Protocols Utilizing Constant pH Molecular Dynamics to Compute pH-Dependent Binding Free Energies
2015-01-01
In protein–ligand binding, the electrostatic environments of the two binding partners may vary significantly in bound and unbound states, which may lead to protonation changes upon binding. In cases where ligand binding results in a net uptake or release of protons, the free energy of binding is pH-dependent. Nevertheless, conventional free energy calculations and molecular docking protocols typically do not rigorously account for changes in protonation that may occur upon ligand binding. To address these shortcomings, we present a simple methodology based on Wyman’s binding polynomial formalism to account for the pH dependence of binding free energies and demonstrate its use on cucurbit[7]uril (CB[7]) host–guest systems. Using constant pH molecular dynamics and a reference binding free energy that is taken either from experiment or from thermodynamic integration computations, the pH-dependent binding free energy is determined. This computational protocol accurately captures the large pKa shifts observed experimentally upon CB[7]:guest association and reproduces experimental binding free energies at different levels of pH. We show that incorrect assignment of fixed protonation states in free energy computations can give errors of >2 kcal/mol in these host–guest systems. Use of the methods presented here avoids such errors, thus suggesting their utility in computing proton-linked binding free energies for protein–ligand complexes. PMID:25134690
Deng, Nanjie; Cui, Di; Zhang, Bin W; Xia, Junchao; Cruz, Jeffrey; Levy, Ronald
2018-06-13
Accurately predicting absolute binding free energies of protein-ligand complexes is important as a fundamental problem in both computational biophysics and pharmaceutical discovery. Calculating binding free energies for charged ligands is generally considered to be challenging because of the strong electrostatic interactions between the ligand and its environment in aqueous solution. In this work, we compare the performance of the potential of mean force (PMF) method and the double decoupling method (DDM) for computing absolute binding free energies for charged ligands. We first clarify an unresolved issue concerning the explicit use of the binding site volume to define the complexed state in DDM together with the use of harmonic restraints. We also provide an alternative derivation for the formula for absolute binding free energy using the PMF approach. We use these formulas to compute the binding free energy of charged ligands at an allosteric site of HIV-1 integrase, which has emerged in recent years as a promising target for developing antiviral therapy. As compared with the experimental results, the absolute binding free energies obtained by using the PMF approach show unsigned errors of 1.5-3.4 kcal mol-1, which are somewhat better than the results from DDM (unsigned errors of 1.6-4.3 kcal mol-1) using the same amount of CPU time. According to the DDM decomposition of the binding free energy, the ligand binding appears to be dominated by nonpolar interactions despite the presence of very large and favorable intermolecular ligand-receptor electrostatic interactions, which are almost completely cancelled out by the equally large free energy cost of desolvation of the charged moiety of the ligands in solution. We discuss the relative strengths of computing absolute binding free energies using the alchemical and physical pathway methods.
Duan, Lili; Liu, Xiao; Zhang, John Z H
2016-05-04
Efficient and reliable calculation of protein-ligand binding free energy is a grand challenge in computational biology and is of critical importance in drug design and many other molecular recognition problems. The main challenge lies in the calculation of entropic contribution to protein-ligand binding or interaction systems. In this report, we present a new interaction entropy method which is theoretically rigorous, computationally efficient, and numerically reliable for calculating entropic contribution to free energy in protein-ligand binding and other interaction processes. Drastically different from the widely employed but extremely expensive normal mode method for calculating entropy change in protein-ligand binding, the new method calculates the entropic component (interaction entropy or -TΔS) of the binding free energy directly from molecular dynamics simulation without any extra computational cost. Extensive study of over a dozen randomly selected protein-ligand binding systems demonstrated that this interaction entropy method is both computationally efficient and numerically reliable and is vastly superior to the standard normal mode approach. This interaction entropy paradigm introduces a novel and intuitive conceptual understanding of the entropic effect in protein-ligand binding and other general interaction systems as well as a practical method for highly efficient calculation of this effect.
Lawrenz, Morgan; Baron, Riccardo; Wang, Yi; McCammon, J Andrew
2012-01-01
The Independent-Trajectory Thermodynamic Integration (IT-TI) approach for free energy calculation with distributed computing is described. IT-TI utilizes diverse conformational sampling obtained from multiple, independent simulations to obtain more reliable free energy estimates compared to single TI predictions. The latter may significantly under- or over-estimate the binding free energy due to finite sampling. We exemplify the advantages of the IT-TI approach using two distinct cases of protein-ligand binding. In both cases, IT-TI yields distributions of absolute binding free energy estimates that are remarkably centered on the target experimental values. Alternative protocols for the practical and general application of IT-TI calculations are investigated. We highlight a protocol that maximizes predictive power and computational efficiency.
Gallicchio, Emilio; Deng, Nanjie; He, Peng; Wickstrom, Lauren; Perryman, Alexander L.; Santiago, Daniel N.; Forli, Stefano; Olson, Arthur J.; Levy, Ronald M.
2014-01-01
As part of the SAMPL4 blind challenge, filtered AutoDock Vina ligand docking predictions and large scale binding energy distribution analysis method binding free energy calculations have been applied to the virtual screening of a focused library of candidate binders to the LEDGF site of the HIV integrase protein. The computational protocol leveraged docking and high level atomistic models to improve enrichment. The enrichment factor of our blind predictions ranked best among all of the computational submissions, and second best overall. This work represents to our knowledge the first example of the application of an all-atom physics-based binding free energy model to large scale virtual screening. A total of 285 parallel Hamiltonian replica exchange molecular dynamics absolute protein-ligand binding free energy simulations were conducted starting from docked poses. The setup of the simulations was fully automated, calculations were distributed on multiple computing resources and were completed in a 6-weeks period. The accuracy of the docked poses and the inclusion of intramolecular strain and entropic losses in the binding free energy estimates were the major factors behind the success of the method. Lack of sufficient time and computing resources to investigate additional protonation states of the ligands was a major cause of mispredictions. The experiment demonstrated the applicability of binding free energy modeling to improve hit rates in challenging virtual screening of focused ligand libraries during lead optimization. PMID:24504704
Interaction entropy for protein-protein binding
NASA Astrophysics Data System (ADS)
Sun, Zhaoxi; Yan, Yu N.; Yang, Maoyou; Zhang, John Z. H.
2017-03-01
Protein-protein interactions are at the heart of signal transduction and are central to the function of protein machine in biology. The highly specific protein-protein binding is quantitatively characterized by the binding free energy whose accurate calculation from the first principle is a grand challenge in computational biology. In this paper, we show how the interaction entropy approach, which was recently proposed for protein-ligand binding free energy calculation, can be applied to computing the entropic contribution to the protein-protein binding free energy. Explicit theoretical derivation of the interaction entropy approach for protein-protein interaction system is given in detail from the basic definition. Extensive computational studies for a dozen realistic protein-protein interaction systems are carried out using the present approach and comparisons of the results for these protein-protein systems with those from the standard normal mode method are presented. Analysis of the present method for application in protein-protein binding as well as the limitation of the method in numerical computation is discussed. Our study and analysis of the results provided useful information for extracting correct entropic contribution in protein-protein binding from molecular dynamics simulations.
Interaction entropy for protein-protein binding.
Sun, Zhaoxi; Yan, Yu N; Yang, Maoyou; Zhang, John Z H
2017-03-28
Protein-protein interactions are at the heart of signal transduction and are central to the function of protein machine in biology. The highly specific protein-protein binding is quantitatively characterized by the binding free energy whose accurate calculation from the first principle is a grand challenge in computational biology. In this paper, we show how the interactionentropy approach, which was recently proposed for protein-ligand binding free energy calculation, can be applied to computing the entropic contribution to the protein-protein binding free energy. Explicit theoretical derivation of the interactionentropy approach for protein-protein interaction system is given in detail from the basic definition. Extensive computational studies for a dozen realistic protein-protein interaction systems are carried out using the present approach and comparisons of the results for these protein-protein systems with those from the standard normal mode method are presented. Analysis of the present method for application in protein-protein binding as well as the limitation of the method in numerical computation is discussed. Our study and analysis of the results provided useful information for extracting correct entropic contribution in protein-protein binding from molecular dynamics simulations.
Free energy landscape for the binding process of Huperzine A to acetylcholinesterase
Bai, Fang; Xu, Yechun; Chen, Jing; Liu, Qiufeng; Gu, Junfeng; Wang, Xicheng; Ma, Jianpeng; Li, Honglin; Onuchic, José N.; Jiang, Hualiang
2013-01-01
Drug-target residence time (t = 1/koff, where koff is the dissociation rate constant) has become an important index in discovering better- or best-in-class drugs. However, little effort has been dedicated to developing computational methods that can accurately predict this kinetic parameter or related parameters, koff and activation free energy of dissociation (). In this paper, energy landscape theory that has been developed to understand protein folding and function is extended to develop a generally applicable computational framework that is able to construct a complete ligand-target binding free energy landscape. This enables both the binding affinity and the binding kinetics to be accurately estimated. We applied this method to simulate the binding event of the anti-Alzheimer’s disease drug (−)−Huperzine A to its target acetylcholinesterase (AChE). The computational results are in excellent agreement with our concurrent experimental measurements. All of the predicted values of binding free energy and activation free energies of association and dissociation deviate from the experimental data only by less than 1 kcal/mol. The method also provides atomic resolution information for the (−)−Huperzine A binding pathway, which may be useful in designing more potent AChE inhibitors. We expect this methodology to be widely applicable to drug discovery and development. PMID:23440190
Free energy landscape for the binding process of Huperzine A to acetylcholinesterase.
Bai, Fang; Xu, Yechun; Chen, Jing; Liu, Qiufeng; Gu, Junfeng; Wang, Xicheng; Ma, Jianpeng; Li, Honglin; Onuchic, José N; Jiang, Hualiang
2013-03-12
Drug-target residence time (t = 1/k(off), where k(off) is the dissociation rate constant) has become an important index in discovering better- or best-in-class drugs. However, little effort has been dedicated to developing computational methods that can accurately predict this kinetic parameter or related parameters, k(off) and activation free energy of dissociation (ΔG(off)≠). In this paper, energy landscape theory that has been developed to understand protein folding and function is extended to develop a generally applicable computational framework that is able to construct a complete ligand-target binding free energy landscape. This enables both the binding affinity and the binding kinetics to be accurately estimated. We applied this method to simulate the binding event of the anti-Alzheimer's disease drug (-)-Huperzine A to its target acetylcholinesterase (AChE). The computational results are in excellent agreement with our concurrent experimental measurements. All of the predicted values of binding free energy and activation free energies of association and dissociation deviate from the experimental data only by less than 1 kcal/mol. The method also provides atomic resolution information for the (-)-Huperzine A binding pathway, which may be useful in designing more potent AChE inhibitors. We expect this methodology to be widely applicable to drug discovery and development.
Kawai, Ryoko; Araki, Mitsugu; Yoshimura, Masashi; Kamiya, Narutoshi; Ono, Masahiro; Saji, Hideo; Okuno, Yasushi
2018-05-16
Development of new diagnostic imaging probes for Alzheimer's disease, such as positron emission tomography (PET) and single photon emission computed tomography (SPECT) probes, has been strongly desired. In this study, we investigated the most accessible amyloid β (Aβ) binding site of [ 123 I]IMPY, a Thioflavin-T-derived SPECT probe, using experimental and computational methods. First, we performed a competitive inhibition assay with Orange-G, which recognizes the KLVFFA region in Aβ fibrils, suggesting that IMPY and Orange-G bind to different sites in Aβ fibrils. Next, we precisely predicted the IMPY binding site on a multiple-protofilament Aβ fibril model using computational approaches, consisting of molecular dynamics and docking simulations. We generated possible IMPY-binding structures using docking simulations to identify candidates for probe-binding sites. The binding free energy of IMPY with the Aβ fibril was calculated by a free energy simulation method, MP-CAFEE. These computational results suggest that IMPY preferentially binds to an interfacial pocket located between two protofilaments and is stabilized mainly through hydrophobic interactions. Finally, our computational approach was validated by comparing it with the experimental results. The present study demonstrates the possibility of computational approaches to screen new PET/SPECT probes for Aβ imaging.
A Prediction Method of Binding Free Energy of Protein and Ligand
NASA Astrophysics Data System (ADS)
Yang, Kun; Wang, Xicheng
2010-05-01
Predicting the binding free energy is an important problem in bimolecular simulation. Such prediction would be great benefit in understanding protein functions, and may be useful for computational prediction of ligand binding strengths, e.g., in discovering pharmaceutical drugs. Free energy perturbation (FEP)/thermodynamics integration (TI) is a classical method to explicitly predict free energy. However, this method need plenty of time to collect datum, and that attempts to deal with some simple systems and small changes of molecular structures. Another one for estimating ligand binding affinities is linear interaction energy (LIE) method. This method employs averages of interaction potential energy terms from molecular dynamics simulations or other thermal conformational sampling techniques. Incorporation of systematic deviations from electrostatic linear response, derived from free energy perturbation studies, into the absolute binding free energy expression significantly enhances the accuracy of the approach. However, it also is time-consuming work. In this paper, a new prediction method based on steered molecular dynamics (SMD) with direction optimization is developed to compute binding free energy. Jarzynski's equality is used to derive the PMF or free-energy. The results for two numerical examples are presented, showing that the method has good accuracy and efficiency. The novel method can also simulate whole binding proceeding and give some important structural information about development of new drugs.
Free energy decomposition of protein-protein interactions.
Noskov, S Y; Lim, C
2001-08-01
A free energy decomposition scheme has been developed and tested on antibody-antigen and protease-inhibitor binding for which accurate experimental structures were available for both free and bound proteins. Using the x-ray coordinates of the free and bound proteins, the absolute binding free energy was computed assuming additivity of three well-defined, physical processes: desolvation of the x-ray structures, isomerization of the x-ray conformation to a nearby local minimum in the gas-phase, and subsequent noncovalent complex formation in the gas phase. This free energy scheme, together with the Generalized Born model for computing the electrostatic solvation free energy, yielded binding free energies in remarkable agreement with experimental data. Two assumptions commonly used in theoretical treatments; viz., the rigid-binding approximation (which assumes no conformational change upon complexation) and the neglect of vdW interactions, were found to yield large errors in the binding free energy. Protein-protein vdW and electrostatic interactions between complementary surfaces over a relatively large area (1400--1700 A(2)) were found to drive antibody-antigen and protease-inhibitor binding.
Calculating binding free energies for protein-carbohydrate complexes.
Hadden, Jodi A; Tessier, Matthew B; Fadda, Elisa; Woods, Robert J
2015-01-01
A variety of computational techniques may be applied to compute theoretical binding free energies for protein-carbohydrate complexes. Elucidation of the intermolecular interactions, as well as the thermodynamic effects, that contribute to the relative strength of receptor binding can shed light on biomolecular recognition, and the resulting initiation or inhibition of a biological process. Three types of free energy methods are discussed here, including MM-PB/GBSA, thermodynamic integration, and a non-equilibrium alternative utilizing SMD. Throughout this chapter, the well-known concanavalin A lectin is employed as a model system to demonstrate the application of these methods to the special case of carbohydrate binding.
Tinker-OpenMM: Absolute and relative alchemical free energies using AMOEBA on GPUs.
Harger, Matthew; Li, Daniel; Wang, Zhi; Dalby, Kevin; Lagardère, Louis; Piquemal, Jean-Philip; Ponder, Jay; Ren, Pengyu
2017-09-05
The capabilities of the polarizable force fields for alchemical free energy calculations have been limited by the high computational cost and complexity of the underlying potential energy functions. In this work, we present a GPU-based general alchemical free energy simulation platform for polarizable potential AMOEBA. Tinker-OpenMM, the OpenMM implementation of the AMOEBA simulation engine has been modified to enable both absolute and relative alchemical simulations on GPUs, which leads to a ∼200-fold improvement in simulation speed over a single CPU core. We show that free energy values calculated using this platform agree with the results of Tinker simulations for the hydration of organic compounds and binding of host-guest systems within the statistical errors. In addition to absolute binding, we designed a relative alchemical approach for computing relative binding affinities of ligands to the same host, where a special path was applied to avoid numerical instability due to polarization between the different ligands that bind to the same site. This scheme is general and does not require ligands to have similar scaffolds. We show that relative hydration and binding free energy calculated using this approach match those computed from the absolute free energy approach. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Funnel metadynamics as accurate binding free-energy method
Limongelli, Vittorio; Bonomi, Massimiliano; Parrinello, Michele
2013-01-01
A detailed description of the events ruling ligand/protein interaction and an accurate estimation of the drug affinity to its target is of great help in speeding drug discovery strategies. We have developed a metadynamics-based approach, named funnel metadynamics, that allows the ligand to enhance the sampling of the target binding sites and its solvated states. This method leads to an efficient characterization of the binding free-energy surface and an accurate calculation of the absolute protein–ligand binding free energy. We illustrate our protocol in two systems, benzamidine/trypsin and SC-558/cyclooxygenase 2. In both cases, the X-ray conformation has been found as the lowest free-energy pose, and the computed protein–ligand binding free energy in good agreement with experiments. Furthermore, funnel metadynamics unveils important information about the binding process, such as the presence of alternative binding modes and the role of waters. The results achieved at an affordable computational cost make funnel metadynamics a valuable method for drug discovery and for dealing with a variety of problems in chemistry, physics, and material science. PMID:23553839
Rocklin, Gabriel J.; Mobley, David L.; Dill, Ken A.
2013-01-01
Binding free energy calculations offer a thermodynamically rigorous method to compute protein-ligand binding, and they depend on empirical force fields with hundreds of parameters. We examined the sensitivity of computed binding free energies to the ligand’s electrostatic and van der Waals parameters. Dielectric screening and cancellation of effects between ligand-protein and ligand-solvent interactions reduce the parameter sensitivity of binding affinity by 65%, compared with interaction strengths computed in the gas-phase. However, multiple changes to parameters combine additively on average, which can lead to large changes in overall affinity from many small changes to parameters. Using these results, we estimate that random, uncorrelated errors in force field nonbonded parameters must be smaller than 0.02 e per charge, 0.06 Å per radius, and 0.01 kcal/mol per well depth in order to obtain 68% (one standard deviation) confidence that a computed affinity for a moderately-sized lead compound will fall within 1 kcal/mol of the true affinity, if these are the only sources of error considered. PMID:24015114
Importance of ligand reorganization free energy in protein-ligand binding-affinity prediction.
Yang, Chao-Yie; Sun, Haiying; Chen, Jianyong; Nikolovska-Coleska, Zaneta; Wang, Shaomeng
2009-09-30
Accurate prediction of the binding affinities of small-molecule ligands to their biological targets is fundamental for structure-based drug design but remains a very challenging task. In this paper, we have performed computational studies to predict the binding models of 31 small-molecule Smac (the second mitochondria-derived activator of caspase) mimetics to their target, the XIAP (X-linked inhibitor of apoptosis) protein, and their binding affinities. Our results showed that computational docking was able to reliably predict the binding models, as confirmed by experimentally determined crystal structures of some Smac mimetics complexed with XIAP. However, all the computational methods we have tested, including an empirical scoring function, two knowledge-based scoring functions, and MM-GBSA (molecular mechanics and generalized Born surface area), yield poor to modest prediction for binding affinities. The linear correlation coefficient (r(2)) value between the predicted affinities and the experimentally determined affinities was found to be between 0.21 and 0.36. Inclusion of ensemble protein-ligand conformations obtained from molecular dynamic simulations did not significantly improve the prediction. However, major improvement was achieved when the free-energy change for ligands between their free- and bound-states, or "ligand-reorganization free energy", was included in the MM-GBSA calculation, and the r(2) value increased from 0.36 to 0.66. The prediction was validated using 10 additional Smac mimetics designed and evaluated by an independent group. This study demonstrates that ligand reorganization free energy plays an important role in the overall binding free energy between Smac mimetics and XIAP. This term should be evaluated for other ligand-protein systems and included in the development of new scoring functions. To our best knowledge, this is the first computational study to demonstrate the importance of ligand reorganization free energy for the prediction of protein-ligand binding free energy.
NASA Astrophysics Data System (ADS)
Yoo, Soohaeng; Shao, Nan; Zeng, X. C.
2009-10-01
We report improved results of lowest-lying silicon clusters Si 30-Si 38. A large population of low-energy clusters are collected from previous searches by several research groups and the binding energies of these clusters are computed using density-functional theory (DFT) methods. Best candidates (isomers with high binding energies) are identified from the screening calculations. Additional constrained search is then performed for the best candidates using the basin-hopping method combined with DFT geometry optimization. The obtained low-lying clusters are classified according to binding energies computed using either the Perdew-Burke-Ernzerhof (PBE) functional or the Becke exchange and Lee-Yang-Parr correlation (BLYP) functional. We propose to rank low-lying clusters according to the mean PBE/BLYP binding energies in view that the PBE functional tends to give greater binding energies for more compact clusters whereas the BLYP functional tends to give greater binding energies for less compact clusters or clusters composed of small-sized magic-number clusters. Except for Si 30, the new search confirms again that medium-size silicon clusters Si 31-Si 38 constructed with proper fullerene cage motifs are most promising to be the lowest-energy structures.
Calculation of Host-Guest Binding Affinities Using a Quantum-Mechanical Energy Model.
Muddana, Hari S; Gilson, Michael K
2012-06-12
The prediction of protein-ligand binding affinities is of central interest in computer-aided drug discovery, but it is still difficult to achieve a high degree of accuracy. Recent studies suggesting that available force fields may be a key source of error motivate the present study, which reports the first mining minima (M2) binding affinity calculations based on a quantum mechanical energy model, rather than an empirical force field. We apply a semi-empirical quantum-mechanical energy function, PM6-DH+, coupled with the COSMO solvation model, to 29 host-guest systems with a wide range of measured binding affinities. After correction for a systematic error, which appears to derive from the treatment of polar solvation, the computed absolute binding affinities agree well with experimental measurements, with a mean error 1.6 kcal/mol and a correlation coefficient of 0.91. These calculations also delineate the contributions of various energy components, including solute energy, configurational entropy, and solvation free energy, to the binding free energies of these host-guest complexes. Comparison with our previous calculations, which used empirical force fields, point to significant differences in both the energetic and entropic components of the binding free energy. The present study demonstrates successful combination of a quantum mechanical Hamiltonian with the M2 affinity method.
The feasibility of an efficient drug design method with high-performance computers.
Yamashita, Takefumi; Ueda, Akihiko; Mitsui, Takashi; Tomonaga, Atsushi; Matsumoto, Shunji; Kodama, Tatsuhiko; Fujitani, Hideaki
2015-01-01
In this study, we propose a supercomputer-assisted drug design approach involving all-atom molecular dynamics (MD)-based binding free energy prediction after the traditional design/selection step. Because this prediction is more accurate than the empirical binding affinity scoring of the traditional approach, the compounds selected by the MD-based prediction should be better drug candidates. In this study, we discuss the applicability of the new approach using two examples. Although the MD-based binding free energy prediction has a huge computational cost, it is feasible with the latest 10 petaflop-scale computer. The supercomputer-assisted drug design approach also involves two important feedback procedures: The first feedback is generated from the MD-based binding free energy prediction step to the drug design step. While the experimental feedback usually provides binding affinities of tens of compounds at one time, the supercomputer allows us to simultaneously obtain the binding free energies of hundreds of compounds. Because the number of calculated binding free energies is sufficiently large, the compounds can be classified into different categories whose properties will aid in the design of the next generation of drug candidates. The second feedback, which occurs from the experiments to the MD simulations, is important to validate the simulation parameters. To demonstrate this, we compare the binding free energies calculated with various force fields to the experimental ones. The results indicate that the prediction will not be very successful, if we use an inaccurate force field. By improving/validating such simulation parameters, the next prediction can be made more accurate.
Zhang, Baofeng; D'Erasmo, Michael P; Murelli, Ryan P; Gallicchio, Emilio
2016-09-30
We report the results of a binding free energy-based virtual screening campaign of a library of 77 α-hydroxytropolone derivatives against the challenging RNase H active site of the reverse transcriptase (RT) enzyme of human immunodeficiency virus-1. Multiple protonation states, rotamer states, and binding modalities of each compound were individually evaluated. The work involved more than 300 individual absolute alchemical binding free energy parallel molecular dynamics calculations and over 1 million CPU hours on national computing clusters and a local campus computational grid. The thermodynamic and structural measures obtained in this work rationalize a series of characteristics of this system useful for guiding future synthetic and biochemical efforts. The free energy model identified key ligand-dependent entropic and conformational reorganization processes difficult to capture using standard docking and scoring approaches. Binding free energy-based optimization of the lead compounds emerging from the virtual screen has yielded four compounds with very favorable binding properties, which will be the subject of further experimental investigations. This work is one of the few reported applications of advanced-binding free energy models to large-scale virtual screening and optimization projects. It further demonstrates that, with suitable algorithms and automation, advanced-binding free energy models can have a useful role in early-stage drug-discovery programs.
Computational scheme for pH-dependent binding free energy calculation with explicit solvent.
Lee, Juyong; Miller, Benjamin T; Brooks, Bernard R
2016-01-01
We present a computational scheme to compute the pH-dependence of binding free energy with explicit solvent. Despite the importance of pH, the effect of pH has been generally neglected in binding free energy calculations because of a lack of accurate methods to model it. To address this limitation, we use a constant-pH methodology to obtain a true ensemble of multiple protonation states of a titratable system at a given pH and analyze the ensemble using the Bennett acceptance ratio (BAR) method. The constant pH method is based on the combination of enveloping distribution sampling (EDS) with the Hamiltonian replica exchange method (HREM), which yields an accurate semi-grand canonical ensemble of a titratable system. By considering the free energy change of constraining multiple protonation states to a single state or releasing a single protonation state to multiple states, the pH dependent binding free energy profile can be obtained. We perform benchmark simulations of a host-guest system: cucurbit[7]uril (CB[7]) and benzimidazole (BZ). BZ experiences a large pKa shift upon complex formation. The pH-dependent binding free energy profiles of the benchmark system are obtained with three different long-range interaction calculation schemes: a cutoff, the particle mesh Ewald (PME), and the isotropic periodic sum (IPS) method. Our scheme captures the pH-dependent behavior of binding free energy successfully. Absolute binding free energy values obtained with the PME and IPS methods are consistent, while cutoff method results are off by 2 kcal mol(-1) . We also discuss the characteristics of three long-range interaction calculation methods for constant-pH simulations. © 2015 The Protein Society.
Computation of pH-Dependent Binding Free Energies
Kim, M. Olivia; McCammon, J. Andrew
2015-01-01
Protein-ligand binding accompanies changes in the surrounding electrostatic environments of the two binding partners and may lead to changes in protonation upon binding. In cases where the complex formation results in a net transfer of protons, the binding process is pH-dependent. However, conventional free energy computations or molecular docking protocols typically employ fixed protonation states for the titratable groups in both binding partners set a priori, which are identical for the free and bound states. In this review, we draw attention to these important yet largely ignored binding-induced protonation changes in protein-ligand association by outlining physical origins and prevalence of the protonation changes upon binding. Following a summary of various theoretical methods for pKa prediction, we discuss the theoretical framework to examine the pH dependence of protein-ligand binding processes. PMID:26202905
Faller, Christina E; Raman, E Prabhu; MacKerell, Alexander D; Guvench, Olgun
2015-01-01
Fragment-based drug design (FBDD) involves screening low molecular weight molecules ("fragments") that correspond to functional groups found in larger drug-like molecules to determine their binding to target proteins or nucleic acids. Based on the principle of thermodynamic additivity, two fragments that bind nonoverlapping nearby sites on the target can be combined to yield a new molecule whose binding free energy is the sum of those of the fragments. Experimental FBDD approaches, like NMR and X-ray crystallography, have proven very useful but can be expensive in terms of time, materials, and labor. Accordingly, a variety of computational FBDD approaches have been developed that provide different levels of detail and accuracy.The Site Identification by Ligand Competitive Saturation (SILCS) method of computational FBDD uses all-atom explicit-solvent molecular dynamics (MD) simulations to identify fragment binding. The target is "soaked" in an aqueous solution with multiple fragments having different identities. The resulting computational competition assay reveals what small molecule types are most likely to bind which regions of the target. From SILCS simulations, 3D probability maps of fragment binding called "FragMaps" can be produced. Based on the probabilities relative to bulk, SILCS FragMaps can be used to determine "Grid Free Energies (GFEs)," which provide per-atom contributions to fragment binding affinities. For essentially no additional computational overhead relative to the production of the FragMaps, GFEs can be used to compute Ligand Grid Free Energies (LGFEs) for arbitrarily complex molecules, and these LGFEs can be used to rank-order the molecules in accordance with binding affinities.
Atomistic models for free energy evaluation of drug binding to membrane proteins.
Durdagi, S; Zhao, C; Cuervo, J E; Noskov, S Y
2011-01-01
The binding of various molecules to integral membrane proteins with optimal affinity and specificity is central to normal function of cell. While membrane proteins represent about one third of the whole cell proteome, they are a majority of common drug targets. The quest for the development of computational models capable of accurate evaluation of binding affinities, decomposition of the binding into its principal components and thus mapping molecular mechanisms of binding remains one of the main goals of modern computational biophysics and related drug development. The primary scope of this review will be on the recent extension of computational methods for the study of drug binding to membrane proteins. Several examples of such applications will be provided ranging from secondary transporters to voltage gated channels. In this mini-review, we will provide a short summary on the breadth of different methods for binding affinity evaluation. These methods include molecular docking with docking scoring functions, molecular dynamics (MD) simulations combined with post-processing analysis using Molecular Mechanics/Poisson Boltzmann (Generalized Born) Surface Area (MM/PB(GB)SA), as well as direct evaluation of free energies from Free Energy Perturbation (FEP) with constraining schemes, and Potential of Mean Force (PMF) computations. We will compare advantages and shortcomings of popular techniques and provide discussion on the integrative strategies for drug development aimed at targeting membrane proteins.
Advances in free-energy-based simulations of protein folding and ligand binding.
Perez, Alberto; Morrone, Joseph A; Simmerling, Carlos; Dill, Ken A
2016-02-01
Free-energy-based simulations are increasingly providing the narratives about the structures, dynamics and biological mechanisms that constitute the fabric of protein science. Here, we review two recent successes. It is becoming practical: first, to fold small proteins with free-energy methods without knowing substructures and second, to compute ligand-protein binding affinities, not just their binding poses. Over the past 40 years, the timescales that can be simulated by atomistic MD are doubling every 1.3 years--which is faster than Moore's law. Thus, these advances are not simply due to the availability of faster computers. Force fields, solvation models and simulation methodology have kept pace with computing advancements, and are now quite good. At the tip of the spear recently are GPU-based computing, improved fast-solvation methods, continued advances in force fields, and conformational sampling methods that harness external information. Copyright © 2015 Elsevier Ltd. All rights reserved.
Cloud Quantum Computing of an Atomic Nucleus
NASA Astrophysics Data System (ADS)
Dumitrescu, E. F.; McCaskey, A. J.; Hagen, G.; Jansen, G. R.; Morris, T. D.; Papenbrock, T.; Pooser, R. C.; Dean, D. J.; Lougovski, P.
2018-05-01
We report a quantum simulation of the deuteron binding energy on quantum processors accessed via cloud servers. We use a Hamiltonian from pionless effective field theory at leading order. We design a low-depth version of the unitary coupled-cluster ansatz, use the variational quantum eigensolver algorithm, and compute the binding energy to within a few percent. Our work is the first step towards scalable nuclear structure computations on a quantum processor via the cloud, and it sheds light on how to map scientific computing applications onto nascent quantum devices.
Cloud Quantum Computing of an Atomic Nucleus
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dumitrescu, Eugene F.; McCaskey, Alex J.; Hagen, Gaute
Here, we report a quantum simulation of the deuteron binding energy on quantum processors accessed via cloud servers. We use a Hamiltonian from pionless effective field theory at leading order. We design a low-depth version of the unitary coupled-cluster ansatz, use the variational quantum eigensolver algorithm, and compute the binding energy to within a few percent. Our work is the first step towards scalable nuclear structure computations on a quantum processor via the cloud, and it sheds light on how to map scientific computing applications onto nascent quantum devices.
Cloud Quantum Computing of an Atomic Nucleus.
Dumitrescu, E F; McCaskey, A J; Hagen, G; Jansen, G R; Morris, T D; Papenbrock, T; Pooser, R C; Dean, D J; Lougovski, P
2018-05-25
We report a quantum simulation of the deuteron binding energy on quantum processors accessed via cloud servers. We use a Hamiltonian from pionless effective field theory at leading order. We design a low-depth version of the unitary coupled-cluster ansatz, use the variational quantum eigensolver algorithm, and compute the binding energy to within a few percent. Our work is the first step towards scalable nuclear structure computations on a quantum processor via the cloud, and it sheds light on how to map scientific computing applications onto nascent quantum devices.
Cloud Quantum Computing of an Atomic Nucleus
Dumitrescu, Eugene F.; McCaskey, Alex J.; Hagen, Gaute; ...
2018-05-23
Here, we report a quantum simulation of the deuteron binding energy on quantum processors accessed via cloud servers. We use a Hamiltonian from pionless effective field theory at leading order. We design a low-depth version of the unitary coupled-cluster ansatz, use the variational quantum eigensolver algorithm, and compute the binding energy to within a few percent. Our work is the first step towards scalable nuclear structure computations on a quantum processor via the cloud, and it sheds light on how to map scientific computing applications onto nascent quantum devices.
Giovannelli, Edoardo; Procacci, Piero; Cardini, Gianni; Pagliai, Marco; Volkov, Victor; Chelli, Riccardo
2017-12-12
The fast-switching decoupling method is a powerful nonequilibrium technique to compute absolute binding free energies of ligand-receptor complexes (Sandberg et al., J. Chem. Theory Comput. 2014, 11, 423-435). Inspired by the theory of noncovalent binding association of Gilson and co-workers (Biophys. J. 1997, 72, 1047-1069), we develop two approaches, termed binded-domain and single-point alchemical-path schemes (BiD-AP and SiP-AP), based on the possibility of performing alchemical trajectories during which the ligand is constrained to fixed positions relative to the receptor. The BiD-AP scheme exploits a recent generalization of nonequilibrium work theorems to estimate the free energy difference between the coupled and uncoupled states of the ligand-receptor complex. With respect to the fast-switching decoupling method without constraints, BiD-AP prevents the ligand from leaving the binding site, but still requires an estimate of the positional binding-site volume, which may not be a simple task. On the other side, the SiP-AP scheme allows avoidance of the calculation of the binding-site volume by introducing an additional equilibrium simulation of ligand and receptor in the bound state. In the companion article (DOI: 10.1021/acs.jctc.7b00595), we show that the extra computational effort required by SiP-AP leads to a significant improvement of accuracy in the free energy estimates.
Rapid and Reliable Binding Affinity Prediction of Bromodomain Inhibitors: A Computational Study
2016-01-01
Binding free energies of bromodomain inhibitors are calculated with recently formulated approaches, namely ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling). A set of compounds is provided by GlaxoSmithKline, which represents a range of chemical functionality and binding affinities. The predicted binding free energies exhibit a good Spearman correlation of 0.78 with the experimental data from the 3-trajectory ESMACS, and an excellent correlation of 0.92 from the TIES approach where applicable. Given access to suitable high end computing resources and a high degree of automation, we can compute individual binding affinities in a few hours with precisions no greater than 0.2 kcal/mol for TIES, and no larger than 0.34 and 1.71 kcal/mol for the 1- and 3-trajectory ESMACS approaches. PMID:28005370
An introduction to best practices in free energy calculations.
Shirts, Michael R; Mobley, David L
2013-01-01
Free energy calculations are extremely useful for investigating small-molecule biophysical properties such as protein-ligand binding affinities and partition coefficients. However, these calculations are also notoriously difficult to implement correctly. In this chapter, we review standard methods for computing free energy via simulation, discussing current best practices and examining potential pitfalls for computational researchers performing them for the first time. We include a variety of examples and tips for how to set up and conduct these calculations, including applications to relative binding affinities and small-molecule solvation free energies.
Faller, Christina E.; Raman, E. Prabhu; MacKerell, Alexander D.; Guvench, Olgun
2015-01-01
Fragment-based drug design (FBDD) involves screening low molecular weight molecules (“fragments”) that correspond to functional groups found in larger drug-like molecules to determine their binding to target proteins or nucleic acids. Based on the principle of thermodynamic additivity, two fragments that bind non-overlapping nearby sites on the target can be combined to yield a new molecule whose binding free energy is the sum of those of the fragments. Experimental FBDD approaches, like NMR and X-ray crystallography, have proven very useful but can be expensive in terms of time, materials, and labor. Accordingly, a variety of computational FBDD approaches have been developed that provide different levels of detail and accuracy. The Site Identification by Ligand Competitive Saturation (SILCS) method of computational FBDD uses all-atom explicit-solvent molecular dynamics (MD) simulations to identify fragment binding. The target is “soaked” in an aqueous solution with multiple fragments having different identities. The resulting computational competition assay reveals what small molecule types are most likely to bind which regions of the target. From SILCS simulations, 3D probability maps of fragment binding called “FragMaps” can be produced. Based on the probabilities relative to bulk, SILCS FragMaps can be used to determine “Grid Free Energies (GFEs),” which provide per-atom contributions to fragment binding affinities. For essentially no additional computational overhead relative to the production of the FragMaps, GFEs can be used to compute Ligand Grid Free Energies (LGFEs) for arbitrarily complex molecules, and these LGFEs can be used to rank-order the molecules in accordance with binding affinities. PMID:25709034
Computational search for aflatoxin binding proteins
NASA Astrophysics Data System (ADS)
Wang, Ying; Liu, Jinfeng; Zhang, Lujia; He, Xiao; Zhang, John Z. H.
2017-10-01
Aflatoxin is one of the mycotoxins that contaminate various food products. Among various aflatoxin types (B1, B2, G1, G2 and M1), aflatoxin B1 is the most important and the most toxic one. In this study, through computational screening, we found that several proteins may bind specifically with different type of aflatoxins. Combination of theoretical methods including target fishing, molecular docking, molecular dynamics (MD) simulation, MM/PBSA calculation were utilized to search for new aflatoxin B1 binding proteins. A recently developed method for calculating entropic contribution to binding free energy called interaction entropy (IE) was employed to compute the binding free energy between the protein and aflatoxin B1. Through comprehensive comparison, three proteins, namely, trihydroxynaphthalene reductase, GSK-3b, and Pim-1 were eventually selected as potent aflatoxin B1 binding proteins. GSK-3b and Pim-1 are drug targets of cancers or neurological diseases. GSK-3b is the strongest binder for aflatoxin B1.
NASA Astrophysics Data System (ADS)
Sarkar, Supratik; Sarkar, Samrat; Bose, Chayanika
2018-07-01
We present a general formulation of the ground state binding energy of a shallow hydrogenic impurity in spherical quantum dot with parabolic confinement, considering the effects of polarization and self energy. The variational approach within the effective mass approximation is employed here. The binding energy of an on-center impurity is computed for a GaAs/AlxGa1-xAs quantum dot as a function of the dot size with the dot barrier as parameter. The influence of polarization and self energy are also treated separately. Results indicate that the binding energy increases due to the presence of polarization charge, while decreases due to the self energy of the carrier. An overall enhancement in impurity binding energy, especially for small dots is noted.
On binding energy of trions in bulk materials
NASA Astrophysics Data System (ADS)
Filikhin, Igor; Kezerashvili, Roman Ya.; Vlahovic, Branislav
2018-03-01
We study the negatively T- and positively T+ charged trions in bulk materials in the effective mass approximation within the framework of a potential model. The binding energies of trions in various semiconductors are calculated by employing Faddeev equation in configuration space. Results of calculations of the binding energies for T- are consistent with previous computational studies and are in reasonable agreement with experimental measurements, while the T+ is unbound for all considered cases. The mechanism of formation of the binding energy of trions is analyzed by comparing contributions of a mass-polarization term related to kinetic energy operators and a term related to the Coulomb repulsion of identical particles.
Computational studies of Ras and PI3K
NASA Technical Reports Server (NTRS)
Ren, Lei; Cucinotta, Francis A.
2004-01-01
Until recently, experimental techniques in molecular cell biology have been the primary means to investigate biological risk upon space radiation. However, computational modeling provides an alternative theoretical approach, which utilizes various computational tools to simulate proteins, nucleotides, and their interactions. In this study, we are focused on using molecular mechanics (MM) and molecular dynamics (MD) to study the mechanism of protein-protein binding and to estimate the binding free energy between proteins. Ras is a key element in a variety of cell processes, and its activation of phosphoinositide 3-kinase (PI3K) is important for survival of transformed cells. Different computational approaches for this particular study are presented to calculate the solvation energies and binding free energies of H-Ras and PI3K. The goal of this study is to establish computational methods to investigate the roles of different proteins played in the cellular responses to space radiation, including modification of protein function through gene mutation, and to support the studies in molecular cell biology and theoretical kinetics models for our risk assessment project.
Wahl, Joel; Smiesko, Martin
2018-05-04
Computational methods, namely Molecular Dynamics Simulations (MD simulations) in combination with Inhomogeneous Fluid Solvation Theory (IFST) were used to retrospectively investigate various cases of ligand structure modifications that led to the displacement of binding site water molecules. Our findings are that the water displacement per se is energetically unfavorable in the discussed examples, and that it is merely the fine balance between change in protein-ligand interaction energy, ligand solvation free energies and binding site solvation free energies that determine if water displacement is favorable or not. We furthermore evaluated if we can reproduce experimental binding affinities by a computational approach combining changes in solvation free energies with changes in protein-ligand interaction energies and entropies. In two of the seven cases, this estimation led to large errors, implying that accurate predictions of relative binding free energies based on solvent thermodynamics is challenging. Still, MD simulations can provide insights into which water molecules can be targeted for displacement. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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.
Accurate, robust and reliable calculations of Poisson-Boltzmann binding energies
Nguyen, Duc D.; Wang, Bao
2017-01-01
Poisson-Boltzmann (PB) model is one of the most popular implicit solvent models in biophysical modeling and computation. The ability of providing accurate and reliable PB estimation of electrostatic solvation free energy, ΔGel, and binding free energy, ΔΔGel, is important to computational biophysics and biochemistry. In this work, we investigate the grid dependence of our PB solver (MIBPB) with SESs for estimating both electrostatic solvation free energies and electrostatic binding free energies. It is found that the relative absolute error of ΔGel obtained at the grid spacing of 1.0 Å compared to ΔGel at 0.2 Å averaged over 153 molecules is less than 0.2%. Our results indicate that the use of grid spacing 0.6 Å ensures accuracy and reliability in ΔΔGel calculation. In fact, the grid spacing of 1.1 Å appears to deliver adequate accuracy for high throughput screening. PMID:28211071
Theoretical study of transition-metal ions bound to benzene
NASA Technical Reports Server (NTRS)
Bauschlicher, Charles W., Jr.; Partridge, Harry; Langhoff, Stephen R.
1992-01-01
Theoretical binding energies are reported for all first-row and selected second-row transition metal ions (M+) bound to benzene. The calculations employ basis sets of at least double-zeta plus polarization quality and account for electron correlation using the modified coupled-pair functional method. While the bending is predominantly electrostatic, the binding energies are significantly increased by electron correlation, because the donation from the metal d orbitals to the benzene pi* orbitals is not well described at the self-consistent-field level. The uncertainties in the computed binding energies are estimated to be about 5 kcal/mol. Although the calculated and experimental binding energies generally agree to within their combined uncertainties, it is likely that the true binding energies lie in the lower portion of the experimental range. This is supported by the very good agreement between the theoretical and recent experimental binding energies for AgC6H6(+).
Calculation of Cyclodextrin Binding Affinities: Energy, Entropy, and Implications for Drug Design
Chen, Wei; Chang, Chia-En; Gilson, Michael K.
2004-01-01
The second generation Mining Minima method yields binding affinities accurate to within 0.8 kcal/mol for the associations of α-, β-, and γ-cyclodextrin with benzene, resorcinol, flurbiprofen, naproxen, and nabumetone. These calculations require hours to a day on a commodity computer. The calculations also indicate that the changes in configurational entropy upon binding oppose association by as much as 24 kcal/mol and result primarily from a narrowing of energy wells in the bound versus the free state, rather than from a drop in the number of distinct low-energy conformations on binding. Also, the configurational entropy is found to vary substantially among the bound conformations of a given cyclodextrin-guest complex. This result suggests that the configurational entropy must be accounted for to reliably rank docked conformations in both host-guest and ligand-protein complexes. In close analogy with the common experimental observation of entropy-enthalpy compensation, the computed entropy changes show a near-linear relationship with the changes in mean potential plus solvation energy. PMID:15339804
The Successive OH Binding Energies of Sc(OH)n+ for n=1-3
NASA Technical Reports Server (NTRS)
Bauschlicher, Charles W., Jr.; Partridge, Harry; Arnold, James O. (Technical Monitor)
1996-01-01
The geometries of Sc(OH)n+, for n = 1-3, have been optimized using density functional theory, in conjunction with the B3LYP hybrid functional. The zero-point energies are computed at the same level of theory. The successive OH bond energies have been computed at the CCSD(T) level for ScOH+ and Sc(OH)2+. The computed result for ScOD+ is in excellent agreement with the recent experiment of Armentrout and co-workers. There is a dramatic drop for the third OH, because Sc+ has only two valence electrons and therefore the bonding changes when the third OH is added. The difference between the B3LYP and CCSD(T) OH binding energies for the first two OH groups is discussed.
Raman, E. Prabhu; MacKerell, Alexander D.
2015-01-01
The thermodynamic driving forces behind small molecule-protein binding are still not well understood, including the variability of those forces associated with different types of ligands in different binding pockets. To better understand these phenomena we calculate spatially resolved thermodynamic contributions of the different molecular degrees of freedom for the binding of propane and methanol to multiple pockets on the proteins Factor Xa and p38 MAP kinase. Binding thermodynamics are computed using a statistical thermodynamics based end-point method applied on a canonical ensemble comprising the protein-ligand complexes and the corresponding free states in an explicit solvent environment. Energetic and entropic contributions of water and ligand degrees of freedom computed from the configurational ensemble provides an unprecedented level of detail into the mechanisms of binding. Direct protein-ligand interaction energies play a significant role in both non-polar and polar binding, which is comparable to water reorganization energy. Loss of interactions with water upon binding strongly compensates these contributions leading to relatively small binding enthalpies. For both solutes, the entropy of water reorganization is found to favor binding in agreement with the classical view of the “hydrophobic effect”. Depending on the specifics of the binding pocket, both energy-entropy compensation and reinforcement mechanisms are observed. Notable is the ability to visualize the spatial distribution of the thermodynamic contributions to binding at atomic resolution showing significant differences in the thermodynamic contributions of water to the binding of propane versus methanol. PMID:25625202
Jiang, Wei; Roux, Benoît
2010-07-01
Free Energy Perturbation with Replica Exchange Molecular Dynamics (FEP/REMD) offers a powerful strategy to improve the convergence of free energy computations. In particular, it has been shown previously that a FEP/REMD scheme allowing random moves within an extended replica ensemble of thermodynamic coupling parameters "lambda" can improve the statistical convergence in calculations of absolute binding free energy of ligands to proteins [J. Chem. Theory Comput. 2009, 5, 2583]. In the present study, FEP/REMD is extended and combined with an accelerated MD simulations method based on Hamiltonian replica-exchange MD (H-REMD) to overcome the additional problems arising from the existence of kinetically trapped conformations within the protein receptor. In the combined strategy, each system with a given thermodynamic coupling factor lambda in the extended ensemble is further coupled with a set of replicas evolving on a biased energy surface with boosting potentials used to accelerate the inter-conversion among different rotameric states of the side chains in the neighborhood of the binding site. Exchanges are allowed to occur alternatively along the axes corresponding to the thermodynamic coupling parameter lambda and the boosting potential, in an extended dual array of coupled lambda- and H-REMD simulations. The method is implemented on the basis of new extensions to the REPDSTR module of the biomolecular simulation program CHARMM. As an illustrative example, the absolute binding free energy of p-xylene to the nonpolar cavity of the L99A mutant of T4 lysozyme was calculated. The tests demonstrate that the dual lambda-REMD and H-REMD simulation scheme greatly accelerates the configurational sampling of the rotameric states of the side chains around the binding pocket, thereby improving the convergence of the FEP computations.
Raman, E Prabhu; Lakkaraju, Sirish Kaushik; Denny, Rajiah Aldrin; MacKerell, Alexander D
2017-06-05
Accurate and rapid estimation of relative binding affinities of ligand-protein complexes is a requirement of computational methods for their effective use in rational ligand design. Of the approaches commonly used, free energy perturbation (FEP) methods are considered one of the most accurate, although they require significant computational resources. Accordingly, it is desirable to have alternative methods of similar accuracy but greater computational efficiency to facilitate ligand design. In the present study relative free energies of binding are estimated for one or two non-hydrogen atom changes in compounds targeting the proteins ACK1 and p38 MAP kinase using three methods. The methods include standard FEP, single-step free energy perturbation (SSFEP) and the site-identification by ligand competitive saturation (SILCS) ligand grid free energy (LGFE) approach. Results show the SSFEP and SILCS LGFE methods to be competitive with or better than the FEP results for the studied systems, with SILCS LGFE giving the best agreement with experimental results. This is supported by additional comparisons with published FEP data on p38 MAP kinase inhibitors. While both the SSFEP and SILCS LGFE approaches require a significant upfront computational investment, they offer a 1000-fold computational savings over FEP for calculating the relative affinities of ligand modifications once those pre-computations are complete. An illustrative example of the potential application of these methods in the context of screening large numbers of transformations is presented. Thus, the SSFEP and SILCS LGFE approaches represent viable alternatives for actively driving ligand design during drug discovery and development. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Evaluation of water displacement energetics in protein binding sites with grid cell theory.
Gerogiokas, G; Southey, M W Y; Mazanetz, M P; Heifetz, A; Hefeitz, A; Bodkin, M; Law, R J; Michel, J
2015-04-07
Excess free energies, enthalpies and entropies of water in protein binding sites were computed via classical simulations and Grid Cell Theory (GCT) analyses for three pairs of congeneric ligands in complex with the proteins scytalone dehydratase, p38α MAP kinase and EGFR kinase respectively. Comparative analysis is of interest since the binding modes for each ligand pair differ in the displacement of one binding site water molecule, but significant variations in relative binding affinities are observed. Protocols that vary in their use of restraints on protein and ligand atoms were compared to determine the influence of protein-ligand flexibility on computed water structure and energetics, and to assess protocols for routine analyses of protein-ligand complexes. The GCT-derived binding affinities correctly reproduce experimental trends, but the magnitude of the predicted changes in binding affinities is exaggerated with respect to results from a previous Monte Carlo Free Energy Perturbation study. Breakdown of the GCT water free energies into enthalpic and entropic components indicates that enthalpy changes dominate the observed variations in energetics. In EGFR kinase GCT analyses revealed that replacement of a pyrimidine by a cyanopyridine perturbs water energetics up three hydration shells away from the ligand.
Calculating binding free energies of host-guest systems using the AMOEBA polarizable force field.
Bell, David R; Qi, Rui; Jing, Zhifeng; Xiang, Jin Yu; Mejias, Christopher; Schnieders, Michael J; Ponder, Jay W; Ren, Pengyu
2016-11-09
Molecular recognition is of paramount interest in many applications. Here we investigate a series of host-guest systems previously used in the SAMPL4 blind challenge by using molecular simulations and the AMOEBA polarizable force field. The free energy results computed by Bennett's acceptance ratio (BAR) method using the AMOEBA polarizable force field ranked favorably among the entries submitted to the SAMPL4 host-guest competition [Muddana, et al., J. Comput.-Aided Mol. Des., 2014, 28, 305-317]. In this work we conduct an in-depth analysis of the AMOEBA force field host-guest binding thermodynamics by using both BAR and the orthogonal space random walk (OSRW) methods. The binding entropy-enthalpy contributions are analyzed for each host-guest system. For systems of inordinate binding entropy-enthalpy values, we further examine the hydrogen bonding patterns and configurational entropy contribution. The binding mechanism of this series of host-guest systems varies from ligand to ligand, driven by enthalpy and/or entropy changes. Convergence of BAR and OSRW binding free energy methods is discussed. Ultimately, this work illustrates the value of molecular modelling and advanced force fields for the exploration and interpretation of binding thermodynamics.
Viricel, Clément; de Givry, Simon; Schiex, Thomas; Barbe, Sophie
2018-02-20
Accurate and economic methods to predict change in protein binding free energy upon mutation are imperative to accelerate the design of proteins for a wide range of applications. Free energy is defined by enthalpic and entropic contributions. Following the recent progresses of Artificial Intelligence-based algorithms for guaranteed NP-hard energy optimization and partition function computation, it becomes possible to quickly compute minimum energy conformations and to reliably estimate the entropic contribution of side-chains in the change of free energy of large protein interfaces. Using guaranteed Cost Function Network algorithms, Rosetta energy functions and Dunbrack's rotamer library, we developed and assessed EasyE and JayZ, two methods for binding affinity estimation that ignore or include conformational entropic contributions on a large benchmark of binding affinity experimental measures. If both approaches outperform most established tools, we observe that side-chain conformational entropy brings little or no improvement on most systems but becomes crucial in some rare cases. as open-source Python/C ++ code at sourcesup.renater.fr/projects/easy-jayz. thomas.schiex@inra.fr and sophie.barbe@insa-toulouse.fr. Supplementary data are available at Bioinformatics online.
Free Energy Simulations of Ligand Binding to the Aspartate Transporter GltPh
Heinzelmann, Germano; Baştuğ, Turgut; Kuyucak, Serdar
2011-01-01
Glutamate/Aspartate transporters cotransport three Na+ and one H+ ions with the substrate and countertransport one K+ ion. The binding sites for the substrate and two Na+ ions have been observed in the crystal structure of the archeal homolog GltPh, while the binding site for the third Na+ ion has been proposed from computational studies and confirmed by experiments. Here we perform detailed free energy simulations of GltPh, giving a comprehensive characterization of the substrate and ion binding sites, and calculating their binding free energies in various configurations. Our results show unequivocally that the substrate binds after the binding of two Na+ ions. They also shed light into Asp/Glu selectivity of GltPh, which is not observed in eukaryotic glutamate transporters. PMID:22098736
NASA Astrophysics Data System (ADS)
Tran, Diem-Trang T.; Le, Ly T.; Truong, Thanh N.
2013-08-01
Drug binding and unbinding are transient processes which are hardly observed by experiment and difficult to analyze by computational techniques. In this paper, we employed a cost-effective method called "pathway docking" in which molecular docking was used to screen ligand-receptor binding free energy surface to reveal possible paths of ligand approaching protein binding pocket. A case study was applied on oseltamivir, the key drug against influenza a virus. The equilibrium pathways identified by this method are found to be similar to those identified in prior studies using highly expensive computational approaches.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Villarreal, Oscar D.; Yu, Lili; Department of Laboratory Medicine, Yancheng Vocational Institute of Health Sciences, Yancheng, Jiangsu 224006
Computing the ligand-protein binding affinity (or the Gibbs free energy) with chemical accuracy has long been a challenge for which many methods/approaches have been developed and refined with various successful applications. False positives and, even more harmful, false negatives have been and still are a common occurrence in practical applications. Inevitable in all approaches are the errors in the force field parameters we obtain from quantum mechanical computation and/or empirical fittings for the intra- and inter-molecular interactions. These errors propagate to the final results of the computed binding affinities even if we were able to perfectly implement the statistical mechanicsmore » of all the processes relevant to a given problem. And they are actually amplified to various degrees even in the mature, sophisticated computational approaches. In particular, the free energy perturbation (alchemical) approaches amplify the errors in the force field parameters because they rely on extracting the small differences between similarly large numbers. In this paper, we develop a hybrid steered molecular dynamics (hSMD) approach to the difficult binding problems of a ligand buried deep inside a protein. Sampling the transition along a physical (not alchemical) dissociation path of opening up the binding cavity- -pulling out the ligand- -closing back the cavity, we can avoid the problem of error amplifications by not relying on small differences between similar numbers. We tested this new form of hSMD on retinol inside cellular retinol-binding protein 1 and three cases of a ligand (a benzylacetate, a 2-nitrothiophene, and a benzene) inside a T4 lysozyme L99A/M102Q(H) double mutant. In all cases, we obtained binding free energies in close agreement with the experimentally measured values. This indicates that the force field parameters we employed are accurate and that hSMD (a brute force, unsophisticated approach) is free from the problem of error amplification suffered by many sophisticated approaches in the literature.« less
Zhang, Yuxin; Huang, Xiaoqin; Han, Keli; Zheng, Fang; Zhan, Chang-Guo
2016-11-25
The combined molecular dynamics (MD) and potential of mean force (PMF) simulations have been performed to determine the free energy profile of the CocE)-(+)-cocaine binding process in comparison with that of the corresponding CocE-(-)-cocaine binding process. According to the MD simulations, the equilibrium CocE-(+)-cocaine binding mode is similar to the CocE-(-)-cocaine binding mode. However, based on the simulated free energy profiles, a significant free energy barrier (∼5 kcal/mol) exists in the CocE-(+)-cocaine binding process whereas no obvious free energy barrier exists in the CocE-(-)-cocaine binding process, although the free energy barrier of ∼5 kcal/mol is not high enough to really slow down the CocE-(+)-cocaine binding process. In addition, the obtained free energy profiles also demonstrate that (+)-cocaine and (-)-cocaine have very close binding free energies with CocE, with a negligible difference (∼0.2 kcal/mol), which is qualitatively consistent with the nearly same experimental K M values of the CocE enzyme for (+)-cocaine and (-)-cocaine. The consistency between the computational results and available experimental data suggests that the mechanistic insights obtained from this study are reasonable. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Universal aspects of adhesion and atomic force microscopy
NASA Technical Reports Server (NTRS)
Banerjea, Amitava; Smith, John R.; Ferrante, John
1990-01-01
Adhesive energies are computed for flat and atomically sharp tips as a function of the normal distance to the substrate. The dependence of binding energies on tip shape is investigated. The magnitudes of the binding energies for the atomic force microscope are found to depend sensitively on tip material, tip shape and the sample site being probed. The form of the energy-distance curve, however, is universal and independent of these variables, including tip shape.
2017-01-01
Binding free energy calculations that make use of alchemical pathways are becoming increasingly feasible thanks to advances in hardware and algorithms. Although relative binding free energy (RBFE) calculations are starting to find widespread use, absolute binding free energy (ABFE) calculations are still being explored mainly in academic settings due to the high computational requirements and still uncertain predictive value. However, in some drug design scenarios, RBFE calculations are not applicable and ABFE calculations could provide an alternative. Computationally cheaper end-point calculations in implicit solvent, such as molecular mechanics Poisson–Boltzmann surface area (MMPBSA) calculations, could too be used if one is primarily interested in a relative ranking of affinities. Here, we compare MMPBSA calculations to previously performed absolute alchemical free energy calculations in their ability to correlate with experimental binding free energies for three sets of bromodomain–inhibitor pairs. Different MMPBSA approaches have been considered, including a standard single-trajectory protocol, a protocol that includes a binding entropy estimate, and protocols that take into account the ligand hydration shell. Despite the improvements observed with the latter two MMPBSA approaches, ABFE calculations were found to be overall superior in obtaining correlation with experimental affinities for the test cases considered. A difference in weighted average Pearson () and Spearman () correlations of 0.25 and 0.31 was observed when using a standard single-trajectory MMPBSA setup ( = 0.64 and = 0.66 for ABFE; = 0.39 and = 0.35 for MMPBSA). The best performing MMPBSA protocols returned weighted average Pearson and Spearman correlations that were about 0.1 inferior to ABFE calculations: = 0.55 and = 0.56 when including an entropy estimate, and = 0.53 and = 0.55 when including explicit water molecules. Overall, the study suggests that ABFE calculations are indeed the more accurate approach, yet there is also value in MMPBSA calculations considering the lower compute requirements, and if agreement to experimental affinities in absolute terms is not of interest. Moreover, for the specific protein–ligand systems considered in this study, we find that including an explicit ligand hydration shell or a binding entropy estimate in the MMPBSA calculations resulted in significant performance improvements at a negligible computational cost. PMID:28786670
Tropomyosin movement on F-actin during muscle activation explained by energy landscapes
Orzechowski, Marek; Moore, Jeffrey R.; Fischer, Stefan; Lehman, William
2014-01-01
Muscle contraction is regulated by tropomyosin movement across the thin filament surface, which exposes or blocks myosin-binding sites on actin. Recent atomic structures of F-actin-tropomyosin have yielded the positions of tropomyosin on myosin-free and myosin-decorated actin. Here, the repositioning of α-tropomyosin between these locations on F-actin was systematically examined by optimizing the energy of the complex for a wide range of tropomyosin positions on F-actin. The resulting energy landscape provides a full-map of the F-actin surface preferred by tropomyosin, revealing a broad energy basin associated with the tropomyosin position that blocks myosin-binding. This is consistent with previously proposed low-energy oscillations of semi-rigid tropomyosin, necessary for shifting of tropomyosin following troponin-binding. In contrast, the landscape shows much less favorable energies when tropomyosin locates near its myosin-induced “open-state” position. This indicates that spontaneous movement of tropomyosin away from its energetic “ground-state” to the open-state is unlikely in absence of myosin. Instead, myosin-binding must drive tropomyosin toward the open-state to activate the thin filament. Additional energy landscapes were computed for disease-causing actin mutants that distort the topology of the actin-tropomyosin energy landscape, explaining their phenotypes. Thus, the computation of such energy landscapes offers a sensitive way to estimate the impact of mutations. PMID:24412204
Tropomyosin movement on F-actin during muscle activation explained by energy landscapes.
