A Simple "Boxed Molecular Kinetics" Approach To Accelerate Rare Events in the Stochastic Kinetic Master Equation.

PubMed

Shannon, Robin; Glowacki, David R

2018-02-15

The chemical master equation is a powerful theoretical tool for analyzing the kinetics of complex multiwell potential energy surfaces in a wide range of different domains of chemical kinetics spanning combustion, atmospheric chemistry, gas-surface chemistry, solution phase chemistry, and biochemistry. There are two well-established methodologies for solving the chemical master equation: a stochastic "kinetic Monte Carlo" approach and a matrix-based approach. In principle, the results yielded by both approaches are identical; the decision of which approach is better suited to a particular study depends on the details of the specific system under investigation. In this Article, we present a rigorous method for accelerating stochastic approaches by several orders of magnitude, along with a method for unbiasing the accelerated results to recover the "true" value. The approach we take in this paper is inspired by the so-called "boxed molecular dynamics" (BXD) method, which has previously only been applied to accelerate rare events in molecular dynamics simulations. Here we extend BXD to design a simple algorithmic strategy for accelerating rare events in stochastic kinetic simulations. Tests on a number of systems show that the results obtained using the BXD rare event strategy are in good agreement with unbiased results. To carry out these tests, we have implemented a kinetic Monte Carlo approach in MESMER, which is a cross-platform, open-source, and freely available master equation solver.

High-resolution reversible folding of hyperstable RNA tetraloops using molecular dynamics simulations

PubMed Central

Chen, Alan A.; García, Angel E.

2013-01-01

We report the de novo folding of three hyperstable RNA tetraloops to 1–3 Å rmsd from their experimentally determined structures using molecular dynamics simulations initialized in the unfolded state. RNA tetraloops with loop sequences UUCG, GCAA, or CUUG are hyperstable because of the formation of noncanonical loop-stabilizing interactions, and they are all faithfully reproduced to angstrom-level accuracy in replica exchange molecular dynamics simulations, including explicit solvent and ion molecules. This accuracy is accomplished using unique RNA parameters, in which biases that favor rigid, highly stacked conformations are corrected to accurately capture the inherent flexibility of ssRNA loops, accurate base stacking energetics, and purine syn-anti interconversions. In a departure from traditional quantum chemistrycentric approaches to force field optimization, our parameters are calibrated directly from thermodynamic and kinetic measurements of intra- and internucleotide structural transitions. The ability to recapitulate the signature noncanonical interactions of the three most abundant hyperstable stem loop motifs represents a significant milestone to the accurate prediction of RNA tertiary structure using unbiased all-atom molecular dynamics simulations. PMID:24043821

Insight into the Mechanism of Hydrolysis of Meropenem by OXA-23 Serine-β-lactamase Gained by Quantum Mechanics/Molecular Mechanics Calculations.

PubMed

Sgrignani, Jacopo; Grazioso, Giovanni; De Amici, Marco

2016-09-13

The fast and constant development of drug resistant bacteria represents a serious medical emergency. To overcome this problem, the development of drugs with new structures and modes of action is urgently needed. In this work, we investigated, at the atomistic level, the mechanisms of hydrolysis of Meropenem by OXA-23, a class D β-lactamase, combining unbiased classical molecular dynamics and umbrella sampling simulations with classical force field-based and quantum mechanics/molecular mechanics potentials. Our calculations provide a detailed structural and dynamic picture of the molecular steps leading to the formation of the Meropenem-OXA-23 covalent adduct, the subsequent hydrolysis, and the final release of the inactive antibiotic. In this mechanistic framework, the predicted activation energy is in good agreement with experimental kinetic measurements, validating the expected reaction path.

New Approach for Investigating Reaction Dynamics and Rates with Ab Initio Calculations.

PubMed

Fleming, Kelly L; Tiwary, Pratyush; Pfaendtner, Jim

2016-01-21

Herein, we demonstrate a convenient approach to systematically investigate chemical reaction dynamics using the metadynamics (MetaD) family of enhanced sampling methods. Using a symmetric SN2 reaction as a model system, we applied infrequent metadynamics, a theoretical framework based on acceleration factors, to quantitatively estimate the rate of reaction from biased and unbiased simulations. A systematic study of the algorithm and its application to chemical reactions was performed by sampling over 5000 independent reaction events. Additionally, we quantitatively reweighed exhaustive free-energy calculations to obtain the reaction potential-energy surface and showed that infrequent metadynamics works to effectively determine Arrhenius-like activation energies. Exact agreement with unbiased high-temperature kinetics is also shown. The feasibility of using the approach on actual ab initio molecular dynamics calculations is then presented by using Car-Parrinello MD+MetaD to sample the same reaction using only 10-20 calculations of the rare event. Owing to the ease of use and comparatively low-cost of computation, the approach has extensive potential applications for catalysis, combustion, pyrolysis, and enzymology.

Solutions of burnt-bridge models for molecular motor transport.

PubMed

Morozov, Alexander Yu; Pronina, Ekaterina; Kolomeisky, Anatoly B; Artyomov, Maxim N

2007-03-01

Transport of molecular motors, stimulated by interactions with specific links between consecutive binding sites (called "bridges"), is investigated theoretically by analyzing discrete-state stochastic "burnt-bridge" models. When an unbiased diffusing particle crosses the bridge, the link can be destroyed ("burned") with a probability p , creating a biased directed motion for the particle. It is shown that for probability of burning p=1 the system can be mapped into a one-dimensional single-particle hopping model along the periodic infinite lattice that allows one to calculate exactly all dynamic properties. For the general case of p<1 a theoretical method is developed and dynamic properties are computed explicitly. Discrete-time and continuous-time dynamics for periodic distribution of bridges and different burning dynamics are analyzed and compared. Analytical predictions are supported by extensive Monte Carlo computer simulations. Theoretical results are applied for analysis of the experiments on collagenase motor proteins.

Exact Solutions of Burnt-Bridge Models for Molecular Motor Transport

NASA Astrophysics Data System (ADS)

Morozov, Alexander; Pronina, Ekaterina; Kolomeisky, Anatoly; Artyomov, Maxim

2007-03-01

Transport of molecular motors, stimulated by interactions with specific links between consecutive binding sites (called ``bridges''), is investigated theoretically by analyzing discrete-state stochastic ``burnt-bridge'' models. When an unbiased diffusing particle crosses the bridge, the link can be destroyed (``burned'') with a probability p, creating a biased directed motion for the particle. It is shown that for probability of burning p=1 the system can be mapped into one-dimensional single-particle hopping model along the periodic infinite lattice that allows one to calculate exactly all dynamic properties. For general case of p<1 a new theoretical method is developed, and dynamic properties are computed explicitly. Discrete-time and continuous-time dynamics, periodic and random distribution of bridges and different burning dynamics are analyzed and compared. Theoretical predictions are supported by extensive Monte Carlo computer simulations. Theoretical results are applied for analysis of the experiments on collagenase motor proteins.

Solutions of burnt-bridge models for molecular motor transport

NASA Astrophysics Data System (ADS)

Morozov, Alexander Yu.; Pronina, Ekaterina; Kolomeisky, Anatoly B.; Artyomov, Maxim N.

2007-03-01

Transport of molecular motors, stimulated by interactions with specific links between consecutive binding sites (called “bridges”), is investigated theoretically by analyzing discrete-state stochastic “burnt-bridge” models. When an unbiased diffusing particle crosses the bridge, the link can be destroyed (“burned”) with a probability p , creating a biased directed motion for the particle. It is shown that for probability of burning p=1 the system can be mapped into a one-dimensional single-particle hopping model along the periodic infinite lattice that allows one to calculate exactly all dynamic properties. For the general case of p<1 a theoretical method is developed and dynamic properties are computed explicitly. Discrete-time and continuous-time dynamics for periodic distribution of bridges and different burning dynamics are analyzed and compared. Analytical predictions are supported by extensive Monte Carlo computer simulations. Theoretical results are applied for analysis of the experiments on collagenase motor proteins.

Potential-based dynamical reweighting for Markov state models of protein dynamics.

PubMed

Weber, Jeffrey K; Pande, Vijay S

2015-06-09

As simulators attempt to replicate the dynamics of large cellular components in silico, problems related to sampling slow, glassy degrees of freedom in molecular systems will be amplified manyfold. It is tempting to augment simulation techniques with external biases to overcome such barriers with ease; biased simulations, however, offer little utility unless equilibrium properties of interest (both kinetic and thermodynamic) can be recovered from the data generated. In this Article, we present a general scheme that harnesses the power of Markov state models (MSMs) to extract equilibrium kinetic properties from molecular dynamics trajectories collected on biased potential energy surfaces. We first validate our reweighting protocol on a simple two-well potential, and we proceed to test our method on potential-biased simulations of the Trp-cage miniprotein. In both cases, we find that equilibrium populations, time scales, and dynamical processes are reliably reproduced as compared to gold standard, unbiased data sets. We go on to discuss the limitations of our dynamical reweighting approach, and we suggest auspicious target systems for further application.

Free energies from dynamic weighted histogram analysis using unbiased Markov state model.

PubMed

Rosta, Edina; Hummer, Gerhard

2015-01-13

The weighted histogram analysis method (WHAM) is widely used to obtain accurate free energies from biased molecular simulations. However, WHAM free energies can exhibit significant errors if some of the biasing windows are not fully equilibrated. To account for the lack of full equilibration, we develop the dynamic histogram analysis method (DHAM). DHAM uses a global Markov state model to obtain the free energy along the reaction coordinate. A maximum likelihood estimate of the Markov transition matrix is constructed by joint unbiasing of the transition counts from multiple umbrella-sampling simulations along discretized reaction coordinates. The free energy profile is the stationary distribution of the resulting Markov matrix. For this matrix, we derive an explicit approximation that does not require the usual iterative solution of WHAM. We apply DHAM to model systems, a chemical reaction in water treated using quantum-mechanics/molecular-mechanics (QM/MM) simulations, and the Na(+) ion passage through the membrane-embedded ion channel GLIC. We find that DHAM gives accurate free energies even in cases where WHAM fails. In addition, DHAM provides kinetic information, which we here use to assess the extent of convergence in each of the simulation windows. DHAM may also prove useful in the construction of Markov state models from biased simulations in phase-space regions with otherwise low population.

Convergence of Free Energy Profile of Coumarin in Lipid Bilayer

PubMed Central

2012-01-01

Atomistic molecular dynamics (MD) simulations of druglike molecules embedded in lipid bilayers are of considerable interest as models for drug penetration and positioning in biological membranes. Here we analyze partitioning of coumarin in dioleoylphosphatidylcholine (DOPC) bilayer, based on both multiple, unbiased 3 μs MD simulations (total length) and free energy profiles along the bilayer normal calculated by biased MD simulations (∼7 μs in total). The convergences in time of free energy profiles calculated by both umbrella sampling and z-constraint techniques are thoroughly analyzed. Two sets of starting structures are also considered, one from unbiased MD simulation and the other from “pulling” coumarin along the bilayer normal. The structures obtained by pulling simulation contain water defects on the lipid bilayer surface, while those acquired from unbiased simulation have no membrane defects. The free energy profiles converge more rapidly when starting frames from unbiased simulations are used. In addition, z-constraint simulation leads to more rapid convergence than umbrella sampling, due to quicker relaxation of membrane defects. Furthermore, we show that the choice of RESP, PRODRG, or Mulliken charges considerably affects the resulting free energy profile of our model drug along the bilayer normal. We recommend using z-constraint biased MD simulations based on starting geometries acquired from unbiased MD simulations for efficient calculation of convergent free energy profiles of druglike molecules along bilayer normals. The calculation of free energy profile should start with an unbiased simulation, though the polar molecules might need a slow pulling afterward. Results obtained with the recommended simulation protocol agree well with available experimental data for two coumarin derivatives. PMID:22545027

Convergence of Free Energy Profile of Coumarin in Lipid Bilayer.

PubMed

Paloncýová, Markéta; Berka, Karel; Otyepka, Michal

2012-04-10

Atomistic molecular dynamics (MD) simulations of druglike molecules embedded in lipid bilayers are of considerable interest as models for drug penetration and positioning in biological membranes. Here we analyze partitioning of coumarin in dioleoylphosphatidylcholine (DOPC) bilayer, based on both multiple, unbiased 3 μs MD simulations (total length) and free energy profiles along the bilayer normal calculated by biased MD simulations (∼7 μs in total). The convergences in time of free energy profiles calculated by both umbrella sampling and z-constraint techniques are thoroughly analyzed. Two sets of starting structures are also considered, one from unbiased MD simulation and the other from "pulling" coumarin along the bilayer normal. The structures obtained by pulling simulation contain water defects on the lipid bilayer surface, while those acquired from unbiased simulation have no membrane defects. The free energy profiles converge more rapidly when starting frames from unbiased simulations are used. In addition, z-constraint simulation leads to more rapid convergence than umbrella sampling, due to quicker relaxation of membrane defects. Furthermore, we show that the choice of RESP, PRODRG, or Mulliken charges considerably affects the resulting free energy profile of our model drug along the bilayer normal. We recommend using z-constraint biased MD simulations based on starting geometries acquired from unbiased MD simulations for efficient calculation of convergent free energy profiles of druglike molecules along bilayer normals. The calculation of free energy profile should start with an unbiased simulation, though the polar molecules might need a slow pulling afterward. Results obtained with the recommended simulation protocol agree well with available experimental data for two coumarin derivatives.

Free-energy landscape of a hyperstable RNA tetraloop

PubMed Central

Miner, Jacob C.; Chen, Alan A.; García, Angel E.

2016-01-01

We report the characterization of the energy landscape and the folding/unfolding thermodynamics of a hyperstable RNA tetraloop obtained through high-performance molecular dynamics simulations at microsecond timescales. Sampling of the configurational landscape is conducted using temperature replica exchange molecular dynamics over three isochores at high, ambient, and negative pressures to determine the thermodynamic stability and the free-energy landscape of the tetraloop. The simulations reveal reversible folding/unfolding transitions of the tetraloop into the canonical A-RNA conformation and the presence of two alternative configurations, including a left-handed Z-RNA conformation and a compact purine Triplet. Increasing hydrostatic pressure shows a stabilizing effect on the A-RNA conformation and a destabilization of the left-handed Z-RNA. Our results provide a comprehensive description of the folded free-energy landscape of a hyperstable RNA tetraloop and highlight the significant advances of all-atom molecular dynamics in describing the unbiased folding of a simple RNA secondary structure motif. PMID:27233937

Molecular dynamics analysis of stabilities of the telomeric Watson-Crick duplex and the associated i-motif as a function of pH and temperature.

PubMed

Panczyk, Tomasz; Wolski, Pawel

2018-06-01

This work deals with a molecular dynamics analysis of the protonated and deprotonated states of the natural sequence d[(CCCTAA) 3 CCCT] of the telomeric DNA forming the intercalated i-motif or paired with the sequence d[(CCCTAA) 3 CCCT] and forming the Watson-Crick (WC) duplex. By utilizing the amber force field for nucleic acids we built the i-motif and the WC duplex either with native cytosines or using their protonated forms. We studied, by applying molecular dynamics simulations, the role of hydrogen bonds between cytosines or in cytosine-guanine pairs in the stabilization of both structures in the physiological fluid. We found that hydrogen bonds exist in the case of protonated i-motif and in the standard form of the WC duplex. They, however, vanish in the case of the deprotonated i-motif and protonated form of the WC duplex. By determining potentials of mean force in the enforced unwrapping of these structures we found that the protonated i-motif is thermodynamically the most stable. Its deprotonation leads to spontaneous and observed directly in the unbiased calculations unfolding of the i-motif to the hairpin structure at normal temperature. The WC duplex is stable in its standard form and its slight destabilization is observed at the acidic pH. However, the protonated WC duplex unwraps very slowly at 310 K and its decomposition was not observed in the unbiased calculations. At higher temperatures (ca. 400 K or more) the WC duplex unwraps spontaneously. Copyright © 2018. Published by Elsevier B.V.

The biological function of an insect antifreeze protein simulated by molecular dynamics

PubMed Central

Kuiper, Michael J; Morton, Craig J; Abraham, Sneha E; Gray-Weale, Angus

2015-01-01

Antifreeze proteins (AFPs) protect certain cold-adapted organisms from freezing to death by selectively adsorbing to internal ice crystals and inhibiting ice propagation. The molecular details of AFP adsorption-inhibition is uncertain but is proposed to involve the Gibbs–Thomson effect. Here we show by using unbiased molecular dynamics simulations a protein structure-function mechanism for the spruce budworm Choristoneura fumiferana AFP, including stereo-specific binding and consequential melting and freezing inhibition. The protein binds indirectly to the prism ice face through a linear array of ordered water molecules that are structurally distinct from the ice. Mutation of the ice binding surface disrupts water-ordering and abolishes activity. The adsorption is virtually irreversible, and we confirm the ice growth inhibition is consistent with the Gibbs–Thomson law. DOI: http://dx.doi.org/10.7554/eLife.05142.001 PMID:25951514

METAGUI 3: A graphical user interface for choosing the collective variables in molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Giorgino, Toni; Laio, Alessandro; Rodriguez, Alex

2017-08-01

Molecular dynamics (MD) simulations allow the exploration of the phase space of biopolymers through the integration of equations of motion of their constituent atoms. The analysis of MD trajectories often relies on the choice of collective variables (CVs) along which the dynamics of the system is projected. We developed a graphical user interface (GUI) for facilitating the interactive choice of the appropriate CVs. The GUI allows: defining interactively new CVs; partitioning the configurations into microstates characterized by similar values of the CVs; calculating the free energies of the microstates for both unbiased and biased (metadynamics) simulations; clustering the microstates in kinetic basins; visualizing the free energy landscape as a function of a subset of the CVs used for the analysis. A simple mouse click allows one to quickly inspect structures corresponding to specific points in the landscape.

Conformational Transition Pathways of Epidermal Growth Factor Receptor Kinase Domain from Multiple Molecular Dynamics Simulations and Bayesian Clustering.

PubMed

Li, Yan; Li, Xiang; Ma, Weiya; Dong, Zigang

2014-08-12

The epidermal growth factor receptor (EGFR) is aberrantly activated in various cancer cells and an important target for cancer treatment. Deep understanding of EGFR conformational changes between the active and inactive states is of pharmaceutical interest. Here we present a strategy combining multiply targeted molecular dynamics simulations, unbiased molecular dynamics simulations, and Bayesian clustering to investigate transition pathways during the activation/inactivation process of EGFR kinase domain. Two distinct pathways between the active and inactive forms are designed, explored, and compared. Based on Bayesian clustering and rough two-dimensional free energy surfaces, the energy-favorable pathway is recognized, though DFG-flip happens in both pathways. In addition, another pathway with different intermediate states appears in our simulations. Comparison of distinct pathways also indicates that disruption of the Lys745-Glu762 interaction is critically important in DFG-flip while movement of the A-loop significantly facilitates the conformational change. Our simulations yield new insights into EGFR conformational transitions. Moreover, our results verify that this approach is valid and efficient in sampling of protein conformational changes and comparison of distinct pathways.

SIRAH: a structurally unbiased coarse-grained force field for proteins with aqueous solvation and long-range electrostatics.

PubMed

Darré, Leonardo; Machado, Matías Rodrigo; Brandner, Astrid Febe; González, Humberto Carlos; Ferreira, Sebastián; Pantano, Sergio

2015-02-10

Modeling of macromolecular structures and interactions represents an important challenge for computational biology, involving different time and length scales. However, this task can be facilitated through the use of coarse-grained (CG) models, which reduce the number of degrees of freedom and allow efficient exploration of complex conformational spaces. This article presents a new CG protein model named SIRAH, developed to work with explicit solvent and to capture sequence, temperature, and ionic strength effects in a topologically unbiased manner. SIRAH is implemented in GROMACS, and interactions are calculated using a standard pairwise Hamiltonian for classical molecular dynamics simulations. We present a set of simulations that test the capability of SIRAH to produce a qualitatively correct solvation on different amino acids, hydrophilic/hydrophobic interactions, and long-range electrostatic recognition leading to spontaneous association of unstructured peptides and stable structures of single polypeptides and protein-protein complexes.

Molecular Dynamics Simulations of G Protein-Coupled Receptors.

PubMed

Bruno, Agostino; Costantino, Gabriele

2012-04-01

G protein-coupled receptors (GPCRs) constitute the largest family of membrane-bound receptors with more than 800 members encoded by 351 genes in humans. It has been estimated that more than 50 % of clinically available drugs act on GPCRs, with an amount of 400, 50 and 25 druggable proteins for the class A, B and C, respectively. Furthermore, Class A GPCRs with approximately 25 % of marketed small drugs represent the most attractive pharmaceutical class. The recent availability of high-resolution 3-dimensional structures of some GPCRs supports the notion that GPCRs are dynamically versatile, and their functions can be modulated by several factors. In this scenario, molecular dynamics (MD) simulations techniques appear to be crucial when studying GPCR flexibility associated to functioning and ligand recognition. A general overview of biased and unbiased MD techniques is here presented with special emphasis on the recent results obtained in the GPCRs field. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

How to Compute Electron Ionization Mass Spectra from First Principles.

PubMed

Bauer, Christoph Alexander; Grimme, Stefan

2016-06-02

The prediction of electron ionization (EI) mass spectra (MS) from first principles has been a major challenge for quantum chemistry (QC). The unimolecular reaction space grows rapidly with increasing molecular size. On the one hand, statistical models like Eyring's quasi-equilibrium theory and Rice-Ramsperger-Kassel-Marcus theory have provided valuable insight, and some predictions and quantitative results can be obtained from such calculations. On the other hand, molecular dynamics-based methods are able to explore automatically the energetically available regions of phase space and thus yield reaction paths in an unbiased way. We describe in this feature article the status of both methodologies in relation to mass spectrometry for small to medium sized molecules. We further present results obtained with the QCEIMS program developed in our laboratory. Our method, which incorporates stochastic and dynamic elements, has been a significant step toward the reliable routine calculation of EI mass spectra.

Role of Molecular Dynamics and Related Methods in Drug Discovery.

PubMed

De Vivo, Marco; Masetti, Matteo; Bottegoni, Giovanni; Cavalli, Andrea

2016-05-12

Molecular dynamics (MD) and related methods are close to becoming routine computational tools for drug discovery. Their main advantage is in explicitly treating structural flexibility and entropic effects. This allows a more accurate estimate of the thermodynamics and kinetics associated with drug-target recognition and binding, as better algorithms and hardware architectures increase their use. Here, we review the theoretical background of MD and enhanced sampling methods, focusing on free-energy perturbation, metadynamics, steered MD, and other methods most consistently used to study drug-target binding. We discuss unbiased MD simulations that nowadays allow the observation of unsupervised ligand-target binding, assessing how these approaches help optimizing target affinity and drug residence time toward improved drug efficacy. Further issues discussed include allosteric modulation and the role of water molecules in ligand binding and optimization. We conclude by calling for more prospective studies to attest to these methods' utility in discovering novel drug candidates.

Structural Properties of Human IAPP Dimer in Membrane Environment Studied by All-Atom Molecular Dynamics Simulations.

PubMed

Liu, Na; Duan, Mojie; Yang, Minghui

2017-08-11

The aggregation of human islet amyloid polypeptide (hIAPP) can damage the membrane of the β-cells in the pancreatic islets and induce type 2 diabetes (T2D). Growing evidences indicated that the major toxic species are small oligomers of IAPP. Due to the fast aggregation nature, it is hard to characterize the structures of IAPP oligomers by experiments, especially in the complex membrane environment. On the other side, molecular dynamics simulation can provide atomic details of the structure and dynamics of the aggregation of IAPP. In this study, all-atom bias-exchange metadynamics (BE-Meta) and unbiased molecular dynamics simulations were employed to study the structural properties of IAPP dimer in the membranes environments. A number of intermediates, including α-helical states, β-sheet states, and fully disordered states, are identified. The formation of N-terminal β-sheet structure is prior to the C-terminal β-sheet structure towards the final fibril-like structures. The α-helical intermediates have lower propensity in the dimeric hIAPP and are off-pathway intermediates. The simulations also demonstrate that the β-sheet intermediates induce more perturbation on the membrane than the α-helical and disordered states and thus pose higher disruption ability.

Conformational free energies of methyl-α-L-iduronic and methyl-β-D-glucuronic acids in water

NASA Astrophysics Data System (ADS)

Babin, Volodymyr; Sagui, Celeste

2010-03-01

We present a simulation protocol that allows for efficient sampling of the degrees of freedom of a solute in explicit solvent. The protocol involves using a nonequilibrium umbrella sampling method, in this case, the recently developed adaptively biased molecular dynamics method, to compute an approximate free energy for the slow modes of the solute in explicit solvent. This approximate free energy is then used to set up a Hamiltonian replica exchange scheme that samples both from biased and unbiased distributions. The final accurate free energy is recovered via the weighted histogram analysis technique applied to all the replicas, and equilibrium properties of the solute are computed from the unbiased trajectory. We illustrate the approach by applying it to the study of the puckering landscapes of the methyl glycosides of α-L-iduronic acid and its C5 epimer β-D-glucuronic acid in water. Big savings in computational resources are gained in comparison to the standard parallel tempering method.

Conformational free energies of methyl-alpha-L-iduronic and methyl-beta-D-glucuronic acids in water.

PubMed

Babin, Volodymyr; Sagui, Celeste

2010-03-14

We present a simulation protocol that allows for efficient sampling of the degrees of freedom of a solute in explicit solvent. The protocol involves using a nonequilibrium umbrella sampling method, in this case, the recently developed adaptively biased molecular dynamics method, to compute an approximate free energy for the slow modes of the solute in explicit solvent. This approximate free energy is then used to set up a Hamiltonian replica exchange scheme that samples both from biased and unbiased distributions. The final accurate free energy is recovered via the weighted histogram analysis technique applied to all the replicas, and equilibrium properties of the solute are computed from the unbiased trajectory. We illustrate the approach by applying it to the study of the puckering landscapes of the methyl glycosides of alpha-L-iduronic acid and its C5 epimer beta-D-glucuronic acid in water. Big savings in computational resources are gained in comparison to the standard parallel tempering method.

Large deviations in the presence of cooperativity and slow dynamics

NASA Astrophysics Data System (ADS)

Whitelam, Stephen

2018-06-01

We study simple models of intermittency, involving switching between two states, within the dynamical large-deviation formalism. Singularities appear in the formalism when switching is cooperative or when its basic time scale diverges. In the first case the unbiased trajectory distribution undergoes a symmetry breaking, leading to a change in shape of the large-deviation rate function for a particular dynamical observable. In the second case the symmetry of the unbiased trajectory distribution remains unbroken. Comparison of these models suggests that singularities of the dynamical large-deviation formalism can signal the dynamical equivalent of an equilibrium phase transition but do not necessarily do so.

Equilibrium thermodynamics and folding kinetics of a short, fast-folding, beta-hairpin.

PubMed

Jimenez-Cruz, Camilo A; Garcia, Angel E

2014-04-14

Equilibrium thermodynamics of a short beta-hairpin are studied using unbiased all-atom replica exchange molecular dynamics simulations in explicit solvent. An exploratory analysis of the free energy landscape of the system is provided in terms of various structural characteristics, for both the folded and unfolded ensembles. We find that the favorable interactions between the ends introduced by the tryptophan cap, along with the flexibility of the turn region, explain the remarkable stability of the folded state. Charging of the N termini results in effective roughening of the free energy landscape and stabilization of non-native contacts. Folding-unfolding dynamics are further discussed using a set of 2413 independent molecular dynamics simulations, 2 ns to 20 ns long, at the melting temperature of the beta-hairpin. A novel method for the construction of Markov models consisting of an iterative refinement of the discretization in reduced dimensionality is presented and used to generate a detailed kinetic network of the system. The hairpin is found to fold heterogeneously on sub-microsecond timescales, with the relative position of the tryptophan side chains driving the selection of the specific pathway.

Interplay of stereoelectronic and enviromental effects in tuning the structural and magnetic properties of a prototypical spin probe: further insights from a first principle dynamical approach.

PubMed

Pavone, Michele; Cimino, Paola; De Angelis, Filippo; Barone, Vincenzo

2006-04-05

The nitrogen isotropic hyperfine coupling constant (hcc) and the g tensor of a prototypical spin probe (di-tert-butyl nitroxide, DTBN) in aqueous solution have been investigated by means of an integrated computational approach including Car-Parrinello molecular dynamics and quantum mechanical calculations involving a discrete-continuum embedding. The quantitative agreement between computed and experimental parameters fully validates our integrated approach. Decoupling of the structural, dynamical, and environmental contributions acting onto the spectral observables allows an unbiased judgment of the role played by different effects in determining the overall experimental observables and highlights the importance of finite-temperature vibrational averaging. Together with their intrinsic interest, our results pave the route toward more reliable interpretations of EPR parameters of complex systems of biological and technological relevance.

Energetic and flexibility properties captured by long molecular dynamics simulations of a membrane-embedded pMHCII-TCR complex.

PubMed

Bello, Martiniano; Correa-Basurto, José

2016-04-01

Although crystallographic data have provided important molecular insight into the interactions in the pMHC-TCR complex, the inherent features of this structural approach cause it to only provide a static picture of the interactions. While unbiased molecular dynamics simulations (UMDSs) have provided important information about the dynamic structural behavior of the pMHC-TCR complex, most of them have modeled the pMHC-TCR complex as soluble, when in physiological conditions, this complex is membrane bound; therefore, following this latter UMDS protocol might hamper important dynamic results. In this contribution, we performed three independent 300 ns-long UMDSs of the pMHCII-TCR complex anchored in two opposing membranes to explore the structural and energetic properties of the recognition of pMHCII by the TCR. The conformational ensemble generated through UMDSs was subjected to clustering and Cartesian principal component analyses (cPCA) to explore the dynamical behavior of the pMHCII-TCR association. Furthermore, based on the conformational population sampled through UMDSs, the effective binding free energy, per-residue free energy decomposition, and alanine scanning mutations were explored for the native pMHCII-TCR complex, as well as for 12 mutations (p1-p12MHCII-TCR) introduced in the native peptide. Clustering analyses and cPCA provide insight into the rocking motion of the TCR onto pMHCII, together with the presence of new electrostatic interactions not observed through crystallographic methods. Energetic results provide evidence of the main contributors to the pMHC-TCR complex formation as well as the key residues involved in this molecular recognition process.

Locating binding poses in protein-ligand systems using reconnaissance metadynamics

PubMed Central

Söderhjelm, Pär; Tribello, Gareth A.; Parrinello, Michele

2012-01-01

A molecular dynamics-based protocol is proposed for finding and scoring protein-ligand binding poses. This protocol uses the recently developed reconnaissance metadynamics method, which employs a self-learning algorithm to construct a bias that pushes the system away from the kinetic traps where it would otherwise remain. The exploration of phase space with this algorithm is shown to be roughly six to eight times faster than unbiased molecular dynamics and is only limited by the time taken to diffuse about the surface of the protein. We apply this method to the well-studied trypsin–benzamidine system and show that we are able to refind all the poses obtained from a reference EADock blind docking calculation. These poses can be scored based on the length of time the system remains trapped in the pose. Alternatively, one can perform dimensionality reduction on the output trajectory and obtain a map of phase space that can be used in more expensive free-energy calculations. PMID:22440749

Variationally Optimized Free-Energy Flooding for Rate Calculation.

PubMed

McCarty, James; Valsson, Omar; Tiwary, Pratyush; Parrinello, Michele

2015-08-14

We propose a new method to obtain kinetic properties of infrequent events from molecular dynamics simulation. The procedure employs a recently introduced variational approach [Valsson and Parrinello, Phys. Rev. Lett. 113, 090601 (2014)] to construct a bias potential as a function of several collective variables that is designed to flood the associated free energy surface up to a predefined level. The resulting bias potential effectively accelerates transitions between metastable free energy minima while ensuring bias-free transition states, thus allowing accurate kinetic rates to be obtained. We test the method on a few illustrative systems for which we obtain an order of magnitude improvement in efficiency relative to previous approaches and several orders of magnitude relative to unbiased molecular dynamics. We expect an even larger improvement in more complex systems. This and the ability of the variational approach to deal efficiently with a large number of collective variables will greatly enhance the scope of these calculations. This work is a vindication of the potential that the variational principle has if applied in innovative ways.

Locating binding poses in protein-ligand systems using reconnaissance metadynamics.

PubMed

Söderhjelm, Pär; Tribello, Gareth A; Parrinello, Michele

2012-04-03

A molecular dynamics-based protocol is proposed for finding and scoring protein-ligand binding poses. This protocol uses the recently developed reconnaissance metadynamics method, which employs a self-learning algorithm to construct a bias that pushes the system away from the kinetic traps where it would otherwise remain. The exploration of phase space with this algorithm is shown to be roughly six to eight times faster than unbiased molecular dynamics and is only limited by the time taken to diffuse about the surface of the protein. We apply this method to the well-studied trypsin-benzamidine system and show that we are able to refind all the poses obtained from a reference EADock blind docking calculation. These poses can be scored based on the length of time the system remains trapped in the pose. Alternatively, one can perform dimensionality reduction on the output trajectory and obtain a map of phase space that can be used in more expensive free-energy calculations.

Toward an Enhanced Sampling Molecular Dynamics Method for Studying Ligand-Induced Conformational Changes in Proteins.

PubMed

Andersen, Ole Juul; Grouleff, Julie; Needham, Perri; Walker, Ross C; Jensen, Frank

2015-11-19

Current enhanced sampling molecular dynamics methods for studying large conformational changes in proteins suffer from certain limitations. These include, among others, the need for user defined collective variables, the prerequisite of both start and end point structures of the conformational change, and the need for a priori knowledge of the amount by which to boost specific parts of the potential. In this paper, a framework is proposed for a molecular dynamics method for studying ligand-induced conformational changes, in which the nonbonded interactions between the ligand and the protein are used to calculate a biasing force. The method requires only a single input structure, and does not entail the use of collective variables. We provide a proof-of-concept for accelerating conformational changes in three simple test molecules, as well as promising results for two proteins known to undergo domain closure upon ligand binding. For the ribose-binding protein, backbone root-mean-square deviations as low as 0.75 Å compared to the crystal structure of the closed conformation are obtained within 50 ns simulations, whereas no domain closures are observed in unbiased simulations. A skewed closed structure is obtained for the glutamine-binding protein at high bias values, indicating that specific protein-ligand interactions might suppress important protein-protein interactions.

Turn-Directed α-β Conformational Transition of α-syn12 Peptide at Different pH Revealed by Unbiased Molecular Dynamics Simulations

PubMed Central

Liu, Lei; Cao, Zanxia

2013-01-01

The transition from α-helical to β-hairpin conformations of α-syn12 peptide is characterized here using long timescale, unbiased molecular dynamics (MD) simulations in explicit solvent models at physiological and acidic pH values. Four independent normal MD trajectories, each 2500 ns, are performed at 300 K using the GROMOS 43A1 force field and SPC water model. The most clustered structures at both pH values are β-hairpin but with different turns and hydrogen bonds. Turn9-6 and four hydrogen bonds (HB9-6, HB6-9, HB11-4 and HB4-11) are formed at physiological pH; turn8-5 and five hydrogen bonds (HB8-5, HB5-8, HB10-3, HB3-10 and HB12-1) are formed at acidic pH. A common folding mechanism is observed: the formation of the turn is always before the formation of the hydrogen bonds, which means the turn is always found to be the major determinant in initiating the transition process. Furthermore, two transition paths are observed at physiological pH. One of the transition paths tends to form the most-clustered turn and improper hydrogen bonds at the beginning, and then form the most-clustered hydrogen bonds. Another transition path tends to form the most-clustered turn, and turn5-2 firstly, followed by the formation of part hydrogen bonds, then turn5-2 is extended and more hydrogen bonds are formed. The transition path at acidic pH is as the same as the first path described at physiological pH. PMID:23708094

On the Dynamical Behavior of the Cysteine Dioxygenase-l-Cysteine Complex in the Presence of Free Dioxygen and l-Cysteine.

PubMed

Pietra, Francesco

2017-11-01

In this work, viable models of cysteine dioxygenase (CDO) and its complex with l-cysteine dianion were built for the first time, under strict adherence to the crystal structure from X-ray diffraction studies, for all atom molecular dynamics (MD). Based on the CHARMM36 FF, the active site, featuring an octahedral dummy Fe(II) model, allowed us observing water exchange, which would have escaped attention with the more popular bonded models. Free dioxygen (O 2 ) and l-cysteine, added at the active site, could be observed being expelled toward the solvating medium under Random Accelerated Molecular Dynamics (RAMD) along major and minor pathways. Correspondingly, free dioxygen (O 2 ), added to the solvating medium, could be observed to follow the same above pathways in getting to the active site under unbiased MD. For the bulky l-cysteine, 600 ns of trajectory were insufficient for protein penetration, and the molecule was stuck at the protein borders. These models pave the way to free energy studies of ligand associations, devised to better clarify how this cardinal enzyme behaves in human metabolism. © 2017 Wiley-VHCA AG, Zurich, Switzerland.

A Molecular Census of Arcuate Hypothalamus and Median Eminence Cell Types

PubMed Central

Campbell, John N.; Macosko, Evan Z.; Fenselau, Henning; Pers, Tune H.; Lyubetskaya, Anna; Tenen, Danielle; Goldman, Melissa; Verstegen, Anne M.J.; Resch, Jon M.; McCarroll, Steven A.; Rosen, Evan D.; Lowell, Bradford B.; Tsai, Linus

2017-01-01

The hypothalamic arcuate-median eminence complex (Arc-ME) controls energy balance, fertility, and growth through molecularly distinct cell types, many of which remain unknown. To catalog cell types in an unbiased way, we profiled gene expression in 20,921 individual cells in and around the adult mouse Arc-ME using Drop-seq. We identify 50 transcriptionally distinct Arc-ME cell populations, including a rare tanycyte population at the Arc-ME diffusion barrier, a novel leptin-sensing neuronal population, multiple AgRP and POMC subtypes, and an orexigenic somatostatin neuronal population. We extended Drop-seq to detect dynamic expression changes across relevant physiological perturbations, revealing cell type-specific responses to energy status, including distinctly responsive subtypes of AgRP and POMC neurons. Finally, integrating our data with human GWAS data implicates two previously unknown neuronal subtypes in the genetic control of obesity. This resource will accelerate biological discovery by providing insights into molecular and cell type diversity from which function can be inferred. PMID:28166221

A novel approach to the investigation of passive molecular permeation through lipid bilayers from atomistic simulations.

PubMed

Ghaemi, Zhaleh; Minozzi, Manuela; Carloni, Paolo; Laio, Alessandro

2012-07-26

Predicting the permeability coefficient (P) of drugs permeating through the cell membrane is of paramount importance in drug discovery. We here propose an approach for calculating P based on bias-exchange metadynamics. The approach allows constructing from atomistic simulations a model of permeation taking explicitly into account not only the "trivial" reaction coordinate, the position of the drug along the direction normal to the lipid membrane plane, but also other degrees of freedom, for example, the torsional angles of the permeating molecule, or variables describing its solvation/desolvation. This allows deriving an accurate picture of the permeation process, and constructing a detailed molecular model of the transition state, making a rational control of permeation properties possible. We benchmarked this approach on the permeation of ethanol molecules through a POPC membrane, showing that the value of P calculated with our model agrees with the one calculated by a long unbiased molecular dynamics of the same system.

Detection of seizures from small samples using nonlinear dynamic system theory.

PubMed

Yaylali, I; Koçak, H; Jayakar, P

1996-07-01

The electroencephalogram (EEG), like many other biological phenomena, is quite likely governed by nonlinear dynamics. Certain characteristics of the underlying dynamics have recently been quantified by computing the correlation dimensions (D2) of EEG time series data. In this paper, D2 of the unbiased autocovariance function of the scalp EEG data was used to detect electrographic seizure activity. Digital EEG data were acquired at a sampling rate of 200 Hz per channel and organized in continuous frames (duration 2.56 s, 512 data points). To increase the reliability of D2 computations with short duration data, raw EEG data were initially simplified using unbiased autocovariance analysis to highlight the periodic activity that is present during seizures. The D2 computation was then performed from the unbiased autocovariance function of each channel using the Grassberger-Procaccia method with Theiler's box-assisted correlation algorithm. Even with short duration data, this preprocessing proved to be computationally robust and displayed no significant sensitivity to implementation details such as the choices of embedding dimension and box size. The system successfully identified various types of seizures in clinical studies.

Molecular details of dimerization kinetics reveal negligible populations of transient µ-opioid receptor homodimers at physiological concentrations.

PubMed

Meral, Derya; Provasi, Davide; Prada-Gracia, Diego; Möller, Jan; Marino, Kristen; Lohse, Martin J; Filizola, Marta

2018-05-16

Various experimental and computational techniques have been employed over the past decade to provide structural and thermodynamic insights into G Protein-Coupled Receptor (GPCR) dimerization. Here, we use multiple microsecond-long, coarse-grained, biased and unbiased molecular dynamics simulations (a total of ~4 milliseconds) combined with multi-ensemble Markov state models to elucidate the kinetics of homodimerization of a prototypic GPCR, the µ-opioid receptor (MOR), embedded in a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC)/cholesterol lipid bilayer. Analysis of these computations identifies kinetically distinct macrostates comprising several different short-lived dimeric configurations of either inactive or activated MOR. Calculated kinetic rates and fractions of dimers at different MOR concentrations suggest a negligible population of MOR homodimers at physiological concentrations, which is supported by acceptor photobleaching fluorescence resonance energy transfer (FRET) experiments. This study provides a rigorous, quantitative explanation for some conflicting experimental data on GPCR oligomerization.

Sampling the multiple folding mechanisms of Trp-cage in explicit solvent

PubMed Central

Juraszek, J.; Bolhuis, P. G.

2006-01-01

We investigate the kinetic pathways of folding and unfolding of the designed miniprotein Trp- cage in explicit solvent. Straightforward molecular dynamics and replica exchange methods both have severe convergence problems, whereas transition path sampling allows us to sample unbiased dynamical pathways between folded and unfolded states and leads to deeper understanding of the mechanisms of (un)folding. In contrast to previous predictions employing an implicit solvent, we find that Trp-cage folds primarily (80% of the paths) via a pathway forming the tertiary contacts and the salt bridge, before helix formation. The remaining 20% of the paths occur in the opposite order, by first forming the helix. The transition states of the rate-limiting steps are solvated native-like structures. Water expulsion is found to be the last step upon folding for each route. Committor analysis suggests that the dynamics of the solvent is not part of the reaction coordinate. Nevertheless, during the transition, specific water molecules are strongly bound and can play a structural role in the folding. PMID:17035504

Protein free energy landscapes from long equilibrium simulations

NASA Astrophysics Data System (ADS)

Piana-Agostinetti, Stefano

Many computational techniques based on molecular dynamics (MD) simulation can be used to generate data to aid in the construction of protein free energy landscapes with atomistic detail. Unbiased, long, equilibrium MD simulations--although computationally very expensive--are particularly appealing, as they can provide direct kinetic and thermodynamic information on the transitions between the states that populate a protein free energy surface. It can be challenging to know how to analyze and interpret even results generated by this direct technique, however. I will discuss approaches we have employed, using equilibrium MD simulation data, to obtain descriptions of the free energy landscapes of proteins ranging in size from tens to thousands of amino acids.

The technology and biology of single-cell RNA sequencing.

PubMed

Kolodziejczyk, Aleksandra A; Kim, Jong Kyoung; Svensson, Valentine; Marioni, John C; Teichmann, Sarah A

2015-05-21

The differences between individual cells can have profound functional consequences, in both unicellular and multicellular organisms. Recently developed single-cell mRNA-sequencing methods enable unbiased, high-throughput, and high-resolution transcriptomic analysis of individual cells. This provides an additional dimension to transcriptomic information relative to traditional methods that profile bulk populations of cells. Already, single-cell RNA-sequencing methods have revealed new biology in terms of the composition of tissues, the dynamics of transcription, and the regulatory relationships between genes. Rapid technological developments at the level of cell capture, phenotyping, molecular biology, and bioinformatics promise an exciting future with numerous biological and medical applications. Copyright © 2015 Elsevier Inc. All rights reserved.

Extended molecular dynamics of a c-kit promoter quadruplex

PubMed Central

Islam, Barira; Stadlbauer, Petr; Krepl, Miroslav; Koca, Jaroslav; Neidle, Stephen; Haider, Shozeb; Sponer, Jiri

2015-01-01

The 22-mer c-kit promoter sequence folds into a parallel-stranded quadruplex with a unique structure, which has been elucidated by crystallographic and NMR methods and shows a high degree of structural conservation. We have carried out a series of extended (up to 10 μs long, ∼50 μs in total) molecular dynamics simulations to explore conformational stability and loop dynamics of this quadruplex. Unfolding no-salt simulations are consistent with a multi-pathway model of quadruplex folding and identify the single-nucleotide propeller loops as the most fragile part of the quadruplex. Thus, formation of propeller loops represents a peculiar atomistic aspect of quadruplex folding. Unbiased simulations reveal μs-scale transitions in the loops, which emphasizes the need for extended simulations in studies of quadruplex loops. We identify ion binding in the loops which may contribute to quadruplex stability. The long lateral-propeller loop is internally very stable but extensively fluctuates as a rigid entity. It creates a size-adaptable cleft between the loop and the stem, which can facilitate ligand binding. The stability gain by forming the internal network of GA base pairs and stacks of this loop may be dictating which of the many possible quadruplex topologies is observed in the ground state by this promoter quadruplex. PMID:26245347

From metadynamics to dynamics.

PubMed

Tiwary, Pratyush; Parrinello, Michele

2013-12-06

Metadynamics is a commonly used and successful enhanced sampling method. By the introduction of a history dependent bias which depends on a restricted number of collective variables it can explore complex free energy surfaces characterized by several metastable states separated by large free energy barriers. Here we extend its scope by introducing a simple yet powerful method for calculating the rates of transition between different metastable states. The method does not rely on a previous knowledge of the transition states or reaction coordinates, as long as collective variables are known that can distinguish between the various stable minima in free energy space. We demonstrate that our method recovers the correct escape rates out of these stable states and also preserves the correct sequence of state-to-state transitions, with minimal extra computational effort needed over ordinary metadynamics. We apply the formalism to three different problems and in each case find excellent agreement with the results of long unbiased molecular dynamics runs.

From Metadynamics to Dynamics

NASA Astrophysics Data System (ADS)

Tiwary, Pratyush; Parrinello, Michele

2013-12-01

Metadynamics is a commonly used and successful enhanced sampling method. By the introduction of a history dependent bias which depends on a restricted number of collective variables it can explore complex free energy surfaces characterized by several metastable states separated by large free energy barriers. Here we extend its scope by introducing a simple yet powerful method for calculating the rates of transition between different metastable states. The method does not rely on a previous knowledge of the transition states or reaction coordinates, as long as collective variables are known that can distinguish between the various stable minima in free energy space. We demonstrate that our method recovers the correct escape rates out of these stable states and also preserves the correct sequence of state-to-state transitions, with minimal extra computational effort needed over ordinary metadynamics. We apply the formalism to three different problems and in each case find excellent agreement with the results of long unbiased molecular dynamics runs.

Dynamic Cluster Analysis: An Unbiased Method for Identifying A + 2 Element Containing Compounds in Liquid Chromatographic High-Resolution Time-of-Flight Mass Spectrometric Data.

PubMed

Andersen, Aaron John Christian; Hansen, Per Juel; Jørgensen, Kevin; Nielsen, Kristian Fog

2016-12-20

Dynamic cluster analysis (DCA) is an automated, unbiased technique which can identify Cl, Br, S, and other A + 2 element containing metabolites in liquid chromatographic high-resolution mass spectrometric data. DCA is based on three features, primarily the previously unutilized A + 1 to A + 2 isotope cluster spacing which is a strong classifier in itself but improved with the addition of the monoisotopic mass, and the well-known A:A+2 intensity ratio. Utilizing only the A + 1 to A + 2 isotope cluster spacing and the monoisotopic mass it was possible to filter a chromatogram for metabolites which contain Cl, Br, and S. Screening simulated isotope patterns of the Antibase Natural Products Database it was determined that the A + 1 to A + 2 isotope cluster spacing can be used to correctly classify 97.4% of molecular formulas containing these elements, only misclassifying a few metabolites which were either over 2800 u or metabolites which contained other A + 2 elements, such as Cu, Ni, Mg, and Zn. It was determined that with an interisotopic mass accuracy of 1 ppm, in a fully automated process, using all three parameters, it is possible to specifically filter a chromatogram for S containing metabolites with monoisotopic masses less than 825 u. Furthermore, it was possible to specifically filter a chromatogram for Cl and Br containing metabolites with monoisotopic masses less than 1613 u. Here DCA is applied on (i) simulated isotope patterns of the Antibase natural products databases, (ii) LC-QTOF data of reference standards, and (iii) LC-QTOF data of crude extracts of 10 strains of laboratory grown cultures of the microalga Prymnesium parvum where it identified known metabolites of the prymnesin series as well as over 20 previously undescribed prymnesin-like molecular features.

Melittin Aggregation in Aqueous Solutions: Insight from Molecular Dynamics Simulations.

PubMed

Liao, Chenyi; Esai Selvan, Myvizhi; Zhao, Jun; Slimovitch, Jonathan L; Schneebeli, Severin T; Shelley, Mee; Shelley, John C; Li, Jianing

2015-08-20

Melittin is a natural peptide that aggregates in aqueous solutions with paradigmatic monomer-to-tetramer and coil-to-helix transitions. Since little is known about the molecular mechanisms of melittin aggregation in solution, we simulated its self-aggregation process under various conditions. After confirming the stability of a melittin tetramer in solution, we observed—for the first time in atomistic detail—that four separated melittin monomers aggregate into a tetramer. Our simulated dependence of melittin aggregation on peptide concentration, temperature, and ionic strength is in good agreement with prior experiments. We propose that melittin mainly self-aggregates via a mechanism involving the sequential addition of monomers, which is supported by both qualitative and quantitative evidence obtained from unbiased and metadynamics simulations. Moreover, by combining computer simulations and a theory of the electrical double layer, we provide evidence to suggest why melittin aggregation in solution likely stops at the tetramer, rather than forming higher-order oligomers. Overall, our study not only explains prior experimental results at the molecular level but also provides quantitative mechanistic information that may guide the engineering of melittin for higher efficacy and safety.

Linear Response Path Following: A Molecular Dynamics Method To Simulate Global Conformational Changes of Protein upon Ligand Binding.

PubMed

Tamura, Koichi; Hayashi, Shigehiko

2015-07-14

Molecular functions of proteins are often fulfilled by global conformational changes that couple with local events such as the binding of ligand molecules. High molecular complexity of proteins has, however, been an obstacle to obtain an atomistic view of the global conformational transitions, imposing a limitation on the mechanistic understanding of the functional processes. In this study, we developed a new method of molecular dynamics (MD) simulation called the linear response path following (LRPF) to simulate a protein's global conformational changes upon ligand binding. The method introduces a biasing force based on a linear response theory, which determines a local reaction coordinate in the configuration space that represents linear coupling between local events of ligand binding and global conformational changes and thus provides one with fully atomistic models undergoing large conformational changes without knowledge of a target structure. The overall transition process involving nonlinear conformational changes is simulated through iterative cycles consisting of a biased MD simulation with an updated linear response force and a following unbiased MD simulation for relaxation. We applied the method to the simulation of global conformational changes of the yeast calmodulin N-terminal domain and successfully searched out the end conformation. The atomistically detailed trajectories revealed a sequence of molecular events that properly lead to the global conformational changes and identified key steps of local-global coupling that induce the conformational transitions. The LRPF method provides one with a powerful means to model conformational changes of proteins such as motors and transporters where local-global coupling plays a pivotal role in their functional processes.

Diabat Interpolation for Polymorph Free-Energy Differences.

PubMed

Kamat, Kartik; Peters, Baron

2017-02-02

Existing methods to compute free-energy differences between polymorphs use harmonic approximations, advanced non-Boltzmann bias sampling techniques, and/or multistage free-energy perturbations. This work demonstrates how Bennett's diabat interpolation method ( J. Comput. Phys. 1976, 22, 245 ) can be combined with energy gaps from lattice-switch Monte Carlo techniques ( Phys. Rev. E 2000, 61, 906 ) to swiftly estimate polymorph free-energy differences. The new method requires only two unbiased molecular dynamics simulations, one for each polymorph. To illustrate the new method, we compute the free-energy difference between face-centered cubic and body-centered cubic polymorphs for a Gaussian core solid. We discuss the justification for parabolic models of the free-energy diabats and similarities to methods that have been used in studies of electron transfer.

tICA-Metadynamics: Accelerating Metadynamics by Using Kinetically Selected Collective Variables.

PubMed

M Sultan, Mohammad; Pande, Vijay S

2017-06-13

Metadynamics is a powerful enhanced molecular dynamics sampling method that accelerates simulations by adding history-dependent multidimensional Gaussians along selective collective variables (CVs). In practice, choosing a small number of slow CVs remains challenging due to the inherent high dimensionality of biophysical systems. Here we show that time-structure based independent component analysis (tICA), a recent advance in Markov state model literature, can be used to identify a set of variationally optimal slow coordinates for use as CVs for Metadynamics. We show that linear and nonlinear tICA-Metadynamics can complement existing MD studies by explicitly sampling the system's slowest modes and can even drive transitions along the slowest modes even when no such transitions are observed in unbiased simulations.

Structural Diversity of Ligand-Binding Androgen Receptors Revealed by Microsecond Long Molecular Dynamics Simulations and Enhanced Sampling.

PubMed

Duan, Mojie; Liu, Na; Zhou, Wenfang; Li, Dan; Yang, Minghui; Hou, Tingjun

2016-09-13

Androgen receptor (AR) plays important roles in the development of prostate cancer (PCa). The antagonistic drugs, which suppress the activity of AR, are widely used in the treatment of PCa. However, the molecular mechanism of antagonism about how ligands affect the structures of AR remains elusive. To better understand the conformational variability of ARs bound with agonists or antagonists, we performed long time unbiased molecular dynamics (MD) simulations and enhanced sampling simulations for the ligand binding domain of AR (AR-LBD) in complex with various ligands. Based on the simulation results, we proposed an allosteric pathway linking ligands and helix 12 (H12) of AR-LBD, which involves the interactions among the ligands and the residues W741, H874, and I899. The interaction pathway provides an atomistic explanation of how ligands affect the structure of AR-LBD. A repositioning of H12 was observed, but it is facilitated by the C-terminal of H12, instead of by the loop between helix 11 (H11) and H12. The bias-exchange metadynamics simulations further demonstrated the above observations. More importantly, the free energy profiles constructed by the enhanced sampling simulations revealed the transition process between the antagonistic form and agonistic form of AR-LBD. Our results would be helpful for the design of more efficient antagonists of AR to combat PCa.

A molecular description of ligand binding to the two overlapping binding pockets of the nuclear vitamin D receptor (VDR): structure-function implications

PubMed Central

Mizwicki, Mathew T.; Menegaz, Danusa; Yaghmaei, Sepideh; Henry, Helen L.; Norman, Anthony W.

2010-01-01

Molecular modeling results indicate that the VDR contains two overlapping ligand binding pockets (LBP). Differential ligand stability and fractional occupancy of the two LBP has been physiochemically linked to the regulation of VDR-dependent genomic and non-genomic cellular responses. The purpose of this report is to develop an unbiased molecular modeling protocol that serves as a good starting point in simulating the dynamic interaction between 1α,25(OH)2-vitamin D3 (1,25D3) and the VDR LBP. To accomplish this goal, the flexible docking protocol developed allowed for flexibility in the VDR ligand and the VDR atoms that form the surfaces of the VDR LBP. This approach blindly replicated the 1,25D3 conformation and side-chain dynamics observed in the VDR x-ray structure. The results are also consistent with the previously published tenants of the vitamin D sterol (VDS)-VDR conformational ensemble model. Furthermore, we used flexible docking in combination with whole cell patch clamp electrophysiology and steroid competition assays to demonstrate that a) new non-vitamin D VDR ligands show a different pocket selectivity when compared to 1,25D3 that is qualitatively consistent with their ability to stimulate chloride channels and b) a new route of ligand binding provides a novel hypothesis describing the structural nuances that underlie hypercalceamia. PMID:20398762

Combination of Markov state models and kinetic networks for the analysis of molecular dynamics simulations of peptide folding.

PubMed

Radford, Isolde H; Fersht, Alan R; Settanni, Giovanni

2011-06-09

Atomistic molecular dynamics simulations of the TZ1 beta-hairpin peptide have been carried out using an implicit model for the solvent. The trajectories have been analyzed using a Markov state model defined on the projections along two significant observables and a kinetic network approach. The Markov state model allowed for an unbiased identification of the metastable states of the system, and provided the basis for commitment probability calculations performed on the kinetic network. The kinetic network analysis served to extract the main transition state for folding of the peptide and to validate the results from the Markov state analysis. The combination of the two techniques allowed for a consistent and concise characterization of the dynamics of the peptide. The slowest relaxation process identified is the exchange between variably folded and denatured species, and the second slowest process is the exchange between two different subsets of the denatured state which could not be otherwise identified by simple inspection of the projected trajectory. The third slowest process is the exchange between a fully native and a partially folded intermediate state characterized by a native turn with a proximal backbone H-bond, and frayed side-chain packing and termini. The transition state for the main folding reaction is similar to the intermediate state, although a more native like side-chain packing is observed.

Metadynamics Enhanced Markov Modeling of Protein Dynamics.

PubMed

Biswas, Mithun; Lickert, Benjamin; Stock, Gerhard

2018-05-31

Enhanced sampling techniques represent a versatile approach to account for rare conformational transitions in biomolecules. A particularly promising strategy is to combine massive parallel computing of short molecular dynamics (MD) trajectories (to sample the free energy landscape of the system) with Markov state modeling (to rebuild the kinetics from the sampled data). To obtain well-distributed initial structures for the short trajectories, it is proposed to employ metadynamics MD, which quickly sweeps through the entire free energy landscape of interest. Being only used to generate initial conformations, the implementation of metadynamics can be simple and fast. The conformational dynamics of helical peptide Aib 9 is adopted to discuss various technical issues of the approach, including metadynamics settings, minimal number and length of short MD trajectories, and the validation of the resulting Markov models. Using metadynamics to launch some thousands of nanosecond trajectories, several Markov state models are constructed that reveal that previous unbiased MD simulations of in total 16 μs length cannot provide correct equilibrium populations or qualitative features of the pathway distribution of the short peptide.

Markov state models from short non-equilibrium simulations—Analysis and correction of estimation bias

NASA Astrophysics Data System (ADS)

Nüske, Feliks; Wu, Hao; Prinz, Jan-Hendrik; Wehmeyer, Christoph; Clementi, Cecilia; Noé, Frank

2017-03-01

Many state-of-the-art methods for the thermodynamic and kinetic characterization of large and complex biomolecular systems by simulation rely on ensemble approaches, where data from large numbers of relatively short trajectories are integrated. In this context, Markov state models (MSMs) are extremely popular because they can be used to compute stationary quantities and long-time kinetics from ensembles of short simulations, provided that these short simulations are in "local equilibrium" within the MSM states. However, over the last 15 years since the inception of MSMs, it has been controversially discussed and not yet been answered how deviations from local equilibrium can be detected, whether these deviations induce a practical bias in MSM estimation, and how to correct for them. In this paper, we address these issues: We systematically analyze the estimation of MSMs from short non-equilibrium simulations, and we provide an expression for the error between unbiased transition probabilities and the expected estimate from many short simulations. We show that the unbiased MSM estimate can be obtained even from relatively short non-equilibrium simulations in the limit of long lag times and good discretization. Further, we exploit observable operator model (OOM) theory to derive an unbiased estimator for the MSM transition matrix that corrects for the effect of starting out of equilibrium, even when short lag times are used. Finally, we show how the OOM framework can be used to estimate the exact eigenvalues or relaxation time scales of the system without estimating an MSM transition matrix, which allows us to practically assess the discretization quality of the MSM. Applications to model systems and molecular dynamics simulation data of alanine dipeptide are included for illustration. The improved MSM estimator is implemented in PyEMMA of version 2.3.

Adaptive enhanced sampling with a path-variable for the simulation of protein folding and aggregation

NASA Astrophysics Data System (ADS)

Peter, Emanuel K.

2017-12-01

In this article, we present a novel adaptive enhanced sampling molecular dynamics (MD) method for the accelerated simulation of protein folding and aggregation. We introduce a path-variable L based on the un-biased momenta p and displacements dq for the definition of the bias s applied to the system and derive 3 algorithms: general adaptive bias MD, adaptive path-sampling, and a hybrid method which combines the first 2 methodologies. Through the analysis of the correlations between the bias and the un-biased gradient in the system, we find that the hybrid methodology leads to an improved force correlation and acceleration in the sampling of the phase space. We apply our method on SPC/E water, where we find a conservation of the average water structure. We then use our method to sample dialanine and the folding of TrpCage, where we find a good agreement with simulation data reported in the literature. Finally, we apply our methodologies on the initial stages of aggregation of a hexamer of Alzheimer's amyloid β fragment 25-35 (Aβ 25-35) and find that transitions within the hexameric aggregate are dominated by entropic barriers, while we speculate that especially the conformation entropy plays a major role in the formation of the fibril as a rate limiting factor.

Adaptive enhanced sampling with a path-variable for the simulation of protein folding and aggregation.

PubMed

Peter, Emanuel K

2017-12-07

In this article, we present a novel adaptive enhanced sampling molecular dynamics (MD) method for the accelerated simulation of protein folding and aggregation. We introduce a path-variable L based on the un-biased momenta p and displacements dq for the definition of the bias s applied to the system and derive 3 algorithms: general adaptive bias MD, adaptive path-sampling, and a hybrid method which combines the first 2 methodologies. Through the analysis of the correlations between the bias and the un-biased gradient in the system, we find that the hybrid methodology leads to an improved force correlation and acceleration in the sampling of the phase space. We apply our method on SPC/E water, where we find a conservation of the average water structure. We then use our method to sample dialanine and the folding of TrpCage, where we find a good agreement with simulation data reported in the literature. Finally, we apply our methodologies on the initial stages of aggregation of a hexamer of Alzheimer's amyloid β fragment 25-35 (Aβ 25-35) and find that transitions within the hexameric aggregate are dominated by entropic barriers, while we speculate that especially the conformation entropy plays a major role in the formation of the fibril as a rate limiting factor.

Weighted Ensemble Simulation: Review of Methodology, Applications, and Software

PubMed Central

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

Weighted Ensemble Simulation: Review of Methodology, Applications, and Software.

PubMed

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.

Using Markov state models to study self-assembly

NASA Astrophysics Data System (ADS)

Perkett, Matthew R.; Hagan, Michael F.

2014-06-01

Markov state models (MSMs) have been demonstrated to be a powerful method for computationally studying intramolecular processes such as protein folding and macromolecular conformational changes. In this article, we present a new approach to construct MSMs that is applicable to modeling a broad class of multi-molecular assembly reactions. Distinct structures formed during assembly are distinguished by their undirected graphs, which are defined by strong subunit interactions. Spatial inhomogeneities of free subunits are accounted for using a recently developed Gaussian-based signature. Simplifications to this state identification are also investigated. The feasibility of this approach is demonstrated on two different coarse-grained models for virus self-assembly. We find good agreement between the dynamics predicted by the MSMs and long, unbiased simulations, and that the MSMs can reduce overall simulation time by orders of magnitude.

A distance-limited sample of massive molecular outflows

NASA Astrophysics Data System (ADS)

Maud, L. T.; Moore, T. J. T.; Lumsden, S. L.; Mottram, J. C.; Urquhart, J. S.; Hoare, M. G.

2015-10-01

We have observed 99 mid-infrared-bright, massive young stellar objects and compact H II regions drawn from the Red MSX source survey in the J = 3-2 transition of 12CO and 13CO, using the James Clerk Maxwell Telescope. 89 targets are within 6 kpc of the Sun, covering a representative range of luminosities and core masses. These constitute a relatively unbiased sample of bipolar molecular outflows associated with massive star formation. Of these, 59, 17 and 13 sources (66, 19 and 15 per cent) are found to have outflows, show some evidence of outflow, and have no evidence of outflow, respectively. The time-dependent parameters of the high-velocity molecular flows are calculated using a spatially variable dynamic time-scale. The canonical correlations between the outflow parameters and source luminosity are recovered and shown to scale with those of low-mass sources. For coeval star formation, we find the scaling is consistent with all the protostars in an embedded cluster providing the outflow force, with massive stars up to ˜30 M⊙ generating outflows. Taken at face value, the results support the model of a scaled-up version of the accretion-related outflow-generation mechanism associated with discs and jets in low-mass objects with time-averaged accretion rates of ˜10-3 M⊙ yr-1 on to the cores. However, we also suggest an alternative model, in which the molecular outflow dynamics are dominated by the entrained mass and are unrelated to the details of the acceleration mechanism. We find no evidence that outflows contribute significantly to the turbulent kinetic energy of the surrounding dense cores.

Molecular Dynamics Simulations of the Human Glucose Transporter GLUT1

PubMed Central

Park, Min-Sun

2015-01-01

Glucose transporters (GLUTs) provide a pathway for glucose transport across membranes. Human GLUTs are implicated in devastating diseases such as heart disease, hyper- and hypo-glycemia, type 2 diabetes and caner. The human GLUT1 has been recently crystalized in the inward-facing open conformation. However, there is no other structural information for other conformations. The X-ray structures of E. coli Xylose permease (XylE), a glucose transporter homolog, are available in multiple conformations with and without the substrates D-xylose and D-glucose. XylE has high sequence homology to human GLUT1 and key residues in the sugar-binding pocket are conserved. Here we construct a homology model for human GLUT1 based on the available XylE crystal structure in the partially occluded outward-facing conformation. A long unbiased all atom molecular dynamics simulation starting from the model can capture a new fully opened outward-facing conformation. Our investigation of molecular interactions at the interface between the transmembrane (TM) domains and the intracellular helices (ICH) domain in the outward- and inward-facing conformation supports that the ICH domain likely stabilizes the outward-facing conformation in GLUT1. Furthermore, inducing a conformational transition, our simulations manifest a global asymmetric rocker switch motion and detailed molecular interactions between the substrate and residues through the water-filled selective pore along a pathway from the extracellular to the intracellular side. The results presented here are consistent with previously published biochemical, mutagenesis and functional studies. Together, this study shed light on the structure and functional relationships of GLUT1 in multiple conformational states. PMID:25919356

A hybrid approach to simulation of electron transfer in complex molecular systems

PubMed Central

Kubař, Tomáš; Elstner, Marcus

2013-01-01

Electron transfer (ET) reactions in biomolecular systems represent an important class of processes at the interface of physics, chemistry and biology. The theoretical description of these reactions constitutes a huge challenge because extensive systems require a quantum-mechanical treatment and a broad range of time scales are involved. Thus, only small model systems may be investigated with the modern density functional theory techniques combined with non-adiabatic dynamics algorithms. On the other hand, model calculations based on Marcus's seminal theory describe the ET involving several assumptions that may not always be met. We review a multi-scale method that combines a non-adiabatic propagation scheme and a linear scaling quantum-chemical method with a molecular mechanics force field in such a way that an unbiased description of the dynamics of excess electron is achieved and the number of degrees of freedom is reduced effectively at the same time. ET reactions taking nanoseconds in systems with hundreds of quantum atoms can be simulated, bridging the gap between non-adiabatic ab initio simulations and model approaches such as the Marcus theory. A major recent application is hole transfer in DNA, which represents an archetypal ET reaction in a polarizable medium. Ongoing work focuses on hole transfer in proteins, peptides and organic semi-conductors. PMID:23883952

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grosso, Marcos; Kalstein, Adrian; Parisi, Gustavo

The native state of a protein consists of an equilibrium of conformational states on an energy landscape rather than existing as a single static state. The co-existence of conformers with different ligand-affinities in a dynamical equilibrium is the basis for the conformational selection model for ligand binding. In this context, the development of theoretical methods that allow us to analyze not only the structural changes but also changes in the fluctuation patterns between conformers will contribute to elucidate the differential properties acquired upon ligand binding. Molecular dynamics simulations can provide the required information to explore these features. Its use inmore » combination with subsequent essential dynamics analysis allows separating large concerted conformational rearrangements from irrelevant fluctuations. We present a novel procedure to define the size and composition of essential dynamics subspaces associated with ligand-bound and ligand-free conformations. These definitions allow us to compare essential dynamics subspaces between different conformers. Our procedure attempts to emphasize the main similarities and differences between the different essential dynamics in an unbiased way. Essential dynamics subspaces associated to conformational transitions can also be analyzed. As a test case, we study the glutaminase interacting protein (GIP), composed of a single PDZ domain. Both GIP ligand-free state and glutaminase L peptide-bound states are analyzed. Our findings concerning the relative changes in the flexibility pattern upon binding are in good agreement with experimental Nuclear Magnetic Resonance data.« less

Precision medicine in the age of big data: The present and future role of large-scale unbiased sequencing in drug discovery and development.

