the structural ensembles of Rec1-resilin in solution. PMID:26042819
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Balu, Rajkamal; Knott, Robert; Cowieson, Nathan P; Elvin, Christopher M; Hill, Anita J; Choudhury, Namita R; Dutta, Naba K
2015-06-04
Rec1-resilin is the first recombinant resilin-mimetic protein polymer, synthesized from exon-1 of the Drosophila melanogaster gene CG15920 that has demonstrated unusual multi-stimuli responsiveness in aqueous solution. Crosslinked hydrogels of Rec1-resilin have also displayed remarkable mechanical properties including near-perfect rubber-like elasticity. The structural basis of these extraordinary properties is not clearly understood. Here we combine a computational and experimental investigation to examine structural ensembles of Rec1-resilin in aqueous solution. The structure of Rec1-resilin in aqueous solutions is investigated experimentally using circular dichroism (CD) spectroscopy and small angle X-ray scattering (SAXS). Both bench-top and synchrotron SAXS are employed to extract structural data sets of Rec1-resilin and to confirm their validity. Computational approaches have been applied to these experimental data sets in order to extract quantitative information about structural ensembles including radius of gyration, pair-distance distribution function, and the fractal dimension. The present work confirms that Rec1-resilin is an intrinsically disordered protein (IDP) that displays equilibrium structural qualities between those of a structured globular protein and a denatured protein. The ensemble optimization method (EOM) analysis reveals a single conformational population with partial compactness. This work provides new insight into the structural ensembles of Rec1-resilin in solution.
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NASA Astrophysics Data System (ADS)
Balu, Rajkamal; Knott, Robert; Cowieson, Nathan P.; Elvin, Christopher M.; Hill, Anita J.; Choudhury, Namita R.; Dutta, Naba K.
2015-06-01
Rec1-resilin is the first recombinant resilin-mimetic protein polymer, synthesized from exon-1 of the Drosophila melanogaster gene CG15920 that has demonstrated unusual multi-stimuli responsiveness in aqueous solution. Crosslinked hydrogels of Rec1-resilin have also displayed remarkable mechanical properties including near-perfect rubber-like elasticity. The structural basis of these extraordinary properties is not clearly understood. Here we combine a computational and experimental investigation to examine structural ensembles of Rec1-resilin in aqueous solution. The structure of Rec1-resilin in aqueous solutions is investigated experimentally using circular dichroism (CD) spectroscopy and small angle X-ray scattering (SAXS). Both bench-top and synchrotron SAXS are employed to extract structural data sets of Rec1-resilin and to confirm their validity. Computational approaches have been applied to these experimental data sets in order to extract quantitative information about structural ensembles including radius of gyration, pair-distance distribution function, and the fractal dimension. The present work confirms that Rec1-resilin is an intrinsically disordered protein (IDP) that displays equilibrium structural qualities between those of a structured globular protein and a denatured protein. The ensemble optimization method (EOM) analysis reveals a single conformational population with partial compactness. This work provides new insight into the structural ensembles of Rec1-resilin in solution.
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Building alternate protein structures using the elastic network model.
Yang, Qingyi; Sharp, Kim A
2009-02-15
We describe a method for efficiently generating ensembles of alternate, all-atom protein structures that (a) differ significantly from the starting structure, (b) have good stereochemistry (bonded geometry), and (c) have good steric properties (absence of atomic overlap). The method uses reconstruction from a series of backbone framework structures that are obtained from a modified elastic network model (ENM) by perturbation along low-frequency normal modes. To ensure good quality backbone frameworks, the single force parameter ENM is modified by introducing two more force parameters to characterize the interaction between the consecutive carbon alphas and those within the same secondary structure domain. The relative stiffness of the three parameters is parameterized to reproduce B-factors, while maintaining good bonded geometry. After parameterization, violations of experimental Calpha-Calpha distances and Calpha-Calpha-Calpha pseudo angles along the backbone are reduced to less than 1%. Simultaneously, the average B-factor correlation coefficient improves to R = 0.77. Two applications illustrate the potential of the approach. (1) 102,051 protein backbones spanning a conformational space of 15 A root mean square deviation were generated from 148 nonredundant proteins in the PDB database, and all-atom models with minimal bonded and nonbonded violations were produced from this ensemble of backbone structures using the SCWRL side chain building program. (2) Improved backbone templates for homology modeling. Fifteen query sequences were each modeled on two targets. For each of the 30 target frameworks, dozens of improved templates could be produced In all cases, improved full atom homology models resulted, of which 50% could be identified blind using the D-Fire statistical potential. (c) 2008 Wiley-Liss, Inc.
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On the structure and phase transitions of power-law Poissonian ensembles
NASA Astrophysics Data System (ADS)
Eliazar, Iddo; Oshanin, Gleb
2012-10-01
Power-law Poissonian ensembles are Poisson processes that are defined on the positive half-line, and that are governed by power-law intensities. Power-law Poissonian ensembles are stochastic objects of fundamental significance; they uniquely display an array of fractal features and they uniquely generate a span of important applications. In this paper we apply three different methods—oligarchic analysis, Lorenzian analysis and heterogeneity analysis—to explore power-law Poissonian ensembles. The amalgamation of these analyses, combined with the topology of power-law Poissonian ensembles, establishes a detailed and multi-faceted picture of the statistical structure and the statistical phase transitions of these elemental ensembles.
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Xiong, Kan; Zwier, Matthew C.; Myshakina, Nataliya S.; Burger, Virginia M.; Asher, Sanford A.; Chong, Lillian T.
2011-01-01
We report the first experimental measurements of Ramachandran Ψ-angle distributions for intrinsically disordered peptides: the N-terminal peptide fragment of tumor suppressor p53 and its P27 mutant form. To provide atomically detailed views of the conformational distributions, we performed classical, explicit-solvent molecular dynamics simulations on the microsecond timescale. Upon binding its partner protein, MDM2, wild-type p53 peptide adopts an α-helical conformation. Mutation of Pro27 to serine results in the highest affinity yet observed for MDM2-binding of the p53 peptide. Both UV resonance Raman spectroscopy (UVRR) and simulations reveal that the P27S mutation decreases the extent of PPII helical content and increases the probability for conformations that are similar to the α-helical MDM2-bound conformation. In addition, UVRR measurements were performed on peptides that were isotopically labeled at the Leu26 residue preceding the Pro27 in order to determine the conformational distributions of Leu26 in the wild-type and mutant peptides. The UVRR and simulation results are in quantitative agreement in terms of the change in the population of non-PPII conformations involving Leu26 upon mutation of Pro27 to serine. Finally, our simulations reveal that the MDM2-bound conformation of the peptide is significantly populated in both the wild-type and mutant isolated peptide ensembles in their unbound states, suggesting that MDM2 binding of the p53 peptides may involve conformational selection. PMID:21528875
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Constraining a Coastal Ocean Model by Surface Observations Using an Ensemble Kalman Filter
NASA Astrophysics Data System (ADS)
De Mey, P. J.; Ayoub, N. K.
2016-02-01
We explore the impact of assimilating sea surface temperature (SST) and sea surface height (SSH) observations in the Bay of Biscay (North-East Atlantic). The study is conducted in the SYMPHONIE coastal circulation model (Marsaleix et al., 2009) on a 3kmx3km grid, with 43 sigma levels. Ensembles are generated by perturbing the wind forcing to analyze the model error subspace spanned by its response to wind forcing uncertainties. The assimilation method is a 4D Ensemble Kalman Filter algorithm with localization. We use the SDAP code developed in the team (https://sourceforge.net/projects/sequoia-dap/). In a first step before the assimilation of real observations, we set up an Ensemble twin experiment protocol where a nature run as well as noisy pseudo-observations of SST and SSH are generated from an Ensemble member (later discarded from the assimilative Ensemble). Our objectives are to assess (1) the adequacy of the choice of error source and perturbation strategy and (2) how effective the surface observational constraint is at constraining the surface and subsurface fields. We first illustrate characteristics of the error subspace generated by the perturbation strategy. We then show that, while the EnKF solves a single seamless problem regardless of the region within our domain, the nature and effectiveness of the data constraint over the shelf differ from those over the abyssal plain.
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Machine learning in the string landscape
NASA Astrophysics Data System (ADS)
Carifio, Jonathan; Halverson, James; Krioukov, Dmitri; Nelson, Brent D.
2017-09-01
We utilize machine learning to study the string landscape. Deep data dives and conjecture generation are proposed as useful frameworks for utilizing machine learning in the landscape, and examples of each are presented. A decision tree accurately predicts the number of weak Fano toric threefolds arising from reflexive polytopes, each of which determines a smooth F-theory compactification, and linear regression generates a previously proven conjecture for the gauge group rank in an ensemble of 4/3× 2.96× {10}^{755} F-theory compactifications. Logistic regression generates a new conjecture for when E 6 arises in the large ensemble of F-theory compactifications, which is then rigorously proven. This result may be relevant for the appearance of visible sectors in the ensemble. Through conjecture generation, machine learning is useful not only for numerics, but also for rigorous results.
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Higher-order chromatin structure: bridging physics and biology.
Fudenberg, Geoffrey; Mirny, Leonid A
2012-04-01
Advances in microscopy and genomic techniques have provided new insight into spatial chromatin organization inside of the nucleus. In particular, chromosome conformation capture data has highlighted the relevance of polymer physics for high-order chromatin organization. In this context, we review basic polymer states, discuss how an appropriate polymer model can be determined from experimental data, and examine the success and limitations of various polymer models of higher-order interphase chromatin organization. By taking into account topological constraints acting on the chromatin fiber, recently developed polymer models of interphase chromatin can reproduce the observed scaling of distances between genomic loci, chromosomal territories, and probabilities of contacts between loci measured by chromosome conformation capture methods. Polymer models provide a framework for the interpretation of experimental data as ensembles of conformations rather than collections of loops, and will be crucial for untangling functional implications of chromosomal organization. Copyright © 2012 Elsevier Ltd. All rights reserved.
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Higher order chromatin structure: bridging physics and biology
Fudenberg, Geoffrey; Mirny, Leonid A.
2012-01-01
Recent advances in microscopy and genomic techniques have provided new insight into spatial chromatin organization inside of the nucleus. In particular, chromosome conformation capture data has highlighted the relevance of polymer physics for high-order chromatin organization. In this context, we review basic polymer states, discuss how an appropriate polymer model can be determined from experimental data, and examine the success and limitations of various polymer models of high-order interphase chromatin organization. By taking into account topological constraints acting on the chromatin fiber, recently-developed polymer models of interphase chromatin can reproduce the observed scaling of distances between genomic loci, chromosomal territories, and probabilities of contacts between loci measured by chromosome conformation capture methods. Polymer models provide a framework for the interpretation of experimental data as ensembles of conformations rather than collections of loops, and will be crucial for untangling functional implications of chromosomal organization. PMID:22360992
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Hybrid Data Assimilation without Ensemble Filtering
NASA Technical Reports Server (NTRS)
Todling, Ricardo; Akkraoui, Amal El
2014-01-01
The Global Modeling and Assimilation Office is preparing to upgrade its three-dimensional variational system to a hybrid approach in which the ensemble is generated using a square-root ensemble Kalman filter (EnKF) and the variational problem is solved using the Grid-point Statistical Interpolation system. As in most EnKF applications, we found it necessary to employ a combination of multiplicative and additive inflations, to compensate for sampling and modeling errors, respectively and, to maintain the small-member ensemble solution close to the variational solution; we also found it necessary to re-center the members of the ensemble about the variational analysis. During tuning of the filter we have found re-centering and additive inflation to play a considerably larger role than expected, particularly in a dual-resolution context when the variational analysis is ran at larger resolution than the ensemble. This led us to consider a hybrid strategy in which the members of the ensemble are generated by simply converting the variational analysis to the resolution of the ensemble and applying additive inflation, thus bypassing the EnKF. Comparisons of this, so-called, filter-free hybrid procedure with an EnKF-based hybrid procedure and a control non-hybrid, traditional, scheme show both hybrid strategies to provide equally significant improvement over the control; more interestingly, the filter-free procedure was found to give qualitatively similar results to the EnKF-based procedure.
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Riniker, Sereina; Christ, Clara D; Hansen, Halvor S; Hünenberger, Philippe H; Oostenbrink, Chris; Steiner, Denise; van Gunsteren, Wilfred F
2011-11-24
The calculation of the relative free energies of ligand-protein binding, of solvation for different compounds, and of different conformational states of a polypeptide is of considerable interest in the design or selection of potential enzyme inhibitors. Since such processes in aqueous solution generally comprise energetic and entropic contributions from many molecular configurations, adequate sampling of the relevant parts of configurational space is required and can be achieved through molecular dynamics simulations. Various techniques to obtain converged ensemble averages and their implementation in the GROMOS software for biomolecular simulation are discussed, and examples of their application to biomolecules in aqueous solution are given. © 2011 American Chemical Society
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Online interactive analysis of protein structure ensembles with Bio3D-web.
Skjærven, Lars; Jariwala, Shashank; Yao, Xin-Qiu; Grant, Barry J
2016-11-15
Bio3D-web is an online application for analyzing the sequence, structure and conformational heterogeneity of protein families. Major functionality is provided for identifying protein structure sets for analysis, their alignment and refined structure superposition, sequence and structure conservation analysis, mapping and clustering of conformations and the quantitative comparison of their predicted structural dynamics. Bio3D-web is based on the Bio3D and Shiny R packages. All major browsers are supported and full source code is available under a GPL2 license from http://thegrantlab.org/bio3d-web CONTACT: bjgrant@umich.edu or lars.skjarven@uib.no. © The Author 2016. Published by Oxford University Press.
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Statistical analysis of EGFR structures' performance in virtual screening
NASA Astrophysics Data System (ADS)
Li, Yan; Li, Xiang; Dong, Zigang
2015-11-01
In this work the ability of EGFR structures to distinguish true inhibitors from decoys in docking and MM-PBSA is assessed by statistical procedures. The docking performance depends critically on the receptor conformation and bound state. The enrichment of known inhibitors is well correlated with the difference between EGFR structures rather than the bound-ligand property. The optimal structures for virtual screening can be selected based purely on the complex information. And the mixed combination of distinct EGFR conformations is recommended for ensemble docking. In MM-PBSA, a variety of EGFR structures have identically good performance in the scoring and ranking of known inhibitors, indicating that the choice of the receptor structure has little effect on the screening.
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Conformational ensemble of human α-synuclein physiological form predicted by molecular simulations.
Rossetti, G; Musiani, F; Abad, E; Dibenedetto, D; Mouhib, H; Fernandez, C O; Carloni, P
2016-02-17
We perform here enhanced sampling simulations of N-terminally acetylated human α-synuclein, an intrinsically disordered protein involved in Parkinson's disease. The calculations, consistent with experiments, suggest that the post-translational modification leads to the formation of a transient amphipathic α-helix. The latter, absent in the non-physiological form, alters protein dynamics at the N-terminal and intramolecular interactions.
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Accelerating the Conformational Sampling of Intrinsically Disordered Proteins.
Do, Trang Nhu; Choy, Wing-Yiu; Karttunen, Mikko
2014-11-11
Intrinsically disordered proteins (IDPs) are a class of proteins lacking a well-defined secondary structure. Instead, they are able to attain multiple conformations, bind to multiple targets, and respond to changes in their surroundings. Functionally, IDPs have been associated with molecular recognition, cell regulation, and signal transduction. The dynamic conformational ensemble of IDPs is highly environmental and binding partner dependent, rendering the characterization of IDPs extremely challenging. Here, we compare the sampling efficiencies of conventional molecular dynamics (MD), well-tempered metadynamics (WT-META), and bias-exchange metadynamics (BE-META). The total simulation time was over 10 μs, and a 20-mer peptide derived from the Neh2 domain of the Nuclear factor erythroid 2-related factor 2 (Nrf2) protein was simulated. BE-META, with a neutral replica and seven biased replicas employing a set of seven relevant collective variables (CVs), provided the most reliable and efficient sampling. Finally, we propose a free-energy reconstruction method based on the probability distribution of the secondary structure contents. This postprocessing analysis confirms the presence of not only the β-hairpin conformation of the free Neh2 peptide but also its rare bound-state-like conformation, both of that have been experimentally observed. In addition, our simulations also predict other possible conformations to be verified with future experiments.
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Imprinting and Recalling Cortical Ensembles
Carrillo-Reid, Luis; Yang, Weijian; Bando, Yuki; Peterka, Darcy S.; Yuste, Rafael
2017-01-01
Neuronal ensembles are coactive groups of neurons that may represent emergent building blocks of neural circuits. They could be formed by Hebbian plasticity, whereby synapses between coactive neurons are strengthened. Here we report that repetitive activation with two-photon optogenetics of neuronal populations in visual cortex of awake mice generates artificially induced ensembles which recur spontaneously after being imprinted and do not disrupt preexistent ones. Moreover, imprinted ensembles can be recalled by single cell stimulation and remain coactive on consecutive days. Our results demonstrate the persistent reconfiguration of cortical circuits by two-photon optogenetics into neuronal ensembles that can perform pattern completion. PMID:27516599
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Huynh, Kim-Hung; Hong, Myoung-ki; Lee, Clarice; Tran, Huyen-Thi; Lee, Sang Hee; Ahn, Yeh-Jin; Cha, Sun-Shin; Kang, Lin-Woo
2015-11-01
Acinetobacter baumannii, which is emerging as a multidrug-resistant nosocomial pathogen, causes a number of diseases, including pneumonia, bacteremia, meningitis, and skin infections. With ATP hydrolysis, the D-alanine-D-alanine ligase (DDL) catalyzes the synthesis of D-alanyl-D-alanine, which is an essential component of bacterial peptidoglycan. In this study, we determined the crystal structure of DDL from A. baumannii (AbDDL) at a resolution of 2.2 Å. The asymmetric unit contained six protomers of AbDDL. Five protomers had a closed conformation in the central domain, while one protomer had an open conformation in the central domain. The central domain with an open conformation did not interact with crystallographic symmetry-related protomers and the conformational change of the central domain was not due to crystal packing. The central domain of AbDDL can have an ensemble of the open and closed conformations before the binding of substrate ATP. The conformational change of the central domain is important for the catalytic activity and the detail information will be useful for the development of inhibitors against AbDDL and putative antibacterial agents against A. baumannii. The AbDDL structure was compared with that of other DDLs that were in complex with potent inhibitors and the catalytic activity of AbDDL was confirmed using enzyme kinetics assays.
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Multiple conformations are a conserved and regulatory feature of the RB1 5′ UTR
Kutchko, Katrina M.; Sanders, Wes; Ziehr, Ben; Phillips, Gabriela; Solem, Amanda; Halvorsen, Matthew; Weeks, Kevin M.; Moorman, Nathaniel
2015-01-01
Folding to a well-defined conformation is essential for the function of structured ribonucleic acids (RNAs) like the ribosome and tRNA. Structured elements in the untranslated regions (UTRs) of specific messenger RNAs (mRNAs) are known to control expression. The importance of unstructured regions adopting multiple conformations, however, is still poorly understood. High-resolution SHAPE-directed Boltzmann suboptimal sampling of the Homo sapiens Retinoblastoma 1 (RB1) 5′ UTR yields three distinct conformations compatible with the experimental data. Private single nucleotide variants (SNVs) identified in two patients with retinoblastoma each collapse the structural ensemble to a single but distinct well-defined conformation. The RB1 5′ UTRs from Bos taurus (cow) and Trichechus manatus latirostris (manatee) are divergent in sequence from H. sapiens (human) yet maintain structural compatibility with high-probability base pairs. SHAPE chemical probing of the cow and manatee RB1 5′ UTRs reveals that they also adopt multiple conformations. Luciferase reporter assays reveal that 5′ UTR mutations alter RB1 expression. In a traditional model of disease, causative SNVs disrupt a key structural element in the RNA. For the subset of patients with heritable retinoblastoma-associated SNVs in the RB1 5′ UTR, the absence of multiple structures is likely causative of the cancer. Our data therefore suggest that selective pressure will favor multiple conformations in eukaryotic UTRs to regulate expression. PMID:25999316
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Ganguly, Debabani; Chen, Jianhan
2009-04-15
Intrinsically disordered proteins (IDPs) are a newly recognized class of functional proteins for which a lack of stable tertiary fold is required for function. Because of the heterogeneous and dynamical nature, molecular modeling is necessary to provide the missing details of disordered states of IDP that are crucial for understanding their functions. In particular, generalized Born (GB) implicit solvent, combined with replica exchange (REX), might offer an optimal balance between accuracy and efficiency for modeling IDPs. We carried out extensive REX simulations in an optimized GB force field to characterize the disordered states of a regulatory IDP, KID domain of transcription factor CREB, and its phosphorylated form, pKID. The results revealed that both KID and pKID, though highly disordered on the tertiary level, are compact and mainly occupy a small number of helical substates. Interestingly, although phosphorylation of KID Ser133 leads only to marginal changes in average helicities on the ensemble level, underlying conformational substates differ significantly. In particular, pSer133 appears to restrict the accessible conformational space of the loop region and thus reduces the entropic cost of KID folding upon binding to the KIX domain of CREB-binding protein. Such an expanded role of phosphorylation in the KID:KIX recognition was not previously recognized because of a lack of substantial conformational changes on the ensemble level and inaccessibility of the structural details from experiments. The results also suggest that an implicit solvent-based modeling framework, despite various existing limitations, might be feasible for accurate atomistic simulation of small IDPs in general.
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The role of alpha-, 3(10)-, and pi-helix in helix-->coil transitions.
Armen, Roger; Alonso, Darwin O V; Daggett, Valerie
2003-06-01
The conformational equilibrium between 3(10)- and alpha-helical structure has been studied via high-resolution NMR spectroscopy by Millhauser and coworkers using the MW peptide Ac-AMAAKAWAAKA AAARA-NH2. Their 750-MHz nuclear Overhauser effect spectroscopy (NOESY) spectra were interpreted to reflect appreciable populations of 3(10)-helix throughout the peptide, with the greatest contribution at the N and C termini. The presence of simultaneous alphaN(i,i + 2) and alphaN(i,i + 4) NOE cross-peaks was proposed to represent conformational averaging between 3(10)- and alpha-helical structures. In this study, we describe 25-nsec molecular dynamics simulations of the MW peptide at 298 K, using both an 8 A and a 10 A force-shifted nonbonded cutoff. The ensemble averages of both simulations are in reasonable agreement with the experimental helical content from circular dichroism (CD), the (3)J(HNalpha) coupling constants, and the 57 observed NOEs. Analysis of the structures from both simulations revealed very little formation of contiguous i --> i + 3 hydrogen bonds (3(10)-helix); however, there was a large population of bifurcated i --> i + 3 and i --> i + 4 alpha-helical hydrogen bonds. In addition, both simulations contained considerable populations of pi-helix (i --> i + 5 hydrogen bonds). Individual turns formed over residues 1-9, which we predict contribute to the intensities of the experimentally observed alphaN(i,i + 2) NOEs. Here we show how sampling of both folded and unfolded structures can provide a structural framework for deconvolution of the conformational contributions to experimental ensemble averages.