Orzechowski, Marek; Moore, Jeffrey R; Fischer, Stefan; Lehman, William
2014-03-01
Muscle contraction is regulated by tropomyosin movement across the thin filament surface, which exposes or blocks myosin-binding sites on actin. Recent atomic structures of F-actin-tropomyosin have yielded the positions of tropomyosin on myosin-free and myosin-decorated actin. Here, the repositioning of α-tropomyosin between these locations on F-actin was systematically examined by optimizing the energy of the complex for a wide range of tropomyosin positions on F-actin. The resulting energy landscape provides a full-map of the F-actin surface preferred by tropomyosin, revealing a broad energy basin associated with the tropomyosin position that blocks myosin-binding. This is consistent with previously proposed low-energy oscillations of semi-rigid tropomyosin, necessary for shifting of tropomyosin following troponin-binding. In contrast, the landscape shows much less favorable energies when tropomyosin locates near its myosin-induced "open-state" position. This indicates that spontaneous movement of tropomyosin away from its energetic "ground-state" to the open-state is unlikely in absence of myosin. Instead, myosin-binding must drive tropomyosin toward the open-state to activate the thin filament. Additional energy landscapes were computed for disease-causing actin mutants that distort the topology of the actin-tropomyosin energy landscape, explaining their phenotypes. Thus, the computation of such energy landscapes offers a sensitive way to estimate the impact of mutations. Copyright © 2014 Elsevier Inc. All rights reserved.
The Study of the Successive Metal-ligand Binding Energies for Fe(+), Fe(-), V(+) and Co(+)
NASA Technical Reports Server (NTRS)
Bauschlicher, Charles W., Jr.; Ricca, Alessandra; Maitre, Philippe; Langhoff, Stephen R. (Technical Monitor)
1994-01-01
The successive binding energies of CO and H2O to Fe(+), CO to Fe(-), and H2 to Co(+) and V(+) are presented. Overall the computed results are in good agreement with experiment. The trends in binding energies are analyzed in terms of metal to ligand donation, ligand to metal donation, ligand-ligand repulsion, and changes in the metal atom, such as hybridization, promotion, and spin multiplicity. The geometry and vibrational frequencies are also shown to be directly affected by these effects.
The Study Of The Successive Metal-Ligand Binding Energies For Fe+, Fe-, V+ and Co+
NASA Technical Reports Server (NTRS)
Bauschicher, Charles W., Jr.; Ricca, Alessandra; Maitre, Philippe; Langhoff, Stephen R. (Technical Monitor)
1995-01-01
The successive binding energies of CO and H2O to Fe(+), CO to Fe(-), and H2 to Co(+) and V(+) are presented. Overall the computed results are in good agreement with experiment. The trends in binding energies are analyzed in terms of metal to ligand donation, ligand to metal donation, ligand-ligand repulsion, and changes in the metal atom, such as hybridization, promotion, and spin multiplicity. The geometry and vibrational frequencies are also shown to be directly affected by these effects.
Towards accurate free energy calculations in ligand protein-binding studies.
Steinbrecher, Thomas; Labahn, Andreas
2010-01-01
Cells contain a multitude of different chemical reaction paths running simultaneously and quite independently next to each other. This amazing feat is enabled by molecular recognition, the ability of biomolecules to form stable and specific complexes with each other and with their substrates. A better understanding of this process, i.e. of the kinetics, structures and thermodynamic properties of biomolecule binding, would be invaluable in the study of biological systems. In addition, as the mode of action of many pharmaceuticals is based upon their inhibition or activation of biomolecule targets, predictive models of small molecule receptor binding are very helpful tools in rational drug design. Since the goal here is normally to design a new compound with a high inhibition strength, one of the most important thermodynamic properties is the binding free energy DeltaG(0). The prediction of binding constants has always been one of the major goals in the field of computational chemistry, because the ability to reliably assess a hypothetical compound's binding properties without having to synthesize it first would save a tremendous amount of work. The different approaches to this question range from fast and simple empirical descriptor methods to elaborate simulation protocols aimed at putting the computation of free energies onto a solid foundation of statistical thermodynamics. While the later methods are still not suited for the screenings of thousands of compounds that are routinely performed in computational drug design studies, they are increasingly put to use for the detailed study of protein ligand interactions. This review will focus on molecular mechanics force field based free energy calculations and their application to the study of protein ligand interactions. After a brief overview of other popular methods for the calculation of free energies, we will describe recent advances in methodology and a variety of exemplary studies of molecular dynamics simulation based free energy calculations.
Fox, Stephen J; Pittock, Chris; Tautermann, Christofer S; Fox, Thomas; Christ, Clara; Malcolm, N O J; Essex, Jonathan W; Skylaris, Chris-Kriton
2013-08-15
Schemes of increasing sophistication for obtaining free energies of binding have been developed over the years, where configurational sampling is used to include the all-important entropic contributions to the free energies. However, the quality of the results will also depend on the accuracy with which the intermolecular interactions are computed at each molecular configuration. In this context, the energy change associated with the rearrangement of electrons (electronic polarization and charge transfer) upon binding is a very important effect. Classical molecular mechanics force fields do not take this effect into account explicitly, and polarizable force fields and semiempirical quantum or hybrid quantum-classical (QM/MM) calculations are increasingly employed (at higher computational cost) to compute intermolecular interactions in free-energy schemes. In this work, we investigate the use of large-scale quantum mechanical calculations from first-principles as a way of fully taking into account electronic effects in free-energy calculations. We employ a one-step free-energy perturbation (FEP) scheme from a molecular mechanical (MM) potential to a quantum mechanical (QM) potential as a correction to thermodynamic integration calculations within the MM potential. We use this approach to calculate relative free energies of hydration of small aromatic molecules. Our quantum calculations are performed on multiple configurations from classical molecular dynamics simulations. The quantum energy of each configuration is obtained from density functional theory calculations with a near-complete psinc basis set on over 600 atoms using the ONETEP program.
Conformational Transitions and Convergence of Absolute Binding Free Energy Calculations
Lapelosa, Mauro; Gallicchio, Emilio; Levy, Ronald M.
2011-01-01
The Binding Energy Distribution Analysis Method (BEDAM) is employed to compute the standard binding free energies of a series of ligands to a FK506 binding protein (FKBP12) with implicit solvation. Binding free energy estimates are in reasonably good agreement with experimental affinities. The conformations of the complexes identified by the simulations are in good agreement with crystallographic data, which was not used to restrain ligand orientations. The BEDAM method is based on λ -hopping Hamiltonian parallel Replica Exchange (HREM) molecular dynamics conformational sampling, the OPLS-AA/AGBNP2 effective potential, and multi-state free energy estimators (MBAR). Achieving converged and accurate results depends on all of these elements of the calculation. Convergence of the binding free energy is tied to the level of convergence of binding energy distributions at critical intermediate states where bound and unbound states are at equilibrium, and where the rate of binding/unbinding conformational transitions is maximal. This finding mirrors similar observations in the context of order/disorder transitions as for example in protein folding. Insights concerning the physical mechanism of ligand binding and unbinding are obtained. Convergence for the largest FK506 ligand is achieved only after imposing strict conformational restraints, which however require accurate prior structural knowledge of the structure of the complex. The analytical AGBNP2 model is found to underestimate the magnitude of the hydrophobic driving force towards binding in these systems characterized by loosely packed protein-ligand binding interfaces. Rescoring of the binding energies using a numerical surface area model corrects this deficiency. This study illustrates the complex interplay between energy models, exploration of conformational space, and free energy estimators needed to obtain robust estimates from binding free energy calculations. PMID:22368530
Harris, Robert C; Deng, Nanjie; Levy, Ronald M; Ishizuka, Ryosuke; Matubayasi, Nobuyuki
2017-06-05
Many biomolecules undergo conformational changes associated with allostery or ligand binding. Observing these changes in computer simulations is difficult if their timescales are long. These calculations can be accelerated by observing the transition on an auxiliary free energy surface with a simpler Hamiltonian and connecting this free energy surface to the target free energy surface with free energy calculations. Here, we show that the free energy legs of the cycle can be replaced with energy representation (ER) density functional approximations. We compute: (1) The conformational free energy changes for alanine dipeptide transitioning from the right-handed free energy basin to the left-handed basin and (2) the free energy difference between the open and closed conformations of β-cyclodextrin, a "host" molecule that serves as a model for molecular recognition in host-guest binding. β-cyclodextrin contains 147 atoms compared to 22 atoms for alanine dipeptide, making β-cyclodextrin a large molecule for which to compute solvation free energies by free energy perturbation or integration methods and the largest system for which the ER method has been compared to exact free energy methods. The ER method replaced the 28 simulations to compute each coupling free energy with two endpoint simulations, reducing the computational time for the alanine dipeptide calculation by about 70% and for the β-cyclodextrin by > 95%. The method works even when the distribution of conformations on the auxiliary free energy surface differs substantially from that on the target free energy surface, although some degree of overlap between the two surfaces is required. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Computer-Assisted Drug Formulation Design: Novel Approach in Drug Delivery.
Metwally, Abdelkader A; Hathout, Rania M
2015-08-03
We hypothesize that, by using several chemo/bio informatics tools and statistical computational methods, we can study and then predict the behavior of several drugs in model nanoparticulate lipid and polymeric systems. Accordingly, two different matrices comprising tripalmitin, a core component of solid lipid nanoparticles (SLN), and PLGA were first modeled using molecular dynamics simulation, and then the interaction of drugs with these systems was studied by means of computing the free energy of binding using the molecular docking technique. These binding energies were hence correlated with the loadings of these drugs in the nanoparticles obtained experimentally from the available literature. The obtained relations were verified experimentally in our laboratory using curcumin as a model drug. Artificial neural networks were then used to establish the effect of the drugs' molecular descriptors on the binding energies and hence on the drug loading. The results showed that the used soft computing methods can provide an accurate method for in silico prediction of drug loading in tripalmitin-based and PLGA nanoparticulate systems. These results have the prospective of being applied to other nano drug-carrier systems, and this integrated statistical and chemo/bio informatics approach offers a new toolbox to the formulation science by proposing what we present as computer-assisted drug formulation design (CADFD).
Bai, Qifeng; Shao, Yonghua; Pan, Dabo; Zhang, Yang; Liu, Huanxiang; Yao, Xiaojun
2014-01-01
We designed a program called MolGridCal that can be used to screen small molecule database in grid computing on basis of JPPF grid environment. Based on MolGridCal program, we proposed an integrated strategy for virtual screening and binding mode investigation by combining molecular docking, molecular dynamics (MD) simulations and free energy calculations. To test the effectiveness of MolGridCal, we screened potential ligands for β2 adrenergic receptor (β2AR) from a database containing 50,000 small molecules. MolGridCal can not only send tasks to the grid server automatically, but also can distribute tasks using the screensaver function. As for the results of virtual screening, the known agonist BI-167107 of β2AR is ranked among the top 2% of the screened candidates, indicating MolGridCal program can give reasonable results. To further study the binding mode and refine the results of MolGridCal, more accurate docking and scoring methods are used to estimate the binding affinity for the top three molecules (agonist BI-167107, neutral antagonist alprenolol and inverse agonist ICI 118,551). The results indicate agonist BI-167107 has the best binding affinity. MD simulation and free energy calculation are employed to investigate the dynamic interaction mechanism between the ligands and β2AR. The results show that the agonist BI-167107 also has the lowest binding free energy. This study can provide a new way to perform virtual screening effectively through integrating molecular docking based on grid computing, MD simulations and free energy calculations. The source codes of MolGridCal are freely available at http://molgridcal.codeplex.com. PMID:25229694
Cournia, Zoe; Allen, Bryce; Sherman, Woody
2017-12-26
Accurate in silico prediction of protein-ligand binding affinities has been a primary objective of structure-based drug design for decades due to the putative value it would bring to the drug discovery process. However, computational methods have historically failed to deliver value in real-world drug discovery applications due to a variety of scientific, technical, and practical challenges. Recently, a family of approaches commonly referred to as relative binding free energy (RBFE) calculations, which rely on physics-based molecular simulations and statistical mechanics, have shown promise in reliably generating accurate predictions in the context of drug discovery projects. This advance arises from accumulating developments in the underlying scientific methods (decades of research on force fields and sampling algorithms) coupled with vast increases in computational resources (graphics processing units and cloud infrastructures). Mounting evidence from retrospective validation studies, blind challenge predictions, and prospective applications suggests that RBFE simulations can now predict the affinity differences for congeneric ligands with sufficient accuracy and throughput to deliver considerable value in hit-to-lead and lead optimization efforts. Here, we present an overview of current RBFE implementations, highlighting recent advances and remaining challenges, along with examples that emphasize practical considerations for obtaining reliable RBFE results. We focus specifically on relative binding free energies because the calculations are less computationally intensive than absolute binding free energy (ABFE) calculations and map directly onto the hit-to-lead and lead optimization processes, where the prediction of relative binding energies between a reference molecule and new ideas (virtual molecules) can be used to prioritize molecules for synthesis. We describe the critical aspects of running RBFE calculations, from both theoretical and applied perspectives, using a combination of retrospective literature examples and prospective studies from drug discovery projects. This work is intended to provide a contemporary overview of the scientific, technical, and practical issues associated with running relative binding free energy simulations, with a focus on real-world drug discovery applications. We offer guidelines for improving the accuracy of RBFE simulations, especially for challenging cases, and emphasize unresolved issues that could be improved by further research in the field.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Parkes, Marie V.; Sava Gallis, Dorina F.; Greathouse, Jeffery A.
Computational screening of metal-organic framework (MOF) materials for selective oxygen adsorption from air could lead to new sorbents for the oxyfuel combustion process feedstock streams. A comprehensive study on the effect of MOF metal chemistry on gas binding energies in two common but structurally disparate metal-organic frameworks has been undertaken. Dispersion-corrected density functional theory methods were used to calculate the oxygen and nitrogen binding energies with each of fourteen metals, respectively, substituted into two MOF series, M 2(dobdc) and M 3(btc) 2. The accuracy of DFT methods was validated by comparing trends in binding energy with experimental gas sorption measurements.more » A periodic trend in oxygen binding energies was found, with greater oxygen binding energies for early transition-metal-substituted MOFs compared to late transition metal MOFs; this was independent of MOF structural type. The larger binding energies were associated with oxygen binding in a side-on configuration to the metal, with concomitant lengthening of the O-O bond. In contrast, nitrogen binding energies were similar across the transition metal series, regardless of both MOF structural type and metal identity. Altogether, these findings suggest that early transition metal MOFs are best suited to separating oxygen from nitrogen, and that the MOF structural type is less important than the metal identity.« less
Calculation of protein-ligand binding affinities.
Gilson, Michael K; Zhou, Huan-Xiang
2007-01-01
Accurate methods of computing the affinity of a small molecule with a protein are needed to speed the discovery of new medications and biological probes. This paper reviews physics-based models of binding, beginning with a summary of the changes in potential energy, solvation energy, and configurational entropy that influence affinity, and a theoretical overview to frame the discussion of specific computational approaches. Important advances are reported in modeling protein-ligand energetics, such as the incorporation of electronic polarization and the use of quantum mechanical methods. Recent calculations suggest that changes in configurational entropy strongly oppose binding and must be included if accurate affinities are to be obtained. The linear interaction energy (LIE) and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) methods are analyzed, as are free energy pathway methods, which show promise and may be ready for more extensive testing. Ultimately, major improvements in modeling accuracy will likely require advances on multiple fronts, as well as continued validation against experiment.
A COMPUTER MODELING STUDY OF BINDING PROPERTIES OF CHIRAL NUCLEOPEPTIDE FOR BIOMEDICAL APPLICATIONS.
Pirtskhalava, M; Egoyan, A; Mirtskhulava, M; Roviello, G
2017-12-01
Nucleopeptides often show interesting properties of molecular binding that render them good candidates for development of innovative drugs for anticancer and antiviral therapies. In this work we present results of computer modeling of interactions between the molecules of hexathymine nucleopeptide (T6) and poly rA RNA (A18). The results of geometry optimization calculated using Hyperchem software and our own computer program for molecular docking show that molecules establish stable complexes due to the complementary-nucleobase interaction and the electrostatic interaction between the negative phosphate group of poly rA and the positively-charged residues present in the cationic nucleopeptide structure. Computer modeling makes it possible to find the optimal binding configuration of the molecules of a nucleopeptide and poly rA RNA and to estimate the binding energy between the molecules.
NASA Astrophysics Data System (ADS)
Gaudio, Anderson Coser; Takahata, Yuji; Richards, William Graham
1998-01-01
The probable binding mode of the herpes simplex virus thymidine kinase (HSV1 TK) N2-[substituted]-phenylguanine inhibitors is proposed. A computational experiment was designed to check some qualitative binding parameters and to calculate the interaction binding energies of alternative binding modes of N2-phenylguanines. The known binding modes of the HSV1 TK natural substrate deoxythymidine and one of its competitive inhibitors ganciclovir were used as templates. Both the qualitative and quantitative parts of the computational experiment indicated that the N2-phenylguanine derivatives bind to the HSV1 TK active site in the deoxythymidine-like binding mode. An experimental observation that N2-phenylguanosine derivatives are not phosphorylated during the interaction with the HSV1 TK gives support to the proposed binding mode.
FAST TRACK COMMUNICATION: Finite-temperature magnetism in bcc Fe under compression
NASA Astrophysics Data System (ADS)
Sha, Xianwei; Cohen, R. E.
2010-09-01
We investigate the contributions of finite-temperature magnetic fluctuations to the thermodynamic properties of bcc Fe as functions of pressure. First, we apply a tight-binding total-energy model parameterized to first-principles linearized augmented plane-wave computations to examine various ferromagnetic, anti-ferromagnetic, and noncollinear spin spiral states at zero temperature. The tight-binding data are fit to a generalized Heisenberg Hamiltonian to describe the magnetic energy functional based on local moments. We then use Monte Carlo simulations to compute the magnetic susceptibility, the Curie temperature, heat capacity, and magnetic free energy. Including the finite-temperature magnetism improves the agreement with experiment for the calculated thermal expansion coefficients.
NASA Technical Reports Server (NTRS)
Bauschlicher, Charles W., Jr.; Ricca, Alessandra; Maitre, Philippe; Langhoff, Stephen R. (Technical Monitor)
1995-01-01
The successive binding energies of CO and H2O to Fe(sup +), CO to Fe(sup -), and H2 to Co(sup +) and V(sup +) are presented. Overall the computed results are in good agreement with experiment. The trends in binding energies are analyzed in terms of metal to ligand donation, ligand to metal donation, ligand-ligand repulsion, and changes in the metal atom, such as hybridization, promotion, and spin multiplicity. The geometry and vibrational frequencies are also shown to be directly affected by these effects.
Energetics of Glutamate Binding to an Ionotropic Glutamate Receptor.
Yu, Alvin; Lau, Albert Y
2017-11-22
Ionotropic glutamate receptors (iGluRs) are ligand-gated ion channels that are responsible for the majority of excitatory transmission at the synaptic cleft. Mechanically speaking, agonist binding to the ligand binding domain (LBD) activates the receptor by triggering a conformational change that is transmitted to the transmembrane region, opening the ion channel pore. We use fully atomistic molecular dynamics simulations to investigate the binding process in the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor, an iGluR subtype. The string method with swarms of trajectories was applied to calculate the possible pathways glutamate traverses during ligand binding. Residues peripheral to the binding cleft are found to metastably bind the ligand prior to ligand entry into the binding pocket. Umbrella sampling simulations were performed to compute the free energy barriers along the binding pathways. The calculated free energy profiles demonstrate that metastable interactions contribute substantially to the energetics of ligand binding and form local minima in the overall free energy landscape. Protein-ligand interactions at sites outside of the orthosteric agonist-binding site may serve to lower the transition barriers of the binding process.
Computational membrane biophysics: From ion channel interactions with drugs to cellular function.
Miranda, Williams E; Ngo, Van A; Perissinotti, Laura L; Noskov, Sergei Yu
2017-11-01
The rapid development of experimental and computational techniques has changed fundamentally our understanding of cellular-membrane transport. The advent of powerful computers and refined force-fields for proteins, ions, and lipids has expanded the applicability of Molecular Dynamics (MD) simulations. A myriad of cellular responses is modulated through the binding of endogenous and exogenous ligands (e.g. neurotransmitters and drugs, respectively) to ion channels. Deciphering the thermodynamics and kinetics of the ligand binding processes to these membrane proteins is at the heart of modern drug development. The ever-increasing computational power has already provided insightful data on the thermodynamics and kinetics of drug-target interactions, free energies of solvation, and partitioning into lipid bilayers for drugs. This review aims to provide a brief summary about modeling approaches to map out crucial binding pathways with intermediate conformations and free-energy surfaces for drug-ion channel binding mechanisms that are responsible for multiple effects on cellular functions. We will discuss post-processing analysis of simulation-generated data, which are then transformed to kinetic models to better understand the molecular underpinning of the experimental observables under the influence of drugs or mutations in ion channels. This review highlights crucial mathematical frameworks and perspectives on bridging different well-established computational techniques to connect the dynamics and timescales from all-atom MD and free energy simulations of ion channels to the physiology of action potentials in cellular models. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman. Copyright © 2017 Elsevier B.V. All rights reserved.
Beyond the benzene dimer: an investigation of the additivity of pi-pi interactions.
Tauer, Tony P; Sherrill, C David
2005-11-24
The benzene dimer is the simplest prototype of pi-pi interactions and has been used to understand the fundamental physics of these interactions as they are observed in more complex systems. In biological systems, however, aromatic rings are rarely found in isolated pairs; thus, it is important to understand whether aromatic pairs remain a good model of pi-pi interactions in clusters. In this study, ab initio methods are used to compute the binding energies of several benzene trimers and tetramers, most of them in 1D stacked configurations. The two-body terms change only slightly relative to the dimer, and except for the cyclic trimer, the three- and four-body terms are negligible. This indicates that aromatic clusters do not feature any large nonadditive effects in their binding energies, and polarization effects in benzene clusters do not greatly change the binding that would be anticipated from unperturbed benzene-benzene interactions, at least for the 1D stacked systems considered. Three-body effects are larger for the cyclic trimer, but for all systems considered, the computed binding energies are within 10% of what would be estimated from benzene dimer energies at the same geometries.
Hydrogen incorporation into BN fullerene-like nanostructures: A first-principles study
NASA Astrophysics Data System (ADS)
Ganji, M. D.; Abbaszadeh, B.; Ahaz, B.
2011-10-01
We performed density functional theory calculations to investigate the possibility of formation of endohedrally H@(BN) n-fullerene ( n: 24, 36, 60) and H@C 60 complexes for potential applications in solid-state quantum-computers. Spin-polarized approach within the generalized gradient approximation with the Perdew-Burke-Ernzerhof functional was used for the total energies and structural relaxation calculations. The calculated binding energies show that H atom being incorporated into B 60N 60 nanocage can form most stable complexes while the B 24N 24 and C 60 nanocages might form unstable complex with positive binding energy. We have also examined the penetration of an H atom into the respective nanocages and the calculated barrier energies indicate that the H atom prefers to penetrate into the B 24N 24 and B 60N 60 nanocages with barrier energy of about 0.47 eV (10.84 kcal/mol). Furthermore the binding characteristic is rationalized by analyzing the electronic structures. Our findings reveal that the B 60N 60 nanocage has fascinating potential application in future solid-state quantum-computers.
Semi-empirical quantum evaluation of peptide - MHC class II binding
NASA Astrophysics Data System (ADS)
González, Ronald; Suárez, Carlos F.; Bohórquez, Hugo J.; Patarroyo, Manuel A.; Patarroyo, Manuel E.
2017-01-01
Peptide presentation by the major histocompatibility complex (MHC) is a key process for triggering a specific immune response. Studying peptide-MHC (pMHC) binding from a structural-based approach has potential for reducing the costs of investigation into vaccine development. This study involved using two semi-empirical quantum chemistry methods (PM7 and FMO-DFTB) for computing the binding energies of peptides bonded to HLA-DR1 and HLA-DR2. We found that key stabilising water molecules involved in the peptide binding mechanism were required for finding high correlation with IC50 experimental values. Our proposal is computationally non-intensive, and is a reliable alternative for studying pMHC binding interactions.
Olsson, Martin A; Söderhjelm, Pär; Ryde, Ulf
2016-06-30
In this article, the convergence of quantum mechanical (QM) free-energy simulations based on molecular dynamics simulations at the molecular mechanics (MM) level has been investigated. We have estimated relative free energies for the binding of nine cyclic carboxylate ligands to the octa-acid deep-cavity host, including the host, the ligand, and all water molecules within 4.5 Å of the ligand in the QM calculations (158-224 atoms). We use single-step exponential averaging (ssEA) and the non-Boltzmann Bennett acceptance ratio (NBB) methods to estimate QM/MM free energy with the semi-empirical PM6-DH2X method, both based on interaction energies. We show that ssEA with cumulant expansion gives a better convergence and uses half as many QM calculations as NBB, although the two methods give consistent results. With 720,000 QM calculations per transformation, QM/MM free-energy estimates with a precision of 1 kJ/mol can be obtained for all eight relative energies with ssEA, showing that this approach can be used to calculate converged QM/MM binding free energies for realistic systems and large QM partitions. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.
Binding free energy prediction in strongly hydrophobic biomolecular systems.
Charlier, Landry; Nespoulous, Claude; Fiorucci, Sébastien; Antonczak, Serge; Golebiowski, Jérome
2007-11-21
We present a comparison of various computational approaches aiming at predicting the binding free energy in ligand-protein systems where the ligand is located within a highly hydrophobic cavity. The relative binding free energy between similar ligands is obtained by means of the thermodynamic integration (TI) method and compared to experimental data obtained through isothermal titration calorimetry measurements. The absolute free energy of binding prediction was obtained on a similar system (a pyrazine derivative bound to a lipocalin) by TI, potential of mean force (PMF) and also by means of the MMPBSA protocols. Although the TI protocol performs poorly either with an explicit or an implicit solvation scheme, the PMF calculation using an implicit solvation scheme leads to encouraging results, with a prediction of the binding affinity being 2 kcal mol(-1) lower than the experimental value. The use of an implicit solvation scheme appears to be well suited for the study of such hydrophobic systems, due to the lack of water molecules within the binding site.
Free energy component analysis for drug design: a case study of HIV-1 protease-inhibitor binding.
Kalra, P; Reddy, T V; Jayaram, B
2001-12-06
A theoretically rigorous and computationally tractable methodology for the prediction of the free energies of binding of protein-ligand complexes is presented. The method formulated involves developing molecular dynamics trajectories of the enzyme, the inhibitor, and the complex, followed by a free energy component analysis that conveys information on the physicochemical forces driving the protein-ligand complex formation and enables an elucidation of drug design principles for a given receptor from a thermodynamic perspective. The complexes of HIV-1 protease with two peptidomimetic inhibitors were taken as illustrative cases. Four-nanosecond-level all-atom molecular dynamics simulations using explicit solvent without any restraints were carried out on the protease-inhibitor complexes and the free proteases, and the trajectories were analyzed via a thermodynamic cycle to calculate the binding free energies. The computed free energies were seen to be in good accord with the reported data. It was noted that the net van der Waals and hydrophobic contributions were favorable to binding while the net electrostatics, entropies, and adaptation expense were unfavorable in these protease-inhibitor complexes. The hydrogen bond between the CH2OH group of the inhibitor at the scissile position and the catalytic aspartate was found to be favorable to binding. Various implicit solvent models were also considered and their shortcomings discussed. In addition, some plausible modifications to the inhibitor residues were attempted, which led to better binding affinities. The generality of the method and the transferability of the protocol with essentially no changes to any other protein-ligand system are emphasized.
Aldeghi, Matteo; Bodkin, Michael J; Knapp, Stefan; Biggin, Philip C
2017-09-25
Binding free energy calculations that make use of alchemical pathways are becoming increasingly feasible thanks to advances in hardware and algorithms. Although relative binding free energy (RBFE) calculations are starting to find widespread use, absolute binding free energy (ABFE) calculations are still being explored mainly in academic settings due to the high computational requirements and still uncertain predictive value. However, in some drug design scenarios, RBFE calculations are not applicable and ABFE calculations could provide an alternative. Computationally cheaper end-point calculations in implicit solvent, such as molecular mechanics Poisson-Boltzmann surface area (MMPBSA) calculations, could too be used if one is primarily interested in a relative ranking of affinities. Here, we compare MMPBSA calculations to previously performed absolute alchemical free energy calculations in their ability to correlate with experimental binding free energies for three sets of bromodomain-inhibitor pairs. Different MMPBSA approaches have been considered, including a standard single-trajectory protocol, a protocol that includes a binding entropy estimate, and protocols that take into account the ligand hydration shell. Despite the improvements observed with the latter two MMPBSA approaches, ABFE calculations were found to be overall superior in obtaining correlation with experimental affinities for the test cases considered. A difference in weighted average Pearson ([Formula: see text]) and Spearman ([Formula: see text]) correlations of 0.25 and 0.31 was observed when using a standard single-trajectory MMPBSA setup ([Formula: see text] = 0.64 and [Formula: see text] = 0.66 for ABFE; [Formula: see text] = 0.39 and [Formula: see text] = 0.35 for MMPBSA). The best performing MMPBSA protocols returned weighted average Pearson and Spearman correlations that were about 0.1 inferior to ABFE calculations: [Formula: see text] = 0.55 and [Formula: see text] = 0.56 when including an entropy estimate, and [Formula: see text] = 0.53 and [Formula: see text] = 0.55 when including explicit water molecules. Overall, the study suggests that ABFE calculations are indeed the more accurate approach, yet there is also value in MMPBSA calculations considering the lower compute requirements, and if agreement to experimental affinities in absolute terms is not of interest. Moreover, for the specific protein-ligand systems considered in this study, we find that including an explicit ligand hydration shell or a binding entropy estimate in the MMPBSA calculations resulted in significant performance improvements at a negligible computational cost.
Huang, Xiaoqiang; Han, Kehang; Zhu, Yushan
2013-01-01
A systematic optimization model for binding sequence selection in computational enzyme design was developed based on the transition state theory of enzyme catalysis and graph-theoretical modeling. The saddle point on the free energy surface of the reaction system was represented by catalytic geometrical constraints, and the binding energy between the active site and transition state was minimized to reduce the activation energy barrier. The resulting hyperscale combinatorial optimization problem was tackled using a novel heuristic global optimization algorithm, which was inspired and tested by the protein core sequence selection problem. The sequence recapitulation tests on native active sites for two enzyme catalyzed hydrolytic reactions were applied to evaluate the predictive power of the design methodology. The results of the calculation show that most of the native binding sites can be successfully identified if the catalytic geometrical constraints and the structural motifs of the substrate are taken into account. Reliably predicting active site sequences may have significant implications for the creation of novel enzymes that are capable of catalyzing targeted chemical reactions. PMID:23649589
2017-01-01
Virtually all biological processes depend on the interaction between proteins at some point. The correct prediction of biomolecular binding free-energies has many interesting applications in both basic and applied pharmaceutical research. While recent advances in the field of molecular dynamics (MD) simulations have proven the feasibility of the calculation of protein–protein binding free energies, the large conformational freedom of proteins and complex free energy landscapes of binding processes make such calculations a difficult task. Moreover, convergence and reversibility of resulting free-energy values remain poorly described. In this work, an easy-to-use, yet robust approach for the calculation of standard-state protein–protein binding free energies using perturbed distance restraints is described. In the binding process the conformations of the proteins were restrained, as suggested earlier. Two approaches to avoid end-state problems upon release of the conformational restraints were compared. The method was evaluated by practical application to a small model complex of ubiquitin and the very flexible ubiquitin-binding domain of human DNA polymerase ι (UBM2). All computed free energy differences were closely monitored for convergence, and the calculated binding free energies had a mean unsigned deviation of only 1.4 or 2.5 kJ·mol–1 from experimental values. Statistical error estimates were in the order of thermal noise. We conclude that the presented method has promising potential for broad applicability to quantitatively describe protein–protein and various other kinds of complex formation. PMID:28898077
Spichty, Martin; Taly, Antoine; Hagn, Franz; Kessler, Horst; Barluenga, Sofia; Winssinger, Nicolas; Karplus, Martin
2009-01-01
We determine the binding mode of a macrocyclic radicicol-like oxime to yeast HSP90 by combining computer simulations and experimental measurements. We sample the macrocyclic scaffold of the unbound ligand by parallel tempering simulations and dock the most populated conformations to yeast HSP90. Docking poses are then evaluated by the use of binding free energy estimations with the linear interaction energy method. Comparison of QM/MM-calculated NMR chemical shifts with experimental shift data for a selective subset of back-bone 15N provides an additional evaluation criteria. As a last test we check the binding modes against available structure-activity-relationships. We find that the most likely binding mode of the oxime to yeast HSP90 is very similar to the known structure of the radicicol-HSP90 complex. PMID:19482409
NASA Technical Reports Server (NTRS)
Huang, K.-N.; Aoyagi, M.; Mark, H.; Chen, M. H.; Crasemann, B.
1976-01-01
Electron binding energies in neutral atoms have been calculated relativistically, with the requirement of complete relaxation. Hartree-Fock-Slater wave functions served as zeroth-order eigenfunctions to compute the expectation of the total Hamiltonian. A first-order correction to the local approximation was thus included. Quantum-electrodynamic corrections were made. For all elements with atomic numbers ranging from 2 to 106, the following quantities are listed: total energies, electron kinetic energies, electron-nucleus potential energies, electron-electron potential energies consisting of electrostatic and Breit interaction (magnetic and retardation) terms, and vacuum polarization energies. Binding energies including relaxation are listed for all electrons in all atoms over the indicated range of atomic numbers. A self-energy correction is included for the 1s, 2s, and 2p(1/2) levels. Results for selected atoms are compared with energies calculated by other methods and with experimental values.
Theoretical study of the BeLi, BeNa, MgLi, MgNa, and AlBe molecules and their negative ions
NASA Technical Reports Server (NTRS)
Bauschlicher, Charles W., Jr.; Langhoff, Stephen R.; Partridge, Harry
1992-01-01
The alkaline earth-alkali diatomics are found to have weak bonds, because the diffuse alkali valence s orbitals cannot form a bond of sufficient strength to pay the promotion energy of the alkaline-earth atoms. This leads to van der Waals bonding in the neutrals as well as the negative ions. In fact, the negative ions have larger binding energies than the neutrals as a result of the much larger polarizability of the negative ion. The binding energy of AlBe is significantly larger than the Be-alkali molecules, due to a covalent contribution to the bonding. The binding energy in AlBe(-) is considerably larger than AlBe; the binding energy of the X 3Sigma(-) state of AlBe(-) is computed to be 1.36 eV, as compared with 0.57 eV for the X 2Pi state of AlBe.
Role of Desolvation in Thermodynamics and Kinetics of Ligand Binding to a Kinase
2015-01-01
Computer simulations are used to determine the free energy landscape for the binding of the anticancer drug Dasatinib to its src kinase receptor and show that before settling into a free energy basin the ligand must surmount a free energy barrier. An analysis based on using both the ligand-pocket separation and the pocket-water occupancy as reaction coordinates shows that the free energy barrier is a result of the free energy cost for almost complete desolvation of the binding pocket. The simulations further show that the barrier is not a result of the reorganization free energy of the binding pocket. Although a continuum solvent model gives the location of free energy minima, it is not able to reproduce the intermediate free energy barrier. Finally, it is shown that a kinetic model for the on rate constant in which the ligand diffuses up to a doorway state and then surmounts the desolvation free energy barrier is consistent with published microsecond time-scale simulations of the ligand binding kinetics for this system [Shaw, D. E. et al. J. Am. Chem. Soc.2011, 133, 9181−918321545110]. PMID:25516727
Parkes, Marie V.; Sava Gallis, Dorina F.; Greathouse, Jeffery A.; ...
2015-03-02
Computational screening of metal-organic framework (MOF) materials for selective oxygen adsorption from air could lead to new sorbents for the oxyfuel combustion process feedstock streams. A comprehensive study on the effect of MOF metal chemistry on gas binding energies in two common but structurally disparate metal-organic frameworks has been undertaken. Dispersion-corrected density functional theory methods were used to calculate the oxygen and nitrogen binding energies with each of fourteen metals, respectively, substituted into two MOF series, M 2(dobdc) and M 3(btc) 2. The accuracy of DFT methods was validated by comparing trends in binding energy with experimental gas sorption measurements.more » A periodic trend in oxygen binding energies was found, with greater oxygen binding energies for early transition-metal-substituted MOFs compared to late transition metal MOFs; this was independent of MOF structural type. The larger binding energies were associated with oxygen binding in a side-on configuration to the metal, with concomitant lengthening of the O-O bond. In contrast, nitrogen binding energies were similar across the transition metal series, regardless of both MOF structural type and metal identity. Altogether, these findings suggest that early transition metal MOFs are best suited to separating oxygen from nitrogen, and that the MOF structural type is less important than the metal identity.« less
Accurate Evaluation Method of Molecular Binding Affinity from Fluctuation Frequency
NASA Astrophysics Data System (ADS)
Hoshino, Tyuji; Iwamoto, Koji; Ode, Hirotaka; Ohdomari, Iwao
2008-05-01
Exact estimation of the molecular binding affinity is significantly important for drug discovery. The energy calculation is a direct method to compute the strength of the interaction between two molecules. This energetic approach is, however, not accurate enough to evaluate a slight difference in binding affinity when distinguishing a prospective substance from dozens of candidates for medicine. Hence more accurate estimation of drug efficacy in a computer is currently demanded. Previously we proposed a concept of estimating molecular binding affinity, focusing on the fluctuation at an interface between two molecules. The aim of this paper is to demonstrate the compatibility between the proposed computational technique and experimental measurements, through several examples for computer simulations of an association of human immunodeficiency virus type-1 (HIV-1) protease and its inhibitor (an example for a drug-enzyme binding), a complexation of an antigen and its antibody (an example for a protein-protein binding), and a combination of estrogen receptor and its ligand chemicals (an example for a ligand-receptor binding). The proposed affinity estimation has proven to be a promising technique in the advanced stage of the discovery and the design of drugs.
Energy Fluctuations Shape Free Energy of Nonspecific Biomolecular Interactions
NASA Astrophysics Data System (ADS)
Elkin, Michael; Andre, Ingemar; Lukatsky, David B.
2012-01-01
Understanding design principles of biomolecular recognition is a key question of molecular biology. Yet the enormous complexity and diversity of biological molecules hamper the efforts to gain a predictive ability for the free energy of protein-protein, protein-DNA, and protein-RNA binding. Here, using a variant of the Derrida model, we predict that for a large class of biomolecular interactions, it is possible to accurately estimate the relative free energy of binding based on the fluctuation properties of their energy spectra, even if a finite number of the energy levels is known. We show that the free energy of the system possessing a wider binding energy spectrum is almost surely lower compared with the system possessing a narrower energy spectrum. Our predictions imply that low-affinity binding scores, usually wasted in protein-protein and protein-DNA docking algorithms, can be efficiently utilized to compute the free energy. Using the results of Rosetta docking simulations of protein-protein interactions from Andre et al. (Proc. Natl. Acad. Sci. USA 105:16148, 2008), we demonstrate the power of our predictions.
Predicting bioactive conformations and binding modes of macrocycles
NASA Astrophysics Data System (ADS)
Anighoro, Andrew; de la Vega de León, Antonio; Bajorath, Jürgen
2016-10-01
Macrocyclic compounds experience increasing interest in drug discovery. It is often thought that these large and chemically complex molecules provide promising candidates to address difficult targets and interfere with protein-protein interactions. From a computational viewpoint, these molecules are difficult to treat. For example, flexible docking of macrocyclic compounds is hindered by the limited ability of current docking approaches to optimize conformations of extended ring systems for pose prediction. Herein, we report predictions of bioactive conformations of macrocycles using conformational search and binding modes using docking. Conformational ensembles generated using specialized search technique of about 70 % of the tested macrocycles contained accurate bioactive conformations. However, these conformations were difficult to identify on the basis of conformational energies. Moreover, docking calculations with limited ligand flexibility starting from individual low energy conformations rarely yielded highly accurate binding modes. In about 40 % of the test cases, binding modes were approximated with reasonable accuracy. However, when conformational ensembles were subjected to rigid body docking, an increase in meaningful binding mode predictions to more than 50 % of the test cases was observed. Electrostatic effects did not contribute to these predictions in a positive or negative manner. Rather, achieving shape complementarity at macrocycle-target interfaces was a decisive factor. In summary, a combined computational protocol using pre-computed conformational ensembles of macrocycles as a starting point for docking shows promise in modeling binding modes of macrocyclic compounds.
Pan, Yuliang; Wang, Zixiang; Zhan, Weihua; Deng, Lei
2018-05-01
Identifying RNA-binding residues, especially energetically favored hot spots, can provide valuable clues for understanding the mechanisms and functional importance of protein-RNA interactions. Yet, limited availability of experimentally recognized energy hot spots in protein-RNA crystal structures leads to the difficulties in developing empirical identification approaches. Computational prediction of RNA-binding hot spot residues is still in its infant stage. Here, we describe a computational method, PrabHot (Prediction of protein-RNA binding hot spots), that can effectively detect hot spot residues on protein-RNA binding interfaces using an ensemble of conceptually different machine learning classifiers. Residue interaction network features and new solvent exposure characteristics are combined together and selected for classification with the Boruta algorithm. In particular, two new reference datasets (benchmark and independent) have been generated containing 107 hot spots from 47 known protein-RNA complex structures. In 10-fold cross-validation on the training dataset, PrabHot achieves promising performances with an AUC score of 0.86 and a sensitivity of 0.78, which are significantly better than that of the pioneer RNA-binding hot spot prediction method HotSPRing. We also demonstrate the capability of our proposed method on the independent test dataset and gain a competitive advantage as a result. The PrabHot webserver is freely available at http://denglab.org/PrabHot/. leideng@csu.edu.cn. Supplementary data are available at Bioinformatics online.
First-principles study of the binding energy between nanostructures and its scaling with system size
NASA Astrophysics Data System (ADS)
Tao, Jianmin; Jiao, Yang; Mo, Yuxiang; Yang, Zeng-Hui; Zhu, Jian-Xin; Hyldgaard, Per; Perdew, John P.
2018-04-01
The equilibrium van der Waals binding energy is an important factor in the design of materials and devices. However, it presents great computational challenges for materials built up from nanostructures. Here we investigate the binding-energy scaling behavior from first-principles calculations. We show that the equilibrium binding energy per atom between identical nanostructures can scale up or down with nanostructure size, but can be parametrized for large N with an analytical formula (in meV/atom), Eb/N =a +b /N +c /N2+d /N3 , where N is the number of atoms in a nanostructure and a , b , c , and d are fitting parameters, depending on the properties of a nanostructure. The formula is consistent with a finite large-size limit of binding energy per atom. We find that there are two competing factors in the determination of the binding energy: Nonadditivities of van der Waals coefficients and center-to-center distance between nanostructures. To decode the detail, the nonadditivity of the static multipole polarizability is investigated from an accurate spherical-shell model. We find that the higher-order multipole polarizability displays ultrastrong intrinsic nonadditivity, no matter if the dipole polarizability is additive or not.
lee, Lee-Peng; Tidor, Bruce
2001-01-01
Theoretical and experimental studies have shown that the large desolvation penalty required for polar and charged groups frequently precludes their involvement in electrostatic interactions that contribute strongly to net stability in the folding or binding of proteins in aqueous solution near room temperature. We have previously developed a theoretical framework for computing optimized electrostatic interactions and illustrated use of the algorithm with simplified geometries. Given a receptor and model assumptions, the method computes the ligand-charge distribution that provides the most favorable balance of desolvation and interaction effects on binding. In this paper the method has been extended to treat complexes using actual molecular shapes. The barnase-barstar protein complex was investigated with barnase treated as a target receptor. The atomic point charges of barstar were varied to optimize the electrostatic binding free energy. Barnase and natural barstar form a tight complex (Kd ∼ 10−14 M) with many charged and polar groups near the interface that make this a particularly relevant system for investigating the role of electrostatic effects on binding. The results show that sets of barstar charges (resulting from optimization with different constraints) can be found that give rise to relatively large predicted improvements in electrostatic binding free energy. Principles for enhancing the effect of electrostatic interactions in molecular binding in aqueous environments are discussed in light of the optima. Our findings suggest that, in general, the enhancements in electrostatic binding free energy resulting from modification of polar and charged groups can be substantial. Moreover, a recently proposed definition of electrostatic complementarity is shown to be a useful tool for examining binding interfaces. Finally, calculational results suggest that wild-type barstar is closer to being affinity optimized than is barnase for their mutual binding, consistent with the known roles of these proteins. PMID:11266622
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rakhecha, Shalu, E-mail: shalurakhecha@yahoo.com; Vyas, P. R.; Gohel, V. B.
In the present communication, we have computed static and dynamic properties (binding energy-E, bulk modulus-B and second moment- ) as well as first order pressure induced phase transition (FCC-BCC) using local form of pseudopotential for Calcium and Strontium. The form of pseudopotential used for the computation is directly extracted from Generalized Pseudopotential Theory (GPT) which contains three parameters (r{sub c}, r{sub d} and β). We have suggested a simple method using which pseudopotential is determined by single parameter (β). Our computed results for binding energy and bulk modulii are in excellent agreement with experimental findings and are better than othermore » theoretical results. The present study confirms that s-d hybridization is accounted properly in the presently used pseudopotential and can be extended for the study of lattice mechanical properties of these metals.« less
NASA Astrophysics Data System (ADS)
Hao, Ge-Fei; Tan, Ying; Yu, Ning-Xi; Yang, Guang-Fu
2011-03-01
Protoporphyrinogen oxidase (PPO, EC 1.3.3.4), which has been identified as a significant target for a great family of herbicides with diverse chemical structures, is the last common enzyme responsible for the seventh step in the biosynthetic pathway to heme and chlorophyll. Among the existing PPO inhibitors, diphenyl-ether is the first commercial family of PPO inhibitors and used as agriculture herbicides for decades. Most importantly, diphenyl-ether inhibitors have been found recently to possess the potential in Photodynamic therapy (PDT) to treat cancer. Herein, molecular dynamics simulations, approximate free energy calculations and hydrogen bond energy calculations were integrated together to uncover the structure-activity relationships of this type of PPO inhibitors. The calculated binding free energies are correlated very well with the values derived from the experimental k i data. According to the established computational models and the results of approximate free energy calculation, the substitution effects at different position were rationalized from the view of binding free energy. Some outlier ( e.g. LS) in traditional QSAR study can also be explained reasonably. In addition, the hydrogen bond energy calculation and interaction analysis results indicated that the carbonyl oxygen on position-9 and the NO2 group at position-8 are both vital for the electrostatic interaction with Arg98, which made a great contribution to the binding free energy. These insights from computational simulations are not only helpful for understanding the molecular mechanism of PPO-inhibitor interactions, but also beneficial to the future rational design of novel promising PPO inhibitors.
Lu, Haiting; Huang, Xiaoqin; AbdulHameed, Mohamed Diwan M; Zhan, Chang-Guo
2014-04-01
Molecular dynamics (MD) simulations and hybrid quantum mechanical/molecular mechanical (QM/MM) calculations have been performed to explore the dynamic behaviors of cytochrome P450 2A6 (CYP2A6) binding with nicotine analogs (that are typical inhibitors) and to calculate their binding free energies in combination with Poisson-Boltzmann surface area (PBSA) calculations. The combined MD simulations and QM/MM-PBSA calculations reveal that the most important structural parameters affecting the CYP2A6-inhibitor binding affinity are two crucial internuclear distances, that is, the distance between the heme iron atom of CYP2A6 and the coordinating atom of the inhibitor, and the hydrogen-bonding distance between the N297 side chain of CYP2A6 and the pyridine nitrogen of the inhibitor. The combined MD simulations and QM/MM-PBSA calculations have led to dynamic CYP2A6-inhibitor binding structures that are consistent with the observed dynamic behaviors and structural features of CYP2A6-inhibitor binding, and led to the binding free energies that are in good agreement with the experimentally-derived binding free energies. The agreement between the calculated binding free energies and the experimentally-derived binding free energies suggests that the combined MD and QM/MM-PBSA approach may be used as a valuable tool to accurately predict the CYP2A6-inhibitor binding affinities in future computational design of new, potent and selective CYP2A6 inhibitors. Copyright © 2014 Elsevier Ltd. All rights reserved.
Trions in bulk and monolayer materials: Faddeev equations and hyperspherical harmonics.
Filikhin, I; Kezerashvili, R Ya; Tsiklauri, Sh M; Vlahovic, B
2018-03-23
The negatively T - and positively T + charged trions in bulk and monolayer semiconductors are studied in the effective mass approximation within the framework of a potential model. The binding energies of trions in various semiconductors are calculated by employing the Faddeev equation with the Coulomb potential in 3D configuration space. Results of calculations of the binding energies for T - are consistent with previous computational studies, while the T + is unbound for all considered cases. The binding energies of trions in monolayer semiconductors are calculated using the method of hyperspherical harmonics by employing the Keldysh potential. It is shown that 2D T - and T + trions are bound and the binding energy of the positive trion is always greater than for the negative trion due to the heavier effective mass of holes. Our calculations demonstrate that screening effects play an important role in the formation of bound states of trions in 2D semiconductors.
Trions in bulk and monolayer materials: Faddeev equations and hyperspherical harmonics
NASA Astrophysics Data System (ADS)
Filikhin, I.; Kezerashvili, R. Ya; Tsiklauri, Sh M.; Vlahovic, B.
2018-03-01
The negatively T - and positively T + charged trions in bulk and monolayer semiconductors are studied in the effective mass approximation within the framework of a potential model. The binding energies of trions in various semiconductors are calculated by employing the Faddeev equation with the Coulomb potential in 3D configuration space. Results of calculations of the binding energies for T - are consistent with previous computational studies, while the T + is unbound for all considered cases. The binding energies of trions in monolayer semiconductors are calculated using the method of hyperspherical harmonics by employing the Keldysh potential. It is shown that 2D T - and T + trions are bound and the binding energy of the positive trion is always greater than for the negative trion due to the heavier effective mass of holes. Our calculations demonstrate that screening effects play an important role in the formation of bound states of trions in 2D semiconductors.
Gallicchio, Emilio
2012-01-01
The results of computer simulations of the binding of etravirine (TMC125) and rilpivirine (TMC278) to HIV reverse transcriptase are reported. It is confirmed that consistent binding free energy estimates are obtained with or without the application of torsional restraints when the free energies of imposing the restraints are taken into account. The restraints have a smaller influence on the thermodynamics and apparent kinetics of binding of TMC125 compared to the more flexible TMC278 inhibitor. The concept of the reorganization free energy of binding is useful to understand and categorize these effects. Contrary to expectations, the use of conformational restraints did not consistently enhance convergence of binding free energy estimates due to suppression of binding/unbinding pathways and due to the influence of rotational degrees of freedom not directly controlled by the restraints. Physical insights concerning the thermodynamic driving forces for binding and the role of “jiggling” and “wiggling” motion of the ligands are discussed. Based on these insights we conclude that an ideal inhibitor, if chemically realizable, would possess the electrostatic charge distribution of TMC125, so as to form strong interactions with the receptor, and the larger and more flexible substituents of TMC278, so as to minimize reorganization free energy penalties and the effects of resistance mutations, suitably modified, as in TMC125, so as to disfavor the formation of non-binding competent extended conformations when free in solution. PMID:22708073
Freedman, Holly; Winter, Philip; Tuszynski, Jack; Tyrrell, D Lorne; Houghton, Michael
2018-06-22
In the development of antiviral drugs that target viral RNA-dependent RNA polymerases, off-target toxicity caused by the inhibition of the human mitochondrial RNA polymerase (POLRMT) is a major liability. Therefore, it is essential that all new ribonucleoside analogue drugs be accurately screened for POLRMT inhibition. A computational tool that can accurately predict NTP binding to POLRMT could assist in evaluating any potential toxicity and in designing possible salvaging strategies. Using the available crystal structure of POLRMT bound to an RNA transcript, here we created a model of POLRMT with an NTP molecule bound in the active site. Furthermore, we implemented a computational screening procedure that determines the relative binding free energy of an NTP analogue to POLRMT by free energy perturbation (FEP), i.e. a simulation in which the natural NTP molecule is slowly transformed into the analogue and back. In each direction, the transformation was performed over 40 ns of simulation on our IBM Blue Gene Q supercomputer. This procedure was validated across a panel of drugs for which experimental dissociation constants were available, showing that NTP relative binding free energies could be predicted to within 0.97 kcal/mol of the experimental values on average. These results demonstrate for the first time that free-energy simulation can be a useful tool for predicting binding affinities of NTP analogues to a polymerase. We expect that our model, together with similar models of viral polymerases, will be very useful in the screening and future design of NTP inhibitors of viral polymerases that have no mitochondrial toxicity. © 2018 Freedman et al.
Three-body Coulomb bound states
NASA Technical Reports Server (NTRS)
Bhatia, A. K.; Drachman, Richard J.
1987-01-01
The binding energies of three-particle systems containing two electrons and one positive particle of mass M are reexamined in an attempt to understand the approximate proportionality of the 1Se ground-state binding energies of the reduced masses, as pointed out by Botero and Green (1986). The contribution to the energy of the mass-polarization term is evaluated. No fundamental principle is involved, since the mass polarization merely decreases somewhat as the mass of the positive particle is reduced below the proton mass. In the case of the excited 3Pe state, this reduction is not sufficient to allow binding when M approaches the electron mass. Some properties of the recently observed negative muonium ion (e/-/ mu/+/ e/-/) are also computed.
Ligand-protein docking using a quantum stochastic tunneling optimization method.
Mancera, Ricardo L; Källblad, Per; Todorov, Nikolay P
2004-04-30
A novel hybrid optimization method called quantum stochastic tunneling has been recently introduced. Here, we report its implementation within a new docking program called EasyDock and a validation with the CCDC/Astex data set of ligand-protein complexes using the PLP score to represent the ligand-protein potential energy surface and ScreenScore to score the ligand-protein binding energies. When taking the top energy-ranked ligand binding mode pose, we were able to predict the correct crystallographic ligand binding mode in up to 75% of the cases. By using this novel optimization method run times for typical docking simulations are significantly shortened. Copyright 2004 Wiley Periodicals, Inc. J Comput Chem 25: 858-864, 2004
Aidas, Kęstutis; Olsen, Jógvan Magnus H; Kongsted, Jacob; Ågren, Hans
2013-02-21
Attempting to unravel mechanisms in optical probing of proteins, we have performed pilot calculations of two cationic chromophores-acridine yellow and proflavin-located at different binding sites within human serum albumin, including the two primary drug binding sites as well as a heme binding site. The computational scheme adopted involves classical molecular dynamics simulations of the ligands bound to the protein and subsequent linear response polarizable embedding density functional theory calculations of the excitation energies. A polarizable embedding potential consisting of point charges fitted to reproduce the electrostatic potential and isotropic atomic polarizabilities computed individually for every residue of the protein was used in the linear response calculations. Comparing the calculated aqueous solution-to-protein shifts of maximum absorption energies to available experimental data, we concluded that the cationic proflavin chromophore is likely not to bind albumin at its drug binding site 1 nor at its heme binding site. Although agreement with experimental data could only be obtained in qualitative terms, our results clearly indicate that the difference in optical response of the two probes is due to deprotonation, and not, as earlier suggested, to different binding sites. The ramifications of this finding for design of molecular probes targeting albumin or other proteins is briefly discussed.
GMXPBSA 2.0: A GROMACS tool to perform MM/PBSA and computational alanine scanning
NASA Astrophysics Data System (ADS)
Paissoni, C.; Spiliotopoulos, D.; Musco, G.; Spitaleri, A.
2014-11-01
GMXPBSA 2.0 is a user-friendly suite of Bash/Perl scripts for streamlining MM/PBSA calculations on structural ensembles derived from GROMACS trajectories, to automatically calculate binding free energies for protein-protein or ligand-protein complexes. GMXPBSA 2.0 is flexible and can easily be customized to specific needs. Additionally, it performs computational alanine scanning (CAS) to study the effects of ligand and/or receptor alanine mutations on the free energy of binding. Calculations require only for protein-protein or protein-ligand MD simulations. GMXPBSA 2.0 performs different comparative analysis, including a posteriori generation of alanine mutants of the wild-type complex, calculation of the binding free energy values of the mutant complexes and comparison of the results with the wild-type system. Moreover, it compares the binding free energy of different complexes trajectories, allowing the study the effects of non-alanine mutations, post-translational modifications or unnatural amino acids on the binding free energy of the system under investigation. Finally, it can calculate and rank relative affinity to the same receptor utilizing MD simulations of proteins in complex with different ligands. In order to dissect the different MM/PBSA energy contributions, including molecular mechanic (MM), electrostatic contribution to solvation (PB) and nonpolar contribution to solvation (SA), the tool combines two freely available programs: the MD simulations software GROMACS and the Poisson-Boltzmann equation solver APBS. All the calculations can be performed in single or distributed automatic fashion on a cluster facility in order to increase the calculation by dividing frames across the available processors. The program is freely available under the GPL license.
Leverentz, Hannah R; Qi, Helena W; Truhlar, Donald G
2013-02-12
The binding energies and relative conformational energies of five configurations of the water 16-mer are computed using 61 levels of density functional (DF) theory, 12 methods combining DF theory with molecular mechanics damped dispersion (DF-MM), seven semiempirical-wave function (SWF) methods, and five methods combining SWF theory with molecular mechanics damped dispersion (SWF-MM). The accuracies of the computed energies are assessed by comparing them to recent high-level ab initio results; this assessment is more relevant to bulk water than previous tests on small clusters because a 16-mer is large enough to have water molecules that participate in more than three hydrogen bonds. We find that for water 16-mer binding energies the best DF, DF-MM, SWF, and SWF-MM methods (and their mean unsigned errors in kcal/mol) are respectively M06-2X (1.6), ωB97X-D (2.3), SCC-DFTB-γ(h) (35.2), and PM3-D (3.2). We also mention the good performance of CAM-B3LYP (1.8), M05-2X (1.9), and TPSSLYP (3.0). In contrast, for relative energies of various water nanoparticle 16-mer structures, the best methods (and mean unsigned errors in kcal/mol), in the same order of classes of methods, are SOGGA11-X (0.3), ωB97X-D (0.2), PM6 (0.4), and PMOv1 (0.6). We also mention the good performance of LC-ωPBE-D3 (0.3) and ωB97X (0.4). When both relative and binding energies are taken into consideration, the best methods overall (out of the 85 tested) are M05-2X without molecular mechanics and ωB97X-D when molecular mechanics corrections are included; with considerably higher average errors and considerably lower cost, the best SWF or SWF-MM method is PMOv1. We use six of the best methods for binding energies of the water 16-mers to calculate the binding energies of water hexamers and water 17-mers to test whether these methods are also reliable for binding energy calculations on other types of water clusters.
Δ isobars and nuclear saturation
NASA Astrophysics Data System (ADS)
Ekström, A.; Hagen, G.; Morris, T. D.; Papenbrock, T.; Schwartz, P. D.
2018-02-01
We construct a nuclear interaction in chiral effective field theory with explicit inclusion of the Δ -isobar Δ (1232 ) degree of freedom at all orders up to next-to-next-to-leading order (NNLO). We use pion-nucleon (π N ) low-energy constants (LECs) from a Roy-Steiner analysis of π N scattering data, optimize the LECs in the contact potentials up to NNLO to reproduce low-energy nucleon-nucleon scattering phase shifts, and constrain the three-nucleon interaction at NNLO to reproduce the binding energy and point-proton radius of 4He. For heavier nuclei we use the coupled-cluster method to compute binding energies, radii, and neutron skins. We find that radii and binding energies are much improved for interactions with explicit inclusion of Δ (1232 ) , while Δ -less interactions produce nuclei that are not bound with respect to breakup into α particles. The saturation of nuclear matter is significantly improved, and its symmetry energy is consistent with empirical estimates.
Accurate Binding Free Energy Predictions in Fragment Optimization.
Steinbrecher, Thomas B; Dahlgren, Markus; Cappel, Daniel; Lin, Teng; Wang, Lingle; Krilov, Goran; Abel, Robert; Friesner, Richard; Sherman, Woody
2015-11-23
Predicting protein-ligand binding free energies is a central aim of computational structure-based drug design (SBDD)--improved accuracy in binding free energy predictions could significantly reduce costs and accelerate project timelines in lead discovery and optimization. The recent development and validation of advanced free energy calculation methods represents a major step toward this goal. Accurately predicting the relative binding free energy changes of modifications to ligands is especially valuable in the field of fragment-based drug design, since fragment screens tend to deliver initial hits of low binding affinity that require multiple rounds of synthesis to gain the requisite potency for a project. In this study, we show that a free energy perturbation protocol, FEP+, which was previously validated on drug-like lead compounds, is suitable for the calculation of relative binding strengths of fragment-sized compounds as well. We study several pharmaceutically relevant targets with a total of more than 90 fragments and find that the FEP+ methodology, which uses explicit solvent molecular dynamics and physics-based scoring with no parameters adjusted, can accurately predict relative fragment binding affinities. The calculations afford R(2)-values on average greater than 0.5 compared to experimental data and RMS errors of ca. 1.1 kcal/mol overall, demonstrating significant improvements over the docking and MM-GBSA methods tested in this work and indicating that FEP+ has the requisite predictive power to impact fragment-based affinity optimization projects.