PubMed

Vicini, P; Fields, O; Lai, E; Litwack, E D; Martin, A-M; Morgan, T M; Pacanowski, M A; Papaluca, M; Perez, O D; Ringel, M S; Robson, M; Sakul, H; Vockley, J; Zaks, T; Dolsten, M; Søgaard, M

2016-02-01

High throughput molecular and functional profiling of patients is a key driver of precision medicine. DNA and RNA characterization has been enabled at unprecedented cost and scale through rapid, disruptive progress in sequencing technology, but challenges persist in data management and interpretation. We analyze the state-of-the-art of large-scale unbiased sequencing in drug discovery and development, including technology, application, ethical, regulatory, policy and commercial considerations, and discuss issues of LUS implementation in clinical and regulatory practice. © 2015 American Society for Clinical Pharmacology and Therapeutics.

A Kinetic Model of Trp-Cage Folding from Multiple Biased Molecular Dynamics Simulations

PubMed Central

Marinelli, Fabrizio; Pietrucci, Fabio; Laio, Alessandro; Piana, Stefano

2009-01-01

Trp-cage is a designed 20-residue polypeptide that, in spite of its size, shares several features with larger globular proteins. Although the system has been intensively investigated experimentally and theoretically, its folding mechanism is not yet fully understood. Indeed, some experiments suggest a two-state behavior, while others point to the presence of intermediates. In this work we show that the results of a bias-exchange metadynamics simulation can be used for constructing a detailed thermodynamic and kinetic model of the system. The model, although constructed from a biased simulation, has a quality similar to those extracted from the analysis of long unbiased molecular dynamics trajectories. This is demonstrated by a careful benchmark of the approach on a smaller system, the solvated Ace-Ala3-Nme peptide. For the Trp-cage folding, the model predicts that the relaxation time of 3100 ns observed experimentally is due to the presence of a compact molten globule-like conformation. This state has an occupancy of only 3% at 300 K, but acts as a kinetic trap. Instead, non-compact structures relax to the folded state on the sub-microsecond timescale. The model also predicts the presence of a state at of 4.4 Å from the NMR structure in which the Trp strongly interacts with Pro12. This state can explain the abnormal temperature dependence of the and chemical shifts. The structures of the two most stable misfolded intermediates are in agreement with NMR experiments on the unfolded protein. Our work shows that, using biased molecular dynamics trajectories, it is possible to construct a model describing in detail the Trp-cage folding kinetics and thermodynamics in agreement with experimental data. PMID:19662155

A kinetic model of trp-cage folding from multiple biased molecular dynamics simulations.

PubMed

Marinelli, Fabrizio; Pietrucci, Fabio; Laio, Alessandro; Piana, Stefano

2009-08-01

Trp-cage is a designed 20-residue polypeptide that, in spite of its size, shares several features with larger globular proteins.Although the system has been intensively investigated experimentally and theoretically, its folding mechanism is not yet fully understood. Indeed, some experiments suggest a two-state behavior, while others point to the presence of intermediates. In this work we show that the results of a bias-exchange metadynamics simulation can be used for constructing a detailed thermodynamic and kinetic model of the system. The model, although constructed from a biased simulation, has a quality similar to those extracted from the analysis of long unbiased molecular dynamics trajectories. This is demonstrated by a careful benchmark of the approach on a smaller system, the solvated Ace-Ala3-Nme peptide. For theTrp-cage folding, the model predicts that the relaxation time of 3100 ns observed experimentally is due to the presence of a compact molten globule-like conformation. This state has an occupancy of only 3% at 300 K, but acts as a kinetic trap.Instead, non-compact structures relax to the folded state on the sub-microsecond timescale. The model also predicts the presence of a state at Calpha-RMSD of 4.4 A from the NMR structure in which the Trp strongly interacts with Pro12. This state can explain the abnormal temperature dependence of the Pro12-delta3 and Gly11-alpha3 chemical shifts. The structures of the two most stable misfolded intermediates are in agreement with NMR experiments on the unfolded protein. Our work shows that, using biased molecular dynamics trajectories, it is possible to construct a model describing in detail the Trp-cage folding kinetics and thermodynamics in agreement with experimental data.

Molecular Dynamics Study of the Opening Mechanism for DNA Polymerase I

PubMed Central

Miller, Bill R.; Parish, Carol A.; Wu, Eugene Y.

2014-01-01

During DNA replication, DNA polymerases follow an induced fit mechanism in order to rapidly distinguish between correct and incorrect dNTP substrates. The dynamics of this process are crucial to the overall effectiveness of catalysis. Although X-ray crystal structures of DNA polymerase I with substrate dNTPs have revealed key structural states along the catalytic pathway, solution fluorescence studies indicate that those key states are populated in the absence of substrate. Herein, we report the first atomistic simulations showing the conformational changes between the closed, open, and ajar conformations of DNA polymerase I in the binary (enzyme∶DNA) state to better understand its dynamics. We have applied long time-scale, unbiased molecular dynamics to investigate the opening process of the fingers domain in the absence of substrate for B. stearothermophilis DNA polymerase in silico. These simulations are biologically and/or physiologically relevant as they shed light on the transitions between states in this important enzyme. All closed and ajar simulations successfully transitioned into the fully open conformation, which is known to be the dominant binary enzyme-DNA conformation from solution and crystallographic studies. Furthermore, we have detailed the key stages in the opening process starting from the open and ajar crystal structures, including the observation of a previously unknown key intermediate structure. Four backbone dihedrals were identified as important during the opening process, and their movements provide insight into the recognition of dNTP substrate molecules by the polymerase binary state. In addition to revealing the opening mechanism, this study also demonstrates our ability to study biological events of DNA polymerase using current computational methods without biasing the dynamics. PMID:25474643

Probabilistic switching circuits in DNA

PubMed Central

Wilhelm, Daniel; Bruck, Jehoshua

2018-01-01

A natural feature of molecular systems is their inherent stochastic behavior. A fundamental challenge related to the programming of molecular information processing systems is to develop a circuit architecture that controls the stochastic states of individual molecular events. Here we present a systematic implementation of probabilistic switching circuits, using DNA strand displacement reactions. Exploiting the intrinsic stochasticity of molecular interactions, we developed a simple, unbiased DNA switch: An input signal strand binds to the switch and releases an output signal strand with probability one-half. Using this unbiased switch as a molecular building block, we designed DNA circuits that convert an input signal to an output signal with any desired probability. Further, this probability can be switched between 2n different values by simply varying the presence or absence of n distinct DNA molecules. We demonstrated several DNA circuits that have multiple layers and feedback, including a circuit that converts an input strand to an output strand with eight different probabilities, controlled by the combination of three DNA molecules. These circuits combine the advantages of digital and analog computation: They allow a small number of distinct input molecules to control a diverse signal range of output molecules, while keeping the inputs robust to noise and the outputs at precise values. Moreover, arbitrarily complex circuit behaviors can be implemented with just a single type of molecular building block. PMID:29339484

Comprehensive Peptide Ion Structure Studies Using Ion Mobility Techniques: Part 1. An Advanced Protocol for Molecular Dynamics Simulations and Collision Cross-Section Calculation.

PubMed

Ghassabi Kondalaji, Samaneh; Khakinejad, Mahdiar; Tafreshian, Amirmahdi; J Valentine, Stephen

2017-05-01

Collision cross-section (CCS) measurements with a linear drift tube have been utilized to study the gas-phase conformers of a model peptide (acetyl-PAAAAKAAAAKAAAAKAAAAK). Extensive molecular dynamics (MD) simulations have been conducted to derive an advanced protocol for the generation of a comprehensive pool of in-silico structures; both higher energy and more thermodynamically stable structures are included to provide an unbiased sampling of conformational space. MD simulations at 300 K are applied to the in-silico structures to more accurately describe the gas-phase transport properties of the ion conformers including their dynamics. Different methods used previously for trajectory method (TM) CCS calculation employing the Mobcal software [1] are evaluated. A new method for accurate CCS calculation is proposed based on clustering and data mining techniques. CCS values are calculated for all in-silico structures, and those with matching CCS values are chosen as candidate structures. With this approach, more than 300 candidate structures with significant structural variation are produced; although no final gas-phase structure is proposed here, in a second installment of this work, gas-phase hydrogen deuterium exchange data will be utilized as a second criterion to select among these structures as well as to propose relative populations for these ion conformers. Here the need to increase conformer diversity and accurate CCS calculation is demonstrated and the advanced methods are discussed. Graphical Abstract ᅟ.

Comprehensive Peptide Ion Structure Studies Using Ion Mobility Techniques: Part 1. An Advanced Protocol for Molecular Dynamics Simulations and Collision Cross-Section Calculation

NASA Astrophysics Data System (ADS)

Ghassabi Kondalaji, Samaneh; Khakinejad, Mahdiar; Tafreshian, Amirmahdi; J. Valentine, Stephen

2017-05-01

Collision cross-section (CCS) measurements with a linear drift tube have been utilized to study the gas-phase conformers of a model peptide (acetyl-PAAAAKAAAAKAAAAKAAAAK). Extensive molecular dynamics (MD) simulations have been conducted to derive an advanced protocol for the generation of a comprehensive pool of in-silico structures; both higher energy and more thermodynamically stable structures are included to provide an unbiased sampling of conformational space. MD simulations at 300 K are applied to the in-silico structures to more accurately describe the gas-phase transport properties of the ion conformers including their dynamics. Different methods used previously for trajectory method (TM) CCS calculation employing the Mobcal software [1] are evaluated. A new method for accurate CCS calculation is proposed based on clustering and data mining techniques. CCS values are calculated for all in-silico structures, and those with matching CCS values are chosen as candidate structures. With this approach, more than 300 candidate structures with significant structural variation are produced; although no final gas-phase structure is proposed here, in a second installment of this work, gas-phase hydrogen deuterium exchange data will be utilized as a second criterion to select among these structures as well as to propose relative populations for these ion conformers. Here the need to increase conformer diversity and accurate CCS calculation is demonstrated and the advanced methods are discussed.

Current and efficiency of Brownian particles under oscillating forces in entropic barriers

NASA Astrophysics Data System (ADS)

Nutku, Ferhat; Aydιner, Ekrem

2015-04-01

In this study, considering the temporarily unbiased force and different forms of oscillating forces, we investigate the current and efficiency of Brownian particles in an entropic tube structure and present the numerically obtained results. We show that different force forms give rise to different current and efficiency profiles in different optimized parameter intervals. We find that an unbiased oscillating force and an unbiased temporal force lead to the current and efficiency, which are dependent on these parameters. We also observe that the current and efficiency caused by temporal and different oscillating forces have maximum and minimum values in different parameter intervals. We conclude that the current or efficiency can be controlled dynamically by adjusting the parameters of entropic barriers and applied force. Project supported by the Funds from Istanbul University (Grant No. 45662).

On the analysis and comparison of conformer-specific essential dynamics upon ligand binding to a protein.

PubMed

Grosso, Marcos; Kalstein, Adrian; Parisi, Gustavo; Roitberg, Adrian E; Fernandez-Alberti, Sebastian

2015-06-28

The native state of a protein consists of an equilibrium of conformational states on an energy landscape rather than existing as a single static state. The co-existence of conformers with different ligand-affinities in a dynamical equilibrium is the basis for the conformational selection model for ligand binding. In this context, the development of theoretical methods that allow us to analyze not only the structural changes but also changes in the fluctuation patterns between conformers will contribute to elucidate the differential properties acquired upon ligand binding. Molecular dynamics simulations can provide the required information to explore these features. Its use in combination with subsequent essential dynamics analysis allows separating large concerted conformational rearrangements from irrelevant fluctuations. We present a novel procedure to define the size and composition of essential dynamics subspaces associated with ligand-bound and ligand-free conformations. These definitions allow us to compare essential dynamics subspaces between different conformers. Our procedure attempts to emphasize the main similarities and differences between the different essential dynamics in an unbiased way. Essential dynamics subspaces associated to conformational transitions can also be analyzed. As a test case, we study the glutaminase interacting protein (GIP), composed of a single PDZ domain. Both GIP ligand-free state and glutaminase L peptide-bound states are analyzed. Our findings concerning the relative changes in the flexibility pattern upon binding are in good agreement with experimental Nuclear Magnetic Resonance data.

On the analysis and comparison of conformer-specific essential dynamics upon ligand binding to a protein

NASA Astrophysics Data System (ADS)

Grosso, Marcos; Kalstein, Adrian; Parisi, Gustavo; Roitberg, Adrian E.; Fernandez-Alberti, Sebastian

2015-06-01

The native state of a protein consists of an equilibrium of conformational states on an energy landscape rather than existing as a single static state. The co-existence of conformers with different ligand-affinities in a dynamical equilibrium is the basis for the conformational selection model for ligand binding. In this context, the development of theoretical methods that allow us to analyze not only the structural changes but also changes in the fluctuation patterns between conformers will contribute to elucidate the differential properties acquired upon ligand binding. Molecular dynamics simulations can provide the required information to explore these features. Its use in combination with subsequent essential dynamics analysis allows separating large concerted conformational rearrangements from irrelevant fluctuations. We present a novel procedure to define the size and composition of essential dynamics subspaces associated with ligand-bound and ligand-free conformations. These definitions allow us to compare essential dynamics subspaces between different conformers. Our procedure attempts to emphasize the main similarities and differences between the different essential dynamics in an unbiased way. Essential dynamics subspaces associated to conformational transitions can also be analyzed. As a test case, we study the glutaminase interacting protein (GIP), composed of a single PDZ domain. Both GIP ligand-free state and glutaminase L peptide-bound states are analyzed. Our findings concerning the relative changes in the flexibility pattern upon binding are in good agreement with experimental Nuclear Magnetic Resonance data.

Genomic Methods for Clinical and Translational Pain Research

PubMed Central

Wang, Dan; Kim, Hyungsuk; Wang, Xiao-Min; Dionne, Raymond

2012-01-01

Pain is a complex sensory experience for which the molecular mechanisms are yet to be fully elucidated. Individual differences in pain sensitivity are mediated by a complex network of multiple gene polymorphisms, physiological and psychological processes, and environmental factors. Here, we present the methods for applying unbiased molecular-genetic approaches, genome-wide association study (GWAS), and global gene expression analysis, to help better understand the molecular basis of pain sensitivity in humans and variable responses to analgesic drugs. PMID:22351080

Using Markov state models to study self-assembly

PubMed Central

Perkett, Matthew R.; Hagan, Michael F.

2014-01-01

Markov state models (MSMs) have been demonstrated to be a powerful method for computationally studying intramolecular processes such as protein folding and macromolecular conformational changes. In this article, we present a new approach to construct MSMs that is applicable to modeling a broad class of multi-molecular assembly reactions. Distinct structures formed during assembly are distinguished by their undirected graphs, which are defined by strong subunit interactions. Spatial inhomogeneities of free subunits are accounted for using a recently developed Gaussian-based signature. Simplifications to this state identification are also investigated. The feasibility of this approach is demonstrated on two different coarse-grained models for virus self-assembly. We find good agreement between the dynamics predicted by the MSMs and long, unbiased simulations, and that the MSMs can reduce overall simulation time by orders of magnitude. PMID:24907984

A Model of the Temporal Dynamics of Knowledge Brokerage in Sustainable Development

ERIC Educational Resources Information Center

Hukkinen, Janne I.

2016-01-01

I develop a conceptual model of the temporal dynamics of knowledge brokerage for sustainable development. Brokerage refers to efforts to make research and policymaking more accessible to each other. The model enables unbiased and systematic consideration of knowledge brokerage as part of policy evolution. The model is theoretically grounded in…

Multiensemble Markov models of molecular thermodynamics and kinetics.

PubMed

Wu, Hao; Paul, Fabian; Wehmeyer, Christoph; Noé, Frank

2016-06-07

We introduce the general transition-based reweighting analysis method (TRAM), a statistically optimal approach to integrate both unbiased and biased molecular dynamics simulations, such as umbrella sampling or replica exchange. TRAM estimates a multiensemble Markov model (MEMM) with full thermodynamic and kinetic information at all ensembles. The approach combines the benefits of Markov state models-clustering of high-dimensional spaces and modeling of complex many-state systems-with those of the multistate Bennett acceptance ratio of exploiting biased or high-temperature ensembles to accelerate rare-event sampling. TRAM does not depend on any rate model in addition to the widely used Markov state model approximation, but uses only fundamental relations such as detailed balance and binless reweighting of configurations between ensembles. Previous methods, including the multistate Bennett acceptance ratio, discrete TRAM, and Markov state models are special cases and can be derived from the TRAM equations. TRAM is demonstrated by efficiently computing MEMMs in cases where other estimators break down, including the full thermodynamics and rare-event kinetics from high-dimensional simulation data of an all-atom protein-ligand binding model.

Multiensemble Markov models of molecular thermodynamics and kinetics

PubMed Central

Wu, Hao; Paul, Fabian; Noé, Frank

2016-01-01

We introduce the general transition-based reweighting analysis method (TRAM), a statistically optimal approach to integrate both unbiased and biased molecular dynamics simulations, such as umbrella sampling or replica exchange. TRAM estimates a multiensemble Markov model (MEMM) with full thermodynamic and kinetic information at all ensembles. The approach combines the benefits of Markov state models—clustering of high-dimensional spaces and modeling of complex many-state systems—with those of the multistate Bennett acceptance ratio of exploiting biased or high-temperature ensembles to accelerate rare-event sampling. TRAM does not depend on any rate model in addition to the widely used Markov state model approximation, but uses only fundamental relations such as detailed balance and binless reweighting of configurations between ensembles. Previous methods, including the multistate Bennett acceptance ratio, discrete TRAM, and Markov state models are special cases and can be derived from the TRAM equations. TRAM is demonstrated by efficiently computing MEMMs in cases where other estimators break down, including the full thermodynamics and rare-event kinetics from high-dimensional simulation data of an all-atom protein–ligand binding model. PMID:27226302

A molecular simulation protocol to avoid sampling redundancy and discover new states.

PubMed

Bacci, Marco; Vitalis, Andreas; Caflisch, Amedeo

2015-05-01

For biomacromolecules or their assemblies, experimental knowledge is often restricted to specific states. Ambiguity pervades simulations of these complex systems because there is no prior knowledge of relevant phase space domains, and sampling recurrence is difficult to achieve. In molecular dynamics methods, ruggedness of the free energy surface exacerbates this problem by slowing down the unbiased exploration of phase space. Sampling is inefficient if dwell times in metastable states are large. We suggest a heuristic algorithm to terminate and reseed trajectories run in multiple copies in parallel. It uses a recent method to order snapshots, which provides notions of "interesting" and "unique" for individual simulations. We define criteria to guide the reseeding of runs from more "interesting" points if they sample overlapping regions of phase space. Using a pedagogical example and an α-helical peptide, the approach is demonstrated to amplify the rate of exploration of phase space and to discover metastable states not found by conventional sampling schemes. Evidence is provided that accurate kinetics and pathways can be extracted from the simulations. The method, termed PIGS for Progress Index Guided Sampling, proceeds in unsupervised fashion, is scalable, and benefits synergistically from larger numbers of replicas. Results confirm that the underlying ideas are appropriate and sufficient to enhance sampling. In molecular simulations, errors caused by not exploring relevant domains in phase space are always unquantifiable and can be arbitrarily large. Our protocol adds to the toolkit available to researchers in reducing these types of errors. This article is part of a Special Issue entitled "Recent developments of molecular dynamics". Copyright © 2014 Elsevier B.V. All rights reserved.

Unbiased reduced density matrices and electronic properties from full configuration interaction quantum Monte Carlo.

PubMed

Overy, Catherine; Booth, George H; Blunt, N S; Shepherd, James J; Cleland, Deidre; Alavi, Ali

2014-12-28

Properties that are necessarily formulated within pure (symmetric) expectation values are difficult to calculate for projector quantum Monte Carlo approaches, but are critical in order to compute many of the important observable properties of electronic systems. Here, we investigate an approach for the sampling of unbiased reduced density matrices within the full configuration interaction quantum Monte Carlo dynamic, which requires only small computational overheads. This is achieved via an independent replica population of walkers in the dynamic, sampled alongside the original population. The resulting reduced density matrices are free from systematic error (beyond those present via constraints on the dynamic itself) and can be used to compute a variety of expectation values and properties, with rapid convergence to an exact limit. A quasi-variational energy estimate derived from these density matrices is proposed as an accurate alternative to the projected estimator for multiconfigurational wavefunctions, while its variational property could potentially lend itself to accurate extrapolation approaches in larger systems.

FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data

NASA Astrophysics Data System (ADS)

Min, Junhong; Vonesch, Cédric; Kirshner, Hagai; Carlini, Lina; Olivier, Nicolas; Holden, Seamus; Manley, Suliana; Ye, Jong Chul; Unser, Michael

2014-04-01

Super resolution microscopy such as STORM and (F)PALM is now a well known method for biological studies at the nanometer scale. However, conventional imaging schemes based on sparse activation of photo-switchable fluorescent probes have inherently slow temporal resolution which is a serious limitation when investigating live-cell dynamics. Here, we present an algorithm for high-density super-resolution microscopy which combines a sparsity-promoting formulation with a Taylor series approximation of the PSF. Our algorithm is designed to provide unbiased localization on continuous space and high recall rates for high-density imaging, and to have orders-of-magnitude shorter run times compared to previous high-density algorithms. We validated our algorithm on both simulated and experimental data, and demonstrated live-cell imaging with temporal resolution of 2.5 seconds by recovering fast ER dynamics.

FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data

PubMed Central

Min, Junhong; Vonesch, Cédric; Kirshner, Hagai; Carlini, Lina; Olivier, Nicolas; Holden, Seamus; Manley, Suliana; Ye, Jong Chul; Unser, Michael

2014-01-01

Super resolution microscopy such as STORM and (F)PALM is now a well known method for biological studies at the nanometer scale. However, conventional imaging schemes based on sparse activation of photo-switchable fluorescent probes have inherently slow temporal resolution which is a serious limitation when investigating live-cell dynamics. Here, we present an algorithm for high-density super-resolution microscopy which combines a sparsity-promoting formulation with a Taylor series approximation of the PSF. Our algorithm is designed to provide unbiased localization on continuous space and high recall rates for high-density imaging, and to have orders-of-magnitude shorter run times compared to previous high-density algorithms. We validated our algorithm on both simulated and experimental data, and demonstrated live-cell imaging with temporal resolution of 2.5 seconds by recovering fast ER dynamics. PMID:24694686

The dynamics of camphor in the cytochrome P450 CYP101D2

PubMed Central

Vohra, Shabana; Musgaard, Maria; Bell, Stephen G; Wong, Luet-Lok; Zhou, Weihong; Biggin, Philip C

2013-01-01

The recent crystal structures of CYP101D2, a cytochrome P450 protein from the oligotrophic bacterium Novosphingobium aromaticivorans DSM12444 revealed that both the native (substrate-free) and camphor-soaked forms have open conformations. Furthermore, two other potential camphor-binding sites were also identified from electron densities in the camphor-soaked structure, one being located in the access channel and the other in a cavity on the surface near the F-helix side of the F-G loop termed the substrate recognition site. These latter sites may be key intermediate positions on the pathway for substrate access to or product egress from the active site. Here, we show via the use of unbiased atomistic molecular dynamics simulations that despite the open conformation of the native and camphor-bound crystal structures, the underlying dynamics of CYP101D2 appear to be very similar to other CYP proteins. Simulations of the native structure demonstrated that the protein is capable of sampling many different conformational substates. At the same time, simulations with the camphor positioned at various locations within the access channel or recognition site show that movement towards the active site or towards bulk solvent can readily occur on a short timescale, thus confirming many previously reported in silico studies using steered molecular dynamics. The simulations also demonstrate how the fluctuations of an aromatic gate appear to control access to the active site. Finally, comparison of camphor-bound simulations with the native simulations suggests that the fluctuations can be of similar level and thus are more representative of the conformational selection model rather than induced fit. PMID:23832606

A molecular dynamics investigation of CDK8/CycC and ligand binding: conformational flexibility and implication in drug discovery

NASA Astrophysics Data System (ADS)

Cholko, Timothy; Chen, Wei; Tang, Zhiye; Chang, Chia-en A.

2018-05-01

Abnormal activity of cyclin-dependent kinase 8 (CDK8) along with its partner protein cyclin C (CycC) is a common feature of many diseases including colorectal cancer. Using molecular dynamics (MD) simulations, this study determined the dynamics of the CDK8-CycC system and we obtained detailed breakdowns of binding energy contributions for four type-I and five type-II CDK8 inhibitors. We revealed system motions and conformational changes that will affect ligand binding, confirmed the essentialness of CycC for inclusion in future computational studies, and provide guidance in development of CDK8 binders. We employed unbiased all-atom MD simulations for 500 ns on twelve CDK8-CycC systems, including apoproteins and protein-ligand complexes, then performed principal component analysis (PCA) and measured the RMSF of key regions to identify protein dynamics. Binding pocket volume analysis identified conformational changes that accompany ligand binding. Next, H-bond analysis, residue-wise interaction calculations, and MM/PBSA were performed to characterize protein-ligand interactions and find the binding energy. We discovered that CycC is vital for maintaining a proper conformation of CDK8 to facilitate ligand binding and that the system exhibits motion that should be carefully considered in future computational work. Surprisingly, we found that motion of the activation loop did not affect ligand binding. Type-I and type-II ligand binding is driven by van der Waals interactions, but electrostatic energy and entropic penalties affect type-II binding as well. Binding of both ligand types affects protein flexibility. Based on this we provide suggestions for development of tighter-binding CDK8 inhibitors and offer insight that can aid future computational studies.

Understanding nucleotide-regulated FtsZ filament dynamics and the monomer assembly switch with large-scale atomistic simulations.

PubMed

Ramírez-Aportela, Erney; López-Blanco, José Ramón; Andreu, José Manuel; Chacón, Pablo

2014-11-04

Bacterial cytoskeletal protein FtsZ assembles in a head-to-tail manner, forming dynamic filaments that are essential for cell division. Here, we study their dynamics using unbiased atomistic molecular simulations from representative filament crystal structures. In agreement with experimental data, we find different filament curvatures that are supported by a nucleotide-regulated hinge motion between consecutive FtsZ monomers. Whereas GTP-FtsZ filaments bend and twist in a preferred orientation, thereby burying the nucleotide, the differently curved GDP-FtsZ filaments exhibit a heterogeneous distribution of open and closed interfaces between monomers. We identify a coordinated Mg(2+) ion as the key structural element in closing the nucleotide site and stabilizing GTP filaments, whereas the loss of the contacts with loop T7 from the next monomer in GDP filaments leads to open interfaces that are more prone to depolymerization. We monitored the FtsZ monomer assembly switch, which involves opening/closing of the cleft between the C-terminal domain and the H7 helix, and observed the relaxation of isolated and filament minus-end monomers into the closed-cleft inactive conformation. This result validates the proposed switch between the low-affinity monomeric closed-cleft conformation and the active open-cleft FtsZ conformation within filaments. Finally, we observed how the antibiotic PC190723 suppresses the disassembly switch and allosterically induces closure of the intermonomer interfaces, thus stabilizing the filament. Our studies provide detailed structural and dynamic insights into modulation of both the intrinsic curvature of the FtsZ filaments and the molecular switch coupled to the high-affinity end-wise association of FtsZ monomers.

Binding of Capsaicin to the TRPV1 Ion Channel.

PubMed

Darré, Leonardo; Domene, Carmen

2015-12-07

Transient receptor potential (TRP) ion channels constitute a notable family of cation channels involved in the ability of an organisms to detect noxious mechanical, thermal, and chemical stimuli that give rise to the perception of pain, taste, and changes in temperature. One of the most experimentally studied agonist of TRP channels is capsaicin, which is responsible for the burning sensation produced when chili pepper is in contact with organic tissues. Thus, understanding how this molecule interacts and regulates TRP channels is essential to high impact pharmacological applications, particularly those related to pain treatment. The recent publication of a three-dimensional structure of the vanilloid receptor 1 (TRPV1) in the absence and presence of capsaicin from single particle electron cryomicroscopy experiments provides the opportunity to explore these questions at the atomic level. In the present work, molecular docking and unbiased and biased molecular dynamics simulations were employed to generate a structural model of the capsaicin-channel complex. In addition, the standard free energy of binding was estimated using alchemical transformations coupled with conformational, translational, and orientational restraints on the ligand. Key binding modes consistent with previous experimental data are identified, and subtle but essential dynamical features of the binding site are characterized. These observations shed some light into how TRPV1 interacts with capsaicin, and may help to refine design parameters for new TRPV1 antagonists, and potentially guide further developments of TRP channel modulators.

Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories

PubMed Central

Donovan, Rory M.; Tapia, Jose-Juan; Sullivan, Devin P.; Faeder, James R.; Murphy, Robert F.; Dittrich, Markus; Zuckerman, Daniel M.

2016-01-01

The long-term goal of connecting scales in biological simulation can be facilitated by scale-agnostic methods. We demonstrate that the weighted ensemble (WE) strategy, initially developed for molecular simulations, applies effectively to spatially resolved cell-scale simulations. The WE approach runs an ensemble of parallel trajectories with assigned weights and uses a statistical resampling strategy of replicating and pruning trajectories to focus computational effort on difficult-to-sample regions. The method can also generate unbiased estimates of non-equilibrium and equilibrium observables, sometimes with significantly less aggregate computing time than would be possible using standard parallelization. Here, we use WE to orchestrate particle-based kinetic Monte Carlo simulations, which include spatial geometry (e.g., of organelles, plasma membrane) and biochemical interactions among mobile molecular species. We study a series of models exhibiting spatial, temporal and biochemical complexity and show that although WE has important limitations, it can achieve performance significantly exceeding standard parallel simulation—by orders of magnitude for some observables. PMID:26845334

Many Specialists for Suppressing Cortical Excitation

PubMed Central

Burkhalter, Andreas

2008-01-01

Cortical computations are critically dependent on GABA-releasing neurons for dynamically balancing excitation with inhibition that is proportional to the overall level of activity. Although it is widely accepted that there are multiple types of interneurons, defining their identities based on qualitative descriptions of morphological, molecular and physiological features has failed to produce a universally accepted ‘parts list’, which is needed to understand the roles that interneurons play in cortical processing. A list of features has been published by the Petilla Interneurons Nomenclature Group, which represents an important step toward an unbiased classification of interneurons. To this end some essential features have recently been studied quantitatively and their association was examined using multidimensional cluster analyses. These studies revealed at least 3 distinct electrophysiological, 6 morphological and 15 molecular phenotypes. This is a conservative estimate of the number of interneuron types, which almost certainly will be revised as more quantitative studies will be performed and similarities will be defined objectively. It is clear that interneurons are organized with physiological attributes representing the most general, molecular characteristics the most detailed and morphological features occupying the middle ground. By themselves, none of these features are sufficient to define classes of interneurons. The challenge will be to determine which features belong together and how cell type-specific feature combinations are genetically specified. PMID:19225588

Human systems immunology: hypothesis-based modeling and unbiased data-driven approaches.

PubMed

Arazi, Arnon; Pendergraft, William F; Ribeiro, Ruy M; Perelson, Alan S; Hacohen, Nir

2013-10-31

Systems immunology is an emerging paradigm that aims at a more systematic and quantitative understanding of the immune system. Two major approaches have been utilized to date in this field: unbiased data-driven modeling to comprehensively identify molecular and cellular components of a system and their interactions; and hypothesis-based quantitative modeling to understand the operating principles of a system by extracting a minimal set of variables and rules underlying them. In this review, we describe applications of the two approaches to the study of viral infections and autoimmune diseases in humans, and discuss possible ways by which these two approaches can synergize when applied to human immunology. Copyright © 2012 Elsevier Ltd. All rights reserved.

Equilibrium denaturation and preferential interactions of an RNA tetraloop with urea

DOE PAGES

Miner, Jacob Carlson; García, Angel Enrique

2017-02-09

Urea is an important organic cosolute with implications in maintaining osmotic stress in cells and differentially stabilizing ensembles of folded biomolecules. We report an equilibrium study of urea-induced denaturation of a hyperstable RNA tetraloop through unbiased replica exchange molecular dynamics. We find that, in addition to destabilizing the folded state, urea smooths the RNA free energy landscape by destabilizing specific configurations, and forming favorable interactions with RNA nucleobases. A linear concentration-dependence of the free energy (m-value) is observed, in agreement with the results of other RNA hairpins and proteins. Additionally, analysis of the hydrogen-bonding and stacking interactions within RNA primarilymore » show temperature-dependence, while interactions between RNA and urea primarily show concentration-dependence. Lastly, our findings provide valuable insight into the effects of urea on RNA folding and describe the thermodynamics of a basic RNA hairpin as a function of solution chemistry.« less

Equilibrium Denaturation and Preferential Interactions of an RNA Tetraloop with Urea.

PubMed

Miner, Jacob C; García, Angel E

2017-04-20

Urea is an important organic cosolute with implications in maintaining osmotic stress in cells and differentially stabilizing ensembles of folded biomolecules. We report an equilibrium study of urea-induced denaturation of a hyperstable RNA tetraloop through unbiased replica exchange molecular dynamics. We find that, in addition to destabilizing the folded state, urea smooths the RNA free energy landscape by destabilizing specific configurations, and forming favorable interactions with RNA nucleobases. A linear concentration-dependence of the free energy (m-value) is observed, in agreement with the results of other RNA hairpins and proteins. Additionally, analysis of the hydrogen-bonding and stacking interactions within RNA primarily show temperature-dependence, while interactions between RNA and urea primarily show concentration-dependence. Our findings provide valuable insight into the effects of urea on RNA folding and describe the thermodynamics of a basic RNA hairpin as a function of solution chemistry.

Adsorption of charged protein residues on an inorganic nanosheet: Computer simulation of LDH interaction with ion channel

NASA Astrophysics Data System (ADS)

Tsukanov, Alexey A.; Psakhie, Sergey G.

2016-08-01

Quasi-two-dimensional and hybrid nanomaterials based on layered double hydroxides (LDH), cationic clays, layered oxyhydroxides and hydroxides of metals possess large specific surface area and strong electrostatic properties with permanent or pH-dependent electric charge. Such nanomaterials may impact cellular electrostatics, changing the ion balance, pH and membrane potential. Selective ion adsorption/exchange may alter the transmembrane electrochemical gradient, disrupting potential-dependent cellular processes. Cellular proteins as a rule have charged residues which can be effectively adsorbed on the surface of layered hydroxide based nanomaterials. The aim of this study is to attempt to shed some light on the possibility and mechanisms of protein "adhesion" an LDH nanosheet and to propose a new direction in anticancer medicine, based on physical impact and strong electrostatics. An unbiased molecular dynamics simulation was performed and the combined process free energy estimation (COPFEE) approach was used.

Equilibrium denaturation and preferential interactions of an RNA tetraloop with urea

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miner, Jacob Carlson; García, Angel Enrique

Urea is an important organic cosolute with implications in maintaining osmotic stress in cells and differentially stabilizing ensembles of folded biomolecules. We report an equilibrium study of urea-induced denaturation of a hyperstable RNA tetraloop through unbiased replica exchange molecular dynamics. We find that, in addition to destabilizing the folded state, urea smooths the RNA free energy landscape by destabilizing specific configurations, and forming favorable interactions with RNA nucleobases. A linear concentration-dependence of the free energy (m-value) is observed, in agreement with the results of other RNA hairpins and proteins. Additionally, analysis of the hydrogen-bonding and stacking interactions within RNA primarilymore » show temperature-dependence, while interactions between RNA and urea primarily show concentration-dependence. Lastly, our findings provide valuable insight into the effects of urea on RNA folding and describe the thermodynamics of a basic RNA hairpin as a function of solution chemistry.« less

Path Integral Metadynamics.

PubMed

Quhe, Ruge; Nava, Marco; Tiwary, Pratyush; Parrinello, Michele

2015-04-14

We develop a new efficient approach for the simulation of static properties of quantum systems using path integral molecular dynamics in combination with metadynamics. We use the isomorphism between a quantum system and a classical one in which a quantum particle is mapped into a ring polymer. A history dependent biasing potential is built as a function of the elastic energy of the isomorphic polymer. This enhances fluctuations in the shape and size of the necklace in a controllable manner and allows escaping deep energy minima in a limited computer time. In this way, we are able to sample high free energy regions and cross barriers, which would otherwise be insurmountable with unbiased methods. This substantially improves the ability of finding the global free energy minimum as well as exploring other metastable states. The performance of the new technique is demonstrated by illustrative applications on model potentials of varying complexity.

Phosphorylation by PINK1 Releases the UBL Domain and Initializes the Conformational Opening of the E3 Ubiquitin Ligase Parkin

PubMed Central

Moussaud-Lamodière, Elisabeth L.; Dourado, Daniel F. A. R.; Flores, Samuel C.; Springer, Wolfdieter

2014-01-01

Loss-of-function mutations in PINK1 or PARKIN are the most common causes of autosomal recessive Parkinson's disease. Both gene products, the Ser/Thr kinase PINK1 and the E3 Ubiquitin ligase Parkin, functionally cooperate in a mitochondrial quality control pathway. Upon stress, PINK1 activates Parkin and enables its translocation to and ubiquitination of damaged mitochondria to facilitate their clearance from the cell. Though PINK1-dependent phosphorylation of Ser65 is an important initial step, the molecular mechanisms underlying the activation of Parkin's enzymatic functions remain unclear. Using molecular modeling, we generated a complete structural model of human Parkin at all atom resolution. At steady state, the Ub ligase is maintained inactive in a closed, auto-inhibited conformation that results from intra-molecular interactions. Evidently, Parkin has to undergo major structural rearrangements in order to unleash its catalytic activity. As a spark, we have modeled PINK1-dependent Ser65 phosphorylation in silico and provide the first molecular dynamics simulation of Parkin conformations along a sequential unfolding pathway that could release its intertwined domains and enable its catalytic activity. We combined free (unbiased) molecular dynamics simulation, Monte Carlo algorithms, and minimal-biasing methods with cell-based high content imaging and biochemical assays. Phosphorylation of Ser65 results in widening of a newly defined cleft and dissociation of the regulatory N-terminal UBL domain. This motion propagates through further opening conformations that allow binding of an Ub-loaded E2 co-enzyme. Subsequent spatial reorientation of the catalytic centers of both enzymes might facilitate the transfer of the Ub moiety to charge Parkin. Our structure-function study provides the basis to elucidate regulatory mechanisms and activity of the neuroprotective Parkin. This may open up new avenues for the development of small molecule Parkin activators through targeted drug design. PMID:25375667

Unbiased, scalable sampling of protein loop conformations from probabilistic priors.

PubMed

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.

Unbiased, scalable sampling of protein loop conformations from probabilistic priors

PubMed Central

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

AN UNBIASED 1.3 mm EMISSION LINE SURVEY OF THE PROTOPLANETARY DISK ORBITING LkCa 15

DOE Office of Scientific and Technical Information (OSTI.GOV)

Punzi, K. M.; Kastner, J. H.; Hily-Blant, P.

2015-06-01

The outer (>30 AU) regions of the dusty circumstellar disk orbiting the ∼2–5 Myr old, actively accreting solar analog LkCa 15 are known to be chemically rich, and the inner disk may host a young protoplanet within its central cavity. To obtain a complete census of the brightest molecular line emission emanating from the LkCa 15 disk over the 210–270 GHz (1.4–1.1 mm) range, we have conducted an unbiased radio spectroscopic survey with the Institute de Radioastronomie Millimétrique (IRAM) 30 m telescope. The survey demonstrates that in this spectral region, the most readily detectable lines are those of CO andmore » its isotopologues {sup 13}CO and C{sup 18}O, as well as HCO{sup +}, HCN, CN, C{sub 2}H, CS, and H{sub 2}CO. All of these species had been previously detected in the LkCa 15 disk; however, the present survey includes the first complete coverage of the CN (2–1) and C{sub 2}H (3–2) hyperfine complexes. Modeling of these emission complexes indicates that the CN and C{sub 2}H either reside in the coldest regions of the disk or are subthermally excited, and that their abundances are enhanced relative to molecular clouds and young stellar object environments. These results highlight the value of unbiased single-dish line surveys in guiding future high-resolution interferometric imaging of disks.« less

Eavesdropping on altered cell-to-cell signaling in cancer by secretome profiling.

PubMed

Klinke, David J

2016-01-01

In the past decade, cumulative clinical experiences with molecular targeted therapies and immunotherapies for cancer have promoted a shift in our conceptual understanding of cancer. This view shifted from viewing solid tumors as a homogeneous mass of malignant cells to viewing tumors as heterogeneous structures that are dynamically shaped by intercellular interactions among the variety of stromal, immune, and malignant cells present within the tumor microenvironment. As in any dynamic system, identifying how cells communicate to maintain homeostasis and how this communication is altered during oncogenesis are key hurdles for developing therapies to restore normal tissue homeostasis. Here, I discuss tissues as dynamic systems, using the mammary gland as an example, and the evolutionary concepts applied to oncogenesis. Drawing from these concepts, I present 2 competing hypotheses for how intercellular communication might be altered during oncogenesis. As an initial test of these competing hypotheses, a recent secretome comparison between normal human mammary and HER2+ breast cancer cell lines suggested that the particular proteins secreted by the malignant cells reflect a convergent evolutionary path associated with oncogenesis in a specific anatomical niche, despite arising in different individuals. Overall, this study illustrates the emerging power of secretome proteomics to probe, in an unbiased way, how intercellular communication changes during oncogenesis.

Eavesdropping on altered cell-to-cell signaling in cancer by secretome profiling

PubMed Central

Klinke, David J

2016-01-01

In the past decade, cumulative clinical experiences with molecular targeted therapies and immunotherapies for cancer have promoted a shift in our conceptual understanding of cancer. This view shifted from viewing solid tumors as a homogeneous mass of malignant cells to viewing tumors as heterogeneous structures that are dynamically shaped by intercellular interactions among the variety of stromal, immune, and malignant cells present within the tumor microenvironment. As in any dynamic system, identifying how cells communicate to maintain homeostasis and how this communication is altered during oncogenesis are key hurdles for developing therapies to restore normal tissue homeostasis. Here, I discuss tissues as dynamic systems, using the mammary gland as an example, and the evolutionary concepts applied to oncogenesis. Drawing from these concepts, I present 2 competing hypotheses for how intercellular communication might be altered during oncogenesis. As an initial test of these competing hypotheses, a recent secretome comparison between normal human mammary and HER2+ breast cancer cell lines suggested that the particular proteins secreted by the malignant cells reflect a convergent evolutionary path associated with oncogenesis in a specific anatomical niche, despite arising in different individuals. Overall, this study illustrates the emerging power of secretome proteomics to probe, in an unbiased way, how intercellular communication changes during oncogenesis. PMID:27308541

Efficient and Unbiased Sampling of Biomolecular Systems in the Canonical Ensemble: A Review of Self-Guided Langevin Dynamics

PubMed Central

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

A Lipid Pathway for Ligand Binding Is Necessary for a Cannabinoid G Protein-coupled Receptor*

PubMed Central

Hurst, Dow P.; Grossfield, Alan; Lynch, Diane L.; Feller, Scott; Romo, Tod D.; Gawrisch, Klaus; Pitman, Michael C.; Reggio, Patricia H.

2010-01-01

Recent isothiocyanate covalent labeling studies have suggested that a classical cannabinoid, (−)-7′-isothiocyanato-11-hydroxy-1′,1′dimethylheptyl-hexahydrocannabinol (AM841), enters the cannabinoid CB2 receptor via the lipid bilayer (Pei, Y., Mercier, R. W., Anday, J. K., Thakur, G. A., Zvonok, A. M., Hurst, D., Reggio, P. H., Janero, D. R., and Makriyannis, A. (2008) Chem. Biol. 15, 1207–1219). However, the sequence of steps involved in such a lipid pathway entry has not yet been elucidated. Here, we test the hypothesis that the endogenous cannabinoid sn-2-arachidonoylglycerol (2-AG) attains access to the CB2 receptor via the lipid bilayer. To this end, we have employed microsecond time scale all-atom molecular dynamics (MD) simulations of the interaction of 2-AG with CB2 via a palmitoyl-oleoyl-phosphatidylcholine lipid bilayer. Results suggest the following: 1) 2-AG first partitions out of bulk lipid at the transmembrane α-helix (TMH) 6/7 interface; 2) 2-AG then enters the CB2 receptor binding pocket by passing between TMH6 and TMH7; 3) the entrance of the 2-AG headgroup into the CB2 binding pocket is sufficient to trigger breaking of the intracellular TMH3/6 ionic lock and the movement of the TMH6 intracellular end away from TMH3; and 4) subsequent to protonation at D3.49/D6.30, further 2-AG entry into the ligand binding pocket results in both a W6.48 toggle switch change and a large influx of water. To our knowledge, this is the first demonstration via unbiased molecular dynamics that a ligand can access the binding pocket of a class A G protein-coupled receptor via the lipid bilayer and the first demonstration via molecular dynamics of G protein-coupled receptor activation triggered by a ligand binding event. PMID:20220143

Comprehensive Mechanistic Analysis of Hits from High-Throughput and Docking Screens against β-Lactamase

PubMed Central

Babaoglu, Kerim; Simeonov, Anton; Irwin, John J.; Nelson, Michael E.; Feng, Brian; Thomas, Craig J.; Cancian, Laura; Costi, M. Paola; Maltby, David A.; Jadhav, Ajit; Inglese, James; Austin, Christopher P.; Shoichet, Brian K.

2009-01-01

High-throughput screening (HTS) is widely used in drug discovery. Especially for screens of unbiased libraries, false positives can dominate “hit lists”; their origins are much debated. Here we determine the mechanism of every active hit from a screen of 70,563 unbiased molecules against β-lactamase using quantitative HTS (qHTS). Of the 1274 initial inhibitors, 95% were detergent-sensitive and were classified as aggregators. Among the 70 remaining were 25 potent, covalent-acting β-lactams. Mass spectra, counter-screens, and crystallography identified 12 as promiscuous covalent inhibitors. The remaining 33 were either aggregators or irreproducible. No specific reversible inhibitors were found. We turned to molecular docking to prioritize molecules from the same library for testing at higher concentrations. Of 16 tested, 2 were modest inhibitors. Subsequent X-ray structures corresponded to the docking prediction. Analog synthesis improved affinity to 8 µM. These results suggest that it may be the physical behavior of organic molecules, not their reactivity, that accounts for most screening artifacts. Structure-based methods may prioritize weak-but-novel chemotypes in unbiased library screens. PMID:18333608

Molecular wires acting as quantum heat ratchets.

PubMed

Zhan, Fei; Li, Nianbei; Kohler, Sigmund; Hänggi, Peter

2009-12-01

We explore heat transfer in molecular junctions between two leads in the absence of a finite net thermal bias. The application of an unbiased time-periodic temperature modulation of the leads entails a dynamical breaking of reflection symmetry, such that a directed heat current may emerge (ratchet effect). In particular, we consider two cases of adiabatically slow driving, namely, (i) periodic temperature modulation of only one lead and (ii) temperature modulation of both leads with an ac driving that contains a second harmonic, thus, generating harmonic mixing. Both scenarios yield sizable directed heat currents, which should be detectable with present techniques. Adding a static thermal bias allows one to compute the heat current-thermal load characteristics, which includes the ratchet effect of negative thermal bias with positive-valued heat flow against the thermal bias, up to the thermal stop load. The ratchet heat flow in turn generates also an electric current. An applied electric stop voltage, yielding effective zero electric current flow, then mimics a solely heat-ratchet-induced thermopower ("ratchet Seebeck effect"), although no net thermal bias is acting. Moreover, we find that the relative phase between the two harmonics in scenario (ii) enables steering the net heat current into a direction of choice.

Occupancy Modeling for Improved Accuracy and Understanding of Pathogen Prevalence and Dynamics

PubMed Central

Colvin, Michael E.; Peterson, James T.; Kent, Michael L.; Schreck, Carl B.

2015-01-01

Most pathogen detection tests are imperfect, with a sensitivity < 100%, thereby resulting in the potential for a false negative, where a pathogen is present but not detected. False negatives in a sample inflate the number of non-detections, negatively biasing estimates of pathogen prevalence. Histological examination of tissues as a diagnostic test can be advantageous as multiple pathogens can be examined and providing important information on associated pathological changes to the host. However, it is usually less sensitive than molecular or microbiological tests for specific pathogens. Our study objectives were to 1) develop a hierarchical occupancy model to examine pathogen prevalence in spring Chinook salmon Oncorhynchus tshawytscha and their distribution among host tissues 2) use the model to estimate pathogen-specific test sensitivities and infection rates, and 3) illustrate the effect of using replicate within host sampling on sample sizes required to detect a pathogen. We examined histological sections of replicate tissue samples from spring Chinook salmon O. tshawytscha collected after spawning for common pathogens seen in this population: Apophallus/echinostome metacercariae, Parvicapsula minibicornis, Nanophyetus salmincola/ metacercariae, and Renibacterium salmoninarum. A hierarchical occupancy model was developed to estimate pathogen and tissue-specific test sensitivities and unbiased estimation of host- and organ-level infection rates. Model estimated sensitivities and host- and organ-level infections rates varied among pathogens and model estimated infection rate was higher than prevalence unadjusted for test sensitivity, confirming that prevalence unadjusted for test sensitivity was negatively biased. The modeling approach provided an analytical approach for using hierarchically structured pathogen detection data from lower sensitivity diagnostic tests, such as histology, to obtain unbiased pathogen prevalence estimates with associated uncertainties. Accounting for test sensitivity using within host replicate samples also required fewer individual fish to be sampled. This approach is useful for evaluating pathogen or microbe community dynamics when test sensitivity is <100%. PMID:25738709

Occupancy modeling for improved accuracy and understanding of pathogen prevalence and dynamics

USGS Publications Warehouse

Colvin, Michael E.; Peterson, James T.; Kent, Michael L.; Schreck, Carl B.

2015-01-01

Most pathogen detection tests are imperfect, with a sensitivity < 100%, thereby resulting in the potential for a false negative, where a pathogen is present but not detected. False negatives in a sample inflate the number of non-detections, negatively biasing estimates of pathogen prevalence. Histological examination of tissues as a diagnostic test can be advantageous as multiple pathogens can be examined and providing important information on associated pathological changes to the host. However, it is usually less sensitive than molecular or microbiological tests for specific pathogens. Our study objectives were to 1) develop a hierarchical occupancy model to examine pathogen prevalence in spring Chinook salmonOncorhynchus tshawytscha and their distribution among host tissues 2) use the model to estimate pathogen-specific test sensitivities and infection rates, and 3) illustrate the effect of using replicate within host sampling on sample sizes required to detect a pathogen. We examined histological sections of replicate tissue samples from spring Chinook salmon O. tshawytscha collected after spawning for common pathogens seen in this population:Apophallus/echinostome metacercariae, Parvicapsula minibicornis, Nanophyetus salmincola/metacercariae, and Renibacterium salmoninarum. A hierarchical occupancy model was developed to estimate pathogen and tissue-specific test sensitivities and unbiased estimation of host- and organ-level infection rates. Model estimated sensitivities and host- and organ-level infections rates varied among pathogens and model estimated infection rate was higher than prevalence unadjusted for test sensitivity, confirming that prevalence unadjusted for test sensitivity was negatively biased. The modeling approach provided an analytical approach for using hierarchically structured pathogen detection data from lower sensitivity diagnostic tests, such as histology, to obtain unbiased pathogen prevalence estimates with associated uncertainties. Accounting for test sensitivity using within host replicate samples also required fewer individual fish to be sampled. This approach is useful for evaluating pathogen or microbe community dynamics when test sensitivity is <100%.

I. Dissociation free energies of drug-receptor systems via non-equilibrium alchemical simulations: a theoretical framework.

PubMed

Procacci, Piero

2016-06-01

In this contribution I critically revise the alchemical reversible approach in the context of the statistical mechanics theory of non-covalent bonding in drug-receptor systems. I show that most of the pitfalls and entanglements for the binding free energy evaluation in computer simulations are rooted in the equilibrium assumption that is implicit in the reversible method. These critical issues can be resolved by using a non-equilibrium variant of the alchemical method in molecular dynamics simulations, relying on the production of many independent trajectories with a continuous dynamical evolution of an externally driven alchemical coordinate, completing the decoupling of the ligand in a matter of a few tens of picoseconds rather than nanoseconds. The absolute binding free energy can be recovered from the annihilation work distributions by applying an unbiased unidirectional free energy estimate, on the assumption that any observed work distribution is given by a mixture of normal distributions, whose components are identical in either direction of the non-equilibrium process, with weights regulated by the Crooks theorem. I finally show that the inherent reliability and accuracy of the unidirectional estimate of the decoupling free energies, based on the production of a few hundreds of non-equilibrium independent sub-nanosecond unrestrained alchemical annihilation processes, is a direct consequence of the funnel-like shape of the free energy surface in molecular recognition. An application of the technique to a real drug-receptor system is presented in the companion paper.

Atomistic Simulations of the pH Induced Functional Rearrangement of Influenza Hemagglutinin

NASA Astrophysics Data System (ADS)

Lin, Xingcheng; Noel, Jeffrey; Wang, Qinghua; Ma, Jianpeng; Onuchic, Jose

Influenza hemagglutinin (HA), a surface glycoprotein responsible for the entry and replication of flu viruses in their host cells, functions by starting a dramatic conformational rearrangement, which leads to a fusion of the viral and endosomal membranes. It has been claimed that a loop-to-coiled-coil transition of the B-loop domain of HA drives the HA-induced membrane fusion. On the lack of dynamical details, however, the microscopic picture for this proposed ``spring-loaded'' movement is missing. To elaborate on the transition of the B-loop, we performed a set of unbiased all-atom molecular dynamics simulations of the full B-loop structure with the CHARMM36 force field. The complete free-energy profile constructed from our simulations reveals a slow transition rate for the B-loop that is incompatible with a downhill process. Additionally, our simulations indicate two potential sources of kinetic traps in the structural switch of the B-loop: Desolvation barriers and non-native secondary structure formation. The slow timescale of the B-loop transition also confirms our previous discovery from simulations using a coarse-grained structure-based model, which identified two competitive pathways both with a slow B-loop transition for HA to guide the membrane fusion.

Subdiffusion in Membrane Permeation of Small Molecules.

PubMed

Chipot, Christophe; Comer, Jeffrey

2016-11-02

Within the solubility-diffusion model of passive membrane permeation of small molecules, translocation of the permeant across the biological membrane is traditionally assumed to obey the Smoluchowski diffusion equation, which is germane for classical diffusion on an inhomogeneous free-energy and diffusivity landscape. This equation, however, cannot accommodate subdiffusive regimes, which have long been recognized in lipid bilayer dynamics, notably in the lateral diffusion of individual lipids. Through extensive biased and unbiased molecular dynamics simulations, we show that one-dimensional translocation of methanol across a pure lipid membrane remains subdiffusive on timescales approaching typical permeation times. Analysis of permeant motion within the lipid bilayer reveals that, in the absence of a net force, the mean squared displacement depends on time as t 0.7 , in stark contrast with the conventional model, which assumes a strictly linear dependence. We further show that an alternate model using a fractional-derivative generalization of the Smoluchowski equation provides a rigorous framework for describing the motion of the permeant molecule on the pico- to nanosecond timescale. The observed subdiffusive behavior appears to emerge from a crossover between small-scale rattling of the permeant around its present position in the membrane and larger-scale displacements precipitated by the formation of transient voids.

An adaptive bias - hybrid MD/kMC algorithm for protein folding and aggregation.

PubMed

Peter, Emanuel K; Shea, Joan-Emma

2017-07-05

In this paper, we present a novel hybrid Molecular Dynamics/kinetic Monte Carlo (MD/kMC) algorithm and apply it to protein folding and aggregation in explicit solvent. The new algorithm uses a dynamical definition of biases throughout the MD component of the simulation, normalized in relation to the unbiased forces. The algorithm guarantees sampling of the underlying ensemble in dependency of one average linear coupling factor 〈α〉 τ . We test the validity of the kinetics in simulations of dialanine and compare dihedral transition kinetics with long-time MD-simulations. We find that for low 〈α〉 τ values, kinetics are in good quantitative agreement. In folding simulations of TrpCage and TrpZip4 in explicit solvent, we also find good quantitative agreement with experimental results and prior MD/kMC simulations. Finally, we apply our algorithm to study growth of the Alzheimer Amyloid Aβ 16-22 fibril by monomer addition. We observe two possible binding modes, one at the extremity of the fibril (elongation) and one on the surface of the fibril (lateral growth), on timescales ranging from ns to 8 μs.

Unbiased Sampling of Globular Lattice Proteins in Three Dimensions

NASA Astrophysics Data System (ADS)

Jacobsen, Jesper Lykke

2008-03-01

We present a Monte Carlo method that allows efficient and unbiased sampling of Hamiltonian walks on a cubic lattice. Such walks are self-avoiding and visit each lattice site exactly once. They are often used as simple models of globular proteins, upon adding suitable local interactions. Our algorithm can easily be equipped with such interactions, but we study here mainly the flexible homopolymer case where each conformation is generated with uniform probability. We argue that the algorithm is ergodic and has dynamical exponent z=0. We then use it to study polymers of size up to 643=262144 monomers. Results are presented for the effective interaction between end points, and the interaction with the boundaries of the system.

Exhaustively sampling peptide adsorption with metadynamics.

PubMed

Deighan, Michael; Pfaendtner, Jim

2013-06-25

Simulating the adsorption of a peptide or protein and obtaining quantitative estimates of thermodynamic observables remains challenging for many reasons. One reason is the dearth of molecular scale experimental data available for validating such computational models. We also lack simulation methodologies that effectively address the dual challenges of simulating protein adsorption: overcoming strong surface binding and sampling conformational changes. Unbiased classical simulations do not address either of these challenges. Previous attempts that apply enhanced sampling generally focus on only one of the two issues, leaving the other to chance or brute force computing. To improve our ability to accurately resolve adsorbed protein orientation and conformational states, we have applied the Parallel Tempering Metadynamics in the Well-Tempered Ensemble (PTMetaD-WTE) method to several explicitly solvated protein/surface systems. We simulated the adsorption behavior of two peptides, LKα14 and LKβ15, onto two self-assembled monolayer (SAM) surfaces with carboxyl and methyl terminal functionalities. PTMetaD-WTE proved effective at achieving rapid convergence of the simulations, whose results elucidated different aspects of peptide adsorption including: binding free energies, side chain orientations, and preferred conformations. We investigated how specific molecular features of the surface/protein interface change the shape of the multidimensional peptide binding free energy landscape. Additionally, we compared our enhanced sampling technique with umbrella sampling and also evaluated three commonly used molecular dynamics force fields.

Unbiased metabolite profiling by liquid chromatography-quadrupole time-of-flight mass spectrometry and multivariate data analysis for herbal authentication: classification of seven Lonicera species flower buds.

PubMed

Gao, Wen; Yang, Hua; Qi, Lian-Wen; Liu, E-Hu; Ren, Mei-Ting; Yan, Yu-Ting; Chen, Jun; Li, Ping

2012-07-06

Plant-based medicines become increasingly popular over the world. Authentication of herbal raw materials is important to ensure their safety and efficacy. Some herbs belonging to closely related species but differing in medicinal properties are difficult to be identified because of similar morphological and microscopic characteristics. Chromatographic fingerprinting is an alternative method to distinguish them. Existing approaches do not allow a comprehensive analysis for herbal authentication. We have now developed a strategy consisting of (1) full metabolic profiling of herbal medicines by rapid resolution liquid chromatography (RRLC) combined with quadrupole time-of-flight mass spectrometry (QTOF MS), (2) global analysis of non-targeted compounds by molecular feature extraction algorithm, (3) multivariate statistical analysis for classification and prediction, and (4) marker compounds characterization. This approach has provided a fast and unbiased comparative multivariate analysis of the metabolite composition of 33-batch samples covering seven Lonicera species. Individual metabolic profiles are performed at the level of molecular fragments without prior structural assignment. In the entire set, the obtained classifier for seven Lonicera species flower buds showed good prediction performance and a total of 82 statistically different components were rapidly obtained by the strategy. The elemental compositions of discriminative metabolites were characterized by the accurate mass measurement of the pseudomolecular ions and their chemical types were assigned by the MS/MS spectra. The high-resolution, comprehensive and unbiased strategy for metabolite data analysis presented here is powerful and opens the new direction of authentication in herbal analysis. Copyright © 2012 Elsevier B.V. All rights reserved.

Unbiased reduced density matrices and electronic properties from full configuration interaction quantum Monte Carlo

DOE Office of Scientific and Technical Information (OSTI.GOV)

Overy, Catherine; Blunt, N. S.; Shepherd, James J.

2014-12-28

Properties that are necessarily formulated within pure (symmetric) expectation values are difficult to calculate for projector quantum Monte Carlo approaches, but are critical in order to compute many of the important observable properties of electronic systems. Here, we investigate an approach for the sampling of unbiased reduced density matrices within the full configuration interaction quantum Monte Carlo dynamic, which requires only small computational overheads. This is achieved via an independent replica population of walkers in the dynamic, sampled alongside the original population. The resulting reduced density matrices are free from systematic error (beyond those present via constraints on the dynamicmore » itself) and can be used to compute a variety of expectation values and properties, with rapid convergence to an exact limit. A quasi-variational energy estimate derived from these density matrices is proposed as an accurate alternative to the projected estimator for multiconfigurational wavefunctions, while its variational property could potentially lend itself to accurate extrapolation approaches in larger systems.« less

Intrinsic Atomic Orbitals: An Unbiased Bridge between Quantum Theory and Chemical Concepts.

PubMed

Knizia, Gerald

2013-11-12

Modern quantum chemistry can make quantitative predictions on an immense array of chemical systems. However, the interpretation of those predictions is often complicated by the complex wave function expansions used. Here we show that an exceptionally simple algebraic construction allows for defining atomic core and valence orbitals, polarized by the molecular environment, which can exactly represent self-consistent field wave functions. This construction provides an unbiased and direct connection between quantum chemistry and empirical chemical concepts, and can be used, for example, to calculate the nature of bonding in molecules, in chemical terms, from first principles. In particular, we find consistency with electronegativities (χ), C 1s core-level shifts, resonance substituent parameters (σR), Lewis structures, and oxidation states of transition-metal complexes.

Chemical & Biological Point Detection Decontamination

DTIC Science & Technology

2002-04-01

high priority in biological defense. Research on multivalent assays is also ongoing. Biased libraries, generated from immunized animals, or unbiased ...2003 TBD decontamination and modeling and simulation I I The Chem-Bio Point Detection Roadmap The summary level updated and expanded Bio Point... Molecular Imprinted Polymer Sensor, Dendrimer-based Antibody Assays, Pyrolysis-GC-ion mobility spectrometry, and surface enhanced Raman spectroscopy. Data

Unbiased water and methanol maser surveys of NGC 1333

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lyo, A-Ran; Kim, Jongsoo; Byun, Do-Young

2014-11-01

We present the results of unbiased 22 GHz H{sub 2}O water and 44 GHz class I CH{sub 3}OH methanol maser surveys in the central 7' × 10' area of NGC 1333 and two additional mapping observations of a 22 GHz water maser in a ∼3' × 3' area of the IRAS4A region. In the 22 GHz water maser survey of NGC 1333 with a sensitivity of σ ∼ 0.3 Jy, we confirmed the detection of masers toward H{sub 2}O(B) in the region of HH 7-11 and IRAS4B. We also detected new water masers located ∼20'' away in the western directionmore » of IRAS4B or ∼25'' away in the southern direction of IRAS4A. We could not, however, find young stellar objects or molecular outflows associated with them. They showed two different velocity components of ∼0 and ∼16 km s{sup –1}, which are blue- and redshifted relative to the adopted systemic velocity of ∼7 km s{sup –1} for NGC 1333. They also showed time variabilities in both intensity and velocity from multi-epoch observations and an anti-correlation between the intensities of the blue- and redshifted velocity components. We suggest that the unidentified power source of these masers might be found in the earliest evolutionary stage of star formation, before the onset of molecular outflows. Finding this kind of water maser is only possible through an unbiased blind survey. In the 44 GHz methanol maser survey with a sensitivity of σ ∼ 0.5 Jy, we confirmed masers toward IRAS4A2 and the eastern shock region of IRAS2A. Both sources are also detected in 95 and 132 GHz methanol maser lines. In addition, we had new detections of methanol masers at 95 and 132 GHz toward IRAS4B. In terms of the isotropic luminosity, we detected methanol maser sources brighter than ∼5 × 10{sup 25} erg s{sup –1} from our unbiased survey.« less

Synergy between NMR measurements and MD simulations of protein/RNA complexes: application to the RRMs, the most common RNA recognition motifs

PubMed Central

Krepl, Miroslav; Cléry, Antoine; Blatter, Markus; Allain, Frederic H.T.; Sponer, Jiri

2016-01-01

RNA recognition motif (RRM) proteins represent an abundant class of proteins playing key roles in RNA biology. We present a joint atomistic molecular dynamics (MD) and experimental study of two RRM-containing proteins bound with their single-stranded target RNAs, namely the Fox-1 and SRSF1 complexes. The simulations are used in conjunction with NMR spectroscopy to interpret and expand the available structural data. We accumulate more than 50 μs of simulations and show that the MD method is robust enough to reliably describe the structural dynamics of the RRM–RNA complexes. The simulations predict unanticipated specific participation of Arg142 at the protein–RNA interface of the SRFS1 complex, which is subsequently confirmed by NMR and ITC measurements. Several segments of the protein–RNA interface may involve competition between dynamical local substates rather than firmly formed interactions, which is indirectly consistent with the primary NMR data. We demonstrate that the simulations can be used to interpret the NMR atomistic models and can provide qualified predictions. Finally, we propose a protocol for ‘MD-adapted structure ensemble’ as a way to integrate the simulation predictions and expand upon the deposited NMR structures. Unbiased μs-scale atomistic MD could become a technique routinely complementing the NMR measurements of protein–RNA complexes. PMID:27193998

An Atomistic View of Amyloidogenic Self-assembly: Structure and Dynamics of Heterogeneous Conformational States in the Pre-nucleation Phase

PubMed Central

Matthes, Dirk; Gapsys, Vytautas; Brennecke, Julian T.; de Groot, Bert L.

2016-01-01

The formation of well-defined filamentous amyloid structures involves a polydisperse collection of oligomeric states for which relatively little is known in terms of structural organization. Here we use extensive, unbiased explicit solvent molecular dynamics (MD) simulations to investigate the structural and dynamical features of oligomeric aggregates formed by a number of highly amyloidogenic peptides at atomistic resolution on the μs time scale. A consensus approach has been adopted to analyse the simulations in multiple force fields, yielding an in-depth characterization of pre-fibrillar oligomers and their global and local structure properties. A collision cross section analysis revealed structurally heterogeneous aggregate ensembles for the individual oligomeric states that lack a single defined quaternary structure during the pre-nucleation phase. To gain insight into the conformational space sampled in early aggregates, we probed their substructure and found emerging β-sheet subunit layers and a multitude of ordered intermolecular β-structure motifs with growing aggregate size. Among those, anti-parallel out-of-register β-strands compatible with toxic β-barrel oligomers were particularly prevalent already in smaller aggregates and formed prior to ordered fibrillar structure elements. Notably, also distinct fibril-like conformations emerged in the oligomeric state and underscore the notion that pre-nucleated oligomers serve as a critical intermediate step on-pathway to fibrils. PMID:27616019

Exploring the Dynamics of Propeller Loops in Human Telomeric DNA Quadruplexes Using Atomistic Simulations.