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The role of α-, 310-, and π-helix in helix→coil transitions
Armen, Roger; Alonso, Darwin O.V.; Daggett, Valerie
2003-01-01
The conformational equilibrium between 310- and α-helical structure has been studied via high-resolution NMR spectroscopy by Millhauser and coworkers using the MW peptide Ac-AMAAKAWAAKA AAARA-NH2. Their 750-MHz nuclear Overhauser effect spectroscopy (NOESY) spectra were interpreted to reflect appreciable populations of 310-helix throughout the peptide, with the greatest contribution at the N and C termini. The presence of simultaneous αN(i,i + 2) and αN(i,i + 4) NOE cross-peaks was proposed to represent conformational averaging between 310- and α-helical structures. In this study, we describe 25-nsec molecular dynamics simulations of the MW peptide at 298 K, using both an 8 Å and a 10 Å force-shifted nonbonded cutoff. The ensemble averages of both simulations are in reasonable agreement with the experimental helical content from circular dichroism (CD), the 3JHNα coupling constants, and the 57 observed NOEs. Analysis of the structures from both simulations revealed very little formation of contiguous i → i + 3 hydrogen bonds (310-helix); however, there was a large population of bifurcated i → i + 3 and i → i + 4 α-helical hydrogen bonds. In addition, both simulations contained considerable populations of π-helix (i → i + 5 hydrogen bonds). Individual turns formed over residues 1–9, which we predict contribute to the intensities of the experimentally observed αN(i,i + 2) NOEs. Here we show how sampling of both folded and unfolded structures can provide a structural framework for deconvolution of the conformational contributions to experimental ensemble averages. PMID:12761385
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NASA Astrophysics Data System (ADS)
Romanova, Vanya; Hense, Andreas; Wahl, Sabrina; Brune, Sebastian; Baehr, Johanna
2016-04-01
The decadal variability and its predictability of the surface net freshwater fluxes is compared in a set of retrospective predictions, all using the same model setup, and only differing in the implemented ocean initialisation method and ensemble generation method. The basic aim is to deduce the differences between the initialization/ensemble generation methods in view of the uncertainty of the verifying observational data sets. The analysis will give an approximation of the uncertainties of the net freshwater fluxes, which up to now appear to be one of the most uncertain products in observational data and model outputs. All ensemble generation methods are implemented into the MPI-ESM earth system model in the framework of the ongoing MiKlip project (www.fona-miklip.de). Hindcast experiments are initialised annually between 2000-2004, and from each start year 10 ensemble members are initialized for 5 years each. Four different ensemble generation methods are compared: (i) a method based on the Anomaly Transform method (Romanova and Hense, 2015) in which the initial oceanic perturbations represent orthogonal and balanced anomaly structures in space and time and between the variables taken from a control run, (ii) one-day-lagged ocean states from the MPI-ESM-LR baseline system (iii) one-day-lagged of ocean and atmospheric states with preceding full-field nudging to re-analysis in both the atmospheric and the oceanic component of the system - the baseline one MPI-ESM-LR system, (iv) an Ensemble Kalman Filter (EnKF) implemented into oceanic part of MPI-ESM (Brune et al. 2015), assimilating monthly subsurface oceanic temperature and salinity (EN3) using the Parallel Data Assimilation Framework (PDAF). The hindcasts are evaluated probabilistically using fresh water flux data sets from four different reanalysis data sets: MERRA, NCEP-R1, GFDL ocean reanalysis and GECCO2. The assessments show no clear differences in the evaluations scores on regional scales. However, on the global scale the physically motivated methods (i) and (iv) provide probabilistic hindcasts with a consistently higher reliability than the lagged initialization methods (ii)/(iii) despite the large uncertainties in the verifying observations and in the simulations.
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Challenges in Visual Analysis of Ensembles
Crossno, Patricia
2018-04-12
Modeling physical phenomena through computational simulation increasingly relies on generating a collection of related runs, known as an ensemble. In this paper, we explore the challenges we face in developing analysis and visualization systems for large and complex ensemble data sets, which we seek to understand without having to view the results of every simulation run. Implementing approaches and ideas developed in response to this goal, we demonstrate the analysis of a 15K run material fracturing study using Slycat, our ensemble analysis system.
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Challenges in Visual Analysis of Ensembles
DOE Office of Scientific and Technical Information (OSTI.GOV)
Crossno, Patricia
Modeling physical phenomena through computational simulation increasingly relies on generating a collection of related runs, known as an ensemble. In this paper, we explore the challenges we face in developing analysis and visualization systems for large and complex ensemble data sets, which we seek to understand without having to view the results of every simulation run. Implementing approaches and ideas developed in response to this goal, we demonstrate the analysis of a 15K run material fracturing study using Slycat, our ensemble analysis system.
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Cooperative Allosteric Ligand Binding in Calmodulin
NASA Astrophysics Data System (ADS)
Nandigrami, Prithviraj
Conformational dynamics is often essential for a protein's function. For example, proteins are able to communicate the effect of binding at one site to a distal region of the molecule through changes in its conformational dynamics. This so called allosteric coupling fine tunes the sensitivity of ligand binding to changes in concentration. A conformational change between a "closed" (apo) and an "open" (holo) conformation upon ligation often produces this coupling between binding sites. Enhanced sensitivity between the unbound and bound ensembles leads to a sharper binding curve. There are two basic conceptual frameworks that guide our visualization about ligand binding mechanisms. First, a ligand can stabilize the unstable "open" state from a dynamic ensemble of conformations within the unbound basin. This binding mechanism is called conformational selection. Second, a ligand can weakly bind to the low-affinity "closed" state followed by a conformational transition to the "open" state. In this dissertation, I focus on molecular dynamics simulations to understand microscopic origins of ligand binding cooperativity. A minimal model of allosteric binding transitions must include ligand binding/unbinding events, while capturing the transition mechanism between two distinct meta-stable free energy basins. Due in part to computational timescales limitations, work in this dissertation describes large-scale conformational transitions through a simplified, coarse-grained model based on the energy basins defined by the open and closed conformations of the protein Calmodulin (CaM). CaM is a ubiquitous calcium-binding protein consisting of two structurally similar globular domains connected by a flexible linker. The two domains of CaM, N-terminal domain (nCaM) and C-terminal domain (cCaM) consists of two helix-loop-helix motifs (the EF-hands) connected by a flexible linker. Each domain of CaM consists of two binding loops and binds 2 calcium ions each. The intact domain binds up to 4 calcium ions. The simulations use a coupled molecular dynamics/monte carlo scheme where the protein dynamics is simulated explicitly, while ligand binding/unbinding are treated implicitly. In the model, ligand binding/unbinding events coupled with a conformational change of the protein within the grand canonical ensemble. Here, ligand concentration is controlled through the chemical potential (micro). This allows us to use a simple thermodynamic model to analyze the simulated data and quantify binding cooperativity. Simulated binding titration curves are calculated through equilibrium simulations at different values of micro. First, I study domain opening transitions of isolated nCaM and cCaM in the absence of calcium. This work is motivated by results from a recent analytic variational model that predicts distinct domain opening transition mechanism for the domains of CaM. This is a surprising result because the domains have the same folded state topology. In the simulations, I find the two domains of CaM have distinct transition mechanism over a broad range of temperature, in harmony with the analytic predictions. In particular, the simulated transition mechanism of nCaM follows a two-state behavior, while domain opening in cCaM involves global unfolding and refolding of the tertiary structure. The unfolded intermediate also appears in the landscape of nCaM, but at a higher temperature than it appears in cCaM's energy landscape. This is consistent with nCaM's higher thermal stability. Under approximate physiological conditions, majority of the sampled transitions in cCaM involves unfolding and refolding during conformational change. Kinetically, the transient unfolding and refolding in cCaM significantly slows the domain opening and closing rates in cCaM. Second, I investigate the structural origins of binding affinity and allosteric cooperativity of binding 2 calcium-ions to each domain of CaM. In my work, I predict the order of binding strength of CaM's loops. I analyze simulated binding curves within the framework of the classic Monod-Wyman-Changeux (MWC) model of allostery to extract the binding free energies to the closed and open ensembles. The simulations predict that cCaM binds calcium with higher affinity and greater cooperativity than nCaM. Where it is possible to compare, these predictions are in good agreement with experimental results. The analysis of the simulations offers a rationale for why the two domains differ in cooperativity: the higher cooperativity of cCaM is due to larger difference in affinity of its binding loops. Third, I extend the work to investigate structural origins of binding cooperativity of 4 calcium-ions to intact CaM. I characterize the microscopic cooperativities of each ligation state and provide a kinetic description of the binding mechanism. Due to the heterogeneous nature of CaM's loops, as predicted in our simulations of isolated domains, I focus on investigating the influence of this heterogeneity on the kinetic flux of binding pathways as a function of concentration. The formalism developed for Network Models of protein folding kinetics, is used to evaluate the directed flux of all possible pathways between unligated and fully loaded CaM. (Abstract shortened by ProQuest.).
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NASA Astrophysics Data System (ADS)
Maleki, Yusef; Zheltikov, Aleksei M.
2018-01-01
An ensemble of nitrogen-vacancy (NV) centers coupled to a circuit QED device is shown to enable an efficient, high-fidelity generation of high-N00N states. Instead of first creating entanglement and then increasing the number of entangled particles N , our source of high-N00N states first prepares a high-N Fock state in one of the NV ensembles and then entangles it to the rest of the system. With such a strategy, high-N N00N states can be generated in just a few operational steps with an extraordinary fidelity. Once prepared, such a state can be stored over a longer period of time due to the remarkably long coherence time of NV centers.
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Kelly, Kristen L; Dalton, Shannon R; Wai, Rebecca B; Ramchandani, Kanika; Xu, Rosalind J; Linse, Sara; Londergan, Casey H
2018-03-22
Seven native residues on the regulatory protein calmodulin, including three key methionine residues, were replaced (one by one) by the vibrational probe amino acid cyanylated cysteine, which has a unique CN stretching vibration that reports on its local environment. Almost no perturbation was caused by this probe at any of the seven sites, as reported by CD spectra of calcium-bound and apo calmodulin and binding thermodynamics for the formation of a complex between calmodulin and a canonical target peptide from skeletal muscle myosin light chain kinase measured by isothermal titration. The surprising lack of perturbation suggests that this probe group could be applied directly in many protein-protein binding interfaces. The infrared absorption bands for the probe groups reported many dramatic changes in the probes' local environments as CaM went from apo- to calcium-saturated to target peptide-bound conditions, including large frequency shifts and a variety of line shapes from narrow (interpreted as a rigid and invariant local environment) to symmetric to broad and asymmetric (likely from multiple coexisting and dynamically exchanging structures). The fast intrinsic time scale of infrared spectroscopy means that the line shapes report directly on site-specific details of calmodulin's variable structural distribution. Though quantitative interpretation of the probe line shapes depends on a direct connection between simulated ensembles and experimental data that does not yet exist, formation of such a connection to data such as that reported here would provide a new way to evaluate conformational ensembles from data that directly contains the structural distribution. The calmodulin probe sites developed here will also be useful in evaluating the binding mode of calmodulin with many uncharacterized regulatory targets.
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2013-01-01
Here we present a novel, end-point method using the dead-end-elimination and A* algorithms to efficiently and accurately calculate the change in free energy, enthalpy, and configurational entropy of binding for ligand–receptor association reactions. We apply the new approach to the binding of a series of human immunodeficiency virus (HIV-1) protease inhibitors to examine the effect ensemble reranking has on relative accuracy as well as to evaluate the role of the absolute and relative ligand configurational entropy losses upon binding in affinity differences for structurally related inhibitors. Our results suggest that most thermodynamic parameters can be estimated using only a small fraction of the full configurational space, and we see significant improvement in relative accuracy when using an ensemble versus single-conformer approach to ligand ranking. We also find that using approximate metrics based on the single-conformation enthalpy differences between the global minimum energy configuration in the bound as well as unbound states also correlates well with experiment. Using a novel, additive entropy expansion based on conditional mutual information, we also analyze the source of ligand configurational entropy loss upon binding in terms of both uncoupled per degree of freedom losses as well as changes in coupling between inhibitor degrees of freedom. We estimate entropic free energy losses of approximately +24 kcal/mol, 12 kcal/mol of which stems from loss of translational and rotational entropy. Coupling effects contribute only a small fraction to the overall entropy change (1–2 kcal/mol) but suggest differences in how inhibitor dihedral angles couple to each other in the bound versus unbound states. The importance of accounting for flexibility in drug optimization and design is also discussed. PMID:24250277
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Shi, Jade; Nobrega, R. Paul; Schwantes, Christian; ...
2017-03-08
The dynamics of globular proteins can be described in terms of transitions between a folded native state and less-populated intermediates, or excited states, which can play critical roles in both protein folding and function. Excited states are by definition transient species, and therefore are difficult to characterize using current experimental techniques. We report an atomistic model of the excited state ensemble of a stabilized mutant of an extensively studied flavodoxin fold protein CheY. We employed a hybrid simulation and experimental approach in which an aggregate 42 milliseconds of all-atom molecular dynamics were used as an informative prior for the structuremore » of the excited state ensemble. The resulting prior was then refined against small-angle X-ray scattering (SAXS) data employing an established method (EROS). The most striking feature of the resulting excited state ensemble was an unstructured N-terminus stabilized by non-native contacts in a conformation that is topologically simpler than the native state. We then predict incisive single molecule FRET experiments, using these results, as a means of model validation. Our study demonstrates the paradigm of uniting simulation and experiment in a statistical model to study the structure of protein excited states and rationally design validating experiments.« less
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NASA Astrophysics Data System (ADS)
Shi, Jade; Nobrega, R. Paul; Schwantes, Christian; Kathuria, Sagar V.; Bilsel, Osman; Matthews, C. Robert; Lane, T. J.; Pande, Vijay S.
2017-03-01
The dynamics of globular proteins can be described in terms of transitions between a folded native state and less-populated intermediates, or excited states, which can play critical roles in both protein folding and function. Excited states are by definition transient species, and therefore are difficult to characterize using current experimental techniques. Here, we report an atomistic model of the excited state ensemble of a stabilized mutant of an extensively studied flavodoxin fold protein CheY. We employed a hybrid simulation and experimental approach in which an aggregate 42 milliseconds of all-atom molecular dynamics were used as an informative prior for the structure of the excited state ensemble. This prior was then refined against small-angle X-ray scattering (SAXS) data employing an established method (EROS). The most striking feature of the resulting excited state ensemble was an unstructured N-terminus stabilized by non-native contacts in a conformation that is topologically simpler than the native state. Using these results, we then predict incisive single molecule FRET experiments as a means of model validation. This study demonstrates the paradigm of uniting simulation and experiment in a statistical model to study the structure of protein excited states and rationally design validating experiments.
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Johnson, Quentin R; Lindsay, Richard J; Shen, Tongye
2018-02-21
A computational method which extracts the dominant motions from an ensemble of biomolecular conformations via a correlation analysis of residue-residue contacts is presented. The algorithm first renders the structural information into contact matrices, then constructs the collective modes based on the correlated dynamics of a selected set of dynamic contacts. Associated programs can bridge the results for further visualization using graphics software. The aim of this method is to provide an analysis of conformations of biopolymers from the contact viewpoint. It may assist a systematical uncovering of conformational switching mechanisms existing in proteins and biopolymer systems in general by statistical analysis of simulation snapshots. In contrast to conventional correlation analyses of Cartesian coordinates (such as distance covariance analysis and Cartesian principal component analysis), this program also provides an alternative way to locate essential collective motions in general. Herein, we detail the algorithm in a stepwise manner and comment on the importance of the method as applied to decoding allosteric mechanisms. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.
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Structural landscape of the proline-rich domain of Sos1 nucleotide exchange factor.
McDonald, Caleb B; Bhat, Vikas; Kurouski, Dmitry; Mikles, David C; Deegan, Brian J; Seldeen, Kenneth L; Lednev, Igor K; Farooq, Amjad
2013-01-01
Despite its key role in mediating a plethora of cellular signaling cascades pertinent to health and disease, little is known about the structural landscape of the proline-rich (PR) domain of Sos1 guanine nucleotide exchange factor. Herein, using a battery of biophysical tools, we provide evidence that the PR domain of Sos1 is structurally disordered and adopts an extended random coil-like conformation in solution. Of particular interest is the observation that while chemical denaturation of PR domain results in the formation of a significant amount of polyproline II (PPII) helices, it has little or negligible effect on its overall size as measured by its hydrodynamic radius. Our data also show that the PR domain displays a highly dynamic conformational basin in agreement with the knowledge that the intrinsically unstructured proteins rapidly interconvert between an ensemble of conformations. Collectively, our study provides new insights into the conformational equilibrium of a key signaling molecule with important consequences on its physiological function. Copyright © 2013 Elsevier B.V. All rights reserved.
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Computational carbohydrate chemistry: what theoretical methods can tell us
Woods, Robert J.
2014-01-01
Computational methods have had a long history of application to carbohydrate systems and their development in this regard is discussed. The conformational analysis of carbohydrates differs in several ways from that of other biomolecules. Many glycans appear to exhibit numerous conformations coexisting in solution at room temperature and a conformational analysis of a carbohydrate must address both spatial and temporal properties. When solution nuclear magnetic resonance data are used for comparison, the simulation must give rise to ensemble-averaged properties. In contrast, when comparing to experimental data obtained from crystal structures a simulation of a crystal lattice, rather than of an isolated molecule, is appropriate. Molecular dynamics simulations are well suited for such condensed phase modeling. Interactions between carbohydrates and other biological macromolecules are also amenable to computational approaches. Having obtained a three-dimensional structure of the receptor protein, it is possible to model with accuracy the conformation of the carbohydrate in the complex. An example of the application of free energy perturbation simulations to the prediction of carbohydrate-protein binding energies is presented. PMID:9579797
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Single Molecule Study of Metalloregulatory Protein-DNA Interactions
NASA Astrophysics Data System (ADS)
Sarkar, Susanta; Benitez, Jaime; Huang, Zhengxi; Wang, Qi; Chen, Peng
2007-03-01
Control of metal concentrations is essential for living body. Metalloregulatory proteins respond to metal concentrations by regulating transcriptions of metal resistance genes via protein-DNA interactions. It is thus necessary to understand interactions of metalloregulatory proteins with DNA. Ensemble measurements provide average behavior of a vast number of biomolecules. In contrast, single molecule spectroscopy can track single molecules individually and elucidate dynamics of processes of short time scales and intermediate structures not revealed by ensemble measurements. Here we present single molecule study of interactions between PbrR691, a MerR-family metalloregulatory protein and DNA. We presume that the dynamics of protein/DNA conformational changes and interactions are important for the transcription regulation and kinetics of these dynamic processes can provide useful information about the mechanisms of these metalloregulatory proteins.
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Urea-Induced Unfolding of the Immunity Protein Im9 Monitored by spFRET
Tezuka-Kawakami, Tomoko; Gell, Chris; Brockwell, David J.; Radford, Sheena E.; Smith, D. Alastair
2006-01-01
We have studied the urea-induced unfolding of the E colicin immunity protein Im9 using diffusion single-pair fluorescence resonance energy transfer. Detailed examination of the proximity ratio of the native and denatured molecules over a wide range of urea concentrations suggests that the conformational properties of both species are denaturant-dependent. Whereas native molecules become gradually more expanded as urea concentration increases, denatured molecules show a dramatic dependence of the relationship between proximity ratio and denaturant concentration, consistent with substantial compaction of the denatured ensemble at low denaturant concentrations. Analysis of the widths of the proximity ratio distributions for each state suggests that whereas the native state ensemble is relatively narrow and homogeneous, the denatured state may possess heterogeneity in mildly denaturing conditions. PMID:16798813
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Endrizzi, James A; Beernink, Peter T
2017-11-01
A classical model for allosteric regulation of enzyme activity posits an equilibrium between inactive and active conformations. An alternative view is that allosteric activation is achieved by increasing the potential for conformational changes that are essential for catalysis. In the present study, substitution of a basic residue in the active site of the catalytic (C) trimer of aspartate transcarbamoylase with a non-polar residue results in large interdomain hinge changes in the three chains of the trimer. One conformation is more open than the chains in both the wild-type C trimer and the catalytic chains in the holoenzyme, the second is closed similar to the bisubstrate-analog bound conformation and the third hinge angle is intermediate to the other two. The active-site 240s loop conformation is very different between the most open and closed chains, and is disordered in the third chain, as in the holoenzyme. We hypothesize that binding of anionic substrates may promote similar structural changes. Further, the ability of the three catalytic chains in the trimer to access the open and closed active-site conformations simultaneously suggests a cyclic catalytic mechanism, in which at least one of the chains is in an open conformation suitable for substrate binding whereas another chain is closed for catalytic turnover. Based on the many conformations observed for the chains in the isolated catalytic trimer to date, we propose that allosteric activation of the holoenzyme occurs by release of quaternary constraint into an ensemble of active-site conformations. © 2017 The Protein Society.
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NASA Astrophysics Data System (ADS)
Lerner, Eitan; Ingargiola, Antonino; Weiss, Shimon
2018-03-01
Bio-macromolecules carry out complicated functions through structural changes. To understand their mechanism of action, the structure of each step has to be characterized. While classical structural biology techniques allow the characterization of a few "structural snapshots" along the enzymatic cycle (usually of stable conformations), they do not cover all (and often fast interconverting) structures in the ensemble, where each may play an important functional role. Recently, several groups have demonstrated that structures of different conformations in solution could be solved by measuring multiple distances between different pairs of residues using single-molecule Förster resonance energy transfer (smFRET) and using them as constrains for hybrid/integrative structural modeling. However, this approach is limited in cases where the conformational dynamics is faster than the technique's temporal resolution. In this study, we combine existing tools that elucidate sub-millisecond conformational dynamics together with hybrid/integrative structural modeling to study the conformational states of the transcription bubble in the bacterial RNA polymerase-promoter open complex (RPo). We measured microsecond alternating laser excitation-smFRET of differently labeled lacCONS promoter dsDNA constructs. We used a combination of burst variance analysis, photon-by-photon hidden Markov modeling, and the FRET-restrained positioning and screening approach to identify two conformational states for RPo. The experimentally derived distances of one conformational state match the known crystal structure of bacterial RPo. The experimentally derived distances of the other conformational state have characteristics of a scrunched RPo. These findings support the hypothesis that sub-millisecond dynamics in the transcription bubble are responsible for transcription start site selection.