A computational analysis of the binding model of MDM2 with inhibitors
NASA Astrophysics Data System (ADS)
Hu, Guodong; Wang, Dunyou; Liu, Xinguo; Zhang, Qinggang
2010-08-01
It is a new and promising strategy for anticancer drug design to block the MDM2-p53 interaction using a non-peptide small-molecule inhibitor. We carry out molecular dynamics simulations to study the binding of a set of six non-peptide small-molecule inhibitors with the MDM2. The relative binding free energies calculated using molecular mechanics Poisson-Boltzmann surface area method produce a good correlation with experimentally determined results. The study shows that the van der Waals energies are the largest component of the binding free energy for each complex, which indicates that the affinities of these inhibitors for MDM2 are dominated by shape complementarity. The A-ligands and the B-ligands are the same except for the conformation of 2,2-dimethylbutane group. The quantum mechanics and the binding free energies calculation also show the B-ligands are the more possible conformation of ligands. Detailed binding free energies between inhibitors and individual protein residues are calculated to provide insights into the inhibitor-protein binding model through interpretation of the structural and energetic results from the simulations. The study shows that G1, G2 and G3 group mimic the Phe19, Trp23 and Leu26 residues in p53 and their interactions with MDM2, but the binding model of G4 group differs from the original design strategy to mimic Leu22 residue in p53.
Orgován, Zoltán; Ferenczy, György G; Steinbrecher, Thomas; Szilágyi, Bence; Bajusz, Dávid; Keserű, György M
2018-02-01
Optimization of fragment size D-amino acid oxidase (DAAO) inhibitors was investigated using a combination of computational and experimental methods. Retrospective free energy perturbation (FEP) calculations were performed for benzo[d]isoxazole derivatives, a series of known inhibitors with two potential binding modes derived from X-ray structures of other DAAO inhibitors. The good agreement between experimental and computed binding free energies in only one of the hypothesized binding modes strongly support this bioactive conformation. Then, a series of 1-H-indazol-3-ol derivatives formerly not described as DAAO inhibitors was investigated. Binding geometries could be reliably identified by structural similarity to benzo[d]isoxazole and other well characterized series and FEP calculations were performed for several tautomers of the deprotonated and protonated compounds since all these forms are potentially present owing to the experimental pKa values of representative compounds in the series. Deprotonated compounds are proposed to be the most important bound species owing to the significantly better agreement between their calculated and measured affinities compared to the protonated forms. FEP calculations were also used for the prediction of the affinities of compounds not previously tested as DAAO inhibitors and for a comparative structure-activity relationship study of the benzo[d]isoxazole and indazole series. Selected indazole derivatives were synthesized and their measured binding affinity towards DAAO was in good agreement with FEP predictions.
NASA Astrophysics Data System (ADS)
Orgován, Zoltán; Ferenczy, György G.; Steinbrecher, Thomas; Szilágyi, Bence; Bajusz, Dávid; Keserű, György M.
2018-02-01
Optimization of fragment size d-amino acid oxidase (DAAO) inhibitors was investigated using a combination of computational and experimental methods. Retrospective free energy perturbation (FEP) calculations were performed for benzo[d]isoxazole derivatives, a series of known inhibitors with two potential binding modes derived from X-ray structures of other DAAO inhibitors. The good agreement between experimental and computed binding free energies in only one of the hypothesized binding modes strongly support this bioactive conformation. Then, a series of 1-H-indazol-3-ol derivatives formerly not described as DAAO inhibitors was investigated. Binding geometries could be reliably identified by structural similarity to benzo[d]isoxazole and other well characterized series and FEP calculations were performed for several tautomers of the deprotonated and protonated compounds since all these forms are potentially present owing to the experimental pKa values of representative compounds in the series. Deprotonated compounds are proposed to be the most important bound species owing to the significantly better agreement between their calculated and measured affinities compared to the protonated forms. FEP calculations were also used for the prediction of the affinities of compounds not previously tested as DAAO inhibitors and for a comparative structure-activity relationship study of the benzo[d]isoxazole and indazole series. Selected indazole derivatives were synthesized and their measured binding affinity towards DAAO was in good agreement with FEP predictions.
Du, Juan; Qiu, Miaoxue; Guo, Lizhong; Yao, Xiaojun
2018-05-02
Farnesoid X receptor α (FXRα) is a bile acid-activated transcription factor, which plays important roles in the regulation of multiple metabolic processes. Development of FXR antagonist has revealed great potential for the treatment of metabolic disorders. The compound N-Benzyl-N-(3-(tertbutyl)-4-hydroxyphenyl)-2,6-dichloro-4-(dimethylamino). Benzamide (NDB) was recently determined as a selective antagonist of FXRα, while the detailed interaction mechanism is not well understood. In this study, the combined computational methods including molecular dynamics simulations, binding free energy calculation, and principal component analysis were utilized to investigate the effect of NDB on the dynamics behaviors and dimerization of FXRα The binding free energy calculation indicated that the protein dimerization increases NDB affinity and the binding of NDB also stabilizes the interaction between two subunits of FXRα. Further decomposition of the overall binding free energies into individual residues identifies several residues significant for NDB binding, including Leu291, Met294, Ala295, His298, Met332, Ser336, Ala452, and Leu455. It also suggests that the interactions of L289(A)-W458(B), W458(A)-L289(B), R459(A)-N461(B), and N461(A)-R459(B) are important for the dimer stabilization. This study provides a molecular basis for the understanding of binding mechanism between antagonist NDB and FXRα and valuable information for the novel FXR modulators design for the treatment of metabolic syndrome.
NASA Astrophysics Data System (ADS)
Ilayaraja, Renganathan; Rajkumar, Ramalingam; Rajesh, Durairaj; Muralidharan, Arumugam Ramachandran; Padmanabhan, Parasuraman; Archunan, Govindaraju
2014-06-01
Chemosignals play a crucial role in social and sexual communication among inter- and intra-species. Chemical cues are bound with protein that is present in the pheromones irrespective of sex are commonly called as pheromone binding protein (PBP). In rats, the pheromone compounds are bound with low molecular lipocalin protein α2u-globulin (α2u). We reported farnesol is a natural endogenous ligand (compound) present in rat preputial gland as a bound volatile compound. In the present study, an attempt has been made through computational method to evaluating the binding efficiency of α2u with the natural ligand (farnesol) and standard fluorescent molecule (2-naphthol). The docking analysis revealed that the binding energy of farnesol and 2-naphthol was almost equal and likely to share some binding pocket of protein. Further, to extrapolate the results generated through computational approach, the α2u protein was purified and subjected to fluorescence titration and binding assay. The results showed that the farnesol is replaced by 2-naphthol with high hydrophobicity of TYR120 in binding sites of α2u providing an acceptable dissociation constant indicating the binding efficiency of α2u. The obtained results are in corroboration with the data made through computational approach.
Concepts in receptor optimization: targeting the RGD peptide.
Chen, Wei; Chang, Chia-en; Gilson, Michael K
2006-04-12
Synthetic receptors have a wide range of potential applications, but it has been difficult to design low molecular weight receptors that bind ligands with high, "proteinlike" affinities. This study uses novel computational methods to understand why it is hard to design a high-affinity receptor and to explore the limits of affinity, with the bioactive peptide RGD as a model ligand. The M2 modeling method is found to yield excellent agreement with experiment for a known RGD receptor and then is used to analyze a series of receptors generated in silico with a de novo design algorithm. Forces driving binding are found to be systematically opposed by proportionate repulsions due to desolvation and entropy. In particular, strong correlations are found between Coulombic attractions and the electrostatic desolvation penalty and between the mean energy change on binding and the cost in configurational entropy. These correlations help explain why it is hard to achieve high affinity. The change in surface area upon binding is found to correlate poorly with affinity within this series. Measures of receptor efficiency are formulated that summarize how effectively a receptor uses surface area, total energy, and Coulombic energy to achieve affinity. Analysis of the computed efficiencies suggests that a low molecular weight receptor can achieve proteinlike affinity. It is also found that macrocyclization of a receptor can, unexpectedly, increase the entropy cost of binding because the macrocyclic structure further restricts ligand motion.
Simões, Inês C M; Costa, Inês P D; Coimbra, João T S; Ramos, Maria J; Fernandes, Pedro A
2017-01-23
Knowing how proteins make stable complexes enables the development of inhibitors to preclude protein-protein (P:P) binding. The identification of the specific interfacial residues that mostly contribute to protein binding, denominated as hot spots, is thus critical. Here, we refine an in silico alanine scanning mutagenesis protocol, based on a residue-dependent dielectric constant version of the Molecular Mechanics/Poisson-Boltzmann Surface Area method. We have used a large data set of structurally diverse P:P complexes to redefine the residue-dependent dielectric constants used in the determination of binding free energies. The accuracy of the method was validated through comparison with experimental data, considering the per-residue P:P binding free energy (ΔΔG binding ) differences upon alanine mutation. Different protocols were tested, i.e., a geometry optimization protocol and three molecular dynamics (MD) protocols: (1) one using explicit water molecules, (2) another with an implicit solvation model, and (3) a third where we have carried out an accelerated MD with explicit water molecules. Using a set of protein dielectric constants (within the range from 1 to 20) we showed that the dielectric constants of 7 for nonpolar and polar residues and 11 for charged residues (and histidine) provide optimal ΔΔG binding predictions. An overall mean unsigned error (MUE) of 1.4 kcal mol -1 relative to the experiment was achieved in 210 mutations only with geometry optimization, which was further reduced with MD simulations (MUE of 1.1 kcal mol -1 for the MD employing explicit solvent). This recalibrated method allows for a better computational identification of hot spots, avoiding expensive and time-consuming experiments or thermodynamic integration/ free energy perturbation/ uBAR calculations, and will hopefully help new drug discovery campaigns in their quest of searching spots of interest for binding small drug-like molecules at P:P interfaces.
The potential for fast van der Waals computations for layered materials using a Lifshitz model
NASA Astrophysics Data System (ADS)
Zhou, Yao; Pellouchoud, Lenson A.; Reed, Evan J.
2017-06-01
Computation of the van der Waals (vdW) interactions plays a crucial role in the study of layered materials. The adiabatic-connection fluctuation-dissipation theorem within random phase approximation (ACFDT-RPA) has been empirically reported to be the most accurate of commonly used methods, but it is limited to small systems due to its computational complexity. Without a computationally tractable vdW correction, fictitious strains are often introduced in the study of multilayer heterostructures, which, we find, can change the vdW binding energy by as much as 15%. In this work, we employed for the first time a defined Lifshitz model to provide the vdW potentials for a spectrum of layered materials orders of magnitude faster than the ACFDT-RPA for representative layered material structures. We find that a suitably defined Lifshitz model gives the correlation component of the binding energy to within 8-20% of the ACFDT-RPA calculations for a variety of layered heterostructures. Using this fast Lifshitz model, we studied the vdW binding properties of 210 three-layered heterostructures. Our results demonstrate that the three-body vdW effects are generally small (10% of the binding energy) in layered materials for most cases, and that non-negligible second-nearest neighbor layer interaction and three-body effects are observed for only those cases in which the middle layer is atomically thin (e.g. BN or graphene). We find that there is potential for particular combinations of stacked layers to exhibit repulsive three-body van der Waals effects, although these effects are likely to be much smaller than two-body effects.
Homeyer, Nadine; Stoll, Friederike; Hillisch, Alexander; Gohlke, Holger
2014-08-12
Correctly ranking compounds according to their computed relative binding affinities will be of great value for decision making in the lead optimization phase of industrial drug discovery. However, the performance of existing computationally demanding binding free energy calculation methods in this context is largely unknown. We analyzed the performance of the molecular mechanics continuum solvent, the linear interaction energy (LIE), and the thermodynamic integration (TI) approach for three sets of compounds from industrial lead optimization projects. The data sets pose challenges typical for this early stage of drug discovery. None of the methods was sufficiently predictive when applied out of the box without considering these challenges. Detailed investigations of failures revealed critical points that are essential for good binding free energy predictions. When data set-specific features were considered accordingly, predictions valuable for lead optimization could be obtained for all approaches but LIE. Our findings lead to clear recommendations for when to use which of the above approaches. Our findings also stress the important role of expert knowledge in this process, not least for estimating the accuracy of prediction results by TI, using indicators such as the size and chemical structure of exchanged groups and the statistical error in the predictions. Such knowledge will be invaluable when it comes to the question which of the TI results can be trusted for decision making.
Computational biology of RNA interactions.
Dieterich, Christoph; Stadler, Peter F
2013-01-01
The biodiversity of the RNA world has been underestimated for decades. RNA molecules are key building blocks, sensors, and regulators of modern cells. The biological function of RNA molecules cannot be separated from their ability to bind to and interact with a wide space of chemical species, including small molecules, nucleic acids, and proteins. Computational chemists, physicists, and biologists have developed a rich tool set for modeling and predicting RNA interactions. These interactions are to some extent determined by the binding conformation of the RNA molecule. RNA binding conformations are approximated with often acceptable accuracy by sequence and secondary structure motifs. Secondary structure ensembles of a given RNA molecule can be efficiently computed in many relevant situations by employing a standard energy model for base pair interactions and dynamic programming techniques. The case of bi-molecular RNA-RNA interactions can be seen as an extension of this approach. However, unbiased transcriptome-wide scans for local RNA-RNA interactions are computationally challenging yet become efficient if the binding motif/mode is known and other external information can be used to confine the search space. Computational methods are less developed for proteins and small molecules, which bind to RNA with very high specificity. Binding descriptors of proteins are usually determined by in vitro high-throughput assays (e.g., microarrays or sequencing). Intriguingly, recent experimental advances, which are mostly based on light-induced cross-linking of binding partners, render in vivo binding patterns accessible yet require new computational methods for careful data interpretation. The grand challenge is to model the in vivo situation where a complex interplay of RNA binders competes for the same target RNA molecule. Evidently, bioinformaticians are just catching up with the impressive pace of these developments. Copyright © 2012 John Wiley & Sons, Ltd.
NASA Astrophysics Data System (ADS)
Anisimov, Victor M.; Ziemys, Arturas; Kizhake, Smitha; Yuan, Ziyan; Natarajan, Amarnath; Cavasotto, Claudio N.
2011-11-01
The C-terminal domain of BRCA1(BRCT) is involved in the DNA repair pathway by recognizing the pSXXF motif in interacting proteins. It has been reported that short peptides containing this motif bind to BRCA1(BRCT) in the micromolar range with high specificity. In this work, the binding of pSXXF peptides has been studied computationally and experimentally in order to characterize their interaction with BRCA1(BRCT). Elucidation of the contacts that drive the protein-ligand interaction is critical for the development of high affinity small-molecule BRCA1 inhibitors. Molecular dynamics (MD) simulations revealed the key role of threonine at the peptide P+2 position in providing structural rigidity to the ligand in the bound state. The mutation at P+1 had minor effects. Peptide extension at the N-terminal position with the naphthyl amino acid exhibited a modest increase in binding affinity, what could be explained by the dispersion interaction of the naphthyl side-chain with a hydrophobic patch. Three in silico end-point methods were considered for the calculation of binding free energy. The Molecular Mechanics Poisson-Boltzmann Surface Area and the Solvated Interaction Energy methods gave reasonable agreement with experimental data, exhibiting a Pearlman predictive index of 0.71 and 0.78, respectively. The MM-quantum mechanics-surface area method yielded improved results, which was characterized by a Pearlman index of 0.78. The correlation coefficients were 0.59, 0.61 and 0.69, respectively. The ability to apply a QM level of theory within an end-point binding free energy protocol may provide a way for a consistent improvement of accuracy in computer-aided drug design.
NASA Astrophysics Data System (ADS)
Mrugalla, Florian; Kast, Stefan M.
2016-09-01
Complex formation between molecules in solution is the key process by which molecular interactions are translated into functional systems. These processes are governed by the binding or free energy of association which depends on both direct molecular interactions and the solvation contribution. A design goal frequently addressed in pharmaceutical sciences is the optimization of chemical properties of the complex partners in the sense of minimizing their binding free energy with respect to a change in chemical structure. Here, we demonstrate that liquid-state theory in the form of the solute-solute equation of the reference interaction site model provides all necessary information for such a task with high efficiency. In particular, computing derivatives of the potential of mean force (PMF), which defines the free-energy surface of complex formation, with respect to potential parameters can be viewed as a means to define a direction in chemical space toward better binders. We illustrate the methodology in the benchmark case of alkali ion binding to the crown ether 18-crown-6 in aqueous solution. In order to examine the validity of the underlying solute-solute theory, we first compare PMFs computed by different approaches, including explicit free-energy molecular dynamics simulations as a reference. Predictions of an optimally binding ion radius based on free-energy derivatives are then shown to yield consistent results for different ion parameter sets and to compare well with earlier, orders-of-magnitude more costly explicit simulation results. This proof-of-principle study, therefore, demonstrates the potential of liquid-state theory for molecular design problems.
Mrugalla, Florian; Kast, Stefan M
2016-09-01
Complex formation between molecules in solution is the key process by which molecular interactions are translated into functional systems. These processes are governed by the binding or free energy of association which depends on both direct molecular interactions and the solvation contribution. A design goal frequently addressed in pharmaceutical sciences is the optimization of chemical properties of the complex partners in the sense of minimizing their binding free energy with respect to a change in chemical structure. Here, we demonstrate that liquid-state theory in the form of the solute-solute equation of the reference interaction site model provides all necessary information for such a task with high efficiency. In particular, computing derivatives of the potential of mean force (PMF), which defines the free-energy surface of complex formation, with respect to potential parameters can be viewed as a means to define a direction in chemical space toward better binders. We illustrate the methodology in the benchmark case of alkali ion binding to the crown ether 18-crown-6 in aqueous solution. In order to examine the validity of the underlying solute-solute theory, we first compare PMFs computed by different approaches, including explicit free-energy molecular dynamics simulations as a reference. Predictions of an optimally binding ion radius based on free-energy derivatives are then shown to yield consistent results for different ion parameter sets and to compare well with earlier, orders-of-magnitude more costly explicit simulation results. This proof-of-principle study, therefore, demonstrates the potential of liquid-state theory for molecular design problems.
NASA Technical Reports Server (NTRS)
Ricca, Alessandra; Baushlicher, Charles W., Jr.
1995-01-01
The structures and CO binding energies are computed for Fe(CO)n- using a hybrid density functional theory (DFT) approach. The structures and ground states can be explained in terms of maximizing the Fe to CO 2pi* donation and minimizing Fe-CO 5 sigma repulsion. The trends in the CO binding energies for Fe(CO)n- and the differences between the trends for Fe(CO)n- and Fe(CO)n are also explained. For Fe(CO)n-, the second, third, and fourth CO bonding energies are in good agreement with experiment, while the first is too small. The first CO binding is also too small using the coupled cluster singles and doubles approach including a perturbation estimate of the connected triple excitations.
Tight-binding calculation studies of vacancy and adatom defects in graphene
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Wei; Lu, Wen-Cai; Zhang, Hong-Xing
2016-02-19
Computational studies of complex defects in graphene usually need to deal with a larger number of atoms than the current first-principles methods can handle. We show a recently developed three-center tight-binding potential for carbon is very efficient for large scale atomistic simulations and can accurately describe the structures and energies of various defects in graphene. Using the three-center tight-binding potential, we have systematically studied the stable structures and formation energies of vacancy and embedded-atom defects of various sizes up to 4 vacancies and 4 embedded atoms in graphene. In conclusion, our calculations reveal low-energy defect structures and provide a moremore » comprehensive understanding of the structures and stability of defects in graphene.« less
Silva, José Rogério A; Bishai, William R; Govender, Thavendran; Lamichhane, Gyanu; Maguire, Glenn E M; Kruger, Hendrik G; Lameira, Jeronimo; Alves, Cláudio N
2016-01-01
The single crystal X-ray structure of the extracellular portion of the L,D-transpeptidase (ex-LdtMt2 - residues 120-408) enzyme was recently reported. It was observed that imipenem and meropenem inhibit activity of this enzyme, responsible for generating L,D-transpeptide linkages in the peptidoglycan layer of Mycobacterium tuberculosis. Imipenem is more active and isothermal titration calorimetry experiments revealed that meropenem is subjected to an entropy penalty upon binding to the enzyme. Herein, we report a molecular modeling approach to obtain a molecular view of the inhibitor/enzyme interactions. The average binding free energies for nine commercially available inhibitors were calculated using MM/GBSA and Solvation Interaction Energy (SIE) approaches and the calculated energies corresponded well with the available experimentally observed results. The method reproduces the same order of binding energies as experimentally observed for imipenem and meropenem. We have also demonstrated that SIE is a reasonably accurate and cost-effective free energy method, which can be used to predict carbapenem affinities for this enzyme. A theoretical explanation was offered for the experimental entropy penalty observed for meropenem, creating optimism that this computational model can serve as a potential computational model for other researchers in the field.
Davis, Matthew R.; Dougherty, Dennis A.
2015-01-01
Cation-π interactions are common in biological systems, and many structural studies have revealed the aromatic box as a common motif. With the aim of understanding the nature of the aromatic box, several computational methods were evaluated for their ability to reproduce experimental cation-π binding energies. We find the DFT method M06 with the 6-31G(d,p) basis set performs best of several methods tested. The binding of benzene to a number of different cations (sodium, potassium, ammonium, tetramethylammonium, and guanidinium) was studied. In addition, the binding of the organic cations NH4+ and NMe4+ to ab initio generated aromatic boxes as well as examples of aromatic boxes from protein crystal structures were investigated. These data, along with a study of the distance dependence of the cation-π interaction, indicate that multiple aromatic residues can meaningfully contribute to cation binding, even with displacements of more than an angstrom from the optimal cation-π interaction. Progressive fluorination of benzene and indole was studied as well, and binding energies obtained were used to reaffirm the validity of the “fluorination strategy” to study cation-π interactions in vivo. PMID:26467787
Davis, Matthew R; Dougherty, Dennis A
2015-11-21
Cation-π interactions are common in biological systems, and many structural studies have revealed the aromatic box as a common motif. With the aim of understanding the nature of the aromatic box, several computational methods were evaluated for their ability to reproduce experimental cation-π binding energies. We find the DFT method M06 with the 6-31G(d,p) basis set performs best of several methods tested. The binding of benzene to a number of different cations (sodium, potassium, ammonium, tetramethylammonium, and guanidinium) was studied. In addition, the binding of the organic cations NH4(+) and NMe4(+) to ab initio generated aromatic boxes as well as examples of aromatic boxes from protein crystal structures were investigated. These data, along with a study of the distance dependence of the cation-π interaction, indicate that multiple aromatic residues can meaningfully contribute to cation binding, even with displacements of more than an angstrom from the optimal cation-π interaction. Progressive fluorination of benzene and indole was studied as well, and binding energies obtained were used to reaffirm the validity of the "fluorination strategy" to study cation-π interactions in vivo.
CaFE: a tool for binding affinity prediction using end-point free energy methods.
Liu, Hui; Hou, Tingjun
2016-07-15
Accurate prediction of binding free energy is of particular importance to computational biology and structure-based drug design. Among those methods for binding affinity predictions, the end-point approaches, such as MM/PBSA and LIE, have been widely used because they can achieve a good balance between prediction accuracy and computational cost. Here we present an easy-to-use pipeline tool named Calculation of Free Energy (CaFE) to conduct MM/PBSA and LIE calculations. Powered by the VMD and NAMD programs, CaFE is able to handle numerous static coordinate and molecular dynamics trajectory file formats generated by different molecular simulation packages and supports various force field parameters. CaFE source code and documentation are freely available under the GNU General Public License via GitHub at https://github.com/huiliucode/cafe_plugin It is a VMD plugin written in Tcl and the usage is platform-independent. tingjunhou@zju.edu.cn. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Molecular Dynamics Simulations of Protein-Ligand Complexes in Near Physiological Conditions
NASA Astrophysics Data System (ADS)
Wambo, Thierry Oscar
Proteins are important molecules for their key functions. However, under certain circumstances, the function of these proteins needs to be regulated to keep us healthy. Ligands are small molecules often used to modulate the function of proteins. The binding affinity is a quantitative measure of how strong the ligand will modulate the function of the protein: a strong binding affinity will highly impact the performance of the protein. It becomes clear that it is critical to have appropriate techniques to accurately compute the binding affinity. The most difficult task in computer simulations is how to efficiently sample the space spanned by the ligand during the binding process. In this work, we have developed some schemes to compute the binding affinity of a ligand to a protein, and of a metal ion to a protein. Application of these techniques to some complexes yield results in agreement with experimental values. These methods are a brute force approach and make no assumption other than that the complexes are governed by the force field used. Specifically, we computed the free energy of binding between (1) human carbonic anhydrase II and the drug acetazolamide (hcaII-AZM), (2) human carbonic anhydrase II and the zinc ion (hcaII-Zinc), and (3) beta-lactoglobulin and five fatty acids complexes (BLG-FAs). We found the following free energies of binding in unit of kcal/mol: -12.96 +/-2.44 (-15.74) for hcaII-Zinc complex, -5.76+/-0.76 (-5.57) for BLG-OCA , -4.44+/-1.08 (-5.22) for BLG-DKA,-6.89+/-1.25 (-7.24) for BLG-DAO, -8.57+/-0.82 (-8.14) for BLG-MYR, -8.99+/-0.87 (-8.72) for BLG-PLM, and -11.87+/-1.8 (-10.8) for hcaII-AZM. The values inside the parentheses are experimental results. The simulations and quantitative analysis of each system provide interesting insights into the interactions between each entity and helps us to better understand the dynamics of these systems.
Kim, Ki Chul; Fairen-Jimenez, David; Snurr, Randall Q
2017-12-06
A thermodynamic analysis using quantum chemical methods was carried out to identify optimal functional group candidates that can be included in metal-organic frameworks and activated carbons for the selective capture of toxic industrial chemicals (TICs) in humid air. We calculated the binding energies of 14 critical TICs plus water with a series of 10 functional groups attached to a naphthalene ring model. Using vibrational calculations, the free energies of adsorption were calculated in addition to the binding energies. Our results show that, in these systems, the binding energies and free energies follow similar trends. We identified copper(i) carboxylate as the optimal functional group (among those studied) for the selective binding of the majority of the TICs in humid air, and this functional group exhibits especially strong binding for sulfuric acid. Further thermodynamic analysis shows that the presence of water weakens the binding strength of sulfuric acid with the copper carboxylate group. Our calculations predict that functionalization of aromatic rings would be detrimental to selective capture of COCl 2 , CO 2 , and Cl 2 under humid conditions. Finally, we found that forming an ionic complex, H 3 O + HSO 4 - , between H 2 SO 4 and H 2 O via proton transfer is not favorable on copper carboxylate.
An insight to the molecular interactions of the FDA approved HIV PR drugs against L38L↑N↑L PR mutant
NASA Astrophysics Data System (ADS)
Sanusi, Zainab K.; Govender, Thavendran; Maguire, Glenn E. M.; Maseko, Sibusiso B.; Lin, Johnson; Kruger, Hendrik G.; Honarparvar, Bahareh
2018-03-01
The aspartate protease of the human immune deficiency type-1 virus (HIV-1) has become a crucial antiviral target in which many useful antiretroviral inhibitors have been developed. However, it seems the emergence of new HIV-1 PR mutations enhances drug resistance, hence, the available FDA approved drugs show less activity towards the protease. A mutation and insertion designated L38L↑N↑L PR was recently reported from subtype of C-SA HIV-1. An integrated two-layered ONIOM (QM:MM) method was employed in this study to examine the binding affinities of the nine HIV PR inhibitors against this mutant. The computed binding free energies as well as experimental data revealed a reduced inhibitory activity towards the L38L↑N↑L PR in comparison with subtype C-SA HIV-1 PR. This observation suggests that the insertion and mutations significantly affect the binding affinities or characteristics of the HIV PIs and/or parent PR. The same trend for the computational binding free energies was observed for eight of the nine inhibitors with respect to the experimental binding free energies. The outcome of this study shows that ONIOM method can be used as a reliable computational approach to rationalize lead compounds against specific targets. The nature of the intermolecular interactions in terms of the host-guest hydrogen bond interactions is discussed using the atoms in molecules (AIM) analysis. Natural bond orbital analysis was also used to determine the extent of charge transfer between the QM region of the L38L↑N↑L PR enzyme and FDA approved drugs. AIM analysis showed that the interaction between the QM region of the L38L↑N↑L PR and FDA approved drugs are electrostatic dominant, the bond stability computed from the NBO analysis supports the results from the AIM application. Future studies will focus on the improvement of the computational model by considering explicit water molecules in the active pocket. We believe that this approach has the potential to provide information that will aid in the design of much improved HIV-1 PR antiviral drugs.
Tian, Ye; Huang, Xiaoqiang; Zhu, Yushan
2015-08-01
Enzyme amino-acid sequences at ligand-binding interfaces are evolutionarily optimized for reactions, and the natural conformation of an enzyme-ligand complex must have a low free energy relative to alternative conformations in native-like or non-native sequences. Based on this assumption, a combined energy function was developed for enzyme design and then evaluated by recapitulating native enzyme sequences at ligand-binding interfaces for 10 enzyme-ligand complexes. In this energy function, the electrostatic interaction between polar or charged atoms at buried interfaces is described by an explicitly orientation-dependent hydrogen-bonding potential and a pairwise-decomposable generalized Born model based on the general side chain in the protein design framework. The energy function is augmented with a pairwise surface-area based hydrophobic contribution for nonpolar atom burial. Using this function, on average, 78% of the amino acids at ligand-binding sites were predicted correctly in the minimum-energy sequences, whereas 84% were predicted correctly in the most-similar sequences, which were selected from the top 20 sequences for each enzyme-ligand complex. Hydrogen bonds at the enzyme-ligand binding interfaces in the 10 complexes were usually recovered with the correct geometries. The binding energies calculated using the combined energy function helped to discriminate the active sequences from a pool of alternative sequences that were generated by repeatedly solving a series of mixed-integer linear programming problems for sequence selection with increasing integer cuts.
Martins, Silvia A; Sousa, Sergio F
2013-06-05
The determination of differences in solvation free energies between related drug molecules remains an important challenge in computational drug optimization, when fast and accurate calculation of differences in binding free energy are required. In this study, we have evaluated the performance of five commonly used polarized continuum model (PCM) methodologies in the determination of solvation free energies for 53 typical alcohol and alkane small molecules. In addition, the performance of these PCM methods, of a thermodynamic integration (TI) protocol and of the Poisson-Boltzmann (PB) and generalized Born (GB) methods, were tested in the determination of solvation free energies changes for 28 common alkane-alcohol transformations, by the substitution of an hydrogen atom for a hydroxyl substituent. The results show that the solvation model D (SMD) performs better among the PCM-based approaches in estimating solvation free energies for alcohol molecules, and solvation free energy changes for alkane-alcohol transformations, with an average error below 1 kcal/mol for both quantities. However, for the determination of solvation free energy changes on alkane-alcohol transformation, PB and TI yielded better results. TI was particularly accurate in the treatment of hydroxyl groups additions to aromatic rings (0.53 kcal/mol), a common transformation when optimizing drug-binding in computer-aided drug design. Copyright © 2013 Wiley Periodicals, Inc.
Hedger, George; Shorthouse, David; Koldsø, Heidi; Sansom, Mark S P
2016-08-25
Lipid molecules can bind to specific sites on integral membrane proteins, modulating their structure and function. We have undertaken coarse-grained simulations to calculate free energy profiles for glycolipids and phospholipids interacting with modulatory sites on the transmembrane helix dimer of the EGF receptor within a lipid bilayer environment. We identify lipid interaction sites at each end of the transmembrane domain and compute interaction free energy profiles for lipids with these sites. Interaction free energies ranged from ca. -40 to -4 kJ/mol for different lipid species. Those lipids (glycolipid GM3 and phosphoinositide PIP2) known to modulate EGFR function exhibit the strongest binding to interaction sites on the EGFR, and we are able to reproduce the preference for interaction with GM3 over other glycolipids suggested by experiment. Mutation of amino acid residues essential for EGFR function reduce the binding free energy of these key lipid species. The residues interacting with the lipids in the simulations are in agreement with those suggested by experimental (mutational) studies. This approach provides a generalizable tool for characterizing the interactions of lipids that bind to specific sites on integral membrane proteins.
Effective Mass Theory of 2D Excitons Revisited
NASA Astrophysics Data System (ADS)
Gonzalez, Joseph; Oleynik, Ivan
Two-dimensional (2D) semiconducting materials possess an exceptionally unique set of electronic and excitonic properties due to the combined effects of quantum and dielectric confinement. Reliable determination of exciton binding energies from both first-principles many-body perturbation theory (GW/BSE) and experiment is very challenging due to the enormous computational expense as well as the tremendous technical difficulties in experiment.. Very recently, effective mass theories of 2D excitons have been developed as an attractive alternative for inexpensive and accurate evaluation of the exciton binding energies. In this presentation, we evaluate two effective mass theory approaches by Velizhanin et al and Olsen et al in predicting exciton binding energies across a wide range of 2D materials. We specifically analyze the trends related to the varying screening lengths and exciton effective masses. We also extended the effective mass theory of 2D excitons to include effects of electron and hole mass anisotropies (mx ≠ my) , the latter showing a substantial influence on exciton binding energies. The recent predictions of exciton binding energies being independent of the exciton effective mass and a linear correlation with the band gap of a specific material are also critically reexamined.
2016-01-01
Lipid molecules can bind to specific sites on integral membrane proteins, modulating their structure and function. We have undertaken coarse-grained simulations to calculate free energy profiles for glycolipids and phospholipids interacting with modulatory sites on the transmembrane helix dimer of the EGF receptor within a lipid bilayer environment. We identify lipid interaction sites at each end of the transmembrane domain and compute interaction free energy profiles for lipids with these sites. Interaction free energies ranged from ca. −40 to −4 kJ/mol for different lipid species. Those lipids (glycolipid GM3 and phosphoinositide PIP2) known to modulate EGFR function exhibit the strongest binding to interaction sites on the EGFR, and we are able to reproduce the preference for interaction with GM3 over other glycolipids suggested by experiment. Mutation of amino acid residues essential for EGFR function reduce the binding free energy of these key lipid species. The residues interacting with the lipids in the simulations are in agreement with those suggested by experimental (mutational) studies. This approach provides a generalizable tool for characterizing the interactions of lipids that bind to specific sites on integral membrane proteins. PMID:27109430
Nishizawa, Hiroaki; Nishimura, Yoshifumi; Kobayashi, Masato; Irle, Stephan; Nakai, Hiromi
2016-08-05
The linear-scaling divide-and-conquer (DC) quantum chemical methodology is applied to the density-functional tight-binding (DFTB) theory to develop a massively parallel program that achieves on-the-fly molecular reaction dynamics simulations of huge systems from scratch. The functions to perform large scale geometry optimization and molecular dynamics with DC-DFTB potential energy surface are implemented to the program called DC-DFTB-K. A novel interpolation-based algorithm is developed for parallelizing the determination of the Fermi level in the DC method. The performance of the DC-DFTB-K program is assessed using a laboratory computer and the K computer. Numerical tests show the high efficiency of the DC-DFTB-K program, a single-point energy gradient calculation of a one-million-atom system is completed within 60 s using 7290 nodes of the K computer. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Zhong, Haizhen A; Santos, Elizabeth M; Vasileiou, Chrysoula; Zheng, Zheng; Geiger, James H; Borhan, Babak; Merz, Kenneth M
2018-03-14
How to fine-tune the binding free energy of a small-molecule to a receptor site by altering the amino acid residue composition is a key question in protein engineering. Indeed, the ultimate solution to this problem, to chemical accuracy (±1 kcal/mol), will result in profound and wide-ranging applications in protein design. Numerous tools have been developed to address this question using knowledge-based models to more computationally intensive molecular dynamics simulations-based free energy calculations, but while some success has been achieved there remains room for improvement in terms of overall accuracy and in the speed of the methodology. Here we report a fast, knowledge-based movable-type (MT)-based approach to estimate the absolute and relative free energy of binding as influenced by mutations in a small-molecule binding site in a protein. We retrospectively validate our approach using mutagenesis data for retinoic acid binding to the Cellular Retinoic Acid Binding Protein II (CRABPII) system and then make prospective predictions that are borne out experimentally. The overall performance of our approach is supported by its success in identifying mutants that show high or even sub-nano-molar binding affinities of retinoic acid to the CRABPII system.
2014-01-01
Background Binding free energy and binding hot spots at protein-protein interfaces are two important research areas for understanding protein interactions. Computational methods have been developed previously for accurate prediction of binding free energy change upon mutation for interfacial residues. However, a large number of interrupted and unimportant atomic contacts are used in the training phase which caused accuracy loss. Results This work proposes a new method, βACV ASA , to predict the change of binding free energy after alanine mutations. βACV ASA integrates accessible surface area (ASA) and our newly defined β contacts together into an atomic contact vector (ACV). A β contact between two atoms is a direct contact without being interrupted by any other atom between them. A β contact’s potential contribution to protein binding is also supposed to be inversely proportional to its ASA to follow the water exclusion hypothesis of binding hot spots. Tested on a dataset of 396 alanine mutations, our method is found to be superior in classification performance to many other methods, including Robetta, FoldX, HotPOINT, an ACV method of β contacts without ASA integration, and ACV ASA methods (similar to βACV ASA but based on distance-cutoff contacts). Based on our data analysis and results, we can draw conclusions that: (i) our method is powerful in the prediction of binding free energy change after alanine mutation; (ii) β contacts are better than distance-cutoff contacts for modeling the well-organized protein-binding interfaces; (iii) β contacts usually are only a small fraction number of the distance-based contacts; and (iv) water exclusion is a necessary condition for a residue to become a binding hot spot. Conclusions βACV ASA is designed using the advantages of both β contacts and water exclusion. It is an excellent tool to predict binding free energy changes and binding hot spots after alanine mutation. PMID:24568581
Gao, J; Chou, L W; Auerbach, A
1993-01-01
A combined quantum mechanical and molecular mechanical Monte Carlo simulation method was used to determine the free energy of binding between tetramethylammonium ion (TMA+) and benzene in water. The computed free energy as a function of distance (the potential of mean force) has two minima that represent contact and solvent-separated complexes. These species are separated by a broad barrier of about 3 kJ/mol. The results are in good accord with experimental data and suggest that TMA+ binds to benzene more favorably than to chloride ion, with an association constant of about 0.8 M-1. Images FIGURE 2 PMID:8369448
Ligand deconstruction: Why some fragment binding positions are conserved and others are not.
Kozakov, Dima; Hall, David R; Jehle, Stefan; Jehle, Sefan; Luo, Lingqi; Ochiana, Stefan O; Jones, Elizabeth V; Pollastri, Michael; Allen, Karen N; Whitty, Adrian; Vajda, Sandor
2015-05-19
Fragment-based drug discovery (FBDD) relies on the premise that the fragment binding mode will be conserved on subsequent expansion to a larger ligand. However, no general condition has been established to explain when fragment binding modes will be conserved. We show that a remarkably simple condition can be developed in terms of how fragments coincide with binding energy hot spots--regions of the protein where interactions with a ligand contribute substantial binding free energy--the locations of which can easily be determined computationally. Because a substantial fraction of the free energy of ligand binding comes from interacting with the residues in the energetically most important hot spot, a ligand moiety that sufficiently overlaps with this region will retain its location even when other parts of the ligand are removed. This hypothesis is supported by eight case studies. The condition helps identify whether a protein is suitable for FBDD, predicts the size of fragments required for screening, and determines whether a fragment hit can be extended into a higher affinity ligand. Our results show that ligand binding sites can usefully be thought of in terms of an anchor site, which is the top-ranked hot spot and dominates the free energy of binding, surrounded by a number of weaker satellite sites that confer improved affinity and selectivity for a particular ligand and that it is the intrinsic binding potential of the protein surface that determines whether it can serve as a robust binding site for a suitably optimized ligand.
Computational Calorimetry: High-Precision Calculation of Host–Guest Binding Thermodynamics
2015-01-01
We present a strategy for carrying out high-precision calculations of binding free energy and binding enthalpy values from molecular dynamics simulations with explicit solvent. The approach is used to calculate the thermodynamic profiles for binding of nine small molecule guests to either the cucurbit[7]uril (CB7) or β-cyclodextrin (βCD) host. For these systems, calculations using commodity hardware can yield binding free energy and binding enthalpy values with a precision of ∼0.5 kcal/mol (95% CI) in a matter of days. Crucially, the self-consistency of the approach is established by calculating the binding enthalpy directly, via end point potential energy calculations, and indirectly, via the temperature dependence of the binding free energy, i.e., by the van’t Hoff equation. Excellent agreement between the direct and van’t Hoff methods is demonstrated for both host–guest systems and an ion-pair model system for which particularly well-converged results are attainable. Additionally, we find that hydrogen mass repartitioning allows marked acceleration of the calculations with no discernible cost in precision or accuracy. Finally, we provide guidance for accurately assessing numerical uncertainty of the results in settings where complex correlations in the time series can pose challenges to statistical analysis. The routine nature and high precision of these binding calculations opens the possibility of including measured binding thermodynamics as target data in force field optimization so that simulations may be used to reliably interpret experimental data and guide molecular design. PMID:26523125
Computational Design of Ligand Binding Proteins with High Affinity and Selectivity
Dou, Jiayi; Doyle, Lindsey; Nelson, Jorgen W.; Schena, Alberto; Jankowski, Wojciech; Kalodimos, Charalampos G.; Johnsson, Kai; Stoddard, Barry L.; Baker, David
2014-01-01
The ability to design proteins with high affinity and selectivity for any given small molecule would have numerous applications in biosensing, diagnostics, and therapeutics, and is a rigorous test of our understanding of the physiochemical principles that govern molecular recognition phenomena. Attempts to design ligand binding proteins have met with little success, however, and the computational design of precise molecular recognition between proteins and small molecules remains an “unsolved problem”1. We describe a general method for the computational design of small molecule binding sites with pre-organized hydrogen bonding and hydrophobic interfaces and high overall shape complementary to the ligand, and use it to design protein binding sites for the steroid digoxigenin (DIG). Of 17 designs that were experimentally characterized, two bind DIG; the highest affinity design has the lowest predicted interaction energy and the most pre-organized binding site in the set. A comprehensive binding-fitness landscape of this design generated by library selection and deep sequencing was used to guide optimization of binding affinity to a picomolar level, and two X-ray co-crystal structures of optimized complexes show atomic level agreement with the design models. The designed binder has a high selectivity for DIG over the related steroids digitoxigenin, progesterone, and β-estradiol, which can be reprogrammed through the designed hydrogen-bonding interactions. Taken together, the binding fitness landscape, co-crystal structures, and thermodynamic binding parameters illustrate how increases in binding affinity can result from distal sequence changes that limit the protein ensemble to conformers making the most energetically favorable interactions with the ligand. The computational design method presented here should enable the development of a new generation of biosensors, therapeutics, and diagnostics. PMID:24005320
Yu, Rilei; Craik, David J.; Kaas, Quentin
2011-01-01
α-Conotoxins potently inhibit isoforms of nicotinic acetylcholine receptors (nAChRs), which are essential for neuronal and neuromuscular transmission. They are also used as neurochemical tools to study nAChR physiology and are being evaluated as drug leads to treat various neuronal disorders. A number of experimental studies have been performed to investigate the structure-activity relationships of conotoxin/nAChR complexes. However, the structural determinants of their binding interactions are still ambiguous in the absence of experimental structures of conotoxin-receptor complexes. In this study, the binding modes of α-conotoxin ImI to the α7-nAChR, currently the best-studied system experimentally, were investigated using comparative modeling and molecular dynamics simulations. The structures of more than 30 single point mutants of either the conotoxin or the receptor were modeled and analyzed. The models were used to explain qualitatively the change of affinities measured experimentally, including some nAChR positions located outside the binding site. Mutational energies were calculated using different methods that combine a conformational refinement procedure (minimization with a distance dependent dielectric constant or explicit water, or molecular dynamics using five restraint strategies) and a binding energy function (MM-GB/SA or MM-PB/SA). The protocol using explicit water energy minimization and MM-GB/SA gave the best correlations with experimental binding affinities, with an R2 value of 0.74. The van der Waals and non-polar desolvation components were found to be the main driving force for binding of the conotoxin to the nAChR. The electrostatic component was responsible for the selectivity of the various ImI mutants. Overall, this study provides novel insights into the binding mechanism of α-conotoxins to nAChRs and the methodological developments reported here open avenues for computational scanning studies of a rapidly expanding range of wild-type and chemically modified α-conotoxins. PMID:21390272
Golden, Mary S.; Cote, Shaun M.; Sayeg, Marianna; Zerbe, Brandon S.; Villar, Elizabeth A.; Beglov, Dmitri; Sazinsky, Stephen L.; Georgiadis, Rosina M.; Vajda, Sandor; Kozakov, Dima; Whitty, Adrian
2013-01-01
We report a comprehensive analysis of binding energy hot spots at the protein-protein interaction (PPI) interface between NF-κB Essential Modulator (NEMO) and IκB kinase subunit β (IKKβ), an interaction that is critical for NF-κB pathway signaling, using experimental alanine scanning mutagenesis and also the FTMap method for computational fragment screening. The experimental results confirm that the previously identified NBD region of IKKβ contains the highest concentration of hot spot residues, the strongest of which are W739, W741 and L742 (ΔΔG = 4.3, 3.5 and 3.2 kcal/mol, respectively). The region occupied by these residues defines a potentially druggable binding site on NEMO that extends for ~16 Å to additionally include the regions that bind IKKβ L737 and F734. NBD residues D738 and S740 are also important for binding but do not make direct contact with NEMO, instead likely acting to stabilize the active conformation of surrounding residues. We additionally found two previously unknown hot spot regions centered on IKKβ residues L708/V709 and L719/I723. The computational approach successfully identified all three hot spot regions on IKKβ. Moreover, the method was able to accurately quantify the energetic importance of all hot spots residues involving direct contact with NEMO. Our results provide new information to guide the discovery of small molecule inhibitors that target the NEMO/IKKβ interaction. They additionally clarify the structural and energetic complementarity between “pocket-forming” and “pocket occupying” hot spot residues, and further validate computational fragment mapping as a method for identifying hot spots at PPI interfaces. PMID:23506214
Computational Study on New Natural Compound Inhibitors of Pyruvate Dehydrogenase Kinases
Zhou, Xiaoli; Yu, Shanshan; Su, Jing; Sun, Liankun
2016-01-01
Pyruvate dehydrogenase kinases (PDKs) are key enzymes in glucose metabolism, negatively regulating pyruvate dehyrogenase complex (PDC) activity through phosphorylation. Inhibiting PDKs could upregulate PDC activity and drive cells into more aerobic metabolism. Therefore, PDKs are potential targets for metabolism related diseases, such as cancers and diabetes. In this study, a series of computer-aided virtual screening techniques were utilized to discover potential inhibitors of PDKs. Structure-based screening using Libdock was carried out following by ADME (adsorption, distribution, metabolism, excretion) and toxicity prediction. Molecular docking was used to analyze the binding mechanism between these compounds and PDKs. Molecular dynamic simulation was utilized to confirm the stability of potential compound binding. From the computational results, two novel natural coumarins compounds (ZINC12296427 and ZINC12389251) from the ZINC database were found binding to PDKs with favorable interaction energy and predicted to be non-toxic. Our study provide valuable information of PDK-coumarins binding mechanisms in PDK inhibitor-based drug discovery. PMID:26959013
Computational Study on New Natural Compound Inhibitors of Pyruvate Dehydrogenase Kinases.
Zhou, Xiaoli; Yu, Shanshan; Su, Jing; Sun, Liankun
2016-03-04
Pyruvate dehydrogenase kinases (PDKs) are key enzymes in glucose metabolism, negatively regulating pyruvate dehyrogenase complex (PDC) activity through phosphorylation. Inhibiting PDKs could upregulate PDC activity and drive cells into more aerobic metabolism. Therefore, PDKs are potential targets for metabolism related diseases, such as cancers and diabetes. In this study, a series of computer-aided virtual screening techniques were utilized to discover potential inhibitors of PDKs. Structure-based screening using Libdock was carried out following by ADME (adsorption, distribution, metabolism, excretion) and toxicity prediction. Molecular docking was used to analyze the binding mechanism between these compounds and PDKs. Molecular dynamic simulation was utilized to confirm the stability of potential compound binding. From the computational results, two novel natural coumarins compounds (ZINC12296427 and ZINC12389251) from the ZINC database were found binding to PDKs with favorable interaction energy and predicted to be non-toxic. Our study provide valuable information of PDK-coumarins binding mechanisms in PDK inhibitor-based drug discovery.
Gill, Samuel C; Lim, Nathan M; Grinaway, Patrick B; Rustenburg, Ariën S; Fass, Josh; Ross, Gregory A; Chodera, John D; Mobley, David L
2018-05-31
Accurately predicting protein-ligand binding affinities and binding modes is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation time scales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes. In this technique, the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over 2 orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step toward applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding modes of ligands using enhanced sampling (BLUES) package which is freely available on GitHub.
Deng, Nanjie; Flynn, William F; Xia, Junchao; Vijayan, R S K; Zhang, Baofeng; He, Peng; Mentes, Ahmet; Gallicchio, Emilio; Levy, Ronald M
2016-09-01
We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90. The present D3R challenge was built around experimental datasets involving Heat shock protein (Hsp) 90, an ATP-dependent molecular chaperone which is an important anticancer drug target. The Hsp90 ATP binding site is known to be a challenging target for accurate calculations of ligand binding affinities because of the ligand-dependent conformational changes in the binding site, the presence of ordered waters and the broad chemical diversity of ligands that can bind at this site. Our primary focus here is to distinguish binders from nonbinders. Large scale absolute binding free energy calculations that cover over 3000 protein-ligand complexes were performed using the BEDAM method starting from docked structures generated by Glide docking. Although the ligand dataset in this study resembles an intermediate to late stage lead optimization project while the BEDAM method is mainly developed for early stage virtual screening of hit molecules, the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target. Results show that, using a statistical mechanics based free energy method like BEDAM starting from docked poses offers better enrichment than classical docking scoring functions and rescoring methods like Prime MM-GBSA for the Hsp90 data set in this blind challenge. Importantly, among the three methods tested here, only the mean value of the BEDAM binding free energy scores is able to separate the large group of binders from the small group of nonbinders with a gap of 2.4 kcal/mol. None of the three methods that we have tested provided accurate ranking of the affinities of the 147 active compounds. We discuss the possible sources of errors in the binding free energy calculations. The study suggests that BEDAM can be used strategically to discriminate binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity.
NASA Astrophysics Data System (ADS)
Deng, Nanjie; Flynn, William F.; Xia, Junchao; Vijayan, R. S. K.; Zhang, Baofeng; He, Peng; Mentes, Ahmet; Gallicchio, Emilio; Levy, Ronald M.
2016-09-01
We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90. The present D3R challenge was built around experimental datasets involving Heat shock protein (Hsp) 90, an ATP-dependent molecular chaperone which is an important anticancer drug target. The Hsp90 ATP binding site is known to be a challenging target for accurate calculations of ligand binding affinities because of the ligand-dependent conformational changes in the binding site, the presence of ordered waters and the broad chemical diversity of ligands that can bind at this site. Our primary focus here is to distinguish binders from nonbinders. Large scale absolute binding free energy calculations that cover over 3000 protein-ligand complexes were performed using the BEDAM method starting from docked structures generated by Glide docking. Although the ligand dataset in this study resembles an intermediate to late stage lead optimization project while the BEDAM method is mainly developed for early stage virtual screening of hit molecules, the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target. Results show that, using a statistical mechanics based free energy method like BEDAM starting from docked poses offers better enrichment than classical docking scoring functions and rescoring methods like Prime MM-GBSA for the Hsp90 data set in this blind challenge. Importantly, among the three methods tested here, only the mean value of the BEDAM binding free energy scores is able to separate the large group of binders from the small group of nonbinders with a gap of 2.4 kcal/mol. None of the three methods that we have tested provided accurate ranking of the affinities of the 147 active compounds. We discuss the possible sources of errors in the binding free energy calculations. The study suggests that BEDAM can be used strategically to discriminate binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity.
Mechanical work makes important contributions to surface chemistry at steps.
Francis, M F; Curtin, W A
2015-02-13
The effect of mechanical strain on the binding energy of adsorbates to late transition metals is believed to be entirely controlled by electronic factors, with tensile stress inducing stronger binding. Here we show, via computation, that mechanical strain of late transition metals can modify binding at stepped surfaces opposite to well-established trends on flat surfaces. The mechanism driving the trend is mechanical, arising from the relaxation of stored mechanical energy. The mechanical energy change can be larger than, and of opposite sign than, the energy changes due to electronic effects and leads to a violation of trends predicted by the widely accepted electronic 'd-band' model. This trend has a direct impact on catalytic activity, which is demonstrated here for methanation, where biaxial tension is predicted to shift the activity of nickel significantly, reaching the peak of the volcano plot and comparable to cobalt and ruthenium.
Kumar, Akhil; Srivastava, Gaurava; Srivastava, Swati; Verma, Seema; Negi, Arvind S; Sharma, Ashok
2017-08-01
BACE-1 and GSK-3β are potential therapeutic drug targets for Alzheimer's disease. Recently, both the targets received attention for designing dual inhibitors for Alzheimer's disease. Until now, only two-scaffold triazinone and curcumin have been reported as BACE-1 and GSK-3β dual inhibitors. Docking, molecular dynamics, clustering, binding energy, and network analysis of triazinone derivatives with BACE-1 and GSK-3β was performed to get molecular insight into the first reported dual inhibitor. Further, we designed and evaluated a naphthofuran series for its ability to inhibit BACE-1 and GSK-3β with the computational approaches. Docking study of naphthofuran series showed a good binding affinity towards both the targets. Molecular dynamics, binding energy, and network analysis were performed to compare their binding with the targets and amino acids responsible for binding. Naphthofuran series derivatives showed good interaction within the active site residues of both of the targets. Hydrogen bond occupancy and binding energy suggested strong binding with the targets. Dual-inhibitor binding was mostly governed by the hydrophobic interactions for both of the targets. Per residue energy decomposition and network analysis identified the key residues involved in the binding and inhibiting BACE-1 and GSK-3β. The results indicated that naphthofuran series derivative 11 may be a promising first-in-class dual inhibitor against BACE-1 and GSK-3β. This naphthofuran series may be further explored to design better dual inhibitors. Graphical abstract Naphthofuran derivative as a dual inhibitor for BACE-1 and GSK-3β.
A method for fast energy estimation and visualization of protein-ligand interaction
NASA Astrophysics Data System (ADS)
Tomioka, Nobuo; Itai, Akiko; Iitaka, Yoichi
1987-10-01
A new computational and graphical method for facilitating ligand-protein docking studies is developed on a three-dimensional computer graphics display. Various physical and chemical properties inside the ligand binding pocket of a receptor protein, whose structure is elucidated by X-ray crystal analysis, are calculated on three-dimensional grid points and are stored in advance. By utilizing those tabulated data, it is possible to estimate the non-bonded and electrostatic interaction energy and the number of possible hydrogen bonds between protein and ligand molecules in real time during an interactive docking operation. The method also provides a comprehensive visualization of the local environment inside the binding pocket. With this method, it becomes easier to find a roughly stable geometry of ligand molecules, and one can therefore make a rapid survey of the binding capability of many drug candidates. The method will be useful for drug design as well as for the examination of protein-ligand interactions.
GMXPBSA 2.1: A GROMACS tool to perform MM/PBSA and computational alanine scanning
NASA Astrophysics Data System (ADS)
Paissoni, C.; Spiliotopoulos, D.; Musco, G.; Spitaleri, A.
2015-01-01
GMXPBSA 2.1 is a user-friendly suite of Bash/Perl scripts for streamlining MM/PBSA calculations on structural ensembles derived from GROMACS trajectories, to automatically calculate binding free energies for protein-protein or ligand-protein complexes [R.T. Bradshaw et al., Protein Eng. Des. Sel. 24 (2011) 197-207]. GMXPBSA 2.1 is flexible and can easily be customized to specific needs and it is an improvement of the previous GMXPBSA 2.0 [C. Paissoni et al., Comput. Phys. Commun. (2014), 185, 2920-2929]. Additionally, it performs computational alanine scanning (CAS) to study the effects of ligand and/or receptor alanine mutations on the free energy of binding. Calculations require only for protein-protein or protein-ligand MD simulations. GMXPBSA 2.1 performs different comparative analyses, including a posteriori generation of alanine mutants of the wild-type complex, calculation of the binding free energy values of the mutant complexes and comparison of the results with the wild-type system. Moreover, it compares the binding free energy of different complex trajectories, allowing the study of the effects of non-alanine mutations, post-translational modifications or unnatural amino acids on the binding free energy of the system under investigation. Finally, it can calculate and rank relative affinity to the same receptor utilizing MD simulations of proteins in complex with different ligands. In order to dissect the different MM/PBSA energy contributions, including molecular mechanic (MM), electrostatic contribution to solvation (PB) and nonpolar contribution to solvation (SA), the tool combines two freely available programs: the MD simulations software GROMACS [S. Pronk et al., Bioinformatics 29 (2013) 845-854] and the Poisson-Boltzmann equation solver APBS [N.A. Baker et al., Proc. Natl. Acad. Sci. U.S.A 98 (2001) 10037-10041]. All the calculations can be performed in single or distributed automatic fashion on a cluster facility in order to increase the calculation by dividing frames across the available processors. This new version with respect to our previously published GMXPBSA 2.0 fixes some problem and allows additional kind of calculations, such as CAS on single protein in order to individuate the hot-spots, more custom options to perform APBS calculations, improvements of speed calculation of APBS (precF set to 0), possibility to work with multichain systems (see Summary of revisions for more details). The program is freely available under the GPL license.
Fang, Lei; Zhang, Huai; Cui, Wei; Ji, Mingjun
2008-10-01
Bidentate inhibitors of protein tyrosine phosphatase 1B (PTP1B) are considered as a group of ideal inhibitors with high binding potential and high selectivity in treating type II diabetes. In this paper, the binding models of five bidentate inhibitors to PTP1B, TCPTP, and SHP-2 were investigated and compared by using molecular dynamics (MD) simulations and free energy calculations. The binding free energies were computed using the Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) methodology. The calculation results show that the predicted free energies of the complexes are well consistent with the experimental data. The Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) free energy decomposition analysis indicates that the residues ARG24, ARG254, and GLN262 in the second binding site of PTP1B are essential for the high selectivity of inhibitors. Furthermore, the residue PHE182 close to the active site is also important for the selectivity and the binding affinity of the inhibitors. According to our analysis, it can be concluded that in most cases the polarity of the portion of the inhibitor that binds to the second binding site of the protein is positive to the affinity of the inhibitors while negative to the selectivity of the inhibitors. We expect that the information we obtained here can help to develop potential PTP1B inhibitors with more promising specificity.
Yan, Chunli; Xiu, Zhilong; Li, Xiaohui; Li, Shenmin; Hao, Ce; Teng, Hu
2008-10-01
Histone deacetylases (HDACs) play an important role in gene transcription, and inhibitors of HDACs can induce cell differentiation and suppress cell proliferation in tumor cells. Histone deacetylase1 (HDAC1) binds suberanilohydroxamic acid (SAHA) and 7-phenyl-2, 4, 6-hepta-trienoyl hydroxamic acid (CG-1521) with moderately low affinity (DeltaG = -8.6 and -7.8 kcal mol(-1)). The structurally related (E)-2-(3-(3-(hydroxyamino)-3-oxoprop-1-enyl)phenyl)-N(1),N(3)-diphenylmalonamide (SK-683), a Trichostatin A (TSA)-like HDAC1 inhibitor, and TSA are bound to the HDAC1 with -12.3 and -10.3 kcal mol(-1) of DeltaG, higher binding free energies than SAHA and CG-1521. Histone deacetylase-like protein (HDLP), an HDAC homologue, shows a 35.2% sequence identity of HDLP and human HDAC1. Molecular dynamics simulation and the molecular mechanics/generalized-Born surface area (MM-GBSA) free energy calculations were applied to investigate the factors responsible for the relatively activity of these four inhibitors to HDLP. In addition, computational alanine scanning of the binding site residues was carried out to determine the contribution components from van der Waals, electrostatic interaction, nonpolar and polar energy of solvation as well as the effects of backbones and side-chains with the MM-GBSA method. MM-GBSA methods reproduced the experimental relative affinities of the four inhibitors in good agreement (R(2) = 0.996) between experimental and computed binding energies. The MM-GBSA calculations showed that, the number of hydrogen bonds formed between the HDLP and inhibitors, which varied in the system studied, and electrostatic interactions determined the magnitude of the free energies for HDLP-inhibitor interactions. The MM-GBSA calculations revealed that the binding of HDLP to these four hydroxamic acid inhibitors is mainly driven by van der Waals/nonpolar interactions. This study can be a guide for the optimization of HDAC inhibitors and future design of new therapeutic agents for the treatment of cancer.
Tzoupis, Haralambos; Leonis, Georgios; Avramopoulos, Aggelos; Reis, Heribert; Czyżnikowska, Żaneta; Zerva, Sofia; Vergadou, Niki; Peristeras, Loukas D; Papavasileiou, Konstantinos D; Alexis, Michael N; Mavromoustakos, Thomas; Papadopoulos, Manthos G
2015-11-01
We investigate the binding mechanism in renin complexes, involving three drugs (remikiren, zankiren and enalkiren) and one lead compound, which was selected after screening the ZINC database. For this purpose, we used ab initio methods (the effective fragment potential, the variational perturbation theory, the energy decomposition analysis, the atoms-in-molecules), docking, molecular dynamics, and the MM-PBSA method. A biological assay for the lead compound has been performed to validate the theoretical findings. Importantly, binding free energy calculations for the three drug complexes are within 3 kcal/mol of the experimental values, thus further justifying our computational protocol, which has been validated through previous studies on 11 drug-protein systems. The main elements of the discovered mechanism are: (i) minor changes are induced to renin upon drug binding, (ii) the three drugs form an extensive network of hydrogen bonds with renin, whilst the lead compound presented diminished interactions, (iii) ligand binding in all complexes is driven by favorable van der Waals interactions and the nonpolar contribution to solvation, while the lead compound is associated with diminished van der Waals interactions compared to the drug-bound forms of renin, and (iv) the environment (H2O/Na(+)) has a small effect on the renin-remikiren interaction. Copyright © 2015 Elsevier Inc. All rights reserved.