PubMed

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.

Exploring the Dynamics of Propeller Loops in Human Telomeric DNA Quadruplexes Using Atomistic Simulations

PubMed Central

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

Method to manage integration error in the Green-Kubo method.

PubMed

Oliveira, Laura de Sousa; Greaney, P Alex

2017-02-01

The Green-Kubo method is a commonly used approach for predicting transport properties in a system from equilibrium molecular dynamics simulations. The approach is founded on the fluctuation dissipation theorem and relates the property of interest to the lifetime of fluctuations in its thermodynamic driving potential. For heat transport, the lattice thermal conductivity is related to the integral of the autocorrelation of the instantaneous heat flux. A principal source of error in these calculations is that the autocorrelation function requires a long averaging time to reduce remnant noise. Integrating the noise in the tail of the autocorrelation function becomes conflated with physically important slow relaxation processes. In this paper we present a method to quantify the uncertainty on transport properties computed using the Green-Kubo formulation based on recognizing that the integrated noise is a random walk, with a growing envelope of uncertainty. By characterizing the noise we can choose integration conditions to best trade off systematic truncation error with unbiased integration noise, to minimize uncertainty for a given allocation of computational resources.

Mechanisms of passive ion permeation through lipid bilayers

PubMed Central

Tepper, Harald L.; Voth, Gregory A.

2008-01-01

Multi-State Empirical Valence Bond and classical Molecular Dynamics simulations were used to explore mechanisms for passive ion leakage through a dimyristoyl phosphatidylcholine (DMPC) lipid bilayer. In accordance with a previous study on proton leakage, it was found that the permeation mechanism must be a highly concerted one, in which ion, solvent and membrane coordinates are coupled. The presence of the ion itself significantly alters the response of those coordinates, suggesting that simulations of transmembrane water structures without explicit inclusion of the ionic solute are insufficient for elucidating transition mechanisms. The properties of H+, Na+, OH-, and bare water molecules in the membrane interior were compared, both by biased sampling techniques and by constructing complete and unbiased transition paths. It was found that the anomalous difference in leakage rates between protons and other cations can be largely explained by charge delocalization effects, rather than the usual kinetic picture (Grotthuss hopping of the proton). Permeability differences between anions and cations through PC bilayers are correlated with suppression of favorable membrane breathing modes by cations. PMID:17048962

Automated generation of radical species in crystalline carbohydrate using ab initio MD simulations.

PubMed

Aalbergsjø, Siv G; Pauwels, Ewald; Van Yperen-De Deyne, Andy; Van Speybroeck, Veronique; Sagstuen, Einar

2014-08-28

As the chemical structures of radiation damaged molecules may differ greatly from their undamaged counterparts, investigation and description of radiation damaged structures is commonly biased by the researcher. Radical formation from ionizing radiation in crystalline α-l-rhamnose monohydrate has been investigated using a new method where the selection of radical structures is unbiased by the researcher. The method is based on using ab initio molecular dynamics (MD) studies to investigate how ionization damage can form, change and move. Diversity in the radical production is gained by using different points on the potential energy surface of the intact crystal as starting points for the ionizations and letting the initial velocities of the nuclei after ionization be generated randomly. 160 ab initio MD runs produced 12 unique radical structures for investigation. Out of these, 7 of the potential products have never previously been discussed, and 3 products are found to match with radicals previously observed by electron magnetic resonance experiments.

Method to manage integration error in the Green-Kubo method

NASA Astrophysics Data System (ADS)

Oliveira, Laura de Sousa; Greaney, P. Alex

2017-02-01

The Green-Kubo method is a commonly used approach for predicting transport properties in a system from equilibrium molecular dynamics simulations. The approach is founded on the fluctuation dissipation theorem and relates the property of interest to the lifetime of fluctuations in its thermodynamic driving potential. For heat transport, the lattice thermal conductivity is related to the integral of the autocorrelation of the instantaneous heat flux. A principal source of error in these calculations is that the autocorrelation function requires a long averaging time to reduce remnant noise. Integrating the noise in the tail of the autocorrelation function becomes conflated with physically important slow relaxation processes. In this paper we present a method to quantify the uncertainty on transport properties computed using the Green-Kubo formulation based on recognizing that the integrated noise is a random walk, with a growing envelope of uncertainty. By characterizing the noise we can choose integration conditions to best trade off systematic truncation error with unbiased integration noise, to minimize uncertainty for a given allocation of computational resources.

Direct simulation of amphiphilic nanoparticle mediated membrane interactions

NASA Astrophysics Data System (ADS)

Tahir, Mukarram; Alexander-Katz, Alfredo

Membrane fusion is a critical step in the transport of biological cargo through membrane-bound compartments like vesicles. Membrane proteins that alleviate energy barriers for initial stalk formation and eventual rupture of the hemifusion intermediate during fusion generally assist this process. Gold nanoparticles functionalized with a combination of hydrophobic and hydrophilic alkanethiol ligands have recently been shown to induce membrane re-arrangements that are similar to those associated with these fusion proteins. In this work, we utilize molecular dynamics simulation to systematically design nanoparticles that exhibit targeted interactions with membranes. We introduce a method for rapidly parameterizing nanoparticle topology for the MARTINI biomolecular force field to permit long timescale simulation of their interactions with lipid bilayers. We leverage this model to investigate how ligand chemistry governs the nanoparticle's insertion efficacy and the perturbations it generates in the membrane environment. We further demonstrate through unbiased simulations that these nanoparticles can direct the fusion of lipid assemblies such as micelles and vesicles in a manner that mimics the function of biological fusion peptides and SNARE proteins.

FOREST Unbiased Galactic plane Imaging survey with the Nobeyama 45 m telescope (FUGIN): Molecular clouds toward W ; possible evidence for a cloud-cloud collision triggering O star formation

NASA Astrophysics Data System (ADS)

Kohno, Mikito; Torii, Kazufumi; Tachihara, Kengo; Umemoto, Tomofumi; Minamidani, Tetsuhiro; Nishimura, Atsushi; Fujita, Shinji; Matsuo, Mitsuhiro; Yamagishi, Mitsuyoshi; Tsuda, Yuya; Kuriki, Mika; Kuno, Nario; Ohama, Akio; Hattori, Yusuke; Sano, Hidetoshi; Yamamoto, Hiroaki; Fukui, Yasuo

2018-05-01

We observed molecular clouds in the W 33 high-mass star-forming region associated with compact and extended H II regions using the NANTEN2 telescope as well as the Nobeyama 45 m telescope in the J = 1-0 transitions of 12CO, 13CO, and C18O as part of the FOREST Unbiased Galactic plane Imaging survey with the Nobeyama 45 m telescope (FUGIN) legacy survey. We detected three velocity components at 35 km s-1, 45 km s-1, and 58 km s-1. The 35 km s-1 and 58 km s-1 clouds are likely to be physically associated with W 33 because of the enhanced 12CO J = 3-2 to J = 1-0 intensity ratio as R_3-2/1-0 > 1.0 due to the ultraviolet irradiation by OB stars, and morphological correspondence between the distributions of molecular gas and the infrared and radio continuum emissions excited by high-mass stars. The two clouds show complementary distributions around W 33. The velocity separation is too large to be gravitationally bound, and yet not explained by expanding motion by stellar feedback. Therefore, we discuss whether a cloud-cloud collision scenario likely explains the high-mass star formation in W 33.

Particle infectivity of HIV-1 full-length genome infectious molecular clones in a subtype C heterosexual transmission pair following high fidelity amplification and unbiased cloning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deymier, Martin J., E-mail: mdeymie@emory.edu; Claiborne, Daniel T., E-mail: dclaibo@emory.edu; Ende, Zachary, E-mail: zende@emory.edu

The high genetic diversity of HIV-1 impedes high throughput, large-scale sequencing and full-length genome cloning by common restriction enzyme based methods. Applying novel methods that employ a high-fidelity polymerase for amplification and an unbiased fusion-based cloning strategy, we have generated several HIV-1 full-length genome infectious molecular clones from an epidemiologically linked transmission pair. These clones represent the transmitted/founder virus and phylogenetically diverse non-transmitted variants from the chronically infected individual's diverse quasispecies near the time of transmission. We demonstrate that, using this approach, PCR-induced mutations in full-length clones derived from their cognate single genome amplicons are rare. Furthermore, all eight non-transmittedmore » genomes tested produced functional virus with a range of infectivities, belying the previous assumption that a majority of circulating viruses in chronic HIV-1 infection are defective. Thus, these methods provide important tools to update protocols in molecular biology that can be universally applied to the study of human viral pathogens. - Highlights: • Our novel methodology demonstrates accurate amplification and cloning of full-length HIV-1 genomes. • A majority of plasma derived HIV variants from a chronically infected individual are infectious. • The transmitted/founder was more infectious than the majority of the variants from the chronically infected donor.« less

FOREST Unbiased Galactic plane Imaging survey with the Nobeyama 45 m telescope (FUGIN): Molecular clouds toward W 33; possible evidence for a cloud-cloud collision triggering O star formation

NASA Astrophysics Data System (ADS)

Kohno, Mikito; Torii, Kazufumi; Tachihara, Kengo; Umemoto, Tomofumi; Minamidani, Tetsuhiro; Nishimura, Atsushi; Fujita, Shinji; Matsuo, Mitsuhiro; Yamagishi, Mitsuyoshi; Tsuda, Yuya; Kuriki, Mika; Kuno, Nario; Ohama, Akio; Hattori, Yusuke; Sano, Hidetoshi; Yamamoto, Hiroaki; Fukui, Yasuo

2018-01-01

We observed molecular clouds in the W 33 high-mass star-forming region associated with compact and extended H II regions using the NANTEN2 telescope as well as the Nobeyama 45 m telescope in the J = 1-0 transitions of 12CO, 13CO, and C18O as part of the FOREST Unbiased Galactic plane Imaging survey with the Nobeyama 45 m telescope (FUGIN) legacy survey. We detected three velocity components at 35 km s-1, 45 km s-1, and 58 km s-1. The 35 km s-1 and 58 km s-1 clouds are likely to be physically associated with W 33 because of the enhanced 12CO J = 3-2 to J = 1-0 intensity ratio as R3-2/1-0 > 1.0 due to the ultraviolet irradiation by OB stars, and morphological correspondence between the distributions of molecular gas and the infrared and radio continuum emissions excited by high-mass stars. The two clouds show complementary distributions around W 33. The velocity separation is too large to be gravitationally bound, and yet not explained by expanding motion by stellar feedback. Therefore, we discuss whether a cloud-cloud collision scenario likely explains the high-mass star formation in W 33.

FOREST Unbiased Galactic plane Imaging survey with the Nobeyama 45 m telescope (FUGIN): Molecular clouds toward W 33; possible evidence for a cloud-cloud collision triggering O star formation

NASA Astrophysics Data System (ADS)

Kohno, Mikito; Torii, Kazufumi; Tachihara, Kengo; Umemoto, Tomofumi; Minamidani, Tetsuhiro; Nishimura, Atsushi; Fujita, Shinji; Matsuo, Mitsuhiro; Yamagishi, Mitsuyoshi; Tsuda, Yuya; Kuriki, Mika; Kuno, Nario; Ohama, Akio; Hattori, Yusuke; Sano, Hidetoshi; Yamamoto, Hiroaki; Fukui, Yasuo

2018-05-01

We observed molecular clouds in the W 33 high-mass star-forming region associated with compact and extended H II regions using the NANTEN2 telescope as well as the Nobeyama 45 m telescope in the J = 1-0 transitions of 12CO, 13CO, and C18O as part of the FOREST Unbiased Galactic plane Imaging survey with the Nobeyama 45 m telescope (FUGIN) legacy survey. We detected three velocity components at 35 km s-1, 45 km s-1, and 58 km s-1. The 35 km s-1 and 58 km s-1 clouds are likely to be physically associated with W 33 because of the enhanced 12CO J = 3-2 to J = 1-0 intensity ratio as R_3-2/1-0} > 1.0 due to the ultraviolet irradiation by OB stars, and morphological correspondence between the distributions of molecular gas and the infrared and radio continuum emissions excited by high-mass stars. The two clouds show complementary distributions around W 33. The velocity separation is too large to be gravitationally bound, and yet not explained by expanding motion by stellar feedback. Therefore, we discuss whether a cloud-cloud collision scenario likely explains the high-mass star formation in W 33.

The Cohesive Population Genetics of Molecular Drive

PubMed Central

Ohta, Tomoko; Dover, Gabriel A.

1984-01-01

The long-term population genetics of multigene families is influenced by several biased and unbiased mechanisms of nonreciprocal exchanges (gene conversion, unequal exchanges, transposition) between member genes, often distributed on several chromosomes. These mechanisms cause fluctuations in the copy number of variant genes in an individual and lead to a gradual replacement of an original family of n genes (A) in N number of individuals by a variant gene (a). The process for spreading a variant gene through a family and through a population is called molecular drive. Consideration of the known slow rates of nonreciprocal exchanges predicts that the population variance in the copy number of gene a per individual is small at any given generation during molecular drive. Genotypes at a given generation are expected only to range over a small section of all possible genotypes from one extreme (n number of A) to the other (n number of a). A theory is developed for estimating the size of the population variance by using the concept of identity coefficients. In particular, the variance in the course of spreading of a single mutant gene of a multigene family was investigated in detail, and the theory of identity coefficients at the state of steady decay of genetic variability proved to be useful. Monte Carlo simulations and numerical analysis based on realistic rates of exchange in families of known size reveal the correctness of the theoretical prediction and also assess the effect of bias in turnover. The population dynamics of molecular drive in gradually increasing the mean copy number of a variant gene without the generation of a large variance (population cohesion) is of significance regarding potential interactions between natural selection and molecular drive. PMID:6500260

The cohesive population genetics of molecular drive.

PubMed

Ohta, T; Dover, G A

1984-10-01

The long-term population genetics of multigene families is influenced by several biased and unbiased mechanisms of nonreciprocal exchanges (gene conversion, unequal exchanges, transposition) between member genes, often distributed on several chromosomes. These mechanisms cause fluctuations in the copy number of variant genes in an individual and lead to a gradual replacement of an original family of n genes (A) in N number of individuals by a variant gene (a). The process for spreading a variant gene through a family and through a population is called molecular drive. Consideration of the known slow rates of nonreciprocal exchanges predicts that the population variance in the copy number of gene a per individual is small at any given generation during molecular drive. Genotypes at a given generation are expected only to range over a small section of all possible genotypes from one extreme (n number of A) to the other (n number of a). A theory is developed for estimating the size of the population variance by using the concept of identity coefficients. In particular, the variance in the course of spreading of a single mutant gene of a multigene family was investigated in detail, and the theory of identity coefficients at the state of steady decay of genetic variability proved to be useful. Monte Carlo simulations and numerical analysis based on realistic rates of exchange in families of known size reveal the correctness of the theoretical prediction and also assess the effect of bias in turnover. The population dynamics of molecular drive in gradually increasing the mean copy number of a variant gene without the generation of a large variance (population cohesion) is of significance regarding potential interactions between natural selection and molecular drive.

Microsecond simulations of the folding/unfolding thermodynamics of the Trp-cage mini protein

PubMed Central

Day, Ryan; Paschek, Dietmar; Garcia, Angel E.

2012-01-01

We study the unbiased folding/unfolding thermodynamics of the Trp-cage miniprotein using detailed molecular dynamics simulations of an all-atom model of the protein in explicit solvent, using the Amberff99SB force field. Replica-exchange molecular dynamics (REMD) simulations are used to sample the protein ensembles over a broad range of temperatures covering the folded and unfolded states, and at two densities. The obtained ensembles are shown to reach equilibrium in the 1 μs per replica timescale. The total simulation time employed in the calculations exceeds 100 μs. Ensemble averages of the fraction folded, pressure, and energy differences between the folded and unfolded states as a function of temperature are used to model the free energy of the folding transition, ΔG(P,T), over the whole region of temperature and pressures sampled in the simulations. The ΔG(P,T) diagram describes an ellipse over the range of temperatures and pressures sampled, predicting that the system can undergo pressure induced unfolding and cold denaturation at low temperatures and high pressures, and unfolding at low pressures and high temperatures. The calculated free energy function exhibits remarkably good agreement with the experimental folding transition temperature (Tf = 321 K), free energy and specific heat changes. However, changes in enthalpy and entropy are significantly different than the experimental values. We speculate that these differences may be due to the simplicity of the semi-empirical force field used in the simulations and that more elaborate force fields may be required to describe appropriately the thermodynamics of proteins. PMID:20408169

Network representations of immune system complexity

PubMed Central

Subramanian, Naeha; Torabi-Parizi, Parizad; Gottschalk, Rachel A.; Germain, Ronald N.; Dutta, Bhaskar

2015-01-01

The mammalian immune system is a dynamic multi-scale system composed of a hierarchically organized set of molecular, cellular and organismal networks that act in concert to promote effective host defense. These networks range from those involving gene regulatory and protein-protein interactions underlying intracellular signaling pathways and single cell responses to increasingly complex networks of in vivo cellular interaction, positioning and migration that determine the overall immune response of an organism. Immunity is thus not the product of simple signaling events but rather non-linear behaviors arising from dynamic, feedback-regulated interactions among many components. One of the major goals of systems immunology is to quantitatively measure these complex multi-scale spatial and temporal interactions, permitting development of computational models that can be used to predict responses to perturbation. Recent technological advances permit collection of comprehensive datasets at multiple molecular and cellular levels while advances in network biology support representation of the relationships of components at each level as physical or functional interaction networks. The latter facilitate effective visualization of patterns and recognition of emergent properties arising from the many interactions of genes, molecules, and cells of the immune system. We illustrate the power of integrating ‘omics’ and network modeling approaches for unbiased reconstruction of signaling and transcriptional networks with a focus on applications involving the innate immune system. We further discuss future possibilities for reconstruction of increasingly complex cellular and organism-level networks and development of sophisticated computational tools for prediction of emergent immune behavior arising from the concerted action of these networks. PMID:25625853

Biased and unbiased strategies to identify biologically active small molecules.

PubMed

Abet, Valentina; Mariani, Angelica; Truscott, Fiona R; Britton, Sébastien; Rodriguez, Raphaël

2014-08-15

Small molecules are central players in chemical biology studies. They promote the perturbation of cellular processes underlying diseases and enable the identification of biological targets that can be validated for therapeutic intervention. Small molecules have been shown to accurately tune a single function of pluripotent proteins in a reversible manner with exceptional temporal resolution. The identification of molecular probes and drugs remains a worthy challenge that can be addressed by the use of biased and unbiased strategies. Hypothesis-driven methodologies employs a known biological target to synthesize complementary hits while discovery-driven strategies offer the additional means of identifying previously unanticipated biological targets. This review article provides a general overview of recent synthetic frameworks that gave rise to an impressive arsenal of biologically active small molecules with unprecedented cellular mechanisms. Copyright © 2014. Published by Elsevier Ltd.

Neosphincter surgery for fecal incontinence: a critical and unbiased review of the relevant literature.

PubMed

Belyaev, Orlin; Müller, Christophe; Uhl, Waldemar

2006-01-01

Up until about 15 years ago the only realistic option for end-stage fecal incontinence was the creation of a permanent stoma. There have since been several developments. Dynamic graciloplasty (DGP) and artificial bowel sphincter (ABS) are well-established surgical techniques, which offer the patient a chance for continence restoration and improved quality of life; however, they are unfortunately associated with high morbidity and low success rates. Several trials have been done in an attempt to clarify the advantages and disadvantages of these methods and define their place in the second-line treatment of severe, refractory fecal incontinence. This review presents a critical and unbiased overview of the current status of neosphincter surgery according to the available data in the world literature.

Kinetics of Huperzine A Dissociation from Acetylcholinesterase via Multiple Unbinding Pathways.

PubMed

Rydzewski, J; Jakubowski, R; Nowak, W; Grubmüller, H

2018-06-12

The dissociation of huperzine A (hupA) from Torpedo californica acetylcholinesterase ( TcAChE) was investigated by 4 μs unbiased and biased all-atom molecular dynamics (MD) simulations in explicit solvent. We performed our study using memetic sampling (MS) for the determination of reaction pathways (RPs), metadynamics to calculate free energy, and maximum-likelihood estimation (MLE) to recover kinetic rates from unbiased MD simulations. Our simulations suggest that the dissociation of hupA occurs mainly via two RPs: a front door along the axis of the active-site gorge (pwf) and through a new transient side door (pws), i.e., formed by the Ω-loop (residues 67-94 of TcAChE). An analysis of the inhibitor unbinding along the RPs suggests that pws is opened transiently after hupA and the Ω-loop reach a low free-energy transition state characterized by the orientation of the pyridone group of the inhibitor directed toward the Ω-loop plane. Unlike pws, pwf does not require large structural changes in TcAChE to be accessible. The estimated free energies and rates agree well with available experimental data. The dissociation rates along the unbinding pathways are similar, suggesting that the dissociation of hupA along pws is likely to be relevant. This indicates that perturbations to hupA- TcAChE interactions could potentially induce pathway hopping. In summary, our results characterize the slow-onset inhibition of TcAChE by hupA, which may provide the structural and energetic bases for the rational design of the next-generation slow-onset inhibitors with optimized pharmacokinetic properties for the treatment of Alzheimer's disease.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sensoy, Ozge; Weinstein, Harel

Helix-8 (Hx8) is a structurally conserved amphipathic helical motif in class-A GPCRs, adjacent to the C-terminal sequence that is responsible for PDZ-domain-recognition. The Hx8 segment in the dopamine D2 receptor (D2R) constitutes the C-terminal segment and we investigate its role in the function of D2R by studying the interaction with the PDZ-containing GIPC1 using homology models based on the X-ray structures of very closely related analogs: the D3R for the D2R model, and the PDZ domain of GIPC2 for GIPC1–PDZ. The mechanism of this interaction was investigated with all-atom unbiased molecular dynamics (MD) simulations that reveal the role of themore » membrane in maintaining the helical fold of Hx8, and with biased MD simulations to elucidate the energy drive for the interaction with the GIPC1–PDZ. We found that it becomes more favorable energetically for Hx8 to adopt the extended conformation observed in all PDZ–ligand complexes when it moves away from the membrane, and that C-terminus palmitoylation of D2R enhanced membrane penetration by the Hx8 backbone. De-palmitoylation enables Hx8 to move out into the aqueous environment for interaction with the PDZ domain. All-atom unbiased MD simulations of the full D2R–GIPC1-PDZ complex in sphingolipid/cholesterol membranes show that the D2R carboxyl C-terminus samples the region of the conserved GFGL motif located on the carboxylate-binding loop of the GIPC1–PDZ, and the entire complex distances itself from the membrane interface. Altogether, these results outline a likely mechanism of Hx8 involvement in the interaction of the GPCR with PDZ-domains in the course of signaling.« less

Markov State Models Provide Insights into Dynamic Modulation of Protein Function

PubMed Central

2015-01-01

Conspectus Protein function is inextricably linked to protein dynamics. As we move from a static structural picture to a dynamic ensemble view of protein structure and function, novel computational paradigms are required for observing and understanding conformational dynamics of proteins and its functional implications. In principle, molecular dynamics simulations can provide the time evolution of atomistic models of proteins, but the long time scales associated with functional dynamics make it difficult to observe rare dynamical transitions. The issue of extracting essential functional components of protein dynamics from noisy simulation data presents another set of challenges in obtaining an unbiased understanding of protein motions. Therefore, a methodology that provides a statistical framework for efficient sampling and a human-readable view of the key aspects of functional dynamics from data analysis is required. The Markov state model (MSM), which has recently become popular worldwide for studying protein dynamics, is an example of such a framework. In this Account, we review the use of Markov state models for efficient sampling of the hierarchy of time scales associated with protein dynamics, automatic identification of key conformational states, and the degrees of freedom associated with slow dynamical processes. Applications of MSMs for studying long time scale phenomena such as activation mechanisms of cellular signaling proteins has yielded novel insights into protein function. In particular, from MSMs built using large-scale simulations of GPCRs and kinases, we have shown that complex conformational changes in proteins can be described in terms of structural changes in key structural motifs or “molecular switches” within the protein, the transitions between functionally active and inactive states of proteins proceed via multiple pathways, and ligand or substrate binding modulates the flux through these pathways. Finally, MSMs also provide a theoretical toolbox for studying the effect of nonequilibrium perturbations on conformational dynamics. Considering that protein dynamics in vivo occur under nonequilibrium conditions, MSMs coupled with nonequilibrium statistical mechanics provide a way to connect cellular components to their functional environments. Nonequilibrium perturbations of protein folding MSMs reveal the presence of dynamically frozen glass-like states in their conformational landscape. These frozen states are also observed to be rich in β-sheets, which indicates their possible role in the nucleation of β-sheet rich aggregates such as those observed in amyloid-fibril formation. Finally, we describe how MSMs have been used to understand the dynamical behavior of intrinsically disordered proteins such as amyloid-β, human islet amyloid polypeptide, and p53. While certainly not a panacea for studying functional dynamics, MSMs provide a rigorous theoretical foundation for understanding complex entropically dominated processes and a convenient lens for viewing protein motions. PMID:25625937

Smoothed Biasing Forces Yield Unbiased Free Energies with the Extended-System Adaptive Biasing Force Method

PubMed Central

2016-01-01

We report a theoretical description and numerical tests of the extended-system adaptive biasing force method (eABF), together with an unbiased estimator of the free energy surface from eABF dynamics. Whereas the original ABF approach uses its running estimate of the free energy gradient as the adaptive biasing force, eABF is built on the idea that the exact free energy gradient is not necessary for efficient exploration, and that it is still possible to recover the exact free energy separately with an appropriate estimator. eABF does not directly bias the collective coordinates of interest, but rather fictitious variables that are harmonically coupled to them; therefore is does not require second derivative estimates, making it easily applicable to a wider range of problems than ABF. Furthermore, the extended variables present a smoother, coarse-grain-like sampling problem on a mollified free energy surface, leading to faster exploration and convergence. We also introduce CZAR, a simple, unbiased free energy estimator from eABF trajectories. eABF/CZAR converges to the physical free energy surface faster than standard ABF for a wide range of parameters. PMID:27959559

Unbiased multi-fidelity estimate of failure probability of a free plane jet

NASA Astrophysics Data System (ADS)

Marques, Alexandre; Kramer, Boris; Willcox, Karen; Peherstorfer, Benjamin

2017-11-01

Estimating failure probability related to fluid flows is a challenge because it requires a large number of evaluations of expensive models. We address this challenge by leveraging multiple low fidelity models of the flow dynamics to create an optimal unbiased estimator. In particular, we investigate the effects of uncertain inlet conditions in the width of a free plane jet. We classify a condition as failure when the corresponding jet width is below a small threshold, such that failure is a rare event (failure probability is smaller than 0.001). We estimate failure probability by combining the frameworks of multi-fidelity importance sampling and optimal fusion of estimators. Multi-fidelity importance sampling uses a low fidelity model to explore the parameter space and create a biasing distribution. An unbiased estimate is then computed with a relatively small number of evaluations of the high fidelity model. In the presence of multiple low fidelity models, this framework offers multiple competing estimators. Optimal fusion combines all competing estimators into a single estimator with minimal variance. We show that this combined framework can significantly reduce the cost of estimating failure probabilities, and thus can have a large impact in fluid flow applications. This work was funded by DARPA.

Simulating structure and dynamics in small droplets of 1-ethyl-3-methylimidazolium acetate

NASA Astrophysics Data System (ADS)

Brehm, Martin; Sebastiani, Daniel

2018-05-01

To investigate the structure and dynamics of small ionic liquid droplets in gas phase, we performed a DFT-based ab initio molecular dynamics study of several 1-ethyl-3-methylimidazolium acetate clusters in vacuum as well as a bulk phase simulation. We introduce an unbiased criterion for average droplet diameter and density. By extrapolation of the droplet densities, we predict the experimental bulk phase density with a deviation of only a few percent. The hydrogen bond geometry between cations and anions is very similar in droplets and bulk, but the hydrogen bond dynamics is significantly slower in the droplets, becoming slower with increasing system size, with hydrogen bond lifetimes up to 2000 ps. From a normal mode analysis of the trajectories, we identify the modes of the ring proton C-H stretching, which are strongly affected by hydrogen bonding. From analyzing these, we find that the hydrogen bond becomes weaker with increasing system size. The cations possess an increased concentration inside the clusters, whereas the anions show an excess concentration on the outside. Almost all anions point towards the droplet center with their carboxylic groups. Ring stacking is found to be a very important structural motif in the droplets (as in the bulk), but side chain interactions are only of minor importance. By using Voronoi tessellation, we define the exposed droplet surface and find that it consists mainly of hydrogen atoms from the cation's and anion's methyl and ethyl groups. Polar atoms are rarely found on the surface, such that the droplets appear completely hydrophobic on the outside.

Transient photocurrent in molecular junctions: singlet switching on and triplet blocking.

PubMed

Petrov, E G; Leonov, V O; Snitsarev, V

2013-05-14

The kinetic approach adapted to describe charge transmission in molecular junctions, is used for the analysis of the photocurrent under conditions of moderate light intensity of the photochromic molecule. In the framework of the HOMO-LUMO model for the single electron molecular states, the analytic expressions describing the temporary behavior of the transient and steady state sequential (hopping) as well as direct (tunnel) current components have been derived. The conditions at which the current components achieve their maximal values are indicated. It is shown that if the rates of charge transmission in the unbiased molecular diode are much lower than the intramolecular singlet-singlet excitation/de-excitation rate, and the threefold degenerated triplet excited state of the molecule behaves like a trap blocking the charge transmission, a possibility of a large peak-like transient switch-on photocurrent arises.

Personalized recommendation based on unbiased consistence

NASA Astrophysics Data System (ADS)

Zhu, Xuzhen; Tian, Hui; Zhang, Ping; Hu, Zheng; Zhou, Tao

2015-08-01

Recently, in physical dynamics, mass-diffusion-based recommendation algorithms on bipartite network provide an efficient solution by automatically pushing possible relevant items to users according to their past preferences. However, traditional mass-diffusion-based algorithms just focus on unidirectional mass diffusion from objects having been collected to those which should be recommended, resulting in a biased causal similarity estimation and not-so-good performance. In this letter, we argue that in many cases, a user's interests are stable, and thus bidirectional mass diffusion abilities, no matter originated from objects having been collected or from those which should be recommended, should be consistently powerful, showing unbiased consistence. We further propose a consistence-based mass diffusion algorithm via bidirectional diffusion against biased causality, outperforming the state-of-the-art recommendation algorithms in disparate real data sets, including Netflix, MovieLens, Amazon and Rate Your Music.

Using Local States To Drive the Sampling of Global Conformations in Proteins

PubMed Central

2016-01-01

Conformational changes associated with protein function often occur beyond the time scale currently accessible to unbiased molecular dynamics (MD) simulations, so that different approaches have been developed to accelerate their sampling. Here we investigate how the knowledge of backbone conformations preferentially adopted by protein fragments, as contained in precalculated libraries known as structural alphabets (SA), can be used to explore the landscape of protein conformations in MD simulations. We find that (a) enhancing the sampling of native local states in both metadynamics and steered MD simulations allows the recovery of global folded states in small proteins; (b) folded states can still be recovered when the amount of information on the native local states is reduced by using a low-resolution version of the SA, where states are clustered into macrostates; and (c) sequences of SA states derived from collections of structural motifs can be used to sample alternative conformations of preselected protein regions. The present findings have potential impact on several applications, ranging from protein model refinement to protein folding and design. PMID:26808351

Binding of Disordered Peptides to Kelch: Insights from Enhanced Sampling Simulations.

PubMed

Do, Trang Nhu; Choy, Wing-Yiu; Karttunen, Mikko

2016-01-12

Keap1 protein plays an essential role in regulating cellular oxidative stress response and is a crucial binding hub for multiple proteins, several of which are intrinsically disordered proteins (IDP). Among Kelch's IDP binding partners, NRF2 and PTMA are the two most interesting cases. They share a highly similar binding motif; however, NRF2 binds to Kelch with a binding affinity of approximately 100-fold higher than that of PTMA. In this study, we perform an exhaustive sampling composed of 6 μs well-tempered metadynamics and 2 μs unbiased molecular dynamics (MD) simulations aiming at characterizing the binding mechanisms and structural properties of these two peptides. Our results agree with previous experimental observations that PTMA is remarkably more disordered than NRF2 in both the free and bound states. This explains PTMA's lower binding affinity. Our extensive sampling also provides valuable insights into the vast conformational ensembles of both NRF2 and PTMA, supports the hypothesis of coupled folding-binding, and confirms the essential role of linear motifs in IDP binding.

Mechanisms of passive ion permeation through lipid bilayers: insights from simulations.

PubMed

Tepper, Harald L; Voth, Gregory A

2006-10-26

Multistate empirical valence bond and classical molecular dynamics simulations were used to explore mechanisms for passive ion leakage through a dimyristoyl phosphatidylcholine lipid bilayer. In accordance with a previous study on proton leakage (Biophys. J. 2005, 88, 3095), it was found that the permeation mechanism must be a highly concerted one, in which ion, solvent, and membrane coordinates are coupled. The presence of the ion itself significantly alters the response of those coordinates, suggesting that simulations of transmembrane water structures without explicit inclusion of the ionic solute are insufficient for elucidating transition mechanisms. The properties of H(+), Na(+), OH(-), and bare water molecules in the membrane interior were compared, both by biased sampling techniques and by constructing complete and unbiased transition paths. It was found that the anomalous difference in leakage rates between protons and other cations can be largely explained by charge delocalization effects rather than the usual kinetic picture (Grotthuss hopping of the proton). Permeability differences between anions and cations through phosphatidylcholine bilayers are correlated with suppression of favorable membrane breathing modes by cations.

Nanoscale simple-fluid behavior under steady shear.

PubMed

Yong, Xin; Zhang, Lucy T

2012-05-01

In this study, we use two nonequilibrium molecular dynamics algorithms, boundary-driven shear and homogeneous shear, to explore the rheology and flow properties of a simple fluid undergoing steady simple shear. The two distinct algorithms are designed to elucidate the influences of nanoscale confinement. The results of rheological material functions, i.e., viscosity and normal pressure differences, show consistent Newtonian behaviors at low shear rates from both systems. The comparison validates that confinements of the order of 10 nm are not strong enough to deviate the simple fluid behaviors from the continuum hydrodynamics. The non-Newtonian phenomena of the simple fluid are further investigated by the homogeneous shear simulations with much higher shear rates. We observe the "string phase" at high shear rates by applying both profile-biased and profile-unbiased thermostats. Contrary to other findings where the string phase is found to be an artifact of the thermostats, we perform a thorough analysis of the fluid microstructures formed due to shear, which shows that it is possible to have a string phase and second shear thinning for dense simple fluids.

Using Local States To Drive the Sampling of Global Conformations in Proteins.

PubMed

Pandini, Alessandro; Fornili, Arianna

2016-03-08

Conformational changes associated with protein function often occur beyond the time scale currently accessible to unbiased molecular dynamics (MD) simulations, so that different approaches have been developed to accelerate their sampling. Here we investigate how the knowledge of backbone conformations preferentially adopted by protein fragments, as contained in precalculated libraries known as structural alphabets (SA), can be used to explore the landscape of protein conformations in MD simulations. We find that (a) enhancing the sampling of native local states in both metadynamics and steered MD simulations allows the recovery of global folded states in small proteins; (b) folded states can still be recovered when the amount of information on the native local states is reduced by using a low-resolution version of the SA, where states are clustered into macrostates; and (c) sequences of SA states derived from collections of structural motifs can be used to sample alternative conformations of preselected protein regions. The present findings have potential impact on several applications, ranging from protein model refinement to protein folding and design.

Mutually unbiased product bases for multiple qudits

DOE Office of Scientific and Technical Information (OSTI.GOV)

McNulty, Daniel; Pammer, Bogdan; Weigert, Stefan

We investigate the interplay between mutual unbiasedness and product bases for multiple qudits of possibly different dimensions. A product state of such a system is shown to be mutually unbiased to a product basis only if each of its factors is mutually unbiased to all the states which occur in the corresponding factors of the product basis. This result implies both a tight limit on the number of mutually unbiased product bases which the system can support and a complete classification of mutually unbiased product bases for multiple qubits or qutrits. In addition, only maximally entangled states can be mutuallymore » unbiased to a maximal set of mutually unbiased product bases.« less

Clearing out a maze: A model of chemotactic motion in porous media

NASA Astrophysics Data System (ADS)

Schilling, Tanja; Voigtmann, Thomas

2017-12-01

We study the anomalous dynamics of a biased "hungry" (or "greedy") random walk on a percolating cluster. The model mimics chemotaxis in a porous medium: In close resemblance to the 1980s arcade game PAC-MA N ®, the hungry random walker consumes food, which is initially distributed in the maze, and biases its movement towards food-filled sites. We observe that the mean-squared displacement of the process follows a power law with an exponent that is different from previously known exponents describing passive or active microswimmer dynamics. The change in dynamics is well described by a dynamical exponent that depends continuously on the propensity to move towards food. It results in slower differential growth when compared to the unbiased random walk.

Identification and characterization of Highlands J virus from a Mississippi sandhill crane using unbiased next-generation sequencing

USGS Publications Warehouse

Ip, Hon S.; Wiley, Michael R.; Long, Renee; Gustavo, Palacios; Shearn-Bochsler, Valerie; Whitehouse, Chris A.

2014-01-01

Advances in massively parallel DNA sequencing platforms, commonly termed next-generation sequencing (NGS) technologies, have greatly reduced time, labor, and cost associated with DNA sequencing. Thus, NGS has become a routine tool for new viral pathogen discovery and will likely become the standard for routine laboratory diagnostics of infectious diseases in the near future. This study demonstrated the application of NGS for the rapid identification and characterization of a virus isolated from the brain of an endangered Mississippi sandhill crane. This bird was part of a population restoration effort and was found in an emaciated state several days after Hurricane Isaac passed over the refuge in Mississippi in 2012. Post-mortem examination had identified trichostrongyliasis as the possible cause of death, but because a virus with morphology consistent with a togavirus was isolated from the brain of the bird, an arboviral etiology was strongly suspected. Because individual molecular assays for several known arboviruses were negative, unbiased NGS by Illumina MiSeq was used to definitively identify and characterize the causative viral agent. Whole genome sequencing and phylogenetic analysis revealed the viral isolate to be the Highlands J virus, a known avian pathogen. This study demonstrates the use of unbiased NGS for the rapid detection and characterization of an unidentified viral pathogen and the application of this technology to wildlife disease diagnostics and conservation medicine.

Mechanism of mRNA-STAR domain interaction: Molecular dynamics simulations of Mammalian Quaking STAR protein.

PubMed

Sharma, Monika; Anirudh, C R

2017-10-03

STAR proteins are evolutionary conserved mRNA-binding proteins that post-transcriptionally regulate gene expression at all stages of RNA metabolism. These proteins possess conserved STAR domain that recognizes identical RNA regulatory elements as YUAAY. Recently reported crystal structures show that STAR domain is composed of N-terminal QUA1, K-homology domain (KH) and C-terminal QUA2, and mRNA binding is mediated by KH-QUA2 domain. Here, we present simulation studies done to investigate binding of mRNA to STAR protein, mammalian Quaking protein (QKI). We carried out conventional MD simulations of STAR domain in presence and absence of mRNA, and studied the impact of mRNA on the stability, dynamics and underlying allosteric mechanism of STAR domain. Our unbiased simulations results show that presence of mRNA stabilizes the overall STAR domain by reducing the structural deviations, correlating the 'within-domain' motions, and maintaining the native contacts information. Absence of mRNA not only influenced the essential modes of motion of STAR domain, but also affected the connectivity of networks within STAR domain. We further explored the dissociation of mRNA from STAR domain using umbrella sampling simulations, and the results suggest that mRNA binding to STAR domain occurs in multi-step: first conformational selection of mRNA backbone conformations, followed by induced fit mechanism as nucleobases interact with STAR domain.

Multi-Scale Molecular Deconstruction of the Serotonin Neuron System.

PubMed

Okaty, Benjamin W; Freret, Morgan E; Rood, Benjamin D; Brust, Rachael D; Hennessy, Morgan L; deBairos, Danielle; Kim, Jun Chul; Cook, Melloni N; Dymecki, Susan M

2015-11-18

Serotonergic (5HT) neurons modulate diverse behaviors and physiology and are implicated in distinct clinical disorders. Corresponding diversity in 5HT neuronal phenotypes is becoming apparent and is likely rooted in molecular differences, yet a comprehensive approach characterizing molecular variation across the 5HT system is lacking, as is concomitant linkage to cellular phenotypes. Here we combine intersectional fate mapping, neuron sorting, and genome-wide RNA-seq to deconstruct the mouse 5HT system at multiple levels of granularity-from anatomy, to genetic sublineages, to single neurons. Our unbiased analyses reveal principles underlying system organization, 5HT neuron subtypes, constellations of differentially expressed genes distinguishing subtypes, and predictions of subtype-specific functions. Using electrophysiology, subtype-specific neuron silencing, and conditional gene knockout, we show that these molecularly defined 5HT neuron subtypes are functionally distinct. Collectively, this resource classifies molecular diversity across the 5HT system and discovers sertonergic subtypes, markers, organizing principles, and subtype-specific functions with potential disease relevance. Copyright © 2015 Elsevier Inc. All rights reserved.

Multi-Scale Molecular Deconstruction of the Serotonin Neuron System

PubMed Central

Okaty, Benjamin W.; Freret, Morgan E.; Rood, Benjamin D.; Brust, Rachael D.; Hennessy, Morgan L.; deBairos, Danielle; Kim, Jun Chul; Cook, Melloni N.; Dymecki, Susan M.

2016-01-01

Summary Serotonergic (5HT) neurons modulate diverse behaviors and physiology and are implicated in distinct clinical disorders. Corresponding diversity in 5HT neuronal phenotypes is becoming apparent and is likely rooted in molecular differences, yet a comprehensive approach characterizing molecular variation across the 5HT system is lacking, as is concomitant linkage to cellular phenotypes. Here we combine intersectional fate mapping, neuron sorting, and genome-wide RNA-Seq to deconstruct the mouse 5HT system at multiple levels of granularity—from anatomy, to genetic sublineages, to single neurons. Our unbiased analyses reveal: principles underlying system organization, novel 5HT neuron subtypes, constellations of differentially expressed genes distinguishing subtypes, and predictions of subtype-specific functions. Using electrophysiology, subtype-specific neuron silencing, and conditional gene knockout, we show that these molecularly defined 5HT neuron subtypes are functionally distinct. Collectively, this resource classifies molecular diversity across the 5HT system and discovers new subtypes, markers, organizing principles, and subtype-specific functions with potential disease relevance. PMID:26549332

Dynamics and Instabilities of the Shastry-Sutherland Model

NASA Astrophysics Data System (ADS)

Wang, Zhentao; Batista, Cristian D.

2018-06-01

We study the excitation spectrum in the dimer phase of the Shastry-Sutherland model by using an unbiased variational method that works in the thermodynamic limit. The method outputs dynamical correlation functions in all possible channels. This output is exploited to identify the order parameters with the highest susceptibility (single or multitriplon condensation in a specific channel) upon approaching a quantum phase transition in the magnetic field versus the J'/J phase diagram. We find four different instabilities: antiferro spin nematic, plaquette spin nematic, stripe magnetic order, and plaquette order, two of which have been reported in previous studies.

Targeted next-generation sequencing makes new molecular diagnoses and expands genotype-phenotype relationship in Ehlers-Danlos syndrome.

PubMed

Weerakkody, Ruwan A; Vandrovcova, Jana; Kanonidou, Christina; Mueller, Michael; Gampawar, Piyush; Ibrahim, Yousef; Norsworthy, Penny; Biggs, Jennifer; Abdullah, Abdulshakur; Ross, David; Black, Holly A; Ferguson, David; Cheshire, Nicholas J; Kazkaz, Hanadi; Grahame, Rodney; Ghali, Neeti; Vandersteen, Anthony; Pope, F Michael; Aitman, Timothy J

2016-11-01

Ehlers-Danlos syndrome (EDS) comprises a group of overlapping hereditary disorders of connective tissue with significant morbidity and mortality, including major vascular complications. We sought to identify the diagnostic utility of a next-generation sequencing (NGS) panel in a mixed EDS cohort. We developed and applied PCR-based NGS assays for targeted, unbiased sequencing of 12 collagen and aortopathy genes to a cohort of 177 unrelated EDS patients. Variants were scored blind to previous genetic testing and then compared with results of previous Sanger sequencing. Twenty-eight pathogenic variants in COL5A1/2, COL3A1, FBN1, and COL1A1 and four likely pathogenic variants in COL1A1, TGFBR1/2, and SMAD3 were identified by the NGS assays. These included all previously detected single-nucleotide and other short pathogenic variants in these genes, and seven newly detected pathogenic or likely pathogenic variants leading to clinically significant diagnostic revisions. Twenty-two variants of uncertain significance were identified, seven of which were in aortopathy genes and required clinical follow-up. Unbiased NGS-based sequencing made new molecular diagnoses outside the expected EDS genotype-phenotype relationship and identified previously undetected clinically actionable variants in aortopathy susceptibility genes. These data may be of value in guiding future clinical pathways for genetic diagnosis in EDS.Genet Med 18 11, 1119-1127.

Hydrodynamic interactions induce movement against an external load in a ratchet dimer Brownian motor.

PubMed

Fornés, José A

2010-01-15

We use the Brownian dynamics with hydrodynamic interactions simulation in order to describe the movement of a elastically coupled dimer Brownian motor in a ratchet potential. The only external forces considered in our system were the load, the random thermal noise and an unbiased thermal fluctuation. For a given set of parameters we observe direct movement against the load force if hydrodynamic interactions were considered.

Quantification of correlations in quantum many-particle systems.

PubMed

Byczuk, Krzysztof; Kuneš, Jan; Hofstetter, Walter; Vollhardt, Dieter

2012-02-24

We introduce a well-defined and unbiased measure of the strength of correlations in quantum many-particle systems which is based on the relative von Neumann entropy computed from the density operator of correlated and uncorrelated states. The usefulness of this general concept is demonstrated by quantifying correlations of interacting electrons in the Hubbard model and in a series of transition-metal oxides using dynamical mean-field theory.

Screening the receptorome to discover the molecular targets for plant-derived psychoactive compounds: a novel approach for CNS drug discovery.

PubMed

Roth, Bryan L; Lopez, Estela; Beischel, Scott; Westkaemper, Richard B; Evans, Jon M

2004-05-01

Because psychoactive plants exert profound effects on human perception, emotion, and cognition, discovering the molecular mechanisms responsible for psychoactive plant actions will likely yield insights into the molecular underpinnings of human consciousness. Additionally, it is likely that elucidation of the molecular targets responsible for psychoactive drug actions will yield validated targets for CNS drug discovery. This review article focuses on an unbiased, discovery-based approach aimed at uncovering the molecular targets responsible for psychoactive drug actions wherein the main active ingredients of psychoactive plants are screened at the "receptorome" (that portion of the proteome encoding receptors). An overview of the receptorome is given and various in silico, public-domain resources are described. Newly developed tools for the in silico mining of data derived from the National Institute of Mental Health Psychoactive Drug Screening Program's (NIMH-PDSP) K(i) Database (K(i) DB) are described in detail. Additionally, three case studies aimed at discovering the molecular targets responsible for Hypericum perforatum, Salvia divinorum, and Ephedra sinica actions are presented. Finally, recommendations are made for future studies.

Molecular Confirmation of the Specific Status of Anopheles halophylus (Diptera: Culicidae) and Evidence of a New Cryptic Species within An. triannulatus in Central Brazil

DTIC Science & Technology

2006-01-01

unbiased genetic dis- tances and characterized using the unweighted pair group method with arithmetic means ( UPGMA ). Re- Table 1. Gene frequencies for...0.428, and between An. halophylus and the morpho- logical variant was 0.145, supporting the observations seen with allozymes. A UPGMA dendrogram based...and R. C. Wilkerson. 2005. Anopheles tri- annulatus (Neiva and Pinto): a new Anopheles record Fig. 2. UPGMA dendrogram constructed based on RAPD

Chemical genomic profiling via barcode sequencing to predict compound mode of action

PubMed Central

Piotrowski, Jeff S.; Simpkins, Scott W.; Li, Sheena C.; Deshpande, Raamesh; McIlwain, Sean; Ong, Irene; Myers, Chad L.; Boone, Charlie; Andersen, Raymond J.

2015-01-01

Summary Chemical genomics is an unbiased, whole-cell approach to characterizing novel compounds to determine mode of action and cellular target. Our version of this technique is built upon barcoded deletion mutants of Saccharomyces cerevisiae and has been adapted to a high-throughput methodology using next-generation sequencing. Here we describe the steps to generate a chemical genomic profile from a compound of interest, and how to use this information to predict molecular mechanism and targets of bioactive compounds. PMID:25618354

A mechanistic role of Helix 8 in GPCRs: Computational modeling of the dopamine D2 receptor interaction with the GIPC1-PDZ-domain.

PubMed

Sensoy, Ozge; Weinstein, Harel

2015-04-01

Helix-8 (Hx8) is a structurally conserved amphipathic helical motif in class-A GPCRs, adjacent to the C-terminal sequence that is responsible for PDZ-domain-recognition. The Hx8 segment in the dopamine D2 receptor (D2R) constitutes the C-terminal segment and we investigate its role in the function of D2R by studying the interaction with the PDZ-containing GIPC1 using homology models based on the X-ray structures of very closely related analogs: the D3R for the D2R model, and the PDZ domain of GIPC2 for GIPC1-PDZ. The mechanism of this interaction was investigated with all-atom unbiased molecular dynamics (MD) simulations that reveal the role of the membrane in maintaining the helical fold of Hx8, and with biased MD simulations to elucidate the energy drive for the interaction with the GIPC1-PDZ. We found that it becomes more favorable energetically for Hx8 to adopt the extended conformation observed in all PDZ-ligand complexes when it moves away from the membrane, and that C-terminus palmitoylation of D2R enhanced membrane penetration by the Hx8 backbone. De-palmitoylation enables Hx8 to move out into the aqueous environment for interaction with the PDZ domain. All-atom unbiased MD simulations of the full D2R-GIPC1-PDZ complex in sphingolipid/cholesterol membranes show that the D2R carboxyl C-terminus samples the region of the conserved GFGL motif located on the carboxylate-binding loop of the GIPC1-PDZ, and the entire complex distances itself from the membrane interface. Together, these results outline a likely mechanism of Hx8 involvement in the interaction of the GPCR with PDZ-domains in the course of signaling. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

A mechanistic role of Helix 8 in GPCRs: Computational modeling of the dopamine D2 receptor interaction with the GIPC1-PDZ-domain

PubMed Central

Sensoy, Ozge; Weinstein, Harel

2015-01-01

Helix-8 (Hx8) is a structurally conserved amphipathic helical motif in class-A GPCRs, adjacent to the C-terminal sequence that is responsible for PDZ-domain-recognition. The Hx8 segment in the dopamine D2 receptor (D2R) constitutes the C-terminal segment and we investigate its role in the function of D2R by studying the interaction with the PDZ-containing GIPC1 using homology models based on the X-ray structures of very closely related analogs: the D3R for the D2R model, and the PDZ domain of GIPC2 for GIPC1-PDZ. The mechanism of this interaction was investigated with all-atom unbiased molecular dynamics (MD) simulations that reveal the role of the membrane in maintaining the helical fold of Hx8, and with biased MD simulations to elucidate the energy drive for the interaction with the GIPC1-PDZ. We found that it becomes more favorable energetically for Hx8 to adopt the extended conformation observed in all PDZ-ligand complexes when it moves away from the membrane, and that C-terminus palmitoylation of D2R enhanced membrane penetration by the Hx8 backbone. De-palmitoylation enables Hx8 to move out into the aqueous environment for interaction with the PDZ domain. All-atom unbiased MD simulations of the full D2R-GIPC1 complex in sphingolipid/cholesterol membranes shows that the D2R carboxyl C-terminus samples the region of the conserved GFGL motif located on the carboxylate-binding loop of the GIPC1-PDZ, and the entire complex distances itself from the membrane interface. Together, these results outline a likely mechanism of Hx8 involvement in the interaction of the GPCR with PDZ-domains in the course of signaling. PMID:25592838

A mechanistic role of Helix 8 in GPCRs: Computational modeling of the dopamine D2 receptor interaction with the GIPC1–PDZ-domain

DOE PAGES

Sensoy, Ozge; Weinstein, Harel

2015-01-12

Helix-8 (Hx8) is a structurally conserved amphipathic helical motif in class-A GPCRs, adjacent to the C-terminal sequence that is responsible for PDZ-domain-recognition. The Hx8 segment in the dopamine D2 receptor (D2R) constitutes the C-terminal segment and we investigate its role in the function of D2R by studying the interaction with the PDZ-containing GIPC1 using homology models based on the X-ray structures of very closely related analogs: the D3R for the D2R model, and the PDZ domain of GIPC2 for GIPC1–PDZ. The mechanism of this interaction was investigated with all-atom unbiased molecular dynamics (MD) simulations that reveal the role of themore » membrane in maintaining the helical fold of Hx8, and with biased MD simulations to elucidate the energy drive for the interaction with the GIPC1–PDZ. We found that it becomes more favorable energetically for Hx8 to adopt the extended conformation observed in all PDZ–ligand complexes when it moves away from the membrane, and that C-terminus palmitoylation of D2R enhanced membrane penetration by the Hx8 backbone. De-palmitoylation enables Hx8 to move out into the aqueous environment for interaction with the PDZ domain. All-atom unbiased MD simulations of the full D2R–GIPC1-PDZ complex in sphingolipid/cholesterol membranes show that the D2R carboxyl C-terminus samples the region of the conserved GFGL motif located on the carboxylate-binding loop of the GIPC1–PDZ, and the entire complex distances itself from the membrane interface. Altogether, these results outline a likely mechanism of Hx8 involvement in the interaction of the GPCR with PDZ-domains in the course of signaling.« less

Global Culture: A Noise Induced Transition in Finite Systems

NASA Astrophysics Data System (ADS)

Klemm, Konstantin; Eguíluz, Victor M.; Toral, Raúl; San Miguel, Maxi

2003-04-01

We analyze Axelrod's model for the unbiased transmission of culture in the presence of noise. In a one-dimensional lattice, the dynamics is described in terms of a Lyapunov potential, where the disordered configurations are metastable states of the dynamics. In a two-dimensional lattice the dynamics is governed by the average relaxation time T for perturbations to the homogeneous configuration. If the noise rate is smaller than 1/T, the perturbations drive the system to a completely ordered configuration, whereas the system remains disordered for larger noise rates. Based on a mean-field approximation we obtain the average relaxation time T(N) = Nln(N) for system size N. Thus in the limit of infinite system size the system is disordered for any finite noise rate.

Next generation of network medicine: interdisciplinary signaling approaches.

PubMed

Korcsmaros, Tamas; Schneider, Maria Victoria; Superti-Furga, Giulio

2017-02-20

In the last decade, network approaches have transformed our understanding of biological systems. Network analyses and visualizations have allowed us to identify essential molecules and modules in biological systems, and improved our understanding of how changes in cellular processes can lead to complex diseases, such as cancer, infectious and neurodegenerative diseases. "Network medicine" involves unbiased large-scale network-based analyses of diverse data describing interactions between genes, diseases, phenotypes, drug targets, drug transport, drug side-effects, disease trajectories and more. In terms of drug discovery, network medicine exploits our understanding of the network connectivity and signaling system dynamics to help identify optimal, often novel, drug targets. Contrary to initial expectations, however, network approaches have not yet delivered a revolution in molecular medicine. In this review, we propose that a key reason for the limited impact, so far, of network medicine is a lack of quantitative multi-disciplinary studies involving scientists from different backgrounds. To support this argument, we present existing approaches from structural biology, 'omics' technologies (e.g., genomics, proteomics, lipidomics) and computational modeling that point towards how multi-disciplinary efforts allow for important new insights. We also highlight some breakthrough studies as examples of the potential of these approaches, and suggest ways to make greater use of the power of interdisciplinarity. This review reflects discussions held at an interdisciplinary signaling workshop which facilitated knowledge exchange from experts from several different fields, including in silico modelers, computational biologists, biochemists, geneticists, molecular and cell biologists as well as cancer biologists and pharmacologists.

Advantages of a distant cellulase catalytic base.

PubMed

Burgin, Tucker; Ståhlberg, Jerry; Mayes, Heather B

2018-03-30

The inverting glycoside hydrolase Trichoderma reesei ( Hypocrea jecorina ) Cel6A is a promising candidate for protein engineering for more economical production of biofuels. Until recently, its catalytic mechanism had been uncertain: The best candidate residue to serve as a catalytic base, Asp-175, is farther from the glycosidic cleavage site than in other glycoside hydrolase enzymes. Recent unbiased transition path sampling simulations revealed the hydrolytic mechanism for this more distant base, employing a water wire; however, it is not clear why the enzyme employs a more distant catalytic base, a highly conserved feature among homologs across different kingdoms. In this work, we describe molecular dynamics simulations designed to uncover how a base with a longer side chain, as in a D175E mutant, affects procession and active site alignment in the Michaelis complex. We show that the hydrogen bond network is tuned to the shorter aspartate side chain, and that a longer glutamate side chain inhibits procession as well as being less likely to adopt a catalytically productive conformation. Furthermore, we draw comparisons between the active site in Trichoderma reesei Cel6A and another inverting, processive cellulase to deduce the contribution of the water wire to the overall enzyme function, revealing that the more distant catalytic base enhances product release. Our results can inform efforts in the study and design of enzymes by demonstrating how counterintuitive sacrifices in chemical reactivity can have worthwhile benefits for other steps in the catalytic cycle. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Mutually unbiased projectors and duality between lines and bases in finite quantum systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shalaby, M.; Vourdas, A., E-mail: a.vourdas@bradford.ac.uk

2013-10-15

Quantum systems with variables in the ring Z(d) are considered, and the concepts of weak mutually unbiased bases and mutually unbiased projectors are discussed. The lines through the origin in the Z(d)×Z(d) phase space, are classified into maximal lines (sets of d points), and sublines (sets of d{sub i} points where d{sub i}|d). The sublines are intersections of maximal lines. It is shown that there exists a duality between the properties of lines (resp., sublines), and the properties of weak mutually unbiased bases (resp., mutually unbiased projectors). -- Highlights: •Lines in discrete phase space. •Bases in finite quantum systems. •Dualitymore » between bases and lines. •Weak mutually unbiased bases.« less

The unforeseen challenge: from genotype-to-phenotype in cell populations

NASA Astrophysics Data System (ADS)

Braun, Erez

2015-02-01

Biological cells present a paradox, in that they show simultaneous stability and flexibility, allowing them to adapt to new environments and to evolve over time. The emergence of stable cell states depends on genotype-to-phenotype associations, which essentially reflect the organization of gene regulatory modes. The view taken here is that cell-state organization is a dynamical process in which the molecular disorder manifests itself in a macroscopic order. The genome does not determine the ordered cell state; rather, it participates in this process by providing a set of constraints on the spectrum of regulatory modes, analogous to boundary conditions in physical dynamical systems. We have developed an experimental framework, in which cell populations are exposed to unforeseen challenges; novel perturbations they had not encountered before along their evolutionary history. This approach allows an unbiased view of cell dynamics, uncovering the potential of cells to evolve and develop adapted stable states. In the last decade, our experiments have revealed a coherent set of observations within this framework, painting a picture of the living cell that in many ways is not aligned with the conventional one. Of particular importance here, is our finding that adaptation of cell-state organization is essentially an efficient exploratory dynamical process rather than one founded on random mutations. Based on our framework, a set of concepts underlying cell-state organization—exploration evolving by global, non-specific, dynamics of gene activity—is presented here. These concepts have significant consequences for our understanding of the emergence and stabilization of a cell phenotype in diverse biological contexts. Their implications are discussed for three major areas of biological inquiry: evolution, cell differentiation and cancer. There is currently no unified theoretical framework encompassing the emergence of order, a stable state, in the living cell. Hopefully, the integrated picture described here will provide a modest contribution towards a physics theory of the cell.

Biased Brownian dynamics for rate constant calculation.

PubMed

Zou, G; Skeel, R D; Subramaniam, S

2000-08-01

An enhanced sampling method-biased Brownian dynamics-is developed for the calculation of diffusion-limited biomolecular association reaction rates with high energy or entropy barriers. Biased Brownian dynamics introduces a biasing force in addition to the electrostatic force between the reactants, and it associates a probability weight with each trajectory. A simulation loses weight when movement is along the biasing force and gains weight when movement is against the biasing force. The sampling of trajectories is then biased, but the sampling is unbiased when the trajectory outcomes are multiplied by their weights. With a suitable choice of the biasing force, more reacted trajectories are sampled. As a consequence, the variance of the estimate is reduced. In our test case, biased Brownian dynamics gives a sevenfold improvement in central processing unit (CPU) time with the choice of a simple centripetal biasing force.

Automated systematic random sampling and Cavalieri stereology of histologic sections demonstrating acute tubular necrosis after cardiac arrest and cardiopulmonary resuscitation in the mouse.

PubMed

Wakasaki, Rumie; Eiwaz, Mahaba; McClellan, Nicholas; Matsushita, Katsuyuki; Golgotiu, Kirsti; Hutchens, Michael P

2018-06-14

A technical challenge in translational models of kidney injury is determination of the extent of cell death. Histologic sections are commonly analyzed by area morphometry or unbiased stereology, but stereology requires specialized equipment. Therefore, a challenge to rigorous quantification would be addressed by an unbiased stereology tool with reduced equipment dependence. We hypothesized that it would be feasible to build a novel software component which would facilitate unbiased stereologic quantification on scanned slides, and that unbiased stereology would demonstrate greater precision and decreased bias compared with 2D morphometry. We developed a macro for the widely used image analysis program, Image J, and performed cardiac arrest with cardiopulmonary resuscitation (CA/CPR, a model of acute cardiorenal syndrome) in mice. Fluorojade-B stained kidney sections were analyzed using three methods to quantify cell death: gold standard stereology using a controlled stage and commercially-available software, unbiased stereology using the novel ImageJ macro, and quantitative 2D morphometry also using the novel macro. There was strong agreement between both methods of unbiased stereology (bias -0.004±0.006 with 95% limits of agreement -0.015 to 0.007). 2D morphometry demonstrated poor agreement and significant bias compared to either method of unbiased stereology. Unbiased stereology is facilitated by a novel macro for ImageJ and results agree with those obtained using gold-standard methods. Automated 2D morphometry overestimated tubular epithelial cell death and correlated modestly with values obtained from unbiased stereology. These results support widespread use of unbiased stereology for analysis of histologic outcomes of injury models.

Equilibrium Free Energies from Nonequilibrium Metadynamics

NASA Astrophysics Data System (ADS)

Bussi, Giovanni; Laio, Alessandro; Parrinello, Michele

2006-03-01

In this Letter we propose a new formalism to map history-dependent metadynamics in a Markovian process. We apply this formalism to model Langevin dynamics and determine the equilibrium distribution of a collection of simulations. We demonstrate that the reconstructed free energy is an unbiased estimate of the underlying free energy and analytically derive an expression for the error. The present results can be applied to other history-dependent stochastic processes, such as Wang-Landau sampling.

Passive Membrane Permeability: Beyond the Standard Solubility-Diffusion Model.

PubMed

Parisio, Giulia; Stocchero, Matteo; Ferrarini, Alberta

2013-12-10

The spontaneous diffusion of solutes through lipid bilayers is still a challenge for theoretical predictions. Since permeation processes remain beyond the capabilities of unbiased molecular dynamics simulations, an alternative strategy is currently adopted to gain insight into their mechanism and time scale. This is based on a monodimensional description of the translocation process only in terms of the position of the solute along the normal to the lipid bilayer, which is formally expressed in the solubility-diffusion model. Actually, a role of orientational and conformational motions has been pointed out, and the use of advanced simulation techniques has been proposed to take into account their effect. Here, we discuss the limitations of the standard solubility-diffusion approach and propose a more general description of membrane translocation as a diffusion process on a free energy surface, which is a function of the translational and rotational degrees of freedom of the molecule. Simple expressions for the permeability coefficient are obtained under suitable conditions. For fast solute reorientation, the classical solubility-diffusion equation is recovered. Under the assumption that well-defined minima can be identified on the free energy landscape, a mechanistic interpretation of the permeability coefficient in terms of all possible permeation paths is given.

How wet should be the reaction coordinate for ligand unbinding?

PubMed

Tiwary, Pratyush; Berne, B J

2016-08-07

We use a recently proposed method called Spectral Gap Optimization of Order Parameters (SGOOP) [P. Tiwary and B. J. Berne, Proc. Natl. Acad. Sci. U. S. A. 113, 2839 (2016)], to determine an optimal 1-dimensional reaction coordinate (RC) for the unbinding of a bucky-ball from a pocket in explicit water. This RC is estimated as a linear combination of the multiple available order parameters that collectively can be used to distinguish the various stable states relevant for unbinding. We pay special attention to determining and quantifying the degree to which water molecules should be included in the RC. Using SGOOP with under-sampled biased simulations, we predict that water plays a distinct role in the reaction coordinate for unbinding in the case when the ligand is sterically constrained to move along an axis of symmetry. This prediction is validated through extensive calculations of the unbinding times through metadynamics and by comparison through detailed balance with unbiased molecular dynamics estimate of the binding time. However when the steric constraint is removed, we find that the role of water in the reaction coordinate diminishes. Here instead SGOOP identifies a good one-dimensional RC involving various motional degrees of freedom.

ClustENM: ENM-Based Sampling of Essential Conformational Space at Full Atomic Resolution

PubMed Central

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

Lipid tail protrusions initiate spontaneous insertion of charged, amphiphilic nanoparticles into lipid bilayers

NASA Astrophysics Data System (ADS)

van Lehn, Reid; Ricci, Maria; Carney, Randy; Voitchovsky, Kislon; Stellacci, Francesco; Alexander-Katz, Alfredo

2014-03-01

Vesicle fusion is a primary mechanism used to mediate the uptake and trafficking of materials both into and between cells. The pathway of vesicle fusion involves the formation of a lipid stalk in which the hydrophobic core regions of two closely associated bilayers merge. The transition state for stalk formation requires the transient protrusion of hydrophobic lipid tails into solvent; favorable contact between these hydrophobic tails then drives stalk creation. In this work, we use unbiased atomistic molecular dynamics simulations to show that lipid tail protrusions can also induce the insertion of charged, amphiphilic nanoparticles (NPs) into lipid bilayers. As in the case of vesicle fusion, the rate-limiting step for NP-bilayer fusion is the stochastic protrusion of aliphatic lipid tails into solvent and into contact with hydrophobic material in the amphiphilic NP monolayer. We confirm our predictions with experiments on supported lipid bilayers. The strong agreement between simulation and experiments indicates that the pre-stalk transition associated with vesicle fusion may be a general mechanism for the insertion of amphiphilic nano-objects that could be prominent in biological systems given the widespread use of NPs in applications ranging from drug delivery to biosensing.

How wet should be the reaction coordinate for ligand unbinding?

NASA Astrophysics Data System (ADS)

Tiwary, Pratyush; Berne, B. J.