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Internal Spin Control, Squeezing and Decoherence in Ensembles of Alkali Atomic Spins
NASA Astrophysics Data System (ADS)
Norris, Leigh Morgan
Large atomic ensembles interacting with light are one of the most promising platforms for quantum information processing. In the past decade, novel applications for these systems have emerged in quantum communication, quantum computing, and metrology. Essential to all of these applications is the controllability of the atomic ensemble, which is facilitated by a strong coupling between the atoms and light. Non-classical spin squeezed states are a crucial step in attaining greater ensemble control. The degree of entanglement present in these states, furthermore, serves as a benchmark for the strength of the atom-light interaction. Outside the broader context of quantum information processing with atomic ensembles, spin squeezed states have applications in metrology, where their quantum correlations can be harnessed to improve the precision of magnetometers and atomic clocks. This dissertation focuses upon the production of spin squeezed states in large ensembles of cold trapped alkali atoms interacting with optical fields. While most treatments of spin squeezing consider only the case in which the ensemble is composed of two level systems or qubits, we utilize the entire ground manifold of an alkali atom with hyperfine spin f greater than or equal to 1/2, a qudit. Spin squeezing requires non-classical correlations between the constituent atomic spins, which are generated through the atoms' collective coupling to the light. Either through measurement or multiple interactions with the atoms, the light mediates an entangling interaction that produces quantum correlations. Because the spin squeezing treated in this dissertation ultimately originates from the coupling between the light and atoms, conventional approaches of improving this squeezing have focused on increasing the optical density of the ensemble. The greater number of internal degrees of freedom and the controllability of the spin-f ground hyperfine manifold enable novel methods of enhancing squeezing. In particular, we find that state preparation using control of the internal hyperfine spin increases the entangling power of squeezing protocols when f>1/2. Post-processing of the ensemble using additional internal spin control converts this entanglement into metrologically useful spin squeezing. By employing a variation of the Holstein-Primakoff approximation, in which the collective spin observables of the atomic ensemble are treated as quadratures of a bosonic mode, we model entanglement generation, spin squeezing and the effects of internal spin control. The Holstein-Primakoff formalism also enables us to take into account the decoherence of the ensemble due to optical pumping. While most works ignore or treat optical pumping phenomenologically, we employ a master equation derived from first principles. Our analysis shows that state preparation and the hyperfine spin size have a substantial impact upon both the generation of spin squeezing and the decoherence of the ensemble. Through a numerical search, we determine state preparations that enhance squeezing protocols while remaining robust to optical pumping. Finally, most work on spin squeezing in atomic ensembles has treated the light as a plane wave that couples identically to all atoms. In the final part of this dissertation, we go beyond the customary plane wave approximation on the light and employ focused paraxial beams, which are more efficiently mode matched to the radiation pattern of the atomic ensemble. The mathematical formalism and the internal spin control techniques that we applied in the plane wave case are generalized to accommodate the non-homogeneous paraxial probe. We find the optimal geometries of the atomic ensemble and the probe for mode matching and generation of spin squeezing.
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Internal Spin Control, Squeezing and Decoherence in Ensembles of Alkali Atomic Spins
NASA Astrophysics Data System (ADS)
Norris, Leigh Morgan
Large atomic ensembles interacting with light are one of the most promising platforms for quantum information processing. In the past decade, novel applications for these systems have emerged in quantum communication, quantum computing, and metrology. Essential to all of these applications is the controllability of the atomic ensemble, which is facilitated by a strong coupling between the atoms and light. Non-classical spin squeezed states are a crucial step in attaining greater ensemble control. The degree of entanglement present in these states, furthermore, serves as a benchmark for the strength of the atom-light interaction. Outside the broader context of quantum information processing with atomic ensembles, spin squeezed states have applications in metrology, where their quantum correlations can be harnessed to improve the precision of magnetometers and atomic clocks. This dissertation focuses upon the production of spin squeezed states in large ensembles of cold trapped alkali atoms interacting with optical fields. While most treatments of spin squeezing consider only the case in which the ensemble is composed of two level systems or qubits, we utilize the entire ground manifold of an alkali atom with hyperfine spin f greater or equal to 1/2, a qudit. Spin squeezing requires non-classical correlations between the constituent atomic spins, which are generated through the atoms' collective coupling to the light. Either through measurement or multiple interactions with the atoms, the light mediates an entangling interaction that produces quantum correlations. Because the spin squeezing treated in this dissertation ultimately originates from the coupling between the light and atoms, conventional approaches of improving this squeezing have focused on increasing the optical density of the ensemble. The greater number of internal degrees of freedom and the controllability of the spin-f ground hyperfine manifold enable novel methods of enhancing squeezing. In particular, we find that state preparation using control of the internal hyperfine spin increases the entangling power of squeezing protocols when f >1/2. Post-processing of the ensemble using additional internal spin control converts this entanglement into metrologically useful spin squeezing. By employing a variation of the Holstein-Primakoff approximation, in which the collective spin observables of the atomic ensemble are treated as quadratures of a bosonic mode, we model entanglement generation, spin squeezing and the effects of internal spin control. The Holstein-Primakoff formalism also enables us to take into account the decoherence of the ensemble due to optical pumping. While most works ignore or treat optical pumping phenomenologically, we employ a master equation derived from first principles. Our analysis shows that state preparation and the hyperfine spin size have a substantial impact upon both the generation of spin squeezing and the decoherence of the ensemble. Through a numerical search, we determine state preparations that enhance squeezing protocols while remaining robust to optical pumping. Finally, most work on spin squeezing in atomic ensembles has treated the light as a plane wave that couples identically to all atoms. In the final part of this dissertation, we go beyond the customary plane wave approximation on the light and employ focused paraxial beams, which are more efficiently mode matched to the radiation pattern of the atomic ensemble. The mathematical formalism and the internal spin control techniques that we applied in the plane wave case are generalized to accommodate the non-homogeneous paraxial probe. We find the optimal geometries of the atomic ensemble and the probe for mode matching and generation of spin squeezing.
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Ocean Predictability and Uncertainty Forecasts Using Local Ensemble Transfer Kalman Filter (LETKF)
NASA Astrophysics Data System (ADS)
Wei, M.; Hogan, P. J.; Rowley, C. D.; Smedstad, O. M.; Wallcraft, A. J.; Penny, S. G.
2017-12-01
Ocean predictability and uncertainty are studied with an ensemble system that has been developed based on the US Navy's operational HYCOM using the Local Ensemble Transfer Kalman Filter (LETKF) technology. One of the advantages of this method is that the best possible initial analysis states for the HYCOM forecasts are provided by the LETKF which assimilates operational observations using ensemble method. The background covariance during this assimilation process is implicitly supplied with the ensemble avoiding the difficult task of developing tangent linear and adjoint models out of HYCOM with the complicated hybrid isopycnal vertical coordinate for 4D-VAR. The flow-dependent background covariance from the ensemble will be an indispensable part in the next generation hybrid 4D-Var/ensemble data assimilation system. The predictability and uncertainty for the ocean forecasts are studied initially for the Gulf of Mexico. The results are compared with another ensemble system using Ensemble Transfer (ET) method which has been used in the Navy's operational center. The advantages and disadvantages are discussed.
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Application of Ensemble Kalman Filter in Power System State Tracking and Sensitivity
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Yulan; Huang, Zhenyu; Zhou, Ning
2012-05-01
Ensemble Kalman Filter (EnKF) is proposed to track dynamic states of generators. The algorithm of EnKF and its application to generator state tracking are presented in detail. The accuracy and sensitivity of the method are analyzed with respect to initial state errors, measurement noise, unknown fault locations, time steps and parameter errors. It is demonstrated through simulation studies that even with some errors in the parameters, the developed EnKF can effectively track generator dynamic states using disturbance data.
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Matsui, Tsutomu; Tsuruta, Hiro; Johnson, John E.
2010-01-01
Nudaurelia capensis omega virus has a well-characterized T = 4 capsid that undergoes a pH-dependent large conformational changes (LCC) and associated auto-catalytic cleavage of the subunit. We examined previously the particle size at different pH values and showed that maturation occurred at pH 5.5. We now characterized the LCC with time-resolved small-angle x-ray scattering and showed that there were three kinetic stages initiated with an incremental drop in pH: 1), a rapid (<10 ms) collapse to an incrementally smaller particle; 2), a continuous size reduction over the next 5 s; and 3), a smaller final transition occurring in 2–3 min. Equilibrium measurements similar to those reported previously, but now more precise, showed that the particle dimension between pH 5.5 and 5 requires the autocatalytic cleavage to achieve its final compact size. A balance of electrostatic and structural forces shapes the energy landscape of the LCC with the latter requiring annealing of portions of the subunit. Equilibrium experiments showed that many intermediate states could be populated with a homogeneous ensemble of particles by carefully controlling the pH. A titration curve for the LCC was generated that showed that the virtual pKa (i.e., the composite of all titratable residues that contribute to the LCC) is 5.8. PMID:20371334
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Lee, Woonghee; Kim, Jin Hae; Westler, William M; Markley, John L
2011-06-15
PONDEROSA (Peak-picking Of Noe Data Enabled by Restriction of Shift Assignments) accepts input information consisting of a protein sequence, backbone and sidechain NMR resonance assignments, and 3D-NOESY ((13)C-edited and/or (15)N-edited) spectra, and returns assignments of NOESY crosspeaks, distance and angle constraints, and a reliable NMR structure represented by a family of conformers. PONDEROSA incorporates and integrates external software packages (TALOS+, STRIDE and CYANA) to carry out different steps in the structure determination. PONDEROSA implements internal functions that identify and validate NOESY peak assignments and assess the quality of the calculated three-dimensional structure of the protein. The robustness of the analysis results from PONDEROSA's hierarchical processing steps that involve iterative interaction among the internal and external modules. PONDEROSA supports a variety of input formats: SPARKY assignment table (.shifts) and spectrum file formats (.ucsf), XEASY proton file format (.prot), and NMR-STAR format (.star). To demonstrate the utility of PONDEROSA, we used the package to determine 3D structures of two proteins: human ubiquitin and Escherichia coli iron-sulfur scaffold protein variant IscU(D39A). The automatically generated structural constraints and ensembles of conformers were as good as or better than those determined previously by much less automated means. The program, in the form of binary code along with tutorials and reference manuals, is available at http://ponderosa.nmrfam.wisc.edu/.
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Solvation Thermodynamics of Oligoglycine with Respect to Chain Length and Flexibility.
Drake, Justin A; Harris, Robert C; Pettitt, B Montgomery
2016-08-23
Oligoglycine is a backbone mimic for all proteins and is prevalent in the sequences of intrinsically disordered proteins. We have computed the absolute chemical potential of glycine oligomers at infinite dilution by simulation with the CHARMM36 and Amber ff12SB force fields. We performed a thermodynamic decomposition of the solvation free energy (ΔG(sol)) of Gly2-5 into enthalpic (ΔH(sol)) and entropic (ΔS(sol)) components as well as their van der Waals and electrostatic contributions. Gly2-5 was either constrained to a rigid/extended conformation or allowed to be completely flexible during simulations to assess the effects of flexibility on these thermodynamic quantities. For both rigid and flexible oligoglycine models, the decrease in ΔG(sol) with chain length is enthalpically driven with only weak entropic compensation. However, the apparent rates of decrease of ΔG(sol), ΔH(sol), ΔS(sol), and their elec and vdw components differ for the rigid and flexible models. Thus, we find solvation entropy does not drive aggregation for this system and may not explain the collapse of long oligoglycines. Additionally, both force fields yield very similar thermodynamic scaling relationships with respect to chain length despite both force fields generating different conformational ensembles of various oligoglycine chains. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.
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Renormalized Hamiltonian for a peptide chain: Digitalizing the protein folding problem
NASA Astrophysics Data System (ADS)
Fernández, Ariel; Colubri, Andrés
2000-05-01
A renormalized Hamiltonian for a flexible peptide chain is derived to generate the long-time limit dynamics compatible with a coarsening of torsional conformation space. The renormalization procedure is tailored taking into account the coarse graining imposed by the backbone torsional constraints due to the local steric hindrance and the local backbone-side-group interactions. Thus, the torsional degrees of freedom for each residue are resolved modulo basins of attraction in its so-called Ramachandran map. This Ramachandran renormalization (RR) procedure is implemented so that the chain is energetically driven to form contact patterns as their respective collective topological constraints are fulfilled within the coarse description. In this way, the torsional dynamics are digitalized and become codified as an evolving pattern in a binary matrix. Each accepted Monte Carlo step in a canonical ensemble simulation is correlated with the real mean first passage time it takes to reach the destination coarse topological state. This real-time correlation enables us to test the RR dynamics by comparison with experimentally probed kinetic bottlenecks along the dominant folding pathway. Such intermediates are scarcely populated at any given time, but they determine the kinetic funnel leading to the active structure. This landscape region is reached through kinetically controlled steps needed to overcome the conformational entropy of the random coil. The results are specialized for the bovine pancreatic trypsin inhibitor, corroborating the validity of our method.
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2017-01-01
Computational screening is a method to prioritize small-molecule compounds based on the structural and biochemical attributes built from ligand and target information. Previously, we have developed a scalable virtual screening workflow to identify novel multitarget kinase/bromodomain inhibitors. In the current study, we identified several novel N-[3-(2-oxo-pyrrolidinyl)phenyl]-benzenesulfonamide derivatives that scored highly in our ensemble docking protocol. We quantified the binding affinity of these compounds for BRD4(BD1) biochemically and generated cocrystal structures, which were deposited in the Protein Data Bank. As the docking poses obtained in the virtual screening pipeline did not align with the experimental cocrystal structures, we evaluated the predictions of their precise binding modes by performing molecular dynamics (MD) simulations. The MD simulations closely reproduced the experimentally observed protein–ligand cocrystal binding conformations and interactions for all compounds. These results suggest a computational workflow to generate experimental-quality protein–ligand binding models, overcoming limitations of docking results due to receptor flexibility and incomplete sampling, as a useful starting point for the structure-based lead optimization of novel BRD4(BD1) inhibitors. PMID:28884163
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In situ data analytics and indexing of protein trajectories.
Johnston, Travis; Zhang, Boyu; Liwo, Adam; Crivelli, Silvia; Taufer, Michela
2017-06-15
The transition toward exascale computing will be accompanied by a performance dichotomy. Computational peak performance will rapidly increase; I/O performance will either grow slowly or be completely stagnant. Essentially, the rate at which data are generated will grow much faster than the rate at which data can be read from and written to the disk. MD simulations will soon face the I/O problem of efficiently writing to and reading from disk on the next generation of supercomputers. This article targets MD simulations at the exascale and proposes a novel technique for in situ data analysis and indexing of MD trajectories. Our technique maps individual trajectories' substructures (i.e., α-helices, β-strands) to metadata frame by frame. The metadata captures the conformational properties of the substructures. The ensemble of metadata can be used for automatic, strategic analysis within a trajectory or across trajectories, without manually identify those portions of trajectories in which critical changes take place. We demonstrate our technique's effectiveness by applying it to 26.3k helices and 31.2k strands from 9917 PDB proteins and by providing three empirical case studies. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
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MovieMaker: a web server for rapid rendering of protein motions and interactions.
Maiti, Rajarshi; Van Domselaar, Gary H; Wishart, David S
2005-07-01
MovieMaker is a web server that allows short ( approximately 10 s), downloadable movies of protein motions to be generated. It accepts PDB files or PDB accession numbers as input and automatically calculates, renders and merges the necessary image files to create colourful animations covering a wide range of protein motions and other dynamic processes. Users have the option of animating (i) simple rotation, (ii) morphing between two end-state conformers, (iii) short-scale, picosecond vibrations, (iv) ligand docking, (v) protein oligomerization, (vi) mid-scale nanosecond (ensemble) motions and (vii) protein folding/unfolding. MovieMaker does not perform molecular dynamics calculations. Instead it is an animation tool that uses a sophisticated superpositioning algorithm in conjunction with Cartesian coordinate interpolation to rapidly and automatically calculate the intermediate structures needed for many of its animations. Users have extensive control over the rendering style, structure colour, animation quality, background and other image features. MovieMaker is intended to be a general-purpose server that allows both experts and non-experts to easily generate useful, informative protein animations for educational and illustrative purposes. MovieMaker is accessible at http://wishart.biology.ualberta.ca/moviemaker.
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Structural dynamics of free proteins in diffraction.
Lin, Milo M; Shorokhov, Dmitry; Zewail, Ahmed H
2011-10-26
Among the macromolecular patterns of biological significance, right-handed α-helices are perhaps the most abundant structural motifs. Here, guided by experimental findings, we discuss both ultrafast initial steps and longer-time-scale structural dynamics of helix-coil transitions induced by a range of temperature jumps in large, isolated macromolecular ensembles of an α-helical protein segment thymosin β(9) (Tβ(9)), and elucidate the comprehensive picture of (un)folding. In continuation of an earlier theoretical work from this laboratory that utilized a simplistic structure-scrambling algorithm combined with a variety of self-avoidance thresholds to approximately model helix-coil transitions in Tβ(9), in the present contribution we focus on the actual dynamics of unfolding as obtained from massively distributed ensemble-convergent MD simulations which provide an unprecedented scope of information on the nature of transient macromolecular structures, and with atomic-scale spatiotemporal resolution. In addition to the use of radial distribution functions of ultrafast electron diffraction (UED) simulations in gaining an insight into the elementary steps of conformational interconversions, we also investigate the structural dynamics of the protein via the native (α-helical) hydrogen bonding contact metric which is an intuitive coarse graining approach. Importantly, the decay of α-helical motifs and the (globular) conformational annealing in Tβ(9) occur consecutively or competitively, depending on the magnitude of temperature jump.
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Faheem, Muhammad; Heyden, Andreas
2014-08-12
We report the development of a quantum mechanics/molecular mechanics free energy perturbation (QM/MM-FEP) method for modeling chemical reactions at metal-water interfaces. This novel solvation scheme combines planewave density function theory (DFT), periodic electrostatic embedded cluster method (PEECM) calculations using Gaussian-type orbitals, and classical molecular dynamics (MD) simulations to obtain a free energy description of a complex metal-water system. We derive a potential of mean force (PMF) of the reaction system within the QM/MM framework. A fixed-size, finite ensemble of MM conformations is used to permit precise evaluation of the PMF of QM coordinates and its gradient defined within this ensemble. Local conformations of adsorbed reaction moieties are optimized using sequential MD-sampling and QM-optimization steps. An approximate reaction coordinate is constructed using a number of interpolated states and the free energy difference between adjacent states is calculated using the QM/MM-FEP method. By avoiding on-the-fly QM calculations and by circumventing the challenges associated with statistical averaging during MD sampling, a computational speedup of multiple orders of magnitude is realized. The method is systematically validated against the results of ab initio QM calculations and demonstrated for C-C cleavage in double-dehydrogenated ethylene glycol on a Pt (111) model surface.
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Structure Calculation and Reconstruction of Discrete-State Dynamics from Residual Dipolar Couplings.
Cole, Casey A; Mukhopadhyay, Rishi; Omar, Hanin; Hennig, Mirko; Valafar, Homayoun
2016-04-12
Residual dipolar couplings (RDCs) acquired by nuclear magnetic resonance (NMR) spectroscopy are an indispensable source of information in investigation of molecular structures and dynamics. Here, we present a comprehensive strategy for structure calculation and reconstruction of discrete-state dynamics from RDC data that is based on the singular value decomposition (SVD) method of order tensor estimation. In addition to structure determination, we provide a mechanism of producing an ensemble of conformations for the dynamical regions of a protein from RDC data. The developed methodology has been tested on simulated RDC data with ±1 Hz of error from an 83 residue α protein (PDB ID 1A1Z ) and a 213 residue α/β protein DGCR8 (PDB ID 2YT4 ). In nearly all instances, our method reproduced the structure of the protein including the conformational ensemble to within less than 2 Å. On the basis of our investigations, arc motions with more than 30° of rotation are identified as internal dynamics and are reconstructed with sufficient accuracy. Furthermore, states with relative occupancies above 20% are consistently recognized and reconstructed successfully. Arc motions with a magnitude of 15° or relative occupancy of less than 10% are consistently unrecognizable as dynamical regions within the context of ±1 Hz of error.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Di Lisi, Antonio; De Siena, Silvio; Illuminati, Fabrizio
2005-09-15
We introduce an efficient, quasideterministic scheme to generate maximally entangled states of two atomic ensembles. The scheme is based on quantum nondemolition measurements of total atomic populations and on adiabatic quantum feedback conditioned by the measurements outputs. The high efficiency of the scheme is tested and confirmed numerically for ideal photodetection as well as in the presence of losses.
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Prion replication without host adaptation during interspecies transmissions.
Bian, Jifeng; Khaychuk, Vadim; Angers, Rachel C; Fernández-Borges, Natalia; Vidal, Enric; Meyerett-Reid, Crystal; Kim, Sehun; Calvi, Carla L; Bartz, Jason C; Hoover, Edward A; Agrimi, Umberto; Richt, Jürgen A; Castilla, Joaquín; Telling, Glenn C
2017-01-31
Adaptation of prions to new species is thought to reflect the capacity of the host-encoded cellular form of the prion protein (PrP C ) to selectively propagate optimized prion conformations from larger ensembles generated in the species of origin. Here we describe an alternate replicative process, termed nonadaptive prion amplification (NAPA), in which dominant conformers bypass this requirement during particular interspecies transmissions. To model susceptibility of horses to prions, we produced transgenic (Tg) mice expressing cognate PrP C Although disease transmission to only a subset of infected TgEq indicated a significant barrier to EqPrP C conversion, the resulting horse prions unexpectedly failed to cause disease upon further passage to TgEq. TgD expressing deer PrP C was similarly refractory to deer prions from diseased TgD infected with mink prions. In both cases, the resulting prions transmitted to mice expressing PrP C from the species of prion origin, demonstrating that transmission barrier eradication of the originating prions was ephemeral and adaptation superficial in TgEq and TgD. Horse prions produced in vitro by protein misfolding cyclic amplification of mouse prions using horse PrP C also failed to infect TgEq but retained tropism for wild-type mice. Concordant patterns of neuropathology and prion deposition in susceptible mice infected with NAPA prions and the corresponding prion of origin confirmed preservation of strain properties. The comparable responses of both prion types to guanidine hydrochloride denaturation indicated this occurs because NAPA precludes selection of novel prion conformations. Our findings provide insights into mechanisms regulating interspecies prion transmission and a framework to reconcile puzzling epidemiological features of certain prion disorders.