Virtual screening using molecular simulations.
Yang, Tianyi; Wu, Johnny C; Yan, Chunli; Wang, Yuanfeng; Luo, Ray; Gonzales, Michael B; Dalby, Kevin N; Ren, Pengyu
2011-06-01
Effective virtual screening relies on our ability to make accurate prediction of protein-ligand binding, which remains a great challenge. In this work, utilizing the molecular-mechanics Poisson-Boltzmann (or Generalized Born) surface area approach, we have evaluated the binding affinity of a set of 156 ligands to seven families of proteins, trypsin β, thrombin α, cyclin-dependent kinase (CDK), cAMP-dependent kinase (PKA), urokinase-type plasminogen activator, β-glucosidase A, and coagulation factor Xa. The effect of protein dielectric constant in the implicit-solvent model on the binding free energy calculation is shown to be important. The statistical correlations between the binding energy calculated from the implicit-solvent approach and experimental free energy are in the range of 0.56-0.79 across all the families. This performance is better than that of typical docking programs especially given that the latter is directly trained using known binding data whereas the molecular mechanics is based on general physical parameters. Estimation of entropic contribution remains the barrier to accurate free energy calculation. We show that the traditional rigid rotor harmonic oscillator approximation is unable to improve the binding free energy prediction. Inclusion of conformational restriction seems to be promising but requires further investigation. On the other hand, our preliminary study suggests that implicit-solvent based alchemical perturbation, which offers explicit sampling of configuration entropy, can be a viable approach to significantly improve the prediction of binding free energy. Overall, the molecular mechanics approach has the potential for medium to high-throughput computational drug discovery. Copyright © 2011 Wiley-Liss, Inc.
Chen, Jianzhong; Yang, Maoyou; Hu, Guodong; Shi, Shuhua; Yi, Changhong; Zhang, Qinggang
2009-10-01
The molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method combined with molecular dynamics (MD) simulations were used to investigate the functional role of protonation in human immunodeficiency virus type 1 (HIV-1) protease complexed with the inhibitor BEA369. Our results demonstrate that protonation of two aspartic acids (Asp25/Asp25') has a strong influence on the dynamics behavior of the complex, the binding free energy of BEA369, and inhibitor-residue interactions. Relative binding free energies calculated using the MM-PBSA method show that protonation of Asp25 results in the strongest binding of BEA369 to HIV-1 protease. Inhibitor-residue interactions computed by the theory of free energy decomposition also indicate that protonation of Asp25 has the most favorable effect on binding of BEA369. In addition, hydrogen-bond analysis based on the trajectories of the MD simulations shows that protonation of Asp25 strongly influences the water-mediated link of a conserved water molecule, Wat301. We expect that the results of this study will contribute significantly to binding calculations for BEA369, and to the design of high affinity inhibitors.
Hou, Tingjun; Wang, Junmei; Li, Youyong; Wang, Wei
2011-01-24
The Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) and the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) methods calculate binding free energies for macromolecules by combining molecular mechanics calculations and continuum solvation models. To systematically evaluate the performance of these methods, we report here an extensive study of 59 ligands interacting with six different proteins. First, we explored the effects of the length of the molecular dynamics (MD) simulation, ranging from 400 to 4800 ps, and the solute dielectric constant (1, 2, or 4) on the binding free energies predicted by MM/PBSA. The following three important conclusions could be observed: (1) MD simulation length has an obvious impact on the predictions, and longer MD simulation is not always necessary to achieve better predictions. (2) The predictions are quite sensitive to the solute dielectric constant, and this parameter should be carefully determined according to the characteristics of the protein/ligand binding interface. (3) Conformational entropy often show large fluctuations in MD trajectories, and a large number of snapshots are necessary to achieve stable predictions. Next, we evaluated the accuracy of the binding free energies calculated by three Generalized Born (GB) models. We found that the GB model developed by Onufriev and Case was the most successful model in ranking the binding affinities of the studied inhibitors. Finally, we evaluated the performance of MM/GBSA and MM/PBSA in predicting binding free energies. Our results showed that MM/PBSA performed better in calculating absolute, but not necessarily relative, binding free energies than MM/GBSA. Considering its computational efficiency, MM/GBSA can serve as a powerful tool in drug design, where correct ranking of inhibitors is often emphasized.
Calculation of absolute protein-ligand binding free energy using distributed replica sampling.
Rodinger, Tomas; Howell, P Lynne; Pomès, Régis
2008-10-21
Distributed replica sampling [T. Rodinger et al., J. Chem. Theory Comput. 2, 725 (2006)] is a simple and general scheme for Boltzmann sampling of conformational space by computer simulation in which multiple replicas of the system undergo a random walk in reaction coordinate or temperature space. Individual replicas are linked through a generalized Hamiltonian containing an extra potential energy term or bias which depends on the distribution of all replicas, thus enforcing the desired sampling distribution along the coordinate or parameter of interest regardless of free energy barriers. In contrast to replica exchange methods, efficient implementation of the algorithm does not require synchronicity of the individual simulations. The algorithm is inherently suited for large-scale simulations using shared or heterogeneous computing platforms such as a distributed network. In this work, we build on our original algorithm by introducing Boltzmann-weighted jumping, which allows moves of a larger magnitude and thus enhances sampling efficiency along the reaction coordinate. The approach is demonstrated using a realistic and biologically relevant application; we calculate the standard binding free energy of benzene to the L99A mutant of T4 lysozyme. Distributed replica sampling is used in conjunction with thermodynamic integration to compute the potential of mean force for extracting the ligand from protein and solvent along a nonphysical spatial coordinate. Dynamic treatment of the reaction coordinate leads to faster statistical convergence of the potential of mean force than a conventional static coordinate, which suffers from slow transitions on a rugged potential energy surface.
Calculation of absolute protein-ligand binding free energy using distributed replica sampling
NASA Astrophysics Data System (ADS)
Rodinger, Tomas; Howell, P. Lynne; Pomès, Régis
2008-10-01
Distributed replica sampling [T. Rodinger et al., J. Chem. Theory Comput. 2, 725 (2006)] is a simple and general scheme for Boltzmann sampling of conformational space by computer simulation in which multiple replicas of the system undergo a random walk in reaction coordinate or temperature space. Individual replicas are linked through a generalized Hamiltonian containing an extra potential energy term or bias which depends on the distribution of all replicas, thus enforcing the desired sampling distribution along the coordinate or parameter of interest regardless of free energy barriers. In contrast to replica exchange methods, efficient implementation of the algorithm does not require synchronicity of the individual simulations. The algorithm is inherently suited for large-scale simulations using shared or heterogeneous computing platforms such as a distributed network. In this work, we build on our original algorithm by introducing Boltzmann-weighted jumping, which allows moves of a larger magnitude and thus enhances sampling efficiency along the reaction coordinate. The approach is demonstrated using a realistic and biologically relevant application; we calculate the standard binding free energy of benzene to the L99A mutant of T4 lysozyme. Distributed replica sampling is used in conjunction with thermodynamic integration to compute the potential of mean force for extracting the ligand from protein and solvent along a nonphysical spatial coordinate. Dynamic treatment of the reaction coordinate leads to faster statistical convergence of the potential of mean force than a conventional static coordinate, which suffers from slow transitions on a rugged potential energy surface.
Discrimination between olfactory receptor agonists and non-agonists.
Topin, Jérémie; de March, Claire A; Charlier, Landry; Ronin, Catherine; Antonczak, Serge; Golebiowski, Jérôme
2014-08-11
A joint approach combining free-energy calculations and calcium-imaging assays on the broadly tuned human 1G1 olfactory receptor is reported. The free energy of binding of ten odorants was computed by means of molecular-dynamics simulations. This state function allows separating the experimentally determined eight agonists from the two non-agonists. This study constitutes a proof-of-principle for the computational deorphanization of olfactory receptors. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
A computational study of Na behavior on graphene
NASA Astrophysics Data System (ADS)
Malyi, Oleksandr I.; Sopiha, Kostiantyn; Kulish, Vadym V.; Tan, Teck L.; Manzhos, Sergei; Persson, Clas
2015-04-01
We present the first ab initio and molecular dynamics study of Na adsorption and diffusion on ideal graphene that considers Na-Na interaction and dispersion forces. From density functional theory (DFT) calculations using the generalized gradient approximation (GGA), the binding energy (vs. the vacuum reference state) of -0.75 eV is higher than the cohesive energy of Na metal (E
Panel, Nicolas; Sun, Young Joo; Fuentes, Ernesto J; Simonson, Thomas
2017-01-01
PDZ domains generally bind short amino acid sequences at the C-terminus of target proteins, and short peptides can be used as inhibitors or model ligands. Here, we used experimental binding assays and molecular dynamics simulations to characterize 51 complexes involving the Tiam1 PDZ domain and to test the performance of a semi-empirical free energy function. The free energy function combined a Poisson-Boltzmann (PB) continuum electrostatic term, a van der Waals interaction energy, and a surface area term. Each term was empirically weighted, giving a Linear Interaction Energy or "PB/LIE" free energy. The model yielded a mean unsigned deviation of 0.43 kcal/mol and a Pearson correlation of 0.64 between experimental and computed free energies, which was superior to a Null model that assumes all complexes have the same affinity. Analyses of the models support several experimental observations that indicate the orientation of the α 2 helix is a critical determinant for peptide specificity. The models were also used to predict binding free energies for nine new variants, corresponding to point mutants of the Syndecan1 and Caspr4 peptides. The predictions did not reveal improved binding; however, they suggest that an unnatural amino acid could be used to increase protease resistance and peptide lifetimes in vivo . The overall performance of the model should allow its use in the design of new PDZ ligands in the future.
Panel, Nicolas; Sun, Young Joo; Fuentes, Ernesto J.; Simonson, Thomas
2017-01-01
PDZ domains generally bind short amino acid sequences at the C-terminus of target proteins, and short peptides can be used as inhibitors or model ligands. Here, we used experimental binding assays and molecular dynamics simulations to characterize 51 complexes involving the Tiam1 PDZ domain and to test the performance of a semi-empirical free energy function. The free energy function combined a Poisson-Boltzmann (PB) continuum electrostatic term, a van der Waals interaction energy, and a surface area term. Each term was empirically weighted, giving a Linear Interaction Energy or “PB/LIE” free energy. The model yielded a mean unsigned deviation of 0.43 kcal/mol and a Pearson correlation of 0.64 between experimental and computed free energies, which was superior to a Null model that assumes all complexes have the same affinity. Analyses of the models support several experimental observations that indicate the orientation of the α2 helix is a critical determinant for peptide specificity. The models were also used to predict binding free energies for nine new variants, corresponding to point mutants of the Syndecan1 and Caspr4 peptides. The predictions did not reveal improved binding; however, they suggest that an unnatural amino acid could be used to increase protease resistance and peptide lifetimes in vivo. The overall performance of the model should allow its use in the design of new PDZ ligands in the future. PMID:29018806
Sharifi, Tayebeh; Ghayeb, Yousef
2018-05-01
Peroxisome proliferator-activated receptors (PPARs) compose a family of nuclear receptors, PPARα, PPARβ, and PPARγ, which mediate the effects of lipidic ligands at the transcriptional level. Among these, the PPARγ has been known to regulate adipocyte differentiation, fatty acid storage and glucose metabolism, and is a target of antidiabetic drugs. In this work, the interactions between PPARγ and its six known antagonists were investigated using computational methods such as molecular docking, molecular dynamics (MD) simulations, and the hybrid quantum mechanics/molecular mechanics (QM/MM). The binding energies evaluated by molecular docking varied between -22.59 and -35.15 kJ mol - 1 . In addition, MD simulations were performed to investigate the binding modes and PPARγ conformational changes upon binding of antagonists. Analysis of the root-mean-square fluctuations (RMSF) of backbone atoms shows that H3 of PPARγ has a higher mobility in the absence of antagonists and moderate conformational changes were observed. The interaction energies between antagonists and each PPARγ residue involved in the interactions were studied by QM/MM calculations. These calculations reveal that antagonists with different structures show different interaction energies with the same residue of PPARγ. Therefore, it can be concluded that the key residues vary depending on the structure of the ligand, which binds to PPARγ.
Tshabalala, Thabiso N; Tomescu, Mihai-Silviu; Prior, Allan; Balakrishnan, Vijayakumar; Sayed, Yasien; Dirr, Heini W; Achilonu, Ikechukwu
2016-12-01
The energetics of ligand binding to human eukaryotic elongation factor 1 gamma (heEF1γ) was investigated using reduced glutathione (GSH), oxidised glutathione (GSSG), glutathione sulfonate and S-hexylglutathione as ligands. The experiments were conducted using isothermal titration calorimetry, and the findings were supported using computational studies. The data show that the binding of these ligands to heEF1γ is enthalpically favourable and entropically driven (except for the binding of GSSG). The full length heEF1γ binds GSSG with lower affinity (K d = 115 μM), with more hydrogen-bond contacts (ΔH = -73.8 kJ/mol) and unfavourable entropy (-TΔS = 51.7 kJ/mol) compared to the glutathione transferase-like N-terminus domain of heEF1γ, which did not show preference to any specific ligand. Computational free binding energy calculations from the 10 ligand poses show that GSSG and GSH consistently bind heEF1γ, and that both ligands bind at the same site with a folded bioactive conformation. This study reveals the possibility that heEF1γ is a glutathione-binding protein.
Protein surface roughness accounts for binding free energy of Plasmepsin II-ligand complexes.
Valdés-Tresanco, Mario E; Valdés-Tresanco, Mario S; Valiente, Pedro A; Cocho, Germinal; Mansilla, Ricardo; Nieto-Villar, J M
2018-01-01
The calculation of absolute binding affinities for protein-inhibitor complexes remains as one of the main challenges in computational structure-based ligand design. The present work explored the calculations of surface fractal dimension (as a measure of surface roughness) and the relationship with experimental binding free energies of Plasmepsin II complexes. Plasmepsin II is an attractive target for novel therapeutic compounds to treat malaria. However, the structural flexibility of this enzyme is a drawback when searching for specific inhibitors. Concerning that, we performed separate explicitly solvated molecular dynamics simulations using the available high-resolution crystal structures of different Plasmepsin II complexes. Molecular dynamics simulations allowed a better approximation to systems dynamics and, therefore, a more reliable estimation of surface roughness. This constitutes a novel approximation in order to obtain more realistic values of fractal dimension, because previous works considered only x-ray structures. Binding site fractal dimension was calculated considering the ensemble of structures generated at different simulation times. A linear relationship between binding site fractal dimension and experimental binding free energies of the complexes was observed within 20 ns. Previous studies of the subject did not uncover this relationship. Regression model, coined FD model, was built to estimate binding free energies from binding site fractal dimension values. Leave-one-out cross-validation showed that our model reproduced accurately the absolute binding free energies for our training set (R 2 = 0.76; <|error|> =0.55 kcal/mol; SD error = 0.19 kcal/mol). The fact that such a simple model may be applied raises some questions that are addressed in the article. Copyright © 2017 John Wiley & Sons, Ltd.
Relationship between Hot Spot Residues and Ligand Binding Hot Spots in Protein-Protein Interfaces
Zerbe, Brandon S.; Hall, David R.
2013-01-01
In the context of protein-protein interactions, the term “hot spot” refers to a residue or cluster of residues that makes a major contribution to the binding free energy, as determined by alanine scanning mutagenesis. In contrast, in pharmaceutical research a hot spot is a site on a target protein that has high propensity for ligand binding and hence is potentially important for drug discovery. Here we examine the relationship between these two hot spot concepts by comparing alanine scanning data for a set of 15 proteins with results from mapping the protein surfaces for sites that can bind fragment-sized small molecules. We find the two types of hot spots are largely complementary; the residues protruding into hot spot regions identified by computational mapping or experimental fragment screening are almost always themselves hot spot residues as defined by alanine scanning experiments. Conversely, a residue that is found by alanine scanning to contribute little to binding rarely interacts with hot spot regions on the partner protein identified by fragment mapping. In spite of the strong correlation between the two hot spot concepts, they fundamentally differ, however. In particular, while identification of a hot spot by alanine scanning establishes the potential to generate substantial interaction energy with a binding partner, there are additional topological requirements to be a hot spot for small molecule binding. Hence, only a minority of hot spots identified by alanine scanning represent sites that are potentially useful for small inhibitor binding, and it is this subset that is identified by experimental or computational fragment screening. PMID:22770357
Relationship between hot spot residues and ligand binding hot spots in protein-protein interfaces.
Zerbe, Brandon S; Hall, David R; Vajda, Sandor; Whitty, Adrian; Kozakov, Dima
2012-08-27
In the context of protein-protein interactions, the term "hot spot" refers to a residue or cluster of residues that makes a major contribution to the binding free energy, as determined by alanine scanning mutagenesis. In contrast, in pharmaceutical research, a hot spot is a site on a target protein that has high propensity for ligand binding and hence is potentially important for drug discovery. Here we examine the relationship between these two hot spot concepts by comparing alanine scanning data for a set of 15 proteins with results from mapping the protein surfaces for sites that can bind fragment-sized small molecules. We find the two types of hot spots are largely complementary; the residues protruding into hot spot regions identified by computational mapping or experimental fragment screening are almost always themselves hot spot residues as defined by alanine scanning experiments. Conversely, a residue that is found by alanine scanning to contribute little to binding rarely interacts with hot spot regions on the partner protein identified by fragment mapping. In spite of the strong correlation between the two hot spot concepts, they fundamentally differ, however. In particular, while identification of a hot spot by alanine scanning establishes the potential to generate substantial interaction energy with a binding partner, there are additional topological requirements to be a hot spot for small molecule binding. Hence, only a minority of hot spots identified by alanine scanning represent sites that are potentially useful for small inhibitor binding, and it is this subset that is identified by experimental or computational fragment screening.
Crespo, Alejandro; Rodriguez-Granillo, Agustina; Lim, Victoria T
2017-01-01
The development and application of quantum mechanics (QM) methodologies in computer- aided drug design have flourished in the last 10 years. Despite the natural advantage of QM methods to predict binding affinities with a higher level of theory than those methods based on molecular mechanics (MM), there are only a few examples where diverse sets of protein-ligand targets have been evaluated simultaneously. In this work, we review recent advances in QM docking and scoring for those cases in which a systematic analysis has been performed. In addition, we introduce and validate a simplified QM/MM expression to compute protein-ligand binding energies. Overall, QMbased scoring functions are generally better to predict ligand affinities than those based on classical mechanics. However, the agreement between experimental activities and calculated binding energies is highly dependent on the specific chemical series considered. The advantage of more accurate QM methods is evident in cases where charge transfer and polarization effects are important, for example when metals are involved in the binding process or when dispersion forces play a significant role as in the case of hydrophobic or stacking interactions. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Higo, Junichi; Umezawa, Koji
2014-01-01
We introduce computational studies on intrinsically disordered proteins (IDPs). Especially, we present our multicanonical molecular dynamics (McMD) simulations of two IDP-partner systems: NRSF-mSin3 and pKID-KIX. McMD is one of enhanced conformational sampling methods useful for conformational sampling of biomolecular systems. IDP adopts a specific tertiary structure upon binding to its partner molecule, although it is unstructured in the unbound state (i.e. the free state). This IDP-specific property is called "coupled folding and binding". The McMD simulation treats the biomolecules with an all-atom model immersed in an explicit solvent. In the initial configuration of simulation, IDP and its partner molecules are set to be distant from each other, and the IDP conformation is disordered. The computationally obtained free-energy landscape for coupled folding and binding has shown that native- and non-native-complex clusters distribute complicatedly in the conformational space. The all-atom simulation suggests that both of induced-folding and population-selection are coupled complicatedly in the coupled folding and binding. Further analyses have exemplified that the conformational fluctuations (dynamical flexibility) in the bound and unbound states are essentially important to characterize IDP functioning.
NASA Astrophysics Data System (ADS)
Feddi, E.; El-Yadri, M.; Dujardin, F.; Restrepo, R. L.; Duque, C. A.
2017-02-01
In this study, we have investigated the confined donor impurity in a hollow cylindrical-shell quantum dot. The charges are assumed to be completely confined to the interior of the shell with rigid walls. Within the framework of the effective-mass approximation and by using a simple variational approach, we have computed the donor binding energy as a function of the shell sizes in order to study the behavior of the electron-impurity attraction for a very small thickness. Our results show that the binding energy of a donor impurity placed at the center of cylindrical core/shell dots depends strongly on the shell size. The binding energy increases when the shell-wideness becomes smaller and shows the same behavior as in a simple cylindrical quantum dot. A special case has been studied, which corresponds to the ratio between the inner and outer radii near to one (a/b → 1) for which our model gives a non-significant behavior of the impurity binding energy. This fact implies the existence of a critical value (a/b) for which the binding energy of the donor impurity tends to the limit value of 4 effective Rydbergs as in a 2D quantum well. We also analyse the photoionization cross section considering only the in-plane incident radiation polarization. We determine its behavior as a function of photon energy, shell size, and donor position. The measurement of photoionization in such systems would be of great interest to understand the optical properties of carriers in quantum dots.
NASA Astrophysics Data System (ADS)
Fujiwara, Takeo; Nishino, Shinya; Yamamoto, Susumu; Suzuki, Takashi; Ikeda, Minoru; Ohtani, Yasuaki
2018-06-01
A novel tight-binding method is developed, based on the extended Hückel approximation and charge self-consistency, with referring the band structure and the total energy of the local density approximation of the density functional theory. The parameters are so adjusted by computer that the result reproduces the band structure and the total energy, and the algorithm for determining parameters is established. The set of determined parameters is applicable to a variety of crystalline compounds and change of lattice constants, and, in other words, it is transferable. Examples are demonstrated for Si crystals of several crystalline structures varying lattice constants. Since the set of parameters is transferable, the present tight-binding method may be applicable also to molecular dynamics simulations of large-scale systems and long-time dynamical processes.
NASA Astrophysics Data System (ADS)
Pandey, Preeti; Srivastava, Rakesh; Bandyopadhyay, Pradipta
2018-03-01
The relative performance of MM-PBSA and MM-3D-RISM methods to estimate the binding free energy of protein-ligand complexes is investigated by applying these to three proteins (Dihydrofolate Reductase, Catechol-O-methyltransferase, and Stromelysin-1) differing in the number of metal ions they contain. None of the computational methods could distinguish all the ligands based on their calculated binding free energies (as compared to experimental values). The difference between the two comes from both polar and non-polar part of solvation. For charged ligand case, MM-PBSA and MM-3D-RISM give a qualitatively different result for the polar part of solvation.
Machine learning in computational docking.
Khamis, Mohamed A; Gomaa, Walid; Ahmed, Walaa F
2015-03-01
The objective of this paper is to highlight the state-of-the-art machine learning (ML) techniques in computational docking. The use of smart computational methods in the life cycle of drug design is relatively a recent development that has gained much popularity and interest over the last few years. Central to this methodology is the notion of computational docking which is the process of predicting the best pose (orientation + conformation) of a small molecule (drug candidate) when bound to a target larger receptor molecule (protein) in order to form a stable complex molecule. In computational docking, a large number of binding poses are evaluated and ranked using a scoring function. The scoring function is a mathematical predictive model that produces a score that represents the binding free energy, and hence the stability, of the resulting complex molecule. Generally, such a function should produce a set of plausible ligands ranked according to their binding stability along with their binding poses. In more practical terms, an effective scoring function should produce promising drug candidates which can then be synthesized and physically screened using high throughput screening process. Therefore, the key to computer-aided drug design is the design of an efficient highly accurate scoring function (using ML techniques). The methods presented in this paper are specifically based on ML techniques. Despite many traditional techniques have been proposed, the performance was generally poor. Only in the last few years started the application of the ML technology in the design of scoring functions; and the results have been very promising. The ML-based techniques are based on various molecular features extracted from the abundance of protein-ligand information in the public molecular databases, e.g., protein data bank bind (PDBbind). In this paper, we present this paradigm shift elaborating on the main constituent elements of the ML approach to molecular docking along with the state-of-the-art research in this area. For instance, the best random forest (RF)-based scoring function on PDBbind v2007 achieves a Pearson correlation coefficient between the predicted and experimentally determined binding affinities of 0.803 while the best conventional scoring function achieves 0.644. The best RF-based ranking power ranks the ligands correctly based on their experimentally determined binding affinities with accuracy 62.5% and identifies the top binding ligand with accuracy 78.1%. We conclude with open questions and potential future research directions that can be pursued in smart computational docking; using molecular features of different nature (geometrical, energy terms, pharmacophore), advanced ML techniques (e.g., deep learning), combining more than one ML models. Copyright © 2015 Elsevier B.V. All rights reserved.
Capture and quality control mechanisms for ATP binding
Li, Li; Martinis, Susan A.
2013-01-01
The catalytic events in members of the nucleotidylyl transferase superfamily are initiated by a millisecond binding of ATP in the active site. Through metadynamics simulations on a class I aminoacyl-tRNA synthetase (aaRSs), the largest group in the superfamily, we calculate the free energy landscape of ATP selection and binding. Mutagenesis studies and fluorescence spectroscopy validated the identification of the most populated intermediate states. The rapid first binding step involves formation of encounter complexes captured through a fly-casting mechanism that acts up on the triphosphate moiety of ATP. In the slower nucleoside binding step, a conserved histidine in the HxxH motif orients the incoming ATP through base-stacking interactions resulting in a deep minimum in the free energy surface. Mutation of this histidine significantly decreases the binding affinity measured experimentally and computationally. The metadynamics simulations further reveal an intermediate quality control state that the synthetases and most likely other members of the superfamily use to select ATP over other nucleoside triphosphates. PMID:23276298
Capture and quality control mechanisms for adenosine-5'-triphosphate binding.
Li, Li; Martinis, Susan A; Luthey-Schulten, Zaida
2013-04-24
The catalytic events in members of the nucleotidylyl transferase superfamily are initiated by a millisecond binding of ATP in the active site. Through metadynamics simulations on a class I aminoacyl-tRNA synthetase (aaRSs), the largest group in the superfamily, we calculate the free energy landscape of ATP selection and binding. Mutagenesis studies and fluorescence spectroscopy validated the identification of the most populated intermediate states. The rapid first binding step involves formation of encounter complexes captured through a fly casting mechanism that acts upon the triphosphate moiety of ATP. In the slower nucleoside binding step, a conserved histidine in the HxxH motif orients the incoming ATP through base-stacking interactions resulting in a deep minimum in the free energy surface. Mutation of this histidine significantly decreases the binding affinity measured experimentally and computationally. The metadynamics simulations further reveal an intermediate quality control state that the synthetases and most likely other members of the superfamily use to select ATP over other nucleoside triphosphates.
[Computational chemistry in structure-based drug design].
Cao, Ran; Li, Wei; Sun, Han-Zi; Zhou, Yu; Huang, Niu
2013-07-01
Today, the understanding of the sequence and structure of biologically relevant targets is growing rapidly and researchers from many disciplines, physics and computational science in particular, are making significant contributions to modern biology and drug discovery. However, it remains challenging to rationally design small molecular ligands with desired biological characteristics based on the structural information of the drug targets, which demands more accurate calculation of ligand binding free-energy. With the rapid advances in computer power and extensive efforts in algorithm development, physics-based computational chemistry approaches have played more important roles in structure-based drug design. Here we reviewed the newly developed computational chemistry methods in structure-based drug design as well as the elegant applications, including binding-site druggability assessment, large scale virtual screening of chemical database, and lead compound optimization. Importantly, here we address the current bottlenecks and propose practical solutions.
Cloud computing approaches for prediction of ligand binding poses and pathways.
Lawrenz, Morgan; Shukla, Diwakar; Pande, Vijay S
2015-01-22
We describe an innovative protocol for ab initio prediction of ligand crystallographic binding poses and highly effective analysis of large datasets generated for protein-ligand dynamics. We include a procedure for setup and performance of distributed molecular dynamics simulations on cloud computing architectures, a model for efficient analysis of simulation data, and a metric for evaluation of model convergence. We give accurate binding pose predictions for five ligands ranging in affinity from 7 nM to > 200 μM for the immunophilin protein FKBP12, for expedited results in cases where experimental structures are difficult to produce. Our approach goes beyond single, low energy ligand poses to give quantitative kinetic information that can inform protein engineering and ligand design.
Computational Optimization and Characterization of Molecularly Imprinted Polymers
NASA Astrophysics Data System (ADS)
Terracina, Jacob J.
Molecularly imprinted polymers (MIPs) are a class of materials containing sites capable of selectively binding to the imprinted target molecule. Computational chemistry techniques were used to study the effect of different fabrication parameters (the monomer-to-target ratios, pre-polymerization solvent, temperature, and pH) on the formation of the MIP binding sites. Imprinted binding sites were built in silico for the purposes of better characterizing the receptor - ligand interactions. Chiefly, the sites were characterized with respect to their selectivities and the heterogeneity between sites. First, a series of two-step molecular mechanics (MM) and quantum mechanics (QM) computational optimizations of monomer -- target systems was used to determine optimal monomer-to-target ratios for the MIPs. Imidazole- and xanthine-derived target molecules were studied. The investigation included both small-scale models (one-target) and larger scale models (five-targets). The optimal ratios differed between the small and larger scales. For the larger models containing multiple targets, binding-site surface area analysis was used to evaluate the heterogeneity of the sites. The more fully surrounded sites had greater binding energies. Molecular docking was then used to measure the selectivities of the QM-optimized binding sites by comparing the binding energies of the imprinted target to that of a structural analogue. Selectivity was also shown to improve as binding sites become more fully encased by the monomers. For internal sites, docking consistently showed selectivity favoring the molecules that had been imprinted via QM geometry optimizations. The computationally imprinted sites were shown to exhibit size-, shape-, and polarity-based selectivity. This represented a novel approach to investigate the selectivity and heterogeneity of imprinted polymer binding sites, by applying the rapid orientation screening of MM docking to the highly accurate QM-optimized geometries. Next, we sought to computationally construct and investigate binding sites for their enantioselectivity. Again, a two-step MM [special characters removed] QM optimization scheme was used to "computationally imprint" chiral molecules. Using docking techniques, the imprinted binding sites were shown to exhibit an enantioselective preference for the imprinted molecule over its enantiomer. Docking of structurally similar chiral molecules showed that the sites computationally imprinted with R- or S-tBOC-tyrosine were able to differentiate between R- and S-forms of other tyrosine derivatives. The cross-enantioselectivity did not hold for chiral molecules that did not share the tyrosine H-bonding functional group orientations. Further analysis of the individual monomer - target interactions within the binding site led us to conclude that H-bonding functional groups that are located immediately next to the target's chiral center, and therefore spatially fixed relative to the chiral center, will have a stronger contribution to the enantioselectivity of the site than those groups separated from the chiral center by two or more rotatable bonds. These models were the first computationally imprinted binding sites to exhibit this enantioselective preference for the imprinted target molecules. Finally, molecular dynamics (MD) was used to quantify H-bonding interactions between target molecules, monomers, and solvents representative of the pre-polymerization matrix. It was found that both target dimerization and solvent interference decrease the number of monomer - target H-bonds present. Systems were optimized via simulated annealing to create binding sites that were then subjected to molecular docking analysis. Docking showed that the presence of solvent had a detrimental effect on the sensitivity and selectivity of the sites, and that solvents with more H-bonding capabilities were more disruptive to the binding properties of the site. Dynamic simulations also showed that increasing the temperature of the solution can significantly decrease the number of H-bonds formed between the targets and monomers. It is believed that the monomer - target complexes formed within the pre-polymerization matrix are translated into the selective binding cavities formed during polymerization. Elucidating the nature of these interactions in silico improves our understanding of MIPs, ultimately allowing for more optimized sensing materials.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pluharova, Eva; Baer, Marcel D.; Mundy, Christopher J.
2014-07-03
Understanding specific ion effects on proteins remains a considerable challenge. N-methylacetamide serves as a useful proxy for the protein backbone that can be well characterized both experimentally and theoretically. The spectroscopic signatures in the amide I band reflecting the strength of the interaction of alkali cations and alkali earth dications with the carbonyl group remain difficult to assign and controversial to interpret. Herein, we directly compute the IR shifts corresponding to the binding of either sodium or calcium to aqueous N-methylacetamide using ab initio molecular dynamics simulations. We show that the two cations interact with aqueous N-methylacetamide with different affinitiesmore » and in different geometries. Since sodium exhibits a weak interaction with the carbonyl group, the resulting amide I band is similar to an unperturbed carbonyl group undergoing aqueous solvation. In contrast, the stronger calcium binding results in a clear IR shift with respect to N-methylacetamide in pure water. Support from the Czech Ministry of Education (grant LH12001) is gratefully acknowledged. EP thanks the International Max-Planck Research School for support and the Alternative Sponsored Fellowship program at Pacific Northwest National Laboratory (PNNL). PJ acknowledges the Praemium Academie award from the Academy of Sciences. Calculations of the free energy profiles were made possible through generous allocation of computer time from the North-German Supercomputing Alliance (HLRN). Calculations of vibrational spectra were performed in part using the computational resources in the National Energy Research Supercomputing Center (NERSC) at Lawrence Berkeley National Laboratory. This work was supported by National Science Foundation grant CHE-0431312. CJM is supported by the U.S. Department of Energy`s (DOE) Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences. PNNL is operated for the Department of Energy by Battelle. MDB is grateful for the support of the Linus Pauling Distinguished Postdoctoral Fellowship Program at PNNL.« less
Computational Exploration of a Protein Receptor Binding Space with Student Proposed Peptide Ligands
King, Matthew D.; Phillips, Paul; Turner, Matthew W.; Katz, Michael; Lew, Sarah; Bradburn, Sarah; Andersen, Tim; Mcdougal, Owen M.
2017-01-01
Computational molecular docking is a fast and effective in silico method for the analysis of binding between a protein receptor model and a ligand. The visualization and manipulation of protein to ligand binding in three-dimensional space represents a powerful tool in the biochemistry curriculum to enhance student learning. The DockoMatic tutorial described herein provides a framework by which instructors can guide students through a drug screening exercise. Using receptor models derived from readily available protein crystal structures, docking programs have the ability to predict ligand binding properties, such as preferential binding orientations and binding affinities. The use of computational studies can significantly enhance complimentary wet chemical experimentation by providing insight into the important molecular interactions within the system of interest, as well as guide the design of new candidate ligands based on observed binding motifs and energetics. In this laboratory tutorial, the graphical user interface, DockoMatic, facilitates docking job submissions to the docking engine, AutoDock 4.2. The purpose of this exercise is to successfully dock a 17-amino acid peptide, α-conotoxin TxIA, to the acetylcholine binding protein from Aplysia californica-AChBP to determine the most stable binding configuration. Each student will then propose two specific amino acid substitutions of α-conotoxin TxIA to enhance peptide binding affinity, create the mutant in DockoMatic, and perform docking calculations to compare their results with the class. Students will also compare intermolecular forces, binding energy, and geometric orientation of their prepared analog to their initial α-conotoxin TxIA docking results. PMID:26537635
DOE Office of Scientific and Technical Information (OSTI.GOV)
Miliordos, Evangelos; Xantheas, Sotiris S.
2015-06-21
We report MP2 and CCSD(T) binding energies with basis sets up to pentuple zeta quality for the m = 2-6, 8 clusters. Or best CCSD(T)/CBS estimates are -4.99 kcal/mol (dimer), -15.77 kcal/mol (trimer), -27.39 kcal/mol (tetramer), -35.9 ± 0.3 kcal/mol (pentamer), -46.2 ± 0.3 kcal/mol (prism hexamer), -45.9 ± 0.3 kcal/mol (cage hexamer), -45.4 ± 0.3 kcal/mol (book hexamer), -44.3 ± 0.3 kcal/mol (ring hexamer), -73.0 ± 0.5 kcal/mol (D 2d octamer) and -72.9 ± 0.5 kcal/mol (S4 octamer). We have found that the percentage of both the uncorrected (dimer) and BSSE-corrected (dimer CP e) binding energies recovered with respectmore » to the CBS limit falls into a narrow range for each basis set for all clusters and in addition this range was found to decrease upon increasing the basis set. Relatively accurate estimates (within < 0.5%) of the CBS limits can be obtained when using the “ 2/3, 1/3” (for the AVDZ set) or the “½ , ½” (for the AVTZ, AVQZ and AV5Z sets) mixing ratio between dimer e and dimer CPe. Based on those findings we propose an accurate and efficient computational protocol that can be used to estimate accurate binding energies of clusters at the MP2 (for up to 100 molecules) and CCSD(T) (for up to 30 molecules) levels of theory. This work was supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences. Pacific Northwest National Laboratory (PNNL) is a multi program national laboratory operated for DOE by Battelle. This research also used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. AC02-05CH11231.« less
The role of water molecules in computational drug design.
de Beer, Stephanie B A; Vermeulen, Nico P E; Oostenbrink, Chris
2010-01-01
Although water molecules are small and only consist of two different atom types, they play various roles in cellular systems. This review discusses their influence on the binding process between biomacromolecular targets and small molecule ligands and how this influence can be modeled in computational drug design approaches. Both the structure and the thermodynamics of active site waters will be discussed as these influence the binding process significantly. Structurally conserved waters cannot always be determined experimentally and if observed, it is not clear if they will be replaced upon ligand binding, even if sufficient space is available. Methods to predict the presence of water in protein-ligand complexes will be reviewed. Subsequently, we will discuss methods to include water in computational drug research. Either as an additional factor in automated docking experiments, or explicitly in detailed molecular dynamics simulations, the effect of water on the quality of the simulations is significant, but not easily predicted. The most detailed calculations involve estimates of the free energy contribution of water molecules to protein-ligand complexes. These calculations are computationally demanding, but give insight in the versatility and importance of water in ligand binding.
Panda, Dulal; Kunwar, Ambarish
2016-01-01
Tubulin isotypes are found to play an important role in regulating microtubule dynamics. The isotype composition is also thought to contribute in the development of drug resistance as tubulin isotypes show differential binding affinities for various anti-cancer agents. Tubulin isotypes αβII, αβIII and αβIV show differential binding affinity for colchicine. However, the origin of differential binding affinity is not well understood at the molecular level. Here, we investigate the origin of differential binding affinity of a colchicine analogue N-deacetyl-N-(2-mercaptoacetyl)-colchicine (DAMA-colchicine) for human αβII, αβIII and αβIV isotypes, employing sequence analysis, homology modeling, molecular docking, molecular dynamics simulation and MM-GBSA binding free energy calculations. The sequence analysis study shows that the residue compositions are different in the colchicine binding pocket of αβII and αβIII, whereas no such difference is present in αβIV tubulin isotypes. Further, the molecular docking and molecular dynamics simulations results show that residue differences present at the colchicine binding pocket weaken the bonding interactions and the correct binding of DAMA-colchicine at the interface of αβII and αβIII tubulin isotypes. Post molecular dynamics simulation analysis suggests that these residue variations affect the structure and dynamics of αβII and αβIII tubulin isotypes, which in turn affect the binding of DAMA-colchicine. Further, the binding free-energy calculation shows that αβIV tubulin isotype has the highest binding free-energy and αβIII has the lowest binding free-energy for DAMA-colchicine. The order of binding free-energy for DAMA-colchicine is αβIV ≃ αβII >> αβIII. Thus, our computational approaches provide an insight into the effect of residue variations on differential binding of αβII, αβIII and αβIV tubulin isotypes with DAMA-colchicine and may help to design new analogues with higher binding affinities for tubulin isotypes. PMID:27227832
Ligand binding to telomeric G-quadruplex DNA investigated by funnel-metadynamics simulations
Moraca, Federica; Amato, Jussara; Ortuso, Francesco; Artese, Anna; Novellino, Ettore; Alcaro, Stefano; Parrinello, Michele; Limongelli, Vittorio
2017-01-01
G-quadruplexes (G4s) are higher-order DNA structures typically present at promoter regions of genes and telomeres. Here, the G4 formation decreases the replicative DNA at each cell cycle, finally leading to apoptosis. The ability to control this mitotic clock, particularly in cancer cells, is fascinating and passes through a rational understanding of the ligand/G4 interaction. We demonstrate that an accurate description of the ligand/G4 binding mechanism is possible using an innovative free-energy method called funnel-metadynamics (FM), which we have recently developed to investigate ligand/protein interaction. Using FM simulations, we have elucidated the binding mechanism of the anticancer alkaloid berberine to the human telomeric G4 (d[AG3(T2AG3)3]), computing also the binding free-energy landscape. Two ligand binding modes have been identified as the lowest energy states. Furthermore, we have found prebinding sites, which are preparatory to reach the final binding mode. In our simulations, the ions and the water molecules have been explicitly represented and the energetic contribution of the solvent during ligand binding evaluated. Our theoretical results provide an accurate estimate of the absolute ligand/DNA binding free energy (ΔGb0 = −10.3 ± 0.5 kcal/mol) that we validated through steady-state fluorescence binding assays. The good agreement between the theoretical and experimental value demonstrates that FM is a most powerful method to investigate ligand/DNA interaction and can be a useful tool for the rational design also of G4 ligands. PMID:28232513
A Python tool to set up relative free energy calculations in GROMACS.
Klimovich, Pavel V; Mobley, David L
2015-11-01
Free energy calculations based on molecular dynamics (MD) simulations have seen a tremendous growth in the last decade. However, it is still difficult and tedious to set them up in an automated manner, as the majority of the present-day MD simulation packages lack that functionality. Relative free energy calculations are a particular challenge for several reasons, including the problem of finding a common substructure and mapping the transformation to be applied. Here we present a tool, alchemical-setup.py, that automatically generates all the input files needed to perform relative solvation and binding free energy calculations with the MD package GROMACS. When combined with Lead Optimization Mapper (LOMAP; Liu et al. in J Comput Aided Mol Des 27(9):755-770, 2013), recently developed in our group, alchemical-setup.py allows fully automated setup of relative free energy calculations in GROMACS. Taking a graph of the planned calculations and a mapping, both computed by LOMAP, our tool generates the topology and coordinate files needed to perform relative free energy calculations for a given set of molecules, and provides a set of simulation input parameters. The tool was validated by performing relative hydration free energy calculations for a handful of molecules from the SAMPL4 challenge (Mobley et al. in J Comput Aided Mol Des 28(4):135-150, 2014). Good agreement with previously published results and the straightforward way in which free energy calculations can be conducted make alchemical-setup.py a promising tool for automated setup of relative solvation and binding free energy calculations.
Full-potential KKR calculations for vacancies in Al : Screening effect and many-body interactions
NASA Astrophysics Data System (ADS)
Hoshino, T.; Asato, M.; Zeller, R.; Dederichs, P. H.
2004-09-01
We give ab initio calculations for vacancies in Al . The calculations are based on the generalized-gradient approximation in the density-functional theory and employ the all-electron full-potential Korringa-Kohn-Rostoker Green’s function method for point defects, which guarantees the correct embedding of the cluster of point defects in an otherwise perfect crystal. First, we confirm the recent calculated results of Carling [Phys. Rev. Lett. 85, 3862 (2000)], i.e., repulsion of the first-nearest-neighbor (1NN) divacancy in Al , and elucidate quantitatively the micromechanism of repulsion. Using the calculated results for vacancy formation energies and divacancy binding energies in Na , Mg , Al , and Si of face-centered-cubic, we show that the single vacancy in nearly free-electron systems becomes very stable with increasing free-electron density, due to the screening effect, and that the formation of divacancy destroys the stable electron distribution around the single vacancy, resulting in a repulsion of two vacancies on 1NN sites, so that the 1NN divacancy is unstable. Second, we show that the cluster expansion converges rapidly for the binding energies of vacancy agglomerates in Al . The binding energy of 13 vacancies consisting of a central vacancy and its 12 nearest neighbors, is reproduced within the error of 0.002eV per vacancy, if many-body interaction energies up to the four-body terms are taken into account in the cluster expansion, being compared with the average error (>0.1eV) of the glue models which are very often used to provide interatomic potentials for computer simulations. For the cluster expansion of the binding energies of impurities, we get the same convergence as that obtained for vacancies. Thus, the present cluster-expansion approach for the binding energies of agglomerates of vacancies and impurities in Al may provide accurate data to construct the interaction-parameter model for computer simulations which are strongly requested to study the dynamical process in the initial stage of the formation of the so-called Guinier-Preston zones of low-concentrated Al -based alloys such as Al1-cXc ( X=Cu , Zn ; c<0.05 ).
Bu, Lintao; Beckham, Gregg T.; Shirts, Michael R.; Nimlos, Mark R.; Adney, William S.; Himmel, Michael E.; Crowley, Michael F.
2011-01-01
Understanding the enzymatic mechanism that cellulases employ to degrade cellulose is critical to efforts to efficiently utilize plant biomass as a sustainable energy resource. A key component of cellulase action on cellulose is product inhibition from monosaccharide and disaccharides in the product site of cellulase tunnel. The absolute binding free energy of cellobiose and glucose to the product site of the catalytic tunnel of the Family 7 cellobiohydrolase (Cel7A) of Trichoderma reesei (Hypocrea jecorina) was calculated using two different approaches: steered molecular dynamics (SMD) simulations and alchemical free energy perturbation molecular dynamics (FEP/MD) simulations. For the SMD approach, three methods based on Jarzynski's equality were used to construct the potential of mean force from multiple pulling trajectories. The calculated binding free energies, −14.4 kcal/mol using SMD and −11.2 kcal/mol using FEP/MD, are in good qualitative agreement. Analysis of the SMD pulling trajectories suggests that several protein residues (Arg-251, Asp-259, Asp-262, Trp-376, and Tyr-381) play key roles in cellobiose and glucose binding to the catalytic tunnel. Five mutations (R251A, D259A, D262A, W376A, and Y381A) were made computationally to measure the changes in free energy during the product expulsion process. The absolute binding free energies of cellobiose to the catalytic tunnel of these five mutants are −13.1, −6.0, −11.5, −7.5, and −8.8 kcal/mol, respectively. The results demonstrated that all of the mutants tested can lower the binding free energy of cellobiose, which provides potential applications in engineering the enzyme to accelerate the product expulsion process and improve the efficiency of biomass conversion. PMID:21454590
Jiang, Wei; Luo, Yun; Maragliano, Luca; Roux, Benoît
2012-11-13
An extremely scalable computational strategy is described for calculations of the potential of mean force (PMF) in multidimensions on massively distributed supercomputers. The approach involves coupling thousands of umbrella sampling (US) simulation windows distributed to cover the space of order parameters with a Hamiltonian molecular dynamics replica-exchange (H-REMD) algorithm to enhance the sampling of each simulation. In the present application, US/H-REMD is carried out in a two-dimensional (2D) space and exchanges are attempted alternatively along the two axes corresponding to the two order parameters. The US/H-REMD strategy is implemented on the basis of parallel/parallel multiple copy protocol at the MPI level, and therefore can fully exploit computing power of large-scale supercomputers. Here the novel technique is illustrated using the leadership supercomputer IBM Blue Gene/P with an application to a typical biomolecular calculation of general interest, namely the binding of calcium ions to the small protein Calbindin D9k. The free energy landscape associated with two order parameters, the distance between the ion and its binding pocket and the root-mean-square deviation (rmsd) of the binding pocket relative the crystal structure, was calculated using the US/H-REMD method. The results are then used to estimate the absolute binding free energy of calcium ion to Calbindin D9k. The tests demonstrate that the 2D US/H-REMD scheme greatly accelerates the configurational sampling of the binding pocket, thereby improving the convergence of the potential of mean force calculation.
Estimating Atomic Contributions to Hydration and Binding Using Free Energy Perturbation.
Irwin, Benedict W J; Huggins, David J
2018-06-12
We present a general method called atom-wise free energy perturbation (AFEP), which extends a conventional molecular dynamics free energy perturbation (FEP) simulation to give the contribution to a free energy change from each atom. AFEP is derived from an expansion of the Zwanzig equation used in the exponential averaging method by defining that the system total energy can be partitioned into contributions from each atom. A partitioning method is assumed and used to group terms in the expansion to correspond to individual atoms. AFEP is applied to six example free energy changes to demonstrate the method. Firstly, the hydration free energies of methane, methanol, methylamine, methanethiol, and caffeine in water. AFEP highlights the atoms in the molecules that interact favorably or unfavorably with water. Finally AFEP is applied to the binding free energy of human immunodeficiency virus type 1 protease to lopinavir, and AFEP reveals the contribution of each atom to the binding free energy, indicating candidate areas of the molecule to improve to produce a more strongly binding inhibitor. FEP gives a single value for the free energy change and is already a very useful method. AFEP gives a free energy change for each "part" of the system being simulated, where part can mean individual atoms, chemical groups, amino acids, or larger partitions depending on what the user is trying to measure. This method should have various applications in molecular dynamics studies of physical, chemical, or biochemical phenomena, specifically in the field of computational drug discovery.
Ozyurt, A Sinem; Selby, Thomas L
2008-07-01
This study describes a method to computationally assess the function of homologous enzymes through small molecule binding interaction energy. Three experimentally determined X-ray structures and four enzyme models from ornithine cyclo-deaminase, alanine dehydrogenase, and mu-crystallin were used in combination with nine small molecules to derive a function score (FS) for each enzyme-model combination. While energy values varied for a single molecule-enzyme combination due to differences in the active sites, we observe that the binding energies for the entire pathway were proportional for each set of small molecules investigated. This proportionality of energies for a reaction pathway appears to be dependent on the amino acids in the active site and their direct interactions with the small molecules, which allows a function score (FS) to be calculated to assess the specificity of each enzyme. Potential of mean force (PMF) calculations were used to obtain the energies, and the resulting FS values demonstrate that a measurement of function may be obtained using differences between these PMF values. Additionally, limitations of this method are discussed based on: (a) larger substrates with significant conformational flexibility; (b) low homology enzymes; and (c) open active sites. This method should be useful in accurately predicting specificity for single enzymes that have multiple steps in their reactions and in high throughput computational methods to accurately annotate uncharacterized proteins based on active site interaction analysis. 2008 Wiley-Liss, Inc.
Discovery of HIV Type 1 Aspartic Protease Hit Compounds through Combined Computational Approaches.
Xanthopoulos, Dimitrios; Kritsi, Eftichia; Supuran, Claudiu T; Papadopoulos, Manthos G; Leonis, Georgios; Zoumpoulakis, Panagiotis
2016-08-05
A combination of computational techniques and inhibition assay experiments was employed to identify hit compounds from commercial libraries with enhanced inhibitory potency against HIV type 1 aspartic protease (HIV PR). Extensive virtual screening with the aid of reliable pharmacophore models yielded five candidate protease inhibitors. Subsequent molecular dynamics and molecular mechanics Poisson-Boltzmann surface area free-energy calculations for the five ligand-HIV PR complexes suggested a high stability of the systems through hydrogen-bond interactions between the ligands and the protease's flaps (Ile50/50'), as well as interactions with residues of the active site (Asp25/25'/29/29'/30/30'). Binding-energy calculations for the three most promising compounds yielded values between -5 and -10 kcal mol(-1) and suggested that van der Waals interactions contribute most favorably to the total energy. The predicted binding-energy values were verified by in vitro inhibition assays, which showed promising results in the high nanomolar range. These results provide structural considerations that may guide further hit-to-lead optimization toward improved anti-HIV drugs. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Odoh, Samuel O; Bondarevsky, Gary D; Karpus, Jason; Cui, Qiang; He, Chuan; Spezia, Riccardo; Gagliardi, Laura
2014-12-17
The capture of uranyl, UO2(2+), by a recently engineered protein (Zhou et al. Nat. Chem. 2014, 6, 236) with high selectivity and femtomolar sensitivity has been examined by a combination of density functional theory, molecular dynamics, and free-energy simulations. It was found that UO2(2+) is coordinated to five carboxylate oxygen atoms from four amino acid residues of the super uranyl binding protein (SUP). A network of hydrogen bonds between the amino acid residues coordinated to UO2(2+) and residues in its second coordination sphere also affects the protein's uranyl binding affinity. Free-energy simulations show how UO2(2+) capture is governed by the nature of the amino acid residues in the binding site, the integrity and strength of the second-sphere hydrogen bond network, and the number of water molecules in the first coordination sphere. Alteration of any of these three factors through mutations generally results in a reduction of the binding free energy of UO2(2+) to the aqueous protein as well as of the difference between the binding free energies of UO2(2+) and other ions (Ca(2+), Cu(2+), Mg(2+), and Zn(2+)), a proxy for the protein's selectivity over these ions. The results of our free-energy simulations confirmed the previously reported experimental results and allowed us to discover a mutant of SUP, specifically the GLU64ASP mutant, that not only binds UO2(2+) more strongly than SUP but that is also more selective for UO2(2+) over other ions. The predictions from the computations were confirmed experimentally.
Kozakov, Dima; Grove, Laurie E.; Hall, David R.; Bohnuud, Tanggis; Mottarella, Scott; Luo, Lingqi; Xia, Bing; Beglov, Dmitri; Vajda, Sandor
2016-01-01
FTMap is a computational mapping server that identifies binding hot spots of macromolecules, i.e., regions of the surface with major contributions to the ligand binding free energy. To use FTMap, users submit a protein, DNA, or RNA structure in PDB format. FTMap samples billions of positions of small organic molecules used as probes and scores the probe poses using a detailed energy expression. Regions that bind clusters of multiple probe types identify the binding hot spots, in good agreement with experimental data. FTMap serves as basis for other servers, namely FTSite to predict ligand binding sites, FTFlex to account for side chain flexibility, FTMap/param to parameterize additional probes, and FTDyn to map ensembles of protein structures. Applications include determining druggability of proteins, identifying ligand moieties that are most important for binding, finding the most bound-like conformation in ensembles of unliganded protein structures, and providing input for fragment based drug design. FTMap is more accurate than classical mapping methods such as GRID and MCSS, and is much faster than the more recent approaches to protein mapping based on mixed molecular dynamics. Using 16 probe molecules, the FTMap server finds the hot spots of an average size protein in less than an hour. Since FTFlex performs mapping for all low energy conformers of side chains in the binding site, its completion time is proportionately longer. PMID:25855957
Chertkova, Aleksandra A; Schiffman, Joshua S; Nuzhdin, Sergey V; Kozlov, Konstantin N; Samsonova, Maria G; Gursky, Vitaly V
2017-02-07
Cis-regulatory sequences are often composed of many low-affinity transcription factor binding sites (TFBSs). Determining the evolutionary and functional importance of regulatory sequence composition is impeded without a detailed knowledge of the genotype-phenotype map. We simulate the evolution of regulatory sequences involved in Drosophila melanogaster embryo segmentation during early development. Natural selection evaluates gene expression dynamics produced by a computational model of the developmental network. We observe a dramatic decrease in the total number of transcription factor binding sites through the course of evolution. Despite a decrease in average sequence binding energies through time, the regulatory sequences tend towards organisations containing increased high affinity transcription factor binding sites. Additionally, the binding energies of separate sequence segments demonstrate ubiquitous mutual correlations through time. Fewer than 10% of initial TFBSs are maintained throughout the entire simulation, deemed 'core' sites. These sites have increased functional importance as assessed under wild-type conditions and their binding energy distributions are highly conserved. Furthermore, TFBSs within close proximity of core sites exhibit increased longevity, reflecting functional regulatory interactions with core sites. In response to elevated mutational pressure, evolution tends to sample regulatory sequence organisations with fewer, albeit on average, stronger functional transcription factor binding sites. These organisations are also shaped by the regulatory interactions among core binding sites with sites in their local vicinity.
A computational ab initio study of surface diffusion of sulfur on the CdTe (111) surface
NASA Astrophysics Data System (ADS)
Naderi, Ebadollah; Ghaisas, S. V.
2016-08-01
In order to discern the formation of epitaxial growth of CdS shell over CdTe nanocrystals, kinetics related to the initial stages of the growth of CdS on CdTe is investigated using ab-initio methods. We report diffusion of sulfur adatom on the CdTe (111) A-type (Cd-terminated) and B-type (Te-terminated) surfaces within the density functional theory (DFT). The barriers are computed by applying the climbing Nudge Elastic Band (c-NEB) method. From the results surface hopping emerges as the major mode of diffusion. In addition, there is a distinct contribution from kick-out type diffusion in which a CdTe surface atom is kicked out from its position and is replaced by the diffusing sulfur atom. Also, surface vacancy substitution contributes to the concomitant dynamics. There are sites on the B- type surface that are competitively close in terms of the binding energy to the lowest energy site of epitaxy on the surface. The kick-out process is more likely for B-type surface where a Te atom of the surface is displaced by a sulfur adatom. Further, on the B-type surface, subsurface migration of sulfur is indicated. Furthermore, the binding energies of S on CdTe reveal that on the A-type surface, epitaxial sites provide relatively higher binding energies and barriers than on B-type.
A computational ab initio study of surface diffusion of sulfur on the CdTe (111) surface
DOE Office of Scientific and Technical Information (OSTI.GOV)
Naderi, Ebadollah, E-mail: enaderi42@gmail.com; Ghaisas, S. V.
2016-08-15
In order to discern the formation of epitaxial growth of CdS shell over CdTe nanocrystals, kinetics related to the initial stages of the growth of CdS on CdTe is investigated using ab-initio methods. We report diffusion of sulfur adatom on the CdTe (111) A-type (Cd-terminated) and B-type (Te-terminated) surfaces within the density functional theory (DFT). The barriers are computed by applying the climbing Nudge Elastic Band (c-NEB) method. From the results surface hopping emerges as the major mode of diffusion. In addition, there is a distinct contribution from kick-out type diffusion in which a CdTe surface atom is kicked outmore » from its position and is replaced by the diffusing sulfur atom. Also, surface vacancy substitution contributes to the concomitant dynamics. There are sites on the B- type surface that are competitively close in terms of the binding energy to the lowest energy site of epitaxy on the surface. The kick-out process is more likely for B-type surface where a Te atom of the surface is displaced by a sulfur adatom. Further, on the B-type surface, subsurface migration of sulfur is indicated. Furthermore, the binding energies of S on CdTe reveal that on the A-type surface, epitaxial sites provide relatively higher binding energies and barriers than on B-type.« less
Laitinen, Tuomo; Kankare, Jussi A; Peräkylä, Mikael
2004-04-01
Antiestradiol antibody 57-2 binds 17beta-estradiol (E2) with moderately high affinity (K(a) = 5 x 10(8) M(-1)). The structurally related natural estrogens estrone and estriol as well synthetic 17-deoxy-estradiol and 17alpha-estradiol are bound to the antibody with 3.7-4.9 kcal mol(-1) lower binding free energies than E2. Free energy perturbation (FEP) simulations and the molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) method were applied to investigate the factors responsible for the relatively low cross-reactivity of the antibody with these four steroids, differing from E2 by the substituents of the steroid D-ring. In addition, computational alanine scanning of the binding site residues was carried out with the MM-PBSA method. Both the FEP and MM-PBSA methods reproduced the experimental relative affinities of the five steroids in good agreement with experiment. On the basis of FEP simulations, the number of hydrogen bonds formed between the antibody and steroids, which varied from 0 to 3 in the steroids studied, determined directly the magnitude of the steroid-antibody interaction free energies. One hydrogen bond was calculated to contribute about 3 kcal mol(-1) to the interaction energy. Because the relative binding free energies of estrone (two antibody-steroid hydrogen bonds), estriol (three hydrogen bonds), 17-deoxy-estradiol (no hydrogen bonds), and 17alpha-estradiol (two hydrogen bonds) are close to each other and clearly lower than that of E2 (three hydrogen bonds), the water-steroid interactions lost upon binding to the antibody make an important contribution to the binding free energies. The MM-PBSA calculations showed that the binding of steroids to the antiestradiol antibody is driven by van der Waals interactions, whereas specificity is solely due to electrostatic interactions. In addition, binding of steroids to the antiestradiol antibody 57-2 was compared to the binding to the antiprogesterone antibody DB3 and antitestosterone antibody 3-C4F5, studied earlier with the MM-PBSA method. Copyright 2004 Wiley-Liss, Inc.
Xiao, Xingqing; Agris, Paul F; Hall, Carol K
2016-05-01
A computational strategy that integrates our peptide search algorithm with atomistic molecular dynamics simulation was used to design rational peptide drugs that recognize and bind to the anticodon stem and loop domain (ASL(Lys3)) of human tRNAUUULys3 for the purpose of interrupting HIV replication. The score function of the search algorithm was improved by adding a peptide stability term weighted by an adjustable factor λ to the peptide binding free energy. The five best peptide sequences associated with five different values of λ were determined using the search algorithm and then input in atomistic simulations to examine the stability of the peptides' folded conformations and their ability to bind to ASL(Lys3). Simulation results demonstrated that setting an intermediate value of λ achieves a good balance between optimizing the peptide's binding ability and stabilizing its folded conformation during the sequence evolution process, and hence leads to optimal binding to the target ASL(Lys3). Thus, addition of a peptide stability term significantly improves the success rate for our peptide design search. © 2016 Wiley Periodicals, Inc.
Quantum chemical approaches in structure-based virtual screening and lead optimization
NASA Astrophysics Data System (ADS)
Cavasotto, Claudio N.; Adler, Natalia S.; Aucar, Maria G.