2016-08-01

We use a recently proposed method called Spectral Gap Optimization of Order Parameters (SGOOP) [P. Tiwary and B. J. Berne, Proc. Natl. Acad. Sci. U. S. A. 113, 2839 (2016)], to determine an optimal 1-dimensional reaction coordinate (RC) for the unbinding of a bucky-ball from a pocket in explicit water. This RC is estimated as a linear combination of the multiple available order parameters that collectively can be used to distinguish the various stable states relevant for unbinding. We pay special attention to determining and quantifying the degree to which water molecules should be included in the RC. Using SGOOP with under-sampled biased simulations, we predict that water plays a distinct role in the reaction coordinate for unbinding in the case when the ligand is sterically constrained to move along an axis of symmetry. This prediction is validated through extensive calculations of the unbinding times through metadynamics and by comparison through detailed balance with unbiased molecular dynamics estimate of the binding time. However when the steric constraint is removed, we find that the role of water in the reaction coordinate diminishes. Here instead SGOOP identifies a good one-dimensional RC involving various motional degrees of freedom.

How wet should be the reaction coordinate for ligand unbinding?

PubMed Central

Tiwary, Pratyush; Berne, B. J.

2016-01-01

We use a recently proposed method called Spectral Gap Optimization of Order Parameters (SGOOP) [P. Tiwary and B. J. Berne, Proc. Natl. Acad. Sci. U. S. A. 113, 2839 (2016)], to determine an optimal 1-dimensional reaction coordinate (RC) for the unbinding of a bucky-ball from a pocket in explicit water. This RC is estimated as a linear combination of the multiple available order parameters that collectively can be used to distinguish the various stable states relevant for unbinding. We pay special attention to determining and quantifying the degree to which water molecules should be included in the RC. Using SGOOP with under-sampled biased simulations, we predict that water plays a distinct role in the reaction coordinate for unbinding in the case when the ligand is sterically constrained to move along an axis of symmetry. This prediction is validated through extensive calculations of the unbinding times through metadynamics and by comparison through detailed balance with unbiased molecular dynamics estimate of the binding time. However when the steric constraint is removed, we find that the role of water in the reaction coordinate diminishes. Here instead SGOOP identifies a good one-dimensional RC involving various motional degrees of freedom. PMID:27497545

Entropic uncertainty relations and locking: Tight bounds for mutually unbiased bases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ballester, Manuel A.; Wehner, Stephanie

We prove tight entropic uncertainty relations for a large number of mutually unbiased measurements. In particular, we show that a bound derived from the result by Maassen and Uffink [Phys. Rev. Lett. 60, 1103 (1988)] for two such measurements can in fact be tight for up to {radical}(d) measurements in mutually unbiased bases. We then show that using more mutually unbiased bases does not always lead to a better locking effect. We prove that the optimal bound for the accessible information using up to {radical}(d) specific mutually unbiased bases is log d/2, which is the same as can be achievedmore » by using only two bases. Our result indicates that merely using mutually unbiased bases is not sufficient to achieve a strong locking effect and we need to look for additional properties.« less

Efficient Stochastic Rendering of Static and Animated Volumes Using Visibility Sweeps.

PubMed

von Radziewsky, Philipp; Kroes, Thomas; Eisemann, Martin; Eisemann, Elmar

2017-09-01

Stochastically solving the rendering integral (particularly visibility) is the de-facto standard for physically-based light transport but it is computationally expensive, especially when displaying heterogeneous volumetric data. In this work, we present efficient techniques to speed-up the rendering process via a novel visibility-estimation method in concert with an unbiased importance sampling (involving environmental lighting and visibility inside the volume), filtering, and update techniques for both static and animated scenes. Our major contributions include a progressive estimate of partial occlusions based on a fast sweeping-plane algorithm. These occlusions are stored in an octahedral representation, which can be conveniently transformed into a quadtree-based hierarchy suited for a joint importance sampling. Further, we propose sweep-space filtering, which suppresses the occurrence of fireflies and investigate different update schemes for animated scenes. Our technique is unbiased, requires little precomputation, is highly parallelizable, and is applicable to a various volume data sets, dynamic transfer functions, animated volumes and changing environmental lighting.

Whole-Brain Microscopy Meets In Vivo Neuroimaging: Techniques, Benefits, and Limitations.

PubMed

Aswendt, Markus; Schwarz, Martin; Abdelmoula, Walid M; Dijkstra, Jouke; Dedeurwaerdere, Stefanie

2017-02-01

Magnetic resonance imaging, positron emission tomography, and optical imaging have emerged as key tools to understand brain function and neurological disorders in preclinical mouse models. They offer the unique advantage of monitoring individual structural and functional changes over time. What remained unsolved until recently was to generate whole-brain microscopy data which can be correlated to the 3D in vivo neuroimaging data. Conventional histological sections are inappropriate especially for neuronal tracing or the unbiased screening for molecular targets through the whole brain. As part of the European Society for Molecular Imaging (ESMI) meeting 2016 in Utrecht, the Netherlands, we addressed this issue in the Molecular Neuroimaging study group meeting. Presentations covered new brain clearing methods, light sheet microscopes for large samples, and automatic registration of microscopy to in vivo imaging data. In this article, we summarize the discussion; give an overview of the novel techniques; and discuss the practical needs, benefits, and limitations.

Molecular pathogenesis of splenic and nodal marginal zone lymphoma.

PubMed

Spina, Valeria; Rossi, Davide

Genomic studies have improved our understanding of the biological basis of splenic (SMZL) and nodal (NMZL) marginal zone lymphoma by providing a comprehensive and unbiased view of the genes/pathways that are deregulated in these diseases. Consistent with the physiological involvement of NOTCH, NF-κB, B-cell receptor and toll-like receptor signaling in mature B-cells differentiation into the marginal zone B-cells, many oncogenic mutations of genes involved in these pathways have been identified in SMZL and NMZL. Beside genetic lesions, also epigenetic and post-transcriptional modifications contribute to the deregulation of marginal zone B-cell differentiation pathways in SMZL and NMZL. This review describes the progress in understanding the molecular mechanism underlying SMZL and NMZL, including molecular and post-transcriptional modifications, and discusses how information gained from these efforts has provided new insights on potential targets of diagnostic, prognostic and therapeutic relevance in SMZL and NMZL. Copyright © 2016 Elsevier Ltd. All rights reserved.

The dynamics of sex ratio evolution: from the gene perspective to multilevel selection.

PubMed

Argasinski, Krzysztof

2013-01-01

The new dynamical game theoretic model of sex ratio evolution emphasizes the role of males as passive carriers of sex ratio genes. This shows inconsistency between population genetic models of sex ratio evolution and classical strategic models. In this work a novel technique of change of coordinates will be applied to the new model. This will reveal new aspects of the modelled phenomenon which cannot be shown or proven in the original formulation. The underlying goal is to describe the dynamics of selection of particular genes in the entire population, instead of in the same sex subpopulation, as in the previous paper and earlier population genetics approaches. This allows for analytical derivation of the unbiased strategic model from the model with rigorous non-simplified genetics. In effect, an alternative system of replicator equations is derived. It contains two subsystems: the first describes changes in gene frequencies (this is an alternative unbiased formalization of the Fisher-Dusing argument), whereas the second describes changes in the sex ratios in subpopulations of carriers of genes for each strategy. An intriguing analytical result of this work is that the fitness of a gene depends on the current sex ratio in the subpopulation of its carriers, not on the encoded individual strategy. Thus, the argument of the gene fitness function is not constant but is determined by the trajectory of the sex ratio among carriers of that gene. This aspect of the modelled phenomenon cannot be revealed by the static analysis. Dynamics of the sex ratio among gene carriers is driven by a dynamic "tug of war" between female carriers expressing the encoded strategic trait value and random partners of male carriers expressing the average population strategy (a primary sex ratio). This mechanism can be called "double-level selection". Therefore, gene interest perspective leads to multi-level selection.

A New Model for the Estimation of Cell Proliferation Dynamics Using CFSE Data

DTIC Science & Technology

2011-08-20

cells, and hence into the resulting division and death rates . Alternatively, we propose that there is information to be learned not only from...meaningful estimation of population proliferation and death rates in a manner which is unbiased and mechanistically sound. Significantly, this new model is...change in permitting the dependence of the proliferation and death rates (α and β) and the label loss rate (v) on both time t and measured FI x. This

Fractional Brownian motion and the critical dynamics of zipping polymers.

PubMed

Walter, J-C; Ferrantini, A; Carlon, E; Vanderzande, C

2012-03-01

We consider two complementary polymer strands of length L attached by a common-end monomer. The two strands bind through complementary monomers and at low temperatures form a double-stranded conformation (zipping), while at high temperature they dissociate (unzipping). This is a simple model of DNA (or RNA) hairpin formation. Here we investigate the dynamics of the strands at the equilibrium critical temperature T=T(c) using Monte Carlo Rouse dynamics. We find that the dynamics is anomalous, with a characteristic time scaling as τ∼L(2.26(2)), exceeding the Rouse time ∼L(2.18). We investigate the probability distribution function, velocity autocorrelation function, survival probability, and boundary behavior of the underlying stochastic process. These quantities scale as expected from a fractional Brownian motion with a Hurst exponent H=0.44(1). We discuss similarities to and differences from unbiased polymer translocation.

Magic Angle Spinning NMR Metabolomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhi Hu, Jian

Nuclear Magnetic Resonance (NMR) spectroscopy is a non-destructive, quantitative, reproducible, untargeted and unbiased method that requires no or minimal sample preparation, and is one of the leading analytical tools for metabonomics research [1-3]. The easy quantification and the no need of prior knowledge about compounds present in a sample associated with NMR are advantageous over other techniques [1,4]. 1H NMR is especially attractive because protons are present in virtually all metabolites and its NMR sensitivity is high, enabling the simultaneous identification and monitoring of a wide range of low molecular weight metabolites.

Coco is a dual activity modulator of TGFβ signaling

PubMed Central

Deglincerti, Alessia; Haremaki, Tomomi; Warmflash, Aryeh; Sorre, Benoit; Brivanlou, Ali H.

2015-01-01

The TGFβ signaling pathway is a crucial regulator of developmental processes and disease. The activity of TGFβ ligands is modulated by various families of soluble inhibitors that interfere with the interactions between ligands and receptors. In an unbiased, genome-wide RNAi screen to identify genes involved in ligand-dependent signaling, we unexpectedly identified the BMP/Activin/Nodal inhibitor Coco as an enhancer of TGFβ1 signaling. Coco synergizes with TGFβ1 in both cell culture and Xenopus explants. Molecularly, Coco binds to TGFβ1 and enhances TGFβ1 binding to its receptor Alk5. Thus, Coco acts as both an inhibitor and an enhancer of signaling depending on the ligand it binds. This finding raises the need for a global reconsideration of the molecular mechanisms regulating TGFβ signaling. PMID:26116664

Reprogramming neurodegeneration in the big data era.

PubMed

Zhou, Lujia; Verstreken, Patrik

2018-02-01

Recent genome-wide association studies (GWAS) have identified numerous genetic risk variants for late-onset Alzheimer's disease (AD) and Parkinson's disease (PD). However, deciphering the functional consequences of GWAS data is challenging due to a lack of reliable model systems to study the genetic variants that are often of low penetrance and non-coding identities. Pluripotent stem cell (PSC) technologies offer unprecedented opportunities for molecular phenotyping of GWAS variants in human neurons and microglia. Moreover, rapid technological advances in whole-genome RNA-sequencing and epigenome mapping fuel comprehensive and unbiased investigations of molecular alterations in PSC-derived disease models. Here, we review and discuss how integrated studies that utilize PSC technologies and genome-wide approaches may bring new mechanistic insight into the pathogenesis of AD and PD. Copyright © 2018 Elsevier Ltd. All rights reserved.

Genetic Basis of Atherosclerosis: Insights from Mice and Humans

PubMed Central

Stylianou, Ioannis M.; Bauer, Robert C.; Reilly, Muredach P.; Rader, Daniel J.

2012-01-01

Atherosclerosis is a complex and heritable disease involving multiple cell types and the interactions of many different molecular pathways. The genetic and molecular mechanisms of atherosclerosis have in part been elucidated by mouse models; at least 100 different genes have been shown to influence atherosclerosis in mice. Importantly, unbiased genome-wide association studies have recently identified a number of novel loci robustly associated with atherosclerotic coronary artery disease (CAD). Here we review the genetic data elucidated from mouse models of atherosclerosis, as well as significant associations for human CAD. Furthermore, we discuss in greater detail some of these novel human CAD loci. The combination of mouse and human genetics has the potential to identify and validate novel genes that influence atherosclerosis, some of which may be candidates for new therapeutic approaches. PMID:22267839

COLLABORATIVE RESEARCH AND DEVELOPMENT (CR&D) Delivery Order 0059: Molecular Dynamics Modeling Support

DTIC Science & Technology

2008-03-01

Molecular Dynamics Simulations 5 Theory: Equilibrium Molecular Dynamics Simulations 6 Theory: Non...Equilibrium Molecular Dynamics Simulations 8 Carbon Nanotube Simulations : Approach and results from equilibrium and non-equilibrium molecular dynamics ...touched from the perspective of molecular dynamics simulations . However, ordered systems such as “Carbon Nanotubes” have been investigated in terms

A Novel Bifunctional Alkylphenol Anesthetic Allows Characterization of γ-Aminobutyric Acid, Type A (GABAA), Receptor Subunit Binding Selectivity in Synaptosomes.

PubMed

Woll, Kellie A; Murlidaran, Sruthi; Pinch, Benika J; Hénin, Jérôme; Wang, Xiaoshi; Salari, Reza; Covarrubias, Manuel; Dailey, William P; Brannigan, Grace; Garcia, Benjamin A; Eckenhoff, Roderic G

2016-09-23

Propofol, an intravenous anesthetic, is a positive modulator of the GABAA receptor, but the mechanistic details, including the relevant binding sites and alternative targets, remain disputed. Here we undertook an in-depth study of alkylphenol-based anesthetic binding to synaptic membranes. We designed, synthesized, and characterized a chemically active alkylphenol anesthetic (2-((prop-2-yn-1-yloxy)methyl)-5-(3-(trifluoromethyl)-3H-diazirin-3-yl)phenol, AziPm-click (1)), for affinity-based protein profiling (ABPP) of propofol-binding proteins in their native state within mouse synaptosomes. The ABPP strategy captured ∼4% of the synaptosomal proteome, including the unbiased capture of five α or β GABAA receptor subunits. Lack of γ2 subunit capture was not due to low abundance. Consistent with this, independent molecular dynamics simulations with alchemical free energy perturbation calculations predicted selective propofol binding to interfacial sites, with higher affinities for α/β than γ-containing interfaces. The simulations indicated hydrogen bonding is a key component leading to propofol-selective binding within GABAA receptor subunit interfaces, with stable hydrogen bonds observed between propofol and α/β cavity residues but not γ cavity residues. We confirmed this by introducing a hydrogen bond-null propofol analogue as a protecting ligand for targeted-ABPP and observed a lack of GABAA receptor subunit protection. This investigation demonstrates striking interfacial GABAA receptor subunit selectivity in the native milieu, suggesting that asymmetric occupancy of heteropentameric ion channels by alkylphenol-based anesthetics is sufficient to induce modulation of activity. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Cluster Free Energies from Simple Simulations of Small Numbers of Aggregants: Nucleation of Liquid MTBE from Vapor and Aqueous Phases.

PubMed

Patel, Lara A; Kindt, James T

2017-03-14

We introduce a global fitting analysis method to obtain free energies of association of noncovalent molecular clusters using equilibrated cluster size distributions from unbiased constant-temperature molecular dynamics (MD) simulations. Because the systems simulated are small enough that the law of mass action does not describe the aggregation statistics, the method relies on iteratively determining a set of cluster free energies that, using appropriately weighted sums over all possible partitions of N monomers into clusters, produces the best-fit size distribution. The quality of these fits can be used as an objective measure of self-consistency to optimize the cutoff distance that determines how clusters are defined. To showcase the method, we have simulated a united-atom model of methyl tert-butyl ether (MTBE) in the vapor phase and in explicit water solution over a range of system sizes (up to 95 MTBE in the vapor phase and 60 MTBE in the aqueous phase) and concentrations at 273 K. The resulting size-dependent cluster free energy functions follow a form derived from classical nucleation theory (CNT) quite well over the full range of cluster sizes, although deviations are more pronounced for small cluster sizes. The CNT fit to cluster free energies yielded surface tensions that were in both cases lower than those for the simulated planar interfaces. We use a simple model to derive a condition for minimizing non-ideal effects on cluster size distributions and show that the cutoff distance that yields the best global fit is consistent with this condition.

Note: On the relation between Lifson-Jackson and Derrida formulas for effective diffusion coefficient

NASA Astrophysics Data System (ADS)

Kalnin, Juris R.; Berezhkovskii, Alexander M.

2013-11-01

The Lifson-Jackson formula provides the effective free diffusion coefficient for a particle diffusing in an arbitrary one-dimensional periodic potential. Its counterpart, when the underlying dynamics is described in terms of an unbiased nearest-neighbor Markovian random walk on a one-dimensional periodic lattice is given by the formula obtained by Derrida. It is shown that the latter formula can be considered as a discretized version of the Lifson-Jackson formula with correctly chosen position-dependent diffusion coefficient.

Exploring activity-driven network with biased walks

NASA Astrophysics Data System (ADS)

Wang, Yan; Wu, Ding Juan; Lv, Fang; Su, Meng Long

We investigate the concurrent dynamics of biased random walks and the activity-driven network, where the preferential transition probability is in terms of the edge-weighting parameter. We also obtain the analytical expressions for stationary distribution and the coverage function in directed and undirected networks, all of which depend on the weight parameter. Appropriately adjusting this parameter, more effective search strategy can be obtained when compared with the unbiased random walk, whether in directed or undirected networks. Since network weights play a significant role in the diffusion process.

Multilayer-MCTDH approach to the energy transfer dynamics in the LH2 antenna complex

NASA Astrophysics Data System (ADS)

Shibl, Mohamed F.; Schulze, Jan; Al-Marri, Mohammed J.; Kühn, Oliver

2017-09-01

The multilayer multiconfiguration time-dependent Hartree method is used to study the coupled exciton-vibrational dynamics in a high-dimensional nonameric model of the LH2 antenna complex of purple bacteria. The exciton-vibrational coupling is parametrized within the Huang-Rhys model according to phonon and intramolecular vibrational modes derived from an experimental bacteriochlorophyll spectral density. In contrast to reduced density matrix approaches, the Schrödinger equation is solved explicitly, giving access to the full wave function. This facilitates an unbiased analysis in terms of the coupled dynamics of excitonic and vibrational degrees of freedom. For the present system, we identify spectator modes for the B800 to B800 transfer and we find a non-additive effect of phonon and intramolecular vibrational modes on the B800 to B850 exciton transfer.

Peripheral Blood Gene Expression as a Novel Genomic Biomarker in Complicated Sarcoidosis

PubMed Central

Sweiss, Nadera J.; Chen, Edward S.; Moller, David R.; Knox, Kenneth S.; Ma, Shwu-Fan; Wade, Michael S.; Noth, Imre; Machado, Roberto F.; Garcia, Joe G. N.

2012-01-01

Sarcoidosis, a systemic granulomatous syndrome invariably affecting the lung, typically spontaneously remits but in ∼20% of cases progresses with severe lung dysfunction or cardiac and neurologic involvement (complicated sarcoidosis). Unfortunately, current biomarkers fail to distinguish patients with remitting (uncomplicated) sarcoidosis from other fibrotic lung disorders, and fail to identify individuals at risk for complicated sarcoidosis. We utilized genome-wide peripheral blood gene expression analysis to identify a 20-gene sarcoidosis biomarker signature distinguishing sarcoidosis (n = 39) from healthy controls (n = 35, 86% classification accuracy) and which served as a molecular signature for complicated sarcoidosis (n = 17). As aberrancies in T cell receptor (TCR) signaling, JAK-STAT (JS) signaling, and cytokine-cytokine receptor (CCR) signaling are implicated in sarcoidosis pathogenesis, a 31-gene signature comprised of T cell signaling pathway genes associated with sarcoidosis (TCR/JS/CCR) was compared to the unbiased 20-gene biomarker signature but proved inferior in prediction accuracy in distinguishing complicated from uncomplicated sarcoidosis. Additional validation strategies included significant association of single nucleotide polymorphisms (SNPs) in signature genes with sarcoidosis susceptibility and severity (unbiased signature genes - CX3CR1, FKBP1A, NOG, RBM12B, SENS3, TSHZ2; T cell/JAK-STAT pathway genes such as AKT3, CBLB, DLG1, IFNG, IL2RA, IL7R, ITK, JUN, MALT1, NFATC2, PLCG1, SPRED1). In summary, this validated peripheral blood molecular gene signature appears to be a valuable biomarker in identifying cases with sarcoidoisis and predicting risk for complicated sarcoidosis. PMID:22984568

Transcriptional profiling at whole population and single cell levels reveals somatosensory neuron molecular diversity

PubMed Central

Chiu, Isaac M; Barrett, Lee B; Williams, Erika K; Strochlic, David E; Lee, Seungkyu; Weyer, Andy D; Lou, Shan; Bryman, Gregory S; Roberson, David P; Ghasemlou, Nader; Piccoli, Cara; Ahat, Ezgi; Wang, Victor; Cobos, Enrique J; Stucky, Cheryl L; Ma, Qiufu; Liberles, Stephen D; Woolf, Clifford J

2014-01-01

The somatosensory nervous system is critical for the organism's ability to respond to mechanical, thermal, and nociceptive stimuli. Somatosensory neurons are functionally and anatomically diverse but their molecular profiles are not well-defined. Here, we used transcriptional profiling to analyze the detailed molecular signatures of dorsal root ganglion (DRG) sensory neurons. We used two mouse reporter lines and surface IB4 labeling to purify three major non-overlapping classes of neurons: 1) IB4+SNS-Cre/TdTomato+, 2) IB4−SNS-Cre/TdTomato+, and 3) Parv-Cre/TdTomato+ cells, encompassing the majority of nociceptive, pruriceptive, and proprioceptive neurons. These neurons displayed distinct expression patterns of ion channels, transcription factors, and GPCRs. Highly parallel qRT-PCR analysis of 334 single neurons selected by membership of the three populations demonstrated further diversity, with unbiased clustering analysis identifying six distinct subgroups. These data significantly increase our knowledge of the molecular identities of known DRG populations and uncover potentially novel subsets, revealing the complexity and diversity of those neurons underlying somatosensation. DOI: http://dx.doi.org/10.7554/eLife.04660.001 PMID:25525749

New molecular medicine: Diagnomics and pharmacogenomics

NASA Astrophysics Data System (ADS)

Kauffman, Michael G.

1999-04-01

Millennium Predictive Medicine (MPMx), a subsidiary of Millennium Pharmaceuticals, is focusing on the discovery and clinical validation of Diagnomic and Pharmacogenomic Tests which will replace many of the subjective elements of clinical decision making. Diagnomics are molecular diagnostic markers with prognostic and economic impact. While the majority of currently available diagnostics represent data points, Diagnomics allow patients and physicians to make scientifically based, individualized decisions about their disease and its therapy. Pharmacogenomics are diagnostics that specify the use or avoidance of specific therapeutics based on an individual genotype and/or disease subtype. MPMx uses the broad Millennium genomics, proteomics, and bioinformatics technologies in the analysis of human disease and drug response. These technologies permit global and unbiased approaches towards the elucidation of disease pathways and mechanisms at the molecular level. Germline or somatic mutations, RNA levels, or protein levels comprising these pathways and mechanisms are currently being evaluated as markers for disease predisposition, stage, aggressiveness, and likely drug response or drug toxicity. Diagnomic and Pharmacogenomic Tests are part of the new molecular medicine that is transforming clinical practice forma symptom/pathology-based art into a pre-symptom, mechanism- based science.

A statistical test of unbiased evolution of body size in birds.

PubMed

Bokma, Folmer

2002-12-01

Of the approximately 9500 bird species, the vast majority is small-bodied. That is a general feature of evolutionary lineages, also observed for instance in mammals and plants. The avian interspecific body size distribution is right-skewed even on a logarithmic scale. That has previously been interpreted as evidence that body size evolution has been biased. However, a procedure to test for unbiased evolution from the shape of body size distributions was lacking. In the present paper unbiased body size evolution is defined precisely, and a statistical test is developed based on Monte Carlo simulation of unbiased evolution. Application of the test to birds suggests that it is highly unlikely that avian body size evolution has been unbiased as defined. Several possible explanations for this result are discussed. A plausible explanation is that the general model of unbiased evolution assumes that population size and generation time do not affect the evolutionary variability of body size; that is, that micro- and macroevolution are decoupled, which theory suggests is not likely to be the case.

Mutually unbiased bases and semi-definite programming

NASA Astrophysics Data System (ADS)

Brierley, Stephen; Weigert, Stefan

2010-11-01

A complex Hilbert space of dimension six supports at least three but not more than seven mutually unbiased bases. Two computer-aided analytical methods to tighten these bounds are reviewed, based on a discretization of parameter space and on Gröbner bases. A third algorithmic approach is presented: the non-existence of more than three mutually unbiased bases in composite dimensions can be decided by a global optimization method known as semidefinite programming. The method is used to confirm that the spectral matrix cannot be part of a complete set of seven mutually unbiased bases in dimension six.

A concurrent multiscale micromorphic molecular dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Shaofan, E-mail: shaofan@berkeley.edu; Tong, Qi

2015-04-21

In this work, we have derived a multiscale micromorphic molecular dynamics (MMMD) from first principle to extend the (Andersen)-Parrinello-Rahman molecular dynamics to mesoscale and continuum scale. The multiscale micromorphic molecular dynamics is a con-current three-scale dynamics that couples a fine scale molecular dynamics, a mesoscale micromorphic dynamics, and a macroscale nonlocal particle dynamics together. By choosing proper statistical closure conditions, we have shown that the original Andersen-Parrinello-Rahman molecular dynamics is the homogeneous and equilibrium case of the proposed multiscale micromorphic molecular dynamics. In specific, we have shown that the Andersen-Parrinello-Rahman molecular dynamics can be rigorously formulated and justified from firstmore » principle, and its general inhomogeneous case, i.e., the three scale con-current multiscale micromorphic molecular dynamics can take into account of macroscale continuum mechanics boundary condition without the limitation of atomistic boundary condition or periodic boundary conditions. The discovered multiscale scale structure and the corresponding multiscale dynamics reveal a seamless transition from atomistic scale to continuum scale and the intrinsic coupling mechanism among them based on first principle formulation.« less

An Analysis of the Abstracts Presented at the Annual Meetings of the Society for Neuroscience from 2001 to 2006

PubMed Central

Lin, John M.; Bohland, Jason W.; Andrews, Peter; Burns, Gully A. P. C.; Allen, Cara B.; Mitra, Partha P.

2008-01-01

Annual meeting abstracts published by scientific societies often contain rich arrays of information that can be computationally mined and distilled to elucidate the state and dynamics of the subject field. We extracted and processed abstract data from the Society for Neuroscience (SFN) annual meeting abstracts during the period 2001–2006 in order to gain an objective view of contemporary neuroscience. An important first step in the process was the application of data cleaning and disambiguation methods to construct a unified database, since the data were too noisy to be of full utility in the raw form initially available. Using natural language processing, text mining, and other data analysis techniques, we then examined the demographics and structure of the scientific collaboration network, the dynamics of the field over time, major research trends, and the structure of the sources of research funding. Some interesting findings include a high geographical concentration of neuroscience research in the north eastern United States, a surprisingly large transient population (66% of the authors appear in only one out of the six studied years), the central role played by the study of neurodegenerative disorders in the neuroscience community, and an apparent growth of behavioral/systems neuroscience with a corresponding shrinkage of cellular/molecular neuroscience over the six year period. The results from this work will prove useful for scientists, policy makers, and funding agencies seeking to gain a complete and unbiased picture of the community structure and body of knowledge encapsulated by a specific scientific domain. PMID:18446237

Structure and spectral features of H+(H2O)7: Eigen versus Zundel forms.

PubMed

Shin, Ilgyou; Park, Mina; Min, Seung Kyu; Lee, Eun Cheol; Suh, Seung Bum; Kim, Kwang S

2006-12-21

The two dimensional (2D) to three dimensional (3D) transition for the protonated water cluster has been controversial, in particular, for H(+)(H(2)O)(7). For H(+)(H(2)O)(7) the 3D structure is predicted to be lower in energy than the 2D structure at most levels of theory without zero-point energy (ZPE) correction. On the other hand, with ZPE correction it is predicted to be either 2D or 3D depending on the calculational levels. Although the ZPE correction favors the 3D structure at the level of coupled cluster theory with singles, doubles, and perturbative triples excitations [CCSD(T)] using the aug-cc-pVDZ basis set, the result based on the anharmonic zero-point vibrational energy correction favors the 2D structure. Therefore, the authors investigated the energies based on the complete basis set limit scheme (which we devised in an unbiased way) at the resolution of the identity approximation Moller-Plesset second order perturbation theory and CCSD(T) levels, and found that the 2D structure has the lowest energy for H(+)(H(2)O)(7) [though nearly isoenergetic to the 3D structure for D(+)(D(2)O)(7)]. This structure has the Zundel-type configuration, but it shows the quantum probabilistic distribution including some of the Eigen-type configuration. The vibrational spectra of MP2/aug-cc-pVDZ calculations and Car-Parrinello molecular dynamics simulations, taking into account the thermal and dynamic effects, show that the 2D Zundel-type form is in good agreement with experiments.

Structure and spectral features of H+(H2O)7: Eigen versus Zundel forms

NASA Astrophysics Data System (ADS)

Shin, Ilgyou; Park, Mina; Min, Seung Kyu; Lee, Eun Cheol; Suh, Seung Bum; Kim, Kwang S.

2006-12-01

The two dimensional (2D) to three dimensional (3D) transition for the protonated water cluster has been controversial, in particular, for H+(H2O)7. For H+(H2O)7 the 3D structure is predicted to be lower in energy than the 2D structure at most levels of theory without zero-point energy (ZPE) correction. On the other hand, with ZPE correction it is predicted to be either 2D or 3D depending on the calculational levels. Although the ZPE correction favors the 3D structure at the level of coupled cluster theory with singles, doubles, and perturbative triples excitations [CCSD(T)] using the aug-cc-pVDZ basis set, the result based on the anharmonic zero-point vibrational energy correction favors the 2D structure. Therefore, the authors investigated the energies based on the complete basis set limit scheme (which we devised in an unbiased way) at the resolution of the identity approximation Møller-Plesset second order perturbation theory and CCSD(T) levels, and found that the 2D structure has the lowest energy for H+(H2O)7 [though nearly isoenergetic to the 3D structure for D+(D2O)7]. This structure has the Zundel-type configuration, but it shows the quantum probabilistic distribution including some of the Eigen-type configuration. The vibrational spectra of MP2/aug-cc-pVDZ calculations and Car-Parrinello molecular dynamics simulations, taking into account the thermal and dynamic effects, show that the 2D Zundel-type form is in good agreement with experiments.

Jumping genes: Genomic ballast or powerhouse of biological diversification.

PubMed

Choudhury, Rimjhim Roy; Parisod, Christian

2017-09-01

Studying hybridization has the potential to elucidate challenging questions in evolutionary biology such as the nature of adaptive genetic variation and reproductive isolation. A growing body of work highlights that the merging of divergent genomes goes beyond the reshuffling of standing variation from related species and promotes mutations (Abbott et al., ). However, to what extent such genome instability generates evolutionary significant variation remains largely elusive. In this issue of Molecular Ecology, Dennenmoser et al. () report considerable dynamics of transposable elements (TEs) in a recent invasive fish species of hybrid origin (Cottus; Figure ). It adds to the recent examples from plants to support TE-specific genome variation following hybridization. Insights from early, as well as established, hybrids are largely coherent with increased TE activity, and this fish system thus represents an inspiring opportunity to further address the possible association between genome dynamics and "rapid evolution of hybrid species." This work based on genome (re)sequencing contrasts with prior transcriptomics or PCR-based studies of TEs and illustrates how unprecedented amount of information promises a better understanding of the multiple patterns of variation across eukaryotic genomes; provided that we get the better of methodological advances. As discussed here, unbiased assessment of TE variation from genome surveys indeed remains a challenge precluding firm conclusions to be reached about the evolutionary significance of TEs. Despite methodological and conceptual developments that appear necessary to unambiguously uncover the unexplored iceberg below the known tip, the role of coding genes vs. TEs in promoting adaptation and speciation might be clarified in a not so remote future. © 2017 John Wiley & Sons Ltd.

Residues remote from the binding pocket control the antagonist selectivity towards the corticotropin-releasing factor receptor-1

NASA Astrophysics Data System (ADS)

Sun, Xianqiang; Cheng, Jianxin; Wang, Xu; Tang, Yun; Ågren, Hans; Tu, Yaoquan

2015-01-01

The corticotropin releasing factors receptor-1 and receptor-2 (CRF1R and CRF2R) are therapeutic targets for treating neurological diseases. Antagonists targeting CRF1R have been developed for the potential treatment of anxiety disorders and alcohol addiction. It has been found that antagonists targeting CRF1R always show high selectivity, although CRF1R and CRF2R share a very high rate of sequence identity. This has inspired us to study the origin of the selectivity of the antagonists. We have therefore built a homology model for CRF2R and carried out unbiased molecular dynamics and well-tempered metadynamics simulations for systems with the antagonist CP-376395 in CRF1R or CRF2R to address this issue. We found that the side chain of Tyr6.63 forms a hydrogen bond with the residue remote from the binding pocket, which allows Tyr6.63 to adopt different conformations in the two receptors and results in the presence or absence of a bottleneck controlling the antagonist binding to or dissociation from the receptors. The rotameric switch of the side chain of Tyr3566.63 allows the breaking down of the bottleneck and is a perquisite for the dissociation of CP-376395 from CRF1R.

Residues remote from the binding pocket control the antagonist selectivity towards the corticotropin-releasing factor receptor-1.

PubMed

Sun, Xianqiang; Cheng, Jianxin; Wang, Xu; Tang, Yun; Ågren, Hans; Tu, Yaoquan

2015-01-28

The corticotropin releasing factors receptor-1 and receptor-2 (CRF1R and CRF2R) are therapeutic targets for treating neurological diseases. Antagonists targeting CRF1R have been developed for the potential treatment of anxiety disorders and alcohol addiction. It has been found that antagonists targeting CRF1R always show high selectivity, although CRF1R and CRF2R share a very high rate of sequence identity. This has inspired us to study the origin of the selectivity of the antagonists. We have therefore built a homology model for CRF2R and carried out unbiased molecular dynamics and well-tempered metadynamics simulations for systems with the antagonist CP-376395 in CRF1R or CRF2R to address this issue. We found that the side chain of Tyr(6.63) forms a hydrogen bond with the residue remote from the binding pocket, which allows Tyr(6.63) to adopt different conformations in the two receptors and results in the presence or absence of a bottleneck controlling the antagonist binding to or dissociation from the receptors. The rotameric switch of the side chain of Tyr356(6.63) allows the breaking down of the bottleneck and is a perquisite for the dissociation of CP-376395 from CRF1R.

NMSim web server: integrated approach for normal mode-based geometric simulations of biologically relevant conformational transitions in proteins.

PubMed

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.

A Smoluchowski model of crystallization dynamics of small colloidal clusters

NASA Astrophysics Data System (ADS)

Beltran-Villegas, Daniel J.; Sehgal, Ray M.; Maroudas, Dimitrios; Ford, David M.; Bevan, Michael A.

2011-10-01

We investigate the dynamics of colloidal crystallization in a 32-particle system at a fixed value of interparticle depletion attraction that produces coexisting fluid and solid phases. Free energy landscapes (FELs) and diffusivity landscapes (DLs) are obtained as coefficients of 1D Smoluchowski equations using as order parameters either the radius of gyration or the average crystallinity. FELs and DLs are estimated by fitting the Smoluchowski equations to Brownian dynamics (BD) simulations using either linear fits to locally initiated trajectories or global fits to unbiased trajectories using Bayesian inference. The resulting FELs are compared to Monte Carlo Umbrella Sampling results. The accuracy of the FELs and DLs for modeling colloidal crystallization dynamics is evaluated by comparing mean first-passage times from BD simulations with analytical predictions using the FEL and DL models. While the 1D models accurately capture dynamics near the free energy minimum fluid and crystal configurations, predictions near the transition region are not quantitatively accurate. A preliminary investigation of ensemble averaged 2D order parameter trajectories suggests that 2D models are required to capture crystallization dynamics in the transition region.

Cavitand-grafted silicon microcantilevers as a universal probe for illicit and designer drugs in water.

PubMed

Biavardi, Elisa; Federici, Stefania; Tudisco, Cristina; Menozzi, Daniela; Massera, Chiara; Sottini, Andrea; Condorelli, Guglielmo G; Bergese, Paolo; Dalcanale, Enrico

2014-08-25

The direct, clean, and unbiased transduction of molecular recognition into a readable and reproducible response is the biggest challenge associated to the use of synthetic receptors in sensing. All possible solutions demand the mastering of molecular recognition at the solid-liquid interface as prerequisite. The socially relevant issue of screening amine-based illicit and designer drugs is addressed by nanomechanical recognition at the silicon-water interface. The methylamino moieties of different drugs are all first recognized by a single cavitand receptor through a synergistic set of weak interactions. The peculiar recognition ability of the cavitand is then transferred with high fidelity and robustness on silicon microcantilevers and harnessed to realize a nanomechanical device for label-free detection of these drugs in water. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Construction of 4D high-definition cortical surface atlases of infants: Methods and applications.

PubMed

Li, Gang; Wang, Li; Shi, Feng; Gilmore, John H; Lin, Weili; Shen, Dinggang

2015-10-01

In neuroimaging, cortical surface atlases play a fundamental role for spatial normalization, analysis, visualization, and comparison of results across individuals and different studies. However, existing cortical surface atlases created for adults are not suitable for infant brains during the first two postnatal years, which is the most dynamic period of postnatal structural and functional development of the highly-folded cerebral cortex. Therefore, spatiotemporal cortical surface atlases for infant brains are highly desired yet still lacking for accurate mapping of early dynamic brain development. To bridge this significant gap, leveraging our infant-dedicated computational pipeline for cortical surface-based analysis and the unique longitudinal infant MRI dataset acquired in our research center, in this paper, we construct the first spatiotemporal (4D) high-definition cortical surface atlases for the dynamic developing infant cortical structures at seven time points, including 1, 3, 6, 9, 12, 18, and 24 months of age, based on 202 serial MRI scans from 35 healthy infants. For this purpose, we develop a novel method to ensure the longitudinal consistency and unbiasedness to any specific subject and age in our 4D infant cortical surface atlases. Specifically, we first compute the within-subject mean cortical folding by unbiased groupwise registration of longitudinal cortical surfaces of each infant. Then we establish longitudinally-consistent and unbiased inter-subject cortical correspondences by groupwise registration of the geometric features of within-subject mean cortical folding across all infants. Our 4D surface atlases capture both longitudinally-consistent dynamic mean shape changes and the individual variability of cortical folding during early brain development. Experimental results on two independent infant MRI datasets show that using our 4D infant cortical surface atlases as templates leads to significantly improved accuracy for spatial normalization of cortical surfaces across infant individuals, in comparison to the infant surface atlases constructed without longitudinal consistency and also the FreeSurfer adult surface atlas. Moreover, based on our 4D infant surface atlases, for the first time, we reveal the spatially-detailed, region-specific correlation patterns of the dynamic cortical developmental trajectories between different cortical regions during early brain development. Copyright © 2015 Elsevier B.V. All rights reserved.

Thermally induced charge current through long molecules

NASA Astrophysics Data System (ADS)

Zimbovskaya, Natalya A.; Nitzan, Abraham

2018-01-01

In this work, we theoretically study steady state thermoelectric transport through a single-molecule junction with a long chain-like bridge. Electron transmission through the system is computed using a tight-binding model for the bridge. We analyze dependences of thermocurrent on the bridge length in unbiased and biased systems operating within and beyond the linear response regime. It is shown that the length-dependent thermocurrent is controlled by the lineshape of electron transmission in the interval corresponding to the HOMO/LUMO transport channel. Also, it is demonstrated that electron interactions with molecular vibrations may significantly affect the length-dependent thermocurrent.

Unbiasedness

USGS Publications Warehouse

Link, W.A.; Armitage, Peter; Colton, Theodore

1998-01-01

Unbiasedness is probably the best known criterion for evaluating the performance of estimators. This note describes unbiasedness, demonstrating various failings of the criterion. It is shown that unbiased estimators might not exist, or might not be unique; an example of a unique but clearly unacceptable unbiased estimator is given. It is shown that unbiased estimators are not translation invariant. Various alternative criteria are described, and are illustrated through examples.

FAST TRACK COMMUNICATION: Affine constellations without mutually unbiased counterparts

NASA Astrophysics Data System (ADS)

Weigert, Stefan; Durt, Thomas

2010-10-01

It has been conjectured that a complete set of mutually unbiased bases in a space of dimension d exists if and only if there is an affine plane of order d. We introduce affine constellations and compare their existence properties with those of mutually unbiased constellations. The observed discrepancies make a deeper relation between the two existence problems unlikely.

Conformational Smear Characterization and Binning of Single-Molecule Conductance Measurements for Enhanced Molecular Recognition.

PubMed

Korshoj, Lee E; Afsari, Sepideh; Chatterjee, Anushree; Nagpal, Prashant

2017-11-01

Electronic conduction or charge transport through single molecules depends primarily on molecular structure and anchoring groups and forms the basis for a wide range of studies from molecular electronics to DNA sequencing. Several high-throughput nanoelectronic methods such as mechanical break junctions, nanopores, conductive atomic force microscopy, scanning tunneling break junctions, and static nanoscale electrodes are often used for measuring single-molecule conductance. In these measurements, "smearing" due to conformational changes and other entropic factors leads to large variances in the observed molecular conductance, especially in individual measurements. Here, we show a method for characterizing smear in single-molecule conductance measurements and demonstrate how binning measurements according to smear can significantly enhance the use of individual conductance measurements for molecular recognition. Using quantum point contact measurements on single nucleotides within DNA macromolecules, we demonstrate that the distance over which molecular junctions are maintained is a measure of smear, and the resulting variance in unbiased single measurements depends on this smear parameter. Our ability to identify individual DNA nucleotides at 20× coverage increases from 81.3% accuracy without smear analysis to 93.9% with smear characterization and binning (SCRIB). Furthermore, merely 7 conductance measurements (7× coverage) are needed to achieve 97.8% accuracy for DNA nucleotide recognition when only low molecular smear measurements are used, which represents a significant improvement over contemporary sequencing methods. These results have important implications in a broad range of molecular electronics applications from designing robust molecular switches to nanoelectronic DNA sequencing.

Optimal reconstruction of the states in qutrit systems

NASA Astrophysics Data System (ADS)

Yan, Fei; Yang, Ming; Cao, Zhuo-Liang

2010-10-01

Based on mutually unbiased measurements, an optimal tomographic scheme for the multiqutrit states is presented explicitly. Because the reconstruction process of states based on mutually unbiased states is free of information waste, we refer to our scheme as the optimal scheme. By optimal we mean that the number of the required conditional operations reaches the minimum in this tomographic scheme for the states of qutrit systems. Special attention will be paid to how those different mutually unbiased measurements are realized; that is, how to decompose each transformation that connects each mutually unbiased basis with the standard computational basis. It is found that all those transformations can be decomposed into several basic implementable single- and two-qutrit unitary operations. For the three-qutrit system, there exist five different mutually unbiased-bases structures with different entanglement properties, so we introduce the concept of physical complexity to minimize the number of nonlocal operations needed over the five different structures. This scheme is helpful for experimental scientists to realize the most economical reconstruction of quantum states in qutrit systems.

Rationalization of reduced penetration of drugs through ceramide gel phase membrane.

PubMed

Paloncýová, Markéta; DeVane, Russell H; Murch, Bruce P; Berka, Karel; Otyepka, Michal

2014-11-25

Since computing resources have advanced enough to allow routine molecular simulation studies of drug molecules interacting with biologically relevant membranes, a considerable amount of work has been carried out with fluid phospholipid systems. However, there is very little work in the literature on drug interactions with gel phase lipids. This poses a significant limitation for understanding permeation through the stratum corneum where the primary pathway is expected to be through a highly ordered lipid matrix. To address this point, we analyzed the interactions of p-aminobenzoic acid (PABA) and its ethyl (benzocaine) and butyl (butamben) esters with two membrane bilayers, which differ in their fluidity at ambient conditions. We considered a dioleoylphosphatidylcholine (DOPC) bilayer in a fluid state and a ceramide 2 (CER2, ceramide NS) bilayer in a gel phase. We carried out unbiased (100 ns long) and biased z-constraint molecular dynamics simulations and calculated the free energy profiles of all molecules along the bilayer normal. The free energy profiles converged significantly slower for the gel phase. While the compounds have comparable affinities for both membranes, they exhibit penetration barriers almost 3 times higher in the gel phase CER2 bilayer. This elevated barrier and slower diffusion in the CER2 bilayer, which are caused by the high ordering of CER2 lipid chains, explain the low permeability of the gel phase membranes. We also compared the free energy profiles from MD simulations with those obtained from COSMOmic. This method provided the same trends in behavior for the guest molecules in both bilayers; however, the penetration barriers calculated by COSMOmic did not differ between membranes. In conclusion, we show how membrane fluid properties affect the interaction of drug-like molecules with membranes.

Equations of State for Mixtures: Results from DFT Simulations of Xenon/Ethane Mixtures Compared to High Accuracy Validation Experiments on Z

NASA Astrophysics Data System (ADS)

Magyar, Rudolph

2013-06-01

We report a computational and validation study of equation of state (EOS) properties of liquid / dense plasma mixtures of xenon and ethane to explore and to illustrate the physics of the molecular scale mixing of light elements with heavy elements. Accurate EOS models are crucial to achieve high-fidelity hydrodynamics simulations of many high-energy-density phenomena such as inertial confinement fusion and strong shock waves. While the EOS is often tabulated for separate species, the equation of state for arbitrary mixtures is generally not available, requiring properties of the mixture to be approximated by combining physical properties of the pure systems. The main goal of this study is to access how accurate this approximation is under shock conditions. Density functional theory molecular dynamics (DFT-MD) at elevated-temperature and pressure is used to assess the thermodynamics of the xenon-ethane mixture. The simulations are unbiased as to elemental species and therefore provide comparable accuracy when describing total energies, pressures, and other physical properties of mixtures as they do for pure systems. In addition, we have performed shock compression experiments using the Sandia Z-accelerator on pure xenon, ethane, and various mixture ratios thereof. The Hugoniot results are compared to the DFT-MD results and the predictions of different rules for combing EOS tables. The DFT-based simulation results compare well with the experimental points, and it is found that a mixing rule based on pressure equilibration performs reliably well for the mixtures considered. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Unbiased Quantitative Models of Protein Translation Derived from Ribosome Profiling Data

PubMed Central

Gritsenko, Alexey A.; Hulsman, Marc; Reinders, Marcel J. T.; de Ridder, Dick

2015-01-01

Translation of RNA to protein is a core process for any living organism. While for some steps of this process the effect on protein production is understood, a holistic understanding of translation still remains elusive. In silico modelling is a promising approach for elucidating the process of protein synthesis. Although a number of computational models of the process have been proposed, their application is limited by the assumptions they make. Ribosome profiling (RP), a relatively new sequencing-based technique capable of recording snapshots of the locations of actively translating ribosomes, is a promising source of information for deriving unbiased data-driven translation models. However, quantitative analysis of RP data is challenging due to high measurement variance and the inability to discriminate between the number of ribosomes measured on a gene and their speed of translation. We propose a solution in the form of a novel multi-scale interpretation of RP data that allows for deriving models with translation dynamics extracted from the snapshots. We demonstrate the usefulness of this approach by simultaneously determining for the first time per-codon translation elongation and per-gene translation initiation rates of Saccharomyces cerevisiae from RP data for two versions of the Totally Asymmetric Exclusion Process (TASEP) model of translation. We do this in an unbiased fashion, by fitting the models using only RP data with a novel optimization scheme based on Monte Carlo simulation to keep the problem tractable. The fitted models match the data significantly better than existing models and their predictions show better agreement with several independent protein abundance datasets than existing models. Results additionally indicate that the tRNA pool adaptation hypothesis is incomplete, with evidence suggesting that tRNA post-transcriptional modifications and codon context may play a role in determining codon elongation rates. PMID:26275099

Unbiased Quantitative Models of Protein Translation Derived from Ribosome Profiling Data.

PubMed

Gritsenko, Alexey A; Hulsman, Marc; Reinders, Marcel J T; de Ridder, Dick

2015-08-01

Translation of RNA to protein is a core process for any living organism. While for some steps of this process the effect on protein production is understood, a holistic understanding of translation still remains elusive. In silico modelling is a promising approach for elucidating the process of protein synthesis. Although a number of computational models of the process have been proposed, their application is limited by the assumptions they make. Ribosome profiling (RP), a relatively new sequencing-based technique capable of recording snapshots of the locations of actively translating ribosomes, is a promising source of information for deriving unbiased data-driven translation models. However, quantitative analysis of RP data is challenging due to high measurement variance and the inability to discriminate between the number of ribosomes measured on a gene and their speed of translation. We propose a solution in the form of a novel multi-scale interpretation of RP data that allows for deriving models with translation dynamics extracted from the snapshots. We demonstrate the usefulness of this approach by simultaneously determining for the first time per-codon translation elongation and per-gene translation initiation rates of Saccharomyces cerevisiae from RP data for two versions of the Totally Asymmetric Exclusion Process (TASEP) model of translation. We do this in an unbiased fashion, by fitting the models using only RP data with a novel optimization scheme based on Monte Carlo simulation to keep the problem tractable. The fitted models match the data significantly better than existing models and their predictions show better agreement with several independent protein abundance datasets than existing models. Results additionally indicate that the tRNA pool adaptation hypothesis is incomplete, with evidence suggesting that tRNA post-transcriptional modifications and codon context may play a role in determining codon elongation rates.

Differentiation of five body fluids from forensic samples by expression analysis of four microRNAs using quantitative PCR.

PubMed

Sauer, Eva; Reinke, Ann-Kathrin; Courts, Cornelius

2016-05-01

Applying molecular genetic approaches for the identification of forensically relevant body fluids, which often yield crucial information for the reconstruction of a potential crime, is a current topic of forensic research. Due to their body fluid specific expression patterns and stability against degradation, microRNAs (miRNA) emerged as a promising molecular species, with a range of candidate markers published. The analysis of miRNA via quantitative Real-Time PCR, however, should be based on a relevant strategy of normalization of non-biological variances to deliver reliable and biologically meaningful results. The herein presented work is the as yet most comprehensive study of forensic body fluid identification via miRNA expression analysis based on a thoroughly validated qPCR procedure and unbiased statistical decision making to identify single source samples. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Testing the Two-Layer Model for Correcting Clear Sky Reflectance near Clouds

NASA Technical Reports Server (NTRS)

Wen, Guoyong; Marshak, Alexander; Evans, Frank; Varnai, Tamas; Levy, Rob

2015-01-01

A two-layer model (2LM) was developed in our earlier studies to estimate the clear sky reflectance enhancement due to cloud-molecular radiative interaction at MODIS at 0.47 micrometers. Recently, we extended the model to include cloud-surface and cloud-aerosol radiative interactions. We use the LES/SHDOM simulated 3D true radiation fields to test the 2LM for reflectance enhancement at 0.47 micrometers. We find: The simple model captures the viewing angle dependence of the reflectance enhancement near cloud, suggesting the physics of this model is correct; the cloud-molecular interaction alone accounts for 70 percent of the enhancement; the cloud-surface interaction accounts for 16 percent of the enhancement; the cloud-aerosol interaction accounts for an additional 13 percent of the enhancement. We conclude that the 2LM is simple to apply and unbiased.

Diverse types of genetic variation converge on functional gene networks involved in schizophrenia.

PubMed

Gilman, Sarah R; Chang, Jonathan; Xu, Bin; Bawa, Tejdeep S; Gogos, Joseph A; Karayiorgou, Maria; Vitkup, Dennis

2012-12-01

Despite the successful identification of several relevant genomic loci, the underlying molecular mechanisms of schizophrenia remain largely unclear. We developed a computational approach (NETBAG+) that allows an integrated analysis of diverse disease-related genetic data using a unified statistical framework. The application of this approach to schizophrenia-associated genetic variations, obtained using unbiased whole-genome methods, allowed us to identify several cohesive gene networks related to axon guidance, neuronal cell mobility, synaptic function and chromosomal remodeling. The genes forming the networks are highly expressed in the brain, with higher brain expression during prenatal development. The identified networks are functionally related to genes previously implicated in schizophrenia, autism and intellectual disability. A comparative analysis of copy number variants associated with autism and schizophrenia suggests that although the molecular networks implicated in these distinct disorders may be related, the mutations associated with each disease are likely to lead, at least on average, to different functional consequences.

Boundary Conditions for the Paleoenvironment: Chemical and Physical Processes in the Pre-Solar Nebula

NASA Technical Reports Server (NTRS)

Irvine, William M.; Schloerb, F. Peter

1997-01-01

The basic theme of this program is the study of molecular complexity and evolution in interstellar clouds and in primitive solar system objects. Research has included the detection and study of a number of new interstellar molecules and investigation of reaction pathways for astrochemistry from a comparison of theory and observed molecular abundances. The latter includes studies of cold, dark clouds in which ion-molecule chemistry should predominate, searches for the effects of interchange of material between the gas and solid phases in interstellar clouds, unbiased spectral surveys of particular sources, and systematic investigation of the interlinked chemistry and physics of dense interstellar clouds. In addition, the study of comets has allowed a comparison between the chemistry of such minimally thermally processed objects and that of interstellar clouds, shedding light on the evolution of the biogenic elements during the process of solar system formation.

System-Wide Quantitative Proteomics of the Metabolic Syndrome in Mice: Genotypic and Dietary Effects.

PubMed

Terfve, Camille; Sabidó, Eduard; Wu, Yibo; Gonçalves, Emanuel; Choi, Meena; Vaga, Stefania; Vitek, Olga; Saez-Rodriguez, Julio; Aebersold, Ruedi

2017-02-03

Advances in mass spectrometry have made the quantitative measurement of proteins across multiple samples a reality, allowing for the study of complex biological systems such as the metabolic syndrome. Although the deregulation of lipid metabolism and increased hepatic storage of triacylglycerides are known to play a part in the onset of the metabolic syndrome, its molecular basis and dependency on dietary and genotypic factors are poorly characterized. Here, we used an experimental design with two different mouse strains and dietary and metabolic perturbations to generate a compendium of quantitative proteome data using three mass spectrometric techniques. The data reproduce known properties of the metabolic system and indicate differential molecular adaptation of the two mouse strains to perturbations, contributing to a better understanding of the metabolic syndrome. We show that high-quality, high-throughput proteomic data sets provide an unbiased broad overview of the behavior of complex systems after perturbation.

Using Imaging Methods to Interrogate Radiation-Induced Cell Signaling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shankaran, Harish; Weber, Thomas J.; Freiin von Neubeck, Claere H.

2012-04-01

There is increasing emphasis on the use of systems biology approaches to define radiation induced responses in cells and tissues. Such approaches frequently rely on global screening using various high throughput 'omics' platforms. Although these methods are ideal for obtaining an unbiased overview of cellular responses, they often cannot reflect the inherent heterogeneity of the system or provide detailed spatial information. Additionally, performing such studies with multiple sampling time points can be prohibitively expensive. Imaging provides a complementary method with high spatial and temporal resolution capable of following the dynamics of signaling processes. In this review, we utilize specific examplesmore » to illustrate how imaging approaches have furthered our understanding of radiation induced cellular signaling. Particular emphasis is placed on protein co-localization, and oscillatory and transient signaling dynamics.« less

Atomic resolution mechanism of ligand binding to a solvent inaccessible cavity in T4 lysozyme

PubMed Central

Ahalawat, Navjeet; Pandit, Subhendu; Kay, Lewis E.

2018-01-01

Ligand binding sites in proteins are often localized to deeply buried cavities, inaccessible to bulk solvent. Yet, in many cases binding of cognate ligands occurs rapidly. An intriguing system is presented by the L99A cavity mutant of T4 Lysozyme (T4L L99A) that rapidly binds benzene (~106 M-1s-1). Although the protein has long served as a model system for protein thermodynamics and crystal structures of both free and benzene-bound T4L L99A are available, the kinetic pathways by which benzene reaches its solvent-inaccessible binding cavity remain elusive. The current work, using extensive molecular dynamics simulation, achieves this by capturing the complete process of spontaneous recognition of benzene by T4L L99A at atomistic resolution. A series of multi-microsecond unbiased molecular dynamics simulation trajectories unequivocally reveal how benzene, starting in bulk solvent, diffuses to the protein and spontaneously reaches the solvent inaccessible cavity of T4L L99A. The simulated and high-resolution X-ray derived bound structures are in excellent agreement. A robust four-state Markov model, developed using cumulative 60 μs trajectories, identifies and quantifies multiple ligand binding pathways with low activation barriers. Interestingly, none of these identified binding pathways required large conformational changes for ligand access to the buried cavity. Rather, these involve transient but crucial opening of a channel to the cavity via subtle displacements in the positions of key helices (helix4/helix6, helix7/helix9) leading to rapid binding. Free energy simulations further elucidate that these channel-opening events would have been unfavorable in wild type T4L. Taken together and via integrating with results from experiments, these simulations provide unprecedented mechanistic insights into the complete ligand recognition process in a buried cavity. By illustrating the power of subtle helix movements in opening up multiple pathways for ligand access, this work offers an alternate view of ligand recognition in a solvent-inaccessible cavity, contrary to the common perception of a single dominant pathway for ligand binding. PMID:29775455

RNA-seq based transcriptomic map reveals new insights into mouse salivary gland development and maturation.

PubMed

Gluck, Christian; Min, Sangwon; Oyelakin, Akinsola; Smalley, Kirsten; Sinha, Satrajit; Romano, Rose-Anne

2016-11-16

Mouse models have served a valuable role in deciphering various facets of Salivary Gland (SG) biology, from normal developmental programs to diseased states. To facilitate such studies, gene expression profiling maps have been generated for various stages of SG organogenesis. However these prior studies fall short of capturing the transcriptional complexity due to the limited scope of gene-centric microarray-based technology. Compared to microarray, RNA-sequencing (RNA-seq) offers unbiased detection of novel transcripts, broader dynamic range and high specificity and sensitivity for detection of genes, transcripts, and differential gene expression. Although RNA-seq data, particularly under the auspices of the ENCODE project, have covered a large number of biological specimens, studies on the SG have been lacking. To better appreciate the wide spectrum of gene expression profiles, we isolated RNA from mouse submandibular salivary glands at different embryonic and adult stages. In parallel, we processed RNA-seq data for 24 organs and tissues obtained from the mouse ENCODE consortium and calculated the average gene expression values. To identify molecular players and pathways likely to be relevant for SG biology, we performed functional gene enrichment analysis, network construction and hierarchal clustering of the RNA-seq datasets obtained from different stages of SG development and maturation, and other mouse organs and tissues. Our bioinformatics-based data analysis not only reaffirmed known modulators of SG morphogenesis but revealed novel transcription factors and signaling pathways unique to mouse SG biology and function. Finally we demonstrated that the unique SG gene signature obtained from our mouse studies is also well conserved and can demarcate features of the human SG transcriptome that is different from other tissues. Our RNA-seq based Atlas has revealed a high-resolution cartographic view of the dynamic transcriptomic landscape of the mouse SG at various stages. These RNA-seq datasets will complement pre-existing microarray based datasets, including the Salivary Gland Molecular Anatomy Project by offering a broader systems-biology based perspective rather than the classical gene-centric view. Ultimately such resources will be valuable in providing a useful toolkit to better understand how the diverse cell population of the SG are organized and controlled during development and differentiation.

Aspects of mutually unbiased bases in odd-prime-power dimensions

NASA Astrophysics Data System (ADS)

Chaturvedi, S.

2002-04-01

We rephrase the Wootters-Fields construction [W. K. Wootters and B. C. Fields, Ann. Phys. 191, 363 (1989)] of a full set of mutually unbiased bases in a complex vector space of dimensions N=pr, where p is an odd prime, in terms of the character vectors of the cyclic group G of order p. This form may be useful in explicitly writing down mutually unbiased bases for N=pr.

Fandom Biases Retrospective Judgments Not Perception.

PubMed

Huff, Markus; Papenmeier, Frank; Maurer, Annika E; Meitz, Tino G K; Garsoffky, Bärbel; Schwan, Stephan

2017-02-24

Attitudes and motivations have been shown to affect the processing of visual input, indicating that observers may see a given situation each literally in a different way. Yet, in real-life, processing information in an unbiased manner is considered to be of high adaptive value. Attitudinal and motivational effects were found for attention, characterization, categorization, and memory. On the other hand, for dynamic real-life events, visual processing has been found to be highly synchronous among viewers. Thus, while in a seminal study fandom as a particularly strong case of attitudes did bias judgments of a sports event, it left the question open whether attitudes do bias prior processing stages. Here, we investigated influences of fandom during the live TV broadcasting of the 2013 UEFA-Champions-League Final regarding attention, event segmentation, immediate and delayed cued recall, as well as affect, memory confidence, and retrospective judgments. Even though we replicated biased retrospective judgments, we found that eye-movements, event segmentation, and cued recall were largely similar across both groups of fans. Our findings demonstrate that, while highly involving sports events are interpreted in a fan dependent way, at initial stages they are processed in an unbiased manner.

Fandom Biases Retrospective Judgments Not Perception

PubMed Central

Huff, Markus; Papenmeier, Frank; Maurer, Annika E.; Meitz, Tino G. K.; Garsoffky, Bärbel; Schwan, Stephan

2017-01-01

Attitudes and motivations have been shown to affect the processing of visual input, indicating that observers may see a given situation each literally in a different way. Yet, in real-life, processing information in an unbiased manner is considered to be of high adaptive value. Attitudinal and motivational effects were found for attention, characterization, categorization, and memory. On the other hand, for dynamic real-life events, visual processing has been found to be highly synchronous among viewers. Thus, while in a seminal study fandom as a particularly strong case of attitudes did bias judgments of a sports event, it left the question open whether attitudes do bias prior processing stages. Here, we investigated influences of fandom during the live TV broadcasting of the 2013 UEFA-Champions-League Final regarding attention, event segmentation, immediate and delayed cued recall, as well as affect, memory confidence, and retrospective judgments. Even though we replicated biased retrospective judgments, we found that eye-movements, event segmentation, and cued recall were largely similar across both groups of fans. Our findings demonstrate that, while highly involving sports events are interpreted in a fan dependent way, at initial stages they are processed in an unbiased manner. PMID:28233877

Evolution of learning strategies in temporally and spatially variable environments: A review of theory

PubMed Central

Aoki, Kenichi; Feldman, Marcus W.

2013-01-01

The theoretical literature from 1985 to the present on the evolution of learning strategies in variable environments is reviewed, with the focus on deterministic dynamical models that are amenable to local stability analysis, and on deterministic models yielding evolutionarily stable strategies. Individual learning, unbiased and biased social learning, mixed learning, and learning schedules are considered. A rapidly changing environment or frequent migration in a spatially heterogeneous environment favors individual learning over unbiased social learning. However, results are not so straightforward in the context of learning schedules or when biases in social learning are introduced. The three major methods of modeling temporal environmental change – coevolutionary, two-timescale, and information decay – are compared and shown to sometimes yield contradictory results. The so-called Rogers’ paradox is inherent in the two-timescale method as originally applied to the evolution of pure strategies, but is often eliminated when the other methods are used. Moreover, Rogers’ paradox is not observed for the mixed learning strategies and learning schedules that we review. We believe that further theoretical work is necessary on learning schedules and biased social learning, based on models that are logically consistent and empirically pertinent. PMID:24211681

Evolution of learning strategies in temporally and spatially variable environments: a review of theory.

PubMed

Aoki, Kenichi; Feldman, Marcus W

2014-02-01

The theoretical literature from 1985 to the present on the evolution of learning strategies in variable environments is reviewed, with the focus on deterministic dynamical models that are amenable to local stability analysis, and on deterministic models yielding evolutionarily stable strategies. Individual learning, unbiased and biased social learning, mixed learning, and learning schedules are considered. A rapidly changing environment or frequent migration in a spatially heterogeneous environment favors individual learning over unbiased social learning. However, results are not so straightforward in the context of learning schedules or when biases in social learning are introduced. The three major methods of modeling temporal environmental change--coevolutionary, two-timescale, and information decay--are compared and shown to sometimes yield contradictory results. The so-called Rogers' paradox is inherent in the two-timescale method as originally applied to the evolution of pure strategies, but is often eliminated when the other methods are used. Moreover, Rogers' paradox is not observed for the mixed learning strategies and learning schedules that we review. We believe that further theoretical work is necessary on learning schedules and biased social learning, based on models that are logically consistent and empirically pertinent. Copyright © 2013 Elsevier Inc. All rights reserved.

Unusual Structure and Magnetism in MnO Nanoclusters

NASA Astrophysics Data System (ADS)

Ganguly, Shreemoyee; Kabir, Mukul; Sanyal, Biplab; Mookerjee, Abhijit

2011-03-01

We report an unusual structural and magnetic evolution in stoichiometric MnO nanoclusters by an extensive and unbiased search through the potential energy surface within density functional theory. The (MnO)n nanoclusters adopt two-dimensional structures in size ranges in which Mnn nanoclusters are three-dimensional and regardless of the size of the nanocluster, the magnetic coupling is found to be antiferromagnetic, and is strikingly different from Mn-based molecular magnets. Both of these features are explained through the inherent electronic structures of the nanoclusters. We gratefully acknowledge financial support from Swedish Research Links program funded by VR/SIDA and Carl Tryggers Foundation, Sweden.

Ligand-directed profiling of organelles with internalizing phage libraries

PubMed Central

Dobroff, Andrey S.; Rangel, Roberto; Guzman-Roja, Liliana; Salmeron, Carolina C.; Gelovani, Juri G.; Sidman, Richard L.; Bologa, Cristian G.; Oprea, Tudor I.; Brinker, C. Jeffrey; Pasqualini, Renata; Arap, Wadih

2015-01-01

Phage display is a resourceful tool to, in an unbiased manner, discover and characterize functional protein-protein interactions, to create vaccines, and to engineer peptides, antibodies, and other proteins as targeted diagnostic and/or therapeutic agents. Recently, our group has developed a new class of internalizing phage (iPhage) for ligand-directed targeting of organelles and/or to identify molecular pathways within live cells. This unique technology is suitable for applications ranging from fundamental cell biology to drug development. Here we describe the method for generating and screening the iPhage display system, and explain how to select and validate candidate internalizing homing peptide. PMID:25640897

Structural phenotyping of stem cell-derived cardiomyocytes.

PubMed

Pasqualini, Francesco Silvio; Sheehy, Sean Paul; Agarwal, Ashutosh; Aratyn-Schaus, Yvonne; Parker, Kevin Kit

2015-03-10

Structural phenotyping based on classical image feature detection has been adopted to elucidate the molecular mechanisms behind genetically or pharmacologically induced changes in cell morphology. Here, we developed a set of 11 metrics to capture the increasing sarcomere organization that occurs intracellularly during striated muscle cell development. To test our metrics, we analyzed the localization of the contractile protein α-actinin in a variety of primary and stem-cell derived cardiomyocytes. Further, we combined these metrics with data mining algorithms to unbiasedly score the phenotypic maturity of human-induced pluripotent stem cell-derived cardiomyocytes. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Machine learning for autonomous crystal structure identification.

PubMed

Reinhart, Wesley F; Long, Andrew W; Howard, Michael P; Ferguson, Andrew L; Panagiotopoulos, Athanassios Z

2017-07-21

We present a machine learning technique to discover and distinguish relevant ordered structures from molecular simulation snapshots or particle tracking data. Unlike other popular methods for structural identification, our technique requires no a priori description of the target structures. Instead, we use nonlinear manifold learning to infer structural relationships between particles according to the topology of their local environment. This graph-based approach yields unbiased structural information which allows us to quantify the crystalline character of particles near defects, grain boundaries, and interfaces. We demonstrate the method by classifying particles in a simulation of colloidal crystallization, and show that our method identifies structural features that are missed by standard techniques.