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Prion replication without host adaptation during interspecies transmissions
Bian, Jifeng; Khaychuk, Vadim; Angers, Rachel C.; Fernández-Borges, Natalia; Meyerett-Reid, Crystal; Kim, Sehun; Calvi, Carla L.; Bartz, Jason C.; Hoover, Edward A.; Agrimi, Umberto; Richt, Jürgen A.; Castilla, Joaquín; Telling, Glenn C.
2017-01-01
Adaptation of prions to new species is thought to reflect the capacity of the host-encoded cellular form of the prion protein (PrPC) to selectively propagate optimized prion conformations from larger ensembles generated in the species of origin. Here we describe an alternate replicative process, termed nonadaptive prion amplification (NAPA), in which dominant conformers bypass this requirement during particular interspecies transmissions. To model susceptibility of horses to prions, we produced transgenic (Tg) mice expressing cognate PrPC. Although disease transmission to only a subset of infected TgEq indicated a significant barrier to EqPrPC conversion, the resulting horse prions unexpectedly failed to cause disease upon further passage to TgEq. TgD expressing deer PrPC was similarly refractory to deer prions from diseased TgD infected with mink prions. In both cases, the resulting prions transmitted to mice expressing PrPC from the species of prion origin, demonstrating that transmission barrier eradication of the originating prions was ephemeral and adaptation superficial in TgEq and TgD. Horse prions produced in vitro by protein misfolding cyclic amplification of mouse prions using horse PrPC also failed to infect TgEq but retained tropism for wild-type mice. Concordant patterns of neuropathology and prion deposition in susceptible mice infected with NAPA prions and the corresponding prion of origin confirmed preservation of strain properties. The comparable responses of both prion types to guanidine hydrochloride denaturation indicated this occurs because NAPA precludes selection of novel prion conformations. Our findings provide insights into mechanisms regulating interspecies prion transmission and a framework to reconcile puzzling epidemiological features of certain prion disorders. PMID:28096357
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Quasi-most unstable modes: a window to 'À la carte' ensemble diversity?
NASA Astrophysics Data System (ADS)
Homar Santaner, Victor; Stensrud, David J.
2010-05-01
The atmospheric scientific community is nowadays facing the ambitious challenge of providing useful forecasts of atmospheric events that produce high societal impact. The low level of social resilience to false alarms creates tremendous pressure on forecasting offices to issue accurate, timely and reliable warnings.Currently, no operational numerical forecasting system is able to respond to the societal demand for high-resolution (in time and space) predictions in the 12-72h time span. The main reasons for such deficiencies are the lack of adequate observations and the high non-linearity of the numerical models that are currently used. The whole weather forecasting problem is intrinsically probabilistic and current methods aim at coping with the various sources of uncertainties and the error propagation throughout the forecasting system. This probabilistic perspective is often created by generating ensembles of deterministic predictions that are aimed at sampling the most important sources of uncertainty in the forecasting system. The ensemble generation/sampling strategy is a crucial aspect of their performance and various methods have been proposed. Although global forecasting offices have been using ensembles of perturbed initial conditions for medium-range operational forecasts since 1994, no consensus exists regarding the optimum sampling strategy for high resolution short-range ensemble forecasts. Bred vectors, however, have been hypothesized to better capture the growing modes in the highly nonlinear mesoscale dynamics of severe episodes than singular vectors or observation perturbations. Yet even this technique is not able to produce enough diversity in the ensembles to accurately and routinely predict extreme phenomena such as severe weather. Thus, we propose a new method to generate ensembles of initial conditions perturbations that is based on the breeding technique. Given a standard bred mode, a set of customized perturbations is derived with specified amplitudes and horizontal scales. This allows the ensemble to excite growing modes across a wider range of scales. Results show that this approach produces significantly more spread in the ensemble prediction than standard bred modes alone. Several examples that illustrate the benefits from this approach for severe weather forecasts will be provided.
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Thermal preparation of an entangled steady state of distant driven spin ensembles
NASA Astrophysics Data System (ADS)
Teper, Natalia
2018-02-01
Entanglement properties are studied in the continuous-variable system of three nitrogen-vacancy center ensembles cou-pled to separate transmission line resonators interconnected by current-biased Josephson junction. The circuit is enhanced by Josephson parametric amplifier, which serves as source of squeezed microwave field. Bosonic modes of nitrogen-vacancy-center ensembles exhibit steady state entanglement for certain range of parameters. Squeezed microwave field can be consider as a driving force of entanglement. Proposed scheme provides generating entanglement for each of the three pairs of spin ensembles.
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Koh, Hye Ran; Roy, Rahul; Sorokina, Maria; Tang, Guo-Qing; Nandakumar, Divya; Patel, Smita S; Ha, Taekjip
2018-05-17
We provide a comprehensive analysis of transcription in real time by T7 RNA Polymerase (RNAP) using single-molecule fluorescence resonance energy transfer by monitoring the entire life history of transcription initiation, including stepwise RNA synthesis with near base-pair resolution, abortive cycling, and transition into elongation. Kinetically branching pathways were observed for abortive initiation with an RNAP either recycling on the same promoter or exchanging with another RNAP from solution. We detected fast and slow populations of RNAP in their transition into elongation, consistent with the efficient and delayed promoter release, respectively, observed in ensemble studies. Real-time monitoring of abortive cycling using three-probe analysis showed that the initiation events are stochastically branched into productive and failed transcription. The abortive products are generated primarily from initiation events that fail to progress to elongation, and a majority of the productive events transit to elongation without making abortive products. Copyright © 2018 Elsevier Inc. All rights reserved.
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Replica Exchange Improves Sampling in Low-Resolution Docking Stage of RosettaDock
Zhang, Zhe; Lange, Oliver F.
2013-01-01
Many protein-protein docking protocols are based on a shotgun approach, in which thousands of independent random-start trajectories minimize the rigid-body degrees of freedom. Another strategy is enumerative sampling as used in ZDOCK. Here, we introduce an alternative strategy, ReplicaDock, using a small number of long trajectories of temperature replica exchange. We compare replica exchange sampling as low-resolution stage of RosettaDock with RosettaDock's original shotgun sampling as well as with ZDOCK. A benchmark of 30 complexes starting from structures of the unbound binding partners shows improved performance for ReplicaDock and ZDOCK when compared to shotgun sampling at equal or less computational expense. ReplicaDock and ZDOCK consistently reach lower energies and generate significantly more near-native conformations than shotgun sampling. Accordingly, they both improve typical metrics of prediction quality of complex structures after refinement. Additionally, the refined ReplicaDock ensembles reach significantly lower interface energies and many previously hidden features of the docking energy landscape become visible when ReplicaDock is applied. PMID:24009670
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Ahalawat, Navjeet; Arora, Simran; Murarka, Rajesh K
2015-08-27
The human cluster determinant 4 (CD4), expressed primarily on the surface of T helper cells, serves as a coreceptor in T-cell receptor recognition of MHC II antigen complexes. Besides its cellular functions, CD4 serves as a primary receptor of human immunodeficiency virus (HIV) type 1. The cytoplasmic tail of CD4 (residues 402-419) is known to be involved in direct interaction with the HIV-1 proteins Vpu and Nef. These two viral accessory proteins (Vpu and Nef) downregulate CD4 in HIV-1 infected cells by multiple strategies and make the body susceptible to all forms of infections. In this work, we carried out extensive replica exchange molecular dynamics simulations in explicit water with three popular protein force fields Amber ff99SB, Amber ff99SB*-ILDN, and CHARMM36 to characterize the equilibrium conformational ensemble of CD4-tail (402-419) and further validated the simulated ensembles with known NMR data. We found that ff99SB*-ILDN gives a better description of the structural ensemble of this peptide compared with ff99SB and CHARMM36. The peptide adopts multiple distinct conformations with varying degree of residual secondary structures. In particular, we observed 28, 7, and 5% average α-helical, β-strand, and 3(10)-helix content, respectively, for ff99SB*-ILDN. The peptide chain shows the tendency of helix formation in a cooperative manner, seeding at residues 407-410, and subsequently extending toward both ends of the chain. Furthermore, we constructed Markov state model (MSM) from large-scale molecular dynamics simulations to study the dynamics of transitions between different metastable states explored by this peptide. The mean first passage times computed from MSM indicate rapid interconversion of these states, and the time scales of transitions range from several nanoseconds to hundreds of microseconds. Our results show good agreement with experimental data and could help to understand the key molecular mechanisms of T-cell activation and HIV-mediated receptor interference.
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Protein Conformational Populations and Functionally Relevant Sub-states
DOE Office of Scientific and Technical Information (OSTI.GOV)
Agarwal, Pratul K; Burger, Virginia; Savol, Andrej
2013-01-01
Functioning proteins do not remain fixed in a unique structure, but instead they sample a range of conformations facilitated by motions within the protein. Even in the native state, a protein exists as a collection of interconverting conformations driven by thermodynamic fluctuations. Motions on the fast time scale allow a protein to sample conformations in the nearby area of its conformational landscape, while motions on slower time scales give it access to conformations in distal areas of the landscape. Emerging evidence indicates that protein landscapes contain conformational substates with dynamic and structural features that support the designated function of themore » protein. Nuclear magnetic resonance (NMR) experiments provide information about conformational ensembles of proteins. X-ray crystallography allows researchers to identify the most populated states along the landscape, and computational simulations give atom-level information about the conformational substates of different proteins. This ability to characterize and obtain quantitative information about the conformational substates and the populations of proteins within them is allowing researchers to better understand the relationship between protein structure and dynamics and the mechanisms of protein function. In this Account, we discuss recent developments and challenges in the characterization of functionally relevant conformational populations and substates of proteins. In some enzymes, the sampling of functionally relevant conformational substates is connected to promoting the overall mechanism of catalysis. For example, the conformational landscape of the enzyme dihydrofolate reductase has multiple substates, which facilitate the binding and the release of the cofactor and substrate and catalyze the hydride transfer. For the enzyme cyclophilin A, computational simulations reveal that the long time scale conformational fluctuations enable the enzyme to access conformational substates that allow it to attain the transition state, therefore promoting the reaction mechanism. In the long term, this emerging view of proteins with conformational substates has broad implications for improving our understanding of enzymes, enzyme engineering, and better drug design. Researchers have already used photoactivation to modulate protein conformations as a strategy to develop a hypercatalytic enzyme. In addition, the alteration of the conformational substates through binding of ligands at locations other than the active site provides the basis for the design of new medicines through allosteric modulation.« less
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NASA Astrophysics Data System (ADS)
Oh, Seok-Geun; Suh, Myoung-Seok
2017-07-01
The projection skills of five ensemble methods were analyzed according to simulation skills, training period, and ensemble members, using 198 sets of pseudo-simulation data (PSD) produced by random number generation assuming the simulated temperature of regional climate models. The PSD sets were classified into 18 categories according to the relative magnitude of bias, variance ratio, and correlation coefficient, where each category had 11 sets (including 1 truth set) with 50 samples. The ensemble methods used were as follows: equal weighted averaging without bias correction (EWA_NBC), EWA with bias correction (EWA_WBC), weighted ensemble averaging based on root mean square errors and correlation (WEA_RAC), WEA based on the Taylor score (WEA_Tay), and multivariate linear regression (Mul_Reg). The projection skills of the ensemble methods improved generally as compared with the best member for each category. However, their projection skills are significantly affected by the simulation skills of the ensemble member. The weighted ensemble methods showed better projection skills than non-weighted methods, in particular, for the PSD categories having systematic biases and various correlation coefficients. The EWA_NBC showed considerably lower projection skills than the other methods, in particular, for the PSD categories with systematic biases. Although Mul_Reg showed relatively good skills, it showed strong sensitivity to the PSD categories, training periods, and number of members. On the other hand, the WEA_Tay and WEA_RAC showed relatively superior skills in both the accuracy and reliability for all the sensitivity experiments. This indicates that WEA_Tay and WEA_RAC are applicable even for simulation data with systematic biases, a short training period, and a small number of ensemble members.
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Mamidi, Ashalatha Sreshty; Surolia, Avadhesha
2015-01-01
Structural information over the entire course of binding interactions based on the analyses of energy landscapes is described, which provides a framework to understand the events involved during biomolecular recognition. Conformational dynamics of malectin's exquisite selectivity for diglucosylated N-glycan (Dig-N-glycan), a highly flexible oligosaccharide comprising of numerous dihedral torsion angles, are described as an example. For this purpose, a novel approach based on hierarchical sampling for acquiring metastable molecular conformations constituting low-energy minima for understanding the structural features involved in a biologic recognition is proposed. For this purpose, four variants of principal component analysis were employed recursively in both Cartesian space and dihedral angles space that are characterized by free energy landscapes to select the most stable conformational substates. Subsequently, k-means clustering algorithm was implemented for geometric separation of the major native state to acquire a final ensemble of metastable conformers. A comparison of malectin complexes was then performed to characterize their conformational properties. Analyses of stereochemical metrics and other concerted binding events revealed surface complementarity, cooperative and bidentate hydrogen bonds, water-mediated hydrogen bonds, carbohydrate-aromatic interactions including CH-π and stacking interactions involved in this recognition. Additionally, a striking structural transition from loop to β-strands in malectin CRD upon specific binding to Dig-N-glycan is observed. The interplay of the above-mentioned binding events in malectin and Dig-N-glycan supports an extended conformational selection model as the underlying binding mechanism.
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Complement Factor H and Simian Virus 40 bind the GM1 ganglioside in distinct conformations.
Blaum, Bärbel S; Frank, Martin; Walker, Ross C; Neu, Ursula; Stehle, Thilo
2016-05-01
Mammalian cell surfaces are decorated with a variety of glycan chains that orchestrate development and defense and are exploited by pathogens for cellular attachment and entry. While glycosidic linkages are, in principle, flexible, the conformational space that a given glycan can sample is subject to spatial and electrostatic restrictions imposed by its overall chemical structure. Here, we show how the glycan moiety of the GM1 ganglioside, a branched, monosialylated pentasaccharide that serves as a ligand for various proteins, undergoes differential conformational selection in its interactions with different lectins. Using STD NMR and X-ray crystallography, we found that the innate immune regulator complement Factor H (FH) binds a previously not reported GM1 conformation that is not compatible with the GM1-binding sites of other structurally characterized GM1-binding lectins such as the Simian Virus 40 (SV40) capsid. Molecular dynamics simulations of the free glycan in explicit solvent on the 10 μs timescale reveal that the FH-bound conformation nevertheless corresponds to a minimum in the Gibbs free energy plot. In contrast to the GM1 conformation recognized by SV40, the FH-bound GM1 conformation is associated with poor NOE restraints, explaining how it escaped(1)H-(1)H NOE-restrained modeling in the past and highlighting the necessity for ensemble representations of glycan structures. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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HLPI-Ensemble: Prediction of human lncRNA-protein interactions based on ensemble strategy.
Hu, Huan; Zhang, Li; Ai, Haixin; Zhang, Hui; Fan, Yetian; Zhao, Qi; Liu, Hongsheng
2018-03-27
LncRNA plays an important role in many biological and disease progression by binding to related proteins. However, the experimental methods for studying lncRNA-protein interactions are time-consuming and expensive. Although there are a few models designed to predict the interactions of ncRNA-protein, they all have some common drawbacks that limit their predictive performance. In this study, we present a model called HLPI-Ensemble designed specifically for human lncRNA-protein interactions. HLPI-Ensemble adopts the ensemble strategy based on three mainstream machine learning algorithms of Support Vector Machines (SVM), Random Forests (RF) and Extreme Gradient Boosting (XGB) to generate HLPI-SVM Ensemble, HLPI-RF Ensemble and HLPI-XGB Ensemble, respectively. The results of 10-fold cross-validation show that HLPI-SVM Ensemble, HLPI-RF Ensemble and HLPI-XGB Ensemble achieved AUCs of 0.95, 0.96 and 0.96, respectively, in the test dataset. Furthermore, we compared the performance of the HLPI-Ensemble models with the previous models through external validation dataset. The results show that the false positives (FPs) of HLPI-Ensemble models are much lower than that of the previous models, and other evaluation indicators of HLPI-Ensemble models are also higher than those of the previous models. It is further showed that HLPI-Ensemble models are superior in predicting human lncRNA-protein interaction compared with previous models. The HLPI-Ensemble is publicly available at: http://ccsipb.lnu.edu.cn/hlpiensemble/ .
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New Software for Ensemble Creation in the Spitzer-Space-Telescope Operations Database
NASA Technical Reports Server (NTRS)
Laher, Russ; Rector, John
2004-01-01
Some of the computer pipelines used to process digital astronomical images from NASA's Spitzer Space Telescope require multiple input images, in order to generate high-level science and calibration products. The images are grouped into ensembles according to well documented ensemble-creation rules by making explicit associations in the operations Informix database at the Spitzer Science Center (SSC). The advantage of this approach is that a simple database query can retrieve the required ensemble of pipeline input images. New and improved software for ensemble creation has been developed. The new software is much faster than the existing software because it uses pre-compiled database stored-procedures written in Informix SPL (SQL programming language). The new software is also more flexible because the ensemble creation rules are now stored in and read from newly defined database tables. This table-driven approach was implemented so that ensemble rules can be inserted, updated, or deleted without modifying software.
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Conformational analysis by intersection: CONAN.
Smellie, Andrew; Stanton, Robert; Henne, Randy; Teig, Steve
2003-01-15
As high throughput techniques in chemical synthesis and screening improve, more demands are placed on computer assisted design and virtual screening. Many of these computational methods require one or more three-dimensional conformations for molecules, creating a demand for a conformational analysis tool that can rapidly and robustly cover the low-energy conformational spaces of small molecules. A new algorithm of intersection is presented here, which quickly generates (on average <0.5 seconds/stereoisomer) a complete description of the low energy conformational space of a small molecule. The molecule is first decomposed into nonoverlapping nodes N (usually rings) and overlapping paths P with conformations (N and P) generated in an offline process. In a second step the node and path data are combined to form distinct conformers of the molecule. Finally, heuristics are applied after intersection to generate a small representative collection of conformations that span the conformational space. In a study of approximately 97,000 randomly selected molecules from the MDDR, results are presented that explore these conformations and their ability to cover low-energy conformational space. Copyright 2002 Wiley Periodicals, Inc. J Comput Chem 24: 10-20, 2003
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NASA Astrophysics Data System (ADS)
Negri, Matthias; Recanatini, Maurizio; Hartmann, Rolf W.
2011-09-01
17β-Hydroxysteroid dehydrogenase type 1 (17β-HSD1) catalyzes the last step of the estrogen biosynthesis, namely the reduction of estrone to the biologically potent estradiol. As such it is a potentially attractive drug target for the treatment of estrogen-dependent diseases like breast cancer and endometriosis. 17β-HSD1 belongs to the bisubstrate enzymes and exists as an ensemble of conformations. These principally differ in the region of the βFαG'-loop, suggesting a prominent role in substrate and inhibitor binding. Although several classes of potent non-steroidal 17β-HSD1 inhibitors currently exist, their binding mode is still unclear. We aimed to elucidate the binding mode of bis(hydroxyphenyl)arenes, a highly potent class of 17β-HSD1 inhibitors, and to rank these compounds correctly with respect to their inhibitory potency, two essential aspects in drug design. Ensemble docking experiments resulted in a steroidal binding mode for the closed enzyme conformations and in an alternative mode for the opened and occluded conformers with the inhibitors placed below the NADPH interacting with it synergically via π-π stacking and H-bond formation. Both binding modes were investigated by MD simulations and MM-PBSA binding free energy estimations using as representative member for this class compound 1 (50 nM). Notably, only the alternative binding mode proved stable and was energetically more favorable, while when simulated in the steroidal binding mode compound 1 was displaced from the active site. In parallel, ab initio studies of small NADPH-inhibitor complexes were performed, which supported the importance of the synergistic interaction between inhibitors and cofactor.
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Multiscale Macromolecular Simulation: Role of Evolving Ensembles
Singharoy, A.; Joshi, H.; Ortoleva, P.J.
2013-01-01
Multiscale analysis provides an algorithm for the efficient simulation of macromolecular assemblies. This algorithm involves the coevolution of a quasiequilibrium probability density of atomic configurations and the Langevin dynamics of spatial coarse-grained variables denoted order parameters (OPs) characterizing nanoscale system features. In practice, implementation of the probability density involves the generation of constant OP ensembles of atomic configurations. Such ensembles are used to construct thermal forces and diffusion factors that mediate the stochastic OP dynamics. Generation of all-atom ensembles at every Langevin timestep is computationally expensive. Here, multiscale computation for macromolecular systems is made more efficient by a method that self-consistently folds in ensembles of all-atom configurations constructed in an earlier step, history, of the Langevin evolution. This procedure accounts for the temporal evolution of these ensembles, accurately providing thermal forces and diffusions. It is shown that efficiency and accuracy of the OP-based simulations is increased via the integration of this historical information. Accuracy improves with the square root of the number of historical timesteps included in the calculation. As a result, CPU usage can be decreased by a factor of 3-8 without loss of accuracy. The algorithm is implemented into our existing force-field based multiscale simulation platform and demonstrated via the structural dynamics of viral capsomers. PMID:22978601
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Simulation of an ensemble of future climate time series with an hourly weather generator
NASA Astrophysics Data System (ADS)
Caporali, E.; Fatichi, S.; Ivanov, V. Y.; Kim, J.
2010-12-01
There is evidence that climate change is occurring in many regions of the world. The necessity of climate change predictions at the local scale and fine temporal resolution is thus warranted for hydrological, ecological, geomorphological, and agricultural applications that can provide thematic insights into the corresponding impacts. Numerous downscaling techniques have been proposed to bridge the gap between the spatial scales adopted in General Circulation Models (GCM) and regional analyses. Nevertheless, the time and spatial resolutions obtained as well as the type of meteorological variables may not be sufficient for detailed studies of climate change effects at the local scales. In this context, this study presents a stochastic downscaling technique that makes use of an hourly weather generator to simulate time series of predicted future climate. Using a Bayesian approach, the downscaling procedure derives distributions of factors of change for several climate statistics from a multi-model ensemble of GCMs. Factors of change are sampled from their distributions using a Monte Carlo technique to entirely account for the probabilistic information obtained with the Bayesian multi-model ensemble. Factors of change are subsequently applied to the statistics derived from observations to re-evaluate the parameters of the weather generator. The weather generator can reproduce a wide set of climate variables and statistics over a range of temporal scales, from extremes, to the low-frequency inter-annual variability. The final result of such a procedure is the generation of an ensemble of hourly time series of meteorological variables that can be considered as representative of future climate, as inferred from GCMs. The generated ensemble of scenarios also accounts for the uncertainty derived from multiple GCMs used in downscaling. Applications of the procedure in reproducing present and future climates are presented for different locations world-wide: Tucson (AZ), Detroit (MI), and Firenze (Italy). The stochastic downscaling is carried out with eight GCMs from the CMIP3 multi-model dataset (IPCC 4AR, A1B scenario).