2018-05-01
Today computational chemistry is a consolidated tool in drug lead discovery endeavors. Due to methodological developments and to the enormous advance in computer hardware, methods based on quantum mechanics (QM) have gained great attention in the last 10 years, and calculations on biomacromolecules are becoming increasingly explored, aiming to provide better accuracy in the description of protein-ligand interactions and the prediction of binding affinities. In principle, the QM formulation includes all contributions to the energy, accounting for terms usually missing in molecular mechanics force-fields, such as electronic polarization effects, metal coordination, and covalent binding; moreover, QM methods are systematically improvable, and provide a greater degree of transferability. In this mini-review we present recent applications of explicit QM-based methods in small-molecule docking and scoring, and in the calculation of binding free-energy in protein-ligand systems. Although the routine use of QM-based approaches in an industrial drug lead discovery setting remains a formidable challenging task, it is likely they will increasingly become active players within the drug discovery pipeline.
Advancing Drug Discovery through Enhanced Free Energy Calculations.
Abel, Robert; Wang, Lingle; Harder, Edward D; Berne, B J; Friesner, Richard A
2017-07-18
A principal goal of drug discovery project is to design molecules that can tightly and selectively bind to the target protein receptor. Accurate prediction of protein-ligand binding free energies is therefore of central importance in computational chemistry and computer aided drug design. Multiple recent improvements in computing power, classical force field accuracy, enhanced sampling methods, and simulation setup have enabled accurate and reliable calculations of protein-ligands binding free energies, and position free energy calculations to play a guiding role in small molecule drug discovery. In this Account, we outline the relevant methodological advances, including the REST2 (Replica Exchange with Solute Temperting) enhanced sampling, the incorporation of REST2 sampling with convential FEP (Free Energy Perturbation) through FEP/REST, the OPLS3 force field, and the advanced simulation setup that constitute our FEP+ approach, followed by the presentation of extensive comparisons with experiment, demonstrating sufficient accuracy in potency prediction (better than 1 kcal/mol) to substantially impact lead optimization campaigns. The limitations of the current FEP+ implementation and best practices in drug discovery applications are also discussed followed by the future methodology development plans to address those limitations. We then report results from a recent drug discovery project, in which several thousand FEP+ calculations were successfully deployed to simultaneously optimize potency, selectivity, and solubility, illustrating the power of the approach to solve challenging drug design problems. The capabilities of free energy calculations to accurately predict potency and selectivity have led to the advance of ongoing drug discovery projects, in challenging situations where alternative approaches would have great difficulties. The ability to effectively carry out projects evaluating tens of thousands, or hundreds of thousands, of proposed drug candidates, is potentially transformative in enabling hard to drug targets to be attacked, and in facilitating the development of superior compounds, in various dimensions, for a wide range of targets. More effective integration of FEP+ calculations into the drug discovery process will ensure that the results are deployed in an optimal fashion for yielding the best possible compounds entering the clinic; this is where the greatest payoff is in the exploitation of computer driven design capabilities. A key conclusion from the work described is the surprisingly robust and accurate results that are attainable within the conventional classical simulation, fixed charge paradigm. No doubt there are individual cases that would benefit from a more sophisticated energy model or dynamical treatment, and properties other than protein-ligand binding energies may be more sensitive to these approximations. We conclude that an inflection point in the ability of MD simulations to impact drug discovery has now been attained, due to the confluence of hardware and software development along with the formulation of "good enough" theoretical methods and models.
Computational exploration of a protein receptor binding space with student proposed peptide ligands.
King, Matthew D; Phillips, Paul; Turner, Matthew W; Katz, Michael; Lew, Sarah; Bradburn, Sarah; Andersen, Tim; McDougal, Owen M
2016-01-01
Computational molecular docking is a fast and effective in silico method for the analysis of binding between a protein receptor model and a ligand. The visualization and manipulation of protein to ligand binding in three-dimensional space represents a powerful tool in the biochemistry curriculum to enhance student learning. The DockoMatic tutorial described herein provides a framework by which instructors can guide students through a drug screening exercise. Using receptor models derived from readily available protein crystal structures, docking programs have the ability to predict ligand binding properties, such as preferential binding orientations and binding affinities. The use of computational studies can significantly enhance complimentary wet chemical experimentation by providing insight into the important molecular interactions within the system of interest, as well as guide the design of new candidate ligands based on observed binding motifs and energetics. In this laboratory tutorial, the graphical user interface, DockoMatic, facilitates docking job submissions to the docking engine, AutoDock 4.2. The purpose of this exercise is to successfully dock a 17-amino acid peptide, α-conotoxin TxIA, to the acetylcholine binding protein from Aplysia californica-AChBP to determine the most stable binding configuration. Each student will then propose two specific amino acid substitutions of α-conotoxin TxIA to enhance peptide binding affinity, create the mutant in DockoMatic, and perform docking calculations to compare their results with the class. Students will also compare intermolecular forces, binding energy, and geometric orientation of their prepared analog to their initial α-conotoxin TxIA docking results. © 2015 The International Union of Biochemistry and Molecular Biology.
NASA Astrophysics Data System (ADS)
Maurya, Neha; ud din Parray, Mehraj; Maurya, Jitendra Kumar; Kumar, Amit; Patel, Rajan
2018-06-01
The binding nature of amphiphilic drugs viz. promethazine hydrochloride (PMT) and adiphenine hydrochloride (ADP), with human hemoglobin (Hb) was unraveled by fluorescence, absorbance, time resolved fluorescence, fluorescence resonance energy transfer (FRET) and circular dichroism (CD) spectral techniques in combination with molecular docking and molecular dynamic simulation methods. The steady state fluorescence spectra indicated that both PMT and ADP quenches the fluorescence of Hb through static quenching mechanism which was further confirmed by time resolved fluorescence spectra. The UV-Vis spectroscopy suggested ground state complex formation. The activation energy (Ea) was observed more in the case of Hb-ADP than Hb-PMT interaction system. The FRET result indicates the high probability of energy transfer from β Trp37 residue of Hb to the PMT (r = 2.02 nm) and ADP (r = 2.33 nm). The thermodynamic data reveal that binding of PMT with Hb are exothermic in nature involving hydrogen bonding and van der Waal interaction whereas in the case of ADP hydrophobic forces play the major role and binding process is endothermic in nature. The CD results show that both PMT and ADP, induced secondary structural changes of Hb and unfold the protein by losing a large helical content while the effect is more pronounced with ADP. Additionally, we also utilized computational approaches for deep insight into the binding of these drugs with Hb and the results are well matched with our experimental results.
Maurya, Neha; Ud Din Parray, Mehraj; Maurya, Jitendra Kumar; Kumar, Amit; Patel, Rajan
2018-06-15
The binding nature of amphiphilic drugs viz. promethazine hydrochloride (PMT) and adiphenine hydrochloride (ADP), with human hemoglobin (Hb) was unraveled by fluorescence, absorbance, time resolved fluorescence, fluorescence resonance energy transfer (FRET) and circular dichroism (CD) spectral techniques in combination with molecular docking and molecular dynamic simulation methods. The steady state fluorescence spectra indicated that both PMT and ADP quenches the fluorescence of Hb through static quenching mechanism which was further confirmed by time resolved fluorescence spectra. The UV-Vis spectroscopy suggested ground state complex formation. The activation energy (E a ) was observed more in the case of Hb-ADP than Hb-PMT interaction system. The FRET result indicates the high probability of energy transfer from β Trp37 residue of Hb to the PMT (r=2.02nm) and ADP (r=2.33nm). The thermodynamic data reveal that binding of PMT with Hb are exothermic in nature involving hydrogen bonding and van der Waal interaction whereas in the case of ADP hydrophobic forces play the major role and binding process is endothermic in nature. The CD results show that both PMT and ADP, induced secondary structural changes of Hb and unfold the protein by losing a large helical content while the effect is more pronounced with ADP. Additionally, we also utilized computational approaches for deep insight into the binding of these drugs with Hb and the results are well matched with our experimental results. Copyright © 2018 Elsevier B.V. All rights reserved.
Methyl Transfer by Substrate Signaling from a Knotted Protein Fold
Christian, Thomas; Sakaguchi, Reiko; Perlinska, Agata P.; Lahoud, Georges; Ito, Takuhiro; Taylor, Erika A.; Yokoyama, Shigeyuki; Sulkowska, Joanna I.; Hou, Ya-Ming
2017-01-01
Proteins with knotted configurations are restricted in conformational space relative to unknotted proteins. Little is known if knotted proteins have sufficient dynamics to communicate between spatially separated substrate-binding sites. In bacteria, TrmD is a methyl transferase that uses a knotted protein fold to catalyze methyl transfer from S-adenosyl methionine (AdoMet) to G37-tRNA. The product m1G37-tRNA is essential for life as a determinant to maintain protein synthesis reading-frame. Using an integrated approach of structure, kinetic, and computational analysis, we show here that the structurally constrained TrmD knot is required for its catalytic activity. Unexpectedly, the TrmD knot has complex internal movements that respond to AdoMet binding and signaling. Most of the signaling propagates the free energy of AdoMet binding to stabilize tRNA binding and to assemble the active site. This work demonstrates new principles of knots as an organized structure that captures the free energies of substrate binding to facilitate catalysis. PMID:27571175
NASA Astrophysics Data System (ADS)
Woods, Christopher J.; Malaisree, Maturos; Long, Ben; McIntosh-Smith, Simon; Mulholland, Adrian J.
2013-12-01
The emergence of a novel H7N9 avian influenza that infects humans is a serious cause for concern. Of the genome sequences of H7N9 neuraminidase available, one contains a substitution of arginine to lysine at position 292, suggesting a potential for reduced drug binding efficacy. We have performed molecular dynamics simulations of oseltamivir, zanamivir and peramivir bound to H7N9, H7N9-R292K, and a structurally related H11N9 neuraminidase. They show that H7N9 neuraminidase is structurally homologous to H11N9, binding the drugs in identical modes. The simulations reveal that the R292K mutation disrupts drug binding in H7N9 in a comparable manner to that observed experimentally for H11N9-R292K. Absolute binding free energy calculations with the WaterSwap method confirm a reduction in binding affinity. This indicates that the efficacy of antiviral drugs against H7N9-R292K will be reduced. Simulations can assist in predicting disruption of binding caused by mutations in neuraminidase, thereby providing a computational `assay.'
Chen, Jianzhong; Zhang, Dinglin; Zhang, Yuxin; Li, Guohui
2012-01-01
Inhibition of p53-MDM2/MDMX interaction is considered to be a promising strategy for anticancer drug design to activate wild-type p53 in tumors. We carry out molecular dynamics (MD) simulations to study the binding mechanisms of peptide and non-peptide inhibitors to MDM2/MDMX. The rank of binding free energies calculated by molecular mechanics generalized Born surface area (MM-GBSA) method agrees with one of the experimental values. The results suggest that van der Waals energy drives two kinds of inhibitors to MDM2/MDMX. We also find that the peptide inhibitors can produce more interaction contacts with MDM2/MDMX than the non-peptide inhibitors. Binding mode predictions based on the inhibitor-residue interactions show that the π–π, CH–π and CH–CH interactions dominated by shape complimentarity, govern the binding of the inhibitors in the hydrophobic cleft of MDM2/MDMX. Our studies confirm the residue Tyr99 in MDMX can generate a steric clash with the inhibitors due to energy and structure. This finding may theoretically provide help to develop potent dual-specific or MDMX inhibitors. PMID:22408446
NASA Astrophysics Data System (ADS)
Tzoupis, Haralambos; Leonis, Georgios; Durdagi, Serdar; Mouchlis, Varnavas; Mavromoustakos, Thomas; Papadopoulos, Manthos G.
2011-10-01
The objectives of this study include the design of a series of novel fullerene-based inhibitors for HIV-1 protease (HIV-1 PR), by employing two strategies that can also be applied to the design of inhibitors for any other target. Additionally, the interactions which contribute to the observed exceptionally high binding free energies were analyzed. In particular, we investigated: (1) hydrogen bonding (H-bond) interactions between specific fullerene derivatives and the protease, (2) the regions of HIV-1 PR that play a significant role in binding, (3) protease changes upon binding and (4) various contributions to the binding free energy, in order to identify the most significant of them. This study has been performed by employing a docking technique, two 3D-QSAR models, molecular dynamics (MD) simulations and the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method. Our computed binding free energies are in satisfactory agreement with the experimental results. The suitability of specific fullerene derivatives as drug candidates was further enhanced, after ADMET (absorption, distribution, metabolism, excretion and toxicity) properties have been estimated to be promising. The outcomes of this study revealed important protein-ligand interaction patterns that may lead towards the development of novel, potent HIV-1 PR inhibitors.
Signatures of van der Waals binding: A coupling-constant scaling analysis
NASA Astrophysics Data System (ADS)
Jiao, Yang; Schröder, Elsebeth; Hyldgaard, Per
2018-02-01
The van der Waals (vdW) density functional (vdW-DF) method [Rep. Prog. Phys. 78, 066501 (2015), 10.1088/0034-4885/78/6/066501] describes dispersion or vdW binding by tracking the effects of an electrodynamic coupling among pairs of electrons and their associated exchange-correlation holes. This is done in a nonlocal-correlation energy term Ecnl, which permits density functional theory calculation in the Kohn-Sham scheme. However, to map the nature of vdW forces in a fully interacting materials system, it is necessary to also account for associated kinetic-correlation energy effects. Here, we present a coupling-constant scaling analysis, which permits us to compute the kinetic-correlation energy Tcnl that is specific to the vdW-DF account of nonlocal correlations. We thus provide a more complete spatially resolved analysis of the electrodynamical-coupling nature of nonlocal-correlation binding, including vdW attraction, in both covalently and noncovalently bonded systems. We find that kinetic-correlation energy effects play a significant role in the account of vdW or dispersion interactions among molecules. Furthermore, our mapping shows that the total nonlocal-correlation binding is concentrated to pockets in the sparse electron distribution located between the material fragments.
NASA Astrophysics Data System (ADS)
Rifai, Eko Aditya; van Dijk, Marc; Vermeulen, Nico P. E.; Geerke, Daan P.
2018-01-01
Computational protein binding affinity prediction can play an important role in drug research but performing efficient and accurate binding free energy calculations is still challenging. In the context of phase 2 of the Drug Design Data Resource (D3R) Grand Challenge 2 we used our automated eTOX ALLIES approach to apply the (iterative) linear interaction energy (LIE) method and we evaluated its performance in predicting binding affinities for farnesoid X receptor (FXR) agonists. Efficiency was obtained by our pre-calibrated LIE models and molecular dynamics (MD) simulations at the nanosecond scale, while predictive accuracy was obtained for a small subset of compounds. Using our recently introduced reliability estimation metrics, we could classify predictions with higher confidence by featuring an applicability domain (AD) analysis in combination with protein-ligand interaction profiling. The outcomes of and agreement between our AD and interaction-profile analyses to distinguish and rationalize the performance of our predictions highlighted the relevance of sufficiently exploring protein-ligand interactions during training and it demonstrated the possibility to quantitatively and efficiently evaluate if this is achieved by using simulation data only.
Kilina, Svetlana; Yarotski, Dzmitry A.; Talin, A. Alec; ...
2011-01-01
We present a combined approach that relies on computational simulations and scanning tunneling microscopy (STM) measurements to reveal morphological properties and stability criteria of carbon nanotube-DNA (CNT-DNA) constructs. Application of STM allows direct observation of very stable CNT-DNA hybrid structures with the well-defined DNA wrapping angle of 63.4 ° and a coiling period of 3.3 nm. Using force field simulations, we determine how the DNA-CNT binding energy depends on the sequence and binding geometry of a single strand DNA. This dependence allows us to quantitatively characterize the stability of a hybrid structure with an optimal π-stacking between DNA nucleotides and themore » tube surface and better interpret STM data. Our simulations clearly demonstrate the existence of a very stable DNA binding geometry for (6,5) CNT as evidenced by the presence of a well-defined minimum in the binding energy as a function of an angle between DNA strand and the nanotube chiral vector. This novel approach demonstrates the feasibility of CNT-DNA geometry studies with subnanometer resolution and paves the way towards complete characterization of the structural and electronic properties of drug-delivering systems based on DNA-CNT hybrids as a function of DNA sequence and a nanotube chirality.« less
Tu, Jing; Li, Jiao Jiao; Shan, Zhi Jie; Zhai, Hong Lin
2017-01-01
The non-nucleoside drugs have been developed to treat HBV infection owing to their increased efficacy and lesser side effects, in which heteroaryldihydropyrimidines (HAPs) have been identified as effective inhibitors of HBV capsid. In this paper, the binding mechanism of HAPs targeting on HBV capsid protein was explored through three-dimensional quantitative structure-activity relationship, molecular dynamics and binding free energy decompositions. The obtained models of comparative molecular field analysis and comparative molecular similarity indices analysis enable the sufficient interpretation of structure-activity relationship of HAPs-HBV. The binding free energy analysis correlates with the experimental data. The computational results disclose that the non-polar contribution is the major driving force and Y132A mutation enhances the binding affinity for inhibitor 2 bound to HBV. The hydrogen bond interactions between the inhibitors and Trp102 help to stabilize the conformation of HAPs-HBV. The study provides insight into the binding mechanism of HAPs-HBV and would be useful for the rational design and modification of new lead compounds of HAP drugs. Copyright © 2016 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Dickson, Bradley M.; de Waal, Parker W.; Ramjan, Zachary H.; Xu, H. Eric; Rothbart, Scott B.
2016-10-01
In this communication we introduce an efficient implementation of adaptive biasing that greatly improves the speed of free energy computation in molecular dynamics simulations. We investigated the use of accelerated simulations to inform on compound design using a recently reported and clinically relevant inhibitor of the chromatin regulator BRD4 (bromodomain-containing protein 4). Benchmarking on our local compute cluster, our implementation achieves up to 2.5 times more force calls per day than plumed2. Results of five 1 μs-long simulations are presented, which reveal a conformational switch in the BRD4 inhibitor between a binding competent and incompetent state. Stabilization of the switch led to a -3 kcal/mol improvement of absolute binding free energy. These studies suggest an unexplored ligand design principle and offer new actionable hypotheses for medicinal chemistry efforts against this druggable epigenetic target class.
Dickson, Bradley M.; Ramjan, Zachary H.; Xu, H. Eric
2016-01-01
In this communication we introduce an efficient implementation of adaptive biasing that greatly improves the speed of free energy computation in molecular dynamics simulations. We investigated the use of accelerated simulations to inform on compound design using a recently reported and clinically relevant inhibitor of the chromatin regulator BRD4 (bromodomain-containing protein 4). Benchmarking on our local compute cluster, our implementation achieves up to 2.5 times more force calls per day than plumed2. Results of five 1 μs-long simulations are presented, which reveal a conformational switch in the BRD4 inhibitor between a binding competent and incompetent state. Stabilization of the switch led to a −3 kcal/mol improvement of absolute binding free energy. These studies suggest an unexplored ligand design principle and offer new actionable hypotheses for medicinal chemistry efforts against this druggable epigenetic target class. PMID:27782467
Computational inhibitor design against malaria plasmepsins.
Bjelic, S; Nervall, M; Gutiérrez-de-Terán, H; Ersmark, K; Hallberg, A; Aqvist, J
2007-09-01
Plasmepsins are aspartic proteases involved in the degradation of the host cell hemoglobin that is used as a food source by the malaria parasite. Plasmepsins are highly promising as drug targets, especially when combined with the inhibition of falcipains that are also involved in hemoglobin catabolism. In this review, we discuss the mechanism of plasmepsins I-IV in view of the interest in transition state mimetics as potential compounds for lead development. Inhibitor development against plasmepsin II as well as relevant crystal structures are summarized in order to give an overview of the field. Application of computational techniques, especially binding affinity prediction by the linear interaction energy method, in the development of malarial plasmepsin inhibitors has been highly successful and is discussed in detail. Homology modeling and molecular docking have been useful in the current inhibitor design project, and the combination of such methods with binding free energy calculations is analyzed.
The application of quantum mechanics in structure-based drug design.
Mucs, Daniel; Bryce, Richard A
2013-03-01
Computational chemistry has become an established and valuable component in structure-based drug design. However the chemical complexity of many ligands and active sites challenges the accuracy of the empirical potentials commonly used to describe these systems. Consequently, there is a growing interest in utilizing electronic structure methods for addressing problems in protein-ligand recognition. In this review, the authors discuss recent progress in the development and application of quantum chemical approaches to modeling protein-ligand interactions. The authors specifically consider the development of quantum mechanics (QM) approaches for studying large molecular systems pertinent to biology, focusing on protein-ligand docking, protein-ligand binding affinities and ligand strain on binding. Although computation of binding energies remains a challenging and evolving area, current QM methods can underpin improved docking approaches and offer detailed insights into ligand strain and into the nature and relative strengths of complex active site interactions. The authors envisage that QM will become an increasingly routine and valued tool of the computational medicinal chemist.
Stability of ALS-related Superoxide Dismutase Protein variants
NASA Astrophysics Data System (ADS)
Lusebrink, Daniel; Plotkin, Steven
Superoxide dismutase (SOD1) is a metal binding, homodimeric protein, whose misfolding is implicated in the neurodegenerative disease amyotrophic lateral sclerosis (ALS). Monomerization is believed to be a key step in the propagation of the disease. The dimer stability is often difficult to measure experimentally however, because it is entangled with protein unfolding and metal loss. We thus computationally investigate the dimer stability of mutants of SOD1 known to be associated with ALS. We report on systematic trends in dimer stability, as well as intriguing allosteric communication between mutations and the dimer interface. We study the dimer stabilities in molecular dynamics simulations and obtain the binding free energies of the dimers from pulling essays. Mutations are applied in silicoand we compare the differences of binding free energies compared to the wild type.
Ligand deconstruction: Why some fragment binding positions are conserved and others are not
Kozakov, Dima; Hall, David R.; Jehle, Stefan; Luo, Lingqi; Ochiana, Stefan O.; Jones, Elizabeth V.; Pollastri, Michael; Allen, Karen N.; Whitty, Adrian; Vajda, Sandor
2015-01-01
Fragment-based drug discovery (FBDD) relies on the premise that the fragment binding mode will be conserved on subsequent expansion to a larger ligand. However, no general condition has been established to explain when fragment binding modes will be conserved. We show that a remarkably simple condition can be developed in terms of how fragments coincide with binding energy hot spots—regions of the protein where interactions with a ligand contribute substantial binding free energy—the locations of which can easily be determined computationally. Because a substantial fraction of the free energy of ligand binding comes from interacting with the residues in the energetically most important hot spot, a ligand moiety that sufficiently overlaps with this region will retain its location even when other parts of the ligand are removed. This hypothesis is supported by eight case studies. The condition helps identify whether a protein is suitable for FBDD, predicts the size of fragments required for screening, and determines whether a fragment hit can be extended into a higher affinity ligand. Our results show that ligand binding sites can usefully be thought of in terms of an anchor site, which is the top-ranked hot spot and dominates the free energy of binding, surrounded by a number of weaker satellite sites that confer improved affinity and selectivity for a particular ligand and that it is the intrinsic binding potential of the protein surface that determines whether it can serve as a robust binding site for a suitably optimized ligand. PMID:25918377
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nishimoto, Yoshio, E-mail: nishimoto.yoshio@fukui.kyoto-u.ac.jp
2015-09-07
We develop a formalism for the calculation of excitation energies and excited state gradients for the self-consistent-charge density-functional tight-binding method with the third-order contributions of a Taylor series of the density functional theory energy with respect to the fluctuation of electron density (time-dependent density-functional tight-binding (TD-DFTB3)). The formulation of the excitation energy is based on the existing time-dependent density functional theory and the older TD-DFTB2 formulae. The analytical gradient is computed by solving Z-vector equations, and it requires one to calculate the third-order derivative of the total energy with respect to density matrix elements due to the inclusion of themore » third-order contributions. The comparison of adiabatic excitation energies for selected small and medium-size molecules using the TD-DFTB2 and TD-DFTB3 methods shows that the inclusion of the third-order contributions does not affect excitation energies significantly. A different set of parameters, which are optimized for DFTB3, slightly improves the prediction of adiabatic excitation energies statistically. The application of TD-DFTB for the prediction of absorption and fluorescence energies of cresyl violet demonstrates that TD-DFTB3 reproduced the experimental fluorescence energy quite well.« less
Olsson, Martin A.; Söderhjelm, Pär
2016-01-01
In this article, the convergence of quantum mechanical (QM) free‐energy simulations based on molecular dynamics simulations at the molecular mechanics (MM) level has been investigated. We have estimated relative free energies for the binding of nine cyclic carboxylate ligands to the octa‐acid deep‐cavity host, including the host, the ligand, and all water molecules within 4.5 Å of the ligand in the QM calculations (158–224 atoms). We use single‐step exponential averaging (ssEA) and the non‐Boltzmann Bennett acceptance ratio (NBB) methods to estimate QM/MM free energy with the semi‐empirical PM6‐DH2X method, both based on interaction energies. We show that ssEA with cumulant expansion gives a better convergence and uses half as many QM calculations as NBB, although the two methods give consistent results. With 720,000 QM calculations per transformation, QM/MM free‐energy estimates with a precision of 1 kJ/mol can be obtained for all eight relative energies with ssEA, showing that this approach can be used to calculate converged QM/MM binding free energies for realistic systems and large QM partitions. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. PMID:27117350
Nishimoto, Yoshio
2015-09-07
We develop a formalism for the calculation of excitation energies and excited state gradients for the self-consistent-charge density-functional tight-binding method with the third-order contributions of a Taylor series of the density functional theory energy with respect to the fluctuation of electron density (time-dependent density-functional tight-binding (TD-DFTB3)). The formulation of the excitation energy is based on the existing time-dependent density functional theory and the older TD-DFTB2 formulae. The analytical gradient is computed by solving Z-vector equations, and it requires one to calculate the third-order derivative of the total energy with respect to density matrix elements due to the inclusion of the third-order contributions. The comparison of adiabatic excitation energies for selected small and medium-size molecules using the TD-DFTB2 and TD-DFTB3 methods shows that the inclusion of the third-order contributions does not affect excitation energies significantly. A different set of parameters, which are optimized for DFTB3, slightly improves the prediction of adiabatic excitation energies statistically. The application of TD-DFTB for the prediction of absorption and fluorescence energies of cresyl violet demonstrates that TD-DFTB3 reproduced the experimental fluorescence energy quite well.
Lin, Yen -Lin; Meng, Yilin; Huang, Lei; ...
2014-10-22
Gleevec is a potent inhibitor of Abl tyrosine kinase but not of the highly homologous c-Src kinase. Because the ligand binds to an inactive form of the protein in which an Asp-Phe-Gly structural motif along the activation loop adopts a so-called DFG-out conformation, it was suggested that binding specificity was controlled by a “conformational selection” mechanism. In this context, the binding affinity displayed by the kinase inhibitor G6G poses an intriguing challenge. Although it possesses a chemical core very similar to that of Gleevec, G6G is a potent inhibitor of both Abl and c-Src kinases. Both inhibitors bind to themore » DFG-out conformation of the kinases, which seems to be in contradiction with the conformational selection mechanism. To address this issue and display the hidden thermodynamic contributions affecting the binding selectivity, molecular dynamics free energy simulations with explicit solvent molecules were carried out. Relative to Gleevec, G6G forms highly favorable van der Waals dispersive interactions upon binding to the kinases via its triazine functional group, which is considerably larger than the corresponding pyridine moiety in Gleevec. Upon binding of G6G to c-Src, these interactions offset the unfavorable free energy cost of the DFG-out conformation. When binding to Abl, however, G6G experiences an unfavorable free energy penalty due to steric clashes with the phosphate-binding loop, yielding an overall binding affinity that is similar to that of Gleevec. Such steric clashes are absent when G6G binds to c-Src, due to the extended conformation of the phosphate-binding loop.« less
Stewart, James J P
2016-11-01
A new method for predicting the energy contributions to substrate binding and to specificity has been developed. Conventional global optimization methods do not permit the subtle effects responsible for these properties to be modeled with sufficient precision to allow confidence to be placed in the results, but by making simple alterations to the model, the precisions of the various energies involved can be improved from about ±2 kcal mol -1 to ±0.1 kcal mol -1 . This technique was applied to the oxidized nucleotide pyrophosphohydrolase enzyme MTH1. MTH1 is unusual in that the binding and reaction sites are well separated-an advantage from a computational chemistry perspective, as it allows the energetics involved in docking to be modeled without the need to consider any issues relating to reaction mechanisms. In this study, two types of energy terms were investigated: the noncovalent interactions between the binding site and the substrate, and those responsible for discriminating between the oxidized nucleotide 8-oxo-dGTP and the normal dGTP. Both of these were investigated using the semiempirical method PM7 in the program MOPAC. The contributions of the individual residues to both the binding energy and the specificity of MTH1 were calculated by simulating the effect of mutations. Where comparisons were possible, all calculated results were in agreement with experimental observations. This technique provides fresh insight into the binding mechanism that enzymes use for discriminating between possible substrates.
NASA Astrophysics Data System (ADS)
Maity, Subhajit; Chakraborty, Sandipan; Chakraborti, Abhay Sankar
2017-02-01
The present study demonstrates critical insight into the binding of a bioactive flavanone naringenin with normal human haemoglobin (NHb). Both spectrophotometric and spectrofluorimetric studies reveal that naringenin interacts with NHb. The binding affinity constant and number of binding sites appear to be approximately (1.5 ± 0.2) × 104 M-1 and 1, respectively. Static quenching seems to be an important factor in binding process, as evident from steady-state and time-resolved fluorescence spectroscopic studies. Far UV circular dichroism spectroscopy depicts that binding of naringenin to NHb causes no change in the secondary structure of the protein, which is also evident from Fourier transform infrared spectroscopic study. Free energy change (ΔG0) for naringenin-NHb interaction, determined by spectroscopic and isothermal calorimetric method, appears to be -5.67 kcal/mol and -6.90 kcal/mol, respectively, and is close to the docking energy -6.84 kcal/mol. Molecular docking suggests that naringenin binds near the cavity of the tetrameric heme protein, forming hydrogen bonds with surrounding amino acid residues. The binding site is away from the heme moieties, implicating naringenin binding does not affect the oxygen binding capacity of NHb, which makes the protein a suitable carrier of the flavonoid.
Sudarshana Reddy, B; Pavankumar, P; Sridhar, L; Saha, Soumen; Narahari Sastry, G; Prabhakar, S
2018-04-24
The intercellular and intracellular transport of charged species (Na + /K + ) entail interaction of the ions with neutral organic molecules and formation of adduct ions. The rate of transport of the ions across the cell membrane(s) may depend on the stability of the adduct ions, which in turn rely on structural aspects of the organic molecules that interact with the ions. Positive ion ESI mass spectra were recorded for the solutions containing fatty acids (FAs) and monovalent cations (X=Li + , Na + , K + , Rb + and Cs + ). Product ion spectra of the [FA+X] + ions were recorded at different collision energies. Theoretical studies were exploited under both gas phase and solvent phase to investigate the structural effects of the fatty acids during cationization. Stability of [FA+X] + adduct ions were further estimated by means of AIM topological analyses and interaction energy (IE) values. Positive ion ESI-MS analyses of the solution of FAs and X + ions showed preferential binding of the K + ions to FAs. The K + ion binding increased with the increase in number of double bonds of FAs, while decreased with increase in the number of carbons of FAs. Dissociation curves of [FA+X] + ions indicated the relative stability order of the [FA+X] + ions and it was in line with the observed trends in ESI-MS. The solvent phase computational studies divulged the mode of binding and the binding efficiencies of different FAs with monovalent cations. Among the studied monovalent cations, the cationization of FAs follow the order K + >Na + >Li + >Rb + >Cs + . The docosahexaenoic acid showed high efficiency in binding with K + ion. The K + ion binding efficiency of FAs depends on the number of double bonds in unsaturated FAs and the carbon chain length in saturated FAs. The cationization trends of FAs obtained from the ESI-MS, ESI-MS/MS analyses were in good agreement with solvent phase computational studies. This article is protected by copyright. All rights reserved.
NASA Astrophysics Data System (ADS)
Monroe, Jacob I.; Shirts, Michael R.
2014-04-01
Molecular containers such as cucurbit[7]uril (CB7) and the octa-acid (OA) host are ideal simplified model test systems for optimizing and analyzing methods for computing free energies of binding intended for use with biologically relevant protein-ligand complexes. To this end, we have performed initially blind free energy calculations to determine the free energies of binding for ligands of both the CB7 and OA hosts. A subset of the selected guest molecules were those included in the SAMPL4 prediction challenge. Using expanded ensemble simulations in the dimension of coupling host-guest intermolecular interactions, we are able to show that our estimates in most cases can be demonstrated to fully converge and that the errors in our estimates are due almost entirely to the assigned force field parameters and the choice of environmental conditions used to model experiment. We confirm the convergence through the use of alternative simulation methodologies and thermodynamic pathways, analyzing sampled conformations, and directly observing changes of the free energy with respect to simulation time. Our results demonstrate the benefits of enhanced sampling of multiple local free energy minima made possible by the use of expanded ensemble molecular dynamics and may indicate the presence of significant problems with current transferable force fields for organic molecules when used for calculating binding affinities, especially in non-protein chemistries.
Monroe, Jacob I; Shirts, Michael R
2014-04-01
Molecular containers such as cucurbit[7]uril (CB7) and the octa-acid (OA) host are ideal simplified model test systems for optimizing and analyzing methods for computing free energies of binding intended for use with biologically relevant protein-ligand complexes. To this end, we have performed initially blind free energy calculations to determine the free energies of binding for ligands of both the CB7 and OA hosts. A subset of the selected guest molecules were those included in the SAMPL4 prediction challenge. Using expanded ensemble simulations in the dimension of coupling host-guest intermolecular interactions, we are able to show that our estimates in most cases can be demonstrated to fully converge and that the errors in our estimates are due almost entirely to the assigned force field parameters and the choice of environmental conditions used to model experiment. We confirm the convergence through the use of alternative simulation methodologies and thermodynamic pathways, analyzing sampled conformations, and directly observing changes of the free energy with respect to simulation time. Our results demonstrate the benefits of enhanced sampling of multiple local free energy minima made possible by the use of expanded ensemble molecular dynamics and may indicate the presence of significant problems with current transferable force fields for organic molecules when used for calculating binding affinities, especially in non-protein chemistries.
Kulp, John L.; Cloudsdale, Ian S.; Kulp, John L.
2017-01-01
Chemically diverse fragments tend to collectively bind at localized sites on proteins, which is a cornerstone of fragment-based techniques. A central question is how general are these strategies for predicting a wide variety of molecular interactions such as small molecule-protein, protein-protein and protein-nucleic acid for both experimental and computational methods. To address this issue, we recently proposed three governing principles, (1) accurate prediction of fragment-macromolecule binding free energy, (2) accurate prediction of water-macromolecule binding free energy, and (3) locating sites on a macromolecule that have high affinity for a diversity of fragments and low affinity for water. To test the generality of these concepts we used the computational technique of Simulated Annealing of Chemical Potential to design one small fragment to break the RecA-RecA protein-protein interaction and three fragments that inhibit peptide-deformylase via water-mediated multi-body interactions. Experiments confirm the predictions that 6-hydroxydopamine potently inhibits RecA and that PDF inhibition quantitatively tracks the water-mediated binding predictions. Additionally, the principles correctly predict the essential bound waters in HIV Protease, the surprisingly extensive binding site of elastase, the pinpoint location of electron transfer in dihydrofolate reductase, the HIV TAT-TAR protein-RNA interactions, and the MDM2-MDM4 differential binding to p53. The experimental confirmations of highly non-obvious predictions combined with the precise characterization of a broad range of known phenomena lend strong support to the generality of fragment-based methods for characterizing molecular recognition. PMID:28837642
Kulp, John L; Cloudsdale, Ian S; Kulp, John L; Guarnieri, Frank
2017-01-01
Chemically diverse fragments tend to collectively bind at localized sites on proteins, which is a cornerstone of fragment-based techniques. A central question is how general are these strategies for predicting a wide variety of molecular interactions such as small molecule-protein, protein-protein and protein-nucleic acid for both experimental and computational methods. To address this issue, we recently proposed three governing principles, (1) accurate prediction of fragment-macromolecule binding free energy, (2) accurate prediction of water-macromolecule binding free energy, and (3) locating sites on a macromolecule that have high affinity for a diversity of fragments and low affinity for water. To test the generality of these concepts we used the computational technique of Simulated Annealing of Chemical Potential to design one small fragment to break the RecA-RecA protein-protein interaction and three fragments that inhibit peptide-deformylase via water-mediated multi-body interactions. Experiments confirm the predictions that 6-hydroxydopamine potently inhibits RecA and that PDF inhibition quantitatively tracks the water-mediated binding predictions. Additionally, the principles correctly predict the essential bound waters in HIV Protease, the surprisingly extensive binding site of elastase, the pinpoint location of electron transfer in dihydrofolate reductase, the HIV TAT-TAR protein-RNA interactions, and the MDM2-MDM4 differential binding to p53. The experimental confirmations of highly non-obvious predictions combined with the precise characterization of a broad range of known phenomena lend strong support to the generality of fragment-based methods for characterizing molecular recognition.
Kumar, Akhil; Srivastava, Gaurava; Negi, Arvind S; Sharma, Ashok
2018-01-19
BACE-1 and GSK-3β both are potential therapeutic drug targets for Alzheimer's disease. Recently, both these targets received attention for designing dual inhibitors. Till now only two scaffolds (triazinone and curcumin) derivatives have been reported as BACE-1 and GSK-3β dual inhibitors. In our previous work, we have reported first in class dual inhibitor for BACE-1 and GSK-3β. In this study, we have explored other naphthofuran derivatives for their potential to inhibit BACE-1 and GSK-3β through docking, molecular dynamics, binding energy (MM-PBSA). These computational methods were performed to estimate the binding affinity of naphthofuran derivatives towards the BACE-1 and GSK-3β. In the docking results, two derivatives (NS7 and NS9) showed better binding affinity as compared to previously reported inhibitors. Hydrogen bond occupancy of NS7 and NS9 generated from MD trajectories showed good interaction with the flap residues Gln73, Thr72 of BACE-1 and Arg141, Thr138 residues of GSK-3β. MM-PBSA and energy decomposition per residue revealed different components of binding energy and relative importance of amino acid involved in binding. The results showed that the binding of inhibitors was majorly governed by the hydrophobic interactions and suggesting that hydrophobic interactions might be the key to design dual inhibitors for BACE1-1 and GSK-3β. Distance between important pair of amino acid residues indicated that BACE-1 and GSK-3β adopt closed conformation and become inactive after ligand binding. The results suggested that naphthofuran derivatives might act as dual inhibitor against BACE-1 and GSK-3β.
Basis sets for the calculation of core-electron binding energies
NASA Astrophysics Data System (ADS)
Hanson-Heine, Magnus W. D.; George, Michael W.; Besley, Nicholas A.
2018-05-01
Core-electron binding energies (CEBEs) computed within a Δ self-consistent field approach require large basis sets to achieve convergence with respect to the basis set limit. It is shown that supplementing a basis set with basis functions from the corresponding basis set for the element with the next highest nuclear charge (Z + 1) provides basis sets that give CEBEs close to the basis set limit. This simple procedure provides relatively small basis sets that are well suited for calculations where the description of a core-ionised state is important, such as time-dependent density functional theory calculations of X-ray emission spectroscopy.
Interaction between IGFBP7 and insulin: a theoretical and experimental study
NASA Astrophysics Data System (ADS)
Ruan, Wenjing; Kang, Zhengzhong; Li, Youzhao; Sun, Tianyang; Wang, Lipei; Liang, Lijun; Lai, Maode; Wu, Tao
2016-04-01
Insulin-like growth factor binding protein 7 (IGFBP7) can bind to insulin with high affinity which inhibits the early steps of insulin action. Lack of recognition mechanism impairs our understanding of insulin regulation before it binds to insulin receptor. Here we combine computational simulations with experimental methods to investigate the interaction between IGFBP7 and insulin. Molecular dynamics simulations indicated that His200 and Arg198 in IGFBP7 were key residues. Verified by experimental data, the interaction remained strong in single mutation systems R198E and H200F but became weak in double mutation system R198E-H200F relative to that in wild-type IGFBP7. The results and methods in present study could be adopted in future research of discovery of drugs by disrupting protein-protein interactions in insulin signaling. Nevertheless, the accuracy, reproducibility, and costs of free-energy calculation are still problems that need to be addressed before computational methods can become standard binding prediction tools in discovery pipelines.
Incorporation of the TIP4P water model into a continuum solvent for computing solvation free energy
NASA Astrophysics Data System (ADS)
Yang, Pei-Kun
2014-10-01
The continuum solvent model is one of the commonly used strategies to compute solvation free energy especially for large-scale conformational transitions such as protein folding or to calculate the binding affinity of protein-protein/ligand interactions. However, the dielectric polarization for computing solvation free energy from the continuum solvent is different than that obtained from molecular dynamic simulations. To mimic the dielectric polarization surrounding a solute in molecular dynamic simulations, the first-shell water molecules was modeled using a charge distribution of TIP4P in a hard sphere; the time-averaged charge distribution from the first-shell water molecules were estimated based on the coordination number of the solute, and the orientation distribution of the first-shell waters and the intermediate water molecules were treated as that of a bulk solvent. Based on this strategy, an equation describing the solvation free energy of ions was derived.
Recovery of known T-cell epitopes by computational scanning of a viral genome
NASA Astrophysics Data System (ADS)
Logean, Antoine; Rognan, Didier
2002-04-01
A new computational method (EpiDock) is proposed for predicting peptide binding to class I MHC proteins, from the amino acid sequence of any protein of immunological interest. Starting from the primary structure of the target protein, individual three-dimensional structures of all possible MHC-peptide (8-, 9- and 10-mers) complexes are obtained by homology modelling. A free energy scoring function (Fresno) is then used to predict the absolute binding free energy of all possible peptides to the class I MHC restriction protein. Assuming that immunodominant epitopes are usually found among the top MHC binders, the method can thus be applied to predict the location of immunogenic peptides on the sequence of the protein target. When applied to the prediction of HLA-A*0201-restricted T-cell epitopes from the Hepatitis B virus, EpiDock was able to recover 92% of known high affinity binders and 80% of known epitopes within a filtered subset of all possible nonapeptides corresponding to about one tenth of the full theoretical list. The proposed method is fully automated and fast enough to scan a viral genome in less than an hour on a parallel computing architecture. As it requires very few starting experimental data, EpiDock can be used: (i) to predict potential T-cell epitopes from viral genomes (ii) to roughly predict still unknown peptide binding motifs for novel class I MHC alleles.
Ramezani-Dakhel, Hadi; Mirau, Peter A; Naik, Rajesh R; Knecht, Marc R; Heinz, Hendrik
2013-04-21
Surfactant-stabilized metal nanoparticles have shown promise as catalysts although specific surface features and their influence on catalytic performance have not been well understood. We quantify the thermodynamic stability, the facet composition of the surface, and distinct atom types that affect rates of atom leaching for a series of twenty near-spherical Pd nanoparticles of 1.8 to 3.1 nm size using computational models. Cohesive energies indicate higher stability of certain particles that feature an approximate 60/20/20 ratio of {111}, {100}, and {110} facets while less stable particles exhibit widely variable facet composition. Unique patterns of atom types on the surface cause apparent differences in binding energies and changes in reactivity. Estimates of the relative rate of atom leaching as a function of particle size were obtained by the summation of Boltzmann-weighted binding energies over all surface atoms. Computed leaching rates are in good qualitative correlation with the measured catalytic activity of peptide-stabilized Pd nanoparticles of the same shape and size in Stille coupling reactions. The agreement supports rate-controlling contributions by atom leaching in the presence of reactive substrates. The computational approach provides a pathway to estimate the catalytic activity of metal nanostructures of engineered shape and size, and possible further refinements are described.
Xu, Peng; Gordon, Mark S
2014-09-04
Anionic water clusters are generally considered to be extremely challenging to model using fragmentation approaches due to the diffuse nature of the excess electron distribution. The local correlation coupled cluster (CC) framework cluster-in-molecule (CIM) approach combined with the completely renormalized CR-CC(2,3) method [abbreviated CIM/CR-CC(2,3)] is shown to be a viable alternative for computing the vertical electron binding energies (VEBE). CIM/CR-CC(2,3) with the threshold parameter ζ set to 0.001, as a trade-off between accuracy and computational cost, demonstrates the reliability of predicting the VEBE, with an average percentage error of ∼15% compared to the full ab initio calculation at the same level of theory. The errors are predominantly from the electron correlation energy. The CIM/CR-CC(2,3) approach provides the ease of a black-box type calculation with few threshold parameters to manipulate. The cluster sizes that can be studied by high-level ab initio methods are significantly increased in comparison with full CC calculations. Therefore, the VEBE computed by the CIM/CR-CC(2,3) method can be used as benchmarks for testing model potential approaches in small-to-intermediate-sized water clusters.
NASA Astrophysics Data System (ADS)
Athanasiou, Christina; Vasilakaki, Sofia; Dellis, Dimitris; Cournia, Zoe
2018-01-01
Computer-aided drug design has become an integral part of drug discovery and development in the pharmaceutical and biotechnology industry, and is nowadays extensively used in the lead identification and lead optimization phases. The drug design data resource (D3R) organizes challenges against blinded experimental data to prospectively test computational methodologies as an opportunity for improved methods and algorithms to emerge. We participated in Grand Challenge 2 to predict the crystallographic poses of 36 Farnesoid X Receptor (FXR)-bound ligands and the relative binding affinities for two designated subsets of 18 and 15 FXR-bound ligands. Here, we present our methodology for pose and affinity predictions and its evaluation after the release of the experimental data. For predicting the crystallographic poses, we used docking and physics-based pose prediction methods guided by the binding poses of native ligands. For FXR ligands with known chemotypes in the PDB, we accurately predicted their binding modes, while for those with unknown chemotypes the predictions were more challenging. Our group ranked #1st (based on the median RMSD) out of 46 groups, which submitted complete entries for the binding pose prediction challenge. For the relative binding affinity prediction challenge, we performed free energy perturbation (FEP) calculations coupled with molecular dynamics (MD) simulations. FEP/MD calculations displayed a high success rate in identifying compounds with better or worse binding affinity than the reference (parent) compound. Our studies suggest that when ligands with chemical precedent are available in the literature, binding pose predictions using docking and physics-based methods are reliable; however, predictions are challenging for ligands with completely unknown chemotypes. We also show that FEP/MD calculations hold predictive value and can nowadays be used in a high throughput mode in a lead optimization project provided that crystal structures of sufficiently high quality are available.
Georgieva, I; Mihaylov, Tz; Trendafilova, N
2014-06-01
The present paper summarizes theoretical and spectroscopic investigations on a series of active coumarins and their lanthanide and transition metal complexes with application in medicine and pharmacy. Molecular modeling as well as IR, Raman, NMR and electronic spectral simulations at different levels of theory were performed to obtain important molecular descriptors: total energy, formation energy, binding energy, stability, conformations, structural parameters, electron density distribution, molecular electrostatic potential, Fukui functions, atomic charges, and reactive indexes. The computations are performed both in gas phase and in solution with consideration of the solvent effect on the molecular structural and energetic parameters. The investigations have shown that the advanced computational methods are reliable for prediction of the metal-coumarin binding mode, electron density distribution, thermodynamic properties as well as the strength and nature of the metal-coumarin interaction (not experimentally accessible) and correctly interpret the experimental spectroscopic data. Known results from biological tests for cytotoxic, antimicrobial, anti-fungal, spasmolytic and anti-HIV activities on the studied metal complexes are reported and discussed. Copyright © 2014 Elsevier Inc. All rights reserved.
Role of Electrostatics in Protein-RNA Binding: The Global vs the Local Energy Landscape.
Ghaemi, Zhaleh; Guzman, Irisbel; Gnutt, David; Luthey-Schulten, Zaida; Gruebele, Martin
2017-09-14
U1A protein-stem loop 2 RNA association is a basic step in the assembly of the spliceosomal U1 small nuclear ribonucleoprotein. Long-range electrostatic interactions due to the positive charge of U1A are thought to provide high binding affinity for the negatively charged RNA. Short range interactions, such as hydrogen bonds and contacts between RNA bases and protein side chains, favor a specific binding site. Here, we propose that electrostatic interactions are as important as local contacts in biasing the protein-RNA energy landscape toward a specific binding site. We show by using molecular dynamics simulations that deletion of two long-range electrostatic interactions (K22Q and K50Q) leads to mutant-specific alternative RNA bound states. One of these states preserves short-range interactions with aromatic residues in the original binding site, while the other one does not. We test the computational prediction with experimental temperature-jump kinetics using a tryptophan probe in the U1A-RNA binding site. The two mutants show the distinct predicted kinetic behaviors. Thus, the stem loop 2 RNA has multiple binding sites on a rough RNA-protein binding landscape. We speculate that the rough protein-RNA binding landscape, when biased to different local minima by electrostatics, could be one way that protein-RNA interactions evolve toward new binding sites and novel function.
Enhanced conformational sampling to visualize a free-energy landscape of protein complex formation
Iida, Shinji; Nakamura, Haruki; Higo, Junichi
2016-01-01
We introduce various, recently developed, generalized ensemble methods, which are useful to sample various molecular configurations emerging in the process of protein–protein or protein–ligand binding. The methods introduced here are those that have been or will be applied to biomolecular binding, where the biomolecules are treated as flexible molecules expressed by an all-atom model in an explicit solvent. Sampling produces an ensemble of conformations (snapshots) that are thermodynamically probable at room temperature. Then, projection of those conformations to an abstract low-dimensional space generates a free-energy landscape. As an example, we show a landscape of homo-dimer formation of an endothelin-1-like molecule computed using a generalized ensemble method. The lowest free-energy cluster at room temperature coincided precisely with the experimentally determined complex structure. Two minor clusters were also found in the landscape, which were largely different from the native complex form. Although those clusters were isolated at room temperature, with rising temperature a pathway emerged linking the lowest and second-lowest free-energy clusters, and a further temperature increment connected all the clusters. This exemplifies that the generalized ensemble method is a powerful tool for computing the free-energy landscape, by which one can discuss the thermodynamic stability of clusters and the temperature dependence of the cluster networks. PMID:27288028
Tight-Binding study of Boron structures
NASA Astrophysics Data System (ADS)
McGrady, Joseph W.; Papaconstantopoulos, Dimitrios A.; Mehl, Michael J.
2014-10-01
We have performed Linearized Augmented Plane Wave (LAPW) calculations for five crystal structures (alpha, dhcp, sc, fcc, bcc) of Boron which we then fitted to a non-orthogonal tight-binding model following the Naval Research Laboratory Tight-Binding (NRL-TB) method. The predictions of the NRL-TB approach for complicated Boron structures such as R105 (or β-rhombohedral) and T190 are in agreement with recent first-principles calculations. Fully utilizing the computational speed of the NRL-TB method we calculated the energy differences of various structures, including those containing vacancies using supercells with up to 5000 atoms.
Van Dornshuld, Eric; Holy, Christina M; Tschumper, Gregory S
2014-05-08
This work provides the first characterization of five stationary points of the homogeneous thioformaldehyde dimer, (CH2S)2, and seven stationary points of the heterogeneous formaldehyde/thioformaldehyde dimer, CH2O/CH2S, with correlated ab initio electronic structure methods. Full geometry optimizations and corresponding harmonic vibrational frequencies were computed with second-order Møller-Plesset perturbation theory (MP2) and 13 different density functionals in conjunction with triple-ζ basis sets augmented with diffuse and multiple sets of polarization functions. The MP2 results indicate that the three stationary points of (CH2S)2 and four of CH2O/CH2S are minima, in contrast to two stationary points of the formaldehyde dimer, (CH2O)2. Single-point energies were also computed using the explicitly correlated MP2-F12 and CCSD(T)-F12 methods and basis sets as large as heavy-aug-cc-pVTZ. The (CH2O)2 and CH2O/CH2S MP2 and MP2-F12 binding energies deviated from the CCSD(T)-F12 binding energies by no more than 0.2 and 0.4 kcal mol(-1), respectively. The (CH2O)2 and CH2O/CH2S global minimum is the same at every level of theory. However, the MP2 methods overbind (CH2S)2 by as much as 1.1 kcal mol(-1), effectively altering the energetic ordering of the thioformaldehyde dimer minima relative to the CCSD(T)-F12 energies. The CCSD(T)-F12 binding energies of the (CH2O)2 and CH2O/CH2S stationary points are quite similar, with the former ranging from around -2.4 to -4.6 kcal mol(-1) and the latter from about -1.1 to -4.4 kcal mol(-1). Corresponding (CH2S)2 stationary points have appreciably smaller CCSD(T)-F12 binding energies ranging from ca. -1.1 to -3.4 kcal mol(-1). The vibrational frequency shifts upon dimerization are also reported for each minimum on the MP2 potential energy surfaces.
Tang, Yat T; Marshall, Garland R
2011-02-28
Binding affinity prediction is one of the most critical components to computer-aided structure-based drug design. Despite advances in first-principle methods for predicting binding affinity, empirical scoring functions that are fast and only relatively accurate are still widely used in structure-based drug design. With the increasing availability of X-ray crystallographic structures in the Protein Data Bank and continuing application of biophysical methods such as isothermal titration calorimetry to measure thermodynamic parameters contributing to binding free energy, sufficient experimental data exists that scoring functions can now be derived by separating enthalpic (ΔH) and entropic (TΔS) contributions to binding free energy (ΔG). PHOENIX, a scoring function to predict binding affinities of protein-ligand complexes, utilizes the increasing availability of experimental data to improve binding affinity predictions by the following: model training and testing using high-resolution crystallographic data to minimize structural noise, independent models of enthalpic and entropic contributions fitted to thermodynamic parameters assumed to be thermodynamically biased to calculate binding free energy, use of shape and volume descriptors to better capture entropic contributions. A set of 42 descriptors and 112 protein-ligand complexes were used to derive functions using partial least-squares for change of enthalpy (ΔH) and change of entropy (TΔS) to calculate change of binding free energy (ΔG), resulting in a predictive r2 (r(pred)2) of 0.55 and a standard error (SE) of 1.34 kcal/mol. External validation using the 2009 version of the PDBbind "refined set" (n = 1612) resulted in a Pearson correlation coefficient (R(p)) of 0.575 and a mean error (ME) of 1.41 pK(d). Enthalpy and entropy predictions were of limited accuracy individually. However, their difference resulted in a relatively accurate binding free energy. While the development of an accurate and applicable scoring function was an objective of this study, the main focus was evaluation of the use of high-resolution X-ray crystal structures with high-quality thermodynamic parameters from isothermal titration calorimetry for scoring function development. With the increasing application of structure-based methods in molecular design, this study suggests that using high-resolution crystal structures, separating enthalpy and entropy contributions to binding free energy, and including descriptors to better capture entropic contributions may prove to be effective strategies toward rapid and accurate calculation of binding affinity.
Giannotti, Marina I; Cabeza de Vaca, Israel; Artés, Juan M; Sanz, Fausto; Guallar, Victor; Gorostiza, Pau
2015-09-10
The structural basis of the low reorganization energy of cupredoxins has long been debated. These proteins reconcile a conformationally heterogeneous and exposed metal-chelating site with the highly rigid copper center required for efficient electron transfer. Here we combine single-molecule mechanical unfolding experiments with statistical analysis and computer simulations to show that the metal-binding region of apo-azurin is mechanically flexible and that high mechanical stability is imparted by copper binding. The unfolding pathway of the metal site depends on the pulling residue and suggests that partial unfolding of the metal-binding site could be facilitated by the physical interaction with certain regions of the redox protein.
Free energy of a heavy quark-antiquark pair in a thermal medium from AdS/CFT
NASA Astrophysics Data System (ADS)
Ewerz, Carlo; Kaczmarek, Olaf; Samberg, Andreas
2018-03-01
We study the free energy of a heavy quark-antiquark pair in a thermal medium using the AdS/CFT correspondence. We point out that a commonly used prescription for calculating this quantity leads to a temperature dependence in conflict with general properties of the free energy. The problem originates from a particular way of subtracting divergences. We argue that the commonly used prescription gives rise to the binding energy rather than the free energy. We consider a different subtraction procedure and show that the resulting free energy is well-behaved and in qualitative agreement with results from lattice QCD. The free energy and the binding energy of the quark pair are computed for N=4 supersymmetric Yang-Mills theory and several non-conformal theories. We also calculate the entropy and the internal energy of the pair in these theories. Using the consistent subtraction, we further study the free energy, entropy, and internal energy of a single heavy quark in the thermal medium for various theories. Also here the results are found to be in qualitative agreement with lattice QCD results.
Umadevi, Deivasigamani; Narahari Sastry, G
2015-11-11
Graphane has emerged as a two-dimensional hydrocarbon with interesting physical properties and potential applications. Understanding the interaction of graphane with various molecules and ions is crucial to appreciate its potential applications. We investigated the interaction of nucleobases, aminoacids, saturated and unsaturated heterocycles, small molecules, metal ions and onium ions with graphane by using density functional theory calculations. The preferred orientations of these molecules and ions on the graphane surface have been analysed. The binding energies of graphane with these molecules have been compared with the corresponding binding energies of graphene. Our results reveal that graphane forms stable complexes with all the molecules and ions yet showing lesser binding affinity when compared to graphene. As an exemption, the preferential strong binding of H2O with graphane than graphene reveals the fact that graphane is more hydrophilic than graphene. Charge transfer between graphane and the molecules and ions have been found to be an important factor in determining the binding strength of the complexes. The effect of the interaction of these molecules and ions on the HOMO-LUMO energy gap of graphane has also been investigated.
The Movable Type Method Applied to Protein-Ligand Binding.
Zheng, Zheng; Ucisik, Melek N; Merz, Kenneth M
2013-12-10
Accurately computing the free energy for biological processes like protein folding or protein-ligand association remains a challenging problem. Both describing the complex intermolecular forces involved and sampling the requisite configuration space make understanding these processes innately difficult. Herein, we address the sampling problem using a novel methodology we term "movable type". Conceptually it can be understood by analogy with the evolution of printing and, hence, the name movable type. For example, a common approach to the study of protein-ligand complexation involves taking a database of intact drug-like molecules and exhaustively docking them into a binding pocket. This is reminiscent of early woodblock printing where each page had to be laboriously created prior to printing a book. However, printing evolved to an approach where a database of symbols (letters, numerals, etc.) was created and then assembled using a movable type system, which allowed for the creation of all possible combinations of symbols on a given page, thereby, revolutionizing the dissemination of knowledge. Our movable type (MT) method involves the identification of all atom pairs seen in protein-ligand complexes and then creating two databases: one with their associated pairwise distant dependent energies and another associated with the probability of how these pairs can combine in terms of bonds, angles, dihedrals and non-bonded interactions. Combining these two databases coupled with the principles of statistical mechanics allows us to accurately estimate binding free energies as well as the pose of a ligand in a receptor. This method, by its mathematical construction, samples all of configuration space of a selected region (the protein active site here) in one shot without resorting to brute force sampling schemes involving Monte Carlo, genetic algorithms or molecular dynamics simulations making the methodology extremely efficient. Importantly, this method explores the free energy surface eliminating the need to estimate the enthalpy and entropy components individually. Finally, low free energy structures can be obtained via a free energy minimization procedure yielding all low free energy poses on a given free energy surface. Besides revolutionizing the protein-ligand docking and scoring problem this approach can be utilized in a wide range of applications in computational biology which involve the computation of free energies for systems with extensive phase spaces including protein folding, protein-protein docking and protein design.
Rui, Huan; Artigas, Pablo; Roux, Benoît
2016-01-01
The Na+/K+-pump maintains the physiological K+ and Na+ electrochemical gradients across the cell membrane. It operates via an 'alternating-access' mechanism, making iterative transitions between inward-facing (E1) and outward-facing (E2) conformations. Although the general features of the transport cycle are known, the detailed physicochemical factors governing the binding site selectivity remain mysterious. Free energy molecular dynamics simulations show that the ion binding sites switch their binding specificity in E1 and E2. This is accompanied by small structural arrangements and changes in protonation states of the coordinating residues. Additional computations on structural models of the intermediate states along the conformational transition pathway reveal that the free energy barrier toward the occlusion step is considerably increased when the wrong type of ion is loaded into the binding pocket, prohibiting the pump cycle from proceeding forward. This self-correcting mechanism strengthens the overall transport selectivity and protects the stoichiometry of the pump cycle. DOI: http://dx.doi.org/10.7554/eLife.16616.001 PMID:27490484
Kandeel, Mahmoud; Kitade, Yukio
2013-07-01
RNA interference (RNAi) is a critical cellular pathway activated by double stranded RNA and regulates the gene expression of target mRNA. During RNAi, the 3' end of siRNA binds with the PAZ domain, followed by release and rebinding in a cyclic manner, which deemed essential for proper gene silencing. Recently, we provided the forces underlying the recognition of small interfering RNA by PAZ in a computational study based on the structure of Drosophila Argonaute 2 (Ago2) PAZ domain. We have now reanalyzed these data within the view of the new available structures from human Argonauts. While the parameters of weak binding are correlated with higher (RNAi) in the Drosophila model, a different profile is predicted with the human Ago2 PAZ domain. On the basis of the human Ago2 PAZ models, the indicators of stronger binding as the total binding energy and the free energy were associated with better RNAi efficacy. This discrepancy might be attributable to differences in the binding site topology and the difference in the conformation of the bound nucleotides.