Nobeyama 45 m Cygnus-X CO Survey. I. Photodissociation of Molecules Revealed by the Unbiased Large-scale CN and C18O Maps

NASA Astrophysics Data System (ADS)

Yamagishi, M.; Nishimura, A.; Fujita, S.; Takekoshi, T.; Matsuo, M.; Minamidani, T.; Taniguchi, K.; Tokuda, K.; Shimajiri, Y.

2018-03-01

We present an unbiased large-scale (9 deg2) CN (N = 1–0) and C18O (J = 1–0) survey of Cygnus-X conducted with the Nobeyama 45 m Cygnus-X CO survey. CN and C18O are detected in various objects toward the Cygnus-X North and South (e.g., DR17, DR18, DR21, DR22, DR23, and W75N). We find that CN/C18O integrated intensity ratios are systematically different from region to region, and are especially enhanced in DR17 and DR18, which are irradiated by the nearby OB stars. This result suggests that CN/C18O ratios are enhanced via photodissociation reactions. We investigate the relation between the CN/C18O ratio and strength of the UV radiation field. As a result, we find that CN/C18O ratios correlate with the far-UV intensities, G 0. We also find that CN/C18O ratios decrease inside molecular clouds, where the interstellar UV radiation is reduced due to the interstellar dust extinction. We conclude that the CN/C18O ratio is controlled by the UV radiation, and is a good probe of photon-dominated regions.

Understanding the Differential Selectivity of Arrestins toward the Phosphorylation State of the Receptor.

PubMed

Sensoy, Ozge; Moreira, Irina S; Morra, Giulia

2016-09-21

Proteins in the arrestin family exhibit a conserved structural fold that nevertheless allows for significant differences in their selectivity for G-protein coupled receptors (GPCRs) and their phosphorylation states. To reveal the mechanism of activation that prepares arrestin for selective interaction with GPCRs, and to understand the basis for these differences, we used unbiased molecular dynamics simulations to compare the structural and dynamic properties of wild type Arr1 (Arr1-WT), Arr3 (Arr3-WT), and a constitutively active Arr1 mutant, Arr1-R175E, characterized by a perturbation of the phosphate recognition region called "polar core". We find that in our simulations the mutant evolves toward a conformation that resembles the known preactivated structures of an Arr1 splice-variant, and the structurally similar phosphopeptide-bound Arr2-WT, while this does not happen for Arr1-WT. Hence, we propose an activation allosteric mechanism connecting the perturbation of the polar core to a global conformational change, including the relative reorientation of N- and C-domains, and the emergence of electrostatic properties of putative binding surfaces. The underlying local structural changes are interpreted as markers of the evolution of an arrestin structure toward an active-like conformation. Similar activation related changes occur in Arr3-WT in the absence of any perturbation of the polar core, suggesting that this system could spontaneously visit preactivated states in solution. This hypothesis is proposed to explain the lower selectivity of Arr3 toward nonphosphorylated receptors. Moreover, by elucidating the allosteric mechanism underlying activation, we identify functionally critical regions on arrestin structure that can be targeted with drugs or chemical tools for functional modulation.

Mechanistic Insights into the Allosteric Modulation of Opioid Receptors by Sodium Ions

PubMed Central

2015-01-01

The idea of sodium ions altering G-protein-coupled receptor (GPCR) ligand binding and signaling was first suggested for opioid receptors (ORs) in the 1970s and subsequently extended to other GPCRs. Recently published ultra-high-resolution crystal structures of GPCRs, including that of the δ-OR subtype, have started to shed light on the mechanism underlying sodium control in GPCR signaling by revealing details of the sodium binding site. Whether sodium accesses different receptor subtypes from the extra- or intracellular sides, following similar or different pathways, is still an open question. Earlier experiments in brain homogenates suggested a differential sodium regulation of ligand binding to the three major OR subtypes, in spite of their high degree of sequence similarity. Intrigued by this possibility, we explored the dynamic nature of sodium binding to δ-OR, μ-OR, and κ-OR by means of microsecond-scale, all-atom molecular dynamics (MD) simulations. Rapid sodium permeation was observed exclusively from the extracellular milieu, and following similar binding pathways in all three ligand-free OR systems, notwithstanding extra densities of sodium observed near nonconserved residues of κ-OR and δ-OR, but not in μ-OR. We speculate that these differences may be responsible for the differential increase in antagonist binding affinity of μ-OR by sodium resulting from specific ligand binding experiments in transfected cells. On the other hand, sodium reduced the level of binding of subtype-specific agonists to all OR subtypes. Additional biased and unbiased MD simulations were conducted using the δ-OR ultra-high-resolution crystal structure as a model system to provide a mechanistic explanation for this experimental observation. PMID:25073009

Mechanistic insights into the allosteric modulation of opioid receptors by sodium ions.

PubMed

Shang, Yi; LeRouzic, Valerie; Schneider, Sebastian; Bisignano, Paola; Pasternak, Gavril W; Filizola, Marta

2014-08-12

The idea of sodium ions altering G-protein-coupled receptor (GPCR) ligand binding and signaling was first suggested for opioid receptors (ORs) in the 1970s and subsequently extended to other GPCRs. Recently published ultra-high-resolution crystal structures of GPCRs, including that of the δ-OR subtype, have started to shed light on the mechanism underlying sodium control in GPCR signaling by revealing details of the sodium binding site. Whether sodium accesses different receptor subtypes from the extra- or intracellular sides, following similar or different pathways, is still an open question. Earlier experiments in brain homogenates suggested a differential sodium regulation of ligand binding to the three major OR subtypes, in spite of their high degree of sequence similarity. Intrigued by this possibility, we explored the dynamic nature of sodium binding to δ-OR, μ-OR, and κ-OR by means of microsecond-scale, all-atom molecular dynamics (MD) simulations. Rapid sodium permeation was observed exclusively from the extracellular milieu, and following similar binding pathways in all three ligand-free OR systems, notwithstanding extra densities of sodium observed near nonconserved residues of κ-OR and δ-OR, but not in μ-OR. We speculate that these differences may be responsible for the differential increase in antagonist binding affinity of μ-OR by sodium resulting from specific ligand binding experiments in transfected cells. On the other hand, sodium reduced the level of binding of subtype-specific agonists to all OR subtypes. Additional biased and unbiased MD simulations were conducted using the δ-OR ultra-high-resolution crystal structure as a model system to provide a mechanistic explanation for this experimental observation.

Structure and transport properties of nanostructured materials.

PubMed

Sonwane, C G; Li, Q

2005-03-31

In the present manuscript, we have presented the simulation of nanoporous aluminum oxide using a molecular-dynamics approach with recently developed dynamic charge transfer potential using serial/parallel programming techniques (Streitz and Mintmire Phys. Rev. B 1994, 50, 11996). The structures resembling recently invented ordered nanoporous crystalline material, MCM-41/SBA-15 (Kresge et al. Nature 1992, 359, 710), and inverted porous solids (hollow nanospheres) with up to 10 000 atoms were fabricated and studied in the present work. These materials have been used for separation of gases and catalysis. On several occasions including the design of the reactor, the knowledge of surface diffusion is necessary. In the present work, a new method for estimating surface transport of gases based on a hybrid Monte Carlo method with unbiased random walk of tracer atom on the pore surface has been introduced. The nonoverlapping packings used in the present work were fabricated using an algorithm of very slowly settling rigid spheres from a dilute suspension into a randomly packed bed. The algorithm was modified to obtain unimodal, homogeneous Gaussian and segregated bimodal porous solids. The porosity of these solids was varied by densification using an arbitrary function or by coarsening from a highly densified pellet. The surface tortuosity for the densified solids indicated an inverted bell shape curve consistent with the fact that at very high porosities there is a reduction in the connectivity while at low porosities the pores become inaccessible or dead-end. The first passage time distribution approach was found to be more efficient in terms of computation time (fewer tracer atoms needed for the linearity of Einstein's plot). Results by hybrid discrete-continuum simulations were close to the discrete simulations for a boundary layer thickness of 5lambda.

FF12MC: A revised AMBER forcefield and new protein simulation protocol

PubMed Central

2016-01-01

ABSTRACT Specialized to simulate proteins in molecular dynamics (MD) simulations with explicit solvation, FF12MC is a combination of a new protein simulation protocol employing uniformly reduced atomic masses by tenfold and a revised AMBER forcefield FF99 with (i) shortened C—H bonds, (ii) removal of torsions involving a nonperipheral sp3 atom, and (iii) reduced 1–4 interaction scaling factors of torsions ϕ and ψ. This article reports that in multiple, distinct, independent, unrestricted, unbiased, isobaric–isothermal, and classical MD simulations FF12MC can (i) simulate the experimentally observed flipping between left‐ and right‐handed configurations for C14–C38 of BPTI in solution, (ii) autonomously fold chignolin, CLN025, and Trp‐cage with folding times that agree with the experimental values, (iii) simulate subsequent unfolding and refolding of these miniproteins, and (iv) achieve a robust Z score of 1.33 for refining protein models TMR01, TMR04, and TMR07. By comparison, the latest general‐purpose AMBER forcefield FF14SB locks the C14–C38 bond to the right‐handed configuration in solution under the same protein simulation conditions. Statistical survival analysis shows that FF12MC folds chignolin and CLN025 in isobaric–isothermal MD simulations 2–4 times faster than FF14SB under the same protein simulation conditions. These results suggest that FF12MC may be used for protein simulations to study kinetics and thermodynamics of miniprotein folding as well as protein structure and dynamics. Proteins 2016; 84:1490–1516. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc. PMID:27348292

Can Sgr A* flares reveal the molecular gas density PDF?

NASA Astrophysics Data System (ADS)

Churazov, E.; Khabibullin, I.; Sunyaev, R.; Ponti, G.

2017-11-01

Illumination of dense gas in the Central Molecular Zone by powerful X-ray flares from Sgr A* leads to prominent structures in the reflected emission that can be observed long after the end of the flare. By studying this emission, we learn about past activity of the supermassive black hole in our Galactic Center and, at the same time, we obtain unique information on the structure of molecular clouds that is essentially impossible to get by other means. Here we discuss how X-ray data can improve our knowledge of both sides of the problem. Existing data already provide (I) an estimate of the flare age, (II) a model-independent lower limit on the luminosity of Sgr A* during the flare and (III) an estimate of the total emitted energy during Sgr A* flare. On the molecular clouds side, the data clearly show a voids-and-walls structure of the clouds and can provide an almost unbiased probe of the mass/density distribution of the molecular gas with the hydrogen column densities lower than few 1023 cm-2. For instance, the probability distribution function of the gas density PDF(ρ) can be measured this way. Future high energy resolution X-ray missions will provide the information on the gas velocities, allowing, for example, a reconstruction of the velocity field structure functions and cross-matching the X-ray and molecular data based on positions and velocities.

Comparative modeling and benchmarking data sets for human histone deacetylases and sirtuin families.

PubMed

Xia, Jie; Tilahun, Ermias Lemma; Kebede, Eyob Hailu; Reid, Terry-Elinor; Zhang, Liangren; Wang, Xiang Simon

2015-02-23

Histone deacetylases (HDACs) are an important class of drug targets for the treatment of cancers, neurodegenerative diseases, and other types of diseases. Virtual screening (VS) has become fairly effective approaches for drug discovery of novel and highly selective histone deacetylase inhibitors (HDACIs). To facilitate the process, we constructed maximal unbiased benchmarking data sets for HDACs (MUBD-HDACs) using our recently published methods that were originally developed for building unbiased benchmarking sets for ligand-based virtual screening (LBVS). The MUBD-HDACs cover all four classes including Class III (Sirtuins family) and 14 HDAC isoforms, composed of 631 inhibitors and 24609 unbiased decoys. Its ligand sets have been validated extensively as chemically diverse, while the decoy sets were shown to be property-matching with ligands and maximal unbiased in terms of "artificial enrichment" and "analogue bias". We also conducted comparative studies with DUD-E and DEKOIS 2.0 sets against HDAC2 and HDAC8 targets and demonstrate that our MUBD-HDACs are unique in that they can be applied unbiasedly to both LBVS and SBVS approaches. In addition, we defined a novel metric, i.e. NLBScore, to detect the "2D bias" and "LBVS favorable" effect within the benchmarking sets. In summary, MUBD-HDACs are the only comprehensive and maximal-unbiased benchmark data sets for HDACs (including Sirtuins) that are available so far. MUBD-HDACs are freely available at http://www.xswlab.org/ .

Filling the gap: adding super-resolution to array tomography for correlated ultrastructural and molecular identification of electrical synapses at the C. elegans connectome.

PubMed

Markert, Sebastian Matthias; Britz, Sebastian; Proppert, Sven; Lang, Marietta; Witvliet, Daniel; Mulcahy, Ben; Sauer, Markus; Zhen, Mei; Bessereau, Jean-Louis; Stigloher, Christian

2016-10-01

Correlating molecular labeling at the ultrastructural level with high confidence remains challenging. Array tomography (AT) allows for a combination of fluorescence and electron microscopy (EM) to visualize subcellular protein localization on serial EM sections. Here, we describe an application for AT that combines near-native tissue preservation via high-pressure freezing and freeze substitution with super-resolution light microscopy and high-resolution scanning electron microscopy (SEM) analysis on the same section. We established protocols that combine SEM with structured illumination microscopy (SIM) and direct stochastic optical reconstruction microscopy (dSTORM). We devised a method for easy, precise, and unbiased correlation of EM images and super-resolution imaging data using endogenous cellular landmarks and freely available image processing software. We demonstrate that these methods allow us to identify and label gap junctions in Caenorhabditis elegans with precision and confidence, and imaging of even smaller structures is feasible. With the emergence of connectomics, these methods will allow us to fill in the gap-acquiring the correlated ultrastructural and molecular identity of electrical synapses.

BiP and Multiple DNAJ Molecular Chaperones in the Endoplasmic Reticulum Are Required for Efficient Simian Virus 40 Infection

PubMed Central

Goodwin, Edward C.; Lipovsky, Alex; Inoue, Takamasa; Magaldi, Thomas G.; Edwards, Anne P. B.; Van Goor, Kristin E. Y.; Paton, Adrienne W.; Paton, James C.; Atwood, Walter J.; Tsai, Billy; DiMaio, Daniel

2011-01-01

ABSTRACT Simian virus 40 (SV40) is a nonenveloped DNA virus that traffics through the endoplasmic reticulum (ER) en route to the nucleus, but the mechanisms of capsid disassembly and ER exit are poorly understood. We conducted an unbiased RNA interference screen to identify cellular genes required for SV40 infection. SV40 infection was specifically inhibited by up to 50-fold by knockdown of four different DNAJ molecular cochaperones or by inhibition of BiP, the Hsp70 partner of DNAJB11. These proteins were not required for the initiation of capsid disassembly, but knockdown markedly inhibited SV40 exit from the ER. In addition, BiP formed a complex with SV40 capsids in the ER in a DNAJB11-dependent fashion. These experiments identify five new cellular proteins required for SV40 infection and suggest that the binding of BiP to the capsid is required for ER exit. Further studies of these proteins will provide insight into the molecular mechanisms of polyomavirus infection and ER function. PMID:21673190

Hierarchical thinking in network biology: the unbiased modularization of biochemical networks.

PubMed

Papin, Jason A; Reed, Jennifer L; Palsson, Bernhard O

2004-12-01

As reconstructed biochemical reaction networks continue to grow in size and scope, there is a growing need to describe the functional modules within them. Such modules facilitate the study of biological processes by deconstructing complex biological networks into conceptually simple entities. The definition of network modules is often based on intuitive reasoning. As an alternative, methods are being developed for defining biochemical network modules in an unbiased fashion. These unbiased network modules are mathematically derived from the structure of the whole network under consideration.

Comprehensive analysis of gene expression patterns in Friedreich's ataxia fibroblasts by RNA sequencing reveals altered levels of protein synthesis factors and solute carriers

PubMed Central

Li, Yanjie; Lu, Yue; Lin, Kevin; Hauser, Lauren A.; Lynch, David R.

2017-01-01

ABSTRACT Friedreich's ataxia (FRDA) is an autosomal recessive neurodegenerative disease usually caused by large homozygous expansions of GAA repeat sequences in intron 1 of the frataxin (FXN) gene. FRDA patients homozygous for GAA expansions have low FXN mRNA and protein levels when compared with heterozygous carriers or healthy controls. Frataxin is a mitochondrial protein involved in iron–sulfur cluster synthesis, and many FRDA phenotypes result from deficiencies in cellular metabolism due to lowered expression of FXN. Presently, there is no effective treatment for FRDA, and biomarkers to measure therapeutic trial outcomes and/or to gauge disease progression are lacking. Peripheral tissues, including blood cells, buccal cells and skin fibroblasts, can readily be isolated from FRDA patients and used to define molecular hallmarks of disease pathogenesis. For instance, FXN mRNA and protein levels as well as FXN GAA-repeat tract lengths are routinely determined using all of these cell types. However, because these tissues are not directly involved in disease pathogenesis, their relevance as models of the molecular aspects of the disease is yet to be decided. Herein, we conducted unbiased RNA sequencing to profile the transcriptomes of fibroblast cell lines derived from 18 FRDA patients and 17 unaffected control individuals. Bioinformatic analyses revealed significantly upregulated expression of genes encoding plasma membrane solute carrier proteins in FRDA fibroblasts. Conversely, the expression of genes encoding accessory factors and enzymes involved in cytoplasmic and mitochondrial protein synthesis was consistently decreased in FRDA fibroblasts. Finally, comparison of genes differentially expressed in FRDA fibroblasts to three previously published gene expression signatures defined for FRDA blood cells showed substantial overlap between the independent datasets, including correspondingly deficient expression of antioxidant defense genes. Together, these results indicate that gene expression profiling of cells derived from peripheral tissues can, in fact, consistently reveal novel molecular pathways of the disease. When performed on statistically meaningful sample group sizes, unbiased global profiling analyses utilizing peripheral tissues are critical for the discovery and validation of FRDA disease biomarkers. PMID:29125828

A multi-state coarse grained modeling approach for an intrinsically disordered peptide

NASA Astrophysics Data System (ADS)

Ramezanghorbani, Farhad; Dalgicdir, Cahit; Sayar, Mehmet

2017-09-01

Many proteins display a marginally stable tertiary structure, which can be altered via external stimuli. Since a majority of coarse grained (CG) models are aimed at structure prediction, their success for an intrinsically disordered peptide's conformational space with marginal stability and sensitivity to external stimuli cannot be taken for granted. In this study, by using the LKα 14 peptide as a test system, we demonstrate a bottom-up approach for constructing a multi-state CG model, which can capture the conformational behavior of this peptide in three distinct environments with a unique set of interaction parameters. LKα 14 is disordered in dilute solutions; however, it strictly adopts the α -helix conformation upon aggregation or when in contact with a hydrophobic/hydrophilic interface. Our bottom-up approach combines a generic base model, that is unbiased for any particular secondary structure, with nonbonded interactions which represent hydrogen bonds, electrostatics, and hydrophobic forces. We demonstrate that by using carefully designed all atom potential of mean force calculations from all three states of interest, one can get a balanced representation of the nonbonded interactions. Our CG model behaves intrinsically disordered in bulk water, folds into an α -helix in the presence of an interface or a neighboring peptide, and is stable as a tetrameric unit, successfully reproducing the all atom molecular dynamics simulations and experimental results.

The Taguchi methodology as a statistical tool for biotechnological applications: a critical appraisal.

PubMed

Rao, Ravella Sreenivas; Kumar, C Ganesh; Prakasham, R Shetty; Hobbs, Phil J

2008-04-01

Success in experiments and/or technology mainly depends on a properly designed process or product. The traditional method of process optimization involves the study of one variable at a time, which requires a number of combinations of experiments that are time, cost and labor intensive. The Taguchi method of design of experiments is a simple statistical tool involving a system of tabulated designs (arrays) that allows a maximum number of main effects to be estimated in an unbiased (orthogonal) fashion with a minimum number of experimental runs. It has been applied to predict the significant contribution of the design variable(s) and the optimum combination of each variable by conducting experiments on a real-time basis. The modeling that is performed essentially relates signal-to-noise ratio to the control variables in a 'main effect only' approach. This approach enables both multiple response and dynamic problems to be studied by handling noise factors. Taguchi principles and concepts have made extensive contributions to industry by bringing focused awareness to robustness, noise and quality. This methodology has been widely applied in many industrial sectors; however, its application in biological sciences has been limited. In the present review, the application and comparison of the Taguchi methodology has been emphasized with specific case studies in the field of biotechnology, particularly in diverse areas like fermentation, food processing, molecular biology, wastewater treatment and bioremediation.

Residues remote from the binding pocket control the antagonist selectivity towards the corticotropin-releasing factor receptor-1

PubMed Central

Sun, Xianqiang; Cheng, Jianxin; Wang, Xu; Tang, Yun; Ågren, Hans; Tu, Yaoquan

2015-01-01

The corticotropin releasing factors receptor-1 and receptor-2 (CRF1R and CRF2R) are therapeutic targets for treating neurological diseases. Antagonists targeting CRF1R have been developed for the potential treatment of anxiety disorders and alcohol addiction. It has been found that antagonists targeting CRF1R always show high selectivity, although CRF1R and CRF2R share a very high rate of sequence identity. This has inspired us to study the origin of the selectivity of the antagonists. We have therefore built a homology model for CRF2R and carried out unbiased molecular dynamics and well-tempered metadynamics simulations for systems with the antagonist CP-376395 in CRF1R or CRF2R to address this issue. We found that the side chain of Tyr6.63 forms a hydrogen bond with the residue remote from the binding pocket, which allows Tyr6.63 to adopt different conformations in the two receptors and results in the presence or absence of a bottleneck controlling the antagonist binding to or dissociation from the receptors. The rotameric switch of the side chain of Tyr3566.63 allows the breaking down of the bottleneck and is a perquisite for the dissociation of CP-376395 from CRF1R. PMID:25628267

Unfolding of the cold shock protein studied with biased molecular dynamics.

PubMed

Morra, Giulia; Hodoscek, Milan; Knapp, Ernst-Walter

2003-11-15

The cold shock protein from Bacillus caldolyticus is a small beta-barrel protein that folds in a two-state mechanism. For the native protein and for several mutants, a wealth of experimental data are available on stability and folding, so that it is an optimal system to study this process. We compare data from unfolding simulations (trajectories of 5 and up to 12 ns) obtained with a bias potential at room temperature and from unbiased thermal unfolding simulations with experimental data. The unfolding patterns derived from the trajectories starting from different native-like conformations and subject to different unfolding conditions agree. The transition state found in the simulations of unfolding is close to the native structure in agreement with experiment. Moreover, a lower value of the free energy barrier of unfolding was found for the mutant R3E than for the mutant E46A and the native protein, as indicated by experimental data. The first unfolding event involves the three-stranded beta-sheet whose decomposition corresponds to the transition state. In contrast to conclusions drawn from experiments, we found that the two-stranded beta-strand forms the most stable substructure, which decomposes very late in the unfolding process. However, assuming that this structure forms very early in the folding process, our findings would not contradict the experiments but require a different interpretation of them. Copyright 2003 Wiley-Liss, Inc.

How Oliceridine (TRV-130) Binds and Stabilizes a μ-Opioid Receptor Conformational State That Selectively Triggers G Protein Signaling Pathways.

PubMed

Schneider, Sebastian; Provasi, Davide; Filizola, Marta

2016-11-22

Substantial attention has recently been devoted to G protein-biased agonism of the μ-opioid receptor (MOR) as an ideal new mechanism for the design of analgesics devoid of serious side effects. However, designing opioids with appropriate efficacy and bias is challenging because it requires an understanding of the ligand binding process and of the allosteric modulation of the receptor. Here, we investigated these phenomena for TRV-130, a G protein-biased MOR small-molecule agonist that has been shown to exert analgesia with less respiratory depression and constipation than morphine and that is currently being evaluated in human clinical trials for acute pain management. Specifically, we carried out multimicrosecond, all-atom molecular dynamics (MD) simulations of the binding of this ligand to the activated MOR crystal structure. Analysis of >50 μs of these MD simulations provides insights into the energetically preferred binding pathway of TRV-130 and its stable pose at the orthosteric binding site of MOR. Information transfer from the TRV-130 binding pocket to the intracellular region of the receptor was also analyzed, and was compared to a similar analysis carried out on the receptor bound to the classical unbiased agonist morphine. Taken together, these studies lead to a series of testable hypotheses of ligand-receptor interactions that are expected to inform the structure-based design of improved opioid analgesics.

A multi-state coarse grained modeling approach for an intrinsically disordered peptide.

PubMed

Ramezanghorbani, Farhad; Dalgicdir, Cahit; Sayar, Mehmet

2017-09-07

Many proteins display a marginally stable tertiary structure, which can be altered via external stimuli. Since a majority of coarse grained (CG) models are aimed at structure prediction, their success for an intrinsically disordered peptide's conformational space with marginal stability and sensitivity to external stimuli cannot be taken for granted. In this study, by using the LKα14 peptide as a test system, we demonstrate a bottom-up approach for constructing a multi-state CG model, which can capture the conformational behavior of this peptide in three distinct environments with a unique set of interaction parameters. LKα14 is disordered in dilute solutions; however, it strictly adopts the α-helix conformation upon aggregation or when in contact with a hydrophobic/hydrophilic interface. Our bottom-up approach combines a generic base model, that is unbiased for any particular secondary structure, with nonbonded interactions which represent hydrogen bonds, electrostatics, and hydrophobic forces. We demonstrate that by using carefully designed all atom potential of mean force calculations from all three states of interest, one can get a balanced representation of the nonbonded interactions. Our CG model behaves intrinsically disordered in bulk water, folds into an α-helix in the presence of an interface or a neighboring peptide, and is stable as a tetrameric unit, successfully reproducing the all atom molecular dynamics simulations and experimental results.

Phosphoproteomic network analysis in the sea urchin Strongylocentrotus purpuratus reveals new candidates in egg activation.

PubMed

Guo, Hongbo; Garcia-Vedrenne, Ana Elisa; Isserlin, Ruth; Lugowski, Andrew; Morada, Anthony; Sun, Alex; Miao, Yishen; Kuzmanov, Uros; Wan, Cuihong; Ma, Hongyue; Foltz, Kathy; Emili, Andrew

2015-12-01

Fertilization triggers a dynamic symphony of molecular transformations induced by a rapid rise in intracellular calcium. Most prominent are surface alterations, metabolic activation, cytoskeletal reorganization, and cell-cycle reentry. While the activation process appears to be broadly evolutionarily conserved, and protein phosphorylation is known to play a key role, the signaling networks mediating the response to fertilization are not well described. To address this gap, we performed a time course phosphoproteomic analysis of egg activation in the sea urchin Strongylocentrotus purpuratus, a system that offers biochemical tractability coupled with exquisite synchronicity. By coupling large-scale phosphopeptide enrichment with unbiased quantitative MS, we identified striking changes in global phosphoprotein patterns at 2- and 5-min postfertilization as compared to unfertilized eggs. Overall, we mapped 8796 distinct phosphosite modifications on 2833 phosphoproteins, of which 15% were differentially regulated in early egg activation. Activated kinases were identified by phosphosite mapping, while enrichment analyses revealed conserved signaling cascades not previously associated with egg activation. This work represents the most comprehensive study of signaling associated with egg activation to date, suggesting novel mechanisms that can be experimentally tested and providing a valuable resource for the broader research community. All MS data have been deposited in the ProteomeXchange with identifier PXD002239 (http://proteomecentral.proteomexchange.org/dataset/PXD002239). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Toll-Like Receptor-9-Mediated Invasion in Breast Cancer

DTIC Science & Technology

2011-07-01

Molecular Dynamics Simulations. Theoretical structural models were obtained from molecular dynamics simulations using explicit solvation by...with AMBER by MARDIGRAS. The solution structure was then derived by coupling the resulting NMR distance restraints with a molecular dynamic ...Overlay of NMR restrained structure (red) with theoretical molecular dynamic simulated annealing structure (blue). Energetic stability of the 9-mer

Revisiting AFLP fingerprinting for an unbiased assessment of genetic structure and differentiation of taurine and zebu cattle

PubMed Central

2014-01-01

Background Descendants from the extinct aurochs (Bos primigenius), taurine (Bos taurus) and zebu cattle (Bos indicus) were domesticated 10,000 years ago in Southwestern and Southern Asia, respectively, and colonized the world undergoing complex events of admixture and selection. Molecular data, in particular genome-wide single nucleotide polymorphism (SNP) markers, can complement historic and archaeological records to elucidate these past events. However, SNP ascertainment in cattle has been optimized for taurine breeds, imposing limitations to the study of diversity in zebu cattle. As amplified fragment length polymorphism (AFLP) markers are discovered and genotyped as the samples are assayed, this type of marker is free of ascertainment bias. In order to obtain unbiased assessments of genetic differentiation and structure in taurine and zebu cattle, we analyzed a dataset of 135 AFLP markers in 1,593 samples from 13 zebu and 58 taurine breeds, representing nine continental areas. Results We found a geographical pattern of expected heterozygosity in European taurine breeds decreasing with the distance from the domestication centre, arguing against a large-scale introgression from European or African aurochs. Zebu cattle were found to be at least as diverse as taurine cattle. Western African zebu cattle were found to have diverged more from Indian zebu than South American zebu. Model-based clustering and ancestry informative markers analyses suggested that this is due to taurine introgression. Although a large part of South American zebu cattle also descend from taurine cows, we did not detect significant levels of taurine ancestry in these breeds, probably because of systematic backcrossing with zebu bulls. Furthermore, limited zebu introgression was found in Podolian taurine breeds in Italy. Conclusions The assessment of cattle diversity reported here contributes an unbiased global view to genetic differentiation and structure of taurine and zebu cattle populations, which is essential for an effective conservation of the bovine genetic resources. PMID:24739206

Comparative Modeling and Benchmarking Data Sets for Human Histone Deacetylases and Sirtuin Families

PubMed Central

Xia, Jie; Tilahun, Ermias Lemma; Kebede, Eyob Hailu; Reid, Terry-Elinor; Zhang, Liangren; Wang, Xiang Simon

2015-01-01

Histone Deacetylases (HDACs) are an important class of drug targets for the treatment of cancers, neurodegenerative diseases and other types of diseases. Virtual screening (VS) has become fairly effective approaches for drug discovery of novel and highly selective Histone Deacetylases Inhibitors (HDACIs). To facilitate the process, we constructed the Maximal Unbiased Benchmarking Data Sets for HDACs (MUBD-HDACs) using our recently published methods that were originally developed for building unbiased benchmarking sets for ligand-based virtual screening (LBVS). The MUBD-HDACs covers all 4 Classes including Class III (Sirtuins family) and 14 HDACs isoforms, composed of 631 inhibitors and 24,609 unbiased decoys. Its ligand sets have been validated extensively as chemically diverse, while the decoy sets were shown to be property-matching with ligands and maximal unbiased in terms of “artificial enrichment” and “analogue bias”. We also conducted comparative studies with DUD-E and DEKOIS 2.0 sets against HDAC2 and HDAC8 targets, and demonstrate that our MUBD-HDACs is unique in that it can be applied unbiasedly to both LBVS and SBVS approaches. In addition, we defined a novel metric, i.e. NLBScore, to detect the “2D bias” and “LBVS favorable” effect within the benchmarking sets. In summary, MUBD-HDACs is the only comprehensive and maximal-unbiased benchmark data sets for HDACs (including Sirtuins) that is available so far. MUBD-HDACs is freely available at http://www.xswlab.org/. PMID:25633490

An Unbiased Estimator of Gene Diversity with Improved Variance for Samples Containing Related and Inbred Individuals of any Ploidy

PubMed Central

Harris, Alexandre M.; DeGiorgio, Michael

2016-01-01

Gene diversity, or expected heterozygosity (H), is a common statistic for assessing genetic variation within populations. Estimation of this statistic decreases in accuracy and precision when individuals are related or inbred, due to increased dependence among allele copies in the sample. The original unbiased estimator of expected heterozygosity underestimates true population diversity in samples containing relatives, as it only accounts for sample size. More recently, a general unbiased estimator of expected heterozygosity was developed that explicitly accounts for related and inbred individuals in samples. Though unbiased, this estimator’s variance is greater than that of the original estimator. To address this issue, we introduce a general unbiased estimator of gene diversity for samples containing related or inbred individuals, which employs the best linear unbiased estimator of allele frequencies, rather than the commonly used sample proportion. We examine the properties of this estimator, H∼BLUE, relative to alternative estimators using simulations and theoretical predictions, and show that it predominantly has the smallest mean squared error relative to others. Further, we empirically assess the performance of H∼BLUE on a global human microsatellite dataset of 5795 individuals, from 267 populations, genotyped at 645 loci. Additionally, we show that the improved variance of H∼BLUE leads to improved estimates of the population differentiation statistic, FST, which employs measures of gene diversity within its calculation. Finally, we provide an R script, BestHet, to compute this estimator from genomic and pedigree data. PMID:28040781

Reaction wheel low-speed compensation using a dither signal

NASA Astrophysics Data System (ADS)

Stetson, John B., Jr.

1993-08-01

A method for improving low-speed reaction wheel performance on a three-axis controlled spacecraft is presented. The method combines a constant amplitude offset with an unbiased, oscillating dither to harmonically linearize rolling solid friction dynamics. The complete, nonlinear rolling solid friction dynamics using an analytic modification to the experimentally verified Dahl solid friction model were analyzed using the dual-input describing function method to assess the benefits of dither compensation. The modified analytic solid friction model was experimentally verified with a small dc servomotor actuated reaction wheel assembly. Using dither compensation abrupt static friction disturbances are eliminated and near linear behavior through zero rate can be achieved. Simulated vehicle response to a wheel rate reversal shows that when the dither and offset compensation is used, elastic modes are not significantly excited, and the uncompensated attitude error reduces by 34:1.

Unsupervised Discovery of Demixed, Low-Dimensional Neural Dynamics across Multiple Timescales through Tensor Component Analysis.

PubMed

Williams, Alex H; Kim, Tony Hyun; Wang, Forea; Vyas, Saurabh; Ryu, Stephen I; Shenoy, Krishna V; Schnitzer, Mark; Kolda, Tamara G; Ganguli, Surya

2018-06-27

Perceptions, thoughts, and actions unfold over millisecond timescales, while learned behaviors can require many days to mature. While recent experimental advances enable large-scale and long-term neural recordings with high temporal fidelity, it remains a formidable challenge to extract unbiased and interpretable descriptions of how rapid single-trial circuit dynamics change slowly over many trials to mediate learning. We demonstrate a simple tensor component analysis (TCA) can meet this challenge by extracting three interconnected, low-dimensional descriptions of neural data: neuron factors, reflecting cell assemblies; temporal factors, reflecting rapid circuit dynamics mediating perceptions, thoughts, and actions within each trial; and trial factors, describing both long-term learning and trial-to-trial changes in cognitive state. We demonstrate the broad applicability of TCA by revealing insights into diverse datasets derived from artificial neural networks, large-scale calcium imaging of rodent prefrontal cortex during maze navigation, and multielectrode recordings of macaque motor cortex during brain machine interface learning. Copyright © 2018 Elsevier Inc. All rights reserved.

Side-chain mobility in the folded state of Myoglobin

NASA Astrophysics Data System (ADS)

Lammert, Heiko; Onuchic, Jose

We study the accessibility of alternative side-chain rotamer configurations in the native state of Myoglobin, using an all-atom structure-based model. From long, unbiased simulation trajectories we determine occupancies of rotameric states and also estimate configurational and vibrational entropies. Direct sampling of the full native-state dynamics, enabled by the simple model, reveals facilitation of side-chain motions by backbone dynamics. Correlations between different dihedral angles are quantified and prove to be weak. We confirm global trends in the mobilities of side-chains, following burial and also the chemical character of residues. Surface residues loose little configurational entropy upon folding; side-chains contribute significantly to the entropy of the folded state. Mobilities of buried side-chains vary strongly with temperature. At ambient temperature, individual side-chains in the core of the protein gain substantial access to alternative rotamers, with occupancies that are likely observable experimentally. Finally, the dynamics of buried side-chains may be linked to the internal pockets, available to ligand gas molecules in Myoglobin.

Ribosome dynamics and tRNA movement by time-resolved electron cryomicroscopy.

PubMed

Fischer, Niels; Konevega, Andrey L; Wintermeyer, Wolfgang; Rodnina, Marina V; Stark, Holger

2010-07-15

The translocation step of protein synthesis entails large-scale rearrangements of the ribosome-transfer RNA (tRNA) complex. Here we have followed tRNA movement through the ribosome during translocation by time-resolved single-particle electron cryomicroscopy (cryo-EM). Unbiased computational sorting of cryo-EM images yielded 50 distinct three-dimensional reconstructions, showing the tRNAs in classical, hybrid and various novel intermediate states that provide trajectories and kinetic information about tRNA movement through the ribosome. The structures indicate how tRNA movement is coupled with global and local conformational changes of the ribosome, in particular of the head and body of the small ribosomal subunit, and show that dynamic interactions between tRNAs and ribosomal residues confine the path of the tRNAs through the ribosome. The temperature dependence of ribosome dynamics reveals a surprisingly flat energy landscape of conformational variations at physiological temperature. The ribosome functions as a Brownian machine that couples spontaneous conformational changes driven by thermal energy to directed movement.

Joshua Vermaas | NREL

Science.gov Websites

molecular dynamics simulations to explore biological interfaces, such as those found at the cell membrane or in lignocellulosic biomass. In particular, molecular dynamics can see in molecular detail the research toward fruitful results. Areas of Expertise Molecular dynamics Compound parameterization

Molecular Dynamics Analysis of Lysozyme Protein in Ethanol- Water Mixed Solvent

DTIC Science & Technology

2012-01-01

molecular dynamics simulations of solvent effect on lysozyme protein, using water, ethanol, and different concentrations of water-ethanol mixtures as...understood. This work focuses on detailed molecular dynamics simulations of solvent effect on lysozyme protein, using water, ethanol, and different...using GROMACS molecular dynamics simulation (MD) code. Compared to water environment, the lysozyme structure showed remarkable changes in water

Integration of Molecular Dynamics Based Predictions into the Optimization of De Novo Protein Designs: Limitations and Benefits.

PubMed

Carvalho, Henrique F; Barbosa, Arménio J M; Roque, Ana C A; Iranzo, Olga; Branco, Ricardo J F

2017-01-01

Recent advances in de novo protein design have gained considerable insight from the intrinsic dynamics of proteins, based on the integration of molecular dynamics simulations protocols on the state-of-the-art de novo protein design protocols used nowadays. With this protocol we illustrate how to set up and run a molecular dynamics simulation followed by a functional protein dynamics analysis. New users will be introduced to some useful open-source computational tools, including the GROMACS molecular dynamics simulation software package and ProDy for protein structural dynamics analysis.

Potent New Small-Molecule Inhibitor of Botulinum Neurotoxin Serotype A Endopeptidase Developed by Synthesis-Based Computer-Aided Molecular Design

DTIC Science & Technology

2009-11-01

dynamics of the complex predicted by multiple molecular dynamics simulations , and discuss further structural optimization to achieve better in vivo efficacy...complex with BoNTAe and the dynamics of the complex predicted by multiple molecular dynamics simulations (MMDSs). On the basis of the 3D model, we discuss...is unlimited whereas AHP exhibited 54% inhibition under the same conditions (Table 1). Computer Simulation Twenty different molecular dynamics

Spectroscopic observation of SN2017gkk by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Onori, F.; Benetti, S.; Cappellaro, E.; Losada, Illa R.; Gafton, E.; NUTS Collaboration

2017-09-01

The Nordic Optical Telescope (NOT) Unbiased Transient Survey (NUTS; ATel #8992) reports the spectroscopic classification of supernova SN2017gkk (=MASTER OT J091344.71762842.5) in host galaxy NGC 2748.

Spectroscopic observation of ASASSN-17he by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Kostrzewa-Rutkowska, Z.; Benetti, S.; Dong, S.; Stritzinger, M.; Stanek, K.; Brimacombe, J.; Sagues, A.; Galindo, P.; Losada, I. Rivero

2017-10-01

The Nordic Optical Telescope (NOT) Unbiased Transient Survey (NUTS; ATel #8992) reports the spectroscopic classification of ASASSN-17he. The candidate was discovered by by the All-Sky Automated Survey for Supernovae.

The "Collisions Cube" Molecular Dynamics Simulator.

ERIC Educational Resources Information Center

Nash, John J.; Smith, Paul E.

1995-01-01

Describes a molecular dynamics simulator that employs ping-pong balls as the atoms or molecules and is suitable for either large lecture halls or small classrooms. Discusses its use in illustrating many of the fundamental concepts related to molecular motion and dynamics and providing a three-dimensional perspective of molecular motion. (JRH)

Protein Folding Simulations Combining Self-Guided Langevin Dynamics and Temperature-Based Replica Exchange

DTIC Science & Technology

2010-01-01

formulations of molecular dynamics (MD) and Langevin dynamics (LD) simulations for the prediction of thermodynamic folding observables of the Trp-cage...ad hoc force term in the SGLD model. Introduction Molecular dynamics (MD) simulations of small proteins provide insight into the mechanisms and... molecular dynamics (MD) and Langevin dynamics (LD) simulations for the prediction of thermodynamic folding observables of the Trp-cage mini-protein. All

Membrane Insertion Profiles of Peptides Probed by Molecular Dynamics Simulations

DTIC Science & Technology

2008-07-17

Membrane insertion profiles of peptides probed by molecular dynamics simulations In-Chul Yeh,* Mark A. Olson,# Michael S. Lee,*#§ and Anders...a methodology based on molecular dynamics simulation techniques to probe the insertion profiles of small peptides across the membrane interface. The...profiles of peptides probed by molecular dynamics simulations 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d

Efficient Conformational Sampling in Explicit Solvent Using a Hybrid Replica Exchange Molecular Dynamics Method

DTIC Science & Technology

2011-12-01

REMD while reproducing the energy landscape of explicit solvent simulations . ’ INTRODUCTION Molecular dynamics (MD) simulations of proteins can pro...Mongan, J.; McCammon, J. A. Accelerated molecular dynamics : a promising and efficient simulation method for biomolecules. J. Chem. Phys. 2004, 120 (24...Chemical Theory and Computation ARTICLE (8) Abraham,M. J.; Gready, J. E. Ensuringmixing efficiency of replica- exchange molecular dynamics simulations . J

Spectroscopic classification of Gaia18adv by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Gall, C.; Benetti, S.; Wyrzykowski, L.; Stritzinger, M.; Holmbo, S.; Dong, S.; Siltala, Lauri; NUTS Collaboration

2018-01-01

The Nordic Optical Telescope (NOT) Unbiased Transient Survey (NUTS; ATel #8992) collaboration reports the spectroscopic classification of Gaia18adv (SN2018hh) near the host galaxy SDSS J121341.37+282640.0.

Gibbs Sampler-Based λ-Dynamics and Rao-Blackwell Estimator for Alchemical Free Energy Calculation.

PubMed

Ding, Xinqiang; Vilseck, Jonah Z; Hayes, Ryan L; Brooks, Charles L

2017-06-13

λ-dynamics is a generalized ensemble method for alchemical free energy calculations. In traditional λ-dynamics, the alchemical switch variable λ is treated as a continuous variable ranging from 0 to 1 and an empirical estimator is utilized to approximate the free energy. In the present article, we describe an alternative formulation of λ-dynamics that utilizes the Gibbs sampler framework, which we call Gibbs sampler-based λ-dynamics (GSLD). GSLD, like traditional λ-dynamics, can be readily extended to calculate free energy differences between multiple ligands in one simulation. We also introduce a new free energy estimator, the Rao-Blackwell estimator (RBE), for use in conjunction with GSLD. Compared with the current empirical estimator, the advantage of RBE is that RBE is an unbiased estimator and its variance is usually smaller than the current empirical estimator. We also show that the multistate Bennett acceptance ratio equation or the unbinned weighted histogram analysis method equation can be derived using the RBE. We illustrate the use and performance of this new free energy computational framework by application to a simple harmonic system as well as relevant calculations of small molecule relative free energies of solvation and binding to a protein receptor. Our findings demonstrate consistent and improved performance compared with conventional alchemical free energy methods.

Predicting longitudinal trajectories of health probabilities with random-effects multinomial logit regression.

PubMed

Liu, Xian; Engel, Charles C

2012-12-20

Researchers often encounter longitudinal health data characterized with three or more ordinal or nominal categories. Random-effects multinomial logit models are generally applied to account for potential lack of independence inherent in such clustered data. When parameter estimates are used to describe longitudinal processes, however, random effects, both between and within individuals, need to be retransformed for correctly predicting outcome probabilities. This study attempts to go beyond existing work by developing a retransformation method that derives longitudinal growth trajectories of unbiased health probabilities. We estimated variances of the predicted probabilities by using the delta method. Additionally, we transformed the covariates' regression coefficients on the multinomial logit function, not substantively meaningful, to the conditional effects on the predicted probabilities. The empirical illustration uses the longitudinal data from the Asset and Health Dynamics among the Oldest Old. Our analysis compared three sets of the predicted probabilities of three health states at six time points, obtained from, respectively, the retransformation method, the best linear unbiased prediction, and the fixed-effects approach. The results demonstrate that neglect of retransforming random errors in the random-effects multinomial logit model results in severely biased longitudinal trajectories of health probabilities as well as overestimated effects of covariates on the probabilities. Copyright © 2012 John Wiley & Sons, Ltd.

Application of maximum-likelihood estimation in optical coherence tomography for nanometer-class thickness estimation

NASA Astrophysics Data System (ADS)

Huang, Jinxin; Yuan, Qun; Tankam, Patrice; Clarkson, Eric; Kupinski, Matthew; Hindman, Holly B.; Aquavella, James V.; Rolland, Jannick P.

2015-03-01

In biophotonics imaging, one important and quantitative task is layer-thickness estimation. In this study, we investigate the approach of combining optical coherence tomography and a maximum-likelihood (ML) estimator for layer thickness estimation in the context of tear film imaging. The motivation of this study is to extend our understanding of tear film dynamics, which is the prerequisite to advance the management of Dry Eye Disease, through the simultaneous estimation of the thickness of the tear film lipid and aqueous layers. The estimator takes into account the different statistical processes associated with the imaging chain. We theoretically investigated the impact of key system parameters, such as the axial point spread functions (PSF) and various sources of noise on measurement uncertainty. Simulations show that an OCT system with a 1 μm axial PSF (FWHM) allows unbiased estimates down to nanometers with nanometer precision. In implementation, we built a customized Fourier domain OCT system that operates in the 600 to 1000 nm spectral window and achieves 0.93 micron axial PSF in corneal epithelium. We then validated the theoretical framework with physical phantoms made of custom optical coatings, with layer thicknesses from tens of nanometers to microns. Results demonstrate unbiased nanometer-class thickness estimates in three different physical phantoms.

The influence of cooperation and defection on social decision making in depression: A study of the iterated Prisoner's Dilemma Game.

PubMed

Sorgi, Kristen M; van 't Wout, Mascha

2016-12-30

This study evaluated the influence of self-reported levels of depression on interpersonal strategic decision making when interacting with partners who differed in their predetermined tendency to cooperate in three separate computerized iterated Prisoner's Dilemma Games (iPDGs). Across 29 participants, cooperation was lowest when interacting with a predominantly defecting partner and highest when interacting with a predominantly cooperating partner. Greater depression severity was related to steadier and continued cooperation over trials with the cooperating partner, seeming to reflect a prosocial response tendency when interacting with this partner. With the unbiased partner, depression severity was associated with a more volatile response pattern in reaction to cooperation and defection by this partner. Severity of depression did not influence cooperation with a defecting partner or expectations about partner cooperation reported before the task began. Taken together, these data appear to show that in predominately positive interactions, as in the cooperating partner condition, depression is associated with less volatile, more consistent cooperation. When such clear feedback is absent, as in the unbiased partner condition, depression is associated with more volatile behavior. Nonetheless, participants were generally able to adapt their behavior accordingly in this dynamic interpersonal decision making context. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Effects of a mutation on the folding mechanism of a beta-hairpin.

PubMed

Juraszek, Jarek; Bolhuis, Peter G

2009-12-17

The folding mechanism of a protein is determined by its primary sequence. Yet, how the mechanism is changed by a mutation is still poorly understood, even for basic secondary structures such as beta-hairpins. We perform an extensive simulation study of the effects of mutating the GB1 beta-hairpin into Trpzip4 (Y5W, F12W, V14W) on the folding mechanism. While Trpzip4 has a much more stable native state due to very strong hydrophobic interactions of the side chains, its folding rate does not differ significantly from the wild type beta-hairpin. We sample the free-energy landscapes of both hairpins with Replica Exchange Molecular Dynamics (REMD) and identify the four (meta)stable states (U, H, F, and N). Using Transition Path Sampling (TPS), we then harvest ensembles of unbiased pathways between the H and F states and between the F and N states to investigate the unbiased folding mechanisms. In both hairpins, the hydrophobic collapse (U-H) is followed by the middle hydrogen bond formation (H-F), and finally a closing of the strands in a zipper-like fashion (F-N). For the Trpzip4, the path ensembles indicate that the final F-N step is much more difficult than for GB1 and involves partial unfolding, rezipping of hydrogen bonds, and rearrangement of the Trp-14 side chain. For the rate-limiting (H-F) step, the path ensembles show that in GB1 desolvation and strand closure go hand in hand, while in Trpzip4 desolvation is decoupled from strand closure. Nevertheless, likelihood maximization shows that the reaction coordinate for both hairpins remains the interstrand distance. We conclude that the folding mechanism of both hairpins is a combination of hydrophobic collapse and zipping of hydrogen bonds but that the zipper mechanism is more visible in Trpzip4. A major difference between the two hairpins is that in the transition state of the rate-limiting step for Trpzip4 one tryptophan is exposed to the solvent due to steric hindrance, making the folding mechanism more complex and leading to an increased F-N barrier. Thus, our results show in atomistic detail how a mutation leads to a different folding mechanism and results in a more frustrated folding free-energy landscape.

A Force Balanced Fragmentation Method for ab Initio Molecular Dynamic Simulation of Protein.

PubMed

Xu, Mingyuan; Zhu, Tong; Zhang, John Z H

2018-01-01

A force balanced generalized molecular fractionation with conjugate caps (FB-GMFCC) method is proposed for ab initio molecular dynamic simulation of proteins. In this approach, the energy of the protein is computed by a linear combination of the QM energies of individual residues and molecular fragments that account for the two-body interaction of hydrogen bond between backbone peptides. The atomic forces on the caped H atoms were corrected to conserve the total force of the protein. Using this approach, ab initio molecular dynamic simulation of an Ace-(ALA) 9 -NME linear peptide showed the conservation of the total energy of the system throughout the simulation. Further a more robust 110 ps ab initio molecular dynamic simulation was performed for a protein with 56 residues and 862 atoms in explicit water. Compared with the classical force field, the ab initio molecular dynamic simulations gave better description of the geometry of peptide bonds. Although further development is still needed, the current approach is highly efficient, trivially parallel, and can be applied to ab initio molecular dynamic simulation study of large proteins.

Parallel Fast Multipole Method For Molecular Dynamics

DTIC Science & Technology

2007-06-01

Parallel Fast Multipole Method For Molecular Dynamics THESIS Reid G. Ormseth, Captain, USAF AFIT/GAP/ENP/07-J02 DEPARTMENT OF THE AIR FORCE AIR...the United States Government. AFIT/GAP/ENP/07-J02 Parallel Fast Multipole Method For Molecular Dynamics THESIS Presented to the Faculty Department of...has also been provided by ‘The Art of Molecular Dynamics Simulation ’ by Dennis Rapaport. This work is the clearest treatment of the Fast Multipole

Molecular Dynamics Simulations of Folding and Insertion of the Ebola Virus Fusion Peptide into a Membrane Bilayer

DTIC Science & Technology

2008-07-01

Molecular Dynamics Simulations of Folding and Insertion of the Ebola Virus Fusion Peptide into a Membrane Bilayer Mark A. Olson1, In...presents replica-exchange molecular dynamics simulations of the folding and insertion of a 16- residue Ebola virus fusion peptide into a membrane...separate calculated structures into conformational basins. 2.1 Simulation models Molecular dynamics simulations were performed using the all-atom

Rationale and design of the Duke Electrophysiology Genetic and Genomic Studies (EPGEN) biorepository.

PubMed

Koontz, Jason I; Haithcock, Daniel; Cumbea, Valerie; Waldron, Anthony; Stricker, Kristie; Hughes, Amy; Nilsson, Kent; Sun, Albert; Piccini, Jonathan P; Kraus, William E; Pitt, Geoffrey S; Shah, Svati H; Hranitzky, Patrick

2009-11-01

Disturbances in cardiac rhythm can lead to significant morbidity and mortality. Many arrhythmias are known to have a heritable component, but the degree to which genetic variation contributes to disease risk and morbidity is poorly understood. The EPGEN is a prospective single-center repository that archives DNA, RNA, and protein samples obtained at the time of an electrophysiologic evaluation or intervention. To identify genes and molecular variants that are associated with risk for arrhythmic phenotypes, EPGEN uses unbiased genomic screening; candidate gene analysis; and both unbiased and targeted transcript, protein, and metabolite profiling. To date, EPGEN has successfully enrolled >1,500 subjects. The median age of the study population is 62.9 years; 35% of the subjects are female and 21% are black. To this point, the study population has been composed of patients who had undergone defibrillator (implantable cardioverter-defibrillator or cardiac resynchronization therapy defibrillator) implantation (45%), electrophysiology studies or ablation procedures (35%), and pacemaker implantation or other procedures (20%). The cohort has a high prevalence of comorbidities, including diabetes (33%), hypertension (73%), chronic kidney disease (26%), and peripheral vascular disease (13%). We have established a biorepository and clinical database composed of patients with electrophysiologic diseases. EPGEN will seek to (1) improve risk stratification, (2) elucidate mechanisms of arrhythmogenesis, and (3) identify novel pharmacologic targets for the treatment of heart rhythm disorders.

Multi-color electron microscopy by element-guided identification of cells, organelles and molecules.

PubMed

Scotuzzi, Marijke; Kuipers, Jeroen; Wensveen, Dasha I; de Boer, Pascal; Hagen, Kees C W; Hoogenboom, Jacob P; Giepmans, Ben N G

2017-04-07

Cellular complexity is unraveled at nanometer resolution using electron microscopy (EM), but interpretation of macromolecular functionality is hampered by the difficulty in interpreting grey-scale images and the unidentified molecular content. We perform large-scale EM on mammalian tissue complemented with energy-dispersive X-ray analysis (EDX) to allow EM-data analysis based on elemental composition. Endogenous elements, labels (gold and cadmium-based nanoparticles) as well as stains are analyzed at ultrastructural resolution. This provides a wide palette of colors to paint the traditional grey-scale EM images for composition-based interpretation. Our proof-of-principle application of EM-EDX reveals that endocrine and exocrine vesicles exist in single cells in Islets of Langerhans. This highlights how elemental mapping reveals unbiased biomedical relevant information. Broad application of EM-EDX will further allow experimental analysis on large-scale tissue using endogenous elements, multiple stains, and multiple markers and thus brings nanometer-scale 'color-EM' as a promising tool to unravel molecular (de)regulation in biomedicine.

Multi-color electron microscopy by element-guided identification of cells, organelles and molecules

PubMed Central

Scotuzzi, Marijke; Kuipers, Jeroen; Wensveen, Dasha I.; de Boer, Pascal; Hagen, Kees (C.) W.; Hoogenboom, Jacob P.; Giepmans, Ben N. G.

2017-01-01

Cellular complexity is unraveled at nanometer resolution using electron microscopy (EM), but interpretation of macromolecular functionality is hampered by the difficulty in interpreting grey-scale images and the unidentified molecular content. We perform large-scale EM on mammalian tissue complemented with energy-dispersive X-ray analysis (EDX) to allow EM-data analysis based on elemental composition. Endogenous elements, labels (gold and cadmium-based nanoparticles) as well as stains are analyzed at ultrastructural resolution. This provides a wide palette of colors to paint the traditional grey-scale EM images for composition-based interpretation. Our proof-of-principle application of EM-EDX reveals that endocrine and exocrine vesicles exist in single cells in Islets of Langerhans. This highlights how elemental mapping reveals unbiased biomedical relevant information. Broad application of EM-EDX will further allow experimental analysis on large-scale tissue using endogenous elements, multiple stains, and multiple markers and thus brings nanometer-scale ‘color-EM’ as a promising tool to unravel molecular (de)regulation in biomedicine. PMID:28387351

Proximity-Based Differential Single-Cell Analysis of the Niche to Identify Stem/Progenitor Cell Regulators.

PubMed

Silberstein, Lev; Goncalves, Kevin A; Kharchenko, Peter V; Turcotte, Raphael; Kfoury, Youmna; Mercier, Francois; Baryawno, Ninib; Severe, Nicolas; Bachand, Jacqueline; Spencer, Joel A; Papazian, Ani; Lee, Dongjun; Chitteti, Brahmananda Reddy; Srour, Edward F; Hoggatt, Jonathan; Tate, Tiffany; Lo Celso, Cristina; Ono, Noriaki; Nutt, Stephen; Heino, Jyrki; Sipilä, Kalle; Shioda, Toshihiro; Osawa, Masatake; Lin, Charles P; Hu, Guo-Fu; Scadden, David T

2016-10-06

Physiological stem cell function is regulated by secreted factors produced by niche cells. In this study, we describe an unbiased approach based on the differential single-cell gene expression analysis of mesenchymal osteolineage cells close to, and further removed from, hematopoietic stem/progenitor cells (HSPCs) to identify candidate niche factors. Mesenchymal cells displayed distinct molecular profiles based on their relative location. We functionally examined, among the genes that were preferentially expressed in proximal cells, three secreted or cell-surface molecules not previously connected to HSPC biology-the secreted RNase angiogenin, the cytokine IL18, and the adhesion molecule Embigin-and discovered that all of these factors are HSPC quiescence regulators. Therefore, our proximity-based differential single-cell approach reveals molecular heterogeneity within niche cells and can be used to identify novel extrinsic stem/progenitor cell regulators. Similar approaches could also be applied to other stem cell/niche pairs to advance the understanding of microenvironmental regulation of stem cell function. Copyright © 2016 Elsevier Inc. All rights reserved.

The Presynaptic Component of the Serotonergic System is Required for Clozapine's Efficacy

PubMed Central

Yadav, Prem N; Abbas, Atheir I; Farrell, Martilias S; Setola, Vincent; Sciaky, Noah; Huang, Xi-Ping; Kroeze, Wesley K; Crawford, LaTasha K; Piel, David A; Keiser, Michael J; Irwin, John J; Shoichet, Brian K; Deneris, Evan S; Gingrich, Jay; Beck, Sheryl G; Roth, Bryan L

2011-01-01

Clozapine, by virtue of its absence of extrapyramidal side effects and greater efficacy, revolutionized the treatment of schizophrenia, although the mechanisms underlying this exceptional activity remain controversial. Combining an unbiased cheminformatics and physical screening approach, we evaluated clozapine's activity at >2350 distinct molecular targets. Clozapine, and the closely related atypical antipsychotic drug olanzapine, interacted potently with a unique spectrum of molecular targets. This distinct pattern, which was not shared with the typical antipsychotic drug haloperidol, suggested that the serotonergic neuronal system was a key determinant of clozapine's actions. To test this hypothesis, we used pet1−/− mice, which are deficient in serotonergic presynaptic markers. We discovered that the antipsychotic-like properties of the atypical antipsychotic drugs clozapine and olanzapine were abolished in a pharmacological model that mimics NMDA-receptor hypofunction in pet1−/− mice, whereas haloperidol's efficacy was unaffected. These results show that clozapine's ability to normalize NMDA-receptor hypofunction, which is characteristic of schizophrenia, depends on an intact presynaptic serotonergic neuronal system. PMID:21048700

Spectroscopic classification of supernovae SN 2018aei and SN 2018aej by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Cannizzaro, G.; Kuncarayakti, H.; Fraser, M.; Hamanowicz, A.; Jonker, P.; Kankare, E.; Kostrzewa-Rutkowska, Z.; Onori, F.; Wevers, T.; Wyrzykowski, L.; Galbany, L.

2018-03-01

The NOT Unbiased Transient Survey (NUTS; ATel #8992) collaboration reports the spectroscopic classification of supernovae SN 2018aei and SN 2018aej, discovered by PanSTARSS Survey for Transients (ATel #11408).

Reconfigurable generation and measurement of mutually unbiased bases for time-bin qudits

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lukens, Joseph M.; Islam, Nurul T.; Lim, Charles Ci Wen

Here, we propose a method for implementing mutually unbiased generation and measurement of time-bin qudits using a cascade of electro-optic phase modulator–coded fiber Bragg grating pairs. Our approach requires only a single spatial mode and can switch rapidly between basis choices. We obtain explicit solutions for dimensions d = 2, 3, and 4 that realize all d + 1 possible mutually unbiased bases and analyze the performance of our approach in quantum key distribution. Given its practicality and compatibility with current technology, our approach provides a promising springboard for scalable processing of high-dimensional time-bin states.

Reconfigurable generation and measurement of mutually unbiased bases for time-bin qudits

DOE PAGES

Lukens, Joseph M.; Islam, Nurul T.; Lim, Charles Ci Wen; ...

2018-03-12

Here, we propose a method for implementing mutually unbiased generation and measurement of time-bin qudits using a cascade of electro-optic phase modulator–coded fiber Bragg grating pairs. Our approach requires only a single spatial mode and can switch rapidly between basis choices. We obtain explicit solutions for dimensions d = 2, 3, and 4 that realize all d + 1 possible mutually unbiased bases and analyze the performance of our approach in quantum key distribution. Given its practicality and compatibility with current technology, our approach provides a promising springboard for scalable processing of high-dimensional time-bin states.

Reconfigurable generation and measurement of mutually unbiased bases for time-bin qudits

NASA Astrophysics Data System (ADS)

Lukens, Joseph M.; Islam, Nurul T.; Lim, Charles Ci Wen; Gauthier, Daniel J.

2018-03-01

We propose a method for implementing mutually unbiased generation and measurement of time-bin qudits using a cascade of electro-optic phase modulator-coded fiber Bragg grating pairs. Our approach requires only a single spatial mode and can switch rapidly between basis choices. We obtain explicit solutions for dimensions d = 2, 3, and 4 that realize all d + 1 possible mutually unbiased bases and analyze the performance of our approach in quantum key distribution. Given its practicality and compatibility with current technology, our approach provides a promising springboard for scalable processing of high-dimensional time-bin states.

Next generation extended Lagrangian first principles molecular dynamics

NASA Astrophysics Data System (ADS)

Niklasson, Anders M. N.

2017-08-01

Extended Lagrangian Born-Oppenheimer molecular dynamics [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] is formulated for general Hohenberg-Kohn density-functional theory and compared with the extended Lagrangian framework of first principles molecular dynamics by Car and Parrinello [Phys. Rev. Lett. 55, 2471 (1985)]. It is shown how extended Lagrangian Born-Oppenheimer molecular dynamics overcomes several shortcomings of regular, direct Born-Oppenheimer molecular dynamics, while improving or maintaining important features of Car-Parrinello simulations. The accuracy of the electronic degrees of freedom in extended Lagrangian Born-Oppenheimer molecular dynamics, with respect to the exact Born-Oppenheimer solution, is of second-order in the size of the integration time step and of fourth order in the potential energy surface. Improved stability over recent formulations of extended Lagrangian Born-Oppenheimer molecular dynamics is achieved by generalizing the theory to finite temperature ensembles, using fractional occupation numbers in the calculation of the inner-product kernel of the extended harmonic oscillator that appears as a preconditioner in the electronic equations of motion. Material systems that normally exhibit slow self-consistent field convergence can be simulated using integration time steps of the same order as in direct Born-Oppenheimer molecular dynamics, but without the requirement of an iterative, non-linear electronic ground-state optimization prior to the force evaluations and without a systematic drift in the total energy. In combination with proposed low-rank and on the fly updates of the kernel, this formulation provides an efficient and general framework for quantum-based Born-Oppenheimer molecular dynamics simulations.

Next generation extended Lagrangian first principles molecular dynamics.

PubMed

Niklasson, Anders M N

2017-08-07

Extended Lagrangian Born-Oppenheimer molecular dynamics [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] is formulated for general Hohenberg-Kohn density-functional theory and compared with the extended Lagrangian framework of first principles molecular dynamics by Car and Parrinello [Phys. Rev. Lett. 55, 2471 (1985)]. It is shown how extended Lagrangian Born-Oppenheimer molecular dynamics overcomes several shortcomings of regular, direct Born-Oppenheimer molecular dynamics, while improving or maintaining important features of Car-Parrinello simulations. The accuracy of the electronic degrees of freedom in extended Lagrangian Born-Oppenheimer molecular dynamics, with respect to the exact Born-Oppenheimer solution, is of second-order in the size of the integration time step and of fourth order in the potential energy surface. Improved stability over recent formulations of extended Lagrangian Born-Oppenheimer molecular dynamics is achieved by generalizing the theory to finite temperature ensembles, using fractional occupation numbers in the calculation of the inner-product kernel of the extended harmonic oscillator that appears as a preconditioner in the electronic equations of motion. Material systems that normally exhibit slow self-consistent field convergence can be simulated using integration time steps of the same order as in direct Born-Oppenheimer molecular dynamics, but without the requirement of an iterative, non-linear electronic ground-state optimization prior to the force evaluations and without a systematic drift in the total energy. In combination with proposed low-rank and on the fly updates of the kernel, this formulation provides an efficient and general framework for quantum-based Born-Oppenheimer molecular dynamics simulations.

The Design, Synthesis, and Study of Solid-State Molecular Rotors: Structure/Function Relationships for Condensed-Phase Anisotropic Dynamics

NASA Astrophysics Data System (ADS)

Vogelsberg, Cortnie Sue

Amphidynamic crystals are an extremely promising platform for the development of artificial molecular machines and stimuli-responsive materials. In analogy to skeletal muscle, their function will rely upon the collective operation of many densely packed molecular machines (i.e. actin-bound myosin) that are self-assembled in a highly organized anisotropic medium. By choosing lattice-forming elements and moving "parts" with specific functionalities, individual molecular machines may be synthesized and self-assembled in order to carry out desirable functions. In recent years, efforts in the design of amphidynamic materials based on molecular gyroscopes and compasses have shown that a certain amount of free volume is essential to facilitate internal rotation and reorientation within a crystal. In order to further establish structure/function relationships to advance the development of increasingly complex molecular machinery, molecular rotors and a molecular "spinning" top were synthesized and incorporated into a variety of solid-state architectures with different degrees of periodicity, dimensionality, and free volume. Specifically, lamellar molecular crystals, hierarchically ordered periodic mesoporous organosilicas, and metal-organic frameworks were targeted for the development of solid-state molecular machines. Using an array of solid-state nuclear magnetic resonance spectroscopy techniques, the dynamic properties of these novel molecular machine assemblies were determined and correlated with their corresponding structural features. It was found that architecture type has a profound influence on functional dynamics. The study of layered molecular crystals, composed of either molecular rotors or "spinning" tops, probed functional dynamics within dense, highly organized environments. From their study, it was discovered that: 1) crystallographically distinct sites may be utilized to differentiate machine function, 2) halogen bonding interactions are sufficiently strong to direct an assembly of molecular machines, 3) the relative flexibility of the crystal environment proximate to a dynamic component may have a significant effect on its function, and, 4) molecular machines, which possess both solid-state photochemical reactivity and dynamics may show complex reaction kinetics if the correlation time of the dynamic process and the lifetime of the excited state occur on the same time scale and the dynamic moiety inherently participates as a reaction intermediate. The study of periodic mesoporous organosilica with hierarchical order probed molecular dynamics within 2D layers of molecular rotors, organized in only one dimension and with ca. 50% exposed to the mesopore free volume. From their study, it was discovered that: 1) molecular rotors, which comprise the layers of the mesopore walls, form a 2D rotational glass, 2) rotator dynamics within the 2D rotational glass undergo a transition to a 2D rotational fluid, and, 3) a 2D rotational glass transition may be exploited to develop hyper-sensitive thermally activated molecular machines. The study of a metal-organic framework assembled from molecular rotors probed dynamics in a periodic three-dimensional free-volume environment, without the presence of close contacts. From the study of this solid-state material, it was determined that: 1) the intrinsic electronic barrier is one of the few factors, which may affect functional dynamics in a true free-volume environment, and, 2) molecular machines with dynamic barriers <

Denoising time-resolved microscopy image sequences with singular value thresholding.