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Le Bailly, Bryden A. F.; Byrne, Liam; Diemer, Vincent; Foroozandeh, Mohammadali; Morris, Gareth A.
2015-01-01
Although foldamers, by definition, are extended molecular structures with a well-defined conformation, minor conformers must be populated at least to some extent in solution. We present a quantitative analysis of these minor conformers for a series of helical oligomers built from achiral but helicogenic α-amino acids. By measuring the chain length dependence or chain position dependence of NMR or CD quantities that measure screw-sense preference in a helical oligomer, we quantify values for the decay constant of a conformational signal as it passes through the molecular structure. This conformational signal is a perturbation of the racemic mixture of M and P helices that such oligomers typically adopt by the inclusion of an N or C terminal chiral inducer. We show that decay constants may be very low (<1% signal loss per residue) in non-polar solvents, and we evaluate the increase in decay constant that results in polar solvents, at higher temperatures, and with more conformationally flexible residues such as Gly. Decay constants are independent of whether the signal originates from the N or the C terminus. By interpreting the decay constant in terms of the probability with which conformations containing a screw-sense reversal are populated, we quantify the populations of these alternative minor conformers within the overall ensemble of secondary structures adopted by the foldamer. We deduce helical persistence lengths for Aib polymers that allow us to show that in a non-polar solvent a peptide helix, even in the absence of chiral residues, may continue with the same screw sense for approximately 200 residues. PMID:29308146
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Casiano-Negroni, Anette; Sun, Xiaoyan; Al-Hashimi, Hashim M.
2012-01-01
Many regulatory RNAs undergo large changes in structure upon recognition of proteins and ligands but the mechanism by which this occur remains poorly understood. Using NMR residual dipolar coupling (RDCs), we characterized Na+ induced changes in the structure and dynamics of the bulge-containing HIV-1 transactivation response element (TAR) RNA that mirror changes induced by small molecules bearing a different number of cationic groups. Increasing the Na+ concentration from 25 mM to 320 mM led to a continuous reduction in the average inter-helical bend angle (from 46° to 22°), inter-helical twist angle (from 66° to −18°) and inter-helix flexibility (as measured by an increase in the internal generalized degree of order from 0.56 to 0.74). Similar conformational changes were observed with Mg2+, indicating that non-specific electrostatic interactions drive the conformational transition, although results also suggest that Na+ and Mg2+ may associate with TAR in distinct modes. The transition can be rationalized based on a population-weighted average of two ensembles comprising an electrostatically relaxed bent and flexible TAR conformation that is weakly associated with counterions, and a globally rigid coaxial conformation which has stronger electrostatic potential and association with counterions. The TAR inter-helical orientations that are stabilized by small molecules fall around the metal-induced conformational pathway, indicating that counterions may help predispose the TAR conformation for target recognition. Our results underscore the intricate sensitivity of RNA conformational dynamics to environmental conditions and demonstrate the ability to detect subtle conformational changes using NMR RDCs. PMID:17488097
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Vögeli, Beat; Orts, Julien; Strotz, Dean; Chi, Celestine; Minges, Martina; Wälti, Marielle Aulikki; Güntert, Peter; Riek, Roland
2014-04-01
Confined by the Boltzmann distribution of the energies of the states, a multitude of structural states are inherent to biomolecules. For a detailed understanding of a protein's function, its entire structural landscape at atomic resolution and insight into the interconversion between all the structural states (i.e. dynamics) are required. Whereas dedicated trickery with NMR relaxation provides aspects of local dynamics, and 3D structure determination by NMR is well established, only recently have several attempts been made to formulate a more comprehensive description of the dynamics and the structural landscape of a protein. Here, a perspective is given on the use of exact NOEs (eNOEs) for the elucidation of structural ensembles of a protein describing the covered conformational space. Copyright © 2013 Elsevier Inc. All rights reserved.
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Three-Point Functions in c≤1 Liouville Theory and Conformal Loop Ensembles.
Ikhlef, Yacine; Jacobsen, Jesper Lykke; Saleur, Hubert
2016-04-01
The possibility of extending the Liouville conformal field theory from values of the central charge c≥25 to c≤1 has been debated for many years in condensed matter physics as well as in string theory. It was only recently proven that such an extension-involving a real spectrum of critical exponents as well as an analytic continuation of the Dorn-Otto-Zamolodchikov-Zamolodchikov formula for three-point couplings-does give rise to a consistent theory. We show in this Letter that this theory can be interpreted in terms of microscopic loop models. We introduce in particular a family of geometrical operators, and, using an efficient algorithm to compute three-point functions from the lattice, we show that their operator algebra corresponds exactly to that of vertex operators V_{α[over ^]} in c≤1 Liouville theory. We interpret geometrically the limit α[over ^]→0 of V_{α[over ^]} and explain why it is not the identity operator (despite having conformal weight Δ=0).
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Modeling and docking antibody structures with Rosetta
Weitzner, Brian D.; Jeliazkov, Jeliazko R.; Lyskov, Sergey; Marze, Nicholas; Kuroda, Daisuke; Frick, Rahel; Adolf-Bryfogle, Jared; Biswas, Naireeta; Dunbrack, Roland L.; Gray, Jeffrey J.
2017-01-01
We describe Rosetta-based computational protocols for predicting the three-dimensional structure of an antibody from sequence (RosettaAntibody) and then docking the antibody to protein antigens (SnugDock). Antibody modeling leverages canonical loop conformations to graft large segments from experimentally-determined structures as well as (1) energetic calculations to minimize loops, (2) docking methodology to refine the VL–VH relative orientation, and (3) de novo prediction of the elusive complementarity determining region (CDR) H3 loop. To alleviate model uncertainty, antibody–antigen docking resamples CDR loop conformations and can use multiple models to represent an ensemble of conformations for the antibody, the antigen or both. These protocols can be run fully-automated via the ROSIE web server (http://rosie.rosettacommons.org/) or manually on a computer with user control of individual steps. For best results, the protocol requires roughly 1,000 CPU-hours for antibody modeling and 250 CPU-hours for antibody–antigen docking. Tasks can be completed in under a day by using public supercomputers. PMID:28125104
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Trajectories of the ribosome as a Brownian nanomachine
Dashti, Ali; Schwander, Peter; Langlois, Robert; ...
2014-11-24
In a Brownian machine, there is a tiny device buffeted by the random motions of molecules in the environment, is capable of exploiting these thermal motions for many of the conformational changes in its work cycle. Such machines are now thought to be ubiquitous, with the ribosome, a molecular machine responsible for protein synthesis, increasingly regarded as prototypical. We present a new analytical approach capable of determining the free-energy landscape and the continuous trajectories of molecular machines from a large number of snapshots obtained by cryogenic electron microscopy. We demonstrate this approach in the context of experimental cryogenic electron microscopemore » images of a large ensemble of nontranslating ribosomes purified from yeast cells. The free-energy landscape is seen to contain a closed path of low energy, along which the ribosome exhibits conformational changes known to be associated with the elongation cycle. This approach allows model-free quantitative analysis of the degrees of freedom and the energy landscape underlying continuous conformational changes in nanomachines, including those important for biological function.« less
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McHaourab, Hassane S; Steed, P Ryan; Kazmier, Kelli
2011-11-09
Trapping membrane proteins in the confines of a crystal lattice obscures dynamic modes essential for interconversion between multiple conformations in the functional cycle. Moreover, lattice forces could conspire with detergent solubilization to stabilize a minor conformer in an ensemble thus confounding mechanistic interpretation. Spin labeling in conjunction with electron paramagnetic resonance (EPR) spectroscopy offers an exquisite window into membrane protein dynamics in the native-like environment of a lipid bilayer. Systematic application of spin labeling and EPR identifies sequence-specific secondary structures, defines their topology and their packing in the tertiary fold. Long range distance measurements (60 Å-80 Å) between pairs of spin labels enable quantitative analysis of equilibrium dynamics and triggered conformational changes. This review highlights the contribution of spin labeling to bridging structure and mechanism. Efforts to develop methods for determining structures from EPR restraints and to increase sensitivity and throughput promise to expand spin labeling applications in membrane protein structural biology. Copyright © 2011 Elsevier Ltd. All rights reserved.
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Matsunaga, Yasuhiro
2018-01-01
Single-molecule experiments and molecular dynamics (MD) simulations are indispensable tools for investigating protein conformational dynamics. The former provide time-series data, such as donor-acceptor distances, whereas the latter give atomistic information, although this information is often biased by model parameters. Here, we devise a machine-learning method to combine the complementary information from the two approaches and construct a consistent model of conformational dynamics. It is applied to the folding dynamics of the formin-binding protein WW domain. MD simulations over 400 μs led to an initial Markov state model (MSM), which was then "refined" using single-molecule Förster resonance energy transfer (FRET) data through hidden Markov modeling. The refined or data-assimilated MSM reproduces the FRET data and features hairpin one in the transition-state ensemble, consistent with mutation experiments. The folding pathway in the data-assimilated MSM suggests interplay between hydrophobic contacts and turn formation. Our method provides a general framework for investigating conformational transitions in other proteins. PMID:29723137
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Packianathan, Charles; Katen, Sarah P.; Dann, III, Charles E.
2010-01-12
In infected cells, virus components must be organized at the right place and time to ensure assembly of infectious virions. From a different perspective, assembly must be prevented until all components are available. Hypothetically, this can be achieved by allosterically controlling assembly. Consistent with this hypothesis, here we show that the structure of the hepatitis B virus (HBV) core protein dimer, which can spontaneously self-assemble, is incompatible with capsid assembly. Systematic differences between core protein dimer and capsid conformations demonstrate linkage between the intradimer interface and interdimer contact surface. These structures also provide explanations for the capsid-dimer selectivity of somemore » antibodies and the activities of assembly effectors. Solution studies suggest that the assembly-inactive state is more accurately an ensemble of conformations. Simulations show that allostery supports controlled assembly and results in capsids that are resistant to dissociation. We propose that allostery, as demonstrated in HBV, is common to most self-assembling viruses.« less
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Structure Prediction of the Second Extracellular Loop in G-Protein-Coupled Receptors
Kmiecik, Sebastian; Jamroz, Michal; Kolinski, Michal
2014-01-01
G-protein-coupled receptors (GPCRs) play key roles in living organisms. Therefore, it is important to determine their functional structures. The second extracellular loop (ECL2) is a functionally important region of GPCRs, which poses significant challenge for computational structure prediction methods. In this work, we evaluated CABS, a well-established protein modeling tool for predicting ECL2 structure in 13 GPCRs. The ECL2s (with between 13 and 34 residues) are predicted in an environment of other extracellular loops being fully flexible and the transmembrane domain fixed in its x-ray conformation. The modeling procedure used theoretical predictions of ECL2 secondary structure and experimental constraints on disulfide bridges. Our approach yielded ensembles of low-energy conformers and the most populated conformers that contained models close to the available x-ray structures. The level of similarity between the predicted models and x-ray structures is comparable to that of other state-of-the-art computational methods. Our results extend other studies by including newly crystallized GPCRs. PMID:24896119
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Topology, structures, and energy landscapes of human chromosomes
Zhang, Bin; Wolynes, Peter G.
2015-01-01
Chromosome conformation capture experiments provide a rich set of data concerning the spatial organization of the genome. We use these data along with a maximum entropy approach to derive a least-biased effective energy landscape for the chromosome. Simulations of the ensemble of chromosome conformations based on the resulting information theoretic landscape not only accurately reproduce experimental contact probabilities, but also provide a picture of chromosome dynamics and topology. The topology of the simulated chromosomes is probed by computing the distribution of their knot invariants. The simulated chromosome structures are largely free of knots. Topologically associating domains are shown to be crucial for establishing these knotless structures. The simulated chromosome conformations exhibit a tendency to form fibril-like structures like those observed via light microscopy. The topologically associating domains of the interphase chromosome exhibit multistability with varying liquid crystalline ordering that may allow discrete unfolding events and the landscape is locally funneled toward “ideal” chromosome structures that represent hierarchical fibrils of fibrils. PMID:25918364
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Kim, Tae-Woo; Kim, Woojae; Park, Kyu Hyung; Kim, Pyosang; Cho, Jae-Won; Shimizu, Hideyuki; Iyoda, Masahiko; Kim, Dongho
2016-02-04
Exciton dynamics in π-conjugated molecular systems is highly susceptible to conformational disorder. Using time-resolved and single-molecule spectroscopic techniques, the effect of chain length on the exciton dynamics in a series of linear oligothiophenes, for which the conformational disorder increased with increasing chain length, was investigated. As a result, extraordinary features of the exciton dynamics in longer-chain oligothiophene were revealed. Ultrafast fluorescence depolarization processes were observed due to exciton self-trapping in longer and bent chains. Increase in exciton delocalization during dynamic planarization processes was also observed in the linear oligothiophenes via time-resolved fluorescence spectra but was restricted in L-10T because of its considerable conformational disorder. Exciton delocalization was also unexpectedly observed in a bent chain using single-molecule fluorescence spectroscopy. Such delocalization modulates the fluorescence spectral shape by attenuating the 0-0 peak intensity. Collectively, these results provide significant insights into the exciton dynamics in conjugated polymers.
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Conserved conformational selection mechanism of Hsp70 chaperone-substrate interactions
Velyvis, Algirdas; Zoltsman, Guy; Rosenzweig, Rina; Bouvignies, Guillaume
2018-01-01
Molecular recognition is integral to biological function and frequently involves preferred binding of a molecule to one of several exchanging ligand conformations in solution. In such a process the bound structure can be selected from the ensemble of interconverting ligands a priori (conformational selection, CS) or may form once the ligand is bound (induced fit, IF). Here we focus on the ubiquitous and conserved Hsp70 chaperone which oversees the integrity of the cellular proteome through its ATP-dependent interaction with client proteins. We directly quantify the flux along CS and IF pathways using solution NMR spectroscopy that exploits a methyl TROSY effect and selective isotope-labeling methodologies. Our measurements establish that both bacterial and human Hsp70 chaperones interact with clients by selecting the unfolded state from a pre-existing array of interconverting structures, suggesting a conserved mode of client recognition among Hsp70s and highlighting the importance of molecular dynamics in this recognition event. PMID:29460778
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Matsunaga, Yasuhiro; Sugita, Yuji
2018-05-03
Single-molecule experiments and molecular dynamics (MD) simulations are indispensable tools for investigating protein conformational dynamics. The former provide time-series data, such as donor-acceptor distances, whereas the latter give atomistic information, although this information is often biased by model parameters. Here, we devise a machine-learning method to combine the complementary information from the two approaches and construct a consistent model of conformational dynamics. It is applied to the folding dynamics of the formin-binding protein WW domain. MD simulations over 400 μs led to an initial Markov state model (MSM), which was then "refined" using single-molecule Förster resonance energy transfer (FRET) data through hidden Markov modeling. The refined or data-assimilated MSM reproduces the FRET data and features hairpin one in the transition-state ensemble, consistent with mutation experiments. The folding pathway in the data-assimilated MSM suggests interplay between hydrophobic contacts and turn formation. Our method provides a general framework for investigating conformational transitions in other proteins. © 2018, Matsunaga et al.
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NASA Astrophysics Data System (ADS)
Flores, A. N.; Entekhabi, D.; Bras, R. L.
2007-12-01
Soil hydraulic and thermal properties (SHTPs) affect both the rate of moisture redistribution in the soil column and the volumetric soil water capacity. Adequately constraining these properties through field and lab analysis to parameterize spatially-distributed hydrology models is often prohibitively expensive. Because SHTPs vary significantly at small spatial scales individual soil samples are also only reliably indicative of local conditions, and these properties remain a significant source of uncertainty in soil moisture and temperature estimation. In ensemble-based soil moisture data assimilation, uncertainty in the model-produced prior estimate due to associated uncertainty in SHTPs must be taken into account to avoid under-dispersive ensembles. To treat SHTP uncertainty for purposes of supplying inputs to a distributed watershed model we use the restricted pairing (RP) algorithm, an extension of Latin Hypercube (LH) sampling. The RP algorithm generates an arbitrary number of SHTP combinations by sampling the appropriate marginal distributions of the individual soil properties using the LH approach, while imposing a target rank correlation among the properties. A previously-published meta- database of 1309 soils representing 12 textural classes is used to fit appropriate marginal distributions to the properties and compute the target rank correlation structure, conditioned on soil texture. Given categorical soil textures, our implementation of the RP algorithm generates an arbitrarily-sized ensemble of realizations of the SHTPs required as input to the TIN-based Realtime Integrated Basin Simulator with vegetation dynamics (tRIBS+VEGGIE) distributed parameter ecohydrology model. Soil moisture ensembles simulated with RP- generated SHTPs exhibit less variance than ensembles simulated with SHTPs generated by a scheme that neglects correlation among properties. Neglecting correlation among SHTPs can lead to physically unrealistic combinations of parameters that exhibit implausible hydrologic behavior when input to the tRIBS+VEGGIE model.
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CLS 2+1 flavor simulations at physical light-and strange-quark masses
NASA Astrophysics Data System (ADS)
Mohler, Daniel; Schaefer, Stefan; Simeth, Jakob
2018-03-01
We report recent efforts by CLS to generate an ensemble with physical lightand strange-quark masses in a lattice volume of 192 × 963 at β = 3:55 corresponding to a lattice spacing of 0:064 fm. This ensemble is being generated as part of the CLS 2+1 flavor effort with improved Wilson fermions. Our simulations currently cover 5 lattice spacings ranging from 0:039 fm to 0:086 fm at various pion masses along chiral trajectories with either the sum of the quark masses kept fixed, or with the strange-quark mass at the physical value. The current status of simulations is briefly reviewed, including a short discussion of measured autocorrelation times and of the main features of the simulations. We then proceed to discuss the thermalization strategy employed for the generation of the physical quark-mass ensemble and present first results for some simple observables. Challenges encountered in the simulation are highlighted.
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Dong, Ming-Xin; Zhang, Wei; Hou, Zhi-Bo; Yu, Yi-Chen; Shi, Shuai; Ding, Dong-Sheng; Shi, Bao-Sen
2017-11-15
Multi-photon entangled states not only play a crucial role in research on quantum physics but also have many applications in quantum information fields such as quantum computation, quantum communication, and quantum metrology. To fully exploit the multi-photon entangled states, it is important to establish the interaction between entangled photons and matter, which requires that photons have narrow bandwidth. Here, we report on the experimental generation of a narrowband four-photon Greenberger-Horne-Zeilinger state with a fidelity of 64.9% through multiplexing two spontaneous four-wave mixings in a cold Rb85 atomic ensemble. The full bandwidth of the generated GHZ state is about 19.5 MHz. Thus, the generated photons can effectively match the atoms, which are very suitable for building a quantum computation and quantum communication network based on atomic ensembles.
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Ferguson, Kate R; Beavan, Sarah E; Longdell, Jevon J; Sellars, Matthew J
2016-07-08
Here, we demonstrate generating and storing entanglement in a solid-state spin-wave quantum memory with on-demand readout using the process of rephased amplified spontaneous emission (RASE). Amplified spontaneous emission (ASE), resulting from an inverted ensemble of Pr^{3+} ions doped into a Y_{2}SiO_{5} crystal, generates entanglement between collective states of the praseodymium ensemble and the output light. The ensemble is then rephased using a four-level photon echo technique. Entanglement between the ASE and its echo is confirmed and the inseparability violation preserved when the RASE is stored as a spin wave for up to 5 μs. RASE is shown to be temporally multimode with almost perfect distinguishability between two temporal modes demonstrated. These results pave the way for the use of multimode solid-state quantum memories in scalable quantum networks.
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NASA Astrophysics Data System (ADS)
Merker, Claire; Ament, Felix; Clemens, Marco
2017-04-01
The quantification of measurement uncertainty for rain radar data remains challenging. Radar reflectivity measurements are affected, amongst other things, by calibration errors, noise, blocking and clutter, and attenuation. Their combined impact on measurement accuracy is difficult to quantify due to incomplete process understanding and complex interdependencies. An improved quality assessment of rain radar measurements is of interest for applications both in meteorology and hydrology, for example for precipitation ensemble generation, rainfall runoff simulations, or in data assimilation for numerical weather prediction. Especially a detailed description of the spatial and temporal structure of errors is beneficial in order to make best use of the areal precipitation information provided by radars. Radar precipitation ensembles are one promising approach to represent spatially variable radar measurement errors. We present a method combining ensemble radar precipitation nowcasting with data assimilation to estimate radar measurement uncertainty at each pixel. This combination of ensemble forecast and observation yields a consistent spatial and temporal evolution of the radar error field. We use an advection-based nowcasting method to generate an ensemble reflectivity forecast from initial data of a rain radar network. Subsequently, reflectivity data from single radars is assimilated into the forecast using the Local Ensemble Transform Kalman Filter. The spread of the resulting analysis ensemble provides a flow-dependent, spatially and temporally correlated reflectivity error estimate at each pixel. We will present first case studies that illustrate the method using data from a high-resolution X-band radar network.
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Generation, storage, and retrieval of nonclassical states of light using atomic ensembles
NASA Astrophysics Data System (ADS)
Eisaman, Matthew D.
This thesis presents the experimental demonstration of several novel methods for generating, storing, and retrieving nonclassical states of light using atomic ensembles, and describes applications of these methods to frequency-tunable single-photon generation, single-photon memory, quantum networks, and long-distance quantum communication. We first demonstrate emission of quantum-mechanically correlated pulses of light with a time delay between the pulses that is coherently controlled by utilizing 87Rb atoms. The experiment is based on Raman scattering, which produces correlated pairs of excited atoms and photons, followed by coherent conversion of the atomic states into a different photon field after a controllable delay. We then describe experiments demonstrating a novel approach for conditionally generating nonclassical pulses of light with controllable photon numbers, propagation direction, timing, and pulse shapes. We observe nonclassical correlations in relative photon number between correlated pairs of photons, and create few-photon light pulses with sub-Poissonian photon-number statistics via conditional detection on one field of the pair. Spatio-temporal control over the pulses is obtained by exploiting long-lived coherent memory for photon states and electromagnetically induced transparency (EIT) in an optically dense atomic medium. Finally, we demonstrate the use of EIT for the controllable generation, transmission, and storage of single photons with tunable frequency, timing, and bandwidth. To this end, we study the interaction of single photons produced in a "source" ensemble of 87Rb atoms at room temperature with another "target" ensemble. This allows us to simultaneously probe the spectral and quantum statistical properties of narrow-bandwidth single-photon pulses, revealing that their quantum nature is preserved under EIT propagation and storage. We measure the time delay associated with the reduced group velocity of the single-photon pulses and report observations of their storage and retrieval. Together these experiments utilize atomic ensembles to realize a narrow-bandwidth single-photon source, single-photon memory that preserves the quantum nature of the single photons, and a primitive quantum network comprised of two atomic-ensemble quantum memories connected by a single photon in an optical fiber. Each of these experimental demonstrations represents an essential element for the realization of long-distance quantum communication.