Hernández González, Jorge Enrique; Hernández Alvarez, Lilian; Pascutti, Pedro Geraldo; Valiente, Pedro A
2017-09-01
Falcipain-2 (FP-2) is a major hemoglobinase of Plasmodium falciparum, considered an important drug target for the development of antimalarials. A previous study reported a novel series of 20 reversible peptide-based inhibitors of FP-2. However, the lack of tridimensional structures of the complexes hinders further optimization strategies to enhance the inhibitory activity of the compounds. Here we report the prediction of the binding modes of the aforementioned inhibitors to FP-2. A computational approach combining previous knowledge on the determinants of binding to the enzyme, docking, and postdocking refinement steps, is employed. The latter steps comprise molecular dynamics simulations and free energy calculations. Remarkably, this approach leads to the identification of near-native ligand conformations when applied to a validation set of protein-ligand structures. Overall, we proposed substrate-like binding modes of the studied compounds fulfilling the structural requirements for FP-2 binding and yielding free energy values that correlated well with the experimental data. Proteins 2017; 85:1666-1683. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Computational modeling of carbohydrate recognition in protein complex
NASA Astrophysics Data System (ADS)
Ishida, Toyokazu
2017-11-01
To understand the mechanistic principle of carbohydrate recognition in proteins, we propose a systematic computational modeling strategy to identify complex carbohydrate chain onto the reduced 2D free energy surface (2D-FES), determined by MD sampling combined with QM/MM energy corrections. In this article, we first report a detailed atomistic simulation study of the norovirus capsid proteins with carbohydrate antigens based on ab initio QM/MM combined with MD-FEP simulations. The present result clearly shows that the binding geometries of complex carbohydrate antigen are determined not by one single, rigid carbohydrate structure, but rather by the sum of averaged conformations mapped onto the minimum free energy region of QM/MM 2D-FES.
Hao, Ge-Fei; Yang, Sheng-Gang; Huang, Wei; Wang, Le; Shen, Yan-Qing; Tu, Wen-Long; Li, Hui; Huang, Li-Shar; Wu, Jia-Wei; Berry, Edward A.; Yang, Guang-Fu
2015-01-01
Hit to lead (H2L) optimization is a key step for drug and agrochemical discovery. A critical challenge for H2L optimization is the low efficiency due to the lack of predictive method with high accuracy. We described a new computational method called Computational Substitution Optimization (CSO) that has allowed us to rapidly identify compounds with cytochrome bc1 complex inhibitory activity in the nanomolar and subnanomolar range. The comprehensively optimized candidate has proved to be a slow binding inhibitor of bc1 complex, ~73-fold more potent (Ki = 4.1 nM) than the best commercial fungicide azoxystrobin (AZ; Ki = 297.6 nM) and shows excellent in vivo fungicidal activity against downy mildew and powdery mildew disease. The excellent correlation between experimental and calculated binding free-energy shifts together with further crystallographic analysis confirmed the prediction accuracy of CSO method. To the best of our knowledge, CSO is a new computational approach to substitution-scanning mutagenesis of ligand and could be used as a general strategy of H2L optimisation in drug and agrochemical design.
NASA Astrophysics Data System (ADS)
Mey, Antonia S. J. S.; Jiménez, Jordi Juárez; Michel, Julien
2018-01-01
The Drug Design Data Resource (D3R) consortium organises blinded challenges to address the latest advances in computational methods for ligand pose prediction, affinity ranking, and free energy calculations. Within the context of the second D3R Grand Challenge several blinded binding free energies predictions were made for two congeneric series of Farsenoid X Receptor (FXR) inhibitors with a semi-automated alchemical free energy calculation workflow featuring FESetup and SOMD software tools. Reasonable performance was observed in retrospective analyses of literature datasets. Nevertheless, blinded predictions on the full D3R datasets were poor due to difficulties encountered with the ranking of compounds that vary in their net-charge. Performance increased for predictions that were restricted to subsets of compounds carrying the same net-charge. Disclosure of X-ray crystallography derived binding modes maintained or improved the correlation with experiment in a subsequent rounds of predictions. The best performing protocols on D3R set1 and set2 were comparable or superior to predictions made on the basis of analysis of literature structure activity relationships (SAR)s only, and comparable or slightly inferior, to the best submissions from other groups.
Liu, Fengjiao; Zhang, John Z H; Mei, Ye
2016-06-01
Previous experimental study measuring the binding affinities of biotin to the wild type streptavidin (WT) and three mutants (S45A, D128A and S45A/D128A double mutant) has shown that the loss of binding affinity from the double mutation is larger than the direct sum of those from two single mutations. The origin of this cooperativity has been investigated in this work through molecular dynamics simulations and the end-state free energy method using the polarized protein-specific charge. The results show that this cooperativity comes from both the enthalpy and entropy contributions. The former contribution mainly comes from the alternations of solvation free energy. Decomposition analysis shows that the mutated residues nearly have no contributions to the cooperativity. Instead, N49 and S88, which are located at the entry of the binding pocket and interact with the carboxyl group of biotin, make the dominant contribution among all the residues in the first binding shell around biotin.
NASA Astrophysics Data System (ADS)
Liu, Fengjiao; Zhang, John Z. H.; Mei, Ye
2016-06-01
Previous experimental study measuring the binding affinities of biotin to the wild type streptavidin (WT) and three mutants (S45A, D128A and S45A/D128A double mutant) has shown that the loss of binding affinity from the double mutation is larger than the direct sum of those from two single mutations. The origin of this cooperativity has been investigated in this work through molecular dynamics simulations and the end-state free energy method using the polarized protein-specific charge. The results show that this cooperativity comes from both the enthalpy and entropy contributions. The former contribution mainly comes from the alternations of solvation free energy. Decomposition analysis shows that the mutated residues nearly have no contributions to the cooperativity. Instead, N49 and S88, which are located at the entry of the binding pocket and interact with the carboxyl group of biotin, make the dominant contribution among all the residues in the first binding shell around biotin.
Beletskiy, Evgeny V; Wang, Xue-Bin; Kass, Steven Robert
2016-10-05
A benzene ring substituted with 1-3 thiourea containing arms (1-3) were examined by photoelectron spectroscopy and density functional theory computations. Their conjugate bases and chloride, acetate and dihydrogen phosphate anion clusters are reported. The resulting vertical and adiabatic detachment energies span from 3.93 - 5.82 eV (VDE) and 3.65 - 5.10 (ADE) for the deprotonated species and 4.88 - 5.97 eV (VDE) and 4.45 - 5.60 eV (ADE) for the anion complexes. These results reveal the stabilizing effects of multiple hydrogen bonds and anionic host-guest interactions in the gas phase. Previously measured equilibrium binding constants in aqueous dimethyl sulfoxide for all three thioureas are compared to the present results and cooperative binding is uniformly observed in the gas phase but only for one case (i.e., 3 • H2PO4-) in solution.
Rapid calculation method for Frenkel-type two-exciton states in one to three dimensions
NASA Astrophysics Data System (ADS)
Ajiki, Hiroshi
2014-07-01
Biexciton and two-exciton dissociated states of Frenkel-type excitons are well described by a tight-binding model with a nearest-neighbor approximation. Such two-exciton states in a finite-size lattice are usually calculated by numerical diagonalization of the Hamiltonian, which requires an increasing amount of computational time and memory as the lattice size increases. I develop here a rapid, memory-saving method to calculate the energies and wave functions of two-exciton states by employing a bisection method. In addition, an attractive interaction between two excitons in the tight-binding model can be obtained directly so that the biexciton energy agrees with the observed energy, without the need for the trial-and-error procedure implemented in the numerical diagonalization method.
Ivanisenko, Nikita V; Tregubchak, Tatiana V; Saik, Olga V; Ivanisenko, Vladimir A; Shchelkunov, Sergei N
2014-01-01
Inhibition of the activity of the tumor necrosis factor (TNF) has become the main strategy for treating inflammatory diseases. The orthopoxvirus TNF-binding proteins can bind and efficiently neutralize TNF. To analyze the mechanisms of the interaction between human (hTNF) or mouse (mTNF) TNF and the cowpox virus N-terminal binding domain (TNFBD-CPXV), also the variola virus N-terminal binding domain (TNFBD-VARV) and to define the amino acids most importantly involved in the formation of complexes, computer models, derived from the X-ray structure of a homologous hTNF/TNFRII complex, were used together with experiments. The hTNF/TNFBD-CPXV, hTNF/TNFBD-VARV, mTNF/TNFBD-CPXV, and mTNF/TNFBD-VARV complexes were used in the molecular dynamics (MD) simulations and MM/GBSA free energy calculations. The complexes were ordered as hTNF/TNFBD-CPXV, hTNF/TNFBD-VARV, mTNF/TNFBD-CPXV and mTNF/TNFBD-VARV according to increase in the binding affinity. The calculations were in agreement with surface plasmon resonance (SPR) measurements of the binding constants. Key residues involved in complex formation were identified.
Fadda, Elisa; Woods, Robert J
2011-10-11
The ability of ligands to displace conserved water molecules in protein binding sites is of significant interest in drug design and is particularly pertinent in the case of glycomimetic drugs. This concept was explored in previous work [ Clarke et al. J. Am. Chem. Soc. 2001 , 123 , 12238 - 12247 and Kadirvelraj et al. J. Am. Chem. Soc. 2008 , 130 , 16933 - 16942 ] for a highly conserved water molecule located in the binding site of the prototypic carbohydrate-binding protein Concanavalin A (Con A). A synthetic ligand was designed with the aim of displacing such water. While the synthetic ligand bound to Con A in an analogous manner to that of the natural ligand, crystallographic analysis demonstrated that it did not displace the conserved water. In order to quantify the affinity of this particular water for the Con A surface, we report here the calculated standard binding free energy for this water in both ligand-bound and free Con A, employing three popular water models: TIP3P, TIP4P, and TIP5P. Although each model was developed to perform well in simulations of bulk-phase water, the computed binding energies for the isolated water molecule displayed a high sensitivity to the model. Both molecular dynamics simulation and free energy results indicate that the choice of water model may greatly influence the characterization of surface water molecules as conserved (TIP5P) or not (TIP3P) in protein binding sites, an observation of considerable significance to rational drug design. Structural and theoretical aspects at the basis of the different behaviors are identified and discussed.
Kaufmann, Kristian W.; Dawson, Eric S.; Henry, L. Keith; Field, Julie R.; Blakely, Randy D.; Meiler, Jens
2009-01-01
To identify potential determinants of substrate selectivity in serotonin (5-HT) transporters (SERT), models of human and Drosophila serotonin transporters (hSERT, dSERT) were built based on the leucine transporter (LeuTAa) structure reported by Yamashita et al. (Nature 2005;437:215–223), PBDID 2A65. Although the overall amino acid identity between SERTs and the LeuTAa is only 17%, it increases to above 50% in the first shell of the putative 5-HT binding site, allowing de novo computational docking of tryptamine derivatives in atomic detail. Comparison of hSERT and dSERT complexed with substrates pinpoints likely structural determinants for substrate binding. Forgoing the use of experimental transport and binding data of tryptamine derivatives for construction of these models enables us to cHitically assess and validate their predictive power: A single 5-HT binding mode was identified that retains the amine placement observed in the LeuTAa structure, matches site-directed mutagenesis and substituted cysteine accessibility method (SCAM) data, complies with support vector machine derived relations activity relations, and predicts computational binding energies for 5-HT analogs with a significant correlation coefficient (R = 0.72). This binding mode places 5-HT deep in the binding pocket of the SERT with the 5-position near residue hSERT A169/dSERT D164 in transmembrane helix 3, the indole nitrogen next to residue Y176/Y171, and the ethylamine tail under residues F335/F327 and S336/S328 within 4 Å of residue D98. Our studies identify a number of potential contacts whose contribution to substrate binding and transport was previously unsuspected. PMID:18704946
Bayden, Alexander S.; Fornabaio, Micaela; Scarsdale, J. Neel
2009-01-01
A public web server performing computational titration at the active site in a protein-ligand complex has been implemented. This calculation is based on the Hydropathic INTeraction (HINT) noncovalent force field. From 3D coordinate data for the protein, ligand and bridging waters (if available), the server predicts the best combination of protonation states for each ionizable residue and/or ligand functional group as well as the Gibbs free energy of binding for the ionization-optimized protein-ligand complex. The 3D structure for the modified molecules is available as output. In addition, a graph depicting how this energy changes with acidity, i.e., as a function of added protons, can be obtained. This data may prove to be of use in preparing models for virtual screening and molecular docking. A few illustrative examples are presented. In β secretase (2va7) computational titration flipped the amide groups of Gln12 and Asn37 and protonated a ligand amine yielding an improvement of 6.37 kcal mol−1 in the protein-ligand binding score. Protonation of Glu139 in mutant HIV-1 reverse transcriptase (2opq) allows a water bridge between the protein and inhibitor that increases the protein-ligand interaction score by 0.16 kcal mol−1. In human sialidase NEU2 complexed with an isobutyl ether mimetic inhibitor (2f11) computational titration suggested that protonating Glu218, deprotonating Arg237, flipping the amide bond on Tyr334, and optimizing the positions of several other polar protons would increase the protein-ligand interaction score by 0.71 kcal mol−1. PMID:19554265
Effect of magnetic field on the donor impurity in CdTe/Cd1-xMnxTe quantum well wire
NASA Astrophysics Data System (ADS)
Kalpana, P.; Reuben, A. Merwyn Jasper D.; Nithiananthi, P.; Jayakumar, K.
2016-05-01
The donor impurity binding energy in CdTe / Cd1-xMnxTe QWW with square well confinement along x - direction and parabolic confinement along y - direction under the influence of externally applied magnetic field has been computed using variational principle in the effective mass approximation. The spin polaronic shift has also been computed. The results are presented and discussed.
Zou, Yi; Wang, Fang; Wang, Yan; Guo, Wenjie; Zhang, Yihua; Xu, Qiang; Lai, Yisheng
2017-05-05
Indoleamine 2,3-dioxygenase 1 (IDO1) is regarded as an attractive target for cancer immunotherapy. To rationalize the detailed interactions between IDO1 and its inhibitors at the atomic level, an integrated computational approach by combining molecular mechanics and quantum mechanics methods was employed in this report. Specifically, the binding modes of 20 inhibitors was initially investigated using the induced fit docking (IFD) protocol, which outperformed other two docking protocols in terms of correctly predicting ligand conformations. Secondly, molecular dynamics (MD) simulations and MM/PBSA free energy calculations were employed to determine the dynamic binding process and crucial residues were confirmed through close contact analysis, hydrogen-bond analysis and binding free energy decomposition calculations. Subsequent quantum mechanics and nonbonding interaction analysis were carried out to provide in-depth explanations on the critical role of those key residues, and Arg231 and 7-propionate of the heme group were major contributors to ligand binding, which lowed a great amount of interaction energy. We anticipate that these findings will be valuable for enzymatic studies and rational drug design. Copyright © 2017. Published by Elsevier Masson SAS.
Intrinsically Disordered Energy Landscapes
Chebaro, Yassmine; Ballard, Andrew J.; Chakraborty, Debayan; Wales, David J.
2015-01-01
Analysis of an intrinsically disordered protein (IDP) reveals an underlying multifunnel structure for the energy landscape. We suggest that such ‘intrinsically disordered’ landscapes, with a number of very different competing low-energy structures, are likely to characterise IDPs, and provide a useful way to address their properties. In particular, IDPs are present in many cellular protein interaction networks, and several questions arise regarding how they bind to partners. Are conformations resembling the bound structure selected for binding, or does further folding occur on binding the partner in a induced-fit fashion? We focus on the p53 upregulated modulator of apoptosis (PUMA) protein, which adopts an -helical conformation when bound to its partner, and is involved in the activation of apoptosis. Recent experimental evidence shows that folding is not necessary for binding, and supports an induced-fit mechanism. Using a variety of computational approaches we deduce the molecular mechanism behind the instability of the PUMA peptide as a helix in isolation. We find significant barriers between partially folded states and the helix. Our results show that the favoured conformations are molten-globule like, stabilised by charged and hydrophobic contacts, with structures resembling the bound state relatively unpopulated in equilibrium. PMID:25999294
Hassanzadeh, Malihe; Bagherzadeh, Kowsar; Amanlou, Massoud
2016-11-01
Nowadays the ability to prediction of complex behavior rationally based on the computational approaches has been a successful technique in drug discovery. In the present study interactions of a new series of hybrids, which were made by linking colchicine as a tubulin inhibitor and suberoylanilide hydroxamic acid (SAHA) as a HDAC inhibitor, with HDAC8 and HDAC1 were investigated and compared. This research has been facilitated by the availability of experimental information besides employing docking methodology as well as classical molecular dynamics simulations and binding free energy calculation were performed. The obtained findings indicate different modes of interactions and inhibition strengths of the studied inhibitors for HDAC8 and HDAC1. HDAC8 binding free energies (-34.35 to -26.27kcal/mol) revealed higher binding affinity to HDAC8 compared to HDAC1 (-33.17 to -7.99kcal/mol). The binding energy contribution of each residue with the hybrid compounds 4a-4e within the active site of HDAC1 and HDAC8 was analyzed and the results confirmed the rule of key amino acids in interaction with the hybrid compounds. Copyright © 2016 Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mallory, Joel D.; Mandelshtam, Vladimir A.
2015-10-14
The diffusion Monte Carlo (DMC) method is applied to compute the ground state energies of the water monomer and dimer and their D{sub 2}O isotopomers using MB-pol; the most recent and most accurate ab inito-based potential energy surface (PES). MB-pol has already demonstrated excellent agreement with high level electronic structure data, as well as agreement with some experimental, spectroscopic, and thermodynamic data. Here, the DMC binding energies of (H{sub 2}O){sub 2} and (D{sub 2}O){sub 2} agree with the corresponding values obtained from velocity map imaging within, respectively, 0.01 and 0.02 kcal/mol. This work adds two more valuable data points thatmore » highlight the accuracy of the MB-pol PES.« less
Wang, Jinan; Shao, Qiang; Xu, Zhijian; Liu, Yingtao; Yang, Zhuo; Cossins, Benjamin P; Jiang, Hualiang; Chen, Kaixian; Shi, Jiye; Zhu, Weiliang
2014-01-09
Large-scale conformational changes of proteins are usually associated with the binding of ligands. Because the conformational changes are often related to the biological functions of proteins, understanding the molecular mechanisms of these motions and the effects of ligand binding becomes very necessary. In the present study, we use the combination of normal-mode analysis and umbrella sampling molecular dynamics simulation to delineate the atomically detailed conformational transition pathways and the associated free-energy landscapes for three well-known protein systems, viz., adenylate kinase (AdK), calmodulin (CaM), and p38α kinase in the absence and presence of respective ligands. For each protein under study, the transient conformations along the conformational transition pathway and thermodynamic observables are in agreement with experimentally and computationally determined ones. The calculated free-energy profiles reveal that AdK and CaM are intrinsically flexible in structures without obvious energy barrier, and their ligand binding shifts the equilibrium from the ligand-free to ligand-bound conformation (population shift mechanism). In contrast, the ligand binding to p38α leads to a large change in free-energy barrier (ΔΔG ≈ 7 kcal/mol), promoting the transition from DFG-in to DFG-out conformation (induced fit mechanism). Moreover, the effect of the protonation of D168 on the conformational change of p38α is also studied, which reduces the free-energy difference between the two functional states of p38α and thus further facilitates the conformational interconversion. Therefore, the present study suggests that the detailed mechanism of ligand binding and the associated conformational transition is not uniform for all kinds of proteins but correlated to their respective biological functions.
Proposed Mode of Binding and Action of Positive Allosteric Modulators at Opioid Receptors
2016-01-01
Available crystal structures of opioid receptors provide a high-resolution picture of ligand binding at the primary (“orthosteric”) site, that is, the site targeted by endogenous ligands. Recently, positive allosteric modulators of opioid receptors have also been discovered, but their modes of binding and action remain unknown. Here, we use a metadynamics-based strategy to efficiently sample the binding process of a recently discovered positive allosteric modulator of the δ-opioid receptor, BMS-986187, in the presence of the orthosteric agonist SNC-80, and with the receptor embedded in an explicit lipid–water environment. The dynamics of BMS-986187 were enhanced by biasing the potential acting on the ligand–receptor distance and ligand–receptor interaction contacts. Representative lowest-energy structures from the reconstructed free-energy landscape revealed two alternative ligand binding poses at an allosteric site delineated by transmembrane (TM) helices TM1, TM2, and TM7, with some participation of TM6. Mutations of amino acid residues at these proposed allosteric sites were found to either affect the binding of BMS-986187 or its ability to modulate the affinity and/or efficacy of SNC-80. Taken together, these combined experimental and computational studies provide the first atomic-level insight into the modulation of opioid receptor binding and signaling by allosteric modulators. PMID:26841170
NASA Astrophysics Data System (ADS)
Rosenfeld, Robin J.; Goodsell, David S.; Musah, Rabi A.; Morris, Garrett M.; Goodin, David B.; Olson, Arthur J.
2003-08-01
The W191G cavity of cytochrome c peroxidase is useful as a model system for introducing small molecule oxidation in an artificially created cavity. A set of small, cyclic, organic cations was previously shown to bind in the buried, solvent-filled pocket created by the W191G mutation. We docked these ligands and a set of non-binders in the W191G cavity using AutoDock 3.0. For the ligands, we compared docking predictions with experimentally determined binding energies and X-ray crystal structure complexes. For the ligands, predicted binding energies differed from measured values by ± 0.8 kcal/mol. For most ligands, the docking simulation clearly predicted a single binding mode that matched the crystallographic binding mode within 1.0 Å RMSD. For 2 ligands, where the docking procedure yielded an ambiguous result, solutions matching the crystallographic result could be obtained by including an additional crystallographically observed water molecule in the protein model. For the remaining 2 ligands, docking indicated multiple binding modes, consistent with the original electron density, suggesting disordered binding of these ligands. Visual inspection of the atomic affinity grid maps used in docking calculations revealed two patches of high affinity for hydrogen bond donating groups. Multiple solutions are predicted as these two sites compete for polar hydrogens in the ligand during the docking simulation. Ligands could be distinguished, to some extent, from non-binders using a combination of two trends: predicted binding energy and level of clustering. In summary, AutoDock 3.0 appears to be useful in predicting key structural and energetic features of ligand binding in the W191G cavity.
Grasso, Gianvito; Deriu, Marco Agostino; Patrulea, Viorica; Borchard, Gerrit; Möller, Michael; Danani, Andrea
2017-01-01
The success of medical threatments with DNA and silencing interference RNA is strongly related to the design of efficient delivery technologies. Cationic polymers represent an attractive strategy to serve as nucleic-acid carriers with the envisioned advantages of efficient complexation, low cost, ease of production, well-defined size, and low polydispersity index. However, the balance between efficacy and toxicity (safety) of these polymers is a challenge and in need of improvement. With the aim of designing more effective polycationic-based gene carriers, many parameters such as carrier morphology, size, molecular weight, surface chemistry, and flexibility/rigidity ratio need to be taken into consideration. In the present work, the binding mechanism of three cationic polymers (polyarginine, polylysine and polyethyleneimine) to a model siRNA target is computationally investigated at the atomistic level. In order to better understand the polycationic carrier-siRNA interactions, replica exchange molecular dynamic simulations were carried out to provide an exhaustive exploration of all the possible binding sites, taking fully into account the siRNA flexibility together with the presence of explicit solvent and ions. Moreover, well-tempered metadynamics simulations were employed to elucidate how molecular geometry, polycation flexibility, and charge neutralization affect the siRNA-polycations free energy landscape in term of low-energy binding modes and unbinding free energy barriers. Significant differences among polymer binding modes have been detected, revealing the advantageous binding properties of polyarginine and polylysine compared to polyethyleneimine.
Patrulea, Viorica; Borchard, Gerrit; Möller, Michael; Danani, Andrea
2017-01-01
The success of medical threatments with DNA and silencing interference RNA is strongly related to the design of efficient delivery technologies. Cationic polymers represent an attractive strategy to serve as nucleic-acid carriers with the envisioned advantages of efficient complexation, low cost, ease of production, well-defined size, and low polydispersity index. However, the balance between efficacy and toxicity (safety) of these polymers is a challenge and in need of improvement. With the aim of designing more effective polycationic-based gene carriers, many parameters such as carrier morphology, size, molecular weight, surface chemistry, and flexibility/rigidity ratio need to be taken into consideration. In the present work, the binding mechanism of three cationic polymers (polyarginine, polylysine and polyethyleneimine) to a model siRNA target is computationally investigated at the atomistic level. In order to better understand the polycationic carrier-siRNA interactions, replica exchange molecular dynamic simulations were carried out to provide an exhaustive exploration of all the possible binding sites, taking fully into account the siRNA flexibility together with the presence of explicit solvent and ions. Moreover, well-tempered metadynamics simulations were employed to elucidate how molecular geometry, polycation flexibility, and charge neutralization affect the siRNA-polycations free energy landscape in term of low-energy binding modes and unbinding free energy barriers. Significant differences among polymer binding modes have been detected, revealing the advantageous binding properties of polyarginine and polylysine compared to polyethyleneimine. PMID:29088239
Using the Concept of Transient Complex for Affinity Predictions in CAPRI Rounds 20–27 and Beyond
Qin, Sanbo; Zhou, Huan-Xiang
2013-01-01
Predictions of protein-protein binders and binding affinities have traditionally focused on features pertaining to the native complexes. In developing a computational method for predicting protein-protein association rate constants, we introduced the concept of transient complex after mapping the interaction energy surface. The transient complex is located at the outer boundary of the bound-state energy well, having near-native separation and relative orientation between the subunits but not yet formed most of the short-range native interactions. We found that the width of the binding funnel and the electrostatic interaction energy of the transient complex are among the features predictive of binders and binding affinities. These ideas were very promising for the five affinity-related targets (T43–45, 55, and 56) of CAPRI rounds 20–27. For T43, we ranked the single crystallographic complex as number 1 and were one of only two groups that clearly identified that complex as a true binder; for T44, we ranked the only design with measurable binding affinity as number 4. For the nine docking targets, continuing on our success in previous CAPRI rounds, we produced 10 medium-quality models for T47 and acceptable models for T48 and T49. We conclude that the interaction energy landscape and the transient complex in particular will complement existing features in leading to better prediction of binding affinities. PMID:23873496
High performance transcription factor-DNA docking with GPU computing
2012-01-01
Background Protein-DNA docking is a very challenging problem in structural bioinformatics and has important implications in a number of applications, such as structure-based prediction of transcription factor binding sites and rational drug design. Protein-DNA docking is very computational demanding due to the high cost of energy calculation and the statistical nature of conformational sampling algorithms. More importantly, experiments show that the docking quality depends on the coverage of the conformational sampling space. It is therefore desirable to accelerate the computation of the docking algorithm, not only to reduce computing time, but also to improve docking quality. Methods In an attempt to accelerate the sampling process and to improve the docking performance, we developed a graphics processing unit (GPU)-based protein-DNA docking algorithm. The algorithm employs a potential-based energy function to describe the binding affinity of a protein-DNA pair, and integrates Monte-Carlo simulation and a simulated annealing method to search through the conformational space. Algorithmic techniques were developed to improve the computation efficiency and scalability on GPU-based high performance computing systems. Results The effectiveness of our approach is tested on a non-redundant set of 75 TF-DNA complexes and a newly developed TF-DNA docking benchmark. We demonstrated that the GPU-based docking algorithm can significantly accelerate the simulation process and thereby improving the chance of finding near-native TF-DNA complex structures. This study also suggests that further improvement in protein-DNA docking research would require efforts from two integral aspects: improvement in computation efficiency and energy function design. Conclusions We present a high performance computing approach for improving the prediction accuracy of protein-DNA docking. The GPU-based docking algorithm accelerates the search of the conformational space and thus increases the chance of finding more near-native structures. To the best of our knowledge, this is the first ad hoc effort of applying GPU or GPU clusters to the protein-DNA docking problem. PMID:22759575
Plazinska, Anita; Plazinski, Wojciech; Jozwiak, Krzysztof
2014-04-30
The computational approach applicable for the molecular dynamics (MD)-based techniques is proposed to predict the ligand-protein binding affinities dependent on the ligand stereochemistry. All possible stereoconfigurations are expressed in terms of one set of force-field parameters [stereoconfiguration-independent potential (SIP)], which allows for calculating all relative free energies by only single simulation. SIP can be used for studying diverse, stereoconfiguration-dependent phenomena by means of various computational techniques of enhanced sampling. The method has been successfully tested on the β2-adrenergic receptor (β2-AR) binding the four fenoterol stereoisomers by both metadynamics simulations and replica-exchange MD. Both the methods gave very similar results, fully confirming the presence of stereoselective effects in the fenoterol-β2-AR interactions. However, the metadynamics-based approach offered much better efficiency of sampling which allows for significant reduction of the unphysical region in SIP. Copyright © 2014 Wiley Periodicals, Inc.
Continuum Electrostatics Approaches to Calculating pKas and Ems in Proteins
Gunner, MR; Baker, Nathan A.
2017-01-01
Proteins change their charge state through protonation and redox reactions as well as through binding charged ligands. The free energy of these reactions are dominated by solvation and electrostatic energies and modulated by protein conformational relaxation in response to the ionization state changes. Although computational methods for calculating these interactions can provide very powerful tools for predicting protein charge states, they include several critical approximations of which users should be aware. This chapter discusses the strengths, weaknesses, and approximations of popular computational methods for predicting charge states and understanding their underlying electrostatic interactions. The goal of this chapter is to inform users about applications and potential caveats of these methods as well as outline directions for future theoretical and computational research. PMID:27497160
Hughes, Samantha J; Tanner, Julian A; Hindley, Alison D; Miller, Andrew D; Gould, Ian R
2003-01-01
Background Charging of transfer-RNA with cognate amino acid is accomplished by the aminoacyl-tRNA synthetases, and proceeds through an aminoacyl adenylate intermediate. The lysyl-tRNA synthetase has evolved an active site that specifically binds lysine and ATP. Previous molecular dynamics simulations of the heat-inducible Escherichia coli lysyl-tRNA synthetase, LysU, have revealed differences in the binding of ATP and aspects of asymmetry between the nominally equivalent active sites of this dimeric enzyme. The possibility that this asymmetry results in different binding affinities for the ligands is addressed here by a parallel computational and biochemical study. Results Biochemical experiments employing isothermal calorimetry, steady-state fluorescence and circular dichroism are used to determine the order and stoichiometries of the lysine and nucleotide binding events, and the associated thermodynamic parameters. An ordered mechanism of substrate addition is found, with lysine having to bind prior to the nucleotide in a magnesium dependent process. Two lysines are found to bind per dimer, and trigger a large conformational change. Subsequent nucleotide binding causes little structural rearrangement and crucially only occurs at a single catalytic site, in accord with the simulations. Molecular dynamics based free energy calculations of the ATP binding process are used to determine the binding affinities of each site. Significant differences in ATP binding affinities are observed, with only one active site capable of realizing the experimental binding free energy. Half-of-the-sites models in which the nucleotide is only present at one active site achieve their full binding potential irrespective of the subunit choice. This strongly suggests the involvement of an anti-cooperative mechanism. Pathways for relaying information between the two active sites are proposed. Conclusions The asymmetry uncovered here appears to be a common feature of oligomeric aminoacyl-tRNA synthetases, and may play an important functional role. We suggest a manner in which catalytic efficiency could be improved by LysU operating in an alternating sites mechanism. PMID:12787471
Efficient computation of optimal oligo-RNA binding.
Hodas, Nathan O; Aalberts, Daniel P
2004-01-01
We present an algorithm that calculates the optimal binding conformation and free energy of two RNA molecules, one or both oligomeric. This algorithm has applications to modeling DNA microarrays, RNA splice-site recognitions and other antisense problems. Although other recent algorithms perform the same calculation in time proportional to the sum of the lengths cubed, O((N1 + N2)3), our oligomer binding algorithm, called bindigo, scales as the product of the sequence lengths, O(N1*N2). The algorithm performs well in practice with the aid of a heuristic for large asymmetric loops. To demonstrate its speed and utility, we use bindigo to investigate the binding proclivities of U1 snRNA to mRNA donor splice sites.
NASA Astrophysics Data System (ADS)
Isvoran, Adriana
2016-03-01
Assessment of the effects of the herbicides nicosulfuron and chlorsulfuron and the fungicides difenoconazole and drazoxlone upon catalase produced by soil microorganism Proteus mirabilis is performed using the molecular docking technique. The interactions of pesticides with the enzymes are predicted using SwissDock and PatchDock docking tools. There are correlations for predicted binding energy values for enzyme-pesticide complexes obtained using the two docking tools, all the considered pesticides revealing favorable binding to the enzyme, but only the herbicides bind to the catalytic site. These results suggest the inhibitory potential of chlorsulfuron and nicosulfuron on the catalase activity in soil.
Aramesh-Boroujeni, Zahra; Bordbar, Abdol-Khalegh; Khorasani-Motlagh, Mozhgan; Sattarinezhad, Elham; Fani, Najme; Noroozifar, Meissam
2018-05-18
In this work, the terbium(III), dysprosium(III), and ytterbium(III) complexes containing 2, 2'-bipyridine (bpy) ligand have been synthesized and characterized using CHN elemental analysis, FT-IR, UV-Vis and 1 H-NMR techniques and their binding behavior with human serum albumin (HSA) was studied by UV-Vis, fluorescence and molecular docking examinations. The experimental data indicated that all three lanthanide complexes have high binding affinity to HSA with effective quenching of HSA fluorescence via static mechanism. The binding parameters, the type of interaction, the value of resonance energy transfer, and the binding distance between complexes and HSA were estimated from the analysis of fluorescence measurements and Förster theory. The thermodynamic parameters suggested that van der Waals interactions and hydrogen bonds play an important role in the binding mechanism. While, the energy transfer from HSA molecules to all these complexes occurs with high probability, the order of binding constants (BpyTb > BpyDy > BpyYb) represents the importance of radius of Ln 3+ ion in the complex-HSA interaction. The results of molecular docking calculation and competitive experiments assessed site 3 of HSA, located in subdomain IB, as the most probable binding site for these ligands and also indicated the microenvironment residues around the bound mentioned complexes. The computational results kept in good agreement with experimental data.
Discovery of new sites for drug binding to the hypertension-related renin-angiotensinogen complex.
Brás, Natércia F; Fernandes, Pedro A; Ramos, Maria J
2014-04-01
Renin (REN) is a key drug target to stop the hypertension cascade, but thus far only one direct inhibitor has been made commercially available. In this study, we assess an innovative REN inhibition strategy, by targeting the interface of the renin:angiotensinogen (REN:ANG) complex. We characterized the energetic role of interfacial residues of REN:ANG and identified the ones responsible for protein:protein binding, which can serve as drug targets for disruption of the REN:ANG association. For this purpose, we applied a computational alanine scanning mutagenesis protocol, which measures the contribution of each side chain for the protein:protein binding free energy with an accuracy of ≈ 1 kcal/mol. As a result, in REN and ANG, six and eight residues were found to be critical for binding, respectively. The leading force behind REN:ANG complexation was found to be the hydrophobic effect. The binding free energy per residue was found to be proportional to the buried area. Residues responsible for binding were occluded from water at the complex, which promotes an efficient pairing between the two proteins. Two druggable pockets involving critical residues for binding were found on the surface of REN, where small druglike molecules can bind and disrupt the ANG:REN association that may provide an efficient way to achieve REN inhibition and control hypertension.
de Farias Silva, Natália; Lameira, Jerônimo; Alves, Cláudio Nahum
2011-10-01
Plasmepsin (PM) II is one of four enzymes in the food vacuole of Plasmodium falciparum. It has become an attractive target for combating malaria through research regarding its importance in the P. falciparum metabolism and life cycle, making it the target of choice for structure-based drug design. This paper reports the results of hybrid quantum mechanics / molecular mechanics (QM/MM) molecular dynamics (MD) simulations employed to study the details of the interactions established between PM II and N-(3-{(2-benzo[1, 3]dioxol-5-yl-ethyl)[3-(1-methyl-3-oxo-1,3-dihydro-isoindol-2-yl) propionyl]-amino}-1-benzyl-2-(hydroxyl-propyl)-4-benzyloxy-3,5dimethoxy-benzamide (EH58), a well-known potent inhibitor for this enzyme. Electrostatic binding free energy and energy terms decomposition have been computed for PM II complexed with the EH58 inhibitor. The results reveal that there is a strong interaction between Asp34, Val78, Ser79, Tyr192 and Asp214 residues and the EH58 inhibitor. In addition, we have computed the potential of the mean force (PMF) profile in order to assign the protonation state of the two catalytic aspartates in PM II-EH58 complex. The results indicate that the protonation of Asp214 favors a stable active site structure, which is consistent with our electrostatic binding free energy calculation and with previous published works.
Grid-Based Surface Generalized Born Model for Calculation of Electrostatic Binding Free Energies.
Forouzesh, Negin; Izadi, Saeed; Onufriev, Alexey V
2017-10-23
Fast and accurate calculation of solvation free energies is central to many applications, such as rational drug design. In this study, we present a grid-based molecular surface implementation of "R6" flavor of the generalized Born (GB) implicit solvent model, named GBNSR6. The speed, accuracy relative to numerical Poisson-Boltzmann treatment, and sensitivity to grid surface parameters are tested on a set of 15 small protein-ligand complexes and a set of biomolecules in the range of 268 to 25099 atoms. Our results demonstrate that the proposed model provides a relatively successful compromise between the speed and accuracy of computing polar components of the solvation free energies (ΔG pol ) and binding free energies (ΔΔG pol ). The model tolerates a relatively coarse grid size h = 0.5 Å, where the grid artifact error in computing ΔΔG pol remains in the range of k B T ∼ 0.6 kcal/mol. The estimated ΔΔG pol s are well correlated (r 2 = 0.97) with the numerical Poisson-Boltzmann reference, while showing virtually no systematic bias and RMSE = 1.43 kcal/mol. The grid-based GBNSR6 model is available in Amber (AmberTools) package of molecular simulation programs.
Mirchi, Ali; Sizochenko, Natalia; Dinadayalane, Tandabany; Leszczynski, Jerzy
2017-11-22
The effect of substitution of phenyl and naphthyl rings to benzene was examined to elucidate the cation-π interactions involving alkali metal ions with 1,3,5-tri(phenyl)benzene (TPB) and 1,3,5-tri(naphthyl)benzene (TNB). Benzene, TPB, and four TNB isomers (with ααα, ααβ, αββ, and βββ types of fusion) and their complexes with Li + , Na + , K + , Rb + , and Cs + were optimized using DFT approach with B3LYP and M06-2X functionals in conjunction with the def2-QZVP basis set. Higher relative stability of β,β,β-TNB over α,α,α-TNB can be attributed to peri repulsion, which is defined as the nonbonding repulsive interaction between substituents in the 1- and the 8-positions on the naphthalene core. Binding energies, distances between ring centroid and the metal ions, and the distance to metal ions from the center of other six-membered rings were compared for all complexes. Our computational study reveals that the binding affinity of alkali metal cations increases significantly with the 1,3,5-trisubstitution of phenyl and naphthyl rings to benzene. The detailed computational analyses of geometries, partial charges, binding energies, and ligand organization energies reveal the possibility of favorable C-H···M + interactions when a α-naphthyl group exists in complexes of TNB structures. Like benzene-alkali metal ion complexes, the binding affinity of metal ions follows the order: Li + > Na + > K + > Rb + > Cs + for any considered 1,3,5-trisubstituted benzene systems. In case of TNB, we found that the strength of interactions increases as the fusion point changes from α to β position of naphthalene.
NASA Astrophysics Data System (ADS)
Serçinoğlu, Onur; Özcan, Gülin; Kabaş, Zeynep Kutlu; Ozbek, Pemra
2016-07-01
A single amino acid difference (Asp116His), having a key role in a pathogenesis pathway, distinguishes HLA-B*27:05 and HLA-B*27:09 sub-types as associated and non-associated with ankylosing spondylitis, respectively. In this study, molecular docking simulations were carried out with the aim of comprehending the differences in the binding behavior of both alleles at varying pH conditions. A library of modeled peptides was formed upon single point mutations aiming to address the effect of 20 naturally occurring amino acids at the binding core peptide positions. For both alleles, computational docking was applied using Autodock 4.2. Obtained free energies of binding (FEB) were compared within the peptide library and between the alleles at varying pH conditions. The amino acid preferences of each position were studied enlightening the role of each on binding. The preferred amino acids for each position of pVIPR were found to be harmonious with experimental studies. Our results indicate that, as the pH is lowered, the capacity of HLA-B*27:05 to bind peptides in the library is largely lost. Hydrogen bonding analysis suggests that the interaction between the main anchor positions of pVIPR and their respective binding pocket residues are affected from the pH the most, causing an overall shift in the FEB profiles.
Serçinoğlu, Onur; Özcan, Gülin; Kabaş, Zeynep Kutlu; Ozbek, Pemra
2016-07-01
A single amino acid difference (Asp116His), having a key role in a pathogenesis pathway, distinguishes HLA-B*27:05 and HLA-B*27:09 sub-types as associated and non-associated with ankylosing spondylitis, respectively. In this study, molecular docking simulations were carried out with the aim of comprehending the differences in the binding behavior of both alleles at varying pH conditions. A library of modeled peptides was formed upon single point mutations aiming to address the effect of 20 naturally occurring amino acids at the binding core peptide positions. For both alleles, computational docking was applied using Autodock 4.2. Obtained free energies of binding (FEB) were compared within the peptide library and between the alleles at varying pH conditions. The amino acid preferences of each position were studied enlightening the role of each on binding. The preferred amino acids for each position of pVIPR were found to be harmonious with experimental studies. Our results indicate that, as the pH is lowered, the capacity of HLA-B*27:05 to bind peptides in the library is largely lost. Hydrogen bonding analysis suggests that the interaction between the main anchor positions of pVIPR and their respective binding pocket residues are affected from the pH the most, causing an overall shift in the FEB profiles.
Trifluoperazine Regulation of Calmodulin Binding to Fas: A Computational Study
Pan, Di; Yan, Qi; Chen, Yabing; McDonald, Jay M; Song, Yuhua
2011-01-01
Death-inducing signaling complex (DISC) formation is a critical step in Fas-mediated signaling for apoptosis. Previous experiments have demonstrated that the calmodulin (CaM) antagonist, trifluoperazine (TFP) regulates CaM-Fas binding and affects Fas-mediated DISC formation. In this study, we investigated the anti-cooperative characteristics of TFP binding to CaM and the effect of TFP on the CaM-Fas interaction from both structural and thermodynamic perspectives using combined molecular dynamics simulations and binding free energy analyses. We studied the interactions of different numbers of TFP molecules with CaM and explored the effects of the resulting conformational changes in CaM on CaM-Fas binding. Results from these analyses showed that the number of TFP molecules bound to CaM directly influenced α-helix formation and hydrogen bond occupancy within the α-helices of CaM, contributing to the conformational and motion changes in CaM. These changes affected CaM binding to Fas, resulting in secondary structural changes in Fas and conformational and motion changes of Fas in CaM-Fas complexes, potentially perturbing the recruitment of Fas-associated death domain (FADD) for DISC formation. The computational results from this study reveal the structural and molecular mechanisms that underlie the role of the CaM antagonist, TFP, in regulation of CaM-Fas binding and Fas-mediated DISC formation in a concentration-dependent manner. PMID:21656570
Spiliotopoulos, Dimitrios; Spitaleri, Andrea; Musco, Giovanna
2012-01-01
PHD fingers represent one of the largest families of epigenetic readers capable of decoding post-translationally modified or unmodified histone H3 tails. Because of their direct involvement in human pathologies they are increasingly considered as a potential therapeutic target. Several PHD/histone-peptide structures have been determined, however relatively little information is available on their dynamics. Studies aiming to characterize the dynamic and energetic determinants driving histone peptide recognition by epigenetic readers would strongly benefit from computational studies. Herein we focus on the dynamic and energetic characterization of the PHD finger subclass specialized in the recognition of histone H3 peptides unmodified in position K4 (H3K4me0). As a case study we focused on the first PHD finger of autoimmune regulator protein (AIRE-PHD1) in complex with H3K4me0. PCA analysis of the covariance matrix of free AIRE-PHD1 highlights the presence of a "flapping" movement, which is blocked in an open conformation upon binding to H3K4me0. Moreover, binding free energy calculations obtained through Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) methodology are in good qualitative agreement with experiments and allow dissection of the energetic terms associated with native and alanine mutants of AIRE-PHD1/H3K4me0 complexes. MM/PBSA calculations have also been applied to the energetic analysis of other PHD fingers recognizing H3K4me0. In this case we observe excellent correlation between computed and experimental binding free energies. Overall calculations show that H3K4me0 recognition by PHD fingers relies on compensation of the electrostatic and polar solvation energy terms and is stabilized by non-polar interactions.
NASA Astrophysics Data System (ADS)
Divya, A.; Mathavan, T.; Asath, R. Mohamed; Archana, J.; Hayakawa, Y.; Benial, A. Milton Franklin
2016-05-01
A series of strontium oxide functionalized graphene nanoflakes were designed and their optoelectronic properties were studied for enhanced photocatalytic activity. The efficiency of designed molecules was studied using various parameters such as HOMO-LUMO energy gap, light harvesting efficiency and exciton binding energy. The computed results show that by increasing the degree of functionalization of strontium oxide leads to lowering the band gap of hydrogen terminated graphene nanoflakes. Furthermore, the study explores the role of strontium oxide functionalization in Frontier Molecular Orbitals, ionization potential, electron affinity, exciton binding energy and light harvesting efficiency of designed molecules. The infrared and Raman spectra were simulated for pure and SrO functionalized graphene nanoflakes. The electron rich and electron deficient regions which are favorable for electrophilic and nucleophilic attacks respectively were analyzed using molecular electrostatic potential surface analysis.
Enhanced conformational sampling to visualize a free-energy landscape of protein complex formation.
Iida, Shinji; Nakamura, Haruki; Higo, Junichi
2016-06-15
We introduce various, recently developed, generalized ensemble methods, which are useful to sample various molecular configurations emerging in the process of protein-protein or protein-ligand binding. The methods introduced here are those that have been or will be applied to biomolecular binding, where the biomolecules are treated as flexible molecules expressed by an all-atom model in an explicit solvent. Sampling produces an ensemble of conformations (snapshots) that are thermodynamically probable at room temperature. Then, projection of those conformations to an abstract low-dimensional space generates a free-energy landscape. As an example, we show a landscape of homo-dimer formation of an endothelin-1-like molecule computed using a generalized ensemble method. The lowest free-energy cluster at room temperature coincided precisely with the experimentally determined complex structure. Two minor clusters were also found in the landscape, which were largely different from the native complex form. Although those clusters were isolated at room temperature, with rising temperature a pathway emerged linking the lowest and second-lowest free-energy clusters, and a further temperature increment connected all the clusters. This exemplifies that the generalized ensemble method is a powerful tool for computing the free-energy landscape, by which one can discuss the thermodynamic stability of clusters and the temperature dependence of the cluster networks. © 2016 The Author(s).
NASA Astrophysics Data System (ADS)
Neumaier, Marco; Weigend, Florian; Hampe, Oliver; Kappes, Manfred M.
2006-09-01
Near thermal energy reactive collisions of small mixed metal cluster cations AgmAun+ (m +n=4, 5, and 6) with carbon monoxide have been studied in the room temperature Penning trap of a Fourier transform ion-cyclotron-resonance mass spectrometer as a function of cluster size and composition. The tetrameric species AgAu3+ and Ag2Au2+ are found to react dissociatively by way of Au or Ag atom loss, respectively, to form the cluster carbonyl AgAu2CO+. In contrast, measurements on a selection of pentamers and hexamers show that CO is added with absolute rate constants that decrease with increasing silver content. Experimentally determined absolute rate constants for CO adsorption were analyzed using the radiative association kinetics model to obtain cluster cation-CO binding energies ranging from 0.77to1.09eV. High-level ab initio density functional theory (DFT) computations identifying the lowest-energy cluster isomers and the respective CO adsorption energies are in good agreement with the experimental findings clearly showing that CO binds in a "head-on" fashion to a gold atom in the mixed clusters. DFT exploration of reaction pathways in the case of Ag2Au2+ suggests that exoergicities are high enough to access the minimum energy products for all reactive clusters probed.
NASA Astrophysics Data System (ADS)
Rasky, Daniel J.; Milstein, Frederick
1986-02-01
Milstein and Hill previously derived formulas for computing the bulk and shear moduli, κ, μ, and μ', at arbitrary pressures, for cubic crystals in which interatomic interaction energies are modeled by pairwise functions, and they carried out the moduli computations using the complete family of Morse functions. The present study extends their work to a pseudopotential description of atomic binding. Specifically: (1) General formulas are derived for determining these moduli under hydrostatic loading within the framework of a pseudopotential model. (2) A two-parameter pseudopotential model is used to describe atomic binding of the alkali metals, and the two parameters are determined from experimental data (the model employs the Heine-Abarenkov potential with the Taylor dielectric function). (3) For each alkali metal (Li, Na, K, Rb, and Cs), the model is used to compute the pressure-versus-volume behavior and, at zero pressure, the binding energy, the density, and the elastic moduli and their pressure derivatives; the theoretical behavior is found to be in excellent agreement with experiment. (4) Calculations are made of κ, μ, and μ' of the bcc alkali metals over wide ranges of hydrostatic compression and expansion. (5) The pseudopotential results are compared with those of arbitrary-central-force models (wherein κ-(2/3)μ=μ'+2P) and with the specific Morse-function results. The pressures, bulk moduli, and zero-pressure shear moduli (as determined for the Morse and pseudopotential models) are in excellent agreement, but important differences appear in the shear moduli under high compressions. The computations in the present paper are for the bcc metals; a subsequent paper will extend this work to include both the bcc and fcc structures, at compressions and expansions where elastic stability or lattice cohesion is, in practice, lost.
Multiscale computational models in physical systems biology of intracellular trafficking.
Tourdot, Richard W; Bradley, Ryan P; Ramakrishnan, Natesan; Radhakrishnan, Ravi
2014-10-01
In intracellular trafficking, a definitive understanding of the interplay between protein binding and membrane morphology remains incomplete. The authors describe a computational approach by integrating coarse-grained molecular dynamics (CGMD) simulations with continuum Monte Carlo (CM) simulations of the membrane to study protein-membrane interactions and the ensuing membrane curvature. They relate the curvature field strength discerned from the molecular level to its effect at the cellular length-scale. They perform thermodynamic integration on the CM model to describe the free energy landscape of vesiculation in clathrin-mediated endocytosis. The method presented here delineates membrane morphologies and maps out the free energy changes associated with membrane remodeling due to varying coat sizes, coat curvature strengths, membrane bending rigidities, and tensions; furthermore several constraints on mechanisms underlying clathrin-mediated endocytosis have also been identified, Their CGMD simulations have revealed the importance of PIP2 for stable binding of proteins essential for curvature induction in the bilayer and have provided a molecular basis for the positive curvature induction by the epsin N-terminal homology (EIMTH) domain. Calculation of the free energy landscape for vesicle budding has identified the critical size and curvature strength of a clathrin coat required for nucleation and stabilisation of a mature vesicle.
Photoelectron imaging spectroscopy of niobium mononitride anion NbN{sup −}
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berkdemir, Cuneyt; Department of Physics, Faculty of Science, Erciyes University, Kayseri 38039; Gunaratne, K. Don Dasitha
2016-07-21
In this gas-phase photoelectron spectroscopy study, we present the electron binding energy spectrum and photoelectron angular distributions of NbN{sup −} by the velocity-map imaging technique. The electron binding energy of NbN{sup −} is measured to be 1.42 ± 0.02 eV from the X band maximum which defines the 0-0 transition between ground states of anion and neutral. Theoretical binding energies which are the vertical and adiabatic detachment energies are computed by density functional theory to compare them with experiment. The ground state of NbN{sup −} is assigned to the {sup 2}Δ{sub 3/2} state and then the electronic transitions originating frommore » this state into X{sup 3}Δ{sub Ω} (Ω = 1-3), a{sup 1}Δ{sub 2}, A{sup 3}Σ{sub 1}{sup −}, and b{sup 1}Σ{sub 0}{sup +} states of NbN are reported to interpret the spectral features. As a prospective study for catalytic materials, spectral features of NbN{sup −} are compared with those of isovalent ZrO{sup −} and Pd{sup −}.« less
Schneider, Thomas D
2010-10-01
The relationship between information and energy is key to understanding biological systems. We can display the information in DNA sequences specifically bound by proteins by using sequence logos, and we can measure the corresponding binding energy. These can be compared by noting that one of the forms of the second law of thermodynamics defines the minimum energy dissipation required to gain one bit of information. Under the isothermal conditions that molecular machines function this is [Formula in text] joules per bit (kB is Boltzmann's constant and T is the absolute temperature). Then an efficiency of binding can be computed by dividing the information in a logo by the free energy of binding after it has been converted to bits. The isothermal efficiencies of not only genetic control systems, but also visual pigments are near 70%. From information and coding theory, the theoretical efficiency limit for bistate molecular machines is ln 2=0.6931. Evolutionary convergence to maximum efficiency is limited by the constraint that molecular states must be distinct from each other. The result indicates that natural molecular machines operate close to their information processing maximum (the channel capacity), and implies that nanotechnology can attain this goal.
Schneider, Thomas D.
2010-01-01
The relationship between information and energy is key to understanding biological systems. We can display the information in DNA sequences specifically bound by proteins by using sequence logos, and we can measure the corresponding binding energy. These can be compared by noting that one of the forms of the second law of thermodynamics defines the minimum energy dissipation required to gain one bit of information. Under the isothermal conditions that molecular machines function this is joules per bit ( is Boltzmann's constant and T is the absolute temperature). Then an efficiency of binding can be computed by dividing the information in a logo by the free energy of binding after it has been converted to bits. The isothermal efficiencies of not only genetic control systems, but also visual pigments are near 70%. From information and coding theory, the theoretical efficiency limit for bistate molecular machines is ln 2 = 0.6931. Evolutionary convergence to maximum efficiency is limited by the constraint that molecular states must be distinct from each other. The result indicates that natural molecular machines operate close to their information processing maximum (the channel capacity), and implies that nanotechnology can attain this goal. PMID:20562221
NASA Astrophysics Data System (ADS)
Labanc, Daniel; Šulka, Martin; Pitoňák, Michal; Černušák, Ivan; Urban, Miroslav; Neogrády, Pavel
2018-05-01
We present a computational study of the stability of small homonuclear beryllium clusters Be7 - 12 in singlet electronic states. Our predictions are based on highly correlated CCSD(T) coupled cluster calculations. Basis set convergence towards the complete basis set limit as well as the role of the 1s core electron correlation are carefully examined. Our CCSD(T) data for binding energies of Be7 - 12 clusters serve as a benchmark for performance assessment of several density functional theory (DFT) methods frequently used in beryllium cluster chemistry. We observe that, from Be10 clusters on, the deviation from CCSD(T) benchmarks is stable with respect to size, and fluctuating within 0.02 eV error bar for most examined functionals. This opens up the possibility of scaling the DFT binding energies for large Be clusters using CCSD(T) benchmark values for smaller clusters. We also tried to find analogies between the performance of DFT functionals for Be clusters and for the valence-isoelectronic Mg clusters investigated recently in Truhlar's group. We conclude that it is difficult to find DFT functionals that perform reasonably well for both beryllium and magnesium clusters. Out of 12 functionals examined, only the M06-2X functional gives reasonably accurate and balanced binding energies for both Be and Mg clusters.
Ahmed, Shaimaa M; Maguire, Glenn E M; Kruger, Hendrik G; Govender, Thirumala
2014-04-01
Molecular dynamics simulations and binding free energy calculations were used to provide an understanding of the impact of active site drug-resistant mutations of the South African HIV protease subtype C (C-SA HIV PR), V82A and V82F/I84V on drug resistance. Unique per-residue interaction energy 'footprints' were developed to map the overall drug-binding profiles for the wild type and mutants. Results confirmed that these mutations altered the overall binding landscape of the amino acid residues not only in the active site region but also in the flaps as well. Four FDA-approved drugs were investigated in this study; these include ritonavir (RTV), saquinavir (SQV), indinavir (IDV), and nelfinavir (NFV). Computational results compared against experimental findings were found to be complementary. Against the V82F/I84V variant, saquinavir, indinavir, and nelfinavir lose remarkable entropic contributions relative to both wild-type and V82A C-SA HIV PRs. The per-residue energy 'footprints' and the analysis of ligand-receptor interactions for the drug complexes with the wild type and mutants have also highlighted the nature of drug interactions. The data presented in this study will prove useful in the design of more potent inhibitors effective against drug-resistant HIV strains. © 2013 John Wiley & Sons A/S.
Kölsch, Adrian; Hejazi, Mahdi; Stieger, Kai R; Feifel, Sven C; Kern, Jan F; Müh, Frank; Lisdat, Fred; Lokstein, Heiko; Zouni, Athina
2018-06-08
The binding of photosystem I (PS I) from Thermosynechococcus elongatus to the native cytochrome (cyt) c 6 and cyt c from horse heart (cyt c HH ) was analyzed by oxygen consumption measurements, isothermal titration calorimetry (ITC), and rigid body docking combined with electrostatic computations of binding energies. Although PS I has a higher affinity for cyt c HH than for cyt c 6 , the influence of ionic strength and pH on binding is different in the two cases. ITC and theoretical computations revealed the existence of unspecific binding sites for cyt c HH besides one specific binding site close to P 700 Binding to PS I was found to be the same for reduced and oxidized cyt c HH Based on this information, suitable conditions for cocrystallization of cyt c HH with PS I were found, resulting in crystals with a PS I:cyt c HH ratio of 1:1. A crystal structure at 3.4-Å resolution was obtained, but cyt c HH cannot be identified in the electron density map because of unspecific binding sites and/or high flexibility at the specific binding site. Modeling the binding of cyt c 6 to PS I revealed a specific binding site where the distance and orientation of cyt c 6 relative to P 700 are comparable with cyt c 2 from purple bacteria relative to P 870 This work provides new insights into the binding modes of different cytochromes to PS I, thus facilitating steps toward solving the PS I-cyt c costructure and a more detailed understanding of natural electron transport processes.
Theoretical study of Escherichia coli peptide deformylase inhibition by several drugs.
Chikhi, Abdelouahab; Bensegueni, Abderrahmane; Boulahrouf, Abderrahmane; Bencharif, Mustapha
2006-01-01
Because peptide deformylase (PDF) is essential for the initiation of translation in eubacteria but not in eukaryotes, it is a potentially interesting target for antibiotics. Computer simulation using docking software can be used to model protein-ligand interactions, and in this brief report we describe its use in optimizing the design in PDF-directed inhibitors. PDF was used as target for a set of five inhibitors with substantial structural differences. Docking results show that the compound 1BB2 (actinonin) binds with high affinity to the enzyme and produces the most stable complex, forming nine hydrogen bonds with the enzyme active site. Its binding energy is DeltaG = -31.880 kJ/mol. The modeling study shows that when the methyl group of 1BB2 is replaced with an amine group, the binding energy is increased to -35.316 kJ/mole. This enhancement is more marked (DeltaG = -41.141 kJ/mol) when the propyl group and the five-membered ring of 1BB2 are replaced by an amide group and a phenyl ring, respectively. We describe an attempt to design better antibiotics on the basis of a computer-aided simulation of the interaction between a drug and its target molecule.
Capoferri, Luigi; Leth, Rasmus; ter Haar, Ernst; Mohanty, Arun K; Grootenhuis, Peter D J; Vottero, Eduardo; Commandeur, Jan N M; Vermeulen, Nico P E; Jørgensen, Flemming Steen; Olsen, Lars; Geerke, Daan P
2016-03-01
Cytochrome P450 BM3 (CYP102A1) mutant M11 is able to metabolize a wide range of drugs and drug-like compounds. Among these, M11 was recently found to be able to catalyze formation of human metabolites of mefenamic acid and other nonsteroidal anti-inflammatory drugs (NSAIDs). Interestingly, single active-site mutations such as V87I were reported to invert regioselectivity in NSAID hydroxylation. In this work, we combine crystallography and molecular simulation to study the effect of single mutations on binding and regioselective metabolism of mefenamic acid by M11 mutants. The heme domain of the protein mutant M11 was expressed, purified, and crystallized, and its X-ray structure was used as template for modeling. A multistep approach was used that combines molecular docking, molecular dynamics (MD) simulation, and binding free-energy calculations to address protein flexibility. In this way, preferred binding modes that are consistent with oxidation at the experimentally observed sites of metabolism (SOMs) were identified. Whereas docking could not be used to retrospectively predict experimental trends in regioselectivity, we were able to rank binding modes in line with the preferred SOMs of mefenamic acid by M11 and its mutants by including protein flexibility and dynamics in free-energy computation. In addition, we could obtain structural insights into the change in regioselectivity of mefenamic acid hydroxylation due to single active-site mutations. Our findings confirm that use of MD and binding free-energy calculation is useful for studying biocatalysis in those cases in which enzyme binding is a critical event in determining the selective metabolism of a substrate. © 2016 Wiley Periodicals, Inc.
Analysis of ice-binding sites in fish type II antifreeze protein by quantum mechanics.