PubMed

Furnival, Tom; Leary, Rowan K; Midgley, Paul A

2017-07-01

Time-resolved imaging in microscopy is important for the direct observation of a range of dynamic processes in both the physical and life sciences. However, the image sequences are often corrupted by noise, either as a result of high frame rates or a need to limit the radiation dose received by the sample. Here we exploit both spatial and temporal correlations using low-rank matrix recovery methods to denoise microscopy image sequences. We also make use of an unbiased risk estimator to address the issue of how much thresholding to apply in a robust and automated manner. The performance of the technique is demonstrated using simulated image sequences, as well as experimental scanning transmission electron microscopy data, where surface adatom motion and nanoparticle structural dynamics are recovered at rates of up to 32 frames per second. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Dynamics of lineage commitment revealed by single-cell transcriptomics of differentiating embryonic stem cells.

PubMed

Semrau, Stefan; Goldmann, Johanna E; Soumillon, Magali; Mikkelsen, Tarjei S; Jaenisch, Rudolf; van Oudenaarden, Alexander

2017-10-23

Gene expression heterogeneity in the pluripotent state of mouse embryonic stem cells (mESCs) has been increasingly well-characterized. In contrast, exit from pluripotency and lineage commitment have not been studied systematically at the single-cell level. Here we measure the gene expression dynamics of retinoic acid driven mESC differentiation from pluripotency to lineage commitment, using an unbiased single-cell transcriptomics approach. We find that the exit from pluripotency marks the start of a lineage transition as well as a transient phase of increased susceptibility to lineage specifying signals. Our study reveals several transcriptional signatures of this phase, including a sharp increase of gene expression variability and sequential expression of two classes of transcriptional regulators. In summary, we provide a comprehensive analysis of the exit from pluripotency and lineage commitment at the single cell level, a potential stepping stone to improved lineage manipulation through timing of differentiation cues.

Revealing missing charges with generalised quantum fluctuation relations.

PubMed

Mur-Petit, J; Relaño, A; Molina, R A; Jaksch, D

2018-05-22

The non-equilibrium dynamics of quantum many-body systems is one of the most fascinating problems in physics. Open questions range from how they relax to equilibrium to how to extract useful work from them. A critical point lies in assessing whether a system has conserved quantities (or 'charges'), as these can drastically influence its dynamics. Here we propose a general protocol to reveal the existence of charges based on a set of exact relations between out-of-equilibrium fluctuations and equilibrium properties of a quantum system. We apply these generalised quantum fluctuation relations to a driven quantum simulator, demonstrating their relevance to obtain unbiased temperature estimates from non-equilibrium measurements. Our findings will help guide research on the interplay of quantum and thermal fluctuations in quantum simulation, in studying the transition from integrability to chaos and in the design of new quantum devices.

Biological Bases of Space Radiation Risk

NASA Technical Reports Server (NTRS)

1997-01-01

In this session, Session JP4, the discussion focuses on the following topics: Hematopoiesis Dynamics in Irradiated Mammals, Mathematical Modeling; Estimating Health Risks in Space from Galactic Cosmic Rays; Failure of Heavy Ions to Affect Physiological Integrity of the Corneal Endothelial Monolayer; Application of an Unbiased Two-Gel CDNA Library Screening Method to Expression Monitoring of Genes in Irradiated Versus Control Cells; Detection of Radiation-Induced DNA Strand Breaks in Mammalian Cells By Enzymatic Post-Labeling; Evaluation of Bleomycin-Induced Chromosome Aberrations Under Microgravity Conditions in Human Lymphocytes, Using "Fish" Techniques; Technical Description of the Space Exposure Biology Assembly Seba on ISS; and Cytogenetic Research in Biological Dosimetry.

Reconstructing the equilibrium Boltzmann distribution from well-tempered metadynamics.

PubMed

Bonomi, M; Barducci, A; Parrinello, M

2009-08-01

Metadynamics is a widely used and successful method for reconstructing the free-energy surface of complex systems as a function of a small number of suitably chosen collective variables. This is achieved by biasing the dynamics of the system. The bias acting on the collective variables distorts the probability distribution of the other variables. Here we present a simple reweighting algorithm for recovering the unbiased probability distribution of any variable from a well-tempered metadynamics simulation. We show the efficiency of the reweighting procedure by reconstructing the distribution of the four backbone dihedral angles of alanine dipeptide from two and even one dimensional metadynamics simulation. 2009 Wiley Periodicals, Inc.

Stroma-associated master regulators of molecular subtypes predict patient prognosis in ovarian cancer.

PubMed

Zhang, Shengzhe; Jing, Ying; Zhang, Meiying; Zhang, Zhenfeng; Ma, Pengfei; Peng, Huixin; Shi, Kaixuan; Gao, Wei-Qiang; Zhuang, Guanglei

2015-11-04

High-grade serous ovarian carcinoma (HGS-OvCa) has the lowest survival rate among all gynecologic cancers and is hallmarked by a high degree of heterogeneity. The Cancer Genome Atlas network has described a gene expression-based molecular classification of HGS-OvCa into Differentiated, Mesenchymal, Immunoreactive and Proliferative subtypes. However, the biological underpinnings and regulatory mechanisms underlying the distinct molecular subtypes are largely unknown. Here we showed that tumor-infiltrating stromal cells significantly contributed to the assignments of Mesenchymal and Immunoreactive clusters. Using reverse engineering and an unbiased interrogation of subtype regulatory networks, we identified the transcriptional modules containing master regulators that drive gene expression of Mesenchymal and Immunoreactive HGS-OvCa. Mesenchymal master regulators were associated with poor prognosis, while Immunoreactive master regulators positively correlated with overall survival. Meta-analysis of 749 HGS-OvCa expression profiles confirmed that master regulators as a prognostic signature were able to predict patient outcome. Our data unraveled master regulatory programs of HGS-OvCa subtypes with prognostic and potentially therapeutic relevance, and suggested that the unique transcriptional and clinical characteristics of ovarian Mesenchymal and Immunoreactive subtypes could be, at least partially, ascribed to tumor microenvironment.

The IBD interactome: an integrated view of aetiology, pathogenesis and therapy.

PubMed

de Souza, Heitor S P; Fiocchi, Claudio; Iliopoulos, Dimitrios

2017-12-01

Crohn's disease and ulcerative colitis are prototypical complex diseases characterized by chronic and heterogeneous manifestations, induced by interacting environmental, genomic, microbial and immunological factors. These interactions result in an overwhelming complexity that cannot be tackled by studying the totality of each pathological component (an '-ome') in isolation without consideration of the interaction among all relevant -omes that yield an overall 'network effect'. The outcome of this effect is the 'IBD interactome', defined as a disease network in which dysregulation of individual -omes causes intestinal inflammation mediated by dysfunctional molecular modules. To define the IBD interactome, new concepts and tools are needed to implement a systems approach; an unbiased data-driven integration strategy that reveals key players of the system, pinpoints the central drivers of inflammation and enables development of targeted therapies. Powerful bioinformatics tools able to query and integrate multiple -omes are available, enabling the integration of genomic, epigenomic, transcriptomic, proteomic, metabolomic and microbiome information to build a comprehensive molecular map of IBD. This approach will enable identification of IBD molecular subtypes, correlations with clinical phenotypes and elucidation of the central hubs of the IBD interactome that will aid discovery of compounds that can specifically target the hubs that control the disease.

Modeling Molecular and Cellular Aspects of Human Disease using the Nematode Caenorhabditis elegans

PubMed Central

Silverman, Gary A.; Luke, Cliff J.; Bhatia, Sangeeta R.; Long, Olivia S.; Vetica, Anne C.; Perlmutter, David H.; Pak, Stephen C.

2009-01-01

As an experimental system, Caenorhabditis elegans, offers a unique opportunity to interrogate in vivo the genetic and molecular functions of human disease-related genes. For example, C. elegans has provided crucial insights into fundamental biological processes such as cell death and cell fate determinations, as well as pathological processes such as neurodegeneration and microbial susceptibility. The C. elegans model has several distinct advantages including a completely sequenced genome that shares extensive homology with that of mammals, ease of cultivation and storage, a relatively short lifespan and techniques for generating null and transgenic animals. However, the ability to conduct unbiased forward and reverse genetic screens in C. elegans remains one of the most powerful experimental paradigms for discovering the biochemical pathways underlying human disease phenotypes. The identification of these pathways leads to a better understanding of the molecular interactions that perturb cellular physiology, and forms the foundation for designing mechanism-based therapies. To this end, the ability to process large numbers of isogenic animals through automated work stations suggests that C. elegans, manifesting different aspects of human disease phenotypes, will become the platform of choice for in vivo drug discovery and target validation using high-throughput/content screening technologies. PMID:18852689

A Quantum-Based Similarity Method in Virtual Screening.

PubMed

Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

2015-10-02

One of the most widely-used techniques for ligand-based virtual screening is similarity searching. This study adopted the concepts of quantum mechanics to present as state-of-the-art similarity method of molecules inspired from quantum theory. The representation of molecular compounds in mathematical quantum space plays a vital role in the development of quantum-based similarity approach. One of the key concepts of quantum theory is the use of complex numbers. Hence, this study proposed three various techniques to embed and to re-represent the molecular compounds to correspond with complex numbers format. The quantum-based similarity method that developed in this study depending on complex pure Hilbert space of molecules called Standard Quantum-Based (SQB). The recall of retrieved active molecules were at top 1% and top 5%, and significant test is used to evaluate our proposed methods. The MDL drug data report (MDDR), maximum unbiased validation (MUV) and Directory of Useful Decoys (DUD) data sets were used for experiments and were represented by 2D fingerprints. Simulated virtual screening experiment show that the effectiveness of SQB method was significantly increased due to the role of representational power of molecular compounds in complex numbers forms compared to Tanimoto benchmark similarity measure.

Age, environment, object recognition and morphological diversity of GFAP-immunolabeled astrocytes.

PubMed

Diniz, Daniel Guerreiro; de Oliveira, Marcus Augusto; de Lima, Camila Mendes; Fôro, César Augusto Raiol; Sosthenes, Marcia Consentino Kronka; Bento-Torres, João; da Costa Vasconcelos, Pedro Fernando; Anthony, Daniel Clive; Diniz, Cristovam Wanderley Picanço

2016-10-10

Few studies have explored the glial response to a standard environment and how the response may be associated with age-related cognitive decline in learning and memory. Here we investigated aging and environmental influences on hippocampal-dependent tasks and on the morphology of an unbiased selected population of astrocytes from the molecular layer of dentate gyrus, which is the main target of perforant pathway. Six and twenty-month-old female, albino Swiss mice were housed, from weaning, in a standard or enriched environment, including running wheels for exercise and tested for object recognition and contextual memories. Young adult and aged subjects, independent of environment, were able to distinguish familiar from novel objects. All experimental groups, except aged mice from standard environment, distinguish stationary from displaced objects. Young adult but not aged mice, independent of environment, were able to distinguish older from recent objects. Only young mice from an enriched environment were able to distinguish novel from familiar contexts. Unbiased selected astrocytes from the molecular layer of the dentate gyrus were reconstructed in three-dimensions and classified using hierarchical cluster analysis of bimodal or multimodal morphological features. We found two morphological phenotypes of astrocytes and we designated type I the astrocytes that exhibited significantly higher values of morphological complexity as compared with type II. Complexity = [Sum of the terminal orders + Number of terminals] × [Total branch length/Number of primary branches]. On average, type I morphological complexity seems to be much more sensitive to age and environmental influences than that of type II. Indeed, aging and environmental impoverishment interact and reduce the morphological complexity of type I astrocytes at a point that they could not be distinguished anymore from type II. We suggest these two types of astrocytes may have different physiological roles and that the detrimental effects of aging on memory in mice from a standard environment may be associated with a reduction of astrocytes morphological diversity.

The Development and Comparison of Molecular Dynamics Simulation and Monte Carlo Simulation

NASA Astrophysics Data System (ADS)

Chen, Jundong

2018-03-01

Molecular dynamics is an integrated technology that combines physics, mathematics and chemistry. Molecular dynamics method is a computer simulation experimental method, which is a powerful tool for studying condensed matter system. This technique not only can get the trajectory of the atom, but can also observe the microscopic details of the atomic motion. By studying the numerical integration algorithm in molecular dynamics simulation, we can not only analyze the microstructure, the motion of particles and the image of macroscopic relationship between them and the material, but can also study the relationship between the interaction and the macroscopic properties more conveniently. The Monte Carlo Simulation, similar to the molecular dynamics, is a tool for studying the micro-molecular and particle nature. In this paper, the theoretical background of computer numerical simulation is introduced, and the specific methods of numerical integration are summarized, including Verlet method, Leap-frog method and Velocity Verlet method. At the same time, the method and principle of Monte Carlo Simulation are introduced. Finally, similarities and differences of Monte Carlo Simulation and the molecular dynamics simulation are discussed.

Dynamic Structure of a Molecular Liquid S0.5Cl0.5: Ab initio Molecular-Dynamics Simulations

NASA Astrophysics Data System (ADS)

Ohmura, Satoshi; Shimakura, Hironori; Kawakita, Yukinobu; Shimojo, Fuyuki; Yao, Makoto

2013-07-01

The static and dynamic structures of a molecular liquid S0.5Cl0.5 consisting of Cl--S--S--Cl (S2Cl2) type molecules are studied by means of ab initio molecular dynamics simulations. Both the calculated static and dynamic structure factors are in good agreement with experimental results. The dynamic structures are discussed based on van-Hove distinct correlation functions, molecular translational mean-square displacements (TMSD) and rotational mean-square displacements (RMSD). In the TMSD and RMSD, there are ballistic and diffusive regimes in the sub-picosecond and picosecond time regions, respectively. These time scales are consistent with the decay time observed experimentally. The interaction between molecules in the liquid is also discussed in comparison with that in another liquid chalcogen--halogen system Se0.5Cl0.5.

Spectroscopic observation of SN 2017jzp and SN 2018bf by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Kuncarayakti, H.; Mattila, S.; Kotak, R.; Harmanen, J.; Reynolds, T.; Wyrzykowski, L.; Stritzinger, M.; Onori, F.; Somero, A.; Kangas, T.; Lundqvist, P.; Taddia, F.; Ergon, M.

2018-01-01

The Nordic Optical Telescope (NOT) Unbiased Transient Survey (NUTS; ATel #8992) reports the spectroscopic classification of SNe 2017jzp and 2018bf in host galaxies KUG 1326+679 and SDSS J225746.53+253833.5, respectively.

Spectroscopic observation of ASASSN-17nb and CSS170922:172546+342249 by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Harmanen, J.; Mattila, S.; Kuncarayakti, H.; Reynolds, T.; Somero, A.; Kangas, T.; Lundqvist, P.; Taddia, F.; Ergon, M.; Dong, S.; Pastorello, A.; Pursimo, T.; NUTS Collaboration

2017-10-01

The Nordic Optical Telescope (NOT) Unbiased Transient Survey (NUTS; ATel #8992) reports the spectroscopic classification of ASASSN-17nb in MCG+06-17-007 and CSS170922:172546+342249 in an unknown host galaxy.

Losing the rose tinted glasses: neural substrates of unbiased belief updating in depression

PubMed Central

Garrett, Neil; Sharot, Tali; Faulkner, Paul; Korn, Christoph W.; Roiser, Jonathan P.; Dolan, Raymond J.

2014-01-01

Recent evidence suggests that a state of good mental health is associated with biased processing of information that supports a positively skewed view of the future. Depression, on the other hand, is associated with unbiased processing of such information. Here, we use brain imaging in conjunction with a belief update task administered to clinically depressed patients and healthy controls to characterize brain activity that supports unbiased belief updating in clinically depressed individuals. Our results reveal that unbiased belief updating in depression is mediated by strong neural coding of estimation errors in response to both good news (in left inferior frontal gyrus and bilateral superior frontal gyrus) and bad news (in right inferior parietal lobule and right inferior frontal gyrus) regarding the future. In contrast, intact mental health was linked to a relatively attenuated neural coding of bad news about the future. These findings identify a neural substrate mediating the breakdown of biased updating in major depression disorder, which may be essential for mental health. PMID:25221492

Allowable SEM noise for unbiased LER measurement

NASA Astrophysics Data System (ADS)

Papavieros, George; Constantoudis, Vassilios; Gogolides, Evangelos

2018-03-01

Recently, a novel method for the calculation of unbiased Line Edge Roughness based on Power Spectral Density analysis has been proposed. In this paper first an alternative method is discussed and investigated, utilizing the Height-Height Correlation Function (HHCF) of edges. The HHCF-based method enables the unbiased determination of the whole triplet of LER parameters including besides rms the correlation length and roughness exponent. The key of both methods is the sensitivity of PSD and HHCF on noise at high frequencies and short distance respectively. Secondly, we elaborate a testbed of synthesized SEM images with controlled LER and noise to justify the effectiveness of the proposed unbiased methods. Our main objective is to find out the boundaries of the method in respect to noise levels and roughness characteristics, for which the method remains reliable, i.e the maximum amount of noise allowed, for which the output results cope with the controllable known inputs. At the same time, we will also set the extremes of roughness parameters for which the methods hold their accuracy.

Surface induced molecular dynamics of thin lipid films confined to submicron cavities: A 1H multiple-quantum NMR study

NASA Astrophysics Data System (ADS)

Jagadeesh, B.; Prabhakar, A.; Demco, D. E.; Buda, A.; Blümich, B.

2005-03-01

The dynamics and molecular order of thin lipid (lecithin) films confined to 200, 100 and 20 nm cylindrical pores with varying surface coverage, were investigated by 1H multiple-quantum NMR. The results show that the molecular dynamics in the surface controlled layers are less hindered compared to those in the bulk. Dynamic heterogeneity among terminal CH 3 groups is evident. Enhanced dynamic freedom is observed for films with area per molecule, ˜ 128 Å 2. The results are discussed in terms of changes in the lipid molecular organization with respect to surface concentration, its plausible motional modes and dynamic heterogeneity.

The Distributed Diagonal Force Decomposition Method for Parallelizing Molecular Dynamics Simulations

PubMed Central

Boršnik, Urban; Miller, Benjamin T.; Brooks, Bernard R.; Janežič, Dušanka

2011-01-01

Parallelization is an effective way to reduce the computational time needed for molecular dynamics simulations. We describe a new parallelization method, the distributed-diagonal force decomposition method, with which we extend and improve the existing force decomposition methods. Our new method requires less data communication during molecular dynamics simulations than replicated data and current force decomposition methods, increasing the parallel efficiency. It also dynamically load-balances the processors' computational load throughout the simulation. The method is readily implemented in existing molecular dynamics codes and it has been incorporated into the CHARMM program, allowing its immediate use in conjunction with the many molecular dynamics simulation techniques that are already present in the program. We also present the design of the Force Decomposition Machine, a cluster of personal computers and networks that is tailored to running molecular dynamics simulations using the distributed diagonal force decomposition method. The design is expandable and provides various degrees of fault resilience. This approach is easily adaptable to computers with Graphics Processing Units because it is independent of the processor type being used. PMID:21793007

Ab Initio Calculations of Transport in Titanium and Aluminum Mixtures

NASA Astrophysics Data System (ADS)

Walker, Nicholas; Novak, Brian; Tam, Ka Ming; Moldovan, Dorel; Jarrell, Mark

In classical molecular dynamics simulations, the self-diffusion and shear viscosity of titanium about the melting point have fallen within the ranges provided by experimental data. However, the experimental data is difficult to collect and has been rather scattered, making it of limited value for the validation of these calculations. By using ab initio molecular dynamics simulations within the density functional theory framework, the classical molecular dynamics data can be validated. The dynamical data from the ab initio molecular dynamics can also be used to calculate new potentials for use in classical molecular dynamics, allowing for more accurate classical dynamics simulations for the liquid phase. For metallic materials such as titanium and aluminum alloys, these calculations are very valuable due to an increasing demand for the knowledge of their thermophysical properties that drive the development of new materials. For example, alongside knowledge of the surface tension, viscosity is an important input for modeling the additive manufacturing process at the continuum level. We are developing calculations of the viscosity along with the self-diffusion for aluminum, titanium, and titanium-aluminum alloys with ab initio molecular dynamics. Supported by the National Science Foundation through cooperative agreement OIA-1541079 and the Louisiana Board of Regents.

Next Generation Extended Lagrangian Quantum-based Molecular Dynamics

NASA Astrophysics Data System (ADS)

Negre, Christian

2017-06-01

A new framework for extended Lagrangian first-principles molecular dynamics simulations is presented, which overcomes shortcomings of regular, direct Born-Oppenheimer molecular dynamics, while maintaining important advantages of the unified extended Lagrangian formulation of density functional theory pioneered by Car and Parrinello three decades ago. The new framework allows, for the first time, energy conserving, linear-scaling Born-Oppenheimer molecular dynamics simulations, which is necessary to study larger and more realistic systems over longer simulation times than previously possible. Expensive, self-consinstent-field optimizations are avoided and normal integration time steps of regular, direct Born-Oppenheimer molecular dynamics can be used. Linear scaling electronic structure theory is presented using a graph-based approach that is ideal for parallel calculations on hybrid computer platforms. For the first time, quantum based Born-Oppenheimer molecular dynamics simulation is becoming a practically feasible approach in simulations of +100,000 atoms-representing a competitive alternative to classical polarizable force field methods. In collaboration with: Anders Niklasson, Los Alamos National Laboratory.

Preserving correlations between trajectories for efficient path sampling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gingrich, Todd R.; Geissler, Phillip L.; Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720

2015-06-21

Importance sampling of trajectories has proved a uniquely successful strategy for exploring rare dynamical behaviors of complex systems in an unbiased way. Carrying out this sampling, however, requires an ability to propose changes to dynamical pathways that are substantial, yet sufficiently modest to obtain reasonable acceptance rates. Satisfying this requirement becomes very challenging in the case of long trajectories, due to the characteristic divergences of chaotic dynamics. Here, we examine schemes for addressing this problem, which engineer correlation between a trial trajectory and its reference path, for instance using artificial forces. Our analysis is facilitated by a modern perspective onmore » Markov chain Monte Carlo sampling, inspired by non-equilibrium statistical mechanics, which clarifies the types of sampling strategies that can scale to long trajectories. Viewed in this light, the most promising such strategy guides a trial trajectory by manipulating the sequence of random numbers that advance its stochastic time evolution, as done in a handful of existing methods. In cases where this “noise guidance” synchronizes trajectories effectively, as the Glauber dynamics of a two-dimensional Ising model, we show that efficient path sampling can be achieved for even very long trajectories.« less

Electron-impact-ionization dynamics of S F6

NASA Astrophysics Data System (ADS)

Bull, James N.; Lee, Jason W. L.; Vallance, Claire

2017-10-01

A detailed understanding of the dissociative electron ionization dynamics of S F6 is important in the modeling and tuning of dry-etching plasmas used in the semiconductor manufacture industry. This paper reports a crossed-beam electron ionization velocity-map imaging study on the dissociative ionization of cold S F6 molecules, providing complete, unbiased kinetic energy distributions for all significant product ions. Analysis of these distributions suggests that fragmentation following single ionization proceeds via formation of S F5 + or S F3 + ions that then dissociate in a statistical manner through loss of F atoms or F2, until most internal energy has been liberated. Similarly, formation of stable dications is consistent with initial formation of S F4 2 + ions, which then dissociate on a longer time scale. These data allow a comparison between electron ionization and photoionization dynamics, revealing similar dynamical behavior. In parallel with the ion kinetic energy distributions, the velocity-map imaging approach provides a set of partial ionization cross sections for all detected ionic fragments over an electron energy range of 50-100 eV, providing partial cross sections for S2 +, and enables the cross sections for S F4 2 + from S F+ to be resolved.

Block-circulant matrices with circulant blocks, Weil sums, and mutually unbiased bases. II. The prime power case

DOE Office of Scientific and Technical Information (OSTI.GOV)

Combescure, Monique

2009-03-15

In our previous paper [Combescure, M., 'Circulant matrices, Gauss sums and the mutually unbiased bases. I. The prime number case', Cubo A Mathematical Journal (unpublished)] we have shown that the theory of circulant matrices allows to recover the result that there exists p+1 mutually unbiased bases in dimension p, p being an arbitrary prime number. Two orthonormal bases B, B{sup '} of C{sup d} are said mutually unbiased if for all b(set-membership sign)B, for all b{sup '}(set-membership sign)B{sup '} one has that |b{center_dot}b{sup '}|=1/{radical}(d) (b{center_dot}b{sup '} Hermitian scalar product in C{sup d}). In this paper we show that the theorymore » of block-circulant matrices with circulant blocks allows to show very simply the known result that if d=p{sup n} (p a prime number and n any integer) there exists d+1 mutually unbiased bases in C{sup d}. Our result relies heavily on an idea of Klimov et al. [''Geometrical approach to the discrete Wigner function,'' J. Phys. A 39, 14471 (2006)]. As a subproduct we recover properties of quadratic Weil sums for p{>=}3, which generalizes the fact that in the prime case the quadratic Gauss sum properties follow from our results.« less

Breathing dynamics based parameter sensitivity analysis of hetero-polymeric DNA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Talukder, Srijeeta; Sen, Shrabani; Chaudhury, Pinaki, E-mail: pinakc@rediffmail.com

We study the parameter sensitivity of hetero-polymeric DNA within the purview of DNA breathing dynamics. The degree of correlation between the mean bubble size and the model parameters is estimated for this purpose for three different DNA sequences. The analysis leads us to a better understanding of the sequence dependent nature of the breathing dynamics of hetero-polymeric DNA. Out of the 14 model parameters for DNA stability in the statistical Poland-Scheraga approach, the hydrogen bond interaction ε{sub hb}(AT) for an AT base pair and the ring factor ξ turn out to be the most sensitive parameters. In addition, the stackingmore » interaction ε{sub st}(TA-TA) for an TA-TA nearest neighbor pair of base-pairs is found to be the most sensitive one among all stacking interactions. Moreover, we also establish that the nature of stacking interaction has a deciding effect on the DNA breathing dynamics, not the number of times a particular stacking interaction appears in a sequence. We show that the sensitivity analysis can be used as an effective measure to guide a stochastic optimization technique to find the kinetic rate constants related to the dynamics as opposed to the case where the rate constants are measured using the conventional unbiased way of optimization.« less

Structure and Dynamics of End-to-End Loop Formation of the Penta-Peptide Cys-Ala-Gly-Gln-Trp in Implicit Solvents

DTIC Science & Technology

2009-01-01

implicit solvents on peptide structure and dynamics , we performed extensive molecular dynamics simulations on the penta-peptide Cys-Ala-Gly-Gln-Trp. Two...end-to-end distances and dihedral angles obtained from molecular dynamics simulations with implicit solvent models were in a good agreement with those...to maintain the temperature of the systems. Introduction Molecular dynamics (MD) simulation techniques are widely used to study structure and

Nature's inordinate fondness for metabolic enzymes: why metabolic enzyme loci are so frequently targets of selection.

PubMed

Marden, James H

2013-12-01

Metabolic enzyme loci were some of the first genes accessible for molecular evolution and ecology research. New technologies now make the whole genome, transcriptome or proteome readily accessible, allowing unbiased scans for loci exhibiting significant differences in allele frequency or expression level and associated with phenotypes and/or responses to natural selection. With surprising frequency and in many cases in proportions greater than chance relative to other genes, glycolysis and TCA cycle enzyme loci appear among the genes with significant associations in these studies. Hence, there is an ongoing need to understand the basis for fitness effects of metabolic enzyme polymorphisms. Allele-specific effects on the binding affinity and catalytic rate of individual enzymes are well known, but often of uncertain significance because metabolic control theory and in vivo studies indicate that many individual metabolic enzymes do not affect pathway flux rate. I review research, so far little used in evolutionary biology, showing that metabolic enzyme substrates affect signalling pathways that regulate cell and organismal biology, and that these enzymes have moonlighting functions. To date there is little knowledge of how alleles in natural populations affect these phenotypes. I discuss an example in which alleles of a TCA enzyme locus associate with differences in a signalling pathway and development, organismal performance, and ecological dynamics. Ultimately, understanding how metabolic enzyme polymorphisms map to phenotypes and fitness remains a compelling and ongoing need for gaining robust knowledge of ecological and evolutionary processes. © 2013 John Wiley & Sons Ltd.

Cooperative DNA Recognition Modulated by an Interplay between Protein-Protein Interactions and DNA-Mediated Allostery

PubMed Central

Merino, Felipe; Bouvier, Benjamin; Cojocaru, Vlad

2015-01-01

Highly specific transcriptional regulation depends on the cooperative association of transcription factors into enhanceosomes. Usually, their DNA-binding cooperativity originates from either direct interactions or DNA-mediated allostery. Here, we performed unbiased molecular simulations followed by simulations of protein-DNA unbinding and free energy profiling to study the cooperative DNA recognition by OCT4 and SOX2, key components of enhanceosomes in pluripotent cells. We found that SOX2 influences the orientation and dynamics of the DNA-bound configuration of OCT4. In addition SOX2 modifies the unbinding free energy profiles of both DNA-binding domains of OCT4, the POU specific and POU homeodomain, despite interacting directly only with the first. Thus, we demonstrate that the OCT4-SOX2 cooperativity is modulated by an interplay between protein-protein interactions and DNA-mediated allostery. Further, we estimated the change in OCT4-DNA binding free energy due to the cooperativity with SOX2, observed a good agreement with experimental measurements, and found that SOX2 affects the relative DNA-binding strength of the two OCT4 domains. Based on these findings, we propose that available interaction partners in different biological contexts modulate the DNA exploration routes of multi-domain transcription factors such as OCT4. We consider the OCT4-SOX2 cooperativity as a paradigm of how specificity of transcriptional regulation is achieved through concerted modulation of protein-DNA recognition by different types of interactions. PMID:26067358

Cooperative DNA Recognition Modulated by an Interplay between Protein-Protein Interactions and DNA-Mediated Allostery.

PubMed

Merino, Felipe; Bouvier, Benjamin; Cojocaru, Vlad

2015-06-01

Highly specific transcriptional regulation depends on the cooperative association of transcription factors into enhanceosomes. Usually, their DNA-binding cooperativity originates from either direct interactions or DNA-mediated allostery. Here, we performed unbiased molecular simulations followed by simulations of protein-DNA unbinding and free energy profiling to study the cooperative DNA recognition by OCT4 and SOX2, key components of enhanceosomes in pluripotent cells. We found that SOX2 influences the orientation and dynamics of the DNA-bound configuration of OCT4. In addition SOX2 modifies the unbinding free energy profiles of both DNA-binding domains of OCT4, the POU specific and POU homeodomain, despite interacting directly only with the first. Thus, we demonstrate that the OCT4-SOX2 cooperativity is modulated by an interplay between protein-protein interactions and DNA-mediated allostery. Further, we estimated the change in OCT4-DNA binding free energy due to the cooperativity with SOX2, observed a good agreement with experimental measurements, and found that SOX2 affects the relative DNA-binding strength of the two OCT4 domains. Based on these findings, we propose that available interaction partners in different biological contexts modulate the DNA exploration routes of multi-domain transcription factors such as OCT4. We consider the OCT4-SOX2 cooperativity as a paradigm of how specificity of transcriptional regulation is achieved through concerted modulation of protein-DNA recognition by different types of interactions.

How sterol tilt regulates properties and organization of lipid membranes and membrane insertions

PubMed Central

Khelashvili, George; Harries, Daniel

2013-01-01

Serving as a crucial component of mammalian cells, cholesterol critically regulates the functions of biomembranes. This review focuses on a specific property of cholesterol and other sterols: the tilt modulus χ that quantifies the energetic cost of tilting sterol molecules inside the lipid membrane. We show how χ is involved in determining properties of cholesterol-containing membranes, and detail a novel approach to quantify its value from atomistic molecular dynamics (MD) simulations. Specifically, we link χ with other structural, thermodynamic, and mechanical properties of cholesterol-containing lipid membranes, and delineate how this useful parameter can be obtained from the sterol tilt probability distributions derived from relatively small-scale unbiased MD simulations. We demonstrate how the tilt modulus quantitatively describes the aligning field that sterol molecules create inside the phospholipid bilayers, and we relate χ to the bending rigidity of the lipid bilayer through effective tilt and splay energy contributions to the elastic deformations. Moreover, we show how χ can conveniently characterize the “condensing effect” of cholesterol on phospholipids. Finally, we demonstrate the importance of this cholesterol aligning field to the proper folding and interactions of membrane peptides. Given the relative ease of obtaining the tilt modulus from atomistic simulations, we propose that χ can be routinely used to characterize the mechanical properties of sterol/lipid bilayers, and can also serve as a required fitting parameter in multi-scaled simulations of lipid membrane models to relate the different levels of coarse-grained details. PMID:23291283

Role of water and steric constraints in the kinetics of cavity–ligand unbinding

PubMed Central

Tiwary, Pratyush; Mondal, Jagannath; Morrone, Joseph A.; Berne, B. J.

2015-01-01

A key factor influencing a drug’s efficacy is its residence time in the binding pocket of the host protein. Using atomistic computer simulation to predict this residence time and the associated dissociation process is a desirable but extremely difficult task due to the long timescales involved. This gets further complicated by the presence of biophysical factors such as steric and solvation effects. In this work, we perform molecular dynamics (MD) simulations of the unbinding of a popular prototypical hydrophobic cavity–ligand system using a metadynamics-based approach that allows direct assessment of kinetic pathways and parameters. When constrained to move in an axial manner, the unbinding time is found to be on the order of 4,000 s. In accordance with previous studies, we find that the cavity must pass through a region of sharp wetting transition manifested by sudden and high fluctuations in solvent density. When we remove the steric constraints on ligand, the unbinding happens predominantly by an alternate pathway, where the unbinding becomes 20 times faster, and the sharp wetting transition instead becomes continuous. We validate the unbinding timescales from metadynamics through a Poisson analysis, and by comparison through detailed balance to binding timescale estimates from unbiased MD. This work demonstrates that enhanced sampling can be used to perform explicit solvent MD studies at timescales previously unattainable, to our knowledge, obtaining direct and reliable pictures of the underlying physiochemical factors including free energies and rate constants. PMID:26371312

Phase behavior of a simple dipolar fluid under shear flow in an electric field.

PubMed

McWhirter, J Liam

2008-01-21

Nonequilibrium molecular dynamics simulations are performed on a dense simple dipolar fluid under a planar Couette shear flow. Shear generates heat, which is removed by thermostatting terms added to the equations of motion of the fluid particles. The spatial structure of simple fluids at high shear rates is known to depend strongly on the thermostatting mechanism chosen. Kinetic thermostats are either biased or unbiased: biased thermostats neglect the existence of secondary flows that appear at high shear rates superimposed upon the linear velocity profile of the fluid. Simulations that employ a biased thermostat produce a string phase where particles align in strings with hexagonal symmetry along the direction of the flow. This phase is known to be a simulation artifact of biased thermostatting, and has not been observed by experiments on colloidal suspensions under shear flow. In this paper, we investigate the possibility of using a suitably directed electric field, which is coupled to the dipole moments of the fluid particles, to stabilize the string phase. We explore several thermostatting mechanisms where either the kinetic or configurational fluid degrees of freedom are thermostated. Some of these mechanisms do not yield a string phase, but rather a shear-thickening phase; in this case, we find the influence of the dipolar interactions and external field on the packing structure, and in turn their influence on the shear viscosity at the onset of this shear-thickening regime.

Enhanced Conformational Sampling of N-Glycans in Solution with Replica State Exchange Metadynamics.

PubMed

Galvelis, Raimondas; Re, Suyong; Sugita, Yuji

2017-05-09

Molecular dynamics (MD) simulation of a N-glycan in solution is challenging because of high-energy barriers of the glycosidic linkages, functional group rotational barriers, and numerous intra- and intermolecular hydrogen bonds. In this study, we apply different enhanced conformational sampling approaches, namely, metadynamics (MTD), the replica-exchange MD (REMD), and the recently proposed replica state exchange MTD (RSE-MTD), to a N-glycan in solution and compare the conformational sampling efficiencies of the approaches. MTD helps to cross the high-energy barrier along the ω angle by utilizing a bias potential, but it cannot enhance sampling of the other degrees of freedom. REMD ensures moderate-energy barrier crossings by exchanging temperatures between replicas, while it hardly crosses the barriers along ω. In contrast, RSE-MTD succeeds to cross the high-energy barrier along ω as well as to enhance sampling of the other degrees of freedom. We tested two RSE-MTD schemes: in one scheme, 64 replicas were simulated with the bias potential along ω at different temperatures, while simulations of four replicas were performed with the bias potentials for different CVs at 300 K. In both schemes, one unbiased replica at 300 K was included to compute conformational properties of the glycan. The conformational sampling of the former is better than the other enhanced sampling methods, while the latter shows reasonable performance without spending large computational resources. The latter scheme is likely to be useful when a N-glycan-attached protein is simulated.

Role of water and steric constraints in the kinetics of cavity-ligand unbinding.

PubMed

Tiwary, Pratyush; Mondal, Jagannath; Morrone, Joseph A; Berne, B J

2015-09-29

A key factor influencing a drug's efficacy is its residence time in the binding pocket of the host protein. Using atomistic computer simulation to predict this residence time and the associated dissociation process is a desirable but extremely difficult task due to the long timescales involved. This gets further complicated by the presence of biophysical factors such as steric and solvation effects. In this work, we perform molecular dynamics (MD) simulations of the unbinding of a popular prototypical hydrophobic cavity-ligand system using a metadynamics-based approach that allows direct assessment of kinetic pathways and parameters. When constrained to move in an axial manner, the unbinding time is found to be on the order of 4,000 s. In accordance with previous studies, we find that the cavity must pass through a region of sharp wetting transition manifested by sudden and high fluctuations in solvent density. When we remove the steric constraints on ligand, the unbinding happens predominantly by an alternate pathway, where the unbinding becomes 20 times faster, and the sharp wetting transition instead becomes continuous. We validate the unbinding timescales from metadynamics through a Poisson analysis, and by comparison through detailed balance to binding timescale estimates from unbiased MD. This work demonstrates that enhanced sampling can be used to perform explicit solvent MD studies at timescales previously unattainable, to our knowledge, obtaining direct and reliable pictures of the underlying physiochemical factors including free energies and rate constants.

Insight into the Li2CO3-K2CO3 eutectic mixture from classical molecular dynamics: Thermodynamics, structure, and dynamics

NASA Astrophysics Data System (ADS)

Corradini, Dario; Coudert, François-Xavier; Vuilleumier, Rodolphe

2016-03-01

We use molecular dynamics simulations to study the thermodynamics, structure, and dynamics of the Li2CO3-K2CO3 (62:38 mol. %) eutectic mixture. We present a new classical non-polarizable force field for this molten salt mixture, optimized using experimental and first principles molecular dynamics simulations data as reference. This simple force field allows efficient molecular simulations of phenomena at long time scales. We use this optimized force field to describe the behavior of the eutectic mixture in the 900-1100 K temperature range, at pressures between 0 and 5 GPa. After studying the equation of state in these thermodynamic conditions, we present molecular insight into the structure and dynamics of the melt. In particular, we present an analysis of the temperature and pressure dependence of the eutectic mixture's self-diffusion coefficients, viscosity, and ionic conductivity.

Insight into the Li2CO3-K2CO3 eutectic mixture from classical molecular dynamics: Thermodynamics, structure, and dynamics.

PubMed

Corradini, Dario; Coudert, François-Xavier; Vuilleumier, Rodolphe

2016-03-14

We use molecular dynamics simulations to study the thermodynamics, structure, and dynamics of the Li2CO3-K2CO3 (62:38 mol. %) eutectic mixture. We present a new classical non-polarizable force field for this molten salt mixture, optimized using experimental and first principles molecular dynamics simulations data as reference. This simple force field allows efficient molecular simulations of phenomena at long time scales. We use this optimized force field to describe the behavior of the eutectic mixture in the 900-1100 K temperature range, at pressures between 0 and 5 GPa. After studying the equation of state in these thermodynamic conditions, we present molecular insight into the structure and dynamics of the melt. In particular, we present an analysis of the temperature and pressure dependence of the eutectic mixture's self-diffusion coefficients, viscosity, and ionic conductivity.

Discovery of a Chemical Probe Bisamide (CCT251236): An Orally Bioavailable Efficacious Pirin Ligand from a Heat Shock Transcription Factor 1 (HSF1) Phenotypic Screen

PubMed Central

2016-01-01

Phenotypic screens, which focus on measuring and quantifying discrete cellular changes rather than affinity for individual recombinant proteins, have recently attracted renewed interest as an efficient strategy for drug discovery. In this article, we describe the discovery of a new chemical probe, bisamide (CCT251236), identified using an unbiased phenotypic screen to detect inhibitors of the HSF1 stress pathway. The chemical probe is orally bioavailable and displays efficacy in a human ovarian carcinoma xenograft model. By developing cell-based SAR and using chemical proteomics, we identified pirin as a high affinity molecular target, which was confirmed by SPR and crystallography. PMID:28004573

FOREST unbiased Galactic plane imaging survey with the Nobeyama 45 m telescope (FUGIN). I. Project overview and initial results

NASA Astrophysics Data System (ADS)

Umemoto, Tomofumi; Minamidani, Tetsuhiro; Kuno, Nario; Fujita, Shinji; Matsuo, Mitsuhiro; Nishimura, Atsushi; Torii, Kazufumi; Tosaki, Tomoka; Kohno, Mikito; Kuriki, Mika; Tsuda, Yuya; Hirota, Akihiko; Ohashi, Satoshi; Yamagishi, Mitsuyoshi; Handa, Toshihiro; Nakanishi, Hiroyuki; Omodaka, Toshihiro; Koide, Nagito; Matsumoto, Naoko; Onishi, Toshikazu; Tokuda, Kazuki; Seta, Masumichi; Kobayashi, Yukinori; Tachihara, Kengo; Sano, Hidetoshi; Hattori, Yusuke; Onodera, Sachiko; Oasa, Yumiko; Kamegai, Kazuhisa; Tsuboi, Masato; Sofue, Yoshiaki; Higuchi, Aya E.; Chibueze, James O.; Mizuno, Norikazu; Honma, Mareki; Muller, Erik; Inoue, Tsuyoshi; Morokuma-Matsui, Kana; Shinnaga, Hiroko; Ozawa, Takeaki; Takahashi, Ryo; Yoshiike, Satoshi; Costes, Jean; Kuwahara, Sho

2017-10-01

The FUGIN project is one of legacy projects using a new multi-beam FOREST (four-beam receiver system on the 45 m telescope). This project aims to simultaneously investigate the distribution, kinematics, and physical properties of both diffuse and dense molecular gases in the Galaxy by observing 12CO, 13CO, and C18O J = 1-0 lines simultaneously. Mapping regions are parts of the first quadrant (10° ≤ l ≤ 50°, |b| ≤ 1°) and the third quadrant (198° ≤ l ≤ 236°, |b| ≤ 1°) of the Galaxy, where spiral arms, bar structure, and the molecular gas ring are included. This survey achieves the highest angular resolution to date (˜20″) for the Galactic plane survey in the CO J = 1-0 lines, which makes it possible to find dense clumps located farther away than the previous surveys. FUGIN will provide us an invaluable dataset for investigating the physics of the Galactic interstellar medium (ISM), particularly the evolution of interstellar gas covering galactic-scale structures to the internal structures of giant molecular clouds, such as small filaments/clumps/cores. We present an overview of the FUGIN project, the observation plan and initial results. These results reveal wide-field and detailed structures of molecular clouds, such as entangled filaments that have not been obvious in previous surveys, and large-scale kinematics of molecular gas, such as spiral arms.

Nonlinear price impact from linear models

NASA Astrophysics Data System (ADS)

Patzelt, Felix; Bouchaud, Jean-Philippe

2017-12-01

The impact of trades on asset prices is a crucial aspect of market dynamics for academics, regulators, and practitioners alike. Recently, universal and highly nonlinear master curves were observed for price impacts aggregated on all intra-day scales (Patzelt and Bouchaud 2017 arXiv:1706.04163). Here we investigate how well these curves, their scaling, and the underlying return dynamics are captured by linear ‘propagator’ models. We find that the classification of trades as price-changing versus non-price-changing can explain the price impact nonlinearities and short-term return dynamics to a very high degree. The explanatory power provided by the change indicator in addition to the order sign history increases with increasing tick size. To obtain these results, several long-standing technical issues for model calibration and testing are addressed. We present new spectral estimators for two- and three-point cross-correlations, removing the need for previously used approximations. We also show when calibration is unbiased and how to accurately reveal previously overlooked biases. Therefore, our results contribute significantly to understanding both recent empirical results and the properties of a popular class of impact models.

How Dynamic Visualization Technology Can Support Molecular Reasoning

ERIC Educational Resources Information Center

Levy, Dalit

2013-01-01

This paper reports the results of a study aimed at exploring the advantages of dynamic visualization for the development of better understanding of molecular processes. We designed a technology-enhanced curriculum module in which high school chemistry students conduct virtual experiments with dynamic molecular visualizations of solid, liquid, and…

Unbiased Estimates of Variance Components with Bootstrap Procedures

ERIC Educational Resources Information Center

Brennan, Robert L.

2007-01-01

This article provides general procedures for obtaining unbiased estimates of variance components for any random-model balanced design under any bootstrap sampling plan, with the focus on designs of the type typically used in generalizability theory. The results reported here are particularly helpful when the bootstrap is used to estimate standard…

Definition and Measurement of Selection Bias: From Constant Ratio to Constant Difference

ERIC Educational Resources Information Center

Cahan, Sorel; Gamliel, Eyal

2006-01-01

Despite its intuitive appeal and popularity, Thorndike's constant ratio (CR) model for unbiased selection is inherently inconsistent in "n"-free selection. Satisfaction of the condition for unbiased selection, when formulated in terms of success/acceptance probabilities, usually precludes satisfaction by the converse probabilities of…

Spectroscopic observation of Gaia17dht and Gaia17diu by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Fraser, M.; Dyrbye, S.; Cappella, E.

2017-12-01

The Nordic Optical Telescope (NOT) Unbiased Transient Survey (NUTS; ATel #8992) reports the spectroscopic classification of Gaia17dht/SN2017izz and Gaia17diu/SN2017jdb (in host galaxies SDSS J145121.24+283521.6 and LEDA 2753585 respectively).

Statistics as Unbiased Estimators: Exploring the Teaching of Standard Deviation

ERIC Educational Resources Information Center

Wasserman, Nicholas H.; Casey, Stephanie; Champion, Joe; Huey, Maryann

2017-01-01

This manuscript presents findings from a study about the knowledge for and planned teaching of standard deviation. We investigate how understanding variance as an unbiased (inferential) estimator--not just a descriptive statistic for the variation (spread) in data--is related to teachers' instruction regarding standard deviation, particularly…

Generalized approach for using unbiased symmetric metrics with negative values: normalized mean bias factor and normalized mean absolute error factor

EPA Science Inventory

Unbiased symmetric metrics provide a useful measure to quickly compare two datasets, with similar interpretations for both under and overestimations. Two examples include the normalized mean bias factor and normalized mean absolute error factor. However, the original formulations...

Convergence and reproducibility in molecular dynamics simulations of the DNA duplex d(GCACGAACGAACGAACGC).

PubMed

Galindo-Murillo, Rodrigo; Roe, Daniel R; Cheatham, Thomas E

2015-05-01

The structure and dynamics of DNA are critically related to its function. Molecular dynamics simulations augment experiment by providing detailed information about the atomic motions. However, to date the simulations have not been long enough for convergence of the dynamics and structural properties of DNA. Molecular dynamics simulations performed with AMBER using the ff99SB force field with the parmbsc0 modifications, including ensembles of independent simulations, were compared to long timescale molecular dynamics performed with the specialized Anton MD engine on the B-DNA structure d(GCACGAACGAACGAACGC). To assess convergence, the decay of the average RMSD values over longer and longer time intervals was evaluated in addition to assessing convergence of the dynamics via the Kullback-Leibler divergence of principal component projection histograms. These molecular dynamics simulations-including one of the longest simulations of DNA published to date at ~44μs-surprisingly suggest that the structure and dynamics of the DNA helix, neglecting the terminal base pairs, are essentially fully converged on the ~1-5μs timescale. We can now reproducibly converge the structure and dynamics of B-DNA helices, omitting the terminal base pairs, on the μs time scale with both the AMBER and CHARMM C36 nucleic acid force fields. Results from independent ensembles of simulations starting from different initial conditions, when aggregated, match the results from long timescale simulations on the specialized Anton MD engine. With access to large-scale GPU resources or the specialized MD engine "Anton" it is possible for a variety of molecular systems to reproducibly and reliably converge the conformational ensemble of sampled structures. This article is part of a Special Issue entitled: Recent developments of molecular dynamics. Copyright © 2014. Published by Elsevier B.V.

Monitoring the regulation of gene expression in a growing organ using a fluid mechanics formalism

PubMed Central

2010-01-01

Background Technological advances have enabled the accurate quantification of gene expression, even within single cell types. While transcriptome analyses are routinely performed, most experimental designs only provide snapshots of gene expression. Molecular mechanisms underlying cell fate or positional signalling have been revealed through these discontinuous datasets. However, in developing multicellular structures, temporal and spatial cues, known to directly influence transcriptional networks, get entangled as the cells are displaced and expand. Access to an unbiased view of the spatiotemporal regulation of gene expression occurring during development requires a specific framework that properly quantifies the rate of change of a property in a moving and expanding element, such as a cell or an organ segment. Results We show how the rate of change in gene expression can be quantified by combining kinematics and real-time polymerase chain reaction data in a mechanistic model which considers any organ as a continuum. This framework was applied in order to assess the developmental regulation of the two reference genes Actin11 and Elongation Factor 1-β in the apex of poplar root. The growth field was determined by time-lapse photography and transcript density was obtained at high spatial resolution. The net accumulation rates of the transcripts of the two genes were found to display highly contrasted developmental profiles. Actin11 showed pulses of up and down regulation in the accelerating and decelerating parts of the growth zone while the dynamic of EF1β were much slower. This framework provides key information about gene regulation in a developing organ, such as the location, the duration and the intensity of gene induction/repression. Conclusions We demonstrated that gene expression patterns can be monitored using the continuity equation without using mutants or reporter constructions. Given the rise of imaging technologies, this framework in our view opens a new way to dissect the molecular basis of growth regulation, even in non-model species or complex structures. PMID:20202192

Impact of Water-Dilution on the Solvation Properties of the Ionic Liquid 1-Methyltriethoxy-3-ethylimidazolium Acetate for Model Biomass Molecules.

PubMed

Schutt, Timothy C; Hegde, Govind A; Bharadwaj, Vivek S; Johns, Adam J; Maupin, C Mark

2017-02-02

Many studies have suggested that the processing of lignocellulosic biomass could provide a renewable feedstock to supplant much of the current demand on petroleum sources. Currently, alkyl imidazolium-based ionic liquids (ILs) have shown considerable promise in the pretreatment, solvation, and hydrolysis of lignocellulosic materials although their high cost and unfavorable viscosity has limited their widespread use. Functionalizing these ILs with an oligo(ethoxy) tail has previously been shown through experiment to decrease the IL's viscosity resulting in enhanced mass transport characteristics, in addition to other favorable traits including decreased inhibition of some enzymes. Additionally, the use of cosolvents to mitigate the cost and unfavorable traits of ILs is an area of growing interest with particular attention on water as the presence of water in biomass processes is inevitable. Through the use of biased and unbiased molecular dynamics (MD) simulations, this study provides a molecular-level perspective of the various solvent-solvent and solvent-solute interactions in binary mixtures of water and 1-methyltriethoxy-3-ethylimidazolium acetate ([Me-(OEt) 3 -Et-IM + ] [OAc - ]) in the presence of model cellulose compounds (i.e., glucose and cellobiose). It is observed that at ∼75% w/w IL and water a transition in the nanostructure of the solvent occurs between water-like and IL-like solvation characteristics. It is shown that H-bonding interactions between the anion and water are a major driving force that significantly impacts the solvent properties of the IL as well as conformational preferences of the cellulosic model compound. In addition, it is found that the oligo(ethoxy) cation tail is responsible for the reduction in the propensity for tail aggregation as compared to alkyl tails of similar length, which, combined with increased ionic shielding, results in increased diffusion and enhanced water-like solvation characteristics.

Unbiased millimeter-wave line surveys of TW Hya and V4046 Sgr: The enhanced C{sub 2}H and CN abundances of evolved protoplanetary disks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kastner, Joel H.; Punzi, Kristina; Hily-Blant, Pierre

2014-09-20

We have conducted the first comprehensive millimeter-wave molecular emission line surveys of the evolved circumstellar disks orbiting the nearby, roughly solar-mass, pre-main-sequence (T Tauri) stars, TW Hya (D = 54 pc) and V4046 Sgr AB (D = 73 pc). Both disks are known to retain significant residual gaseous components despite the advanced ages of their host stars (∼8 Myr and ∼21 Myr, respectively). Our unbiased broadband radio spectral surveys of the TW Hya and V4046 Sgr disks were performed with the Atacama Pathfinder Experiment 12 m telescope, and are intended to yield a complete census of the bright molecular emissionmore » lines in the range 275-357 GHz (1.1-0.85 mm). We find that lines of {sup 12}CO, {sup 13}CO, HCN, CN, and C{sub 2}H, all of which lie in the higher frequency (>330 GHz) range, constitute the strongest molecular emission from both disks in the spectral region surveyed. The molecule C{sub 2}H is detected here for the first time in both disks, as is CS in the TW Hya disk. The survey results also include the first measurements of the full suite of the hyperfine transitions of CN N = 3 → 2 and C{sub 2}H N = 4 → 3 in both disks. Modeling of these CN and C{sub 2}H hyperfine complexes in the spectrum of TW Hya indicates that the emission from both species is optically thick and may originate from very cold (≲10 K) disk regions. The latter result, if confirmed, would suggest the efficient production of CN and C{sub 2}H in the outer disk and/or near the disk midplane. It furthermore appears that the fractional abundances of CN and C{sub 2}H are significantly enhanced in these evolved protoplanetary disks, relative to the fractional abundances of the same molecules in the environments of deeply embedded protostars. These results, combined with previous determinations of the enhanced abundances of other species (such as HCO{sup +}) in T Tauri star disks, underscore the importance of properly accounting for high-energy (FUV and X-ray) radiation from the central T Tauri star when modeling protoplanetary disk gas chemistry and physical conditions.« less

Molecular Diagnosis of Long-QT syndrome at 10 Days of Life by Rapid Whole Genome Sequencing

PubMed Central

Priest, James R.; Ceresnak, Scott R.; Dewey, Frederick E.; Malloy-Walton, Lindsey E.; Dunn, Kyla; Grove, Megan E.; Perez, Marco V.; Maeda, Katsuhide; Dubin, Anne M.; Ashley, Euan A.

2014-01-01

Background The advent of clinical next generation sequencing is rapidly changing the landscape of rare disease medicine. Molecular diagnosis of long QT syndrome (LQTS) can impact clinical management, including risk stratification and selection of pharmacotherapy based on the type of ion channel affected, but results from current gene panel testing requires 4 to 16 weeks before return to clinicians. Objective A term female infant presented with 2:1 atrioventricular block and ventricular arrhythmias consistent with perinatal LQTS, requiring aggressive treatment including epicardial pacemaker, and cardioverter-defibrillator implantation and sympathectomy on day of life two. We sought to provide a rapid molecular diagnosis for optimization of treatment strategies. Methods We performed CLIA-certified rapid whole genome sequencing (WGS) with a speed-optimized bioinformatics platform to achieve molecular diagnosis at 10 days of life. Results We detected a known pathogenic variant in KCNH2 that was demonstrated to be paternally inherited by followup genotyping. The unbiased assessment of the entire catalog of human genes provided by whole genome sequencing revealed a maternally inherited variant of unknown significance in a novel gene. Conclusions Rapid clinical WGS provides faster and more comprehensive diagnostic information by 10 days of life than standard gene-panel testing. In selected clinical scenarios such as perinatal LQTS, rapid WGS may be able to provide more timely and clinically actionable information than a standard commercial test. PMID:24973560

Extended Lagrangian Density Functional Tight-Binding Molecular Dynamics for Molecules and Solids.

PubMed

Aradi, Bálint; Niklasson, Anders M N; Frauenheim, Thomas

2015-07-14

A computationally fast quantum mechanical molecular dynamics scheme using an extended Lagrangian density functional tight-binding formulation has been developed and implemented in the DFTB+ electronic structure program package for simulations of solids and molecular systems. The scheme combines the computational speed of self-consistent density functional tight-binding theory with the efficiency and long-term accuracy of extended Lagrangian Born-Oppenheimer molecular dynamics. For systems without self-consistent charge instabilities, only a single diagonalization or construction of the single-particle density matrix is required in each time step. The molecular dynamics simulation scheme can be applied to a broad range of problems in materials science, chemistry, and biology.

Easy GROMACS: A Graphical User Interface for GROMACS Molecular Dynamics Simulation Package

NASA Astrophysics Data System (ADS)

Dizkirici, Ayten; Tekpinar, Mustafa

2015-03-01

GROMACS is a widely used molecular dynamics simulation package. Since it is a command driven program, it is difficult to use this program for molecular biologists, biochemists, new graduate students and undergraduate researchers who are interested in molecular dynamics simulations. To alleviate the problem for those researchers, we wrote a graphical user interface that simplifies protein preparation for a classical molecular dynamics simulation. Our program can work with various GROMACS versions and it can perform essential analyses of GROMACS trajectories as well as protein preparation. We named our open source program `Easy GROMACS'. Easy GROMACS can give researchers more time for scientific research instead of dealing with technical intricacies.

Advanced Polymer Network Structures

DTIC Science & Technology

2016-02-01

double networks in a single step was identified from coarse-grained molecular dynamics simulations of polymer solvents bearing rigid side chains dissolved...in a polymer network. Coarse-grained molecular dynamics simulations also explored the mechanical behavior of traditional double networks and...DRI), polymer networks, polymer gels, molecular dynamics simulations , double networks 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF

Molecular Biodynamers: Dynamic Covalent Analogues of Biopolymers

PubMed Central

2017-01-01

Conspectus Constitutional dynamic chemistry (CDC) features the use of reversible linkages at both molecular and supramolecular levels, including reversible covalent bonds (dynamic covalent chemistry, DCC) and noncovalent interactions (dynamic noncovalent chemistry, DNCC). Due to its inherent reversibility and stimuli-responsiveness, CDC has been widely utilized as a powerful tool for the screening of bioactive compounds, the exploitation of receptors or substrates driven by molecular recognition, and the fabrication of constitutionally dynamic materials. Implementation of CDC in biopolymer science leads to the generation of constitutionally dynamic analogues of biopolymers, biodynamers, at the molecular level (molecular biodynamers) through DCC or at the supramolecular level (supramolecular biodynamers) via DNCC. Therefore, biodynamers are prepared by reversible covalent polymerization or noncovalent polyassociation of biorelevant monomers. In particular, molecular biodynamers, biodynamers of the covalent type whose monomeric units are connected by reversible covalent bonds, are generated by reversible polymerization of bio-based monomers and can be seen as a combination of biopolymers with DCC. Owing to the reversible covalent bonds used in DCC, molecular biodynamers can undergo continuous and spontaneous constitutional modifications via incorporation/decorporation and exchange of biorelevant monomers in response to internal or external stimuli. As a result, they behave as adaptive materials with novel properties, such as self-healing, stimuli-responsiveness, and tunable mechanical and optical character. More specifically, molecular biodynamers combine the biorelevant characters (e.g., biocompatibility, biodegradability, biofunctionality) of bioactive monomers with the dynamic features of reversible covalent bonds (e.g., changeable, tunable, controllable, self-healing, and stimuli-responsive capacities), to realize synergistic properties in one system. In addition, molecular biodynamers are commonly produced in aqueous media under mild or even physiological conditions to suit their biorelated applications. In contrast to static biopolymers emphasizing structural stability and unity by using irreversible covalent bonds, molecular biodynamers are seeking relative structural adaptability and diversity through the formation of reversible covalent bonds. Based on these considerations, molecular biodynamers are capable of reorganizing their monomers, generating, identifying, and amplifying the fittest structures in response to environmental factors. Hence, molecular biodynamers have received considerable research attention over the past decades. Accordingly, the construction of molecular biodynamers through equilibrium polymerization of nucleobase-, carbohydrate- or amino-acid-based monomers can lead to the fabrication of dynamic analogues of nucleic acids (DyNAs), polysaccharides (glycodynamers), or proteins (dynamic proteoids), respectively. In this Account, we summarize recent advances in developing different types of molecular biodynamers as structural or functional biomimetics of biopolymers, including DyNAs, glycodynamers, and dynamic proteoids. We introduce how chemists utilize various reversible reactions to generate molecular biodynamers with specific sequences and well-ordered structures in aqueous medium. We also discuss and list their potential applications in various research fields, such as drug delivery, drug discovery, gene sensing, cancer diagnosis, and treatment. PMID:28169527

Mutually unbiased bases in six dimensions: The four most distant bases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raynal, Philippe; Lue Xin; Englert, Berthold-Georg

2011-06-15

We consider the average distance between four bases in six dimensions. The distance between two orthonormal bases vanishes when the bases are the same, and the distance reaches its maximal value of unity when the bases are unbiased. We perform a numerical search for the maximum average distance and find it to be strictly smaller than unity. This is strong evidence that no four mutually unbiased bases exist in six dimensions. We also provide a two-parameter family of three bases which, together with the canonical basis, reach the numerically found maximum of the average distance, and we conduct a detailedmore » study of the structure of the extremal set of bases.« less

Extreme Mean and Its Applications

NASA Technical Reports Server (NTRS)

Swaroop, R.; Brownlow, J. D.

1979-01-01

Extreme value statistics obtained from normally distributed data are considered. An extreme mean is defined as the mean of p-th probability truncated normal distribution. An unbiased estimate of this extreme mean and its large sample distribution are derived. The distribution of this estimate even for very large samples is found to be nonnormal. Further, as the sample size increases, the variance of the unbiased estimate converges to the Cramer-Rao lower bound. The computer program used to obtain the density and distribution functions of the standardized unbiased estimate, and the confidence intervals of the extreme mean for any data are included for ready application. An example is included to demonstrate the usefulness of extreme mean application.

Statistical inference on censored data for targeted clinical trials under enrichment design.

PubMed

Chen, Chen-Fang; Lin, Jr-Rung; Liu, Jen-Pei

2013-01-01

For the traditional clinical trials, inclusion and exclusion criteria are usually based on some clinical endpoints; the genetic or genomic variability of the trial participants are not totally utilized in the criteria. After completion of the human genome project, the disease targets at the molecular level can be identified and can be utilized for the treatment of diseases. However, the accuracy of diagnostic devices for identification of such molecular targets is usually not perfect. Some of the patients enrolled in targeted clinical trials with a positive result for the molecular target might not have the specific molecular targets. As a result, the treatment effect may be underestimated in the patient population truly with the molecular target. To resolve this issue, under the exponential distribution, we develop inferential procedures for the treatment effects of the targeted drug based on the censored endpoints in the patients truly with the molecular targets. Under an enrichment design, we propose using the expectation-maximization algorithm in conjunction with the bootstrap technique to incorporate the inaccuracy of the diagnostic device for detection of the molecular targets on the inference of the treatment effects. A simulation study was conducted to empirically investigate the performance of the proposed methods. Simulation results demonstrate that under the exponential distribution, the proposed estimator is nearly unbiased with adequate precision, and the confidence interval can provide adequate coverage probability. In addition, the proposed testing procedure can adequately control the size with sufficient power. On the other hand, when the proportional hazard assumption is violated, additional simulation studies show that the type I error rate is not controlled at the nominal level and is an increasing function of the positive predictive value. A numerical example illustrates the proposed procedures. Copyright © 2013 John Wiley & Sons, Ltd.

Molecular dynamics simulations of large macromolecular complexes.

PubMed

Perilla, Juan R; Goh, Boon Chong; Cassidy, C Keith; Liu, Bo; Bernardi, Rafael C; Rudack, Till; Yu, Hang; Wu, Zhe; Schulten, Klaus

2015-04-01

Connecting dynamics to structural data from diverse experimental sources, molecular dynamics simulations permit the exploration of biological phenomena in unparalleled detail. Advances in simulations are moving the atomic resolution descriptions of biological systems into the million-to-billion atom regime, in which numerous cell functions reside. In this opinion, we review the progress, driven by large-scale molecular dynamics simulations, in the study of viruses, ribosomes, bioenergetic systems, and other diverse applications. These examples highlight the utility of molecular dynamics simulations in the critical task of relating atomic detail to the function of supramolecular complexes, a task that cannot be achieved by smaller-scale simulations or existing experimental approaches alone. Copyright © 2015 Elsevier Ltd. All rights reserved.

Generalized Green's function molecular dynamics for canonical ensemble simulations

NASA Astrophysics Data System (ADS)

Coluci, V. R.; Dantas, S. O.; Tewary, V. K.

2018-05-01

The need of small integration time steps (˜1 fs) in conventional molecular dynamics simulations is an important issue that inhibits the study of physical, chemical, and biological systems in real timescales. Additionally, to simulate those systems in contact with a thermal bath, thermostating techniques are usually applied. In this work, we generalize the Green's function molecular dynamics technique to allow simulations within the canonical ensemble. By applying this technique to one-dimensional systems, we were able to correctly describe important thermodynamic properties such as the temperature fluctuations, the temperature distribution, and the velocity autocorrelation function. We show that the proposed technique also allows the use of time steps one order of magnitude larger than those typically used in conventional molecular dynamics simulations. We expect that this technique can be used in long-timescale molecular dynamics simulations.

A GPU-accelerated immersive audio-visual framework for interaction with molecular dynamics using consumer depth sensors.

PubMed

Glowacki, David R; O'Connor, Michael; Calabró, Gaetano; Price, James; Tew, Philip; Mitchell, Thomas; Hyde, Joseph; Tew, David P; Coughtrie, David J; McIntosh-Smith, Simon

2014-01-01

With advances in computational power, the rapidly growing role of computational/simulation methodologies in the physical sciences, and the development of new human-computer interaction technologies, the field of interactive molecular dynamics seems destined to expand. In this paper, we describe and benchmark the software algorithms and hardware setup for carrying out interactive molecular dynamics utilizing an array of consumer depth sensors. The system works by interpreting the human form as an energy landscape, and superimposing this landscape on a molecular dynamics simulation to chaperone the motion of the simulated atoms, affecting both graphics and sonified simulation data. GPU acceleration has been key to achieving our target of 60 frames per second (FPS), giving an extremely fluid interactive experience. GPU acceleration has also allowed us to scale the system for use in immersive 360° spaces with an array of up to ten depth sensors, allowing several users to simultaneously chaperone the dynamics. The flexibility of our platform for carrying out molecular dynamics simulations has been considerably enhanced by wrappers that facilitate fast communication with a portable selection of GPU-accelerated molecular force evaluation routines. In this paper, we describe a 360° atmospheric molecular dynamics simulation we have run in a chemistry/physics education context. We also describe initial tests in which users have been able to chaperone the dynamics of 10-alanine peptide embedded in an explicit water solvent. Using this system, both expert and novice users have been able to accelerate peptide rare event dynamics by 3-4 orders of magnitude.

Molecular Dynamics Simulations and XAFS (MD-XAFS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schenter, Gregory K.; Fulton, John L.

2017-01-20

MD-XAFS (Molecular Dynamics X-ray Adsorption Fine Structure) makes the connection between simulation techniques that generate an ensemble of molecular configurations and the direct signal observed from X-ray measurement.