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2012-02-01
AFRL-RX-TY-TR-2012-0022 ANALYSIS OF COMMERCIALLY AVAILABLE HELMET AND BOOT OPTIONS FOR THE JOINT FIREFIGHTER INTEGRATED RESPONSE ENSEMBLE...Interim Technical Report 01-SEP-2010 -- 31-JAN-2011 Analysis of Commercially Available Firefighting Helmet and Boot Options for the Joint Firefighter...ensemble. A requirements correlation matrix was generated and sent to industry detailing objective and threshold measurements for both the helmet
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Conformal field theory out of equilibrium: a review
NASA Astrophysics Data System (ADS)
Bernard, Denis; Doyon, Benjamin
2016-06-01
We provide a pedagogical review of the main ideas and results in non-equilibrium conformal field theory and connected subjects. These concern the understanding of quantum transport and its statistics at and near critical points. Starting with phenomenological considerations, we explain the general framework, illustrated by the example of the Heisenberg quantum chain. We then introduce the main concepts underlying conformal field theory (CFT), the emergence of critical ballistic transport, and the CFT scattering construction of non-equilibrium steady states. Using this we review the theory for energy transport in homogeneous one-dimensional critical systems, including the complete description of its large deviations and the resulting (extended) fluctuation relations. We generalize some of these ideas to one-dimensional critical charge transport and to the presence of defects, as well as beyond one-dimensional criticality. We describe non-equilibrium transport in free-particle models, where connections are made with generalized Gibbs ensembles, and in higher-dimensional and non-integrable quantum field theories, where the use of the powerful hydrodynamic ideas for non-equilibrium steady states is explained. We finish with a list of open questions. The review does not assume any advanced prior knowledge of conformal field theory, large-deviation theory or hydrodynamics.
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Verbaro, Daniel; Ghosh, Indrajit; Nau, Werner M; Schweitzer-Stenner, Reinhard
2010-12-30
Structural preferences in the unfolded state of peptides determined by molecular dynamics still contradict experimental data. A remedy in this regard has been suggested by MD simulations with an optimized Amber force field ff03* ( Best, R. Hummer, G. J. Phys. Chem. B 2009 , 113 , 9004 - 9015 ). The simulations yielded a statistical coil distribution for alanine which is at variance with recent experimental results. To check the validity of this distribution, we investigated the peptide H-A(5)W-OH, which with the exception of the additional terminal tryptophan is analogous to the peptide used to optimize the force fields ff03*. Electronic circular dichroism, vibrational circular dichroism, and infrared spectroscopy as well as J-coupling constants obtained from NMR experiments were used to derive the peptide's conformational ensemble. Additionally, Förster resonance energy transfer between the terminal chromophores of the fluorescently labeled peptide analogue H-Dbo-A(5)W-OH was used to determine its average length, from which the end-to-end distance of the unlabeled peptide was estimated. Qualitatively, the experimental (3)J(H(N),C(α)), VCD, and ECD indicated a preference of alanine for polyproline II-like conformations. The experimental (3)J(H(N),C(α)) for A(5)W closely resembles the constants obtained for A(5). In order to quantitatively relate the conformational distribution of A(5) obtained with the optimized AMBER ff03* force field to experimental data, the former was used to derive a distribution function which expressed the conformational ensemble as a mixture of polyproline II, β-strand, helical, and turn conformations. This model was found to satisfactorily reproduce all experimental J-coupling constants. We employed the model to calculate the amide I' profiles of the IR and vibrational circular dichroism spectrum of A(5)W, as well as the distance between the two terminal peptide carbonyls. This led to an underestimated negative VCD couplet and an overestimated distance between terminal carbonyl groups. In order to more accurately account for the experimental data, we changed the distribution parameters based on results recently obtained for the alanine-based tripeptides. The final model, which satisfactorily reproduced amide I' profiles, J-coupling constant, and the end-to-end distance of A(5)W, reinforces alanine's high structural preference for polyproline II. Our results suggest that distributions obtained from MD simulations suggesting a statistical coil-like distribution for alanine are still based on insufficiently accurate force fields.
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Loop Electrostatics Asymmetry Modulates the Preexisting Conformational Equilibrium in Thrombin.
Pozzi, Nicola; Zerbetto, Mirco; Acquasaliente, Laura; Tescari, Simone; Frezzato, Diego; Polimeno, Antonino; Gohara, David W; Di Cera, Enrico; De Filippis, Vincenzo
2016-07-19
Thrombin exists as an ensemble of active (E) and inactive (E*) conformations that differ in their accessibility to the active site. Here we show that redistribution of the E*-E equilibrium can be achieved by perturbing the electrostatic properties of the enzyme. Removal of the negative charge of the catalytic Asp102 or Asp189 in the primary specificity site destabilizes the E form and causes a shift in the 215-217 segment that compromises substrate entrance. Solution studies and existing structures of D102N document stabilization of the E* form. A new high-resolution structure of D189A also reveals the mutant in the collapsed E* form. These findings establish a new paradigm for the control of the E*-E equilibrium in the trypsin fold.
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Localized AdS_{5}×S^{5} Black Holes.
Dias, Óscar J C; Santos, Jorge E; Way, Benson
2016-10-07
According to heuristic arguments, global AdS_{5}×S^{5} black holes are expected to undergo a phase transition in the microcanonical ensemble. At high energies, one expects black holes that respect the symmetries of the S^{5}; at low energies, one expects "localized" black holes that appear pointlike on the S^{5}. According to anti-de Sitter/conformal field theory correspondence, N=4 supersymmetric Yang-Mills (SYM) theory on a 3-sphere should therefore exhibit spontaneous R-symmetry breaking at strong coupling. In this Letter, we numerically construct these localized black holes. We extrapolate the location of this phase transition, and compute the expectation value of the broken scalar operator with lowest conformal dimension. Via the correspondence, these results offer quantitative predictions for N=4 SYM theory.
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Conformational Equilibria in Monomeric α-Synuclein at the Single-Molecule Level
Tessari, Isabella; Mammi, Stefano; Bergantino, Elisabetta; Musiani, Francesco; Brucale, Marco; Bubacco, Luigi; Samorì, Bruno
2008-01-01
Human α-Synuclein (αSyn) is a natively unfolded protein whose aggregation into amyloid fibrils is involved in the pathology of Parkinson disease. A full comprehension of the structure and dynamics of early intermediates leading to the aggregated states is an unsolved problem of essential importance to researchers attempting to decipher the molecular mechanisms of αSyn aggregation and formation of fibrils. Traditional bulk techniques used so far to solve this problem point to a direct correlation between αSyn's unique conformational properties and its propensity to aggregate, but these techniques can only provide ensemble-averaged information for monomers and oligomers alike. They therefore cannot characterize the full complexity of the conformational equilibria that trigger the aggregation process. We applied atomic force microscopy–based single-molecule mechanical unfolding methodology to study the conformational equilibrium of human wild-type and mutant αSyn. The conformational heterogeneity of monomeric αSyn was characterized at the single-molecule level. Three main classes of conformations, including disordered and “β-like” structures, were directly observed and quantified without any interference from oligomeric soluble forms. The relative abundance of the “β-like” structures significantly increased in different conditions promoting the aggregation of αSyn: the presence of Cu2+, the pathogenic A30P mutation, and high ionic strength. This methodology can explore the full conformational space of a protein at the single-molecule level, detecting even poorly populated conformers and measuring their distribution in a variety of biologically important conditions. To the best of our knowledge, we present for the first time evidence of a conformational equilibrium that controls the population of a specific class of monomeric αSyn conformers, positively correlated with conditions known to promote the formation of aggregates. A new tool is thus made available to test directly the influence of mutations and pharmacological strategies on the conformational equilibrium of monomeric αSyn. PMID:18198943
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NASA Astrophysics Data System (ADS)
Pinson, Pierre
2016-04-01
The operational management of renewable energy generation in power systems and electricity markets requires forecasts in various forms, e.g., deterministic or probabilistic, continuous or categorical, depending upon the decision process at hand. Besides, such forecasts may also be necessary at various spatial and temporal scales, from high temporal resolutions (in the order of minutes) and very localized for an offshore wind farm, to coarser temporal resolutions (hours) and covering a whole country for day-ahead power scheduling problems. As of today, weather predictions are a common input to forecasting methodologies for renewable energy generation. Since for most decision processes, optimal decisions can only be made if accounting for forecast uncertainties, ensemble predictions and density forecasts are increasingly seen as the product of choice. After discussing some of the basic approaches to obtaining ensemble forecasts of renewable power generation, it will be argued that space-time trajectories of renewable power production may or may not be necessitate post-processing ensemble forecasts for relevant weather variables. Example approaches and test case applications will be covered, e.g., looking at the Horns Rev offshore wind farm in Denmark, or gridded forecasts for the whole continental Europe. Eventually, we will illustrate some of the limitations of current frameworks to forecast verification, which actually make it difficult to fully assess the quality of post-processing approaches to obtain renewable energy predictions.
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Discrete structure of an RNA folding intermediate revealed by cryo-electron microscopy.
Baird, Nathan J; Ludtke, Steven J; Khant, Htet; Chiu, Wah; Pan, Tao; Sosnick, Tobin R
2010-11-24
RNA folding occurs via a series of transitions between metastable intermediate states. It is unknown whether folding intermediates are discrete structures folding along defined pathways or heterogeneous ensembles folding along broad landscapes. We use cryo-electron microscopy and single-particle image reconstruction to determine the structure of the major folding intermediate of the specificity domain of a ribonuclease P ribozyme. Our results support the existence of a discrete conformation for this folding intermediate.
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Interaction of the Disordered Yersinia Effector Protein YopE with Its Cognate Chaperone SycE
2009-01-01
structures of YopECBD were molten globules with a hydrophobic core. Molecular dynamics (MD) simulations indi- cated that the structure remained compact at...ensembles of unfolded conformations of the Yersinia effector YopE using REMD simulations and docked them to the chaper- one SycE using a multistep protein...disordered state but transitions into an ordered state upon binding to its cognate chaperone (7). The dynamics of the disordered effector protein and
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Internal protein motions in molecular-dynamics simulations of Bragg and diffuse X-ray scattering.
Wall, Michael E
2018-03-01
Molecular-dynamics (MD) simulations of Bragg and diffuse X-ray scattering provide a means of obtaining experimentally validated models of protein conformational ensembles. This paper shows that compared with a single periodic unit-cell model, the accuracy of simulating diffuse scattering is increased when the crystal is modeled as a periodic supercell consisting of a 2 × 2 × 2 layout of eight unit cells. The MD simulations capture the general dependence of correlations on the separation of atoms. There is substantial agreement between the simulated Bragg reflections and the crystal structure; there are local deviations, however, indicating both the limitation of using a single structure to model disordered regions of the protein and local deviations of the average structure away from the crystal structure. Although it was anticipated that a simulation of longer duration might be required to achieve maximal agreement of the diffuse scattering calculation with the data using the supercell model, only a microsecond is required, the same as for the unit cell. Rigid protein motions only account for a minority fraction of the variation in atom positions from the simulation. The results indicate that protein crystal dynamics may be dominated by internal motions rather than packing interactions, and that MD simulations can be combined with Bragg and diffuse X-ray scattering to model the protein conformational ensemble.
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Dissimilarities of reduced density matrices and eigenstate thermalization hypothesis
NASA Astrophysics Data System (ADS)
He, Song; Lin, Feng-Li; Zhang, Jia-ju
2017-12-01
We calculate various quantities that characterize the dissimilarity of reduced density matrices for a short interval of length ℓ in a two-dimensional (2D) large central charge conformal field theory (CFT). These quantities include the Rényi entropy, entanglement entropy, relative entropy, Jensen-Shannon divergence, as well as the Schatten 2-norm and 4-norm. We adopt the method of operator product expansion of twist operators, and calculate the short interval expansion of these quantities up to order of ℓ9 for the contributions from the vacuum conformal family. The formal forms of these dissimilarity measures and the derived Fisher information metric from contributions of general operators are also given. As an application of the results, we use these dissimilarity measures to compare the excited and thermal states, and examine the eigenstate thermalization hypothesis (ETH) by showing how they behave in high temperature limit. This would help to understand how ETH in 2D CFT can be defined more precisely. We discuss the possibility that all the dissimilarity measures considered here vanish when comparing the reduced density matrices of an excited state and a generalized Gibbs ensemble thermal state. We also discuss ETH for a microcanonical ensemble thermal state in a 2D large central charge CFT, and find that it is approximately satisfied for a small subsystem and violated for a large subsystem.
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Internal protein motions in molecular-dynamics simulations of Bragg and diffuse X-ray scattering
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wall, Michael E.
Molecular-dynamics (MD) simulations of Bragg and diffuse X-ray scattering provide a means of obtaining experimentally validated models of protein conformational ensembles. This paper shows that compared with a single periodic unit-cell model, the accuracy of simulating diffuse scattering is increased when the crystal is modeled as a periodic supercell consisting of a 2 × 2 × 2 layout of eight unit cells. The MD simulations capture the general dependence of correlations on the separation of atoms. There is substantial agreement between the simulated Bragg reflections and the crystal structure; there are local deviations, however, indicating both the limitation of using a single structuremore » to model disordered regions of the protein and local deviations of the average structure away from the crystal structure. Although it was anticipated that a simulation of longer duration might be required to achieve maximal agreement of the diffuse scattering calculation with the data using the supercell model, only a microsecond is required, the same as for the unit cell. Rigid protein motions only account for a minority fraction of the variation in atom positions from the simulation. The results indicate that protein crystal dynamics may be dominated by internal motions rather than packing interactions, and that MD simulations can be combined with Bragg and diffuse X-ray scattering to model the protein conformational ensemble.« less
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Internal protein motions in molecular-dynamics simulations of Bragg and diffuse X-ray scattering
Wall, Michael E.
2018-01-25
Molecular-dynamics (MD) simulations of Bragg and diffuse X-ray scattering provide a means of obtaining experimentally validated models of protein conformational ensembles. This paper shows that compared with a single periodic unit-cell model, the accuracy of simulating diffuse scattering is increased when the crystal is modeled as a periodic supercell consisting of a 2 × 2 × 2 layout of eight unit cells. The MD simulations capture the general dependence of correlations on the separation of atoms. There is substantial agreement between the simulated Bragg reflections and the crystal structure; there are local deviations, however, indicating both the limitation of using a single structuremore » to model disordered regions of the protein and local deviations of the average structure away from the crystal structure. Although it was anticipated that a simulation of longer duration might be required to achieve maximal agreement of the diffuse scattering calculation with the data using the supercell model, only a microsecond is required, the same as for the unit cell. Rigid protein motions only account for a minority fraction of the variation in atom positions from the simulation. The results indicate that protein crystal dynamics may be dominated by internal motions rather than packing interactions, and that MD simulations can be combined with Bragg and diffuse X-ray scattering to model the protein conformational ensemble.« less
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Kozakov, Dima; Grove, Laurie E.; Hall, David R.; Bohnuud, Tanggis; Mottarella, Scott; Luo, Lingqi; Xia, Bing; Beglov, Dmitri; Vajda, Sandor
2016-01-01
FTMap is a computational mapping server that identifies binding hot spots of macromolecules, i.e., regions of the surface with major contributions to the ligand binding free energy. To use FTMap, users submit a protein, DNA, or RNA structure in PDB format. FTMap samples billions of positions of small organic molecules used as probes and scores the probe poses using a detailed energy expression. Regions that bind clusters of multiple probe types identify the binding hot spots, in good agreement with experimental data. FTMap serves as basis for other servers, namely FTSite to predict ligand binding sites, FTFlex to account for side chain flexibility, FTMap/param to parameterize additional probes, and FTDyn to map ensembles of protein structures. Applications include determining druggability of proteins, identifying ligand moieties that are most important for binding, finding the most bound-like conformation in ensembles of unliganded protein structures, and providing input for fragment based drug design. FTMap is more accurate than classical mapping methods such as GRID and MCSS, and is much faster than the more recent approaches to protein mapping based on mixed molecular dynamics. Using 16 probe molecules, the FTMap server finds the hot spots of an average size protein in less than an hour. Since FTFlex performs mapping for all low energy conformers of side chains in the binding site, its completion time is proportionately longer. PMID:25855957
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Els-Heindl, Sylvia; Chollet, Constance; Scheidt, Holger A.; Beck-Sickinger, Annette G.; Meiler, Jens; Huster, Daniel
2015-01-01
The peptide hormone ghrelin activates the growth hormone secretagogue receptor 1a, also known as the ghrelin receptor. This 28-residue peptide is acylated at Ser3 and is the only peptide hormone in the human body that is lipid-modified by an octanoyl group. Little is known about the structure and dynamics of membrane-associated ghrelin. We carried out solid-state NMR studies of ghrelin in lipid vesicles, followed by computational modeling of the peptide using Rosetta. Isotropic chemical shift data of isotopically labeled ghrelin provide information about the peptide’s secondary structure. Spin diffusion experiments indicate that ghrelin binds to membranes via its lipidated Ser3. Further, Phe4, as well as electrostatics involving the peptide’s positively charged residues and lipid polar headgroups, contribute to the binding energy. Other than the lipid anchor, ghrelin is highly flexible and mobile at the membrane surface. This observation is supported by our predicted model ensemble, which is in good agreement with experimentally determined chemical shifts. In the final ensemble of models, residues 8–17 form an α-helix, while residues 21–23 and 26–27 often adopt a polyproline II helical conformation. These helices appear to assist the peptide in forming an amphipathic conformation so that it can bind to the membrane. PMID:25803439
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Suddala, Krishna C.; Rinaldi, Arlie J.; Feng, Jun; Mustoe, Anthony M.; Eichhorn, Catherine D.; Liberman, Joseph A.; Wedekind, Joseph E.; Al-Hashimi, Hashim M.; Brooks, Charles L.; Walter, Nils G.
2013-01-01
Riboswitches are structural elements in the 5′ untranslated regions of many bacterial messenger RNAs that regulate gene expression in response to changing metabolite concentrations by inhibition of either transcription or translation initiation. The preQ1 (7-aminomethyl-7-deazaguanine) riboswitch family comprises some of the smallest metabolite sensing RNAs found in nature. Once ligand-bound, the transcriptional Bacillus subtilis and translational Thermoanaerobacter tengcongensis preQ1 riboswitch aptamers are structurally similar RNA pseudoknots; yet, prior structural studies have characterized their ligand-free conformations as largely unfolded and folded, respectively. In contrast, through single molecule observation, we now show that, at near-physiological Mg2+ concentration and pH, both ligand-free aptamers adopt similar pre-folded state ensembles that differ in their ligand-mediated folding. Structure-based Gō-model simulations of the two aptamers suggest that the ligand binds late (Bacillus subtilis) and early (Thermoanaerobacter tengcongensis) relative to pseudoknot folding, leading to the proposal that the principal distinction between the two riboswitches lies in their relative tendencies to fold via mechanisms of conformational selection and induced fit, respectively. These mechanistic insights are put to the test by rationally designing a single nucleotide swap distal from the ligand binding pocket that we find to predictably control the aptamers′ pre-folded states and their ligand binding affinities. PMID:24003028
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Entanglement of 3000 atoms by detecting one photon
NASA Astrophysics Data System (ADS)
Vuletic, Vladan
2016-05-01
Quantum-mechanically correlated (entangled) states of many particles are of interest in quantum information, quantum computing and quantum metrology. In particular, entangled states of many particles can be used to overcome limits on measurements performed with ensembles of independent atoms (standard quantum limit). Metrologically useful entangled states of large atomic ensembles (spin squeezed states) have been experimentally realized. These states display Gaussian spin distribution functions with a non-negative Wigner quasiprobability distribution function. We report the generation of entanglement in a large atomic ensemble via an interaction with a very weak laser pulse; remarkably, the detection of a single photon prepares several thousand atoms in an entangled state. We reconstruct a negative-valued Wigner function, and verify an entanglement depth (the minimum number of mutually entangled atoms) that comprises 90% of the atomic ensemble containing 3100 atoms. Further technical improvement should allow the generation of more complex Schrödinger cat states, and of states the overcome the standard quantum limit.
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The Correlated Jacobi and the Correlated Cauchy-Lorentz Ensembles
NASA Astrophysics Data System (ADS)
Wirtz, Tim; Waltner, Daniel; Kieburg, Mario; Kumar, Santosh
2016-01-01
We calculate the k-point generating function of the correlated Jacobi ensemble using supersymmetric methods. We use the result for complex matrices for k=1 to derive a closed-form expression for the eigenvalue density. For real matrices we obtain the density in terms of a twofold integral that we evaluate numerically. For both expressions we find agreement when comparing with Monte Carlo simulations. Relations between these quantities for the Jacobi and the Cauchy-Lorentz ensemble are derived.
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Entanglement with negative Wigner function of almost 3,000 atoms heralded by one photon.
McConnell, Robert; Zhang, Hao; Hu, Jiazhong; Ćuk, Senka; Vuletić, Vladan
2015-03-26
Quantum-mechanically correlated (entangled) states of many particles are of interest in quantum information, quantum computing and quantum metrology. Metrologically useful entangled states of large atomic ensembles have been experimentally realized, but these states display Gaussian spin distribution functions with a non-negative Wigner quasiprobability distribution function. Non-Gaussian entangled states have been produced in small ensembles of ions, and very recently in large atomic ensembles. Here we generate entanglement in a large atomic ensemble via an interaction with a very weak laser pulse; remarkably, the detection of a single photon prepares several thousand atoms in an entangled state. We reconstruct a negative-valued Wigner function--an important hallmark of non-classicality--and verify an entanglement depth (the minimum number of mutually entangled atoms) of 2,910 ± 190 out of 3,100 atoms. Attaining such a negative Wigner function and the mutual entanglement of virtually all atoms is unprecedented for an ensemble containing more than a few particles. Although the achieved purity of the state is slightly below the threshold for entanglement-induced metrological gain, further technical improvement should allow the generation of states that surpass this threshold, and of more complex Schrödinger cat states for quantum metrology and information processing. More generally, our results demonstrate the power of heralded methods for entanglement generation, and illustrate how the information contained in a single photon can drastically alter the quantum state of a large system.