Cheng, Yuhua; Yang, Zuoyin; Tan, Hongwei; Liu, Ruozhuang; Chen, Guangju; Jia, Zongchao
2002-10-01
Many organisms living in cold environments can survive subzero temperatures by producing antifreeze proteins (AFPs) or antifreeze glycoproteins. In this paper we investigate the ice-binding surface of type II AFP by quantum mechanical methods, which, to the best of our knowledge, represents the first time that molecular orbital computational approaches have been applied to AFPs. Molecular mechanical approaches, including molecular docking, energy minimization, and molecular dynamics simulation, were used to obtain optimal systems for subsequent quantum mechanical analysis. We selected 17 surface patches covering the entire surface of the type II AFP and evaluated the interaction energy between each of these patches and two different ice planes using semi-empirical quantum mechanical methods. We have demonstrated the weak orbital overlay phenomenon and the change of bond orders in ice. These results consistently indicate that a surface patch containing 19 residues (K37, L38, Y20, E22, Y21, I19, L57, T56, F53, M127, T128, F129, R17, C7, N6, P5, G10, Q1, and W11) is the most favorable ice-binding site for both a regular ice plane and an ice plane where water O atoms are randomly positioned. Furthermore, for the first time the computation results provide new insights into the weakening of the ice lattice upon AFP binding, which may well be a primary factor leading to AFP-induced ice growth inhibition.
Analysis of ice-binding sites in fish type II antifreeze protein by quantum mechanics.
Cheng, Yuhua; Yang, Zuoyin; Tan, Hongwei; Liu, Ruozhuang; Chen, Guangju; Jia, Zongchao
2002-01-01
Many organisms living in cold environments can survive subzero temperatures by producing antifreeze proteins (AFPs) or antifreeze glycoproteins. In this paper we investigate the ice-binding surface of type II AFP by quantum mechanical methods, which, to the best of our knowledge, represents the first time that molecular orbital computational approaches have been applied to AFPs. Molecular mechanical approaches, including molecular docking, energy minimization, and molecular dynamics simulation, were used to obtain optimal systems for subsequent quantum mechanical analysis. We selected 17 surface patches covering the entire surface of the type II AFP and evaluated the interaction energy between each of these patches and two different ice planes using semi-empirical quantum mechanical methods. We have demonstrated the weak orbital overlay phenomenon and the change of bond orders in ice. These results consistently indicate that a surface patch containing 19 residues (K37, L38, Y20, E22, Y21, I19, L57, T56, F53, M127, T128, F129, R17, C7, N6, P5, G10, Q1, and W11) is the most favorable ice-binding site for both a regular ice plane and an ice plane where water O atoms are randomly positioned. Furthermore, for the first time the computation results provide new insights into the weakening of the ice lattice upon AFP binding, which may well be a primary factor leading to AFP-induced ice growth inhibition. PMID:12324437
Universal aspects of brittle fracture, adhesion, and atomic force microscopy
NASA Technical Reports Server (NTRS)
Banerjea, Amitava; Ferrante, John; Smith, John R.
1989-01-01
This universal relation between binding energy and interatomic separation was originally discovered for adhesion at bimetallic interfaces involving the simple metals Al, Zn, Mg, and Na. It is shown here that the same universal relation extends to adhesion at transition-metal interfaces. Adhesive energies have been computed for the low-index interfaces of Al, Ni, Cu, Ag, Fe, and W, using the equivalent-crystal theory (ECT) and keeping the atoms in each semiinfinite slab fixed rigidly in their equilibrium positions. These adhesive energy curves can be scaled onto each other and onto the universal adhesion curve. The effect of tip shape on the adhesive forces in the atomic-force microscope (AFM) is studied by computing energies and forces using the ECT. While the details of the energy-distance and force-distance curves are sensitive to tip shape, all of these curves can be scaled onto the universal adhesion curve.
Petrič, Andrej; Johnson, Scott A.; Pham, Hung V.; Li, Ying; Čeh, Simon; Golobič, Amalija; Agdeppa, Eric D.; Timbol, Gerald; Liu, Jie; Keum, Gyochang; Satyamurthy, Nagichettiar; Kepe, Vladimir; Houk, Kendall N.; Barrio, Jorge R.
2012-01-01
The positron-emission tomography (PET) probe 2-(1-[6-[(2-fluoroethyl)(methyl)amino]-2-naphthyl]ethylidene) (FDDNP) is used for the noninvasive brain imaging of amyloid-β (Aβ) and other amyloid aggregates present in Alzheimer’s disease and other neurodegenerative diseases. A series of FDDNP analogs has been synthesized and characterized using spectroscopic and computational methods. The binding affinities of these molecules have been measured experimentally and explained through the use of a computational model. The analogs were created by systematically modifying the donor and the acceptor sides of FDDNP to learn the structural requirements for optimal binding to Aβ aggregates. FDDNP and its analogs are neutral, environmentally sensitive, fluorescent molecules with high dipole moments, as evidenced by their spectroscopic properties and dipole moment calculations. The preferred solution-state conformation of these compounds is directly related to the binding affinities. The extreme cases were a nonplanar analog t-butyl-FDDNP, which shows low binding affinity for Aβ aggregates (520 nM Ki) in vitro and a nearly planar tricyclic analog cDDNP, which displayed the highest binding affinity (10 pM Ki). Using a previously published X-ray crystallographic model of 1,1-dicyano-2-[6-(dimethylamino)naphthalen-2-yl]propene (DDNP) bound to an amyloidogenic Aβ peptide model, we show that the binding affinity is inversely related to the distortion energy necessary to avoid steric clashes along the internal surface of the binding channel. PMID:23012452
Structure and binding energy of the H2S dimer at the CCSD(T) complete basis set limit.
Lemke, Kono H
2017-06-21
This study presents results for the binding energy and geometry of the H 2 S dimer which have been computed using Møller-Plesset perturbation theory (MP2, MP4) and coupled cluster (CCSD, CCSD(T)) calculations with basis sets up to aug-cc-pV5Z. Estimates of D e , E ZPE , D o , and dimer geometry have been obtained at each level of theory by taking advantage of the systematic convergence behavior toward the complete basis set (CBS) limit. The CBS limit binding energy values of D e are 1.91 (MP2), 1.75 (MP4), 1.41 (CCSD), and 1.69 kcal/mol (CCSD[T]). The most accurate values for the equilibrium S-S distance r SS (without counterpoise correction) are 4.080 (MP2/aug-cc-pV5Z), 4.131 (MP4/aug-cc-pVQZ), 4.225 (CCSD/aug-cc-pVQZ), and 4.146 Å (CCSD(T)/aug-cc-pVQZ). This study also evaluates the effect of counterpoise correction on the H 2 S dimer geometry and binding energy. As regards the structure of (H 2 S) 2 , MPn, CCSD, and CCSD(T) level values of r SS , obtained by performing geometry optimizations on the counterpoise-corrected potential energy surface, converge systematically to CBS limit values of 4.099 (MP2), 4.146 (MP4), 4.233 (CCSD), and 4.167 Å (CCSD(T)). The corresponding CBS limit values of the equilibrium binding energy D e are 1.88 (MP2), 1.76 (MP4), 1.41 (CCSD), and 1.69 kcal/mol (CCSD(T)), the latter in excellent agreement with the measured binding energy value of 1.68 ± 0.02 kcal/mol reported by Ciaffoni et al. [Appl. Phys. B 92, 627 (2008)]. Combining CBS electronic binding energies D e with E ZPE predicted by CCSD(T) vibrational second-order perturbation theory calculations yields D o = 1.08 kcal/mol, which is around 0.6 kcal/mol smaller than the measured value of 1.7 ± 0.3 kcal/mol. Overall, the results presented here demonstrate that the application of high level calculations, in particular CCSD(T), in combination with augmented correlation consistent basis sets provides valuable insight into the structure and energetics of the hydrogen sulfide dimer.
Structure and binding energy of the H2S dimer at the CCSD(T) complete basis set limit
NASA Astrophysics Data System (ADS)
Lemke, Kono H.
2017-06-01
This study presents results for the binding energy and geometry of the H2S dimer which have been computed using Møller-Plesset perturbation theory (MP2, MP4) and coupled cluster (CCSD, CCSD(T)) calculations with basis sets up to aug-cc-pV5Z. Estimates of De, EZPE, Do, and dimer geometry have been obtained at each level of theory by taking advantage of the systematic convergence behavior toward the complete basis set (CBS) limit. The CBS limit binding energy values of De are 1.91 (MP2), 1.75 (MP4), 1.41 (CCSD), and 1.69 kcal/mol (CCSD[T]). The most accurate values for the equilibrium S-S distance rSS (without counterpoise correction) are 4.080 (MP2/aug-cc-pV5Z), 4.131 (MP4/aug-cc-pVQZ), 4.225 (CCSD/aug-cc-pVQZ), and 4.146 Å (CCSD(T)/aug-cc-pVQZ). This study also evaluates the effect of counterpoise correction on the H2S dimer geometry and binding energy. As regards the structure of (H2S)2, MPn, CCSD, and CCSD(T) level values of rSS, obtained by performing geometry optimizations on the counterpoise-corrected potential energy surface, converge systematically to CBS limit values of 4.099 (MP2), 4.146 (MP4), 4.233 (CCSD), and 4.167 Å (CCSD(T)). The corresponding CBS limit values of the equilibrium binding energy De are 1.88 (MP2), 1.76 (MP4), 1.41 (CCSD), and 1.69 kcal/mol (CCSD(T)), the latter in excellent agreement with the measured binding energy value of 1.68 ± 0.02 kcal/mol reported by Ciaffoni et al. [Appl. Phys. B 92, 627 (2008)]. Combining CBS electronic binding energies De with EZPE predicted by CCSD(T) vibrational second-order perturbation theory calculations yields Do = 1.08 kcal/mol, which is around 0.6 kcal/mol smaller than the measured value of 1.7 ± 0.3 kcal/mol. Overall, the results presented here demonstrate that the application of high level calculations, in particular CCSD(T), in combination with augmented correlation consistent basis sets provides valuable insight into the structure and energetics of the hydrogen sulfide dimer.
Anbarasu, K; Jayanthi, S
2018-05-01
Human lemur tyrosine kinase-3 (LMTK3) is primarily involved in regulation of estrogen receptor-α (ERα) by phosphorylation activity. LMTK3 acts as key biomarker for ERα positive breast cancer and identified as novel drug target for breast cancer. Due to the absence of experimental reports, the computational approach has been followed to screen LMTK3 inhibitors from natural product curcumin derivatives based on rational inhibitor design. The initial virtual screening and re-docking resulted in identification of top three leads with favorable binding energy and strong interactions in critical residues of ATP-binding cavity. ADME prediction confirmed the pharmacological activity of the leads with various properties. The stability and binding affinity of leads were well refined in dynamic system from 25 ns MD simulations. The behavior of protein motion towards closure of ATP-binding cavity was evaluated based on eigenvectors by PCA. In addition, MM/PBSA calculations also confirmed the relative binding free energy of LMTK3-lead complexes in favor of the effective binding. From our study, novel LMTK3 inhibitors tetrahydrocurcumin, curcumin 4,4'-diacetate, and demethoxycurcumin have been proposed with inhibition mechanism. Further experimental evaluation on reported lead candidates might prove its role in breast cancer therapeutics.
Exploring the stability of ligand binding modes to proteins by molecular dynamics simulations.
Liu, Kai; Watanabe, Etsurou; Kokubo, Hironori
2017-02-01
The binding mode prediction is of great importance to structure-based drug design. The discrimination of various binding poses of ligand generated by docking is a great challenge not only to docking score functions but also to the relatively expensive free energy calculation methods. Here we systematically analyzed the stability of various ligand poses under molecular dynamics (MD) simulation. First, a data set of 120 complexes was built based on the typical physicochemical properties of drug-like ligands. Three potential binding poses (one correct pose and two decoys) were selected for each ligand from self-docking in addition to the experimental pose. Then, five independent MD simulations for each pose were performed with different initial velocities for the statistical analysis. Finally, the stabilities of ligand poses under MD were evaluated and compared with the native one from crystal structure. We found that about 94% of the native poses were maintained stable during the simulations, which suggests that MD simulations are accurate enough to judge most experimental binding poses as stable properly. Interestingly, incorrect decoy poses were maintained much less and 38-44% of decoys could be excluded just by performing equilibrium MD simulations, though 56-62% of decoys were stable. The computationally-heavy binding free energy calculation can be performed only for these survived poses.
Open sd-shell nuclei from first principles
Jansen, Gustav R.; Signoracci, Angelo J.; Hagen, Gaute; ...
2016-07-05
We extend the ab initio coupled-cluster effective interaction (CCEI) method to open-shell nuclei with protons and neutrons in the valence space, and compute binding energies and excited states of isotopes of neon and magnesium. We employ a nucleon-nucleon and three-nucleon interaction from chiral effective field theory evolved to a lower cutoff via a similarity renormalization group transformation. We find good agreement with experiment for binding energies and spectra, while charge radii of neon isotopes are underestimated. For the deformed nuclei 20Ne and 24Mg we reproduce rotational bands and electric quadrupole transitions within uncertainties estimated from an effective field theory formore » deformed nuclei, thereby demonstrating that collective phenomena in sd-shell nuclei emerge from complex ab initio calculations.« less
Open sd-shell nuclei from first principles
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jansen, Gustav R.; Signoracci, Angelo J.; Hagen, Gaute
We extend the ab initio coupled-cluster effective interaction (CCEI) method to open-shell nuclei with protons and neutrons in the valence space, and compute binding energies and excited states of isotopes of neon and magnesium. We employ a nucleon-nucleon and three-nucleon interaction from chiral effective field theory evolved to a lower cutoff via a similarity renormalization group transformation. We find good agreement with experiment for binding energies and spectra, while charge radii of neon isotopes are underestimated. For the deformed nuclei 20Ne and 24Mg we reproduce rotational bands and electric quadrupole transitions within uncertainties estimated from an effective field theory formore » deformed nuclei, thereby demonstrating that collective phenomena in sd-shell nuclei emerge from complex ab initio calculations.« less
Banerjee, Suvrajit; Parimal, Siddharth; Cramer, Steven M
2017-08-18
Multimodal (MM) chromatography provides a powerful means to enhance the selectivity of protein separations by taking advantage of multiple weak interactions that include electrostatic, hydrophobic and van der Waals interactions. In order to increase our understanding of such phenomena, a computationally efficient approach was developed that combines short molecular dynamics simulations and continuum solvent based coarse-grained free energy calculations in order to study the binding of proteins to Self Assembled Monolayers (SAM) presenting MM ligands. Using this method, the free energies of protein-MM SAM binding over a range of incident orientations of the protein can be determined. The resulting free energies were then examined to identify the more "strongly bound" orientations of different proteins with two multimodal surfaces. The overall free energy of protein-MM surface binding was then determined and correlated to retention factors from isocratic chromatography. This correlation, combined with analytical expressions from the literature, was then employed to predict protein gradient elution salt concentrations as well as selectivity reversals with different MM resin systems. Patches on protein surfaces that interacted strongly with MM surfaces were also identified by determining the frequency of heavy atom contacts with the atoms of the MM SAMs. A comparison of these patches to Electrostatic Potential and hydrophobicity maps indicated that while all of these patches contained significant positive charge, only the highest frequency sites also possessed hydrophobicity. The ability to identify key binding patches on proteins may have significant impact on process development for the separation of bioproduct related impurities. Copyright © 2017 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Christensen, Anders S.; Kromann, Jimmy C.; Jensen, Jan H.; Cui, Qiang
2017-10-01
To facilitate further development of approximate quantum mechanical methods for condensed phase applications, we present a new benchmark dataset of intermolecular interaction energies in the solution phase for a set of 15 dimers, each containing one charged monomer. The reference interaction energy in solution is computed via a thermodynamic cycle that integrates dimer binding energy in the gas phase at the coupled cluster level and solute-solvent interaction with density functional theory; the estimated uncertainty of such calculated interaction energy is ±1.5 kcal/mol. The dataset is used to benchmark the performance of a set of semi-empirical quantum mechanical (SQM) methods that include DFTB3-D3, DFTB3/CPE-D3, OM2-D3, PM6-D3, PM6-D3H+, and PM7 as well as the HF-3c method. We find that while all tested SQM methods tend to underestimate binding energies in the gas phase with a root-mean-squared error (RMSE) of 2-5 kcal/mol, they overestimate binding energies in the solution phase with an RMSE of 3-4 kcal/mol, with the exception of DFTB3/CPE-D3 and OM2-D3, for which the systematic deviation is less pronounced. In addition, we find that HF-3c systematically overestimates binding energies in both gas and solution phases. As most approximate QM methods are parametrized and evaluated using data measured or calculated in the gas phase, the dataset represents an important first step toward calibrating QM based methods for application in the condensed phase where polarization and exchange repulsion need to be treated in a balanced fashion.
Continuum Electrostatics Approaches to Calculating pKas and Ems in Proteins.
Gunner, M R; Baker, N A
2016-01-01
Proteins change their charge state through protonation and redox reactions as well as through binding charged ligands. The free energy of these reactions is dominated by solvation and electrostatic energies and modulated by protein conformational relaxation in response to the ionization state changes. Although computational methods for calculating these interactions can provide very powerful tools for predicting protein charge states, they include several critical approximations of which users should be aware. This chapter discusses the strengths, weaknesses, and approximations of popular computational methods for predicting charge states and understanding the underlying electrostatic interactions. The goal of this chapter is to inform users about applications and potential caveats of these methods as well as outline directions for future theoretical and computational research. © 2016 Elsevier Inc. All rights reserved.
Molecular modelling study of changes induced by netropsin binding to nucleosome core particles.
Pérez, J J; Portugal, J
1990-01-01
It is well known that certain sequence-dependent modulators in structure appear to determine the rotational positioning of DNA on the nucleosome core particle. That preference is rather weak and could be modified by some ligands as netropsin, a minor-groove binding antibiotic. We have undertaken a molecular modelling approach to calculate the relative energy of interaction between a DNA molecule and the protein core particle. The histones particle is considered as a distribution of positive charges on the protein surface that interacts with the DNA molecule. The molecular electrostatic potentials for the DNA, simulated as a discontinuous cylinder, were calculated using the values for all the base pairs. Computing these parameters, we calculated the relative energy of interaction and the more stable rotational setting of DNA. The binding of four molecules of netropsin to this model showed that a new minimum of energy is obtained when the DNA turns toward the protein surface by about 180 degrees, so a new energetically favoured structure appears where netropsin binding sites are located facing toward the histones surface. The effect of netropsin could be explained in terms of an induced change in the phasing of DNA on the core particle. The induced rotation is considered to optimize non-bonded contacts between the netropsin molecules and the DNA backbone. PMID:2165249
NASA Astrophysics Data System (ADS)
Sippl, Wolfgang
2000-08-01
One of the major challenges in computational approaches to drug design is the accurate prediction of binding affinity of biomolecules. In the present study several prediction methods for a published set of estrogen receptor ligands are investigated and compared. The binding modes of 30 ligands were determined using the docking program AutoDock and were compared with available X-ray structures of estrogen receptor-ligand complexes. On the basis of the docking results an interaction energy-based model, which uses the information of the whole ligand-receptor complex, was generated. Several parameters were modified in order to analyze their influence onto the correlation between binding affinities and calculated ligand-receptor interaction energies. The highest correlation coefficient ( r 2 = 0.617, q 2 LOO = 0.570) was obtained considering protein flexibility during the interaction energy evaluation. The second prediction method uses a combination of receptor-based and 3D quantitative structure-activity relationships (3D QSAR) methods. The ligand alignment obtained from the docking simulations was taken as basis for a comparative field analysis applying the GRID/GOLPE program. Using the interaction field derived with a water probe and applying the smart region definition (SRD) variable selection, a significant and robust model was obtained ( r 2 = 0.991, q 2 LOO = 0.921). The predictive ability of the established model was further evaluated by using a test set of six additional compounds. The comparison with the generated interaction energy-based model and with a traditional CoMFA model obtained using a ligand-based alignment ( r 2 = 0.951, q 2 LOO = 0.796) indicates that the combination of receptor-based and 3D QSAR methods is able to improve the quality of the underlying model.
Brown, J B; Nakatsui, Masahiko; Okuno, Yasushi
2014-12-01
The cost of pharmaceutical R&D has risen enormously, both worldwide and in Japan. However, Japan faces a particularly difficult situation in that its population is aging rapidly, and the cost of pharmaceutical R&D affects not only the industry but the entire medical system as well. To attempt to reduce costs, the newly launched K supercomputer is available for big data drug discovery and structural simulation-based drug discovery. We have implemented both primary (direct) and secondary (infrastructure, data processing) methods for the two types of drug discovery, custom tailored to maximally use the 88 128 compute nodes/CPUs of K, and evaluated the implementations. We present two types of results. In the first, we executed the virtual screening of nearly 19 billion compound-protein interactions, and calculated the accuracy of predictions against publicly available experimental data. In the second investigation, we implemented a very computationally intensive binding free energy algorithm, and found that comparison of our binding free energies was considerably accurate when validated against another type of publicly available experimental data. The common feature of both result types is the scale at which computations were executed. The frameworks presented in this article provide prospectives and applications that, while tuned to the computing resources available in Japan, are equally applicable to any equivalent large-scale infrastructure provided elsewhere. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
NASA Technical Reports Server (NTRS)
Garduno-Juarez, R.; Shibata, M.; Zielinski, T. J.; Rein, R.
1987-01-01
A model of the complex between the acetylcholine receptor and the snake neurotoxin, cobratoxin, was built by molecular model building and energy optimization techniques. The experimentally identified functionally important residues of cobratoxin and the dodecapeptide corresponding to the residues 185-196 of acetylcholine receptor alpha subunit were used to build the model. Both cis and trans conformers of cyclic L-cystine portion of the dodecapeptide were examined. Binding residues independently identified on cobratoxin are shown to interact with the dodecapeptide AChR model.
Multiply Reduced Oligofluorenes: Their Nature and Pairing with THF-Solvated Sodium Ions
Wu, Qin; Zaikowski, Lori; Kaur, Parmeet; ...
2016-07-01
Conjugated oligofluorenes are chemically reduced up to five charges in tetrahydrofuran solvent and confirmed with clear spectroscopic evidence. Stimulated by these experimental results, we have conducted a comprehensive computational study of the electronic structure and the solvation structure of representative oligofluorene anions with a focus on the pairing between sodium ions and these multianions. In addition, using density functional theory (DFT) methods and a solvation model of both explicit solvent molecules and implicit polarizable continuum, we first elucidate the structure of tightly solvated free sodium ions, and then explore the pairing of sodium ions either in contact with reduced oligofluorenesmore » or as solvent-separated ion pairs. Computed time-dependent-DFT absorption spectra are compared with experiments to assign the dominant ion pairing structure for each multianion. Computed ion pair binding energies further support our assignment. Lastly, the availability of different length and reducing level of oligofluorenes enables us to investigate the effects of total charge and charge density on the binding with sodium ions, and our results suggest both factors play important roles in ion pairing for small molecules. However, as the oligofluorene size grows, its charge density determines the binding strength with the sodium ion.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wu, Qin; Zaikowski, Lori; Kaur, Parmeet
Conjugated oligofluorenes are chemically reduced up to five charges in tetrahydrofuran solvent and confirmed with clear spectroscopic evidence. Stimulated by these experimental results, we have conducted a comprehensive computational study of the electronic structure and the solvation structure of representative oligofluorene anions with a focus on the pairing between sodium ions and these multianions. In addition, using density functional theory (DFT) methods and a solvation model of both explicit solvent molecules and implicit polarizable continuum, we first elucidate the structure of tightly solvated free sodium ions, and then explore the pairing of sodium ions either in contact with reduced oligofluorenesmore » or as solvent-separated ion pairs. Computed time-dependent-DFT absorption spectra are compared with experiments to assign the dominant ion pairing structure for each multianion. Computed ion pair binding energies further support our assignment. Lastly, the availability of different length and reducing level of oligofluorenes enables us to investigate the effects of total charge and charge density on the binding with sodium ions, and our results suggest both factors play important roles in ion pairing for small molecules. However, as the oligofluorene size grows, its charge density determines the binding strength with the sodium ion.« less
2011-01-01
Background The reliable and robust estimation of ligand binding affinity continues to be a challenge in drug design. Many current methods rely on molecular mechanics (MM) calculations which do not fully explain complex molecular interactions. Full quantum mechanical (QM) computation of the electronic state of protein-ligand complexes has recently become possible by the latest advances in the development of linear-scaling QM methods such as the ab initio fragment molecular orbital (FMO) method. This approximate molecular orbital method is sufficiently fast that it can be incorporated into the development cycle during structure-based drug design for the reliable estimation of ligand binding affinity. Additionally, the FMO method can be combined with approximations for entropy and solvation to make it applicable for binding affinity prediction for a broad range of target and chemotypes. Results We applied this method to examine the binding affinity for a series of published cyclin-dependent kinase 2 (CDK2) inhibitors. We calculated the binding affinity for 28 CDK2 inhibitors using the ab initio FMO method based on a number of X-ray crystal structures. The sum of the pair interaction energies (PIE) was calculated and used to explain the gas-phase enthalpic contribution to binding. The correlation of the ligand potencies to the protein-ligand interaction energies gained from FMO was examined and was seen to give a good correlation which outperformed three MM force field based scoring functions used to appoximate the free energy of binding. Although the FMO calculation allows for the enthalpic component of binding interactions to be understood at the quantum level, as it is an in vacuo single point calculation, the entropic component and solvation terms are neglected. For this reason a more accurate and predictive estimate for binding free energy was desired. Therefore, additional terms used to describe the protein-ligand interactions were then calculated to improve the correlation of the FMO derived values to experimental free energies of binding. These terms were used to account for the polar and non-polar solvation of the molecule estimated by the Poisson-Boltzmann equation and the solvent accessible surface area (SASA), respectively, as well as a correction term for ligand entropy. A quantitative structure-activity relationship (QSAR) model obtained by Partial Least Squares projection to latent structures (PLS) analysis of the ligand potencies and the calculated terms showed a strong correlation (r2 = 0.939, q2 = 0.896) for the 14 molecule test set which had a Pearson rank order correlation of 0.97. A training set of a further 14 molecules was well predicted (r2 = 0.842), and could be used to obtain meaningful estimations of the binding free energy. Conclusions Our results show that binding energies calculated with the FMO method correlate well with published data. Analysis of the terms used to derive the FMO energies adds greater understanding to the binding interactions than can be gained by MM methods. Combining this information with additional terms and creating a scaled model to describe the data results in more accurate predictions of ligand potencies than the absolute values obtained by FMO alone. PMID:21219630
On the role of electrostatics in protein-protein interactions
NASA Astrophysics Data System (ADS)
Zhang, Zhe; Witham, Shawn; Alexov, Emil
2011-06-01
The role of electrostatics in protein-protein interactions and binding is reviewed in this paper. A brief outline of the computational modeling, in the framework of continuum electrostatics, is presented and the basic electrostatic effects occurring upon the formation of the complex are discussed. The effect of the salt concentration and pH of the water phase on protein-protein binding free energy is demonstrated which indicates that the increase of the salt concentration tends to weaken the binding, an observation that is attributed to the optimization of the charge-charge interactions across the interface. It is pointed out that the pH-optimum (pH of optimal binding affinity) varies among the protein-protein complexes, and perhaps is a result of their adaptation to particular subcellular compartments. The similarities and differences between hetero- and homo-complexes are outlined and discussed with respect to the binding mode and charge complementarity.
On the role of electrostatics on protein-protein interactions
Zhang, Zhe; Witham, Shawn; Alexov, Emil
2011-01-01
The role of electrostatics on protein-protein interactions and binding is reviewed in this article. A brief outline of the computational modeling, in the framework of continuum electrostatics, is presented and basic electrostatic effects occurring upon the formation of the complex are discussed. The role of the salt concentration and pH of the water phase on protein-protein binding free energy is demonstrated and indicates that the increase of the salt concentration tends to weaken the binding, an observation that is attributed to the optimization of the charge-charge interactions across the interface. It is pointed out that the pH-optimum (pH of optimal binding affinity) varies among the protein-protein complexes, and perhaps is a result of their adaptation to particular subcellular compartment. At the end, the similarities and differences between hetero- and homo-complexes are outlined and discussed with respect to the binding mode and charge complementarity. PMID:21572182
Cortopassi, Wilian A; Simion, Robert; Honsby, Charles E; França, Tanos C C; Paton, Robert S
2015-12-21
JMJD2A catalyses the demethylation of di- and trimethylated lysine residues in histone tails and is a target for the development of new anticancer medicines. Mechanistic details of demethylation are yet to be elucidated and are important for the understanding of epigenetic processes. We have evaluated the initial step of histone demethylation by JMJD2A and demonstrate the dramatic effect of the protein environment upon oxygen binding using quantum mechanics/molecular mechanics (QM/MM) calculations. The changes in electronic structure have been studied for possible spin states and different conformations of O2 , using a combination of quantum and classical simulations. O2 binding to this histone demethylase is computed to occur preferentially as an end-on superoxo radical bound to a high-spin ferric centre, yielding an overall quintet ground state. The favourability of binding is strongly influenced by the surrounding protein: we have quantified this effect using an energy decomposition scheme into electrostatic and dispersion contributions. His182 and the methylated lysine assist while Glu184 and the oxoglutarate cofactor are deleterious for O2 binding. Charge separation in the superoxo-intermediate benefits from the electrostatic stabilization provided by the surrounding residues, stabilizing the binding process significantly. This work demonstrates the importance of the extended protein environment in oxygen binding, and the role of energy decomposition in understanding the physical origin of binding/recognition. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Energetics of drug-DNA interactions.
Chaires, J B
1997-01-01
Understanding the thermodynamics of drug binding to DNA is of both practical and fundamental interest. The practical interest lies in the contribution that thermodynamics can make to the rational design process for the development of new DNA targeted drugs. Thermodynamics offer key insights into the molecular forces that drive complex formation that cannot be obtained by structural or computational studies alone. The fundamental interest in these interactions lies in what they can reveal about the general problems of parsing and predicting ligand binding free energies. For these problems, drug-DNA interactions offer several distinct advantages, among them being that the structures of many drug-DNA complexes are known at high resolution and that such structures reveal that in many cases the drug acts as a rigid body, with little conformational change upon binding. Complete thermodynamic profiles (delta G, delta H, delta S, delta Cp) for numerous drug-DNA interactions have been obtained, with the help of high-sensitivity microcalorimetry. The purpose of this article is to offer a perspective on the interpretation of these thermodynamics parameters, and in particular how they might be correlated with known structural features. Obligatory conformational changes in the DNA to accommodate intercalators and the loss of translational and rotational freedom upon complex formation both present unfavorable free energy barriers for binding. Such barriers must be overcome by favorable free energy contributions from the hydrophobic transfer of ligand from solution into the binding site, polyelectrolyte contributions from coupled ion release, and molecular interactions (hydrogen and ionic bonds, van der Waals interactions) that form within the binding site. Theoretical and semiempirical tools that allow estimates of these contributions to be made will be discussed, and their use in dissecting experimental data illustrated. This process, even at the current level of approximation, can shed considerable light on the drug-DNA binding process.
Sampling protein motion and solvent effect during ligand binding
Limongelli, Vittorio; Marinelli, Luciana; Cosconati, Sandro; La Motta, Concettina; Sartini, Stefania; Mugnaini, Laura; Da Settimo, Federico; Novellino, Ettore; Parrinello, Michele
2012-01-01
An exhaustive description of the molecular recognition mechanism between a ligand and its biological target is of great value because it provides the opportunity for an exogenous control of the related process. Very often this aim can be pursued using high resolution structures of the complex in combination with inexpensive computational protocols such as docking algorithms. Unfortunately, in many other cases a number of factors, like protein flexibility or solvent effects, increase the degree of complexity of ligand/protein interaction and these standard techniques are no longer sufficient to describe the binding event. We have experienced and tested these limits in the present study in which we have developed and revealed the mechanism of binding of a new series of potent inhibitors of Adenosine Deaminase. We have first performed a large number of docking calculations, which unfortunately failed to yield reliable results due to the dynamical character of the enzyme and the complex role of the solvent. Thus, we have stepped up the computational strategy using a protocol based on metadynamics. Our approach has allowed dealing with protein motion and solvation during ligand binding and finally identifying the lowest energy binding modes of the most potent compound of the series, 4-decyl-pyrazolo[1,5-a]pyrimidin-7-one. PMID:22238423
Modulating the DNA affinity of Elk-1 with computationally selected mutations.
Park, Sheldon; Boder, Eric T; Saven, Jeffery G
2005-04-22
In order to regulate gene expression, transcription factors must first bind their target DNA sequences. The affinity of this binding is determined by both the network of interactions at the interface and the entropy change associated with the complex formation. To study the role of structural fluctuation in fine-tuning DNA affinity, we performed molecular dynamics simulations of two highly homologous proteins, Elk-1 and SAP-1, that exhibit different sequence specificity. Simulation studies show that several residues in Elk have significantly higher main-chain root-mean-square deviations than their counterparts in SAP. In particular, a single residue, D69, may contribute to Elk's lower DNA affinity for P(c-fos) by structurally destabilizing the carboxy terminus of the recognition helix. While D69 does not contact DNA directly, the increased mobility in the region may contribute to its weaker binding. We measured the ability of single point mutants of Elk to bind P(c-fos) in a reporter assay, in which D69 of wild-type Elk has been mutated to other residues with higher helix propensity in order to stabilize the local conformation. The gains in transcriptional activity and the free energy of binding suggested from these measurements correlate well with stability gains computed from helix propensity and charge-macrodipole interactions. The study suggests that residues that are distal to the binding interface may indirectly modulate the binding affinity by stabilizing the protein scaffold required for efficient DNA interaction.
Two- and three-body interatomic dispersion energy contributions to binding in molecules and solids
NASA Astrophysics Data System (ADS)
Anatole von Lilienfeld, O.; Tkatchenko, Alexandre
2010-06-01
We present numerical estimates of the leading two- and three-body dispersion energy terms in van der Waals interactions for a broad variety of molecules and solids. The calculations are based on London and Axilrod-Teller-Muto expressions where the required interatomic dispersion energy coefficients, C6 and C9, are computed "on the fly" from the electron density. Inter- and intramolecular energy contributions are obtained using the Tang-Toennies (TT) damping function for short interatomic distances. The TT range parameters are equally extracted on the fly from the electron density using their linear relationship to van der Waals radii. This relationship is empiricially determined for all the combinations of He-Xe rare gas dimers, as well as for the He and Ar trimers. The investigated systems include the S22 database of noncovalent interactions, Ar, benzene and ice crystals, bilayer graphene, C60 dimer, a peptide (Ala10), an intercalated drug-DNA model [ellipticine-d(CG)2], 42 DNA base pairs, a protein (DHFR, 2616 atoms), double stranded DNA (1905 atoms), and 12 molecular crystal polymorphs from crystal structure prediction blind test studies. The two- and three-body interatomic dispersion energies are found to contribute significantly to binding and cohesive energies, for bilayer graphene the latter reaches 50% of experimentally derived binding energy. These results suggest that interatomic three-body dispersion potentials should be accounted for in atomistic simulations when modeling bulky molecules or condensed phase systems.
Two and three-body interatomic dispersion energy contributions to binding in molecules and solids.
DOE Office of Scientific and Technical Information (OSTI.GOV)
von Lilienfeld-Toal, Otto Anatole; Tkatchenko, Alexandre
We present numerical estimates of the leading two- and three-body dispersion energy terms in van der Waals interactions for a broad variety of molecules and solids. The calculations are based on London and Axilrod-Teller-Muto expressions where the required interatomic dispersion energy coefficients, C{sub 6} and C{sub 9}, are computed 'on the fly' from the electron density. Inter- and intramolecular energy contributions are obtained using the Tang-Toennies (TT) damping function for short interatomic distances. The TT range parameters are equally extracted on the fly from the electron density using their linear relationship to van der Waals radii. This relationship is empiriciallymore » determined for all the combinations of He-Xe rare gas dimers, as well as for the He and Ar trimers. The investigated systems include the S22 database of noncovalent interactions, Ar, benzene and ice crystals, bilayer graphene, C{sub 60} dimer, a peptide (Ala{sub 10}), an intercalated drug-DNA model [ellipticine-d(CG){sub 2}], 42 DNA base pairs, a protein (DHFR, 2616 atoms), double stranded DNA (1905 atoms), and 12 molecular crystal polymorphs from crystal structure prediction blind test studies. The two- and three-body interatomic dispersion energies are found to contribute significantly to binding and cohesive energies, for bilayer graphene the latter reaches 50% of experimentally derived binding energy. These results suggest that interatomic three-body dispersion potentials should be accounted for in atomistic simulations when modeling bulky molecules or condensed phase systems.« less
AMMOS2: a web server for protein-ligand-water complexes refinement via molecular mechanics.
Labbé, Céline M; Pencheva, Tania; Jereva, Dessislava; Desvillechabrol, Dimitri; Becot, Jérôme; Villoutreix, Bruno O; Pajeva, Ilza; Miteva, Maria A
2017-07-03
AMMOS2 is an interactive web server for efficient computational refinement of protein-small organic molecule complexes. The AMMOS2 protocol employs atomic-level energy minimization of a large number of experimental or modeled protein-ligand complexes. The web server is based on the previously developed standalone software AMMOS (Automatic Molecular Mechanics Optimization for in silico Screening). AMMOS utilizes the physics-based force field AMMP sp4 and performs optimization of protein-ligand interactions at five levels of flexibility of the protein receptor. The new version 2 of AMMOS implemented in the AMMOS2 web server allows the users to include explicit water molecules and individual metal ions in the protein-ligand complexes during minimization. The web server provides comprehensive analysis of computed energies and interactive visualization of refined protein-ligand complexes. The ligands are ranked by the minimized binding energies allowing the users to perform additional analysis for drug discovery or chemical biology projects. The web server has been extensively tested on 21 diverse protein-ligand complexes. AMMOS2 minimization shows consistent improvement over the initial complex structures in terms of minimized protein-ligand binding energies and water positions optimization. The AMMOS2 web server is freely available without any registration requirement at the URL: http://drugmod.rpbs.univ-paris-diderot.fr/ammosHome.php. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
AMMOS2: a web server for protein–ligand–water complexes refinement via molecular mechanics
Labbé, Céline M.; Pencheva, Tania; Jereva, Dessislava; Desvillechabrol, Dimitri; Becot, Jérôme; Villoutreix, Bruno O.; Pajeva, Ilza
2017-01-01
Abstract AMMOS2 is an interactive web server for efficient computational refinement of protein–small organic molecule complexes. The AMMOS2 protocol employs atomic-level energy minimization of a large number of experimental or modeled protein–ligand complexes. The web server is based on the previously developed standalone software AMMOS (Automatic Molecular Mechanics Optimization for in silico Screening). AMMOS utilizes the physics-based force field AMMP sp4 and performs optimization of protein–ligand interactions at five levels of flexibility of the protein receptor. The new version 2 of AMMOS implemented in the AMMOS2 web server allows the users to include explicit water molecules and individual metal ions in the protein–ligand complexes during minimization. The web server provides comprehensive analysis of computed energies and interactive visualization of refined protein–ligand complexes. The ligands are ranked by the minimized binding energies allowing the users to perform additional analysis for drug discovery or chemical biology projects. The web server has been extensively tested on 21 diverse protein–ligand complexes. AMMOS2 minimization shows consistent improvement over the initial complex structures in terms of minimized protein–ligand binding energies and water positions optimization. The AMMOS2 web server is freely available without any registration requirement at the URL: http://drugmod.rpbs.univ-paris-diderot.fr/ammosHome.php. PMID:28486703
Tidal disruption of open clusters in their parent molecular clouds
NASA Technical Reports Server (NTRS)
Long, Kevin
1989-01-01
A simple model of tidal encounters has been applied to the problem of an open cluster in a clumpy molecular cloud. The parameters of the clumps are taken from the Blitz, Stark, and Long (1988) catalog of clumps in the Rosette molecular cloud. Encounters are modeled as impulsive, rectilinear collisions between Plummer spheres, but the tidal approximation is not invoked. Mass and binding energy changes during an encounter are computed by considering the velocity impulses given to individual stars in a random realization of a Plummer sphere. Mean rates of mass and binding energy loss are then computed by integrating over many encounters. Self-similar evolutionary calculations using these rates indicate that the disruption process is most sensitive to the cluster radius and relatively insensitive to cluster mass. The calculations indicate that clusters which are born in a cloud similar to the Rosette with a cluster radius greater than about 2.5 pc will not survive long enough to leave the cloud. The majority of clusters, however, have smaller radii and will survive the passage through their parent cloud.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Singh, Gurmeet; Nandi, Apurba; Gadre, Shridhar R., E-mail: gadre@iitk.ac.in
2016-03-14
A pragmatic method based on the molecular tailoring approach (MTA) for estimating the complete basis set (CBS) limit at Møller-Plesset second order perturbation (MP2) theory accurately for large molecular clusters with limited computational resources is developed. It is applied to water clusters, (H{sub 2}O){sub n} (n = 7, 8, 10, 16, 17, and 25) optimized employing aug-cc-pVDZ (aVDZ) basis-set. Binding energies (BEs) of these clusters are estimated at the MP2/aug-cc-pVNZ (aVNZ) [N = T, Q, and 5 (whenever possible)] levels of theory employing grafted MTA (GMTA) methodology and are found to lie within 0.2 kcal/mol of the corresponding full calculationmore » MP2 BE, wherever available. The results are extrapolated to CBS limit using a three point formula. The GMTA-MP2 calculations are feasible on off-the-shelf hardware and show around 50%–65% saving of computational time. The methodology has a potential for application to molecular clusters containing ∼100 atoms.« less
Acioli, Paulo H.; Jellinek, Julius
2017-07-14
A theoretical/computational description and analysis of the spectra of electron binding energies of Al 12 -, Al 13 - and Al 12Ni- clusters, which differ in size and/or composition by a single atom yet possess strikingly different measured photoelectron spectra, is presented. It is shown that the measured spectra can not only be reproduced computationally with quantitative fidelity – this is achieved through a combination of state-of-the-art density functional theory with a highly accurate scheme for conversion of the Kohn-Sham eigenenergies into electron binding energies – but also explained in terms of the effects of size, structure/symmetry and composition. Furthermore,more » a new methodology is developed and applied that provides for disentanglement and differential assignment of the separate roles played by size, structure/symmetry and composition in defining the observed differences in the measured spectra. The methodology is general and applicable to any finite system, homogeneous or heterogeneous. Finally, we project that in combination with advances in synthesis techniques this methodology will become an indispensable computation-based aid in the design of controlled synthesis protocols for manufacture of nanosystems and nanodevices with precisely desired electronic and other characteristics.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Acioli, Paulo H.; Jellinek, Julius
A theoretical/computational description and analysis of the spectra of electron binding energies of Al 12 -, Al 13 - and Al 12Ni- clusters, which differ in size and/or composition by a single atom yet possess strikingly different measured photoelectron spectra, is presented. It is shown that the measured spectra can not only be reproduced computationally with quantitative fidelity – this is achieved through a combination of state-of-the-art density functional theory with a highly accurate scheme for conversion of the Kohn-Sham eigenenergies into electron binding energies – but also explained in terms of the effects of size, structure/symmetry and composition. Furthermore,more » a new methodology is developed and applied that provides for disentanglement and differential assignment of the separate roles played by size, structure/symmetry and composition in defining the observed differences in the measured spectra. The methodology is general and applicable to any finite system, homogeneous or heterogeneous. Finally, we project that in combination with advances in synthesis techniques this methodology will become an indispensable computation-based aid in the design of controlled synthesis protocols for manufacture of nanosystems and nanodevices with precisely desired electronic and other characteristics.« less
Wang, Lingle; Wu, Yujie; Deng, Yuqing; Kim, Byungchan; Pierce, Levi; Krilov, Goran; Lupyan, Dmitry; Robinson, Shaughnessy; Dahlgren, Markus K; Greenwood, Jeremy; Romero, Donna L; Masse, Craig; Knight, Jennifer L; Steinbrecher, Thomas; Beuming, Thijs; Damm, Wolfgang; Harder, Ed; Sherman, Woody; Brewer, Mark; Wester, Ron; Murcko, Mark; Frye, Leah; Farid, Ramy; Lin, Teng; Mobley, David L; Jorgensen, William L; Berne, Bruce J; Friesner, Richard A; Abel, Robert
2015-02-25
Designing tight-binding ligands is a primary objective of small-molecule drug discovery. Over the past few decades, free-energy calculations have benefited from improved force fields and sampling algorithms, as well as the advent of low-cost parallel computing. However, it has proven to be challenging to reliably achieve the level of accuracy that would be needed to guide lead optimization (∼5× in binding affinity) for a wide range of ligands and protein targets. Not surprisingly, widespread commercial application of free-energy simulations has been limited due to the lack of large-scale validation coupled with the technical challenges traditionally associated with running these types of calculations. Here, we report an approach that achieves an unprecedented level of accuracy across a broad range of target classes and ligands, with retrospective results encompassing 200 ligands and a wide variety of chemical perturbations, many of which involve significant changes in ligand chemical structures. In addition, we have applied the method in prospective drug discovery projects and found a significant improvement in the quality of the compounds synthesized that have been predicted to be potent. Compounds predicted to be potent by this approach have a substantial reduction in false positives relative to compounds synthesized on the basis of other computational or medicinal chemistry approaches. Furthermore, the results are consistent with those obtained from our retrospective studies, demonstrating the robustness and broad range of applicability of this approach, which can be used to drive decisions in lead optimization.
2018-01-01
Approximately 90% of the structures in the Protein Data Bank (PDB) were obtained by X-ray crystallography or electron microscopy. Whereas the overall quality of structure is considered high, thanks to a wide range of tools for structure validation, uncertainties may arise from density maps of small molecules, such as organic ligands, ions or water, which are non-covalently bound to the biomolecules. Even with some experience and chemical intuition, the assignment of such disconnected electron densities is often far from obvious. In this study, we suggest the use of molecular dynamics (MD) simulations and free energy calculations, which are well-established computational methods, to aid in the assignment of ambiguous disconnected electron densities. Specifically, estimates of (i) relative binding affinities, for instance between an ion and water, (ii) absolute binding free energies, i.e., free energies for transferring a solute from bulk solvent to a binding site, and (iii) stability assessments during equilibrium simulations may reveal the most plausible assignments. We illustrate this strategy using the crystal structure of the fluoride specific channel (Fluc), which contains five disconnected electron densities previously interpreted as four fluoride and one sodium ion. The simulations support the assignment of the sodium ion. In contrast, calculations of relative and absolute binding free energies as well as stability assessments during free MD simulations suggest that four of the densities represent water molecules instead of fluoride. The assignment of water is compatible with the loss of these densities in the non-conductive F82I/F85I mutant of Fluc. We critically discuss the role of the ion force fields for the calculations presented here. Overall, these findings indicate that MD simulations and free energy calculations are helpful tools for modeling water and ions into crystallographic density maps. PMID:29771936
Uncovering Molecular Bases Underlying Bone Morphogenetic Protein Receptor Inhibitor Selectivity
Alsamarah, Abdelaziz; LaCuran, Alecander E.; Oelschlaeger, Peter; Hao, Jijun; Luo, Yun
2015-01-01
Abnormal alteration of bone morphogenetic protein (BMP) signaling is implicated in many types of diseases including cancer and heterotopic ossifications. Hence, small molecules targeting BMP type I receptors (BMPRI) to interrupt BMP signaling are believed to be an effective approach to treat these diseases. However, lack of understanding of the molecular determinants responsible for the binding selectivity of current BMP inhibitors has been a big hindrance to the development of BMP inhibitors for clinical use. To address this issue, we carried out in silico experiments to test whether computational methods can reproduce and explain the high selectivity of a small molecule BMP inhibitor DMH1 on BMPRI kinase ALK2 vs. the closely related TGF-β type I receptor kinase ALK5 and vascular endothelial growth factor receptor type 2 (VEGFR2) tyrosine kinase. We found that, while the rigid docking method used here gave nearly identical binding affinity scores among the three kinases; free energy perturbation coupled with Hamiltonian replica-exchange molecular dynamics (FEP/H-REMD) simulations reproduced the absolute binding free energies in excellent agreement with experimental data. Furthermore, the binding poses identified by FEP/H-REMD led to a quantitative analysis of physical/chemical determinants governing DMH1 selectivity. The current work illustrates that small changes in the binding site residue type (e.g. pre-hinge region in ALK2 vs. ALK5) or side chain orientation (e.g. Tyr219 in caALK2 vs. wtALK2), as well as a subtle structural modification on the ligand (e.g. DMH1 vs. LDN193189) will cause distinct binding profiles and selectivity among BMP inhibitors. Therefore, the current computational approach represents a new way of investigating BMP inhibitors. Our results provide critical information for designing exclusively selective BMP inhibitors for the development of effective pharmacotherapy for diseases caused by aberrant BMP signaling. PMID:26133550
Accurate and Reliable Prediction of the Binding Affinities of Macrocycles to Their Protein Targets.
Yu, Haoyu S; Deng, Yuqing; Wu, Yujie; Sindhikara, Dan; Rask, Amy R; Kimura, Takayuki; Abel, Robert; Wang, Lingle
2017-12-12
Macrocycles have been emerging as a very important drug class in the past few decades largely due to their expanded chemical diversity benefiting from advances in synthetic methods. Macrocyclization has been recognized as an effective way to restrict the conformational space of acyclic small molecule inhibitors with the hope of improving potency, selectivity, and metabolic stability. Because of their relatively larger size as compared to typical small molecule drugs and the complexity of the structures, efficient sampling of the accessible macrocycle conformational space and accurate prediction of their binding affinities to their target protein receptors poses a great challenge of central importance in computational macrocycle drug design. In this article, we present a novel method for relative binding free energy calculations between macrocycles with different ring sizes and between the macrocycles and their corresponding acyclic counterparts. We have applied the method to seven pharmaceutically interesting data sets taken from recent drug discovery projects including 33 macrocyclic ligands covering a diverse chemical space. The predicted binding free energies are in good agreement with experimental data with an overall root-mean-square error (RMSE) of 0.94 kcal/mol. This is to our knowledge the first time where the free energy of the macrocyclization of linear molecules has been directly calculated with rigorous physics-based free energy calculation methods, and we anticipate the outstanding accuracy demonstrated here across a broad range of target classes may have significant implications for macrocycle drug discovery.
Impact of calcium on N1 influenza neuraminidase dynamics and binding free energy.
Lawrenz, Morgan; Wereszczynski, Jeff; Amaro, Rommie; Walker, Ross; Roitberg, Adrian; McCammon, J Andrew
2010-08-15
The highly pathogenic influenza strains H5N1 and H1N1 are currently treated with inhibitors of the viral surface protein neuraminidase (N1). Crystal structures of N1 indicate a conserved, high affinity calcium binding site located near the active site. The specific role of this calcium in the enzyme mechanism is unknown, though it has been shown to be important for enzymatic activity and thermostability. We report molecular dynamics (MD) simulations of calcium-bound and calcium-free N1 complexes with the inhibitor oseltamivir (marketed as the drug Tamiflu), independently using both the AMBER FF99SB and GROMOS96 force fields, to give structural insight into calcium stabilization of key framework residues. Y347, which demonstrates similar sampling patterns in the simulations of both force fields, is implicated as an important N1 residue that can "clamp" the ligand into a favorable binding pose. Free energy perturbation and thermodynamic integration calculations, using two different force fields, support the importance of Y347 and indicate a +3 to +5 kcal/mol change in the binding free energy of oseltamivir in the absence of calcium. With the important role of structure-based drug design for neuraminidase inhibitors and the growing literature on emerging strains and subtypes, inclusion of this calcium for active site stability is particularly crucial for computational efforts such as homology modeling, virtual screening, and free energy methods. 2010 Wiley-Liss, Inc.
Gresh, Nohad; El Hage, Krystel; Perahia, David; Piquemal, Jean-Philip; Berthomieu, Catherine; Berthomieu, Dorothée
2014-11-05
The existence of a network of structured waters in the vicinity of the bimetallic site of Cu/Zn-superoxide dismutase (SOD) has been inferred from high-resolution X-ray crystallography. Long-duration molecular dynamics (MD) simulations could enable to quantify the lifetimes and possible interchanges of these waters between themselves as well as with a ligand diffusing toward the bimetallic site. The presence of several charged or polar ligands makes it necessary to resort to second-generation polarizable potentials. As a first step toward such simulations, we benchmark in this article the accuracy of one such potential, sum of interactions between fragments Ab initio computed (SIBFA), by comparisons with quantum mechanics (QM) computations. We first consider the bimetallic binding site of a Cu/Zn-SOD, in which three histidines and a water molecule are bound to Cu(I) and three histidines and one aspartate are bound to Zn(II). The comparisons are made for different His6 complexes with either one or both cations, and either with or without Asp and water. The total net charges vary from zero to three. We subsequently perform preliminary short-duration MD simulations of 296 waters solvating Cu/Zn-SOD. Six representative geometries are selected and energy-minimized. Single-point SIBFA and QM computations are then performed in parallel on model binding sites extracted from these six structures, each of which totals 301 atoms including the closest 28 waters from the Cu metal site. The ranking of their relative stabilities as given by SIBFA is identical to the QM one, and the relative energy differences by both approaches are fully consistent. In addition, the lowest-energy structure, from SIBFA and QM, has a close overlap with the crystallographic one. The SIBFA calculations enable to quantify the impact of polarization and charge transfer in the ranking of the six structures. Five structural waters, which connect Arg141 and Glu131, are endowed with very high dipole moments (2.7-3.0 Debye), equal and larger than the one computed by SIBFA in ice-like arrangements (2.7 D). Copyright © 2014 Wiley Periodicals, Inc.
Modeling Ionization Events iduced by Protein Protein Binding
NASA Astrophysics Data System (ADS)
Mitra, Rooplekha; Shyam, Radhey; Alexov, Emil
2009-11-01
The association of two or more biological macromolecules dramatically change the environment of the amino acids situated at binding interface and could change ionization states of titratable groups. The change of ionization due to the binding results in proton uptake/release and causes pH-dependence of the binding free energy. We apply computational method, as implemented in Multi Conformation Continuum Electrostatics (MCCE) algorithm, to study protonation evens on a large set of protein-protein complexes. Our results indicate that proton uptake/release is a common phenomena in protein binding since in vast majority of the cases (70%) the binding caused at least 0.5 units proton change. The proton uptake/release was further investigated with respect to interfacial area and charges of the monomers and it was found that macroscopic characteristics are not important determinants. Instead, charge complementarity across the interface and the number of unpaired ionizable groups at the interface are the primary source of proton uptake/release.
NASA Astrophysics Data System (ADS)
Marques, Alexandra T.; Antunes, Agostinho; Fernandes, Pedro A.; Ramos, Maria J.
Amyloid-beta (Abeta) binding alcohol dehydrogenase (ABAD) is a multifunctional enzyme involved in maintaining the homeostasis. The enzyme can also mediate some diseases, including genetic diseases, Alzheimer's disease, and possibly some prostate cancers. Potent inhibitors of ABAD might facilitate a better clarification of the functions of the enzyme under normal and pathogenic conditions and might also be used for therapeutic intervention in disease conditions mediated by the enzyme. The AG18051 is the only presently available inhibitor of ABAD. It binds in the active-site cavity of the enzyme and reacts with the NAD+ cofactor to form a covalent adduct. In this work, we use computational methods to perform a rational optimization of the AG18051 inhibitor, through the introduction of chemical substitutions directed to improve the affinity of the inhibitor to the enzyme. The molecular mechanics-Poisson-Boltzmann surface area methodology was used to predict the relative free binding energy of the different modified inhibitor-NAD-enzyme complexes. We show that it is possible to increase significantly the affinity of the inhibitor to the enzyme with small modifications, without changing the overall structure and ADME (absorption, distribution, metabolism, and excretion) properties of the original inhibitor.
Role of the pH in state-dependent blockade of hERG currents
NASA Astrophysics Data System (ADS)
Wang, Yibo; Guo, Jiqing; Perissinotti, Laura L.; Lees-Miller, James; Teng, Guoqi; Durdagi, Serdar; Duff, Henry J.; Noskov, Sergei Yu.
2016-10-01
Mutations that reduce inactivation of the voltage-gated Kv11.1 potassium channel (hERG) reduce binding for a number of blockers. State specific block of the inactivated state of hERG block may increase risks of drug-induced Torsade de pointes. In this study, molecular simulations of dofetilide binding to the previously developed and experimentally validated models of the hERG channel in open and open-inactivated states were combined with voltage-clamp experiments to unravel the mechanism(s) of state-dependent blockade. The computations of the free energy profiles associated with the drug block to its binding pocket in the intra-cavitary site display startling differences in the open and open-inactivated states of the channel. It was also found that drug ionization may play a crucial role in preferential targeting to the open-inactivated state of the pore domain. pH-dependent hERG blockade by dofetilie was studied with patch-clamp recordings. The results show that low pH increases the extent and speed of drug-induced block. Both experimental and computational findings indicate that binding to the open-inactivated state is of key importance to our understanding of the dofetilide’s mode of action.
NASA Astrophysics Data System (ADS)
El-Yadri, M.; Aghoutane, N.; El Aouami, A.; Feddi, E.; Dujardin, F.; Duque, C. A.
2018-05-01
This work reports on theoretical investigation of the temperature and hydrostatic pressure effects on the confined donor impurity in a AlGaAs-GaAs hollow cylindrical core-shell quantum dot. The charges are assumed to be completely confined to the interior of the shell with approximately rigid walls. Within the framework of the effective-mass approximation and by using a variational approach, we have computed the donor binding energies as a function of the shell size in order to study the behavior of the electron-impurity attraction for a very small thickness under the influence of both temperature and hydrostatic pressure. Our results show that the temperature and hydrostatic pressure have a significant influence on the impurity binding energy for large shell quantum dots. It will be shown that the binding energy is more pronounced with increasing pressure and decreasing temperature for any impurity position and quantum dot size. The photoionization cross section is also analyzed by considering only the in-plane incident radiation polarization. Its behavior is investigated as a function of photon energy for different values of pressure and temperature. The opposite effects caused by temperature and hydrostatic pressure reveal a big practical interest and offer an alternative way to tuning of correlated electron-impurity transitions in optoelectronic devices.
Rational computational design for the development of andrographolide molecularly imprinted polymer
NASA Astrophysics Data System (ADS)
Krishnan, Hemavathi; Islam, K. M. Shafiqul; Hamzah, Zainab; Ahmad, Mohd Noor
2017-10-01
Andrographolide is a popular medicinal compound derived from Andrographis Paniculata (AP). Molecularly Imprint Polymer (MIP) is a "Lock and Key" approach, where MIP is the lock and Andrographolide is the key which fits to the MIP lock by both physically and chemically. MIP will be used as selective extraction tool to enrich Andrographolide bioactive compound. Pre-polymerization step is crucial to design MIP. This work investigates molecular interactions and the Gibbs free binding energies on the development of MIP. The structure of Andrographolide (template) and functional monomers were drawn in HyperChem 8.0.10. A hybrid quantum chemical model was used with a few functional monomers. Possible conformations of template and functional monomer as 1:n (n < 4) were designed and simulated to geometrically optimize the complex to the lowest energy in gas phase. The Gibbs free binding energies of each conformation were calculated using semi-empirical PM3 simulation method. Results proved that functional monomers that contain carboxylic group shows higher binding energy compared to those with amine functional group. Itaconic acid (IA) chosen as the best functional monomer at optimum ratio (1:3) of template: monomer to prepare andrographolide MIP. This study demonstrates the importance of studying intermolecular interaction among template, functional monomer and template-monomer ratio in developing MIP.
NASA Astrophysics Data System (ADS)
Patil, Sachin P.; Pacitti, Michael F.; Gilroy, Kevin S.; Ruggiero, John C.; Griffin, Jonathan D.; Butera, Joseph J.; Notarfrancesco, Joseph M.; Tran, Shawn; Stoddart, John W.
2015-02-01
The inhibition of tumor suppressor p53 protein due to its direct interaction with oncogenic murine double minute 2 (MDM2) protein, plays a central role in almost 50 % of all human tumor cells. Therefore, pharmacological inhibition of the p53-binding pocket on MDM2, leading to p53 activation, presents an important therapeutic target against these cancers expressing wild-type p53. In this context, the present study utilized an integrated virtual and experimental screening approach to screen a database of approved drugs for potential p53-MDM2 interaction inhibitors. Specifically, using an ensemble rigid-receptor docking approach with four MDM2 protein crystal structures, six drug molecules were identified as possible p53-MDM2 inhibitors. These drug molecules were then subjected to further molecular modeling investigation through flexible-receptor docking followed by Prime/MM-GBSA binding energy analysis. These studies identified fluspirilene, an approved antipsychotic drug, as a top hit with MDM2 binding mode and energy similar to that of a native MDM2 crystal ligand. The molecular dynamics simulations suggested stable binding of fluspirilene to the p53-binding pocket on MDM2 protein. The experimental testing of fluspirilene showed significant growth inhibition of human colon tumor cells in a p53-dependent manner. Fluspirilene also inhibited growth of several other human tumor cell lines in the NCI60 cell line panel. Taken together, these computational and experimental data suggest a potentially novel role of fluspirilene in inhibiting the p53-MDM2 interaction. It is noteworthy here that fluspirilene has a long history of safe human use, thus presenting immediate clinical potential as a cancer therapeutic. Furthermore, fluspirilene could also serve as a structurally-novel lead molecule for the development of more potent, small-molecule p53-MDM2 inhibitors against several types of cancer. Importantly, the combined computational and experimental screening protocol presented in this study may also prove useful for screening other commercially-available compound databases for identification of novel, small molecule p53-MDM2 inhibitors.
Wang, Yan; Cai, Wen-Sheng; Chen, Luonan; Wang, Guanyu
2017-02-14
Phosphoglycerate mutase 1 (PGAM1) catalyzes the eighth step of glycolysis and is often found upregulated in cancer cells. To test the hypothesis that the phosphorylation of tyrosine 26 residue of PGAM1 greatly enhances its activity, we performed both conventional and steered molecular dynamics simulations on the binding and unbinding of PGAM1 to its substrates, with tyrosine 26 either phosphorylated or not. We analyzed the simulated data in terms of structural stability, hydrogen bond formation, binding free energy, etc. We found that tyrosine 26 phosphorylation enhances the binding of PGAM1 to its substrates through generating electrostatic environment and structural features that are advantageous to the binding. Our results may provide valuable insights into computer-aided design of drugs that specifically target cancer cells with PGAM1 tyrosine 26 phosphorylated.