Coupling unbiased mutagenesis to high-throughput DNA sequencing uncovers functional domains in the Ndc80 kinetochore protein of Saccharomyces cerevisiae.

PubMed

Tien, Jerry F; Fong, Kimberly K; Umbreit, Neil T; Payen, Celia; Zelter, Alex; Asbury, Charles L; Dunham, Maitreya J; Davis, Trisha N

2013-09-01

During mitosis, kinetochores physically link chromosomes to the dynamic ends of spindle microtubules. This linkage depends on the Ndc80 complex, a conserved and essential microtubule-binding component of the kinetochore. As a member of the complex, the Ndc80 protein forms microtubule attachments through a calponin homology domain. Ndc80 is also required for recruiting other components to the kinetochore and responding to mitotic regulatory signals. While the calponin homology domain has been the focus of biochemical and structural characterization, the function of the remainder of Ndc80 is poorly understood. Here, we utilized a new approach that couples high-throughput sequencing to a saturating linker-scanning mutagenesis screen in Saccharomyces cerevisiae. We identified domains in previously uncharacterized regions of Ndc80 that are essential for its function in vivo. We show that a helical hairpin adjacent to the calponin homology domain influences microtubule binding by the complex. Furthermore, a mutation in this hairpin abolishes the ability of the Dam1 complex to strengthen microtubule attachments made by the Ndc80 complex. Finally, we defined a C-terminal segment of Ndc80 required for tetramerization of the Ndc80 complex in vivo. This unbiased mutagenesis approach can be generally applied to genes in S. cerevisiae to identify functional properties and domains.

Estimating Unbiased Treatment Effects in Education Using a Regression Discontinuity Design

ERIC Educational Resources Information Center

Smith, William C.

2014-01-01

The ability of regression discontinuity (RD) designs to provide an unbiased treatment effect while overcoming the ethical concerns plagued by Random Control Trials (RCTs) make it a valuable and useful approach in education evaluation. RD is the only explicitly recognized quasi-experimental approach identified by the Institute of Education…

Molecular dynamics simulations of collision-induced absorption: Implementation in LAMMPS

NASA Astrophysics Data System (ADS)

Fakhardji, W.; Gustafsson, M.

2017-02-01

We pursue simulations of collision-induced absorption in a mixture of argon and xenon gas at room temperature by means of classical molecular dynamics. The established theoretical approach (Hartmann et al. 2011 J. Chem. Phys. 134 094316) is implemented with the molecular dynamics package LAMMPS. The bound state features in the absorption spectrum are well reproduced with the molecular dynamics simulation in comparison with a laboratory measurement. The magnitude of the computed absorption, however, is underestimated in a large part of the spectrum. We suggest some aspects of the simulation that could be improved.

Molecular System for the Division of Self-Propelled Oil Droplets by Component Feeding.

PubMed

Banno, Taisuke; Toyota, Taro

2015-06-30

Unique dynamics using inanimate molecular assemblies have drawn a great amount of attention for demonstrating prebiomimetic molecular systems. For the construction of an organized logic combining two fundamental dynamics of life, we demonstrate here a molecular system that exhibits both division and self-propelled motion using oil droplets. The key molecule of this molecular system is a novel cationic surfactant containing a five-membered acetal moiety, and the molecular system can feed the self-propelled oil droplet composed of a benzaldehyde derivative and an alkanol. The division dynamics of the self-propelled oil droplets were observed through the hydrolysis of the cationic surfactant in bulk solution. The mechanism of the current dynamics is argued to be based on the supply of "fresh" oil components in the moving oil droplets, which is induced by the Marangoni instability. We consider this molecular system to be a prototype of self-reproducing inanimate molecular assembly exhibiting self-propelled motion.

Identification of promising DNA GyrB inhibitors for Tuberculosis using pharmacophore-based virtual screening, molecular docking and molecular dynamics studies.

PubMed

Islam, Md Ataul; Pillay, Tahir S

2017-08-01

In this study, we searched for potential DNA GyrB inhibitors using pharmacophore-based virtual screening followed by molecular docking and molecular dynamics simulation approaches. For this purpose, a set of 248 DNA GyrB inhibitors was collected from the literature and a well-validated pharmacophore model was generated. The best pharmacophore model explained that two each of hydrogen bond acceptors and hydrophobicity regions were critical for inhibition of DNA GyrB. Good statistical results of the pharmacophore model indicated that the model was robust in nature. Virtual screening of molecular databases revealed three molecules as potential antimycobacterial agents. The final screened promising compounds were evaluated in molecular docking and molecular dynamics simulation studies. In the molecular dynamics studies, RMSD and RMSF values undoubtedly explained that the screened compounds formed stable complexes with DNA GyrB. Therefore, it can be concluded that the compounds identified may have potential for the treatment of TB. © 2017 John Wiley & Sons A/S.

Cluster Analysis Identifies 3 Phenotypes within Allergic Asthma.

PubMed

Sendín-Hernández, María Paz; Ávila-Zarza, Carmelo; Sanz, Catalina; García-Sánchez, Asunción; Marcos-Vadillo, Elena; Muñoz-Bellido, Francisco J; Laffond, Elena; Domingo, Christian; Isidoro-García, María; Dávila, Ignacio

Asthma is a heterogeneous chronic disease with different clinical expressions and responses to treatment. In recent years, several unbiased approaches based on clinical, physiological, and molecular features have described several phenotypes of asthma. Some phenotypes are allergic, but little is known about whether these phenotypes can be further subdivided. We aimed to phenotype patients with allergic asthma using an unbiased approach based on multivariate classification techniques (unsupervised hierarchical cluster analysis). From a total of 54 variables of 225 patients with well-characterized allergic asthma diagnosed following American Thoracic Society (ATS) recommendation, positive skin prick test to aeroallergens, and concordant symptoms, we finally selected 19 variables by multiple correspondence analyses. Then a cluster analysis was performed. Three groups were identified. Cluster 1 was constituted by patients with intermittent or mild persistent asthma, without family antecedents of atopy, asthma, or rhinitis. This group showed the lowest total IgE levels. Cluster 2 was constituted by patients with mild asthma with a family history of atopy, asthma, or rhinitis. Total IgE levels were intermediate. Cluster 3 included patients with moderate or severe persistent asthma that needed treatment with corticosteroids and long-acting β-agonists. This group showed the highest total IgE levels. We identified 3 phenotypes of allergic asthma in our population. Furthermore, we described 2 phenotypes of mild atopic asthma mainly differentiated by a family history of allergy. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Express path analysis identifies a tyrosine kinase Src-centric network regulating divergent host responses to Mycobacterium tuberculosis infection.

PubMed

Karim, Ahmad Faisal; Chandra, Pallavi; Chopra, Aanchal; Siddiqui, Zaved; Bhaskar, Ashima; Singh, Amit; Kumar, Dhiraj

2011-11-18

Global gene expression profiling has emerged as a major tool in understanding complex response patterns of biological systems to perturbations. However, a lack of unbiased analytical approaches has restricted the utility of complex microarray data to gain novel system level insights. Here we report a strategy, express path analysis (EPA), that helps to establish various pathways differentially recruited to achieve specific cellular responses under contrasting environmental conditions in an unbiased manner. The analysis superimposes differentially regulated genes between contrasting environments onto the network of functional protein associations followed by a series of iterative enrichments and network analysis. To test the utility of the approach, we infected THP1 macrophage cells with a virulent Mycobacterium tuberculosis strain (H37Rv) or the attenuated non-virulent strain H37Ra as contrasting perturbations and generated the temporal global expression profiles. EPA of the results provided details of response-specific and time-dependent host molecular network perturbations. Further analysis identified tyrosine kinase Src as the major regulatory hub discriminating the responses between wild-type and attenuated Mtb infection. We were then able to verify this novel role of Src experimentally and show that Src executes its role through regulating two vital antimicrobial processes of the host cells (i.e. autophagy and acidification of phagolysosome). These results bear significant potential for developing novel anti-tuberculosis therapy. We propose that EPA could prove extremely useful in understanding complex cellular responses for a variety of perturbations, including pathogenic infections.

Fast genomic predictions via Bayesian G-BLUP and multilocus models of threshold traits including censored Gaussian data.

PubMed

Kärkkäinen, Hanni P; Sillanpää, Mikko J

2013-09-04

Because of the increased availability of genome-wide sets of molecular markers along with reduced cost of genotyping large samples of individuals, genomic estimated breeding values have become an essential resource in plant and animal breeding. Bayesian methods for breeding value estimation have proven to be accurate and efficient; however, the ever-increasing data sets are placing heavy demands on the parameter estimation algorithms. Although a commendable number of fast estimation algorithms are available for Bayesian models of continuous Gaussian traits, there is a shortage for corresponding models of discrete or censored phenotypes. In this work, we consider a threshold approach of binary, ordinal, and censored Gaussian observations for Bayesian multilocus association models and Bayesian genomic best linear unbiased prediction and present a high-speed generalized expectation maximization algorithm for parameter estimation under these models. We demonstrate our method with simulated and real data. Our example analyses suggest that the use of the extra information present in an ordered categorical or censored Gaussian data set, instead of dichotomizing the data into case-control observations, increases the accuracy of genomic breeding values predicted by Bayesian multilocus association models or by Bayesian genomic best linear unbiased prediction. Furthermore, the example analyses indicate that the correct threshold model is more accurate than the directly used Gaussian model with a censored Gaussian data, while with a binary or an ordinal data the superiority of the threshold model could not be confirmed.

Fast Genomic Predictions via Bayesian G-BLUP and Multilocus Models of Threshold Traits Including Censored Gaussian Data

PubMed Central

Kärkkäinen, Hanni P.; Sillanpää, Mikko J.

2013-01-01

Because of the increased availability of genome-wide sets of molecular markers along with reduced cost of genotyping large samples of individuals, genomic estimated breeding values have become an essential resource in plant and animal breeding. Bayesian methods for breeding value estimation have proven to be accurate and efficient; however, the ever-increasing data sets are placing heavy demands on the parameter estimation algorithms. Although a commendable number of fast estimation algorithms are available for Bayesian models of continuous Gaussian traits, there is a shortage for corresponding models of discrete or censored phenotypes. In this work, we consider a threshold approach of binary, ordinal, and censored Gaussian observations for Bayesian multilocus association models and Bayesian genomic best linear unbiased prediction and present a high-speed generalized expectation maximization algorithm for parameter estimation under these models. We demonstrate our method with simulated and real data. Our example analyses suggest that the use of the extra information present in an ordered categorical or censored Gaussian data set, instead of dichotomizing the data into case-control observations, increases the accuracy of genomic breeding values predicted by Bayesian multilocus association models or by Bayesian genomic best linear unbiased prediction. Furthermore, the example analyses indicate that the correct threshold model is more accurate than the directly used Gaussian model with a censored Gaussian data, while with a binary or an ordinal data the superiority of the threshold model could not be confirmed. PMID:23821618

Describing the silent human virome with an emphasis on giant viruses.

PubMed

Popgeorgiev, Nikolay; Temmam, Sarah; Raoult, Didier; Desnues, Christelle

2013-01-01

Viruses are the most abundant obligate intracellular entities in our body. Until recently, they were only considered to be pathogens that caused a broad array of pathologies, ranging from mild disease to deaths in the most severe cases. However, recent advances in unbiased mass sequencing techniques as well as increasing epidemiological evidence have indicated that the human body is home to diverse viral species under non-pathological conditions. Despite these studies, the description of the presumably healthy viral flora, i.e. the normal human virome, is still in its infancy regarding viral composition and dynamics. This review summarizes our current knowledge of the human virome under non-pathological conditions.

Accelerated molecular dynamics and protein conformational change: a theoretical and practical guide using a membrane embedded model neurotransmitter transporter.

PubMed

Gedeon, Patrick C; Thomas, James R; Madura, Jeffry D

2015-01-01

Molecular dynamics simulation provides a powerful and accurate method to model protein conformational change, yet timescale limitations often prevent direct assessment of the kinetic properties of interest. A large number of molecular dynamic steps are necessary for rare events to occur, which allow a system to overcome energy barriers and conformationally transition from one potential energy minimum to another. For many proteins, the energy landscape is further complicated by a multitude of potential energy wells, each separated by high free-energy barriers and each potentially representative of a functionally important protein conformation. To overcome these obstacles, accelerated molecular dynamics utilizes a robust bias potential function to simulate the transition between different potential energy minima. This straightforward approach more efficiently samples conformational space in comparison to classical molecular dynamics simulation, does not require advanced knowledge of the potential energy landscape and converges to the proper canonical distribution. Here, we review the theory behind accelerated molecular dynamics and discuss the approach in the context of modeling protein conformational change. As a practical example, we provide a detailed, step-by-step explanation of how to perform an accelerated molecular dynamics simulation using a model neurotransmitter transporter embedded in a lipid cell membrane. Changes in protein conformation of relevance to the substrate transport cycle are then examined using principle component analysis.

Comparative Investigation of Normal Modes and Molecular Dynamics of Hepatitis C NS5B Protein

NASA Astrophysics Data System (ADS)

Asafi, M. S.; Yildirim, A.; Tekpinar, M.

2016-04-01

Understanding dynamics of proteins has many practical implications in terms of finding a cure for many protein related diseases. Normal mode analysis and molecular dynamics methods are widely used physics-based computational methods for investigating dynamics of proteins. In this work, we studied dynamics of Hepatitis C NS5B protein with molecular dynamics and normal mode analysis. Principal components obtained from a 100 nanoseconds molecular dynamics simulation show good overlaps with normal modes calculated with a coarse-grained elastic network model. Coarse-grained normal mode analysis takes at least an order of magnitude shorter time. Encouraged by this good overlaps and short computation times, we analyzed further low frequency normal modes of Hepatitis C NS5B. Motion directions and average spatial fluctuations have been analyzed in detail. Finally, biological implications of these motions in drug design efforts against Hepatitis C infections have been elaborated.

Insight into the Li{sub 2}CO{sub 3}–K{sub 2}CO{sub 3} eutectic mixture from classical molecular dynamics: Thermodynamics, structure, and dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Corradini, Dario; Vuilleumier, Rodolphe, E-mail: rodolphe.vuilleumier@ens.fr; Sorbonne Universités, UPMC Univ. Paris 06, PASTEUR, 75005 Paris

We use molecular dynamics simulations to study the thermodynamics, structure, and dynamics of the Li{sub 2}CO{sub 3}–K{sub 2}CO{sub 3} (62:38 mol. %) eutectic mixture. We present a new classical non-polarizable force field for this molten salt mixture, optimized using experimental and first principles molecular dynamics simulations data as reference. This simple force field allows efficient molecular simulations of phenomena at long time scales. We use this optimized force field to describe the behavior of the eutectic mixture in the 900–1100 K temperature range, at pressures between 0 and 5 GPa. After studying the equation of state in these thermodynamic conditions, wemore » present molecular insight into the structure and dynamics of the melt. In particular, we present an analysis of the temperature and pressure dependence of the eutectic mixture’s self-diffusion coefficients, viscosity, and ionic conductivity.« less

Enhanced Molecular Dynamics Methods Applied to Drug Design Projects.

PubMed

Ziada, Sonia; Braka, Abdennour; Diharce, Julien; Aci-Sèche, Samia; Bonnet, Pascal

2018-01-01

Nobel Laureate Richard P. Feynman stated: "[…] everything that living things do can be understood in terms of jiggling and wiggling of atoms […]." The importance of computer simulations of macromolecules, which use classical mechanics principles to describe atom behavior, is widely acknowledged and nowadays, they are applied in many fields such as material sciences and drug discovery. With the increase of computing power, molecular dynamics simulations can be applied to understand biological mechanisms at realistic timescales. In this chapter, we share our computational experience providing a global view of two of the widely used enhanced molecular dynamics methods to study protein structure and dynamics through the description of their characteristics, limits and we provide some examples of their applications in drug design. We also discuss the appropriate choice of software and hardware. In a detailed practical procedure, we describe how to set up, run, and analyze two main molecular dynamics methods, the umbrella sampling (US) and the accelerated molecular dynamics (aMD) methods.

Molecular dynamics simulation and NMR investigation of the association of the β-blockers atenolol and propranolol with a chiral molecular micelle

NASA Astrophysics Data System (ADS)

Morris, Kevin F.; Billiot, Eugene J.; Billiot, Fereshteh H.; Hoffman, Charlene B.; Gladis, Ashley A.; Lipkowitz, Kenny B.; Southerland, William M.; Fang, Yayin

2015-08-01

Molecular dynamics simulations and NMR spectroscopy were used to compare the binding of two β-blocker drugs to the chiral molecular micelle poly-(sodium undecyl-(L)-leucine-valine). The molecular micelle is used as a chiral selector in capillary electrophoresis. This study is part of a larger effort to understand the mechanism of chiral recognition in capillary electrophoresis by characterizing the molecular micelle binding of chiral compounds with different geometries and charges. Propranolol and atenolol were chosen because their structures are similar, but their chiral interactions with the molecular micelle are different. Molecular dynamics simulations showed both propranolol enantiomers inserted their aromatic rings into the molecular micelle core and that (S)-propranolol associated more strongly with the molecular micelle than (R)-propranolol. This difference was attributed to stronger molecular micelle hydrogen bonding interactions experienced by (S)-propranolol. Atenolol enantiomers were found to bind near the molecular micelle surface and to have similar molecular micelle binding free energies.

Ligand-Dependent Activation and Deactivation of the Human Adenosine A2A Receptor

PubMed Central

Li, Jianing; Jonsson, Amanda L.; Beuming, Thijs; Shelley, John C.; Voth, Gregory A.

2013-01-01

G protein-coupled receptors (GPCRs) are membrane proteins with critical functions in cellular signal transduction, representing a primary class of drug targets. Acting by direct binding, many drugs modulate GPCR activity and influence the signaling pathways associated with numerous diseases. However, complete details of ligand-dependent GPCR activation/deactivation are difficult to obtain from experiments. Therefore, it remains unclear how ligands modulate a GPCR’s activity. To elucidate the ligand-dependent activation/deactivation mechanism of the human adenosine A2A receptor (AA2AR), a member of the class A GPCRs, we performed large-scale unbiased molecular dynamics and metadynamics simulations of the receptor embedded in a membrane. At the atomic level, we have observed distinct structural states that resemble the active and inactive states. In particular we noted key structural elements changing in a highly concerted fashion during the conformational transitions, including six conformational states of a tryptophan (Trp2466.48). Our findings agree with a previously proposed view, that during activation, this tryptophan residue undergoes a rotameric transition that may be coupled to a series of coherent conformational changes, resulting in the opening of the G protein-binding site. Further, metadynamics simulations provide quantitative evidence for this mechanism, suggesting how ligand binding shifts the equilibrium between the active and inactive states. Our analysis also proposes that a few specific residues are associated with agonism/antagonism, affinity and selectivity, and suggests that the ligand-binding pocket can be thought of as having three distinct regions, providing dynamic features for structure-based design. Additional simulations with AA2AR bound to a novel ligand are consistent with our proposed mechanism. Generally, our study provides insights into the ligand-dependent AA2AR activation/deactivation in addition to what has been found in crystal structures. These results should aid in the discovery of more effective and selective GPCR ligands. PMID:23678995

Conformational transition in signal transduction: metastable states and transition pathways in the activation of a signaling protein.

PubMed

Banerjee, Rahul; Yan, Honggao; Cukier, Robert I

2015-06-04

Signal transduction is of vital importance to the growth and adaptation of living organisms. The key to understand mechanisms of biological signal transduction is elucidation of the conformational dynamics of its signaling proteins, as the activation of a signaling protein is fundamentally a process of conformational transition from an inactive to an active state. A predominant form of signal transduction for bacterial sensing of environmental changes in the wild or inside their hosts is a variety of two-component systems, in which the conformational transition of a response regulator (RR) from an inactive to an active state initiates responses to the environmental changes. Here, RR activation has been investigated using RR468 as a model system by extensive unbiased all-atom molecular dynamics (MD) simulations in explicit solvent, starting from snapshots along a targeted MD trajectory that covers the conformational transition. Markov state modeling, transition path theory, and geometric analyses of the wealth of the MD data have provided a comprehensive description of the RR activation. It involves a network of metastable states, with one metastable state essentially the same as the inactive state and another very similar to the active state that are connected via a small set of intermediates. Five major pathways account for >75% of the fluxes of the conformational transition from the inactive to the active-like state. The thermodynamic stability of the states and the activation barriers between states are found, to identify rate-limiting steps. The conformal transition is initiated predominantly by movements of the β3α3 loop, followed by movements of the β4α4-loop and neighboring α4 helix region, and capped by additional movements of the β3α3 loop. A number of transient hydrophobic and hydrogen bond interactions are revealed, and they may be important for the conformational transition.

Ligand-dependent activation and deactivation of the human adenosine A(2A) receptor.

PubMed

Li, Jianing; Jonsson, Amanda L; Beuming, Thijs; Shelley, John C; Voth, Gregory A

2013-06-12

G-protein-coupled receptors (GPCRs) are membrane proteins with critical functions in cellular signal transduction, representing a primary class of drug targets. Acting by direct binding, many drugs modulate GPCR activity and influence the signaling pathways associated with numerous diseases. However, complete details of ligand-dependent GPCR activation/deactivation are difficult to obtain from experiments. Therefore, it remains unclear how ligands modulate a GPCR's activity. To elucidate the ligand-dependent activation/deactivation mechanism of the human adenosine A2A receptor (AA2AR), a member of the class A GPCRs, we performed large-scale unbiased molecular dynamics and metadynamics simulations of the receptor embedded in a membrane. At the atomic level, we have observed distinct structural states that resemble the active and inactive states. In particular, we noted key structural elements changing in a highly concerted fashion during the conformational transitions, including six conformational states of a tryptophan (Trp246(6.48)). Our findings agree with a previously proposed view that, during activation, this tryptophan residue undergoes a rotameric transition that may be coupled to a series of coherent conformational changes, resulting in the opening of the G-protein binding site. Further, metadynamics simulations provide quantitative evidence for this mechanism, suggesting how ligand binding shifts the equilibrium between the active and inactive states. Our analysis also proposes that a few specific residues are associated with agonism/antagonism, affinity, and selectivity, and suggests that the ligand-binding pocket can be thought of as having three distinct regions, providing dynamic features for structure-based design. Additional simulations with AA2AR bound to a novel ligand are consistent with our proposed mechanism. Generally, our study provides insights into the ligand-dependent AA2AR activation/deactivation in addition to what has been found in crystal structures. These results should aid in the discovery of more effective and selective GPCR ligands.

Extended Lagrangian Density Functional Tight-Binding Molecular Dynamics for Molecules and Solids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aradi, Bálint; Niklasson, Anders M. N.; Frauenheim, Thomas

A computationally fast quantum mechanical molecular dynamics scheme using an extended Lagrangian density functional tight-binding formulation has been developed and implemented in the DFTB+ electronic structure program package for simulations of solids and molecular systems. The scheme combines the computational speed of self-consistent density functional tight-binding theory with the efficiency and long-term accuracy of extended Lagrangian Born–Oppenheimer molecular dynamics. Furthermore, for systems without self-consistent charge instabilities, only a single diagonalization or construction of the single-particle density matrix is required in each time step. The molecular dynamics simulation scheme can also be applied to a broad range of problems in materialsmore » science, chemistry, and biology.« less

Extended Lagrangian Density Functional Tight-Binding Molecular Dynamics for Molecules and Solids

DOE PAGES

Aradi, Bálint; Niklasson, Anders M. N.; Frauenheim, Thomas

2015-06-26

A computationally fast quantum mechanical molecular dynamics scheme using an extended Lagrangian density functional tight-binding formulation has been developed and implemented in the DFTB+ electronic structure program package for simulations of solids and molecular systems. The scheme combines the computational speed of self-consistent density functional tight-binding theory with the efficiency and long-term accuracy of extended Lagrangian Born–Oppenheimer molecular dynamics. Furthermore, for systems without self-consistent charge instabilities, only a single diagonalization or construction of the single-particle density matrix is required in each time step. The molecular dynamics simulation scheme can also be applied to a broad range of problems in materialsmore » science, chemistry, and biology.« less

Identifying the Interaction of Vancomycin With Novel pH-Responsive Lipids as Antibacterial Biomaterials Via Accelerated Molecular Dynamics and Binding Free Energy Calculations.

PubMed

Ahmed, Shaimaa; Vepuri, Suresh B; Jadhav, Mahantesh; Kalhapure, Rahul S; Govender, Thirumala

2018-06-01

Nano-drug delivery systems have proven to be an efficient formulation tool to overcome the challenges with current antibiotics therapy and resistance. A series of pH-responsive lipid molecules were designed and synthesized for future liposomal formulation as a nano-drug delivery system for vancomycin at the infection site. The structures of these lipids differ from each other in respect of hydrocarbon tails: Lipid1, 2, 3 and 4 have stearic, oleic, linoleic, and linolenic acid hydrocarbon chains, respectively. The impact of variation in the hydrocarbon chain in the lipid structure on drug encapsulation and release profile, as well as mode of drug interaction, was investigated using molecular modeling analyses. A wide range of computational tools, including accelerated molecular dynamics, normal molecular dynamics, binding free energy calculations and principle component analysis, were applied to provide comprehensive insight into the interaction landscape between vancomycin and the designed lipid molecules. Interestingly, both MM-GBSA and MM-PBSA binding affinity calculations using normal molecular dynamics and accelerated molecular dynamics trajectories showed a very consistent trend, where the order of binding affinity towards vancomycin was lipid4 > lipid1 > lipid2 > lipid3. From both normal molecular dynamics and accelerated molecular dynamics, the interaction of lipid3 with vancomycin is demonstrated to be the weakest (∆G binding  = -2.17 and -11.57, for normal molecular dynamics and accelerated molecular dynamics, respectively) when compared to other complexes. We believe that the degree of unsaturation of the hydrocarbon chain in the lipid molecules may impact on the overall conformational behavior, interaction mode and encapsulation (wrapping) of the lipid molecules around the vancomycin molecule. This thorough computational analysis prior to the experimental investigation is a valuable approach to guide for predicting the encapsulation ability, drug release and further development of novel liposome-based pH-responsive nano-drug delivery system with refined structural and chemical features of potential lipid molecule for formulation development.

Nonadiabatic Ab Initio Molecular Dynamics with the Floating Occupation Molecular Orbital-Complete Active Space Configuration Interaction Method [Non-Adiabatic Ab Initio Molecular Dynamics with Floating Occupation Molecular Orbitals CASCI Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hollas, Daniel; Sistik, Lukas; Hohenstein, Edward G.

Here, we show that the floating occupation molecular orbital complete active space configuration interaction (FOMO-CASCI) method is a promising alternative to the widely used complete active space self-consistent field (CASSCF) method in direct nonadiabatic dynamics simulations. We have simulated photodynamics of three archetypal molecules in photodynamics: ethylene, methaniminium cation, and malonaldehyde. We compared the time evolution of electronic populations and reaction mechanisms as revealed by the FOMO-CASCI and CASSCF approaches. Generally, the two approaches provide similar results. Some dynamical differences are observed, but these can be traced back to energetically minor differences in the potential energy surfaces. We suggest thatmore » the FOMO-CASCI method represents, due to its efficiency and stability, a promising approach for direct ab initio dynamics in the excited state.« less

Molecular Dynamics implementation of BN2D or 'Mercedes Benz' water model

NASA Astrophysics Data System (ADS)

Scukins, Arturs; Bardik, Vitaliy; Pavlov, Evgen; Nerukh, Dmitry

2015-05-01

Two-dimensional 'Mercedes Benz' (MB) or BN2D water model (Naim, 1971) is implemented in Molecular Dynamics. It is known that the MB model can capture abnormal properties of real water (high heat capacity, minima of pressure and isothermal compressibility, negative thermal expansion coefficient) (Silverstein et al., 1998). In this work formulas for calculating the thermodynamic, structural and dynamic properties in microcanonical (NVE) and isothermal-isobaric (NPT) ensembles for the model from Molecular Dynamics simulation are derived and verified against known Monte Carlo results. The convergence of the thermodynamic properties and the system's numerical stability are investigated. The results qualitatively reproduce the peculiarities of real water making the model a visually convenient tool that also requires less computational resources, thus allowing simulations of large (hydrodynamic scale) molecular systems. We provide the open source code written in C/C++ for the BN2D water model implementation using Molecular Dynamics.

ls1 mardyn: The Massively Parallel Molecular Dynamics Code for Large Systems.

PubMed

Niethammer, Christoph; Becker, Stefan; Bernreuther, Martin; Buchholz, Martin; Eckhardt, Wolfgang; Heinecke, Alexander; Werth, Stephan; Bungartz, Hans-Joachim; Glass, Colin W; Hasse, Hans; Vrabec, Jadran; Horsch, Martin

2014-10-14

The molecular dynamics simulation code ls1 mardyn is presented. It is a highly scalable code, optimized for massively parallel execution on supercomputing architectures and currently holds the world record for the largest molecular simulation with over four trillion particles. It enables the application of pair potentials to length and time scales that were previously out of scope for molecular dynamics simulation. With an efficient dynamic load balancing scheme, it delivers high scalability even for challenging heterogeneous configurations. Presently, multicenter rigid potential models based on Lennard-Jones sites, point charges, and higher-order polarities are supported. Due to its modular design, ls1 mardyn can be extended to new physical models, methods, and algorithms, allowing future users to tailor it to suit their respective needs. Possible applications include scenarios with complex geometries, such as fluids at interfaces, as well as nonequilibrium molecular dynamics simulation of heat and mass transfer.

Protonation-induced stereoisomerism in nicotine: Conformational studies using classical (AMBER) and ab initio (Car Parrinello) molecular dynamics

NASA Astrophysics Data System (ADS)

Hammond, Philip S.; Wu, Yudong; Harris, Rebecca; Minehardt, Todd J.; Car, Roberto; Schmitt, Jeffrey D.

2005-01-01

A variety of biologically active small molecules contain prochiral tertiary amines, which become chiral centers upon protonation. S-nicotine, the prototypical nicotinic acetylcholine receptor agonist, produces two diastereomers on protonation. Results, using both classical (AMBER) and ab initio (Car-Parrinello) molecular dynamical studies, illustrate the significant differences in conformational space explored by each diastereomer. As is expected, this phenomenon has an appreciable effect on nicotine's energy hypersurface and leads to differentiation in molecular shape and divergent sampling. Thus, protonation induced isomerism can produce dynamic effects that may influence the behavior of a molecule in its interaction with a target protein. We also examine differences in the conformational dynamics for each diastereomer as quantified by both molecular dynamics methods.

Anisotropic Rotational Diffusion Studied by Nuclear Spin Relaxation and Molecular Dynamics Simulation: An Undergraduate Physical Chemistry Laboratory

ERIC Educational Resources Information Center

Fuson, Michael M.

2017-01-01

Laboratories studying the anisotropic rotational diffusion of bromobenzene using nuclear spin relaxation and molecular dynamics simulations are described. For many undergraduates, visualizing molecular motion is challenging. Undergraduates rarely encounter laboratories that directly assess molecular motion, and so the concept remains an…

Nuclear Dynamics at Molecule–Metal Interfaces: A Pseudoparticle Perspective

DOE PAGES

Galperin, Michael; Nitzan, Abraham

2015-11-20

We discuss nuclear dynamics at molecule-metal interfaces including nonequilibrium molecular junctions. Starting from the many-body states (pseudoparticle) formulation of the molecule-metal system in the molecular vibronic basis, we introduce gradient expansion to reduce the adiabatic nuclear dynamics (that is, nuclear dynamics on a single molecular potential surface) into its semiclassical form while maintaining the effect of the nonadiabatic electronic transitions between different molecular charge states. Finally, this yields a set of equations for the nuclear dynamics in the presence of these nonadiabatic transitions, which reproduce the surface-hopping formulation in the limit of small metal-molecule coupling (where broadening of the molecularmore » energy levels can be disregarded) and Ehrenfest dynamics (motion on the potential of mean force) when information on the different charging states is traced out.« less

Accelerated molecular dynamics: A promising and efficient simulation method for biomolecules

NASA Astrophysics Data System (ADS)

Hamelberg, Donald; Mongan, John; McCammon, J. Andrew

2004-06-01

Many interesting dynamic properties of biological molecules cannot be simulated directly using molecular dynamics because of nanosecond time scale limitations. These systems are trapped in potential energy minima with high free energy barriers for large numbers of computational steps. The dynamic evolution of many molecular systems occurs through a series of rare events as the system moves from one potential energy basin to another. Therefore, we have proposed a robust bias potential function that can be used in an efficient accelerated molecular dynamics approach to simulate the transition of high energy barriers without any advance knowledge of the location of either the potential energy wells or saddle points. In this method, the potential energy landscape is altered by adding a bias potential to the true potential such that the escape rates from potential wells are enhanced, which accelerates and extends the time scale in molecular dynamics simulations. Our definition of the bias potential echoes the underlying shape of the potential energy landscape on the modified surface, thus allowing for the potential energy minima to be well defined, and hence properly sampled during the simulation. We have shown that our approach, which can be extended to biomolecules, samples the conformational space more efficiently than normal molecular dynamics simulations, and converges to the correct canonical distribution.

The Continuing Debate on Deep Molluscan Phylogeny: Evidence for Serialia (Mollusca, Monoplacophora + Polyplacophora)

PubMed Central

Stöger, I.; Sigwart, J. D.; Kano, Y.; Knebelsberger, T.; Marshall, B. A.; Schwabe, E.; Schrödl, M.

2013-01-01

Molluscs are a diverse animal phylum with a formidable fossil record. Although there is little doubt about the monophyly of the eight extant classes, relationships between these groups are controversial. We analysed a comprehensive multilocus molecular data set for molluscs, the first to include multiple species from all classes, including five monoplacophorans in both extant families. Our analyses of five markers resolve two major clades: the first includes gastropods and bivalves sister to Serialia (monoplacophorans and chitons), and the second comprises scaphopods sister to aplacophorans and cephalopods. Traditional groupings such as Testaria, Aculifera, and Conchifera are rejected by our data with significant Approximately Unbiased (AU) test values. A new molecular clock indicates that molluscs had a terminal Precambrian origin with rapid divergence of all eight extant classes in the Cambrian. The recovery of Serialia as a derived, Late Cambrian clade is potentially in line with the stratigraphic chronology of morphologically heterogeneous early mollusc fossils. Serialia is in conflict with traditional molluscan classifications and recent phylogenomic data. Yet our hypothesis, as others from molecular data, implies frequent molluscan shell and body transformations by heterochronic shifts in development and multiple convergent adaptations, leading to the variable shells and body plans in extant lineages. PMID:24350268

Sensitivity to PI3K and AKT inhibitors is mediated by divergent molecular mechanisms in subtypes of DLBCL.

PubMed

Erdmann, Tabea; Klener, Pavel; Lynch, James T; Grau, Michael; Vočková, Petra; Molinsky, Jan; Tuskova, Diana; Hudson, Kevin; Polanska, Urszula M; Grondine, Michael; Mayo, Michele; Dai, Beiying; Pfeifer, Matthias; Erdmann, Kristian; Schwammbach, Daniela; Zapukhlyak, Myroslav; Staiger, Annette M; Ott, German; Berdel, Wolfgang E; Davies, Barry R; Cruzalegui, Francisco; Trneny, Marek; Lenz, Peter; Barry, Simon T; Lenz, Georg

2017-07-20

Activated B-cell-like (ABC) and germinal center B-cell-like diffuse large B-cell lymphoma (DLBCL) represent the 2 major molecular DLBCL subtypes. They are characterized by differences in clinical course and by divergent addiction to oncogenic pathways. To determine activity of novel compounds in these 2 subtypes, we conducted an unbiased pharmacologic in vitro screen. The phosphatidylinositol-3-kinase (PI3K) α/δ (PI3Kα/δ) inhibitor AZD8835 showed marked potency in ABC DLBCL models, whereas the protein kinase B (AKT) inhibitor AZD5363 induced apoptosis in PTEN-deficient DLBCLs irrespective of their molecular subtype. These in vitro results were confirmed in various cell line xenograft and patient-derived xenograft mouse models in vivo. Treatment with AZD8835 induced inhibition of nuclear factor κB signaling, prompting us to combine AZD8835 with the Bruton's tyrosine kinase inhibitor ibrutinib. This combination was synergistic and effective both in vitro and in vivo. In contrast, the AKT inhibitor AZD5363 was effective in PTEN-deficient DLBCLs through downregulation of the oncogenic transcription factor MYC. Collectively, our data suggest that patients should be stratified according to their oncogenic dependencies when treated with PI3K and AKT inhibitors. © 2017 by The American Society of Hematology.

Five instruments for measuring tree height: an evaluation

Treesearch

Michael S. Williams; William A. Bechtold; V.J. LaBau

1994-01-01

Five instruments were tested for reliability in measuring tree heights under realistic conditions. Four linear models were used to determine if tree height can be measured unbiasedly over all tree sizes and if any of the instruments were more efficient in estimating tree height. The laser height finder was the only instrument to produce unbiased estimates of the true...

Spectroscopic observations of ATLAS17lcs (SN 2017guv) and ASASSN-17mq (AT 2017gvo) by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Dong, Subo; Bose, Subhash; Stritzinger, M.; Holmbo, S.; Fraser, M.; Fedorets, G.

2017-10-01

The Nordic Optical Telescope (NOT) Unbiased Transient Survey (NUTS; ATel #8992) reports the spectroscopic classification of ATLAS17lcs (SN 2017guv) and ASASSN-17mq (AT 2017gvo) in host galaxies 2MASX J19132225-1648031 and CGCG 225-050, respectively.

Spectroscopic observations of ASASSN-17io and ATLAS17hpt (SN 2017faf) by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Pastorello, Andrea; Benetti, Stefano; Cappellaro, Enrico; Terreran, Giacomo; Tomasella, Lina; Fedorets, Grigori; NUTS Collaboration

2017-07-01

The Nordic Optical Telescope (NOT) Unbiased Transient Survey (NUTS; ATel #8992) reports the spectroscopic classification of ASASSN-17io in the galaxy CGCG 316-010, along with the re classification of ATLAS17hpt (SN 2017faf), which was previously classified as a SLSN-I (ATel #10549).

Contextual classification of multispectral image data: An unbiased estimator for the context distribution

NASA Technical Reports Server (NTRS)

Tilton, J. C.; Swain, P. H. (Principal Investigator); Vardeman, S. B.

1981-01-01

A key input to a statistical classification algorithm, which exploits the tendency of certain ground cover classes to occur more frequently in some spatial context than in others, is a statistical characterization of the context: the context distribution. An unbiased estimator of the context distribution is discussed which, besides having the advantage of statistical unbiasedness, has the additional advantage over other estimation techniques of being amenable to an adaptive implementation in which the context distribution estimate varies according to local contextual information. Results from applying the unbiased estimator to the contextual classification of three real LANDSAT data sets are presented and contrasted with results from non-contextual classifications and from contextual classifications utilizing other context distribution estimation techniques.

Estimation of the simple correlation coefficient.

PubMed

Shieh, Gwowen

2010-11-01

This article investigates some unfamiliar properties of the Pearson product-moment correlation coefficient for the estimation of simple correlation coefficient. Although Pearson's r is biased, except for limited situations, and the minimum variance unbiased estimator has been proposed in the literature, researchers routinely employ the sample correlation coefficient in their practical applications, because of its simplicity and popularity. In order to support such practice, this study examines the mean squared errors of r and several prominent formulas. The results reveal specific situations in which the sample correlation coefficient performs better than the unbiased and nearly unbiased estimators, facilitating recommendation of r as an effect size index for the strength of linear association between two variables. In addition, related issues of estimating the squared simple correlation coefficient are also considered.

A centroid molecular dynamics study of liquid para-hydrogen and ortho-deuterium.

PubMed

Hone, Tyler D; Voth, Gregory A

2004-10-01

Centroid molecular dynamics (CMD) is applied to the study of collective and single-particle dynamics in liquid para-hydrogen at two state points and liquid ortho-deuterium at one state point. The CMD results are compared with the results of classical molecular dynamics, quantum mode coupling theory, a maximum entropy analytic continuation approach, pair-product forward- backward semiclassical dynamics, and available experimental results. The self-diffusion constants are in excellent agreement with the experimental measurements for all systems studied. Furthermore, it is shown that the method is able to adequately describe both the single-particle and collective dynamics of quantum liquids. (c) 2004 American Institute of Physics

The first decade of MALDI protein profiling: a lesson in translational biomarker research.

PubMed

Albrethsen, Jakob

2011-05-16

MALDI protein profiling has identified several important challenges in omics-based biomarker research. First, research into the analytical performance of a novel omics-platform of potential diagnostic impact must be carried out in a critical manner and according to common guidelines. Evaluation studies should be performed at an early time and preferably before massive advancement into explorative biomarker research. In particular, MALDI profiling underscores the need for an adequate understanding of the causal relationship between molecular abundance and the quantitative measure in multivariate biomarker research. Secondly, MALDI profiling has raised awareness of the significant risk of false-discovery in biomarker research due to several confounding factors, including sample processing and unspecific host-response to disease. Here, the experience from MALDI profiling supports that a central challenge in unbiased molecular profiling is to pinpoint the aberrations of clinical interest among potentially massive unspecific changes that can accompany disease. The lessons from the first decade of MALDI protein profiling are relevant for future efforts in advancing omics-based biomarker research beyond the laboratory setting and into clinical verification. Copyright © 2011 Elsevier B.V. All rights reserved.

Cosmic Star Formation - Seen from the Milky Way with AtLAST Short Contributed Talk

NASA Astrophysics Data System (ADS)

Kauffmann, Jens

2018-01-01

Herschel and Spitzer provided first truly unbiased overviews of star formation environments in the Milky Way. Today, high–powered instruments like ALMA additionally resolve the immediate birth environments of individual stars in a few selected regions throughout the Galaxy. This progress in the Milky Way is important, because the same facilities also allow us to explore how galaxies evolved over time. Was star formation more efficient in the dense molecular clouds found in starburst galaxies? Why do galaxies often follow star formation relations like those from Kennicutt & Schmidt and Gao & Solomon? A cloud-scale understanding of the star formation processes, that can only be developed in the Milky Way, is necessary to make progress. Unfortunately, ALMA can resolve the detailed substructure only in SELECTED galactic molecular clouds, given mapping with ALMA is very slow. Here I show how surveys of dust continuum and line emission provided by a large and fast single–dish telescope can overcome these critical limitations, e.g. by breaking degeneracies in current theoretical models. My discussion draws on a white papers previously developed for similar telescopes.

Analytic nuclear forces and molecular properties from full configuration interaction quantum Monte Carlo

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas, Robert E.; Overy, Catherine; Opalka, Daniel

Unbiased stochastic sampling of the one- and two-body reduced density matrices is achieved in full configuration interaction quantum Monte Carlo with the introduction of a second, “replica” ensemble of walkers, whose population evolves in imaginary time independently from the first and which entails only modest additional computational overheads. The matrices obtained from this approach are shown to be representative of full configuration-interaction quality and hence provide a realistic opportunity to achieve high-quality results for a range of properties whose operators do not necessarily commute with the Hamiltonian. A density-matrix formulated quasi-variational energy estimator having been already proposed and investigated, themore » present work extends the scope of the theory to take in studies of analytic nuclear forces, molecular dipole moments, and polarisabilities, with extensive comparison to exact results where possible. These new results confirm the suitability of the sampling technique and, where sufficiently large basis sets are available, achieve close agreement with experimental values, expanding the scope of the method to new areas of investigation.« less

Calcium ions in aqueous solutions: Accurate force field description aided by ab initio molecular dynamics and neutron scattering

NASA Astrophysics Data System (ADS)

Martinek, Tomas; Duboué-Dijon, Elise; Timr, Štěpán; Mason, Philip E.; Baxová, Katarina; Fischer, Henry E.; Schmidt, Burkhard; Pluhařová, Eva; Jungwirth, Pavel

2018-06-01

We present a combination of force field and ab initio molecular dynamics simulations together with neutron scattering experiments with isotopic substitution that aim at characterizing ion hydration and pairing in aqueous calcium chloride and formate/acetate solutions. Benchmarking against neutron scattering data on concentrated solutions together with ion pairing free energy profiles from ab initio molecular dynamics allows us to develop an accurate calcium force field which accounts in a mean-field way for electronic polarization effects via charge rescaling. This refined calcium parameterization is directly usable for standard molecular dynamics simulations of processes involving this key biological signaling ion.

Water dynamics in protein hydration shells: the molecular origins of the dynamical perturbation.

PubMed

Fogarty, Aoife C; Laage, Damien

2014-07-17

Protein hydration shell dynamics play an important role in biochemical processes including protein folding, enzyme function, and molecular recognition. We present here a comparison of the reorientation dynamics of individual water molecules within the hydration shell of a series of globular proteins: acetylcholinesterase, subtilisin Carlsberg, lysozyme, and ubiquitin. Molecular dynamics simulations and analytical models are used to access site-resolved information on hydration shell dynamics and to elucidate the molecular origins of the dynamical perturbation of hydration shell water relative to bulk water. We show that all four proteins have very similar hydration shell dynamics, despite their wide range of sizes and functions, and differing secondary structures. We demonstrate that this arises from the similar local surface topology and surface chemical composition of the four proteins, and that such local factors alone are sufficient to rationalize the hydration shell dynamics. We propose that these conclusions can be generalized to a wide range of globular proteins. We also show that protein conformational fluctuations induce a dynamical heterogeneity within the hydration layer. We finally address the effect of confinement on hydration shell dynamics via a site-resolved analysis and connect our results to experiments via the calculation of two-dimensional infrared spectra.

Water Dynamics in Protein Hydration Shells: The Molecular Origins of the Dynamical Perturbation

PubMed Central

2014-01-01

Protein hydration shell dynamics play an important role in biochemical processes including protein folding, enzyme function, and molecular recognition. We present here a comparison of the reorientation dynamics of individual water molecules within the hydration shell of a series of globular proteins: acetylcholinesterase, subtilisin Carlsberg, lysozyme, and ubiquitin. Molecular dynamics simulations and analytical models are used to access site-resolved information on hydration shell dynamics and to elucidate the molecular origins of the dynamical perturbation of hydration shell water relative to bulk water. We show that all four proteins have very similar hydration shell dynamics, despite their wide range of sizes and functions, and differing secondary structures. We demonstrate that this arises from the similar local surface topology and surface chemical composition of the four proteins, and that such local factors alone are sufficient to rationalize the hydration shell dynamics. We propose that these conclusions can be generalized to a wide range of globular proteins. We also show that protein conformational fluctuations induce a dynamical heterogeneity within the hydration layer. We finally address the effect of confinement on hydration shell dynamics via a site-resolved analysis and connect our results to experiments via the calculation of two-dimensional infrared spectra. PMID:24479585

How Dynamic Visualization Technology can Support Molecular Reasoning

NASA Astrophysics Data System (ADS)

Levy, Dalit

2013-10-01

This paper reports the results of a study aimed at exploring the advantages of dynamic visualization for the development of better understanding of molecular processes. We designed a technology-enhanced curriculum module in which high school chemistry students conduct virtual experiments with dynamic molecular visualizations of solid, liquid, and gas. They interact with the visualizations and carry out inquiry activities to make and refine connections between observable phenomena and atomic level processes related to phase change. The explanations proposed by 300 pairs of students in response to pre/post-assessment items have been analyzed using a scale for measuring the level of molecular reasoning. Results indicate that from pretest to posttest, students make progress in their level of molecular reasoning and are better able to connect intermolecular forces and phase change in their explanations. The paper presents the results through the lens of improvement patterns and the metaphor of the "ladder of molecular reasoning," and discusses how this adds to our understanding of the benefits of interacting with dynamic molecular visualizations.

Thermostatted molecular dynamics: How to avoid the Toda demon hidden in Nose-Hoover dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Holian, B.L.; Voter, A.F.; Ravelo, R.

The Nose-Hoover thermostat, which is often used in the hope of modifying molecular dynamics trajectories in order to achieve canonical-ensemble averages, has hidden in it a Toda ``demon,`` which can give rise to unwanted, noncanonical undulations in the instantaneous kinetic temperature. We show how these long-lived oscillations arise from insufficient coupling of the thermostat to the atoms, and give straightforward, practical procedures for avoiding this weak-coupling pathology in isothermal molecular dynamics simulations.

Total synthesis of (-)-doliculide, structure-activity relationship studies and its binding to F-actin.

PubMed

Matcha, Kiran; Madduri, Ashoka V R; Roy, Sayantani; Ziegler, Slava; Waldmann, Herbert; Hirsch, Anna K H; Minnaard, Adriaan J

2012-11-26

Actin, an abundant protein in most eukaryotic cells, is one of the targets in cancer research. Recently, a great deal of attention has been paid to the synthesis and function of actin-targeting compounds and their use as effective molecular probes in chemical biology. In this study, we have developed an efficient synthesis of (-)-doliculide, a very potent actin binder with a higher cell-membrane permeability than phalloidin. Actin polymerization assays with (-)-doliculide and two analogues on HeLa and BSC-1 cells, together with a prediction of their binding mode to F-actin by unbiased computational docking, show that doliculide stabilizes F-actin in a similar way to jasplakinolide and chondramide C. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Circadian Enhancers Coordinate Multiple Phases of Rhythmic Gene Transcription In Vivo

PubMed Central

Fang, Bin; Everett, Logan J.; Jager, Jennifer; Briggs, Erika; Armour, Sean M.; Feng, Dan; Roy, Ankur; Gerhart-Hines, Zachary; Sun, Zheng; Lazar, Mitchell A.

2014-01-01

SUMMARY Mammalian transcriptomes display complex circadian rhythms with multiple phases of gene expression that cannot be accounted for by current models of the molecular clock. We have determined the underlying mechanisms by measuring nascent RNA transcription around the clock in mouse liver. Unbiased examination of eRNAs that cluster in specific circadian phases identified functional enhancers driven by distinct transcription factors (TFs). We further identify on a global scale the components of the TF cistromes that function to orchestrate circadian gene expression. Integrated genomic analyses also revealed novel mechanisms by which a single circadian factor controls opposing transcriptional phases. These findings shed new light on the diversity and specificity of TF function in the generation of multiple phases of circadian gene transcription in a mammalian organ. PMID:25416951

Rapid and Programmable Protein Mutagenesis Using Plasmid Recombineering.

PubMed

Higgins, Sean A; Ouonkap, Sorel V Y; Savage, David F

2017-10-20

Comprehensive and programmable protein mutagenesis is critical for understanding structure-function relationships and improving protein function. There is thus a need for robust and unbiased molecular biological approaches for the construction of the requisite comprehensive protein libraries. Here we demonstrate that plasmid recombineering is a simple and robust in vivo method for the generation of protein mutants for both comprehensive library generation as well as programmable targeting of sequence space. Using the fluorescent protein iLOV as a model target, we build a complete mutagenesis library and find it to be specific and comprehensive, detecting 99.8% of our intended mutations. We then develop a thermostability screen and utilize our comprehensive mutation data to rapidly construct a targeted and multiplexed library that identifies significantly improved variants, thus demonstrating rapid protein engineering in a simple protocol.

Next-Generation Sequencing-Based Approaches for Mutation Mapping and Identification in Caenorhabditis elegans

PubMed Central

Doitsidou, Maria; Jarriault, Sophie; Poole, Richard J.

2016-01-01

The use of next-generation sequencing (NGS) has revolutionized the way phenotypic traits are assigned to genes. In this review, we describe NGS-based methods for mapping a mutation and identifying its molecular identity, with an emphasis on applications in Caenorhabditis elegans. In addition to an overview of the general principles and concepts, we discuss the main methods, provide practical and conceptual pointers, and guide the reader in the types of bioinformatics analyses that are required. Owing to the speed and the plummeting costs of NGS-based methods, mapping and cloning a mutation of interest has become straightforward, quick, and relatively easy. Removing this bottleneck previously associated with forward genetic screens has significantly advanced the use of genetics to probe fundamental biological processes in an unbiased manner. PMID:27729495

Circadian enhancers coordinate multiple phases of rhythmic gene transcription in vivo.

PubMed

Fang, Bin; Everett, Logan J; Jager, Jennifer; Briggs, Erika; Armour, Sean M; Feng, Dan; Roy, Ankur; Gerhart-Hines, Zachary; Sun, Zheng; Lazar, Mitchell A

2014-11-20

Mammalian transcriptomes display complex circadian rhythms with multiple phases of gene expression that cannot be accounted for by current models of the molecular clock. We have determined the underlying mechanisms by measuring nascent RNA transcription around the clock in mouse liver. Unbiased examination of enhancer RNAs (eRNAs) that cluster in specific circadian phases identified functional enhancers driven by distinct transcription factors (TFs). We further identify on a global scale the components of the TF cistromes that function to orchestrate circadian gene expression. Integrated genomic analyses also revealed mechanisms by which a single circadian factor controls opposing transcriptional phases. These findings shed light on the diversity and specificity of TF function in the generation of multiple phases of circadian gene transcription in a mammalian organ.

Molecular dynamics simulation of low-energy recoil events in titanate pyrochlores

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, Liyuan; Setyawan, Wahyu; Li, Yuhong

2017-01-01

Molecular dynamics simulations of low-energy displacements in titanate pyrochlores have been carried out along three main directions, to determineE dfor A, Ti and O, corresponding defect configurations, and defect formation dynamics.

Modelling and enhanced molecular dynamics to steer structure-based drug discovery.

PubMed

Kalyaanamoorthy, Subha; Chen, Yi-Ping Phoebe

2014-05-01

The ever-increasing gap between the availabilities of the genome sequences and the crystal structures of proteins remains one of the significant challenges to the modern drug discovery efforts. The knowledge of structure-dynamics-functionalities of proteins is important in order to understand several key aspects of structure-based drug discovery, such as drug-protein interactions, drug binding and unbinding mechanisms and protein-protein interactions. This review presents a brief overview on the different state of the art computational approaches that are applied for protein structure modelling and molecular dynamics simulations of biological systems. We give an essence of how different enhanced sampling molecular dynamics approaches, together with regular molecular dynamics methods, assist in steering the structure based drug discovery processes. Copyright © 2013 Elsevier Ltd. All rights reserved.

A proteomic chronology of gene expression through the cell cycle in human myeloid leukemia cells.

PubMed

Ly, Tony; Ahmad, Yasmeen; Shlien, Adam; Soroka, Dominique; Mills, Allie; Emanuele, Michael J; Stratton, Michael R; Lamond, Angus I

2014-01-01

Technological advances have enabled the analysis of cellular protein and RNA levels with unprecedented depth and sensitivity, allowing for an unbiased re-evaluation of gene regulation during fundamental biological processes. Here, we have chronicled the dynamics of protein and mRNA expression levels across a minimally perturbed cell cycle in human myeloid leukemia cells using centrifugal elutriation combined with mass spectrometry-based proteomics and RNA-Seq, avoiding artificial synchronization procedures. We identify myeloid-specific gene expression and variations in protein abundance, isoform expression and phosphorylation at different cell cycle stages. We dissect the relationship between protein and mRNA levels for both bulk gene expression and for over ∼6000 genes individually across the cell cycle, revealing complex, gene-specific patterns. This data set, one of the deepest surveys to date of gene expression in human cells, is presented in an online, searchable database, the Encyclopedia of Proteome Dynamics (http://www.peptracker.com/epd/). DOI: http://dx.doi.org/10.7554/eLife.01630.001.

A proteomic chronology of gene expression through the cell cycle in human myeloid leukemia cells

PubMed Central

Ly, Tony; Ahmad, Yasmeen; Shlien, Adam; Soroka, Dominique; Mills, Allie; Emanuele, Michael J; Stratton, Michael R; Lamond, Angus I

2014-01-01

Technological advances have enabled the analysis of cellular protein and RNA levels with unprecedented depth and sensitivity, allowing for an unbiased re-evaluation of gene regulation during fundamental biological processes. Here, we have chronicled the dynamics of protein and mRNA expression levels across a minimally perturbed cell cycle in human myeloid leukemia cells using centrifugal elutriation combined with mass spectrometry-based proteomics and RNA-Seq, avoiding artificial synchronization procedures. We identify myeloid-specific gene expression and variations in protein abundance, isoform expression and phosphorylation at different cell cycle stages. We dissect the relationship between protein and mRNA levels for both bulk gene expression and for over ∼6000 genes individually across the cell cycle, revealing complex, gene-specific patterns. This data set, one of the deepest surveys to date of gene expression in human cells, is presented in an online, searchable database, the Encyclopedia of Proteome Dynamics (http://www.peptracker.com/epd/). DOI: http://dx.doi.org/10.7554/eLife.01630.001 PMID:24596151

Exploring GPCR-Lipid Interactions by Molecular Dynamics Simulations: Excitements, Challenges, and the Way Forward.

PubMed

Sengupta, Durba; Prasanna, Xavier; Mohole, Madhura; Chattopadhyay, Amitabha

2018-06-07

Gprotein-coupled receptors (GPCRs) are seven transmembrane receptors that mediate a large number of cellular responses and are important drug targets. One of the current challenges in GPCR biology is to analyze the molecular signatures of receptor-lipid interactions and their subsequent effects on GPCR structure, organization, and function. Molecular dynamics simulation studies have been successful in predicting molecular determinants of receptor-lipid interactions. In particular, predicted cholesterol interaction sites appear to correspond well with experimentally determined binding sites and estimated time scales of association. In spite of several success stories, the methodologies in molecular dynamics simulations are still emerging. In this Feature Article, we provide a comprehensive overview of coarse-grain and atomistic molecular dynamics simulations of GPCR-lipid interaction in the context of experimental observations. In addition, we discuss the effect of secondary and tertiary structural constraints in coarse-grain simulations in the context of functional dynamics and structural plasticity of GPCRs. We envision that this comprehensive overview will help resolve differences in computational studies and provide a way forward.

Novel Breast Cancer Therapeutics Based on Bacterial Cupredoxin

DTIC Science & Technology

2008-09-01

M. and Lim, C. (1999) Exploring the dynamic information content of a protein NMR structure: comparison of a molecular dynamics simulation with the...crowding has structural effects on the folded ensemble of polypeptides. energy landscape theory excluded volume effect molecular simulations protein... molecular simulations (51). Thermo- dynamic properties such as the radius of gyration (Rg), shape parameters ( and S) (11), and the fraction of native

Visualizing Energy on Target: Molecular Dynamics Simulations

DTIC Science & Technology

2017-12-01

ARL-TR-8234 ● DEC 2017 US Army Research Laboratory Visualizing Energy on Target: Molecular Dynamics Simulations by DeCarlos E...return it to the originator. ARL-TR-8234● DEC 2017 US Army Research Laboratory Visualizing Energy on Target: Molecular Dynamics...REPORT TYPE Technical Report 3. DATES COVERED (From - To) 1 October 2015–30 September 2016 4. TITLE AND SUBTITLE Visualizing Energy on Target

Free-Energy Profiles of Membrane Insertion of the M2 Transmembrane Peptide from Influenza A Virus

DTIC Science & Technology

2008-12-01

ABSTRACT The insertion of the M2 transmembrane peptide from influenza A virus into a membrane has been studied with molecular - dynamics simulations ...performed replica-exchange molecular - dynamics simulations with umbrella-sampling techniques to characterize the probability distribution and conformation...atomic- detailed molecular dynamics (MD) simulation techniques represent a valuable complementary methodology to inves- tigate membrane-insertion of

Maximal Unbiased Benchmarking Data Sets for Human Chemokine Receptors and Comparative Analysis.

PubMed

Xia, Jie; Reid, Terry-Elinor; Wu, Song; Zhang, Liangren; Wang, Xiang Simon

2018-05-29

Chemokine receptors (CRs) have long been druggable targets for the treatment of inflammatory diseases and HIV-1 infection. As a powerful technique, virtual screening (VS) has been widely applied to identifying small molecule leads for modern drug targets including CRs. For rational selection of a wide variety of VS approaches, ligand enrichment assessment based on a benchmarking data set has become an indispensable practice. However, the lack of versatile benchmarking sets for the whole CRs family that are able to unbiasedly evaluate every single approach including both structure- and ligand-based VS somewhat hinders modern drug discovery efforts. To address this issue, we constructed Maximal Unbiased Benchmarking Data sets for human Chemokine Receptors (MUBD-hCRs) using our recently developed tools of MUBD-DecoyMaker. The MUBD-hCRs encompasses 13 subtypes out of 20 chemokine receptors, composed of 404 ligands and 15756 decoys so far and is readily expandable in the future. It had been thoroughly validated that MUBD-hCRs ligands are chemically diverse while its decoys are maximal unbiased in terms of "artificial enrichment", "analogue bias". In addition, we studied the performance of MUBD-hCRs, in particular CXCR4 and CCR5 data sets, in ligand enrichment assessments of both structure- and ligand-based VS approaches in comparison with other benchmarking data sets available in the public domain and demonstrated that MUBD-hCRs is very capable of designating the optimal VS approach. MUBD-hCRs is a unique and maximal unbiased benchmarking set that covers major CRs subtypes so far.

A molecular line survey toward the nearby galaxies NGC 1068, NGC 253, and IC 342 at 3 mm with the Nobeyama 45 m radio telescope: Impact of an AGN on 1 kpc scale molecular abundances

NASA Astrophysics Data System (ADS)

Nakajima, Taku; Takano, Shuro; Kohno, Kotaro; Harada, Nanase; Herbst, Eric

2018-01-01

It is important to investigate the relationships between the power sources and the chemical compositions of galaxies in order to understand the scenario of galaxy evolution. We carried out an unbiased molecular line survey towards active galactic nucleus (AGN) host galaxy NGC1068, and prototypical starburst galaxies, NGC 253 and IC 342, with the Nobeyama 45 m telescope in the 3 mm band. The advantage of this line survey is that the obtained spectra have the highest angular resolution ever obtained with single-dish telescopes. In particular, the beam size of this telescope is ˜15″-19″, which is able to separate spatially the nuclear molecular emission from that of the starburst ring (d ˜ 30″) in NGC 1068. We successfully detected approximately 23 molecular species in each galaxy, and calculated rotation temperatures and column densities. We estimate the molecular fractional abundances with respect to 13CO and CS molecules and compare them among three galaxies in order to investigate the chemical signatures of an AGN environment. As a result, we found clear trends in the abundances of molecules surrounding the AGN on a 1-kpc scale. HCN, H13CN, CN, 13CN, and HC3N are more abundant, and CH3CCH is deficient in NGC 1068 compared with the starburst galaxies. High abundances of HCN, H13CN, and HC3N suggest that the circumnuclear disk in NGC 1068 is in a high-temperature environment. The reason for the non-detection of CH3CCH is likely to be dissociation by high-energy radiation or less sublimation of a precursor of CH3CCH from grains.

Coupled binding-bending-folding: The complex conformational dynamics of protein-DNA binding studied by atomistic molecular dynamics simulations.

PubMed

van der Vaart, Arjan

2015-05-01

Protein-DNA binding often involves dramatic conformational changes such as protein folding and DNA bending. While thermodynamic aspects of this behavior are understood, and its biological function is often known, the mechanism by which the conformational changes occur is generally unclear. By providing detailed structural and energetic data, molecular dynamics simulations have been helpful in elucidating and rationalizing protein-DNA binding. This review will summarize recent atomistic molecular dynamics simulations of the conformational dynamics of DNA and protein-DNA binding. A brief overview of recent developments in DNA force fields is given as well. Simulations have been crucial in rationalizing the intrinsic flexibility of DNA, and have been instrumental in identifying the sequence of binding events, the triggers for the conformational motion, and the mechanism of binding for a number of important DNA-binding proteins. Molecular dynamics simulations are an important tool for understanding the complex binding behavior of DNA-binding proteins. With recent advances in force fields and rapid increases in simulation time scales, simulations will become even more important for future studies. This article is part of a Special Issue entitled Recent developments of molecular dynamics. Copyright © 2014. Published by Elsevier B.V.

Earle K. Plyler Prize Lecture: The Three Pillars of Ultrafast Molecular Science - Time, Phase, Intensity

NASA Astrophysics Data System (ADS)

Stolow, Albert

We discuss the probing and control of molecular wavepacket dynamics in the context of three main `pillars' of light-matter interaction: time, phase, intensity. Time: Using short, coherent laser pulses and perturbative matter-field interactions, we study molecular wavepackets with a focus on the ultrafast non-Born-Oppenheimer dynamics, that is, the coupling of electronic and nuclear motions. Time-Resolved Photoelectron Spectroscopy (TRPES) is a powerful ultrafast probe of these processes in polyatomic molecules because it is sensitive both electronic and vibrational dynamics. Ideally, one would like to observe these ultrafast processes from the molecule's point of view - the Molecular Frame - thereby avoiding loss of information due to orientational averaging. This can be achieved by Time-Resolved Coincidence Imaging Spectroscopy (TRCIS) which images 3D recoil vectors of both photofragments and photoelectrons, in coincidence and as a function of time, permitting direct Molecular Frame imaging of valence electronic dynamics during a molecular dynamics. Phase: Using intermediate strength non-perturbative interactions, we apply the second order (polarizability) Non-Resonant Dynamic Stark Effect (NRDSE) to control molecular dynamics without any net absorption of light. NRDSE is also the interaction underlying molecular alignment and applies to field-free 1D of linear molecules and field-free 3D alignment of general (asymmetric) molecules. Using laser alignment, we can transiently fix a molecule in space, yielding a more general approach to direct Molecular Frame imaging of valence electronic dynamics during a chemical reaction. Intensity: In strong (ionizing) laser fields, a new laser-matter physics emerges for polyatomic systems wherein both the single active electron picture and the adiabatic electron response, both implicit in the standard 3-step models, can fail dramatically. This has important consequences for all attosecond strong field spectroscopies of polyatomic molecules, including high harmonic generation (HHG). We discuss an experimental method, Channel-Resolved Above Threshold Ionization (CRATI), which directly unveils the electronic channels participating in the attosecond molecular strong field ionization response [10]. This work was supported by the National Research Council of Canada and the Natural Sciences & Engineering Research Council.

Perspective: A Dynamics-Based Classification of Ventricular Arrhythmias

PubMed Central

Weiss, James N.; Garfinkel, Alan; Karagueuzian, Hrayr S.; Nguyen, Thao P.; Olcese, Riccardo; Chen, Peng-Sheng; Qu, Zhilin

2015-01-01

Despite key advances in the clinical management of life-threatening ventricular arrhythmias, culminating with the development of implantable cardioverter-defibrillators and catheter ablation techniques, pharmacologic/biologic therapeutics have lagged behind. The fundamental issue is that biological targets are molecular factors. Diseases, however, represent emergent properties at the scale of the organism that result from dynamic interactions between multiple constantly changing molecular factors. For a pharmacologic/biologic therapy to be effective, it must target the dynamic processes that underlie the disease. Here we propose a classification of ventricular arrhythmias that is based on our current understanding of the dynamics occurring at the subcellular, cellular, tissue and organism scales, which cause arrhythmias by simultaneously generating arrhythmia triggers and exacerbating tissue vulnerability. The goal is to create a framework that systematically links these key dynamic factors together with fixed factors (structural and electrophysiological heterogeneity) synergistically promoting electrical dispersion and increased arrhythmia risk to molecular factors that can serve as biological targets. We classify ventricular arrhythmias into three primary dynamic categories related generally to unstable Ca cycling, reduced repolarization, and excess repolarization, respectively. The clinical syndromes, arrhythmia mechanisms, dynamic factors and what is known about their molecular counterparts are discussed. Based on this framework, we propose a computational-experimental strategy for exploring the links between molecular factors, fixed factors and dynamic factors that underlie life-threatening ventricular arrhythmias. The ultimate objective is to facilitate drug development by creating an in silico platform to evaluate and predict comprehensively how molecular interventions affect not only a single targeted arrhythmia, but all primary arrhythmia dynamics categories as well as normal cardiac excitation-contraction coupling. PMID:25769672

Bottom-up derivation of conservative and dissipative interactions for coarse-grained molecular liquids with the conditional reversible work method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deichmann, Gregor; Marcon, Valentina; Vegt, Nico F. A. van der, E-mail: vandervegt@csi.tu-darmstadt.de

Molecular simulations of soft matter systems have been performed in recent years using a variety of systematically coarse-grained models. With these models, structural or thermodynamic properties can be quite accurately represented while the prediction of dynamic properties remains difficult, especially for multi-component systems. In this work, we use constraint molecular dynamics simulations for calculating dissipative pair forces which are used together with conditional reversible work (CRW) conservative forces in dissipative particle dynamics (DPD) simulations. The combined CRW-DPD approach aims to extend the representability of CRW models to dynamic properties and uses a bottom-up approach. Dissipative pair forces are derived frommore » fluctuations of the direct atomistic forces between mapped groups. The conservative CRW potential is obtained from a similar series of constraint dynamics simulations and represents the reversible work performed to couple the direct atomistic interactions between the mapped atom groups. Neopentane, tetrachloromethane, cyclohexane, and n-hexane have been considered as model systems. These molecular liquids are simulated with atomistic molecular dynamics, coarse-grained molecular dynamics, and DPD. We find that the CRW-DPD models reproduce the liquid structure and diffusive dynamics of the liquid systems in reasonable agreement with the atomistic models when using single-site mapping schemes with beads containing five or six heavy atoms. For a two-site representation of n-hexane (3 carbons per bead), time scale separation can no longer be assumed and the DPD approach consequently fails to reproduce the atomistic dynamics.« less

Critical point relascope sampling for unbiased volume estimation of downed coarse woody debris

Treesearch

Jeffrey H. Gove; Michael S. Williams; Mark J. Ducey; Mark J. Ducey

2005-01-01

Critical point relascope sampling is developed and shown to be design-unbiased for the estimation of log volume when used with point relascope sampling for downed coarse woody debris. The method is closely related to critical height sampling for standing trees when trees are first sampled with a wedge prism. Three alternative protocols for determining the critical...