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NASA Astrophysics Data System (ADS)
Lewis, Jared; Bodeker, Greg E.; Kremser, Stefanie; Tait, Andrew
2017-12-01
A method, based on climate pattern scaling, has been developed to expand a small number of projections of fields of a selected climate variable (X) into an ensemble that encapsulates a wide range of indicative model structural uncertainties. The method described in this paper is referred to as the Ensemble Projections Incorporating Climate model uncertainty (EPIC) method. Each ensemble member is constructed by adding contributions from (1) a climatology derived from observations that represents the time-invariant part of the signal; (2) a contribution from forced changes in X, where those changes can be statistically related to changes in global mean surface temperature (Tglobal); and (3) a contribution from unforced variability that is generated by a stochastic weather generator. The patterns of unforced variability are also allowed to respond to changes in Tglobal. The statistical relationships between changes in X (and its patterns of variability) and Tglobal are obtained in a
training
phase. Then, in animplementation
phase, 190 simulations of Tglobal are generated using a simple climate model tuned to emulate 19 different global climate models (GCMs) and 10 different carbon cycle models. Using the generated Tglobal time series and the correlation between the forced changes in X and Tglobal, obtained in thetraining
phase, the forced change in the X field can be generated many times using Monte Carlo analysis. A stochastic weather generator is used to generate realistic representations of weather which include spatial coherence. Because GCMs and regional climate models (RCMs) are less likely to correctly represent unforced variability compared to observations, the stochastic weather generator takes as input measures of variability derived from observations, but also responds to forced changes in climate in a way that is consistent with the RCM projections. This approach to generating a large ensemble of projections is many orders of magnitude more computationally efficient than running multiple GCM or RCM simulations. Such a large ensemble of projections permits a description of a probability density function (PDF) of future climate states rather than a small number of individual story lines within that PDF, which may not be representative of the PDF as a whole; the EPIC method largely corrects for such potential sampling biases. The method is useful for providing projections of changes in climate to users wishing to investigate the impacts and implications of climate change in a probabilistic way. A web-based tool, using the EPIC method to provide probabilistic projections of changes in daily maximum and minimum temperatures for New Zealand, has been developed and is described in this paper. -
The Road to DLCZ Protocol in Rubidium Ensemble
NASA Astrophysics Data System (ADS)
Li, Chang; Pu, Yunfei; Jiang, Nan; Chang, Wei; Zhang, Sheng; CenterQuantum Information, InstituteInterdisciplinary Information Sciences, Tsinghua Univ Team
2017-04-01
Quantum communication is the powerful approach achieving a fully secure information transferal. The DLCZ protocol ensures that photon linearly decays with transferring distance increasing, which improves the success potential and shortens the time to build up an entangled channel. Apart from that, it provides an advanced idea that building up a quantum internet based on different nodes connected to different sites and themselves. In our laboratory, three sets of laser-cooled Rubidium 87 ensemble have been built. Two of them serve as the single photon emitter, which generate the entanglement between ensemble and photon. What's more, crossed AODs are equipped to multiplex and demultiplex optical circuit so that ensemble is divided into 2 hundred of 2D sub-memory cells. And the third ensemble is used as quantum telecommunication, which converts 780nm photon into telecom-wavelength one. And we have been building double-MOT system, which provides more atoms in ensemble and larger optical density.
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Free energy landscapes of peptides by enhanced conformational sampling.
Nakajima, N; Higo, J; Kidera, A; Nakamura, H
2000-02-11
The free energy landscapes of peptide conformations in water have been observed by the enhanced conformational sampling method, applying the selectively enhanced multicanonical molecular dynamics simulations. The conformations of the peptide dimers, -Gly-Gly-, -Gly-Ala-, -Gly-Ser-, -Ala-Gly-, -Asn-Gly-, -Pro-Gly-, -Pro-Ala-, and -Ala-Ala-, which were all blocked with N-terminal acetyl and C-terminal N-methyl groups, were individually sampled with the explicit TIP3P water molecules. From each simulation trajectory, we obtained the canonical ensemble at 300 K, from which the individual three-dimensional landscape was drawn by the potential of mean force using the three reaction coordinates: the backbone dihedral angle, psi, of the first amino acid, the backbone dihedral angle, phi, of the second amino acid, and the distance between the carbonyl oxygen of the N-terminal acetyl group and the C-terminal amide proton. The most stable state and several meta-stable states correspond to extended conformations and typical beta-turn conformations, and their free energy values were accounted for from the potentials of mean force at the states. In addition, the contributions from the intra-molecular energies of peptides and those from the hydration effects were analyzed. Consequently, the stable beta-turn conformations in the free energy landscape were consistent with the empirically preferred beta-turn types for each amino acid sequence. The thermodynamic values for the hydration effect were decomposed and they correlated well with the empirical values estimated from the solvent accessible surface area of each molecular conformation during the trajectories. The origin of the architecture of protein local fragments was analyzed from the viewpoint of the free energy and its decomposed factors. Copyright 2000 Academic Press.
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Frustration-guided motion planning reveals conformational transitions in proteins
DOE Office of Scientific and Technical Information (OSTI.GOV)
Budday, Dominik; Fonseca, Rasmus; Leyendecker, Sigrid
Proteins exist as conformational ensembles, exchanging between substates to perform their function. Advances in experimental techniques yield unprecedented access to structural snapshots of their conformational landscape. However, computationally modeling how proteins use collective motions to transition between substates is challenging owing to a rugged landscape and large energy barriers. Here in this paper, we present a new, robotics-inspired motion planning procedure called dCCRRT that navigates the rugged landscape between substates by introducing dynamic, interatomic constraints to modulate frustration. The constraints balance non-native contacts and flexibility, and instantaneously redirect the motion towards sterically favorable conformations. On a test set of eightmore » proteins determined in two conformations separated by, on average, 7.5Å root mean square deviation (RMSD), our pathways reduced the Cα atom RMSD to the goal conformation by 78%, outperforming peer methods. Additionally, we then applied dCC-RRT to examine how collective, small-scale motions of four side-chains in the active site of cyclophilin A propagate through the protein. dCC-RRT uncovered a spatially contiguous network of residues linked by steric interactions and collective motion connecting the active site to a recently proposed, non-canonical capsid binding site 25Å away, rationalizing NMR and multi-temperature crystallography experiments. In all, dCC-RRT can reveal detailed, all-atom molecular mechanisms for small and large amplitude motions.Source code and binaries are freely available at https://github.com/ExcitedStates/KGS/.« less
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Frustration-guided motion planning reveals conformational transitions in proteins.
Budday, Dominik; Fonseca, Rasmus; Leyendecker, Sigrid; van den Bedem, Henry
2017-10-01
Proteins exist as conformational ensembles, exchanging between substates to perform their function. Advances in experimental techniques yield unprecedented access to structural snapshots of their conformational landscape. However, computationally modeling how proteins use collective motions to transition between substates is challenging owing to a rugged landscape and large energy barriers. Here, we present a new, robotics-inspired motion planning procedure called dCC-RRT that navigates the rugged landscape between substates by introducing dynamic, interatomic constraints to modulate frustration. The constraints balance non-native contacts and flexibility, and instantaneously redirect the motion towards sterically favorable conformations. On a test set of eight proteins determined in two conformations separated by, on average, 7.5 Å root mean square deviation (RMSD), our pathways reduced the Cα atom RMSD to the goal conformation by 78%, outperforming peer methods. We then applied dCC-RRT to examine how collective, small-scale motions of four side-chains in the active site of cyclophilin A propagate through the protein. dCC-RRT uncovered a spatially contiguous network of residues linked by steric interactions and collective motion connecting the active site to a recently proposed, non-canonical capsid binding site 25 Å away, rationalizing NMR and multi-temperature crystallography experiments. In all, dCC-RRT can reveal detailed, all-atom molecular mechanisms for small and large amplitude motions. Source code and binaries are freely available at https://github.com/ExcitedStates/KGS/. © 2017 Wiley Periodicals, Inc.
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Frustration-guided motion planning reveals conformational transitions in proteins
Budday, Dominik; Fonseca, Rasmus; Leyendecker, Sigrid; ...
2017-07-12
Proteins exist as conformational ensembles, exchanging between substates to perform their function. Advances in experimental techniques yield unprecedented access to structural snapshots of their conformational landscape. However, computationally modeling how proteins use collective motions to transition between substates is challenging owing to a rugged landscape and large energy barriers. Here in this paper, we present a new, robotics-inspired motion planning procedure called dCCRRT that navigates the rugged landscape between substates by introducing dynamic, interatomic constraints to modulate frustration. The constraints balance non-native contacts and flexibility, and instantaneously redirect the motion towards sterically favorable conformations. On a test set of eightmore » proteins determined in two conformations separated by, on average, 7.5Å root mean square deviation (RMSD), our pathways reduced the Cα atom RMSD to the goal conformation by 78%, outperforming peer methods. Additionally, we then applied dCC-RRT to examine how collective, small-scale motions of four side-chains in the active site of cyclophilin A propagate through the protein. dCC-RRT uncovered a spatially contiguous network of residues linked by steric interactions and collective motion connecting the active site to a recently proposed, non-canonical capsid binding site 25Å away, rationalizing NMR and multi-temperature crystallography experiments. In all, dCC-RRT can reveal detailed, all-atom molecular mechanisms for small and large amplitude motions.Source code and binaries are freely available at https://github.com/ExcitedStates/KGS/.« less
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Da, Chenxiao; Mooberry, Susan L.; Gupton, John T.; Kellogg, Glen E.
2013-01-01
αβ-tubulin colchicine site inhibitors (CSIs) from four scaffolds that we previously tested for antiproliferative activity were modeled to better understand their effect on microtubules. Docking models, constructed by exploiting the SAR of a pyrrole subset and HINT scoring, guided ensemble docking of all 59 compounds. This conformation set and two variants having progressively less structure knowledge were subjected to CoMFA, CoMFA+HINT, and CoMSIA 3D-QSAR analyses. The CoMFA+HINT model (docked alignment) showed the best statistics: leave-one-out q2 of 0.616, r2 of 0.949 and r2pred (internal test set) of 0.755. An external (tested in other laboratories) collection of 24 CSIs from eight scaffolds were evaluated with the 3D-QSAR models, which correctly ranked their activity trends in 7/8 scaffolds for CoMFA+HINT (8/8 for CoMFA). The combination of SAR, ensemble docking, hydropathic analysis and 3D-QSAR provides an atomic-scale colchicine site model more consistent with a target structure resolution much higher than the ~3.6 Å available for αβ-tubulin. PMID:23961916
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OSPREY: protein design with ensembles, flexibility, and provable algorithms.
Gainza, Pablo; Roberts, Kyle E; Georgiev, Ivelin; Lilien, Ryan H; Keedy, Daniel A; Chen, Cheng-Yu; Reza, Faisal; Anderson, Amy C; Richardson, David C; Richardson, Jane S; Donald, Bruce R
2013-01-01
We have developed a suite of protein redesign algorithms that improves realistic in silico modeling of proteins. These algorithms are based on three characteristics that make them unique: (1) improved flexibility of the protein backbone, protein side-chains, and ligand to accurately capture the conformational changes that are induced by mutations to the protein sequence; (2) modeling of proteins and ligands as ensembles of low-energy structures to better approximate binding affinity; and (3) a globally optimal protein design search, guaranteeing that the computational predictions are optimal with respect to the input model. Here, we illustrate the importance of these three characteristics. We then describe OSPREY, a protein redesign suite that implements our protein design algorithms. OSPREY has been used prospectively, with experimental validation, in several biomedically relevant settings. We show in detail how OSPREY has been used to predict resistance mutations and explain why improved flexibility, ensembles, and provability are essential for this application. OSPREY is free and open source under a Lesser GPL license. The latest version is OSPREY 2.0. The program, user manual, and source code are available at www.cs.duke.edu/donaldlab/software.php. osprey@cs.duke.edu. Copyright © 2013 Elsevier Inc. All rights reserved.
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Revealing the distinct folding phases of an RNA three-helix junction.
Plumridge, Alex; Katz, Andrea M; Calvey, George D; Elber, Ron; Kirmizialtin, Serdal; Pollack, Lois
2018-05-14
Remarkable new insight has emerged into the biological role of RNA in cells. RNA folding and dynamics enable many of these newly discovered functions, calling for an understanding of RNA self-assembly and conformational dynamics. Because RNAs pass through multiple structures as they fold, an ensemble perspective is required to visualize the flow through fleetingly populated sets of states. Here, we combine microfluidic mixing technology and small angle X-ray scattering (SAXS) to measure the Mg-induced folding of a small RNA domain, the tP5abc three helix junction. Our measurements are interpreted using ensemble optimization to select atomically detailed structures that recapitulate each experimental curve. Structural ensembles, derived at key stages in both time-resolved studies and equilibrium titrations, reproduce the features of known intermediates, and more importantly, offer a powerful new structural perspective on the time-progression of folding. Distinct collapse phases along the pathway appear to be orchestrated by specific interactions with Mg ions. These key interactions subsequently direct motions of the backbone that position the partners of tertiary contacts for later bonding, and demonstrate a remarkable synergy between Mg and RNA across numerous time-scales.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Shi, Jade; Nobrega, R. Paul; Schwantes, Christian
The dynamics of globular proteins can be described in terms of transitions between a folded native state and less-populated intermediates, or excited states, which can play critical roles in both protein folding and function. Excited states are by definition transient species, and therefore are difficult to characterize using current experimental techniques. We report an atomistic model of the excited state ensemble of a stabilized mutant of an extensively studied flavodoxin fold protein CheY. We employed a hybrid simulation and experimental approach in which an aggregate 42 milliseconds of all-atom molecular dynamics were used as an informative prior for the structuremore » of the excited state ensemble. The resulting prior was then refined against small-angle X-ray scattering (SAXS) data employing an established method (EROS). The most striking feature of the resulting excited state ensemble was an unstructured N-terminus stabilized by non-native contacts in a conformation that is topologically simpler than the native state. We then predict incisive single molecule FRET experiments, using these results, as a means of model validation. Our study demonstrates the paradigm of uniting simulation and experiment in a statistical model to study the structure of protein excited states and rationally design validating experiments.« less
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Random-fractal Ansatz for the configurations of two-dimensional critical systems
NASA Astrophysics Data System (ADS)
Lee, Ching Hua; Ozaki, Dai; Matsueda, Hiroaki
2016-12-01
Critical systems have always intrigued physicists and precipitated the development of new techniques. Recently, there has been renewed interest in the information contained in the configurations of classical critical systems, whose computation do not require full knowledge of the wave function. Inspired by holographic duality, we investigated the entanglement properties of the classical configurations (snapshots) of the Potts model by introducing an Ansatz ensemble of random fractal images. By virtue of the central limit theorem, our Ansatz accurately reproduces the entanglement spectra of actual Potts snapshots without any fine tuning of parameters or artificial restrictions on ensemble choice. It provides a microscopic interpretation of the results of previous studies, which established a relation between the scaling behavior of snapshot entropy and the critical exponent. More importantly, it elucidates the role of ensemble disorder in restoring conformal invariance, an aspect previously ignored. Away from criticality, the breakdown of scale invariance leads to a renormalization of the parameter Σ in the random fractal Ansatz, whose variation can be used as an alternative determination of the critical exponent. We conclude by providing a recipe for the explicit construction of fractal unit cells consistent with a given scaling exponent.
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Spyrakis, Francesca; Benedetti, Paolo; Decherchi, Sergio; Rocchia, Walter; Cavalli, Andrea; Alcaro, Stefano; Ortuso, Francesco; Baroni, Massimo; Cruciani, Gabriele
2015-10-26
The importance of taking into account protein flexibility in drug design and virtual ligand screening (VS) has been widely debated in the literature, and molecular dynamics (MD) has been recognized as one of the most powerful tools for investigating intrinsic protein dynamics. Nevertheless, deciphering the amount of information hidden in MD simulations and recognizing a significant minimal set of states to be used in virtual screening experiments can be quite complicated. Here we present an integrated MD-FLAP (molecular dynamics-fingerprints for ligand and proteins) approach, comprising a pipeline of molecular dynamics, clustering and linear discriminant analysis, for enhancing accuracy and efficacy in VS campaigns. We first extracted a limited number of representative structures from tens of nanoseconds of MD trajectories by means of the k-medoids clustering algorithm as implemented in the BiKi Life Science Suite ( http://www.bikitech.com [accessed July 21, 2015]). Then, instead of applying arbitrary selection criteria, that is, RMSD, pharmacophore properties, or enrichment performances, we allowed the linear discriminant analysis algorithm implemented in FLAP ( http://www.moldiscovery.com [accessed July 21, 2015]) to automatically choose the best performing conformational states among medoids and X-ray structures. Retrospective virtual screenings confirmed that ensemble receptor protocols outperform single rigid receptor approaches, proved that computationally generated conformations comprise the same quantity/quality of information included in X-ray structures, and pointed to the MD-FLAP approach as a valuable tool for improving VS performances.
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Exploring Early Stages of the Chemical Unfolding of Proteins at the Proteome Scale
Candotti, Michela; Pérez, Alberto; Ferrer-Costa, Carles; Rueda, Manuel; Meyer, Tim; Gelpí, Josep Lluís; Orozco, Modesto
2013-01-01
After decades of using urea as denaturant, the kinetic role of this molecule in the unfolding process is still undefined: does urea actively induce protein unfolding or passively stabilize the unfolded state? By analyzing a set of 30 proteins (representative of all native folds) through extensive molecular dynamics simulations in denaturant (using a range of force-fields), we derived robust rules for urea unfolding that are valid at the proteome level. Irrespective of the protein fold, presence or absence of disulphide bridges, and secondary structure composition, urea concentrates in the first solvation shell of quasi-native proteins, but with a density lower than that of the fully unfolded state. The presence of urea does not alter the spontaneous vibration pattern of proteins. In fact, it reduces the magnitude of such vibrations, leading to a counterintuitive slow down of the atomic-motions that opposes unfolding. Urea stickiness and slow diffusion is, however, crucial for unfolding. Long residence urea molecules placed around the hydrophobic core are crucial to stabilize partially open structures generated by thermal fluctuations. Our simulations indicate that although urea does not favor the formation of partially open microstates, it is not a mere spectator of unfolding that simply displaces to the right of the folded←→unfolded equilibrium. On the contrary, urea actively favors unfolding: it selects and stabilizes partially unfolded microstates, slowly driving the protein conformational ensemble far from the native one and also from the conformations sampled during thermal unfolding. PMID:24348236
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Understanding the Structural Ensembles of a Highly Extended Disordered Protein†
Daughdrill, Gary W.; Kashtanov, Stepan; Stancik, Amber; Hill, Shannon E.; Helms, Gregory; Muschol, Martin
2013-01-01
Developing a comprehensive description of the equilibrium structural ensembles for intrinsically disordered proteins (IDPs) is essential to understanding their function. The p53 transactivation domain (p53TAD) is an IDP that interacts with multiple protein partners and contains numerous phosphorylation sites. Multiple techniques were used to investigate the equilibrium structural ensemble of p53TAD in its native and chemically unfolded states. The results from these experiments show that the native state of p53TAD has dimensions similar to a classical random coil while the chemically unfolded state is more extended. To investigate the molecular properties responsible for this behavior, a novel algorithm that generates diverse and unbiased structural ensembles of IDPs was developed. This algorithm was used to generate a large pool of plausible p53TAD structures that were reweighted to identify a subset of structures with the best fit to small angle X-ray scattering data. High weight structures in the native state ensemble show features that are localized to protein binding sites and regions with high proline content. The features localized to the protein binding sites are mostly eliminated in the chemically unfolded ensemble; while, the regions with high proline content remain relatively unaffected. Data from NMR experiments support these results, showing that residues from the protein binding sites experience larger environmental changes upon unfolding by urea than regions with high proline content. This behavior is consistent with the urea-induced exposure of nonpolar and aromatic side-chains in the protein binding sites that are partially excluded from solvent in the native state ensemble. PMID:21979461
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Zhang, Zhe; Schindler, Christina E. M.; Lange, Oliver F.; Zacharias, Martin
2015-01-01
The high-resolution refinement of docked protein-protein complexes can provide valuable structural and mechanistic insight into protein complex formation complementing experiment. Monte Carlo (MC) based approaches are frequently applied to sample putative interaction geometries of proteins including also possible conformational changes of the binding partners. In order to explore efficiency improvements of the MC sampling, several enhanced sampling techniques, including temperature or Hamiltonian replica exchange and well-tempered ensemble approaches, have been combined with the MC method and were evaluated on 20 protein complexes using unbound partner structures. The well-tempered ensemble method combined with a 2-dimensional temperature and Hamiltonian replica exchange scheme (WTE-H-REMC) was identified as the most efficient search strategy. Comparison with prolonged MC searches indicates that the WTE-H-REMC approach requires approximately 5 times fewer MC steps to identify near native docking geometries compared to conventional MC searches. PMID:26053419
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Ahmed, Aqeel; Rippmann, Friedrich; Barnickel, Gerhard; Gohlke, Holger
2011-07-25
A three-step approach for multiscale modeling of protein conformational changes is presented that incorporates information about preferred directions of protein motions into a geometric simulation algorithm. The first two steps are based on a rigid cluster normal-mode analysis (RCNMA). Low-frequency normal modes are used in the third step (NMSim) to extend the recently introduced idea of constrained geometric simulations of diffusive motions in proteins by biasing backbone motions of the protein, whereas side-chain motions are biased toward favorable rotamer states. The generated structures are iteratively corrected regarding steric clashes and stereochemical constraint violations. The approach allows performing three simulation types: unbiased exploration of conformational space; pathway generation by a targeted simulation; and radius of gyration-guided simulation. When applied to a data set of proteins with experimentally observed conformational changes, conformational variabilities are reproduced very well for 4 out of 5 proteins that show domain motions, with correlation coefficients r > 0.70 and as high as r = 0.92 in the case of adenylate kinase. In 7 out of 8 cases, NMSim simulations starting from unbound structures are able to sample conformations that are similar (root-mean-square deviation = 1.0-3.1 Å) to ligand bound conformations. An NMSim generated pathway of conformational change of adenylate kinase correctly describes the sequence of domain closing. The NMSim approach is a computationally efficient alternative to molecular dynamics simulations for conformational sampling of proteins. The generated conformations and pathways of conformational transitions can serve as input to docking approaches or as starting points for more sophisticated sampling techniques.