Retransformation bias in a stem profile model

Treesearch

Raymond L. Czaplewski; David Bruce

1990-01-01

An unbiased profile model, fit to diameter divided by diameter at breast height, overestimated volume of 5.3-m log sections by 0.5 to 3.5%. Another unbiased profile model, fit to squared diameter divided by squared diameter at breast height, underestimated bole diameters by 0.2 to 2.1%. These biases are caused by retransformation of the predicted dependent variable;...

Unbiased nonorthogonal bases for tomographic reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sainz, Isabel; Klimov, Andrei B.; Roa, Luis

2010-05-15

We have developed a general method for constructing a set of nonorthogonal bases with equal separations between all different basis states in prime dimensions. The results are that the corresponding biorthogonal counterparts are pairwise unbiased with the components of the original bases. Using these bases, we derive an explicit expression for the optimal tomography in nonorthogonal bases. A special two-dimensional case is analyzed separately.

Simultaneous unbiased estimates of multiple downed wood attributes in perpendicular distance sampling

Treesearch

Mark J. Ducey; Jeffrey H. Gove; Harry T. Valentine

2008-01-01

Perpendicular distance sampling (PDS) is a fast probability-proportional-to-size method for inventory of downed wood. However, previous development of PDS had limited the method to estimating only one variable (such as volume per hectare, or surface area per hectare) at a time. Here, we develop a general design-unbiased estimator for PDS. We then show how that...

The dependability of medical students' performance ratings as documented on in-training evaluations.

PubMed

van Barneveld, Christina

2005-03-01

To demonstrate an approach to obtain an unbiased estimate of the dependability of students' performance ratings during training, when the data-collection design includes nesting of student in rater, unbalanced nest sizes, and dependent observations. In 2003, two variance components analyses of in-training evaluation (ITE) report data were conducted using urGENOVA software. In the first analysis, the dependability for the nested and unbalanced data-collection design was calculated. In the second analysis, an approach using multiple generalizability studies was used to obtain an unbiased estimate of the student variance component, resulting in an unbiased estimate of dependability. Results suggested that there is bias in estimates of the dependability of students' performance on ITEs that are attributable to the data-collection design. When the bias was corrected, the results indicated that the dependability of ratings of student performance was almost zero. The combination of the multiple generalizability studies method and the use of specialized software provides an unbiased estimate of the dependability of ratings of student performance on ITE scores for data-collection designs that include nesting of student in rater, unbalanced nest sizes, and dependent observations.

Elements of the cellular metabolic structure

PubMed Central

De la Fuente, Ildefonso M.

2015-01-01

A large number of studies have demonstrated the existence of metabolic covalent modifications in different molecular structures, which are able to store biochemical information that is not encoded by DNA. Some of these covalent mark patterns can be transmitted across generations (epigenetic changes). Recently, the emergence of Hopfield-like attractor dynamics has been observed in self-organized enzymatic networks, which have the capacity to store functional catalytic patterns that can be correctly recovered by specific input stimuli. Hopfield-like metabolic dynamics are stable and can be maintained as a long-term biochemical memory. In addition, specific molecular information can be transferred from the functional dynamics of the metabolic networks to the enzymatic activity involved in covalent post-translational modulation, so that determined functional memory can be embedded in multiple stable molecular marks. The metabolic dynamics governed by Hopfield-type attractors (functional processes), as well as the enzymatic covalent modifications of specific molecules (structural dynamic processes) seem to represent the two stages of the dynamical memory of cellular metabolism (metabolic memory). Epigenetic processes appear to be the structural manifestation of this cellular metabolic memory. Here, a new framework for molecular information storage in the cell is presented, which is characterized by two functionally and molecularly interrelated systems: a dynamic, flexible and adaptive system (metabolic memory) and an essentially conservative system (genetic memory). The molecular information of both systems seems to coordinate the physiological development of the whole cell. PMID:25988183

Achieving Rigorous Accelerated Conformational Sampling in Explicit Solvent.

PubMed

Doshi, Urmi; Hamelberg, Donald

2014-04-03

Molecular dynamics simulations can provide valuable atomistic insights into biomolecular function. However, the accuracy of molecular simulations on general-purpose computers depends on the time scale of the events of interest. Advanced simulation methods, such as accelerated molecular dynamics, have shown tremendous promise in sampling the conformational dynamics of biomolecules, where standard molecular dynamics simulations are nonergodic. Here we present a sampling method based on accelerated molecular dynamics in which rotatable dihedral angles and nonbonded interactions are boosted separately. This method (RaMD-db) is a different implementation of the dual-boost accelerated molecular dynamics, introduced earlier. The advantage is that this method speeds up sampling of the conformational space of biomolecules in explicit solvent, as the degrees of freedom most relevant for conformational transitions are accelerated. We tested RaMD-db on one of the most difficult sampling problems - protein folding. Starting from fully extended polypeptide chains, two fast folding α-helical proteins (Trpcage and the double mutant of C-terminal fragment of Villin headpiece) and a designed β-hairpin (Chignolin) were completely folded to their native structures in very short simulation time. Multiple folding/unfolding transitions could be observed in a single trajectory. Our results show that RaMD-db is a promisingly fast and efficient sampling method for conformational transitions in explicit solvent. RaMD-db thus opens new avenues for understanding biomolecular self-assembly and functional dynamics occurring on long time and length scales.

Solution NMR structure of a designed metalloprotein and complementary molecular dynamics refinement.

PubMed

Calhoun, Jennifer R; Liu, Weixia; Spiegel, Katrin; Dal Peraro, Matteo; Klein, Michael L; Valentine, Kathleen G; Wand, A Joshua; DeGrado, William F

2008-02-01

We report the solution NMR structure of a designed dimetal-binding protein, di-Zn(II) DFsc, along with a secondary refinement step employing molecular dynamics techniques. Calculation of the initial NMR structural ensemble by standard methods led to distortions in the metal-ligand geometries at the active site. Unrestrained molecular dynamics using a nonbonded force field for the metal shell, followed by quantum mechanical/molecular mechanical dynamics of DFsc, were used to relax local frustrations at the dimetal site that were apparent in the initial NMR structure and provide a more realistic description of the structure. The MD model is consistent with NMR restraints, and in good agreement with the structural and functional properties expected for DF proteins. This work demonstrates that NMR structures of metalloproteins can be further refined using classical and first-principles molecular dynamics methods in the presence of explicit solvent to provide otherwise unavailable insight into the geometry of the metal center.

Is an intuitive convergence definition of molecular dynamics simulations solely based on the root mean square deviation possible?

PubMed

Knapp, B; Frantal, S; Cibena, M; Schreiner, W; Bauer, P

2011-08-01

Molecular dynamics is a commonly used technique in computational biology. One key issue of each molecular dynamics simulation is: When does this simulation reach equilibrium state? A widely used way to determine this is the visual and intuitive inspection of root mean square deviation (RMSD) plots of the simulation. Although this technique has been criticized several times, it is still often used. Therefore, we present a study proving that this method is not reliable at all. We conducted a survey with participants from the field in which we illustrated different RMSD plots to scientists in the field of molecular dynamics. These plots were randomized and repeated, using a statistical model and different variants of the plots. We show that there is no mutual consent about the point of equilibrium. The decisions are severely biased by different parameters. Therefore, we conclude that scientists should not discuss the equilibration of a molecular dynamics simulation on the basis of a RMSD plot.

Apparatus bias and place conditioning with ethanol in mice.

PubMed

Cunningham, Christopher L; Ferree, Nikole K; Howard, MacKenzie A

2003-12-01

Although the distinction between "biased" and "unbiased" is generally recognized as an important methodological issue in place conditioning, previous studies have not adequately addressed the distinction between a biased/unbiased apparatus and a biased/unbiased stimulus assignment procedure. Moreover, a review of the recent literature indicates that many reports (70% of 76 papers published in 2001) fail to provide adequate information about apparatus bias. This issue is important because the mechanisms underlying a drug's effect in the place-conditioning procedure may differ depending on whether the apparatus is biased or unbiased. The present studies were designed to assess the impact of apparatus bias and stimulus assignment procedure on ethanol-induced place conditioning in mice (DBA/2 J). A secondary goal was to compare various dependent variables commonly used to index conditioned place preference. Apparatus bias was manipulated by varying the combination of tactile (floor) cues available during preference tests. Experiment 1 used an unbiased apparatus in which the stimulus alternatives were equally preferred during a pre-test as indicated by the group average. Experiment 2 used a biased apparatus in which one of the stimuli was strongly preferred by most mice (mean % time on cue = 67%) during the pre-test. In both studies, the stimulus paired with drug (CS+) was assigned randomly (i.e., an "unbiased" stimulus assignment procedure). Experimental mice received four pairings of CS+ with ethanol (2 g/kg, i.p.) and four pairings of the alternative stimulus (CS-) with saline; control mice received saline on both types of trial. Each experiment concluded with a 60-min choice test. With the unbiased apparatus (experiment 1), significant place conditioning was obtained regardless of whether drug was paired with the subject's initially preferred or non-preferred stimulus. However, with the biased apparatus (experiment 2), place conditioning was apparent only when ethanol was paired with the initially non-preferred cue, and not when it was paired with the initially preferred cue. These conclusions held regardless of which dependent variable was used to index place conditioning, but only if the counterbalancing factor was included in statistical analyses. These studies indicate that apparatus bias plays a major role in determining whether biased assignment of an ethanol-paired stimulus affects ability to demonstrate conditioned place preference. Ethanol's ability to produce conditioned place preference in an unbiased apparatus, regardless of the direction of the initial cue bias, supports previous studies that interpret such findings as evidence of a primary rewarding drug effect. Moreover, these studies suggest that the asymmetrical outcome observed in the biased apparatus is most likely due to a measurement problem (e.g., ceiling effect) rather than to an interaction between the drug's effect and an unconditioned motivational response (e.g., "anxiety") to the initially non-preferred stimulus. More generally, these findings illustrate the importance of providing clear information on apparatus bias in all place-conditioning studies.

Development of a Computational Assay for the Estrogen Receptor

DTIC Science & Technology

2006-07-01

University Ashley Deline, Senior Thesis in chemistry, " Molecular Dynamic Simulations of a Glycoform and its Constituent Parts Related to Rheumatoid Arthritis...involves running a long molecular dynamics (MD) simulation of the uncoupled receptor in order to sample the protein’s unique conformations. The second...Receptor binding domain. * Performed several long molecular dynamics simulations (800 ps - 3 ns) on the ligand-ER system using ligands with known

In Silico Design of Smart Binders to Anthrax PA

DTIC Science & Technology

2012-09-01

nanosecond(ns) molecular dynamics simulation in the NPT ensemble (constant particle number, pressure, and temperature) at 300K, with the CHARMM force...protective antigen (PA). Before the docking runs, the DS23 peptide was simulated using molecular dynamics to generate an ensemble of structures...structure), we do not see a large amount of structural change when using molecular dynamics after Rosetta docking. We note that this RMSD does not take

In Silico Analyses of Substrate Interactions with Human Serum Paraoxonase 1

DTIC Science & Technology

2008-01-01

substrate interactions of HuPON1 remains elusive. In this study, we apply homology modeling, docking, and molecular dynamic (MD) simulations to probe the...mod- eling; docking; molecular dynamics simulations ; binding free energy decomposition. 486 PROTEINS Published 2008 WILEY-LISS, INC. yThis article is a...apply homology modeling, docking, and molecular dynamic (MD) simulations to probe the binding interactions of HuPON1 with representative substrates. The

Predictions of Crystal Structures from First Principles

DTIC Science & Technology

2007-06-01

RDX crystal in hoped that the problem could be resolved by the molecular dynamics simulations . The fully ab initio development of density functional... Molecular Dynamics Simulations of RDX i.e., without any use of experimental results (except that Crystal the geometry of monomers was derived from X-ray...applied in molecular dynamics simulations of the RDX system, due to its size, is intractable by any high-level ab crystal. We performed isothermal

Coarse-Grained Lattice Model Simulations of Sequence-Structure Fitness of a Ribosome-Inactivating Protein

DTIC Science & Technology

2007-11-05

limits of what is considered practical when applying all-atom molecular - dynamics simulation methods. Lattice models provide computationally robust...of expectation values from the density of states. All-atom molecular - dynamics simulations provide the most rigorous sampling method to generate con... molecular - dynamics simulations of protein folding,6–9 reported studies of computing a heat capacity or other calorimetric observables have been limited to

Molecular dynamics simulations: advances and applications

PubMed Central

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

Molecular dynamics simulation of β₂-microglobulin in denaturing and stabilizing conditions.

PubMed

Fogolari, Federico; Corazza, Alessandra; Varini, Nicola; Rotter, Matteo; Gumral, Devrim; Codutti, Luca; Rennella, Enrico; Viglino, Paolo; Bellotti, Vittorio; Esposito, Gennaro

2011-03-01

β₂-Microglobulin has been a model system for the study of fibril formation for 20 years. The experimental study of β₂-microglobulin structure, dynamics, and thermodynamics in solution, at atomic detail, along the pathway leading to fibril formation is difficult because the onset of disorder and aggregation prevents signal resolution in Nuclear Magnetic Resonance experiments. Moreover, it is difficult to characterize conformers in exchange equilibrium. To gain insight (at atomic level) on processes for which experimental information is available at molecular or supramolecular level, molecular dynamics simulations have been widely used in the last decade. Here, we use molecular dynamics to address three key aspects of β₂-microglobulin, which are known to be relevant to amyloid formation: (1) 60 ns molecular dynamics simulations of β₂-microglobulin in trifluoroethanol and in conditions mimicking low pH are used to study the behavior of the protein in environmental conditions that are able to trigger amyloid formation; (2) adaptive biasing force molecular dynamics simulation is used to force cis-trans isomerization at Proline 32 and to calculate the relative free energy in the folded and unfolded state. The native-like trans-conformer (known as intermediate 2 and determining the slow phase of refolding), is simulated for 10 ns, detailing the possible link between cis-trans isomerization and conformational disorder; (3) molecular dynamics simulation of highly concentrated doxycycline (a molecule able to suppress fibril formation) in the presence of β₂-microglobulin provides details of the binding modes of the drug and a rationale for its effect. Copyright © 2010 Wiley-Liss, Inc.

Thermalization dynamics in a quenched many-body state

NASA Astrophysics Data System (ADS)

Kaufman, Adam; Preiss, Philipp; Tai, Eric; Lukin, Alex; Rispoli, Matthew; Schittko, Robert; Greiner, Markus

2016-05-01

Quantum and classical many-body systems appear to have disparate behavior due to the different mechanisms that govern their evolution. The dynamics of a classical many-body system equilibrate to maximally entropic states and quickly re-thermalize when perturbed. The assumptions of ergodicity and unbiased configurations lead to a successful framework of describing classical systems by a sampling of thermal ensembles that are blind to the system's microscopic details. By contrast, an isolated quantum many-body system is governed by unitary evolution: the system retains memory of past dynamics and constant global entropy. However, even with differing characteristics, the long-term behavior for local observables in quenched, non-integrable quantum systems are often well described by the same thermal framework. We explore the onset of this convergence in a many-body system of bosonic atoms in an optical lattice. Our system's finite size allows us to verify full state purity and measure local observables. We observe rapid growth and saturation of the entanglement entropy with constant global purity. The combination of global purity and thermalized local observables agree with the Eigenstate Thermalization Hypothesis in the presence of a near-volume law in the entanglement entropy.

Capturing inertial particle transport in turbulent flows

NASA Astrophysics Data System (ADS)

Stott, Harry; Lawrie, Andrew; Szalai, Robert

2017-11-01

The natural world is replete with examples of particle advection; mankind is both a beneficiary from and sufferer of the consequences. As such, the study of inertial particle dynamics, both aerosol and bubble, is vitally important. In many interesting examples such as cloud microphysics, sedimentation, or sewage transport, many millions of particles are advected in a relatively small volume of fluid. It is impossible to model these processes computationally and simulate every particle. Instead, we advect the probability density field of particle positions allowing unbiased sampling of particle behaviour across the domain. Given a 3-dimensional space discretised into cubes, we construct a transport operator that encodes the flow of particles through the faces of the cubes. By assuming that the dynamics of the particles lie close to an inertial manifold, it is possible to preserve the majority of the inertial properties of the particles between the time steps. We demonstrate the practical use of this method in a pair of instances: the first is an analogue to cloud microphysics- the turbulent breakdown of Taylor Green vortices; the second example is the case of a turbulent jet which has application both in sewage pipe outflow and pesticide spray dynamics. EPSRC.

Modeling structured population dynamics using data from unmarked individuals

USGS Publications Warehouse

Grant, Evan H. Campbell; Zipkin, Elise; Thorson, James T.; See, Kevin; Lynch, Heather J.; Kanno, Yoichiro; Chandler, Richard; Letcher, Benjamin H.; Royle, J. Andrew

2014-01-01

The study of population dynamics requires unbiased, precise estimates of abundance and vital rates that account for the demographic structure inherent in all wildlife and plant populations. Traditionally, these estimates have only been available through approaches that rely on intensive mark–recapture data. We extended recently developed N-mixture models to demonstrate how demographic parameters and abundance can be estimated for structured populations using only stage-structured count data. Our modeling framework can be used to make reliable inferences on abundance as well as recruitment, immigration, stage-specific survival, and detection rates during sampling. We present a range of simulations to illustrate the data requirements, including the number of years and locations necessary for accurate and precise parameter estimates. We apply our modeling framework to a population of northern dusky salamanders (Desmognathus fuscus) in the mid-Atlantic region (USA) and find that the population is unexpectedly declining. Our approach represents a valuable advance in the estimation of population dynamics using multistate data from unmarked individuals and should additionally be useful in the development of integrated models that combine data from intensive (e.g., mark–recapture) and extensive (e.g., counts) data sources.

Inherent conformational flexibility of F1-ATPase α-subunit.

PubMed

Hahn-Herrera, Otto; Salcedo, Guillermo; Barril, Xavier; García-Hernández, Enrique

2016-09-01

The core of F1-ATPase consists of three catalytic (β) and three noncatalytic (α) subunits, forming a hexameric ring in alternating positions. A wealth of experimental and theoretical data has provided a detailed picture of the complex role played by catalytic subunits. Although major conformational changes have only been seen in β-subunits, it is clear that α-subunits have to respond to these changes in order to be able to transmit information during the rotary mechanism. However, the conformational behavior of α-subunits has not been explored in detail. Here, we have combined unbiased molecular dynamics (MD) simulations and calorimetrically measured thermodynamic signatures to investigate the conformational flexibility of isolated α-subunits, as a step toward deepening our understanding of its function inside the α3β3 ring. The simulations indicate that the open-to-closed conformational transition of the α-subunit is essentially barrierless, which is ideal to accompany and transmit the movement of the catalytic subunits. Calorimetric measurements of the recombinant α-subunit from Geobacillus kaustophilus indicate that the isolated subunit undergoes no significant conformational changes upon nucleotide binding. Simulations confirm that the nucleotide-free and nucleotide-bound subunits show average conformations similar to that observed in the F1 crystal structure, but they reveal an increased conformational flexibility of the isolated α-subunit upon MgATP binding, which might explain the evolutionary conserved capacity of α-subunits to recognize nucleotides with considerable strength. Furthermore, we elucidate the different dependencies that α- and β-subunits show on Mg(II) for recognizing ATP. Copyright © 2016 Elsevier B.V. All rights reserved.

Multiwavelength Studies of Dual AGN in the Swift/BAT Sample

NASA Astrophysics Data System (ADS)

Treister, Ezequiel; Privon, George; Sartori, Lia; Nagar, Neil; Bauer, Franz Erik; Schawinski, Kevin; Ricci, Claudio; U, Vivian; Comerford, Julie; Muller-Sanchez, Francisco; Evans, Aaron; Koss, Michael; Sanders, David B.; Urry, Meg; MODA Collaboration

2018-01-01

For the last 30 years there has been growing evidence for a strong connection between major galaxy mergers and simultaneous episodes ofstrong star formation and signicant central supermassive black hole (SMBH) growth. A natural consequence of this scenario is that dual Active Galactic Nuclei (AGN), i.e., systems in which the two nuclear SMBHs are growing simultaneously at separations <10 kpc should be relatively common. This particular stage in a major galaxy merger, albeit short at ~hundreds Myears, is very relevant for galaxy evolution.Here we present the first results from an ongoing survey aimed to study the multiwavelength properties of the dual AGN in the neary universe, z<0.1 selected from mostly-unbiased observations at hard X-rays, E>10 keV, obtained from the Swift-BAT extragalactic survey and complemented by NuSTAR observations. Our work focuses on the study of the physical properties of the ionized, atomic and molecular gas and the dust in confirmed dual AGN by combining observations with ALMA, VLT/MUSE and SINFONI and Keck/OSIRIS among others. In addition to providing general properties of this poulation, we will further focus on two remarkable systems, NGC6240 and Mrk 463. Both systems show evidence of large kpc-scale tidal features, complex gas dynamics and kinematical evidence for both inflows and outflows.These results clearly show the importance of performing high resolution multi wavelength studies covering kpc scales in order to understandthe complex connection between black hole growth and galaxy evolution in this critical phase.Support from this work has been provided by CONICYT FONDECYT 1160999 and PFB-06/2007.

A normal mode-based geometric simulation approach for exploring biologically relevant conformational transitions in proteins.

PubMed

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.

Evidence for an allosteric mechanism of substrate release from membrane-transporter accessory binding proteins.

PubMed

Marinelli, Fabrizio; Kuhlmann, Sonja I; Grell, Ernst; Kunte, Hans-Jörg; Ziegler, Christine; Faraldo-Gómez, José D

2011-12-06

Numerous membrane importers rely on accessory water-soluble proteins to capture their substrates. These substrate-binding proteins (SBP) have a strong affinity for their ligands; yet, substrate release onto the low-affinity membrane transporter must occur for uptake to proceed. It is generally accepted that release is facilitated by the association of SBP and transporter, upon which the SBP adopts a conformation similar to the unliganded state, whose affinity is sufficiently reduced. Despite the appeal of this mechanism, however, direct supporting evidence is lacking. Here, we use experimental and theoretical methods to demonstrate that an allosteric mechanism of enhanced substrate release is indeed plausible. First, we report the atomic-resolution structure of apo TeaA, the SBP of the Na(+)-coupled ectoine TRAP transporter TeaBC from Halomonas elongata DSM2581(T), and compare it with the substrate-bound structure previously reported. Conformational free-energy landscape calculations based upon molecular dynamics simulations are then used to dissect the mechanism that couples ectoine binding to structural change in TeaA. These insights allow us to design a triple mutation that biases TeaA toward apo-like conformations without directly perturbing the binding cleft, thus mimicking the influence of the membrane transporter. Calorimetric measurements demonstrate that the ectoine affinity of the conformationally biased triple mutant is 100-fold weaker than that of the wild type. By contrast, a control mutant predicted to be conformationally unbiased displays wild-type affinity. This work thus demonstrates that substrate release from SBPs onto their membrane transporters can be facilitated by the latter through a mechanism of allosteric modulation of the former.

Spectral Rate Theory for Two-State Kinetics

NASA Astrophysics Data System (ADS)

Prinz, Jan-Hendrik; Chodera, John D.; Noé, Frank

2014-02-01

Classical rate theories often fail in cases where the observable(s) or order parameter(s) used is a poor reaction coordinate or the observed signal is deteriorated by noise, such that no clear separation between reactants and products is possible. Here, we present a general spectral two-state rate theory for ergodic dynamical systems in thermal equilibrium that explicitly takes into account how the system is observed. The theory allows the systematic estimation errors made by standard rate theories to be understood and quantified. We also elucidate the connection of spectral rate theory with the popular Markov state modeling approach for molecular simulation studies. An optimal rate estimator is formulated that gives robust and unbiased results even for poor reaction coordinates and can be applied to both computer simulations and single-molecule experiments. No definition of a dividing surface is required. Another result of the theory is a model-free definition of the reaction coordinate quality. The reaction coordinate quality can be bounded from below by the directly computable observation quality, thus providing a measure allowing the reaction coordinate quality to be optimized by tuning the experimental setup. Additionally, the respective partial probability distributions can be obtained for the reactant and product states along the observed order parameter, even when these strongly overlap. The effects of both filtering (averaging) and uncorrelated noise are also examined. The approach is demonstrated on numerical examples and experimental single-molecule force-probe data of the p5ab RNA hairpin and the apo-myoglobin protein at low pH, focusing here on the case of two-state kinetics.

A Novel Bifunctional Alkylphenol Anesthetic Allows Characterization of γ-Aminobutyric Acid, Type A (GABAA), Receptor Subunit Binding Selectivity in Synaptosomes*

PubMed Central

Woll, Kellie A.; Murlidaran, Sruthi; Pinch, Benika J.; Hénin, Jérôme; Wang, Xiaoshi; Salari, Reza; Covarrubias, Manuel; Dailey, William P.; Brannigan, Grace; Garcia, Benjamin A.; Eckenhoff, Roderic G.

2016-01-01

Propofol, an intravenous anesthetic, is a positive modulator of the GABAA receptor, but the mechanistic details, including the relevant binding sites and alternative targets, remain disputed. Here we undertook an in-depth study of alkylphenol-based anesthetic binding to synaptic membranes. We designed, synthesized, and characterized a chemically active alkylphenol anesthetic (2-((prop-2-yn-1-yloxy)methyl)-5-(3-(trifluoromethyl)-3H-diazirin-3-yl)phenol, AziPm-click (1)), for affinity-based protein profiling (ABPP) of propofol-binding proteins in their native state within mouse synaptosomes. The ABPP strategy captured ∼4% of the synaptosomal proteome, including the unbiased capture of five α or β GABAA receptor subunits. Lack of γ2 subunit capture was not due to low abundance. Consistent with this, independent molecular dynamics simulations with alchemical free energy perturbation calculations predicted selective propofol binding to interfacial sites, with higher affinities for α/β than γ-containing interfaces. The simulations indicated hydrogen bonding is a key component leading to propofol-selective binding within GABAA receptor subunit interfaces, with stable hydrogen bonds observed between propofol and α/β cavity residues but not γ cavity residues. We confirmed this by introducing a hydrogen bond-null propofol analogue as a protecting ligand for targeted-ABPP and observed a lack of GABAA receptor subunit protection. This investigation demonstrates striking interfacial GABAA receptor subunit selectivity in the native milieu, suggesting that asymmetric occupancy of heteropentameric ion channels by alkylphenol-based anesthetics is sufficient to induce modulation of activity. PMID:27462076

An Electrostatic Funnel in the GABA-Binding Pathway

PubMed Central

Lightstone, Felice C.

2016-01-01

The γ-aminobutyric acid type A receptor (GABAA-R) is a major inhibitory neuroreceptor that is activated by the binding of GABA. The structure of the GABAA-R is well characterized, and many of the binding site residues have been identified. However, most of these residues are obscured behind the C-loop that acts as a cover to the binding site. Thus, the mechanism by which the GABA molecule recognizes the binding site, and the pathway it takes to enter the binding site are both unclear. Through the completion and detailed analysis of 100 short, unbiased, independent molecular dynamics simulations, we have investigated this phenomenon of GABA entering the binding site. In each system, GABA was placed quasi-randomly near the binding site of a GABAA-R homology model, and atomistic simulations were carried out to observe the behavior of the GABA molecules. GABA fully entered the binding site in 19 of the 100 simulations. The pathway taken by these molecules was consistent and non-random; the GABA molecules approach the binding site from below, before passing up behind the C-loop and into the binding site. This binding pathway is driven by long-range electrostatic interactions, whereby the electrostatic field acts as a ‘funnel’ that sweeps the GABA molecules towards the binding site, at which point more specific atomic interactions take over. These findings define a nuanced mechanism whereby the GABAA-R uses the general zwitterionic features of the GABA molecule to identify a potential ligand some 2 nm away from the binding site. PMID:27119953

LLSURE: local linear SURE-based edge-preserving image filtering.

PubMed

Qiu, Tianshuang; Wang, Aiqi; Yu, Nannan; Song, Aimin

2013-01-01

In this paper, we propose a novel approach for performing high-quality edge-preserving image filtering. Based on a local linear model and using the principle of Stein's unbiased risk estimate as an estimator for the mean squared error from the noisy image only, we derive a simple explicit image filter which can filter out noise while preserving edges and fine-scale details. Moreover, this filter has a fast and exact linear-time algorithm whose computational complexity is independent of the filtering kernel size; thus, it can be applied to real time image processing tasks. The experimental results demonstrate the effectiveness of the new filter for various computer vision applications, including noise reduction, detail smoothing and enhancement, high dynamic range compression, and flash/no-flash denoising.

DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

NASA Astrophysics Data System (ADS)

Wang, Han; Zhang, Linfeng; Han, Jiequn; E, Weinan

2018-07-01

Recent developments in many-body potential energy representation via deep learning have brought new hopes to addressing the accuracy-versus-efficiency dilemma in molecular simulations. Here we describe DeePMD-kit, a package written in Python/C++ that has been designed to minimize the effort required to build deep learning based representation of potential energy and force field and to perform molecular dynamics. Potential applications of DeePMD-kit span from finite molecules to extended systems and from metallic systems to chemically bonded systems. DeePMD-kit is interfaced with TensorFlow, one of the most popular deep learning frameworks, making the training process highly automatic and efficient. On the other end, DeePMD-kit is interfaced with high-performance classical molecular dynamics and quantum (path-integral) molecular dynamics packages, i.e., LAMMPS and the i-PI, respectively. Thus, upon training, the potential energy and force field models can be used to perform efficient molecular simulations for different purposes. As an example of the many potential applications of the package, we use DeePMD-kit to learn the interatomic potential energy and forces of a water model using data obtained from density functional theory. We demonstrate that the resulted molecular dynamics model reproduces accurately the structural information contained in the original model.

Theory of attosecond delays in molecular photoionization.

PubMed

Baykusheva, Denitsa; Wörner, Hans Jakob

2017-03-28

We present a theoretical formalism for the calculation of attosecond delays in molecular photoionization. It is shown how delays relevant to one-photon-ionization, also known as Eisenbud-Wigner-Smith delays, can be obtained from the complex dipole matrix elements provided by molecular quantum scattering theory. These results are used to derive formulae for the delays measured by two-photon attosecond interferometry based on an attosecond pulse train and a dressing femtosecond infrared pulse. These effective delays are first expressed in the molecular frame where maximal information about the molecular photoionization dynamics is available. The effects of averaging over the emission direction of the electron and the molecular orientation are introduced analytically. We illustrate this general formalism for the case of two polyatomic molecules. N 2 O serves as an example of a polar linear molecule characterized by complex photoionization dynamics resulting from the presence of molecular shape resonances. H 2 O illustrates the case of a non-linear molecule with comparably simple photoionization dynamics resulting from a flat continuum. Our theory establishes the foundation for interpreting measurements of the photoionization dynamics of all molecules by attosecond metrology.

Modern applications of terahertz emission spectroscopy

NASA Astrophysics Data System (ADS)

Harrel, Shayne Matthew

Terahertz (THz) emission spectroscopy (TES) is newly developed experimental technique capable of measuring ultrafast dynamics in a variety of systems. Unlike pump-probe spectroscopies where the signals are obtained indirectly, the THz waveform emitted by the dynamical process serves as the signal field. Information about processes involving a time-dependent magnetization, polarization or current is obtained using TES. The detection scheme is polarization sensitive and allows the direction of the dynamical event to be recovered. The role of solvation on intramolecular charge transfer in DMANS (4-(dimethylamino)-4'-nitrostilbene) is studied using TES in three solvents: benzene, toluene, and 1,3-dichlorobenzene. These solvents have similar molecular structures but different polarities and dielectric constants. The charge transfer dynamics are found to depend on the solvent. A secondary feature in the THz emission appearing 4-6 Ps after the main pulse provides evidence that DMANS may undergo a twisted intramolecular charge transfer state (TICT) upon photoexcitation. The ultrafast magnetization dynamics of polycrystalline Ni and single Fe films ranging in thickness from 5 nm to 60 nm are reported using TES. For samples thicker than the visible optical skin depth, (˜10 nm for Ni and ˜27 nm for Fe), the emission is easily interpreted using Lenz's law. For films thinner than visible optical skin depth, the emission patterns are qualitatively different. These results suggest that there are two generation mechanisms at work: one that arises purely from bulk demagnetization in the thick sample limit and another that is the result of difference frequency generation enhanced by the magnetized surface. A comparative study of the magnetization dynamics of a 40 nm Ni and 40 Fe film shows that the magnetization recovers faster in Fe than in Ni. The dependence of optical rectification and shift currents in unbiased GaAs (111) is reported using TES. It is found that the dependence of the emission with respect to linear excitation polarization is well described by theory. The emission with respect to elliptical polarization also agrees well with theory when exciting below and far above the bandgap. However, the THz emission when exciting slightly above the bandgap is strongly influenced by spin-polarized electrons. The magnetic field generated by these spin-polarized electrons is responsible for altering their own trajectories via the self-induced Hall effect. The dependence of THz generation mechanisms in ZnTe (110) on excitation intensity is investigated using TES. Optical rectification is found to be the dominant generation mechanism only at the lowest excitation powers (<5 mW). A model of second harmonic induced shift currents generating THz radiation is unable to explain the emissions at higher excitation powers.

Propagation of kinetic uncertainties through a canonical topology of the TLR4 signaling network in different regions of biochemical reaction space

PubMed Central

2010-01-01

Background Signal transduction networks represent the information processing systems that dictate which dynamical regimes of biochemical activity can be accessible to a cell under certain circumstances. One of the major concerns in molecular systems biology is centered on the elucidation of the robustness properties and information processing capabilities of signal transduction networks. Achieving this goal requires the establishment of causal relations between the design principle of biochemical reaction systems and their emergent dynamical behaviors. Methods In this study, efforts were focused in the construction of a relatively well informed, deterministic, non-linear dynamic model, accounting for reaction mechanisms grounded on standard mass action and Hill saturation kinetics, of the canonical reaction topology underlying Toll-like receptor 4 (TLR4)-mediated signaling events. This signaling mechanism has been shown to be deployed in macrophages during a relatively short time window in response to lypopolysaccharyde (LPS) stimulation, which leads to a rapidly mounted innate immune response. An extensive computational exploration of the biochemical reaction space inhabited by this signal transduction network was performed via local and global perturbation strategies. Importantly, a broad spectrum of biologically plausible dynamical regimes accessible to the network in widely scattered regions of parameter space was reconstructed computationally. Additionally, experimentally reported transcriptional readouts of target pro-inflammatory genes, which are actively modulated by the network in response to LPS stimulation, were also simulated. This was done with the main goal of carrying out an unbiased statistical assessment of the intrinsic robustness properties of this canonical reaction topology. Results Our simulation results provide convincing numerical evidence supporting the idea that a canonical reaction mechanism of the TLR4 signaling network is capable of performing information processing in a robust manner, a functional property that is independent of the signaling task required to be executed. Nevertheless, it was found that the robust performance of the network is not solely determined by its design principle (topology), but this may be heavily dependent on the network's current position in biochemical reaction space. Ultimately, our results enabled us the identification of key rate limiting steps which most effectively control the performance of the system under diverse dynamical regimes. Conclusions Overall, our in silico study suggests that biologically relevant and non-intuitive aspects on the general behavior of a complex biomolecular network can be elucidated only when taking into account a wide spectrum of dynamical regimes attainable by the system. Most importantly, this strategy provides the means for a suitable assessment of the inherent variational constraints imposed by the structure of the system when systematically probing its parameter space. PMID:20230643

Molecular Dynamics Simulations of Simple Liquids

ERIC Educational Resources Information Center

Speer, Owner F.; Wengerter, Brian C.; Taylor, Ramona S.

2004-01-01

An experiment, in which students were given the opportunity to perform molecular dynamics simulations on a series of molecular liquids using the Amber suite of programs, is presented. They were introduced to both physical theories underlying classical mechanics simulations and to the atom-atom pair distribution function.

Reply to ''Comment on 'Mutually unbiased bases, orthogonal Latin squares, and hidden-variable models'''

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paterek, Tomasz; Dakic, Borivoje; Brukner, Caslav

In this Reply to the preceding Comment by Hall and Rao [Phys. Rev. A 83, 036101 (2011)], we motivate terminology of our original paper and point out that further research is needed in order to (dis)prove the claimed link between every orthogonal Latin square of order being a power of a prime and a mutually unbiased basis.

27ps DFT Molecular Dynamics Simulation of a-maltose: A Reduced Basis Set Study.

USDA-ARS?s Scientific Manuscript database

DFT molecular dynamics simulations are time intensive when carried out on carbohydrates such as alpha-maltose, requiring up to three or more weeks on a fast 16-processor computer to obtain just 5ps of constant energy dynamics. In a recent publication [1] forces for dynamics were generated from B3LY...

Diffusive molecular dynamics simulations of lithiation of silicon nanopillars

NASA Astrophysics Data System (ADS)

Mendez, J. P.; Ponga, M.; Ortiz, M.

2018-06-01

We report diffusive molecular dynamics simulations concerned with the lithiation of Si nano-pillars, i.e., nano-sized Si rods held at both ends by rigid supports. The duration of the lithiation process is of the order of milliseconds, well outside the range of molecular dynamics but readily accessible to diffusive molecular dynamics. The simulations predict an alloy Li15Si4 at the fully lithiated phase, exceedingly large and transient volume increments up to 300% due to the weakening of Sisbnd Si iterations, a crystalline-to-amorphous-to-lithiation phase transition governed by interface kinetics, high misfit strains and residual stresses resulting in surface cracks and severe structural degradation in the form of extensive porosity, among other effects.

Statistical errors in molecular dynamics averages

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schiferl, S.K.; Wallace, D.C.

1985-11-15

A molecular dynamics calculation produces a time-dependent fluctuating signal whose average is a thermodynamic quantity of interest. The average of the kinetic energy, for example, is proportional to the temperature. A procedure is described for determining when the molecular dynamics system is in equilibrium with respect to a given variable, according to the condition that the mean and the bandwidth of the signal should be sensibly constant in time. Confidence limits for the mean are obtained from an analysis of a finite length of the equilibrium signal. The role of serial correlation in this analysis is discussed. The occurence ofmore » unstable behavior in molecular dynamics data is noted, and a statistical test for a level shift is described.« less

Sampling of Protein Folding Transitions: Multicanonical Versus Replica Exchange Molecular Dynamics.

PubMed

Jiang, Ping; Yaşar, Fatih; Hansmann, Ulrich H E

2013-08-13

We compare the efficiency of multicanonical and replica exchange molecular dynamics for the sampling of folding/unfolding events in simulations of proteins with end-to-end β -sheet. In Go-model simulations of the 75-residue MNK6, we observe improvement factors of 30 in the number of folding/unfolding events of multicanonical molecular dynamics over replica exchange molecular dynamics. As an application, we use this enhanced sampling to study the folding landscape of the 36-residue DS119 with an all-atom physical force field and implicit solvent. Here, we find that the rate-limiting step is the formation of the central helix that then provides a scaffold for the parallel β -sheet formed by the two chain ends.

Gromita: a fully integrated graphical user interface to gromacs 4.

PubMed

Sellis, Diamantis; Vlachakis, Dimitrios; Vlassi, Metaxia

2009-09-07

Gromita is a fully integrated and efficient graphical user interface (GUI) to the recently updated molecular dynamics suite Gromacs, version 4. Gromita is a cross-platform, perl/tcl-tk based, interactive front end designed to break the command line barrier and introduce a new user-friendly environment to run molecular dynamics simulations through Gromacs. Our GUI features a novel workflow interface that guides the user through each logical step of the molecular dynamics setup process, making it accessible to both advanced and novice users. This tool provides a seamless interface to the Gromacs package, while providing enhanced functionality by speeding up and simplifying the task of setting up molecular dynamics simulations of biological systems. Gromita can be freely downloaded from http://bio.demokritos.gr/gromita/.

Evidence of Adaptive Evolution and Relaxed Constraints in Sex-Biased Genes of South American and West Indies Fruit Flies (Diptera: Tephritidae).

PubMed

Congrains, Carlos; Campanini, Emeline B; Torres, Felipe R; Rezende, Víctor B; Nakamura, Aline M; de Oliveira, Janaína L; Lima, André L A; Chahad-Ehlers, Samira; Sobrinho, Iderval S; de Brito, Reinaldo A

2018-01-01

Several studies have demonstrated that genes differentially expressed between sexes (sex-biased genes) tend to evolve faster than unbiased genes, particularly in males. The reason for this accelerated evolution is not clear, but several explanations have involved adaptive and nonadaptive mechanisms. Furthermore, the differences of sex-biased expression patterns of closely related species are also little explored out of Drosophila. To address the evolutionary processes involved with sex-biased expression in species with incipient differentiation, we analyzed male and female transcriptomes of Anastrepha fraterculus and Anastrepha obliqua, a pair of species that have diverged recently, likely in the presence of gene flow. Using these data, we inferred differentiation indexes and evolutionary rates and tested for signals of selection in thousands of genes expressed in head and reproductive transcriptomes from both species. Our results indicate that sex-biased and reproductive-biased genes evolve faster than unbiased genes in both species, which is due to both adaptive pressure and relaxed constraints. Furthermore, among male-biased genes evolving under positive selection, we identified some related to sexual functions such as courtship behavior and fertility. These findings suggest that sex-biased genes may have played important roles in the establishment of reproductive isolation between these species, due to a combination of selection and drift, and unveil a plethora of genetic markers useful for more studies in these species and their differentiation. © The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

A detailed comparison of analysis processes for MCC-IMS data in disease classification—Automated methods can replace manual peak annotations

PubMed Central

Horsch, Salome; Kopczynski, Dominik; Kuthe, Elias; Baumbach, Jörg Ingo; Rahmann, Sven

2017-01-01

Motivation Disease classification from molecular measurements typically requires an analysis pipeline from raw noisy measurements to final classification results. Multi capillary column—ion mobility spectrometry (MCC-IMS) is a promising technology for the detection of volatile organic compounds in the air of exhaled breath. From raw measurements, the peak regions representing the compounds have to be identified, quantified, and clustered across different experiments. Currently, several steps of this analysis process require manual intervention of human experts. Our goal is to identify a fully automatic pipeline that yields competitive disease classification results compared to an established but subjective and tedious semi-manual process. Method We combine a large number of modern methods for peak detection, peak clustering, and multivariate classification into analysis pipelines for raw MCC-IMS data. We evaluate all combinations on three different real datasets in an unbiased cross-validation setting. We determine which specific algorithmic combinations lead to high AUC values in disease classifications across the different medical application scenarios. Results The best fully automated analysis process achieves even better classification results than the established manual process. The best algorithms for the three analysis steps are (i) SGLTR (Savitzky-Golay Laplace-operator filter thresholding regions) and LM (Local Maxima) for automated peak identification, (ii) EM clustering (Expectation Maximization) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) for the clustering step and (iii) RF (Random Forest) for multivariate classification. Thus, automated methods can replace the manual steps in the analysis process to enable an unbiased high throughput use of the technology. PMID:28910313

Genomic Prediction for Quantitative Traits Is Improved by Mapping Variants to Gene Ontology Categories in Drosophila melanogaster

PubMed Central

Edwards, Stefan M.; Sørensen, Izel F.; Sarup, Pernille; Mackay, Trudy F. C.; Sørensen, Peter

2016-01-01

Predicting individual quantitative trait phenotypes from high-resolution genomic polymorphism data is important for personalized medicine in humans, plant and animal breeding, and adaptive evolution. However, this is difficult for populations of unrelated individuals when the number of causal variants is low relative to the total number of polymorphisms and causal variants individually have small effects on the traits. We hypothesized that mapping molecular polymorphisms to genomic features such as genes and their gene ontology categories could increase the accuracy of genomic prediction models. We developed a genomic feature best linear unbiased prediction (GFBLUP) model that implements this strategy and applied it to three quantitative traits (startle response, starvation resistance, and chill coma recovery) in the unrelated, sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel. Our results indicate that subsetting markers based on genomic features increases the predictive ability relative to the standard genomic best linear unbiased prediction (GBLUP) model. Both models use all markers, but GFBLUP allows differential weighting of the individual genetic marker relationships, whereas GBLUP weighs the genetic marker relationships equally. Simulation studies show that it is possible to further increase the accuracy of genomic prediction for complex traits using this model, provided the genomic features are enriched for causal variants. Our GFBLUP model using prior information on genomic features enriched for causal variants can increase the accuracy of genomic predictions in populations of unrelated individuals and provides a formal statistical framework for leveraging and evaluating information across multiple experimental studies to provide novel insights into the genetic architecture of complex traits. PMID:27235308

Quantum wavepacket ab initio molecular dynamics: an approach for computing dynamically averaged vibrational spectra including critical nuclear quantum effects.

PubMed

Sumner, Isaiah; Iyengar, Srinivasan S

2007-10-18

We have introduced a computational methodology to study vibrational spectroscopy in clusters inclusive of critical nuclear quantum effects. This approach is based on the recently developed quantum wavepacket ab initio molecular dynamics method that combines quantum wavepacket dynamics with ab initio molecular dynamics. The computational efficiency of the dynamical procedure is drastically improved (by several orders of magnitude) through the utilization of wavelet-based techniques combined with the previously introduced time-dependent deterministic sampling procedure measure to achieve stable, picosecond length, quantum-classical dynamics of electrons and nuclei in clusters. The dynamical information is employed to construct a novel cumulative flux/velocity correlation function, where the wavepacket flux from the quantized particle is combined with classical nuclear velocities to obtain the vibrational density of states. The approach is demonstrated by computing the vibrational density of states of [Cl-H-Cl]-, inclusive of critical quantum nuclear effects, and our results are in good agreement with experiment. A general hierarchical procedure is also provided, based on electronic structure harmonic frequencies, classical ab initio molecular dynamics, computation of nuclear quantum-mechanical eigenstates, and employing quantum wavepacket ab initio dynamics to understand vibrational spectroscopy in hydrogen-bonded clusters that display large degrees of anharmonicities.

Generation and evaluation of an ultra-high-field atlas with applications in DBS planning

NASA Astrophysics Data System (ADS)

Wang, Brian T.; Poirier, Stefan; Guo, Ting; Parrent, Andrew G.; Peters, Terry M.; Khan, Ali R.

2016-03-01

Purpose Deep brain stimulation (DBS) is a common treatment for Parkinson's disease (PD) and involves the use of brain atlases or intrinsic landmarks to estimate the location of target deep brain structures, such as the subthalamic nucleus (STN) and the globus pallidus pars interna (GPi). However, these structures can be difficult to localize with conventional clinical magnetic resonance imaging (MRI), and thus targeting can be prone to error. Ultra-high-field imaging at 7T has the ability to clearly resolve these structures and thus atlases built with these data have the potential to improve targeting accuracy. Methods T1 and T2-weighted images of 12 healthy control subjects were acquired using a 7T MR scanner. These images were then used with groupwise registration to generate an unbiased average template with T1w and T2w contrast. Deep brain structures were manually labelled in each subject by two raters and rater reliability was assessed. We compared the use of this unbiased atlas with two other methods of atlas-based segmentation (single-template and multi-template) for subthalamic nucleus (STN) segmentation on 7T MRI data. We also applied this atlas to clinical DBS data acquired at 1.5T to evaluate its efficacy for DBS target localization as compared to using a standard atlas. Results The unbiased templates provide superb detail of subcortical structures. Through one-way ANOVA tests, the unbiased template is significantly (p <0.05) more accurate than a single-template in atlas-based segmentation and DBS target localization tasks. Conclusion The generated unbiased averaged templates provide better visualization of deep brain nuclei and an increase in accuracy over single-template and lower field strength atlases.

Extending unbiased stereology of brain ultrastructure to three-dimensional volumes

NASA Technical Reports Server (NTRS)

Fiala, J. C.; Harris, K. M.; Koslow, S. H. (Principal Investigator)

2001-01-01

OBJECTIVE: Analysis of brain ultrastructure is needed to reveal how neurons communicate with one another via synapses and how disease processes alter this communication. In the past, such analyses have usually been based on single or paired sections obtained by electron microscopy. Reconstruction from multiple serial sections provides a much needed, richer representation of the three-dimensional organization of the brain. This paper introduces a new reconstruction system and new methods for analyzing in three dimensions the location and ultrastructure of neuronal components, such as synapses, which are distributed non-randomly throughout the brain. DESIGN AND MEASUREMENTS: Volumes are reconstructed by defining transformations that align the entire area of adjacent sections. Whole-field alignment requires rotation, translation, skew, scaling, and second-order nonlinear deformations. Such transformations are implemented by a linear combination of bivariate polynomials. Computer software for generating transformations based on user input is described. Stereological techniques for assessing structural distributions in reconstructed volumes are the unbiased bricking, disector, unbiased ratio, and per-length counting techniques. A new general method, the fractional counter, is also described. This unbiased technique relies on the counting of fractions of objects contained in a test volume. A volume of brain tissue from stratum radiatum of hippocampal area CA1 is reconstructed and analyzed for synaptic density to demonstrate and compare the techniques. RESULTS AND CONCLUSIONS: Reconstruction makes practicable volume-oriented analysis of ultrastructure using such techniques as the unbiased bricking and fractional counter methods. These analysis methods are less sensitive to the section-to-section variations in counts and section thickness, factors that contribute to the inaccuracy of other stereological methods. In addition, volume reconstruction facilitates visualization and modeling of structures and analysis of three-dimensional relationships such as synaptic connectivity.

An Unbiased Method To Build Benchmarking Sets for Ligand-Based Virtual Screening and its Application To GPCRs

PubMed Central

2015-01-01

Benchmarking data sets have become common in recent years for the purpose of virtual screening, though the main focus had been placed on the structure-based virtual screening (SBVS) approaches. Due to the lack of crystal structures, there is great need for unbiased benchmarking sets to evaluate various ligand-based virtual screening (LBVS) methods for important drug targets such as G protein-coupled receptors (GPCRs). To date these ready-to-apply data sets for LBVS are fairly limited, and the direct usage of benchmarking sets designed for SBVS could bring the biases to the evaluation of LBVS. Herein, we propose an unbiased method to build benchmarking sets for LBVS and validate it on a multitude of GPCRs targets. To be more specific, our methods can (1) ensure chemical diversity of ligands, (2) maintain the physicochemical similarity between ligands and decoys, (3) make the decoys dissimilar in chemical topology to all ligands to avoid false negatives, and (4) maximize spatial random distribution of ligands and decoys. We evaluated the quality of our Unbiased Ligand Set (ULS) and Unbiased Decoy Set (UDS) using three common LBVS approaches, with Leave-One-Out (LOO) Cross-Validation (CV) and a metric of average AUC of the ROC curves. Our method has greatly reduced the “artificial enrichment” and “analogue bias” of a published GPCRs benchmarking set, i.e., GPCR Ligand Library (GLL)/GPCR Decoy Database (GDD). In addition, we addressed an important issue about the ratio of decoys per ligand and found that for a range of 30 to 100 it does not affect the quality of the benchmarking set, so we kept the original ratio of 39 from the GLL/GDD. PMID:24749745

An unbiased method to build benchmarking sets for ligand-based virtual screening and its application to GPCRs.

PubMed

Xia, Jie; Jin, Hongwei; Liu, Zhenming; Zhang, Liangren; Wang, Xiang Simon

2014-05-27

Benchmarking data sets have become common in recent years for the purpose of virtual screening, though the main focus had been placed on the structure-based virtual screening (SBVS) approaches. Due to the lack of crystal structures, there is great need for unbiased benchmarking sets to evaluate various ligand-based virtual screening (LBVS) methods for important drug targets such as G protein-coupled receptors (GPCRs). To date these ready-to-apply data sets for LBVS are fairly limited, and the direct usage of benchmarking sets designed for SBVS could bring the biases to the evaluation of LBVS. Herein, we propose an unbiased method to build benchmarking sets for LBVS and validate it on a multitude of GPCRs targets. To be more specific, our methods can (1) ensure chemical diversity of ligands, (2) maintain the physicochemical similarity between ligands and decoys, (3) make the decoys dissimilar in chemical topology to all ligands to avoid false negatives, and (4) maximize spatial random distribution of ligands and decoys. We evaluated the quality of our Unbiased Ligand Set (ULS) and Unbiased Decoy Set (UDS) using three common LBVS approaches, with Leave-One-Out (LOO) Cross-Validation (CV) and a metric of average AUC of the ROC curves. Our method has greatly reduced the "artificial enrichment" and "analogue bias" of a published GPCRs benchmarking set, i.e., GPCR Ligand Library (GLL)/GPCR Decoy Database (GDD). In addition, we addressed an important issue about the ratio of decoys per ligand and found that for a range of 30 to 100 it does not affect the quality of the benchmarking set, so we kept the original ratio of 39 from the GLL/GDD.

Modeling the Hydrogen Bond within Molecular Dynamics

ERIC Educational Resources Information Center

Lykos, Peter

2004-01-01

The structure of a hydrogen bond is elucidated within the framework of molecular dynamics based on the model of Rahman and Stillinger (R-S) liquid water treatment. Thus, undergraduates are exposed to the powerful but simple use of classical mechanics to solid objects from a molecular viewpoint.

Two Argonne scientists named 2012 AAAS fellows | Argonne National

Science.gov Websites

"contributions to understanding structural dynamics of molecular excited states with special . "I'm really interested in how molecules respond to light and how light could influence molecular is being honored for her "contributions to understanding structural dynamics of molecular

The Computer Simulation of Liquids by Molecular Dynamics.

ERIC Educational Resources Information Center

Smith, W.

1987-01-01

Proposes a mathematical computer model for the behavior of liquids using the classical dynamic principles of Sir Isaac Newton and the molecular dynamics method invented by other scientists. Concludes that other applications will be successful using supercomputers to go beyond simple Newtonian physics. (CW)

Enhanced sampling techniques in molecular dynamics simulations of biological systems.

PubMed

Bernardi, Rafael C; Melo, Marcelo C R; Schulten, Klaus

2015-05-01

Molecular dynamics has emerged as an important research methodology covering systems to the level of millions of atoms. However, insufficient sampling often limits its application. The limitation is due to rough energy landscapes, with many local minima separated by high-energy barriers, which govern the biomolecular motion. In the past few decades methods have been developed that address the sampling problem, such as replica-exchange molecular dynamics, metadynamics and simulated annealing. Here we present an overview over theses sampling methods in an attempt to shed light on which should be selected depending on the type of system property studied. Enhanced sampling methods have been employed for a broad range of biological systems and the choice of a suitable method is connected to biological and physical characteristics of the system, in particular system size. While metadynamics and replica-exchange molecular dynamics are the most adopted sampling methods to study biomolecular dynamics, simulated annealing is well suited to characterize very flexible systems. The use of annealing methods for a long time was restricted to simulation of small proteins; however, a variant of the method, generalized simulated annealing, can be employed at a relatively low computational cost to large macromolecular complexes. Molecular dynamics trajectories frequently do not reach all relevant conformational substates, for example those connected with biological function, a problem that can be addressed by employing enhanced sampling algorithms. This article is part of a Special Issue entitled Recent developments of molecular dynamics. Copyright © 2014 Elsevier B.V. All rights reserved.

Large-scale molecular dynamics simulation of DNA: implementation and validation of the AMBER98 force field in LAMMPS.

PubMed

Grindon, Christina; Harris, Sarah; Evans, Tom; Novik, Keir; Coveney, Peter; Laughton, Charles

2004-07-15

Molecular modelling played a central role in the discovery of the structure of DNA by Watson and Crick. Today, such modelling is done on computers: the more powerful these computers are, the more detailed and extensive can be the study of the dynamics of such biological macromolecules. To fully harness the power of modern massively parallel computers, however, we need to develop and deploy algorithms which can exploit the structure of such hardware. The Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is a scalable molecular dynamics code including long-range Coulomb interactions, which has been specifically designed to function efficiently on parallel platforms. Here we describe the implementation of the AMBER98 force field in LAMMPS and its validation for molecular dynamics investigations of DNA structure and flexibility against the benchmark of results obtained with the long-established code AMBER6 (Assisted Model Building with Energy Refinement, version 6). Extended molecular dynamics simulations on the hydrated DNA dodecamer d(CTTTTGCAAAAG)(2), which has previously been the subject of extensive dynamical analysis using AMBER6, show that it is possible to obtain excellent agreement in terms of static, dynamic and thermodynamic parameters between AMBER6 and LAMMPS. In comparison with AMBER6, LAMMPS shows greatly improved scalability in massively parallel environments, opening up the possibility of efficient simulations of order-of-magnitude larger systems and/or for order-of-magnitude greater simulation times.

Structural, dynamic, and vibrational properties during heat transfer in Si/Ge superlattices: A Car-Parrinello molecular dynamics study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ji, Pengfei; Zhang, Yuwen, E-mail: zhangyu@missouri.edu; Yang, Mo

The structural, dynamic, and vibrational properties during heat transfer process in Si/Ge superlattices are studied by analyzing the trajectories generated by the ab initio Car-Parrinello molecular dynamics simulation. The radial distribution functions and mean square displacements are calculated and further discussions are made to explain and probe the structural changes relating to the heat transfer phenomenon. Furthermore, the vibrational density of states of the two layers (Si/Ge) are computed and plotted to analyze the contributions of phonons with different frequencies to the heat conduction. Coherent heat conduction of the low frequency phonons is found and their contributions to facilitate heatmore » transfer are confirmed. The Car-Parrinello molecular dynamics simulation outputs in the work show reasonable thermophysical results of the thermal energy transport process and shed light on the potential applications of treating the heat transfer in the superlattices of semiconductor materials from a quantum mechanical molecular dynamics simulation perspective.« less

A Direct, Quantitative Connection between Molecular Dynamics Simulations and Vibrational Probe Line Shapes.

PubMed

Xu, Rosalind J; Blasiak, Bartosz; Cho, Minhaeng; Layfield, Joshua P; Londergan, Casey H

2018-05-17

A quantitative connection between molecular dynamics simulations and vibrational spectroscopy of probe-labeled systems would enable direct translation of experimental data into structural and dynamical information. To constitute this connection, all-atom molecular dynamics (MD) simulations were performed for two SCN probe sites (solvent-exposed and buried) in a calmodulin-target peptide complex. Two frequency calculation approaches with substantial nonelectrostatic components, a quantum mechanics/molecular mechanics (QM/MM)-based technique and a solvatochromic fragment potential (SolEFP) approach, were used to simulate the infrared probe line shapes. While QM/MM results disagreed with experiment, SolEFP results matched experimental frequencies and line shapes and revealed the physical and dynamic bases for the observed spectroscopic behavior. The main determinant of the CN probe frequency is the exchange repulsion between the probe and its local structural neighbors, and there is a clear dynamic explanation for the relatively broad probe line shape observed at the "buried" probe site. This methodology should be widely applicable to vibrational probes in many environments.

Capillary waves' dynamics at the nanoscale

NASA Astrophysics Data System (ADS)

Delgado-Buscalioni, Rafael; Chacón, Enrique; Tarazona, Pedro

2008-12-01

We study the dynamics of thermally excited capillary waves (CW) at molecular scales, using molecular dynamics simulations of simple liquid slabs. The analysis is based on the Fourier modes of the liquid surface, constructed via the intrinsic sampling method (Chacón and Tarazona 2003 Phys. Rev. Lett. 91 166103). We obtain the time autocorrelation of the Fourier modes to get the frequency and damping rate Γd(q) of each mode, with wavenumber q. Continuum hydrodynamics predicts \\Gamma (q) \\propto q\\gamma (q) and thus provides a dynamic measure of the q-dependent surface tension, γd(q). The dynamical estimation is much more robust than the structural prediction based on the amplitude of the Fourier mode, γs(q). Using the optimal estimation of the intrinsic surface, we obtain quantitative agreement between the structural and dynamic pictures. Quite surprisingly, the hydrodynamic prediction for CW remains valid up to wavelengths of about four molecular diameters. Surface tension hydrodynamics break down at shorter scales, whereby a transition to a molecular diffusion regime is observed.

Structural, dynamic, and vibrational properties during heat transfer in Si/Ge superlattices: A Car-Parrinello molecular dynamics study

NASA Astrophysics Data System (ADS)

Ji, Pengfei; Zhang, Yuwen; Yang, Mo

2013-12-01

The structural, dynamic, and vibrational properties during heat transfer process in Si/Ge superlattices are studied by analyzing the trajectories generated by the ab initio Car-Parrinello molecular dynamics simulation. The radial distribution functions and mean square displacements are calculated and further discussions are made to explain and probe the structural changes relating to the heat transfer phenomenon. Furthermore, the vibrational density of states of the two layers (Si/Ge) are computed and plotted to analyze the contributions of phonons with different frequencies to the heat conduction. Coherent heat conduction of the low frequency phonons is found and their contributions to facilitate heat transfer are confirmed. The Car-Parrinello molecular dynamics simulation outputs in the work show reasonable thermophysical results of the thermal energy transport process and shed light on the potential applications of treating the heat transfer in the superlattices of semiconductor materials from a quantum mechanical molecular dynamics simulation perspective.

Multiple time step integrators in ab initio molecular dynamics.

PubMed

Luehr, Nathan; Markland, Thomas E; Martínez, Todd J

2014-02-28

Multiple time-scale algorithms exploit the natural separation of time-scales in chemical systems to greatly accelerate the efficiency of molecular dynamics simulations. Although the utility of these methods in systems where the interactions are described by empirical potentials is now well established, their application to ab initio molecular dynamics calculations has been limited by difficulties associated with splitting the ab initio potential into fast and slowly varying components. Here we present two schemes that enable efficient time-scale separation in ab initio calculations: one based on fragment decomposition and the other on range separation of the Coulomb operator in the electronic Hamiltonian. We demonstrate for both water clusters and a solvated hydroxide ion that multiple time-scale molecular dynamics allows for outer time steps of 2.5 fs, which are as large as those obtained when such schemes are applied to empirical potentials, while still allowing for bonds to be broken and reformed throughout the dynamics. This permits computational speedups of up to 4.4x, compared to standard Born-Oppenheimer ab initio molecular dynamics with a 0.5 fs time step, while maintaining the same energy conservation and accuracy.

Dynamics of Nanoscale Grain-Boundary Decohesion in Aluminum by Molecular-Dynamics Simulation

NASA Technical Reports Server (NTRS)

Yamakov, V.; Saether, E.; Phillips, D. R.; Glaessegen, E. H.

2007-01-01

The dynamics and energetics of intergranular crack growth along a flat grain boundary in aluminum is studied by a molecular-dynamics simulation model for crack propagation under steady-state conditions. Using the ability of the molecular-dynamics simulation to identify atoms involved in different atomistic mechanisms, it was possible to identify the energy contribution of different processes taking place during crack growth. The energy contributions were divided as: elastic energy, defined as the potential energy of the atoms in fcc crystallographic state; and plastically stored energy, the energy of stacking faults and twin boundaries; grain-boundary and surface energy. In addition, monitoring the amount of heat exchange with the molecular-dynamics thermostat gives the energy dissipated as heat in the system. The energetic analysis indicates that the majority of energy in a fast growing crack is dissipated as heat. This dissipation increases linearly at low speed, and faster than linear at speeds approaching 1/3 the Rayleigh wave speed when the crack tip becomes dynamically unstable producing periodic dislocation bursts until the crack is blunted.

An Example of an Improvable Rao-Blackwell Improvement, Inefficient Maximum Likelihood Estimator, and Unbiased Generalized Bayes Estimator.

PubMed

Galili, Tal; Meilijson, Isaac

2016-01-02

The Rao-Blackwell theorem offers a procedure for converting a crude unbiased estimator of a parameter θ into a "better" one, in fact unique and optimal if the improvement is based on a minimal sufficient statistic that is complete. In contrast, behind every minimal sufficient statistic that is not complete, there is an improvable Rao-Blackwell improvement. This is illustrated via a simple example based on the uniform distribution, in which a rather natural Rao-Blackwell improvement is uniformly improvable. Furthermore, in this example the maximum likelihood estimator is inefficient, and an unbiased generalized Bayes estimator performs exceptionally well. Counterexamples of this sort can be useful didactic tools for explaining the true nature of a methodology and possible consequences when some of the assumptions are violated. [Received December 2014. Revised September 2015.].

Quantum key distribution for composite dimensional finite systems

NASA Astrophysics Data System (ADS)

Shalaby, Mohamed; Kamal, Yasser

2017-06-01

The application of quantum mechanics contributes to the field of cryptography with very important advantage as it offers a mechanism for detecting the eavesdropper. The pioneering work of quantum key distribution uses mutually unbiased bases (MUBs) to prepare and measure qubits (or qudits). Weak mutually unbiased bases (WMUBs) have weaker properties than MUBs properties, however, unlike MUBs, a complete set of WMUBs can be constructed for systems with composite dimensions. In this paper, we study the use of weak mutually unbiased bases (WMUBs) in quantum key distribution for composite dimensional finite systems. We prove that the security analysis of using a complete set of WMUBs to prepare and measure the quantum states in the generalized BB84 protocol, gives better results than using the maximum number of MUBs that can be constructed, when they are analyzed against the intercept and resend attack.

Time-resolved molecular imaging

NASA Astrophysics Data System (ADS)

Xu, Junliang; Blaga, Cosmin I.; Agostini, Pierre; DiMauro, Louis F.

2016-06-01

Time-resolved molecular imaging is a frontier of ultrafast optical science and physical chemistry. In this article, we review present and future key spectroscopic and microscopic techniques for ultrafast imaging of molecular dynamics and show their differences and connections. The advent of femtosecond lasers and free electron x-ray lasers bring us closer to this goal, which eventually will extend our knowledge about molecular dynamics to the attosecond time domain.

Molecular Dynamics Simulations of Supramolecular Anticancer Nanotubes.

PubMed

Kang, Myungshim; Chakraborty, Kaushik; Loverde, Sharon M

2018-06-25

We report here on long-time all-atomistic molecular dynamics simulations of functional supramolecular nanotubes composed by the self-assembly of peptide-drug amphiphiles (DAs). These DAs have been shown to possess an inherently high drug loading of the hydrophobic anticancer drug camptothecin. We probe the self-assembly mechanism from random with ∼0.4 μs molecular dynamics simulations. Furthermore, we also computationally characterize the interfacial structure, directionality of π-π stacking, and water dynamics within several peptide-drug nanotubes with diameters consistent with the reported experimental nanotube diameter. Insight gained should inform the future design of these novel anticancer drug delivery systems.