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Conformational Sampling and Binding Site Assessment of Suppression of Tumorigenicity 2 Ectodomain
Yang, Chao-Yie; Delproposto, James; Chinnaswamy, Krishnapriya; Brown, William Clay; Wang, Shuying; Stuckey, Jeanne A.; Wang, Xinquan
2016-01-01
Suppression of Tumorigenicity 2 (ST2), a member of the interleukin-1 receptor (IL-1R) family, activates type 2 immune responses to pathogens and tissue damage via binding to IL-33. Dysregulated responses contribute to asthma, graft-versus-host and autoinflammatory diseases and disorders. To study ST2 structure for inhibitor development, we performed the principal component (PC) analysis on the crystal structures of IL1-1R1, IL1-1R2, ST2 and the refined ST2 ectodomain (ST2ECD) models, constructed from previously reported small-angle X-ray scattering data. The analysis facilitates mapping of the ST2ECD conformations to PC subspace for characterizing structural changes. Extensive coverage of ST2ECD conformations was then obtained using the accelerated molecular dynamics simulations started with the IL-33 bound ST2ECD structure as instructed by their projected locations on the PC subspace. Cluster analysis of all conformations further determined representative conformations of ST2ECD ensemble in solution. Alignment of the representative conformations with the ST2/IL-33 structure showed that the D3 domain of ST2ECD (containing D1-D3 domains) in most conformations exhibits no clashes with IL-33 in the crystal structure. Our experimental binding data informed that the D1-D2 domain of ST2ECD contributes predominantly to the interaction between ST2ECD and IL-33 underscoring the importance of the D1-D2 domain in binding. Computational binding site assessment revealed one third of the total detected binding sites in the representative conformations may be suitable for binding to potent small molecules. Locations of these sites include the D1-D2 domain ST2ECD and modulation sites conformed to ST2ECD conformations. Our study provides structural models and analyses of ST2ECD that could be useful for inhibitor discovery. PMID:26735493
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Solvent-dependent gating motions of an extremophilic lipase from Pseudomonas aeruginosa
DOE Office of Scientific and Technical Information (OSTI.GOV)
Johnson, Quentin R.; Nellas, Ricky B.; Shen, Tongye
2012-07-25
Understanding how organic solvent-stable proteins can function in anhydrous and often complex solutions is essential for the study of the interaction of protein and molecular immiscible interfaces and the design of efficient industrial enzymes in nonaqueous solvents. Using an extremophilic lipase from Pseudomonas aeruginosa as an example, we investigated the conformational dynamics of an organic solvent-tolerant enzyme in complex solvent milieux. Four 100-ns molecular dynamics simulations of the lipase were performed in solvent systems: water, hexane, and two mixtures of hexane and water, 5% and 95% (w/w) hexane. Our results show a solvent-dependent structural change of the protein, especially inmore » the region that regulates the admission of the substrate. We observed that the lipase is much less flexible in hexane than in aqueous solution or at the immiscible interface. Quantified by the size of the accessible channel, the lipase in water has a closed-gate conformation and no access to the active site, while in the hexane-containing systems, the lipase is at various degrees of open-gate state, with the immiscible interface setup being in the widely open conformation ensembles. Furthermore, the composition of explicit solvents in the access channel showed a significant influence on the conformational dynamics of the protein. Interestingly, the slowest step (bottleneck) of the hexane-induced conformational switch seems to be correlated with the slow dehydration dynamics of the channel.« less
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High resolution approach to the native state ensemble kinetics and thermodynamics.
Wu, Sangwook; Zhuravlev, Pavel I; Papoian, Garegin A
2008-12-15
Many biologically interesting functions such as allosteric switching or protein-ligand binding are determined by the kinetics and mechanisms of transitions between various conformational substates of the native basin of globular proteins. To advance our understanding of these processes, we constructed a two-dimensional free energy surface (FES) of the native basin of a small globular protein, Trp-cage. The corresponding order parameters were defined using two native substructures of Trp-cage. These calculations were based on extensive explicit water all-atom molecular dynamics simulations. Using the obtained two-dimensional FES, we studied the transition kinetics between two Trp-cage conformations, finding that switching process shows a borderline behavior between diffusive and weakly-activated dynamics. The transition is well-characterized kinetically as a biexponential process. We also introduced a new one-dimensional reaction coordinate for the conformational transition, finding reasonable qualitative agreement with the two-dimensional kinetics results. We investigated the distribution of all the 38 native nuclear magnetic resonance structures on the obtained FES, analyzing interactions that stabilize specific low-energy conformations. Finally, we constructed a FES for the same system but with simple dielectric model of water instead of explicit water, finding that the results were surprisingly similar in a small region centered on the native conformations. The dissimilarities between the explicit and implicit model on the larger-scale point to the important role of water in mediating interactions between amino acid residues.
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Dynamic Energy Landscapes of Riboswitches Help Interpret Conformational Rearrangements and Function
Quarta, Giulio; Sin, Ken; Schlick, Tamar
2012-01-01
Riboswitches are RNAs that modulate gene expression by ligand-induced conformational changes. However, the way in which sequence dictates alternative folding pathways of gene regulation remains unclear. In this study, we compute energy landscapes, which describe the accessible secondary structures for a range of sequence lengths, to analyze the transcriptional process as a given sequence elongates to full length. In line with experimental evidence, we find that most riboswitch landscapes can be characterized by three broad classes as a function of sequence length in terms of the distribution and barrier type of the conformational clusters: low-barrier landscape with an ensemble of different conformations in equilibrium before encountering a substrate; barrier-free landscape in which a direct, dominant “downhill” pathway to the minimum free energy structure is apparent; and a barrier-dominated landscape with two isolated conformational states, each associated with a different biological function. Sharing concepts with the “new view” of protein folding energy landscapes, we term the three sequence ranges above as the sensing, downhill folding, and functional windows, respectively. We find that these energy landscape patterns are conserved in various riboswitch classes, though the order of the windows may vary. In fact, the order of the three windows suggests either kinetic or thermodynamic control of ligand binding. These findings help understand riboswitch structure/function relationships and open new avenues to riboswitch design. PMID:22359488
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Islam, Barira; Stadlbauer, Petr; Gil-Ley, Alejandro; Pérez-Hernández, Guillermo; Haider, Shozeb; Neidle, Stephen; Bussi, Giovanni; Banas, Pavel; Otyepka, Michal; Sponer, Jiri
2017-06-13
We have carried out a series of extended unbiased molecular dynamics (MD) simulations (up to 10 μs long, ∼162 μs in total) complemented by replica-exchange with the collective variable tempering (RECT) approach for several human telomeric DNA G-quadruplex (GQ) topologies with TTA propeller loops. We used different AMBER DNA force-field variants and also processed simulations by Markov State Model (MSM) analysis. The slow conformational transitions in the propeller loops took place on a scale of a few μs, emphasizing the need for long simulations in studies of GQ dynamics. The propeller loops sampled similar ensembles for all GQ topologies and for all force-field dihedral-potential variants. The outcomes of standard and RECT simulations were consistent and captured similar spectrum of loop conformations. However, the most common crystallographic loop conformation was very unstable with all force-field versions. Although the loss of canonical γ-trans state of the first propeller loop nucleotide could be related to the indispensable bsc0 α/γ dihedral potential, even supporting this particular dihedral by a bias was insufficient to populate the experimentally dominant loop conformation. In conclusion, while our simulations were capable of providing a reasonable albeit not converged sampling of the TTA propeller loop conformational space, the force-field description still remained far from satisfactory.
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2017-01-01
We have carried out a series of extended unbiased molecular dynamics (MD) simulations (up to 10 μs long, ∼162 μs in total) complemented by replica-exchange with the collective variable tempering (RECT) approach for several human telomeric DNA G-quadruplex (GQ) topologies with TTA propeller loops. We used different AMBER DNA force-field variants and also processed simulations by Markov State Model (MSM) analysis. The slow conformational transitions in the propeller loops took place on a scale of a few μs, emphasizing the need for long simulations in studies of GQ dynamics. The propeller loops sampled similar ensembles for all GQ topologies and for all force-field dihedral-potential variants. The outcomes of standard and RECT simulations were consistent and captured similar spectrum of loop conformations. However, the most common crystallographic loop conformation was very unstable with all force-field versions. Although the loss of canonical γ-trans state of the first propeller loop nucleotide could be related to the indispensable bsc0 α/γ dihedral potential, even supporting this particular dihedral by a bias was insufficient to populate the experimentally dominant loop conformation. In conclusion, while our simulations were capable of providing a reasonable albeit not converged sampling of the TTA propeller loop conformational space, the force-field description still remained far from satisfactory. PMID:28475322
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Krüger, Dennis M; Ahmed, Aqeel; Gohlke, Holger
2012-07-01
The NMSim web server implements a three-step approach for multiscale modeling of protein conformational changes. First, the protein structure is coarse-grained using the FIRST software. Second, a rigid cluster normal-mode analysis provides low-frequency normal modes. Third, these modes are used to extend the recently introduced idea of constrained geometric simulations by biasing backbone motions of the protein, whereas side chain motions are biased toward favorable rotamer states (NMSim). The generated structures are iteratively corrected regarding steric clashes and stereochemical constraint violations. The approach allows performing three simulation types: unbiased exploration of conformational space; pathway generation by a targeted simulation; and radius of gyration-guided simulation. On a data set of proteins with experimentally observed conformational changes, the NMSim approach has been shown to be a computationally efficient alternative to molecular dynamics simulations for conformational sampling of proteins. The generated conformations and pathways of conformational transitions can serve as input to docking approaches or more sophisticated sampling techniques. The web server output is a trajectory of generated conformations, Jmol representations of the coarse-graining and a subset of the trajectory and data plots of structural analyses. The NMSim webserver, accessible at http://www.nmsim.de, is free and open to all users with no login requirement.
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USDA-ARS?s Scientific Manuscript database
Ensembles of process-based crop models are now commonly used to simulate crop growth and development for climate scenarios of temperature and/or precipitation changes corresponding to different projections of atmospheric CO2 concentrations. This approach generates large datasets with thousands of de...
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Image of NCEP Logo WHERE AMERICA'S CLIMATE AND WEATHER SERVICES BEGIN Inventory of Data Products on Generated Products Image of horizontal rule Global Forecast System (GFS) GFS Ensemble Forecast System (GEFS of horizontal rule External Products Image of horizontal rule Canadian Ensemble Forecast System
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NASA Astrophysics Data System (ADS)
Zuehlsdorff, T. J.; Isborn, C. M.
2018-01-01
The correct treatment of vibronic effects is vital for the modeling of absorption spectra of many solvated dyes. Vibronic spectra for small dyes in solution can be easily computed within the Franck-Condon approximation using an implicit solvent model. However, implicit solvent models neglect specific solute-solvent interactions on the electronic excited state. On the other hand, a straightforward way to account for solute-solvent interactions and temperature-dependent broadening is by computing vertical excitation energies obtained from an ensemble of solute-solvent conformations. Ensemble approaches usually do not account for vibronic transitions and thus often produce spectral shapes in poor agreement with experiment. We address these shortcomings by combining zero-temperature vibronic fine structure with vertical excitations computed for a room-temperature ensemble of solute-solvent configurations. In this combined approach, all temperature-dependent broadening is treated classically through the sampling of configurations and quantum mechanical vibronic contributions are included as a zero-temperature correction to each vertical transition. In our calculation of the vertical excitations, significant regions of the solvent environment are treated fully quantum mechanically to account for solute-solvent polarization and charge-transfer. For the Franck-Condon calculations, a small amount of frozen explicit solvent is considered in order to capture solvent effects on the vibronic shape function. We test the proposed method by comparing calculated and experimental absorption spectra of Nile red and the green fluorescent protein chromophore in polar and non-polar solvents. For systems with strong solute-solvent interactions, the combined approach yields significant improvements over the ensemble approach. For systems with weak to moderate solute-solvent interactions, both the high-energy vibronic tail and the width of the spectra are in excellent agreement with experiments.
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Xue, Yi; Skrynnikov, Nikolai R
2014-01-01
Currently, the best existing molecular dynamics (MD) force fields cannot accurately reproduce the global free-energy minimum which realizes the experimental protein structure. As a result, long MD trajectories tend to drift away from the starting coordinates (e.g., crystallographic structures). To address this problem, we have devised a new simulation strategy aimed at protein crystals. An MD simulation of protein crystal is essentially an ensemble simulation involving multiple protein molecules in a crystal unit cell (or a block of unit cells). To ensure that average protein coordinates remain correct during the simulation, we introduced crystallography-based restraints into the MD protocol. Because these restraints are aimed at the ensemble-average structure, they have only minimal impact on conformational dynamics of the individual protein molecules. So long as the average structure remains reasonable, the proteins move in a native-like fashion as dictated by the original force field. To validate this approach, we have used the data from solid-state NMR spectroscopy, which is the orthogonal experimental technique uniquely sensitive to protein local dynamics. The new method has been tested on the well-established model protein, ubiquitin. The ensemble-restrained MD simulations produced lower crystallographic R factors than conventional simulations; they also led to more accurate predictions for crystallographic temperature factors, solid-state chemical shifts, and backbone order parameters. The predictions for 15N R1 relaxation rates are at least as accurate as those obtained from conventional simulations. Taken together, these results suggest that the presented trajectories may be among the most realistic protein MD simulations ever reported. In this context, the ensemble restraints based on high-resolution crystallographic data can be viewed as protein-specific empirical corrections to the standard force fields. PMID:24452989
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Sadiq, S Kashif; Wright, David W; Kenway, Owain A; Coveney, Peter V
2010-05-24
Accurate calculation of important thermodynamic properties, such as macromolecular binding free energies, is one of the principal goals of molecular dynamics simulations. However, single long simulation frequently produces incorrectly converged quantitative results due to inadequate sampling of conformational space in a feasible wall-clock time. Multiple short (ensemble) simulations have been shown to explore conformational space more effectively than single long simulations, but the two methods have not yet been thermodynamically compared. Here we show that, for end-state binding free energy determination methods, ensemble simulations exhibit significantly enhanced thermodynamic sampling over single long simulations and result in accurate and converged relative binding free energies that are reproducible to within 0.5 kcal/mol. Completely correct ranking is obtained for six HIV-1 protease variants bound to lopinavir with a correlation coefficient of 0.89 and a mean relative deviation from experiment of 0.9 kcal/mol. Multidrug resistance to lopinavir is enthalpically driven and increases through a decrease in the protein-ligand van der Waals interaction, principally due to the V82A/I84V mutation, and an increase in net electrostatic repulsion due to water-mediated disruption of protein-ligand interactions in the catalytic region. Furthermore, we correctly rank, to within 1 kcal/mol of experiment, the substantially increased chemical potency of lopinavir binding to the wild-type protease compared to saquinavir and show that lopinavir takes advantage of a decreased net electrostatic repulsion to confer enhanced binding. Our approach is dependent on the combined use of petascale computing resources and on an automated simulation workflow to attain the required level of sampling and turn around time to obtain the results, which can be as little as three days. This level of performance promotes integration of such methodology with clinical decision support systems for the optimization of patient-specific therapy.
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Wu, Xiongwu; Damjanovic, Ana; Brooks, Bernard R.
2013-01-01
This review provides a comprehensive description of the self-guided Langevin dynamics (SGLD) and the self-guided molecular dynamics (SGMD) methods and their applications. Example systems are included to provide guidance on optimal application of these methods in simulation studies. SGMD/SGLD has enhanced ability to overcome energy barriers and accelerate rare events to affordable time scales. It has been demonstrated that with moderate parameters, SGLD can routinely cross energy barriers of 20 kT at a rate that molecular dynamics (MD) or Langevin dynamics (LD) crosses 10 kT barriers. The core of these methods is the use of local averages of forces and momenta in a direct manner that can preserve the canonical ensemble. The use of such local averages results in methods where low frequency motion “borrows” energy from high frequency degrees of freedom when a barrier is approached and then returns that excess energy after a barrier is crossed. This self-guiding effect also results in an accelerated diffusion to enhance conformational sampling efficiency. The resulting ensemble with SGLD deviates in a small way from the canonical ensemble, and that deviation can be corrected with either an on-the-fly or a post processing reweighting procedure that provides an excellent canonical ensemble for systems with a limited number of accelerated degrees of freedom. Since reweighting procedures are generally not size extensive, a newer method, SGLDfp, uses local averages of both momenta and forces to preserve the ensemble without reweighting. The SGLDfp approach is size extensive and can be used to accelerate low frequency motion in large systems, or in systems with explicit solvent where solvent diffusion is also to be enhanced. Since these methods are direct and straightforward, they can be used in conjunction with many other sampling methods or free energy methods by simply replacing the integration of degrees of freedom that are normally sampled by MD or LD. PMID:23913991
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Yuan, C; Byeon, I J; Li, Y; Tsai, M D
1999-03-09
Bovine pancreatic phospholipase A2 (PLA2), a small (13.8 kDa) Ca2+-dependent lipolytic enzyme, is rich in functional and structural character. In an effort to examine its detailed structure-function relationship, we determined its solution structure by multidimensional nuclear magnetic resonance (NMR) spectroscopy at a functionally relevant pH. An ensemble of 20 structures generated has an average root-mean-square deviation (RMSD) of 0.62 +/- 0.08 A for backbone (N, Calpha, C) atoms and 0.98 +/- 0.09 A for all heavy atoms. The overall structure shows several notable differences from the crystal structure: the first three residues at the N-terminus, the calcium-binding loop (Y25-T36), and the surface loop (V63-N72) appear to be flexible; the alpha-helical conformation of helix B (E17-F22) is absent; helix D appears to be shorter (D59-V63 instead of D59-D66); and the hydrogen-bonding network is less defined. These differences were analyzed in relation to the function of PLA2. We then further examined the H-bonding network, because its functional role or even its existence in solution has been in dispute recently. Our results show that part of the H-bonding network (the portion away from N-terminus) clearly exists in solution, as evidenced by direct observation (at 11.1 ppm) of a strong H-bond between Y73 and D99 and an implicated interaction between D99 and H48. Analyses of a series of mutants indicated that the existence of the Y73.D99 H-bond correlates directly with the conformational stability of the mutant. Loss of this H-bond results in a loss of 2-3 kcal/mol in the conformational stability of PLA2. The unequivocal identification and demonstration of the structural importance of a specific hydrogen bond, and the magnitude of its contribution to conformational stability, are uncommon to the best of our knowledge. Our results also suggest that, while the D99.H48 catalytic diad is the key catalytic machinery of PLA2, it also helps to maintain conformational integrity.
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Bringing diffuse X-ray scattering into focus
Wall, Michael E.; Wolff, Alexander M.; Fraser, James S.
2018-02-16
X-ray crystallography is experiencing a renaissance as a method for probing the protein conformational ensemble. The inherent limitations of Bragg analysis, however, which only reveals the mean structure, have given way to a surge in interest in diffuse scattering, which is caused by structure variations. Diffuse scattering is present in all macromolecular crystallography experiments. Recent studies are shedding light on the origins of diffuse scattering in protein crystallography, and provide clues for leveraging diffuse scattering to model protein motions with atomic detail.
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Bringing diffuse X-ray scattering into focus
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wall, Michael E.; Wolff, Alexander M.; Fraser, James S.
X-ray crystallography is experiencing a renaissance as a method for probing the protein conformational ensemble. The inherent limitations of Bragg analysis, however, which only reveals the mean structure, have given way to a surge in interest in diffuse scattering, which is caused by structure variations. Diffuse scattering is present in all macromolecular crystallography experiments. Recent studies are shedding light on the origins of diffuse scattering in protein crystallography, and provide clues for leveraging diffuse scattering to model protein motions with atomic detail.
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Méndez-Luna, David; Bello, Martiniano; Correa-Basurto, José
2016-04-01
The G-protein coupled receptors (GPCRs) represent the largest superfamily of membrane proteins in charge to pass the cell signaling after binding with their cognate ligands to the cell interior. In breast cancer, a GPCR named GPER1 plays a key role in the process of growth and the proliferation of cancer cells. In a previous study, theoretical methods were applied to construct a model of GPER1, which later was submitted to molecular dynamics (MD) simulations to perform a docking calculation. Based on this preceding work, it is known that GPER1 is sensitive to structural differences in its binding site. However, due to the nature of that past study, conformational changes linked to the ligand binding were not observed. Therefore, in this study, in order to explore the conformational changes coupled to the agonist/antagonist binding, MD simulations of about 0.25μs were performed for the free and bound states, summarizing 0.75μs of MD simulation in total. For the bound states, one agonist (G-1) and antagonist (G-15) were chosen since is widely known that these two molecules cause an impact on GPER1 mobility. Based on the conformational ensemble generated through MD simulations, we found that despite G-1 and G-15 being stabilized by similar map of residues, the structural differences between both ligands impact the hydrogen bond pattern not only at the GPER1 binding site but also along the seven-helix bundle, causing significant differences in the conformational mobility along the extracellular and cytoplasmic domain, and to a lesser degree in the curvatures of helix 2, helix 3 and helix 7 between the free and bound states, which is in agreement with reported literature, and might be linked to microscopic characteristics of the activated-inactivated transition. Furthermore, binding free energy calculations using the MM/GBSA method for the bound states, followed by an alanine scanning analysis allowed us to identify some important residues for the complex stabilization. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Zwier, Matthew C.; Adelman, Joshua L.; Kaus, Joseph W.; Pratt, Adam J.; Wong, Kim F.; Rego, Nicholas B.; Suárez, Ernesto; Lettieri, Steven; Wang, David W.; Grabe, Michael; Zuckerman, Daniel M.; Chong, Lillian T.
2015-01-01
The weighted ensemble (WE) path sampling approach orchestrates an ensemble of parallel calculations with intermittent communication to enhance the sampling of rare events, such as molecular associations or conformational changes in proteins or peptides. Trajectories are replicated and pruned in a way that focuses computational effort on under-explored regions of configuration space while maintaining rigorous kinetics. To enable the simulation of rare events at any scale (e.g. atomistic, cellular), we have developed an open-source, interoperable, and highly scalable software package for the execution and analysis of WE simulations: WESTPA (The Weighted Ensemble Simulation Toolkit with Parallelization and Analysis). WESTPA scales to thousands of CPU cores and includes a suite of analysis tools that have been implemented in a massively parallel fashion. The software has been designed to interface conveniently with any dynamics engine and has already been used with a variety of molecular dynamics (e.g. GROMACS, NAMD, OpenMM, AMBER) and cell-modeling packages (e.g. BioNetGen, MCell). WESTPA has been in production use for over a year, and its utility has been demonstrated for a broad set of problems, ranging from atomically detailed host-guest associations to non-spatial chemical kinetics of cellular signaling networks. The following describes the design and features of WESTPA, including the facilities it provides for running WE simulations, storing and analyzing WE simulation data, as well as examples of input and output. PMID:26392815