A detailed spectroscopic study on the interaction of Rhodamine 6G with human hemoglobin.
Mandal, Paulami; Bardhan, Munmun; Ganguly, Tapan
2010-05-03
UV-vis, time-resolved fluorescence and circular dichroism spectroscopic investigations have been made to reveal the nature of the interactions between xanthene dye Rhodamine 6G and the well known protein hemoglobin. From the analysis of the steady-state and time-resolved fluorescence quenching of Rhodamine 6G in aqueous solutions in presence of hemoglobin, it is revealed that the quenching is static in nature. The primary binding pattern between Rhodamine and hemoglobin has been interpreted as combined effect of hydrophobic association and electrostatic interaction. The binding constants, number of binding sites and thermodynamic parameters at various pH of the environment have been computed. The binding average distance between the energy donor Rhodamine and acceptor hemoglobin has been determined from the Forster's theory. Copyright 2010 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Henke, Paul S.; Mak, Chi H.
2014-08-01
The thermodynamic stability of a folded RNA is intricately tied to the counterions and the free energy of this interaction must be accounted for in any realistic RNA simulations. Extending a tight-binding model published previously, in this paper we investigate the fundamental structure of charges arising from the interaction between small functional RNA molecules and divalent ions such as Mg2+ that are especially conducive to stabilizing folded conformations. The characteristic nature of these charges is utilized to construct a discretely connected energy landscape that is then traversed via a novel application of a deterministic graph search technique. This search method can be incorporated into larger simulations of small RNA molecules and provides a fast and accurate way to calculate the free energy arising from the interactions between an RNA and divalent counterions. The utility of this algorithm is demonstrated within a fully atomistic Monte Carlo simulation of the P4-P6 domain of the Tetrahymena group I intron, in which it is shown that the counterion-mediated free energy conclusively directs folding into a compact structure.
Henke, Paul S; Mak, Chi H
2014-08-14
The thermodynamic stability of a folded RNA is intricately tied to the counterions and the free energy of this interaction must be accounted for in any realistic RNA simulations. Extending a tight-binding model published previously, in this paper we investigate the fundamental structure of charges arising from the interaction between small functional RNA molecules and divalent ions such as Mg(2+) that are especially conducive to stabilizing folded conformations. The characteristic nature of these charges is utilized to construct a discretely connected energy landscape that is then traversed via a novel application of a deterministic graph search technique. This search method can be incorporated into larger simulations of small RNA molecules and provides a fast and accurate way to calculate the free energy arising from the interactions between an RNA and divalent counterions. The utility of this algorithm is demonstrated within a fully atomistic Monte Carlo simulation of the P4-P6 domain of the Tetrahymena group I intron, in which it is shown that the counterion-mediated free energy conclusively directs folding into a compact structure.
Exhaustively sampling peptide adsorption with metadynamics.
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.
QM/QM approach to model energy disorder in amorphous organic semiconductors.
Friederich, Pascal; Meded, Velimir; Symalla, Franz; Elstner, Marcus; Wenzel, Wolfgang
2015-02-10
It is an outstanding challenge to model the electronic properties of organic amorphous materials utilized in organic electronics. Computation of the charge carrier mobility is a challenging problem as it requires integration of morphological and electronic degrees of freedom in a coherent methodology and depends strongly on the distribution of polaron energies in the system. Here we represent a QM/QM model to compute the polaron energies combining density functional methods for molecules in the vicinity of the polaron with computationally efficient density functional based tight binding methods in the rest of the environment. For seven widely used amorphous organic semiconductor materials, we show that the calculations are accelerated up to 1 order of magnitude without any loss in accuracy. Considering that the quantum chemical step is the efficiency bottleneck of a workflow to model the carrier mobility, these results are an important step toward accurate and efficient disordered organic semiconductors simulations, a prerequisite for accelerated materials screening and consequent component optimization in the organic electronics industry.
Xie, Huiding; Li, Yupeng; Yu, Fang; Xie, Xiaoguang; Qiu, Kaixiong; Fu, Jijun
2015-11-16
In the recent cancer treatment, B-Raf kinase is one of key targets. Nowadays, a group of imidazopyridines as B-Raf kinase inhibitors have been reported. In order to investigate the interaction between this group of inhibitors and B-Raf kinase, molecular docking, molecular dynamic (MD) simulation and binding free energy (ΔGbind) calculation were performed in this work. Molecular docking was carried out to identify the key residues in the binding site, and MD simulations were performed to determine the detail binding mode. The results obtained from MD simulation reveal that the binding site is stable during the MD simulations, and some hydrogen bonds (H-bonds) in MD simulations are different from H-bonds in the docking mode. Based on the obtained MD trajectories, ΔGbind was computed by using Molecular Mechanics Generalized Born Surface Area (MM-GBSA), and the obtained energies are consistent with the activities. An energetic analysis reveals that both electrostatic and van der Waals contributions are important to ΔGbind, and the unfavorable polar solvation contribution results in the instability of the inhibitor with the lowest activity. These results are expected to understand the binding between B-Raf and imidazopyridines and provide some useful information to design potential B-Raf inhibitors.
2013-01-01
Here we present a novel, end-point method using the dead-end-elimination and A* algorithms to efficiently and accurately calculate the change in free energy, enthalpy, and configurational entropy of binding for ligand–receptor association reactions. We apply the new approach to the binding of a series of human immunodeficiency virus (HIV-1) protease inhibitors to examine the effect ensemble reranking has on relative accuracy as well as to evaluate the role of the absolute and relative ligand configurational entropy losses upon binding in affinity differences for structurally related inhibitors. Our results suggest that most thermodynamic parameters can be estimated using only a small fraction of the full configurational space, and we see significant improvement in relative accuracy when using an ensemble versus single-conformer approach to ligand ranking. We also find that using approximate metrics based on the single-conformation enthalpy differences between the global minimum energy configuration in the bound as well as unbound states also correlates well with experiment. Using a novel, additive entropy expansion based on conditional mutual information, we also analyze the source of ligand configurational entropy loss upon binding in terms of both uncoupled per degree of freedom losses as well as changes in coupling between inhibitor degrees of freedom. We estimate entropic free energy losses of approximately +24 kcal/mol, 12 kcal/mol of which stems from loss of translational and rotational entropy. Coupling effects contribute only a small fraction to the overall entropy change (1–2 kcal/mol) but suggest differences in how inhibitor dihedral angles couple to each other in the bound versus unbound states. The importance of accounting for flexibility in drug optimization and design is also discussed. PMID:24250277
Kearns, F L; Hudson, P S; Boresch, S; Woodcock, H L
2016-01-01
Enzyme activity is inherently linked to free energies of transition states, ligand binding, protonation/deprotonation, etc.; these free energies, and thus enzyme function, can be affected by residue mutations, allosterically induced conformational changes, and much more. Therefore, being able to predict free energies associated with enzymatic processes is critical to understanding and predicting their function. Free energy simulation (FES) has historically been a computational challenge as it requires both the accurate description of inter- and intramolecular interactions and adequate sampling of all relevant conformational degrees of freedom. The hybrid quantum mechanical molecular mechanical (QM/MM) framework is the current tool of choice when accurate computations of macromolecular systems are essential. Unfortunately, robust and efficient approaches that employ the high levels of computational theory needed to accurately describe many reactive processes (ie, ab initio, DFT), while also including explicit solvation effects and accounting for extensive conformational sampling are essentially nonexistent. In this chapter, we will give a brief overview of two recently developed methods that mitigate several major challenges associated with QM/MM FES: the QM non-Boltzmann Bennett's acceptance ratio method and the QM nonequilibrium work method. We will also describe usage of these methods to calculate free energies associated with (1) relative properties and (2) along reaction paths, using simple test cases with relevance to enzymes examples. © 2016 Elsevier Inc. All rights reserved.
Krishnaraj, R Navanietha; Chandran, Saravanan; Pal, Parimal; Berchmans, Sheela
2013-12-01
There is an immense interest among the researchers to identify new herbicides which are effective against the herbs without affecting the environment. In this work, photosynthetic pigments are used as the ligands to predict their herbicidal activity. The enzyme 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase is a good target for the herbicides. Homology modeling of the target enzyme is done using Modeler 9.11 and the model is validated. Docking studies were performed with AutoDock Vina algorithm to predict the binding of the natural pigments such as β-carotene, chlorophyll a, chlorophyll b, phycoerythrin and phycocyanin to the target. β-carotene, phycoerythrin and phycocyanin have higher binding energies indicating the herbicidal activity of the pigments. This work reports a procedure to screen herbicides with computational molecular approach. These pigments will serve as potential bioherbicides in the future.
Suri, Charu; Joshi, Harish C; Naik, Pradeep Kumar
2015-05-01
The initiation of microtubule assembly within cells is guided by a cone shaped multi-protein complex, γ-tubulin ring complex (γTuRC) containing γ-tubulin and atleast five other γ-tubulin-complex proteins (GCPs), i.e., GCP2, GCP3, GCP4, GCP5, and GCP6. The rim of γTuRC is a ring of γ-tubulin molecules that interacts, via one of its longitudinal interfaces, with GCP2, GCP3, or GCP4 and, via other interface, with α/β-tubulin dimers recruited for the microtubule lattice formation. These interactions however, are not well understood in the absence of crystal structure of functional reconstitution of γTuRC subunits. In this study, we elucidate the atomic interactions between γ-tubulin and GCP4 through computational techniques. We simulated two complexes of γ-tubulin-GCP4 complex (we called dimer1 and dimer2) for 25 ns to obtain a stable complex and calculated the ensemble average of binding free energies of -158.82 and -170.19 kcal/mol for dimer1 and -79.53 and -101.50 kcal/mol for dimer2 using MM-PBSA and MM-GBSA methods, respectively. These highly favourable binding free energy values points to very robust interactions between GCP4 and γ-tubulin. From the results of the free-energy decomposition and the computational alanine scanning calculation, we identified the amino acids crucial for the interaction of γ-tubulin with GCP4, called hotspots. Furthermore, in the endeavour to identify chemical leads that might interact at the interface of γ-tubulin-GCP4 complex; we found a class of compounds based on the plant alkaloid, noscapine that binds with high affinity in a cavity close to γ-tubulin-GCP4 interface compared with previously reported compounds. All noscapinoids displayed stable interaction throughout the simulation, however, most robust interaction was observed for bromo-noscapine followed by noscapine and amino-noscapine. This offers a novel chemical scaffold for γ-tubulin binding drugs near γ-tubulin-GCP4 interface. © 2015 Wiley Periodicals, Inc.
Alchemical Free Energy Calculations for Nucleotide Mutations in Protein-DNA Complexes.
Gapsys, Vytautas; de Groot, Bert L
2017-12-12
Nucleotide-sequence-dependent interactions between proteins and DNA are responsible for a wide range of gene regulatory functions. Accurate and generalizable methods to evaluate the strength of protein-DNA binding have long been sought. While numerous computational approaches have been developed, most of them require fitting parameters to experimental data to a certain degree, e.g., machine learning algorithms or knowledge-based statistical potentials. Molecular-dynamics-based free energy calculations offer a robust, system-independent, first-principles-based method to calculate free energy differences upon nucleotide mutation. We present an automated procedure to set up alchemical MD-based calculations to evaluate free energy changes occurring as the result of a nucleotide mutation in DNA. We used these methods to perform a large-scale mutation scan comprising 397 nucleotide mutation cases in 16 protein-DNA complexes. The obtained prediction accuracy reaches 5.6 kJ/mol average unsigned deviation from experiment with a correlation coefficient of 0.57 with respect to the experimentally measured free energies. Overall, the first-principles-based approach performed on par with the molecular modeling approaches Rosetta and FoldX. Subsequently, we utilized the MD-based free energy calculations to construct protein-DNA binding profiles for the zinc finger protein Zif268. The calculation results compare remarkably well with the experimentally determined binding profiles. The software automating the structure and topology setup for alchemical calculations is a part of the pmx package; the utilities have also been made available online at http://pmx.mpibpc.mpg.de/dna_webserver.html .
A "Stepping Stone" Approach for Obtaining Quantum Free Energies of Hydration.
Sampson, Chris; Fox, Thomas; Tautermann, Christofer S; Woods, Christopher; Skylaris, Chris-Kriton
2015-06-11
We present a method which uses DFT (quantum, QM) calculations to improve free energies of binding computed with classical force fields (classical, MM). To overcome the incomplete overlap of configurational spaces between MM and QM, we use a hybrid Monte Carlo approach to generate quickly correct ensembles of structures of intermediate states between a MM and a QM/MM description, hence taking into account a great fraction of the electronic polarization of the quantum system, while being able to use thermodynamic integration to compute the free energy of transition between the MM and QM/MM. Then, we perform a final transition from QM/MM to full QM using a one-step free energy perturbation approach. By using QM/MM as a stepping stone toward the full QM description, we find very small convergence errors (<1 kJ/mol) in the transition to full QM. We apply this method to compute hydration free energies, and we obtain consistent improvements over the MM values for all molecules we used in this study. This approach requires large-scale DFT calculations as the full QM systems involved the ligands and all waters in their simulation cells, so the linear-scaling DFT code ONETEP was used for these calculations.
Conformational elasticity can facilitate TALE-DNA recognition
Lei, Hongxing; Sun, Jiya; Baldwin, Enoch P.; Segal, David J.; Duan, Yong
2015-01-01
Sequence-programmable transcription activator-like effector (TALE) proteins have emerged as a highly efficient tool for genome engineering. Recent crystal structures depict a transition between an open unbound solenoid and more compact DNA-bound solenoid formed by the 34 amino acid repeats. How TALEs switch conformation between these two forms without substantial energetic compensation, and how the repeat-variable di-residues (RVDs) discriminate between the cognate base and other bases still remain unclear. Computational analysis on these two aspects of TALE-DNA interaction mechanism has been conducted in order to achieve a better understanding of the energetics. High elasticity was observed in the molecular dynamics simulations of DNA-free TALE structure that started from the bound conformation where it sampled a wide range of conformations including the experimentally determined apo- and bound- conformations. This elastic feature was also observed in the simulations starting from the apo form which suggests low free energy barrier between the two conformations and small compensation required upon binding. To analyze binding specificity, we performed free energy calculations of various combinations of RVDs and bases using Poisson-Boltzmann/surface area (PBSA) and other approaches. The PBSA calculations indicated that the native RVD-base structures had lower binding free energy than mismatched structures for most of the RVDs examined. Our theoretical analyses provided new insight on the dynamics and energetics of TALE-DNA binding mechanism. PMID:24629191
Conformational elasticity can facilitate TALE-DNA recognition.
Lei, Hongxing; Sun, Jiya; Baldwin, Enoch P; Segal, David J; Duan, Yong
2014-01-01
Sequence-programmable transcription activator-like effector (TALE) proteins have emerged as a highly efficient tool for genome engineering. Recent crystal structures depict a transition between an open unbound solenoid and more compact DNA-bound solenoid formed by the 34 amino acid repeats. How TALEs switch conformation between these two forms without substantial energetic compensation, and how the repeat-variable di-residues (RVDs) discriminate between the cognate base and other bases still remain unclear. Computational analysis on these two aspects of TALE-DNA interaction mechanism has been conducted in order to achieve a better understanding of the energetics. High elasticity was observed in the molecular dynamics simulations of DNA-free TALE structure that started from the bound conformation where it sampled a wide range of conformations including the experimentally determined apo and bound conformations. This elastic feature was also observed in the simulations starting from the apo form which suggests low free energy barrier between the two conformations and small compensation required upon binding. To analyze binding specificity, we performed free energy calculations of various combinations of RVDs and bases using Poisson-Boltzmann surface area (PBSA) and other approaches. The PBSA calculations indicated that the native RVD-base structures had lower binding free energy than mismatched structures for most of the RVDs examined. Our theoretical analyses provided new insight on the dynamics and energetics of TALE-DNA binding mechanism. © 2014 Elsevier Inc. All rights reserved.
Baril, Stefanie A; Koenig, Amber L; Krone, Mackenzie W; Albanese, Katherine I; He, Cyndi Qixin; Lee, Ga Young; Houk, Kendall N; Waters, Marcey L; Brustad, Eric M
2017-12-06
Trimethyllysine (Kme3) reader proteins are targets for inhibition due to their role in mediating gene expression. Although all such reader proteins bind Kme3 in an aromatic cage, the driving force for binding may differ; some readers exhibit evidence for cation-π interactions whereas others do not. We report a general unnatural amino acid mutagenesis approach to quantify the contribution of individual tyrosines to cation binding using the HP1 chromodomain as a model system. We demonstrate that two tyrosines (Y24 and Y48) bind to a Kme3-histone tail peptide via cation-π interactions, but linear free energy trends suggest they do not contribute equally to binding. X-ray structures and computational analysis suggest that the distance and degree of contact between Tyr residues and Kme3 plays an important role in tuning cation-π-mediated Kme3 recognition. Although cation-π interactions have been studied in a number of proteins, this work is the first to utilize direct binding assays, X-ray crystallography, and modeling, to pinpoint factors that influence the magnitude of the individual cation-π interactions.
Taylor, Cooper A; Miller, Bill R; Shah, Soleil S; Parish, Carol A
2017-02-01
Mutations in the amyloid precursor protein (APP) are responsible for the formation of amyloid-β peptides. These peptides play a role in Alzheimer's and other dementia-related diseases. The cargo binding domain of the kinesin-1 light chain motor protein (KLC1) may be responsible for transporting APP either directly or via interaction with C-jun N-terminal kinase-interacting protein 1 (JIP1). However, to date there has been no direct experimental or computational assessment of such binding at the atomistic level. We used molecular dynamics and free energy estimations to gauge the affinity for the binary complexes of KLC1, APP, and JIP1. We find that all binary complexes (KLC1:APP, KLC1:JIP1, and APP:JIP1) contain conformations with favorable binding free energies. For KLC1:APP the inclusion of approximate entropies reduces the favorability. This is likely due to the flexibility of the 42-residue APP protein. In all cases we analyze atomistic/residue driving forces for favorable interactions. Proteins 2017; 85:221-234. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Theoretical and experimental study of polycyclic aromatic compounds as β-tubulin inhibitors.
Olazarán, Fabian E; García-Pérez, Carlos A; Bandyopadhyay, Debasish; Balderas-Rentería, Isaias; Reyes-Figueroa, Angel D; Henschke, Lars; Rivera, Gildardo
2017-03-01
In this work, through a docking analysis of compounds from the ZINC chemical library on human β-tubulin using high performance computer cluster, we report new polycyclic aromatic compounds that bind with high energy on the colchicine binding site of β-tubulin, suggesting three new key amino acids. However, molecular dynamic analysis showed low stability in the interaction between ligand and receptor. Results were confirmed experimentally in in vitro and in vivo models that suggest that molecular dynamics simulation is the best option to find new potential β-tubulin inhibitors. Graphical abstract Bennett's acceptance ratio (BAR) method.
NASA Astrophysics Data System (ADS)
Segura-Cabrera, Aldo; Bocanegra-García, Virgilio; Lizarazo-Ortega, Cristian; Guo, Xianwu; Correa-Basurto, José; Rodríguez-Pérez, Mario A.
2011-12-01
Onchocerciasis is a leading cause of blindness with at least 37 million people infected and more than 120 million people at risk of contracting the disease; most (99%) of this population, threatened by infection, live in Africa. The drug of choice for mass treatment is the microfilaricidal Mectizan® (ivermectin); it does not kill the adult stages of the parasite at the standard dose which is a single annual dose aimed at disease control. However, multiple treatments a year with ivermectin have effects on adult worms. The discovery of new therapeutic targets and drugs directed towards the killing of the adult parasites are thus urgently needed. The chitinase of filarial nematodes is a new drug target due to its essential function in the metabolism and molting of the parasite. Closantel is a potent and specific inhibitor of chitinase of Onchocerca volvulus (OvCHT1) and other filarial chitinases. However, the binding mode and specificity of closantel towards OvCHT1 remain unknown. In the absence of a crystallographic structure of OvCHT1, we developed a homology model of OvCHT1 using the currently available X-ray structures of human chitinases as templates. Energy minimization and molecular dynamics (MD) simulation of the model led to a high quality of 3D structure of OvCHIT1. A flexible docking study using closantel as the ligand on the binding site of OvCHIT1 and human chitinases was performed and demonstrated the differences in the closantel binding mode between OvCHIT1 and human chitinase. Furthermore, molecular dynamics simulations and free-energy calculation were employed to determine and compare the detailed binding mode of closantel with OvCHT1 and the structure of human chitinase. This comparative study allowed identification of structural features and properties responsible for differences in the computationally predicted closantel binding modes. The homology model and the closantel binding mode reported herein might help guide the rational development of novel drugs against the adult parasite of O. volvulus and such findings could be extrapolated to other filarial neglected diseases.
Virtual substitution scan via single-step free energy perturbation.
Chiang, Ying-Chih; Wang, Yi
2016-02-05
With the rapid expansion of our computing power, molecular dynamics (MD) simulations ranging from hundreds of nanoseconds to microseconds or even milliseconds have become increasingly common. The majority of these long trajectories are obtained from plain (vanilla) MD simulations, where no enhanced sampling or free energy calculation method is employed. To promote the 'recycling' of these trajectories, we developed the Virtual Substitution Scan (VSS) toolkit as a plugin of the open-source visualization and analysis software VMD. Based on the single-step free energy perturbation (sFEP) method, VSS enables the user to post-process a vanilla MD trajectory for a fast free energy scan of substituting aryl hydrogens by small functional groups. Dihedrals of the functional groups are sampled explicitly in VSS, which improves the performance of the calculation and is found particularly important for certain groups. As a proof-of-concept demonstration, we employ VSS to compute the solvation free energy change upon substituting the hydrogen of a benzene molecule by 12 small functional groups frequently considered in lead optimization. Additionally, VSS is used to compute the relative binding free energy of four selected ligands of the T4 lysozyme. Overall, the computational cost of VSS is only a fraction of the corresponding multi-step FEP (mFEP) calculation, while its results agree reasonably well with those of mFEP, indicating that VSS offers a promising tool for rapid free energy scan of small functional group substitutions. This article is protected by copyright. All rights reserved. © 2016 Wiley Periodicals, Inc.
Computational analysis of the receptor binding specificity of novel influenza A/H7N9 viruses.
Zhou, Xinrui; Zheng, Jie; Ivan, Fransiskus Xaverius; Yin, Rui; Ranganathan, Shoba; Chow, Vincent T K; Kwoh, Chee-Keong
2018-05-09
Influenza viruses are undergoing continuous and rapid evolution. The fatal influenza A/H7N9 has drawn attention since the first wave of infections in March 2013, and raised more grave concerns with its increased potential to spread among humans. Experimental studies have revealed several host and virulence markers, indicating differential host binding preferences which can help estimate the potential of causing a pandemic. Here we systematically investigate the sequence pattern and structural characteristics of novel influenza A/H7N9 using computational approaches. The sequence analysis highlighted mutations in protein functional domains of influenza viruses. Molecular docking and molecular dynamics simulation revealed that the hemagglutinin (HA) of A/Taiwan/1/2017(H7N9) strain enhanced the binding with both avian and human receptor analogs, compared with the previous A/Shanghai/02/2013(H7N9) strain. The Molecular Mechanics - Poisson Boltzmann Surface Area (MM-PBSA) calculation revealed the change of residue-ligand interaction energy and detected the residues with conspicuous binding preference. The results are novel and specific to the emerging influenza A/Taiwan/1/2017(H7N9) strain compared with A/Shanghai/02/2013(H7N9). Its enhanced ability to bind human receptor analogs, which are abundant in the human upper respiratory tract, may be responsible for the recent outbreak. Residues showing binding preference were detected, which could facilitate monitoring the circulating influenza viruses.
Sorci, Mirco; Dassa, Bareket; Liu, Hongwei; Anand, Gaurav; Dutta, Amit K; Pietrokovski, Shmuel; Belfort, Marlene; Belfort, Georges
2013-06-18
In order to measure the intermolecular binding forces between two halves (or partners) of naturally split protein splicing elements called inteins, a novel thiol-hydrazide linker was designed and used to orient immobilized antibodies specific for each partner. Activation of the surfaces was achieved in one step, allowing direct intermolecular force measurement of the binding of the two partners of the split intein (called protein trans-splicing). Through this binding process, a whole functional intein is formed resulting in subsequent splicing. Atomic force microscopy (AFM) was used to directly measure the split intein partner binding at 1 μm/s between native (wild-type) and mixed pairs of C- and N-terminal partners of naturally occurring split inteins from three cyanobacteria. Native and mixed pairs exhibit similar binding forces within the error of the measurement technique (~52 pN). Bioinformatic sequence analysis and computational structural analysis discovered a zipper-like contact between the two partners with electrostatic and nonpolar attraction between multiple aligned ion pairs and hydrophobic residues. Also, we tested the Jarzynski's equality and demonstrated, as expected, that nonequilibrium dissipative measurements obtained here gave larger energies of interaction as compared with those for equilibrium. Hence, AFM coupled with our immobilization strategy and computational studies provides a useful analytical tool for the direct measurement of intermolecular association of split inteins and could be extended to any interacting protein pair.
Shukla, Shantanu; Bafna, Khushboo; Sundar, Durai; Thorat, Sunil S
2014-01-01
Swertia chirayita, a medicinal herb inhabiting the challenging terrains and high altitudes of the Himalayas, is a rich source of essential phytochemical isolates. Amarogentin, a bitter secoiridoid glycoside from S. chirayita, shows varied activity in several patho-physiological conditions, predominantly in leishmaniasis and carcinogenesis. Experimental analysis has revealed that amarogentin downregulates the cyclooxygenase-2 (COX-2) activity and helps to curtail skin carcinogenesis in mouse models; however, there exists no account on selective inhibition of the inducible cyclooxygenase (COX) isoform by amarogentin. Hence the computer-aided drug discovery methods were used to unravel the COX-2 inhibitory mechanism of amarogentin and to check its selectivity for the inducible isoform over the constitutive one. The generated theoretical models of both isoforms were subjected to molecular docking analysis with amarogentin and twenty-one other Food and Drug Authority (FDA) approved lead molecules. The post-docking binding energy profile of amarogentin was comparable to the binding energy profiles of the FDA approved selective COX-2 inhibitors. Subsequent molecular dynamics simulation analysis delineated the difference in the stability of both complexes, with amarogentin-COX-2 complex being more stable after 40ns simulation. The total binding free energy calculated by MMGBSA for the amarogentin-COX-2 complex was -52.35 KCal/mol against a binding free energy of -8.57 KCal/mol for amarogentin-COX-1 complex, suggesting a possible selective inhibition of the COX-2 protein by the natural inhibitor. Amarogentin achieves this potential selectivity by small, yet significant, structural differences inherent to the binding cavities of the two isoforms. Hypothetically, it might block the entry of the natural substrates in the hydrophobic binding channel of the COX-2, inhibiting the cyclooxygenation step. To sum up briefly, this work highlights the mechanism of the possible selective COX-2 inhibition by amarogentin and endorses the possibility of obtaining efficient, futuristic and targeted therapeutic agents for relieving inflammation and malignancy from this phytochemical source.
Sadiq, S Kashif; Wright, David W; Kenway, Owain A; Coveney, Peter V
2010-05-24
Accurate calculation of important thermodynamic properties, such as macromolecular binding free energies, is one of the principal goals of molecular dynamics simulations. However, single long simulation frequently produces incorrectly converged quantitative results due to inadequate sampling of conformational space in a feasible wall-clock time. Multiple short (ensemble) simulations have been shown to explore conformational space more effectively than single long simulations, but the two methods have not yet been thermodynamically compared. Here we show that, for end-state binding free energy determination methods, ensemble simulations exhibit significantly enhanced thermodynamic sampling over single long simulations and result in accurate and converged relative binding free energies that are reproducible to within 0.5 kcal/mol. Completely correct ranking is obtained for six HIV-1 protease variants bound to lopinavir with a correlation coefficient of 0.89 and a mean relative deviation from experiment of 0.9 kcal/mol. Multidrug resistance to lopinavir is enthalpically driven and increases through a decrease in the protein-ligand van der Waals interaction, principally due to the V82A/I84V mutation, and an increase in net electrostatic repulsion due to water-mediated disruption of protein-ligand interactions in the catalytic region. Furthermore, we correctly rank, to within 1 kcal/mol of experiment, the substantially increased chemical potency of lopinavir binding to the wild-type protease compared to saquinavir and show that lopinavir takes advantage of a decreased net electrostatic repulsion to confer enhanced binding. Our approach is dependent on the combined use of petascale computing resources and on an automated simulation workflow to attain the required level of sampling and turn around time to obtain the results, which can be as little as three days. This level of performance promotes integration of such methodology with clinical decision support systems for the optimization of patient-specific therapy.
A general intermolecular force field based on tight-binding quantum chemical calculations
NASA Astrophysics Data System (ADS)
Grimme, Stefan; Bannwarth, Christoph; Caldeweyher, Eike; Pisarek, Jana; Hansen, Andreas
2017-10-01
A black-box type procedure is presented for the generation of a molecule-specific, intermolecular potential energy function. The method uses quantum chemical (QC) information from our recently published extended tight-binding semi-empirical scheme (GFN-xTB) and can treat non-covalently bound complexes and aggregates with almost arbitrary chemical structure. The necessary QC information consists of the equilibrium structure, Mulliken atomic charges, charge centers of localized molecular orbitals, and also of frontier orbitals and orbital energies. The molecular pair potential includes model density dependent Pauli repulsion, penetration, as well as point charge electrostatics, the newly developed D4 dispersion energy model, Drude oscillators for polarization, and a charge-transfer term. Only one element-specific and about 20 global empirical parameters are needed to cover systems with nuclear charges up to radon (Z = 86). The method is tested for standard small molecule interaction energy benchmark sets where it provides accurate intermolecular energies and equilibrium distances. Examples for structures with a few hundred atoms including charged systems demonstrate the versatility of the approach. The method is implemented in a stand-alone computer code which enables rigid-body, global minimum energy searches for molecular aggregation or alignment.
Mitchell, Joshua A; Zhang, William H; Herde, Michel K; Henneberger, Christian; Janovjak, Harald; O'Mara, Megan L; Jackson, Colin J
2017-01-01
Biosensors that exploit Förster resonance energy transfer (FRET) can be used to visualize biological and physiological processes and are capable of providing detailed information in both spatial and temporal dimensions. In a FRET-based biosensor, substrate binding is associated with a change in the relative positions of two fluorophores, leading to a change in FRET efficiency that may be observed in the fluorescence spectrum. As a result, their design requires a ligand-binding protein that exhibits a conformational change upon binding. However, not all ligand-binding proteins produce responsive sensors upon conjugation to fluorescent proteins or dyes, and identifying the optimum locations for the fluorophores often involves labor-intensive iterative design or high-throughput screening. Combining the genetic fusion of a fluorescent protein to the ligand-binding protein with site-specific covalent attachment of a fluorescent dye can allow fine control over the positions of the two fluorophores, allowing the construction of very sensitive sensors. This relies upon the accurate prediction of the locations of the two fluorophores in bound and unbound states. In this chapter, we describe a method for computational identification of dye-attachment sites that allows the use of cysteine modification to attach synthetic dyes that can be paired with a fluorescent protein for the purposes of creating FRET sensors.
Neyman, Konstantin M; Inntam, Chan; Matveev, Alexei V; Nasluzov, Vladimir A; Rösch, Notker
2005-08-24
Single d-metal atoms on oxygen defects F(s) and F(s+) of the MgO(001) surface were studied theoretically. We employed an accurate density functional method combined with cluster models, embedded in an elastic polarizable environment, and we applied two gradient-corrected exchange-correlation functionals. In this way, we quantified how 17 metal atoms from groups 6-11 of the periodic table (Cu, Ag, Au; Ni, Pd, Pt; Co, Rh, Ir; Fe, Ru, Os; Mn, Re; and Cr, Mo, W) interact with terrace sites of MgO. We found bonding with F(s) and F(s+) defects to be in general stronger than that with O2- sites, except for Mn-, Re-, and Fe/F(s) complexes. In M/F(s) systems, electron density is accumulated on the metal center in a notable fashion. The binding energy on both kinds of O defects increases from 3d- to 4d- to 5d-atoms of a given group, at variance with the binding energy trend established earlier for the M/O2- complexes, 4d < 3d < 5d. Regarding the evolution of the binding energy along a period, group 7 atoms are slightly destabilized compared to their group 6 congeners in both the F(s) and F(s+) complexes; for later transition elements, the binding energy increases gradually up to group 10 and finally decreases again in group 11, most strongly on the F(s) site. This trend is governed by the negative charge on the adsorbed atoms. We discuss implications for an experimental detection of metal atoms on oxide supports based on computed core-level energies.
NASA Astrophysics Data System (ADS)
Negri, Matthias; Recanatini, Maurizio; Hartmann, Rolf W.
2011-09-01
17β-Hydroxysteroid dehydrogenase type 1 (17β-HSD1) catalyzes the last step of the estrogen biosynthesis, namely the reduction of estrone to the biologically potent estradiol. As such it is a potentially attractive drug target for the treatment of estrogen-dependent diseases like breast cancer and endometriosis. 17β-HSD1 belongs to the bisubstrate enzymes and exists as an ensemble of conformations. These principally differ in the region of the βFαG'-loop, suggesting a prominent role in substrate and inhibitor binding. Although several classes of potent non-steroidal 17β-HSD1 inhibitors currently exist, their binding mode is still unclear. We aimed to elucidate the binding mode of bis(hydroxyphenyl)arenes, a highly potent class of 17β-HSD1 inhibitors, and to rank these compounds correctly with respect to their inhibitory potency, two essential aspects in drug design. Ensemble docking experiments resulted in a steroidal binding mode for the closed enzyme conformations and in an alternative mode for the opened and occluded conformers with the inhibitors placed below the NADPH interacting with it synergically via π-π stacking and H-bond formation. Both binding modes were investigated by MD simulations and MM-PBSA binding free energy estimations using as representative member for this class compound 1 (50 nM). Notably, only the alternative binding mode proved stable and was energetically more favorable, while when simulated in the steroidal binding mode compound 1 was displaced from the active site. In parallel, ab initio studies of small NADPH-inhibitor complexes were performed, which supported the importance of the synergistic interaction between inhibitors and cofactor.
Du, Juan; Wang, Xue; Dong, Chun-Hai; Yang, Jian Ming; Yao, Xiao Jun
2016-01-01
Actin is a highly conserved protein. It plays important roles in cellular function and exists either in the monomeric (G-actin) or polymeric form (F-actin). Members of the actin-depolymerizing factor (ADF)/cofilin protein family bind to both G-actin and F-actin and play vital roles in actin dynamics by manipulating the rates of filament polymerization and depolymerization. It has been reported that the S6D and R98A/K100A mutants of actin-depolymerizing factor 1 (ADF1) in Arabidopsis thaliana decreased the binding affinity of ADF for the actin monomer. To investigate the binding mechanism and dynamic behavior of the ADF1-actin complex, we constructed a homology model of the AtADF1-actin complex based on the crystal structure of AtADF1 and the twinfilin C-terminal ADF-H domain in a complex with a mouse actin monomer. The model was then refined for subsequent molecular dynamics simulations. Increased binding energy of the mutated system was observed using the Molecular Mechanics Generalized Born Surface Area and Poisson-Boltzmann Surface Area (MM-GB/PBSA) methods. To determine the residues that make decisive contributions to the ADF1 actin-binding affinity, per-residue decomposition and computational alanine scanning analyses were performed, which provided more detailed information on the binding mechanism. Root-mean-square fluctuation and principal component analyses confirmed that the S6D and R98A/K100A mutants induced an increased conformational flexibility. The comprehensive molecular insight gained from this study is of great importance for understanding the binding mechanism of ADF1 and G-actin.
Wang, Xue; Dong, Chun-Hai; Yang, Jian Ming; Yao, Xiao Jun
2016-01-01
Actin is a highly conserved protein. It plays important roles in cellular function and exists either in the monomeric (G-actin) or polymeric form (F-actin). Members of the actin-depolymerizing factor (ADF)/cofilin protein family bind to both G-actin and F-actin and play vital roles in actin dynamics by manipulating the rates of filament polymerization and depolymerization. It has been reported that the S6D and R98A/K100A mutants of actin-depolymerizing factor 1 (ADF1) in Arabidopsis thaliana decreased the binding affinity of ADF for the actin monomer. To investigate the binding mechanism and dynamic behavior of the ADF1–actin complex, we constructed a homology model of the AtADF1–actin complex based on the crystal structure of AtADF1 and the twinfilin C-terminal ADF-H domain in a complex with a mouse actin monomer. The model was then refined for subsequent molecular dynamics simulations. Increased binding energy of the mutated system was observed using the Molecular Mechanics Generalized Born Surface Area and Poisson–Boltzmann Surface Area (MM-GB/PBSA) methods. To determine the residues that make decisive contributions to the ADF1 actin-binding affinity, per-residue decomposition and computational alanine scanning analyses were performed, which provided more detailed information on the binding mechanism. Root-mean-square fluctuation and principal component analyses confirmed that the S6D and R98A/K100A mutants induced an increased conformational flexibility. The comprehensive molecular insight gained from this study is of great importance for understanding the binding mechanism of ADF1 and G-actin. PMID:27414648
Computational screening and molecular dynamics simulation of disease associated nsSNPs in CENP-E.
Kumar, Ambuj; Purohit, Rituraj
2012-01-01
Aneuploidy and chromosomal instability (CIN) are hallmarks of most solid tumors. Mutations in centroemere proteins have been observed in promoting aneuploidy and tumorigenesis. Recent studies reported that Centromere-associated protein-E (CENP-E) is involved in inducing cancers. In this study we investigated the pathogenic effect of 132 nsSNPs reported in CENP-E using computational platform. Y63H point mutation found to be associated with cancer using SIFT, Polyphen, PhD-SNP, MutPred, CanPredict and Dr. Cancer tools. Further we investigated the binding affinity of ATP molecule to the CENP-E motor domain. Complementarity scores obtained from docking studies showed significant loss in ATP binding affinity of mutant structure. Molecular dynamics simulation was carried to examine the structural consequences of Y63H mutation. Root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (R(g)), solvent accessibility surface area (SASA), energy value, hydrogen bond (NH Bond), eigenvector projection, trace of covariance matrix and atom density analysis results showed notable loss in stability for mutant structure. Y63H mutation was also shown to disrupt the native conformation of ATP binding region in CENP-E motor domain. Docking studies for remaining 18 mutations at 63rd residue position as well as other two computationally predicted disease associated mutations S22L and P69S were also carried to investigate their affect on ATP binding affinity of CENP-E motor domain. Our study provided a promising computational methodology to study the tumorigenic consequences of nsSNPs that have not been characterized and clear clue to the wet lab scientist. Copyright © 2012 Elsevier B.V. All rights reserved.
Guiding lead optimization with GPCR structure modeling and molecular dynamics.
Heifetz, Alexander; James, Tim; Morao, Inaki; Bodkin, Michael J; Biggin, Philip C
2016-10-01
G-protein coupled receptor (GPCR) modeling approaches are widely used in the hit-to-lead and lead optimization stages of drug discovery. Modern protocols that involve molecular dynamics simulation can address key issues such as the free energy of binding (affinity), ligand-induced GPCR flexibility, ligand binding kinetics, conserved water positions and their role in ligand binding and the effects of mutations. The goals of these calculations are to predict the structures of the complexes between existing ligands and their receptors, to understand the key interactions and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this review we present a brief survey of various computational approaches illustrated through a hierarchical GPCR modeling protocol and its prospective application in three industrial drug discovery projects. Copyright © 2016 Elsevier Ltd. All rights reserved.
Role of Molecular Dynamics and Related Methods in Drug Discovery.
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.
NASA Astrophysics Data System (ADS)
Chipot, Christophe; Rozanska, Xavier; Dixit, Surjit B.
2005-11-01
The usefulness of free-energy calculations in non-academic environments, in general, and in the pharmaceutical industry, in particular, is a long-time debated issue, often considered from the angle of cost/performance criteria. In the context of the rational drug design of low-affinity, non-peptide inhibitors to the SH2 domain of the pp60src tyrosine kinase, the continuing difficulties encountered in an attempt to obtain accurate free-energy estimates are addressed. free-energy calculations can provide a convincing answer, assuming that two key-requirements are fulfilled: (i) thorough sampling of the configurational space is necessary to minimize the statistical error, hence raising the question: to which extent can we sacrifice the computational effort, yet without jeopardizing the precision of the free-energy calculation? (ii) the sensitivity of binding free-energies to the parameters utilized imposes an appropriate parametrization of the potential energy function, especially for non-peptide molecules that are usually poorly described by multipurpose macromolecular force fields. Employing the free-energy perturbation method, accurate ranking, within ±0.7 kcal/mol, is obtained in the case of four non-peptide mimes of a sequence recognized by the pp60src SH2 domain.
Impact of Weak Agostic Interactions in Nickel Electrocatalysts for Hydrogen Oxidation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Klug, Christina M.; O’Hagan, Molly; Bullock, R. Morris
To understand how H2 binding and oxidation is influenced by [Ni(PR2NR'2)2]2+ PR2NR'2 catalysts with H2 binding energies close to thermoneutral, two [Ni(PPh2NR'2)2]2+ (R = Me or C14H29) complexes with phenyl substituents on phosphorous and varying alkyl chain lengths on the pendant amine were studied. In the solid state, [Ni(PPh2NMe2)2]2+ exhibits an anagostic interaction between the Ni(II) center and the α-CH3 of the pendant amine, and DFT and variable-temperature 31P NMR experiments suggest than the anagostic interaction persists in solution. The equilibrium constants for H2 addition to these complexes was measured by 31P NMR spectroscopy, affording free energies of H2 additionmore » (ΔG°H2) of –0.8 kcal mol–1 in benzonitrile and –1.6 to –2.3 kcal mol–1 in THF. The anagostic interaction contributes to the low driving force for H2 binding by stabilizing the four-coordinate Ni(II) species prior to binding of H2. The pseudo-first order rate constants for H2 addition at 1 atm were measured by variable scan rate cyclic voltammetry, and were found to be similar for both complexes, less than 0.2 s–1 in benzonitrile and 3 –6 s–1 in THF. In the presence of exogenous base and H2 , turnover frequencies of electrocatalytic H2 oxidation were measured to be less than 0.2 s–1 in benzonitrile and 4 –9 s–1 in THF. These complexes are slower electrocatalysts for H2 oxidation than previously studied [Ni(PR2NR'2)2]2+ complexes due to a competition between H2 binding and formation of the anagostic interaction. However, the decrease in catalytic rate is accompanied by a beneficial 130 mV decrease in overpotential. This research was supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences. Computational resources were provided at the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory. Mass spectrometry experiments were performed in the William R. Wiley Environmental Molecular Sciences Laboratory, a DOE national scientific user facility sponsored by the DOE’s Office of Biological and Environmental Research and located and the Pacific Northwest National Laboratory (PNNL). The authors thank Dr. Rosalie Chu for mass spectroscopy analysis. PNNL is operated by Battelle for DOE.« less
Molecular Dynamics, Monte Carlo Simulations, and Langevin Dynamics: A Computational Review
Paquet, Eric; Viktor, Herna L.
2015-01-01
Macromolecular structures, such as neuraminidases, hemagglutinins, and monoclonal antibodies, are not rigid entities. Rather, they are characterised by their flexibility, which is the result of the interaction and collective motion of their constituent atoms. This conformational diversity has a significant impact on their physicochemical and biological properties. Among these are their structural stability, the transport of ions through the M2 channel, drug resistance, macromolecular docking, binding energy, and rational epitope design. To assess these properties and to calculate the associated thermodynamical observables, the conformational space must be efficiently sampled and the dynamic of the constituent atoms must be simulated. This paper presents algorithms and techniques that address the abovementioned issues. To this end, a computational review of molecular dynamics, Monte Carlo simulations, Langevin dynamics, and free energy calculation is presented. The exposition is made from first principles to promote a better understanding of the potentialities, limitations, applications, and interrelations of these computational methods. PMID:25785262
GPU accelerated implementation of NCI calculations using promolecular density.
Rubez, Gaëtan; Etancelin, Jean-Matthieu; Vigouroux, Xavier; Krajecki, Michael; Boisson, Jean-Charles; Hénon, Eric
2017-05-30
The NCI approach is a modern tool to reveal chemical noncovalent interactions. It is particularly attractive to describe ligand-protein binding. A custom implementation for NCI using promolecular density is presented. It is designed to leverage the computational power of NVIDIA graphics processing unit (GPU) accelerators through the CUDA programming model. The code performances of three versions are examined on a test set of 144 systems. NCI calculations are particularly well suited to the GPU architecture, which reduces drastically the computational time. On a single compute node, the dual-GPU version leads to a 39-fold improvement for the biggest instance compared to the optimal OpenMP parallel run (C code, icc compiler) with 16 CPU cores. Energy consumption measurements carried out on both CPU and GPU NCI tests show that the GPU approach provides substantial energy savings. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jain, Richa Naja, E-mail: ltprichanaja@gmail.com; Chakraborty, Brahmananda; Ramaniah, Lavanya M.
The electronic structure and hydrogen storage capability of Yttrium-doped BNNTs has been theoretically investigated using first principles density functional theory (DFT). Yttrium atom prefers the hollow site in the center of the hexagonal ring with a binding energy of 0.8048eV. Decorating by Y makes the system half-metallic and magnetic with a magnetic moment of 1.0µ{sub B}. Y decorated Boron-Nitride (8,0) nanotube can adsorb up to five hydrogen molecules whose average binding energy is computed as 0.5044eV. All the hydrogen molecules are adsorbed with an average desorption temperature of 644.708 K. Taking that the Y atoms can be placed only in alternatemore » hexagons, the implied wt% comes out to be 5.31%, a relatively acceptable value for hydrogen storage materials. Thus, this system can serve as potential hydrogen storage medium.« less
Moura, Silio Lima; Fajardo, Laura Martinez; Cunha, Leonardo Dos Anjos; Sotomayor, Maria Del Pilar Taboada; Machado, Francisco Bolivar Correto; Ferrão, Luiz Fernando Araújo; Pividori, Maria Isabel
2018-06-01
This study addresses the rational design of a magnetic molecularly imprinted polymer (magnetic-MIP) for the selective recognition of the hormone levothyroxine. The theoretical study was carried out by the density functional theory (DFT) computations considering dispersion interaction energies, and using the D2 Grimme's correction. The B97-D/def2-SV(P)/PCM method is used not only for studying the structure of the template the and monomer-monomer interactions, but also to assess the stoichiometry, noncovalent binding energies, solvation effects and thermodynamics properties such as binding energy. Among the 13 monomers studied in silico, itaconic acid is the most suitable according to the thermodynamic values. In order to assess the efficiency of the computational study, three different magnetic-MIPs based on itaconic acid, acrylic acid and acrylamide were synthesized and experimentally compared. The theoretical results are in agreement with experimental binding studies based on laser confocal microscopy, magneto-actuated immunoassay and electrochemical sensing. Furthermore, and for the first time, the direct electrochemical sensing of L-thyroxine preconcentrated on magnetic-MIP was successfully performed on magneto-actuated electrodes within 30 min with a limit of detection of as low as 0.0356 ng mL -1 which cover the clinical range of total L-thyroxine. Finally, the main analytical features were compared with the gold standard method based on commercial competitive immunoassays. This work provides a thoughtful strategy for magnetic molecularly imprinted polymer design, synthesis and application, opening new perspectives in the integration of these materials in magneto-actuated approaches for replacing specific antibodies in biosensors and microfluidic devices. Copyright © 2018 Elsevier B.V. All rights reserved.
The Self-Association of Graphane Is Driven by London Dispersion and Enhanced Orbital Interactions.
Wang, Changwei; Mo, Yirong; Wagner, J Philipp; Schreiner, Peter R; Jemmis, Eluvathingal D; Danovich, David; Shaik, Sason
2015-04-14
We investigated the nature of the cohesive energy between graphane sheets via multiple CH···HC interactions, using density functional theory (DFT) including dispersion correction (Grimme's D3 approach) computations of [n]graphane σ dimers (n = 6-73). For comparison, we also evaluated the binding between graphene sheets that display prototypical π/π interactions. The results were analyzed using the block-localized wave function (BLW) method, which is a variant of ab initio valence bond (VB) theory. BLW interprets the intermolecular interactions in terms of frozen interaction energy (ΔE(F)) composed of electrostatic and Pauli repulsion interactions, polarization (ΔE(pol)), charge-transfer interaction (ΔE(CT)), and dispersion effects (ΔE(disp)). The BLW analysis reveals that the cohesive energy between graphane sheets is dominated by two stabilizing effects, namely intermolecular London dispersion and two-way charge transfer energy due to the σ(CH) → σ*(HC) interactions. The shift of the electron density around the nonpolar covalent C-H bonds involved in the intermolecular interaction decreases the C-H bond lengths uniformly by 0.001 Å. The ΔE(CT) term, which accounts for ∼15% of the total binding energy, results in the accumulation of electron density in the interface area between two layers. This accumulated electron density thus acts as an electronic "glue" for the graphane layers and constitutes an important driving force in the self-association and stability of graphane under ambient conditions. Similarly, the "double faced adhesive tape" style of charge transfer interactions was also observed among graphene sheets in which it accounts for ∼18% of the total binding energy. The binding energy between graphane sheets is additive and can be expressed as a sum of CH···HC interactions, or as a function of the number of C-H bonds.
Early Universe synthesis of asymmetric dark matter nuggets
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gresham, Moira I.; Lou, Hou Keong; Zurek, Kathryn M.
We compute the mass function of bound states of asymmetric dark matter - nuggets - synthesized in the early Universe. We apply our results for the nugget density and binding energy computed from a nuclear model to obtain analytic estimates of the typical nugget size exiting synthesis. We numerically solve the Boltzmann equation for synthesis including two-to-two fusion reactions, estimating the impact of bottlenecks on the mass function exiting synthesis. These results provide the basis for studying the late Universe cosmology of nuggets in a future companion paper.
Green's function calculations for semi-infinite carbon nanotubes
NASA Astrophysics Data System (ADS)
John, D. L.; Pulfrey, D. L.
2006-02-01
In the modeling of nanoscale electronic devices, the non-equilibrium Green's function technique is gaining increasing popularity. One complication in this method is the need for computation of the self-energy functions that account for the interactions between the active portion of a device and its leads. In the one-dimensional case, these functions may be computed analytically. In higher dimensions, a numerical approach is required. In this work, we generalize earlier methods that were developed for tight-binding Hamiltonians, and present results for the case of a carbon nanotube.
Early Universe synthesis of asymmetric dark matter nuggets
Gresham, Moira I.; Lou, Hou Keong; Zurek, Kathryn M.
2018-02-12
We compute the mass function of bound states of asymmetric dark matter - nuggets - synthesized in the early Universe. We apply our results for the nugget density and binding energy computed from a nuclear model to obtain analytic estimates of the typical nugget size exiting synthesis. We numerically solve the Boltzmann equation for synthesis including two-to-two fusion reactions, estimating the impact of bottlenecks on the mass function exiting synthesis. These results provide the basis for studying the late Universe cosmology of nuggets in a future companion paper.
Early Universe synthesis of asymmetric dark matter nuggets
NASA Astrophysics Data System (ADS)
Gresham, Moira I.; Lou, Hou Keong; Zurek, Kathryn M.
2018-02-01
We compute the mass function of bound states of asymmetric dark matter—nuggets—synthesized in the early Universe. We apply our results for the nugget density and binding energy computed from a nuclear model to obtain analytic estimates of the typical nugget size exiting synthesis. We numerically solve the Boltzmann equation for synthesis including two-to-two fusion reactions, estimating the impact of bottlenecks on the mass function exiting synthesis. These results provide the basis for studying the late Universe cosmology of nuggets in a future companion paper.
NASA Astrophysics Data System (ADS)
Naderi, Ebadollah; Nanavati, Sachin P.; Majumder, Chiranjib; Ghaisas, S. V.
2014-03-01
In the present work we have calculated using density functional theory (DFT), diffusion barrier potentials on both the CdTe (111) surfaces, Cd terminated (A-type) & Te terminated (B-type). We employ nudge elastic band method (NEB) for obtaining the barrier potentials. The barrier is computed for Cd and for Te adatoms on both A-type and B-type surfaces. We report two energetically favourable positions along the normal to the surface, one above and other below the surface. The one above the surface has binding energy slightly more the one below. According to the results of this work, binding energy (in all cases) for adatoms are reasonable and close to experimental data. The barrier potential for hopping adatoms (Cd and Te) on both the surfaces is less than 0.35 eV. Apart from these most probable sites, there are other at least two sites on both the types of surfaces which are meta stable. We have also computed barriers for hopping to and from these meta stable positions. The present results can shade light on the defect formation mechanism in CdTe thin films during growth. The authors would like to thank C-DAC for the computing time on its PARAM series of supercomputers and DST Govt. of India, for partial funding.
Romero, Juan M; Trujillo, Madia; Estrin, Darío A; Rabinovich, Gabriel A; Di Lella, Santiago
2016-12-01
Endogenous lectins can control critical biological responses, including cell communication, signaling, angiogenesis and immunity by decoding glycan-containing information on a variety of cellular receptors and the extracellular matrix. Galectin-1 (Gal-1), a prototype member of the galectin family, displays only one carbohydrate recognition domain and occurs in a subtle homodimerization equilibrium at physiologic concentrations. Such equilibrium critically governs the function of this lectin signaling by allowing tunable interactions with a preferential set of glycosylated receptors. Here, we used a combination of experimental and computational approaches to analyze the kinetics and mechanisms connecting Gal-1 ligand unbinding and dimer dissociation processes. Kinetic constants of both processes were found to differ by an order of magnitude. By means of steered molecular dynamics simulations, the ligand unbinding process was followed monitoring water occupancy changes. By determining the water sites in a carbohydrate binding place during the unbinding process, we found that rupture of ligand-protein interactions induces an increase in energy barrier while ligand unbinding process takes place, whereas the entry of water molecules to the binding groove and further occupation of their corresponding water sites contributes to lowering of the energy barrier. Moreover, our findings suggested local asymmetries between the two subunits in the dimer structure detected at a nanosecond timescale. Thus, integration of experimental and computational data allowed a more complete understanding of lectin ligand binding and dimerization processes, suggesting new insights into the relationship between Gal-1 structure and function and renewing the discussion on the biophysics and biochemistry of lectin-ligand lattices. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Design of graphene nanoparticle undergoing axial compression: quantum study
NASA Astrophysics Data System (ADS)
Glukhova, O. E.; Kirillova, I. V.; Saliy, I. N.; Kolesnikova, A. S.; Slepchenkov, M. M.
2011-03-01
We report the results of quantum mechanical investigations of the atomic structure and deformations of graphene nanoparticle undergoing axial compression. We applied the tight-binding (TB) method. Our transferable tightbinding potential correctly reproduced tight-binding changes in the electronic configuration as a function of the local bonding geometry around each carbon atom. The tight-binding method applied provided the consideration and calculation of the rehybridization between σ- and π-orbitals. To research nanoribbons using tight-binding potential our own program was used. We adapted TB method to be able to run the algorithm on a parallel computing machine (computer cluster). To simulate axial compression of graphene nanoparticles the atoms on the ends were fixed on the plates. The plates were moved towards each other to decrease the length at some percent. Plane atomic network undergoing axial compression became wave-like. The amplitude of wave and its period were not constant and changed along axis. This is a phase transition. The strain energy collapse occurs at the value of axial compression 0.03-0.04. The strain energy increased up to the quantity compression 0.03, then collapsed sharply and decreased. So according to our theoretical investigation, the elasticity of graphene nanoparticles is more than the elasticity of nanotubes the same width and length. The curvature of the atomic network because of compression will decrease the reactivity of graphene nanoparticles. We have calculated the atomic structure and electronic structure of the compression graphene nanopaticle at each step of strain of axial compression. We have come to the conclusion that the wave-like graphenes adsorbing protein and nucleic acid are the effective nanosensors and bionanosensors.
NASA Astrophysics Data System (ADS)
Sathiyanarayanan, Rajesh; Hamouda, Ajmi Bh.; Pimpinelli, A.; Einstein, T. L.
2011-01-01
In an accompanying article we showed that surface morphologies obtained through codeposition of a small quantity (2%) of impurities with Cu during growth (step-flow mode, θ = 40 ML) significantly depends on the lateral nearest-neighbor binding energy (ENN) to Cu adatom and the diffusion barrier (Ed) of the impurity atom on Cu(0 0 1). Based on these two energy parameters, ENN and Ed, we classify impurity atoms into four sets. We study island nucleation and growth in the presence of codeposited impurities from different sets in the submonolayer (θ⩽ 0.7 ML) regime. Similar to growth in the step-flow mode, we find different nucleation and growth behavior for impurities from different sets. We characterize these differences through variations of the number of islands (Ni) and the average island size with coverage (θ). Further, we compute the critical nucleus size (i) for all of these cases from the distribution of capture-zone areas using the generalized Wigner distribution.
An ab initio study of Fe(CO)n, n = 1,5, and Cr(CO)6
NASA Technical Reports Server (NTRS)
Barnes, Leslie A.; Rosi, Marzio; Bauschlicher, Charles W., Jr.
1991-01-01
Ab initio calculations have been performed for Cr(CO)6 and Fe(CO)n, n = 1,5. Basis sets of better than double zeta quality are used, and correlation is included using the modified coupler-pair functional method. The computed geometries and force constants are in reasonable agreement with experiment. The sequential bond dissociation energies of CO from Fe(CO)5 are estimated to be: 39, 31, 25, 22, and greater than 5 kcal/mol. It is noted that the first bond dissociation energy is relative to the singlet ground state of Fe(CO)5 and the lowest singlet state of Fe(CO)4, whereas the second is relative to the ground triplet states of Fe(CO)4 and Fe(CO)3. In addition, the binding energy for Fe-CO would be modified to 18 kcal/mol if dissociation occurred to the Fe(5F) excited state asymptote. The CO binding energies for Fe and Cr are found to be in poorer agreement with experiment than those found in a previous study on Ni(CO)4. The origins of this difference are discussed.
NASA Astrophysics Data System (ADS)
Joshi, R. H.; Thakore, B. Y.; Bhatt, N. K.; Vyas, P. R.; Jani, A. R.
2018-02-01
A density functional theory along with electronic contribution is used to compute quasiharmonic total energy for silver, whereas explicit phonon anharmonic contribution is added through perturbative term in temperature. Within the Mie-Grüneisen approach, we propose a consistent computational scheme for calculating various thermophysical properties of a substance, in which the required Grüneisen parameter γth is calculated from the knowledge of binding energy. The present study demonstrates that no separate relation for volume dependence for γth is needed, and complete thermodynamics under simultaneous high-temperature and high-pressure condition can be derived in a consistent manner. We have calculated static and dynamic equation of states and some important thermodynamic properties along the shock Hugoniot. A careful examination of temperature dependence of Grüneisen parameter reveals the importance of temperature-effect on various thermal properties.
Chen, Po-chia; Kuyucak, Serdar
2009-01-01
Ion channel-toxin complexes are ideal systems for computational studies of protein-ligand interactions, because, in most cases, the channel axis provides a natural reaction coordinate for unbinding of a ligand and a wealth of physiological data is available to check the computational results. We use a recently determined structure of a potassium channel-charybdotoxin complex in molecular dynamics simulations to investigate the mechanism and energetics of unbinding. Pairs of residues on the channel protein and charybdotoxin that are involved in the binding are identified, and their behavior is traced during umbrella-sampling simulations as charybdotoxin is moved away from the binding site. The potential of mean force for the unbinding of charybdotoxin is constructed from the umbrella sampling simulations using the weighted histogram analysis method, and barriers observed are correlated with specific breaking of interactions and influx of water molecules into the binding site. Charybdotoxin is found to undergo conformational changes as a result of the reaction coordinate choice—a nontrivial decision for larger ligands—which we explore in detail, and for which we propose solutions. Agreement between the calculated and the experimental binding energies is obtained once the energetic consequences of these conformational changes are included in the calculations. PMID:19348743
Nisha, J; Shanthi, V
2015-07-01
Mycobacterium leprae, the etiologic agent of leprosy, is non-cultivable in vitro. Consequently, the assessment of antibiotic activity against M. leprae hinge mainly upon the time consuming mouse footpad system. As M. leprae develops resistance against most of the drugs, the evolution of new long acting antimycobacterial compounds stand in need for leprosy control. The rpoB of M. leprae is the target of antimycobacterial drug, rifampicin. Recently, cases were reported that rpoB mutation (S425L) became resistant to rifampicin and the mechanism of resistance is still not well understood. The present study is aimed at studying the molecular and structural mechanism of the rifampicin binding to both native and mutant rpoB through computational approaches. From molecular docking, we demonstrated the stable binding of rifampicin through two hydrogen bonding with His420 residue of native than with mutant rpoB where one hydrogen bonding was found with Ser406. The difference in binding energies observed in the docking study evidently signifies that rifampicin is less effective in the treatment of patients with S425L variant. Moreover, the molecular dynamics studies also highlight the stable binding of rifampicin with native than mutant (S425L) rpoB. © 2015 Wiley Periodicals, Inc.
Spassov, Velin Z; Yan, Lisa
2013-04-01
Understanding the effects of mutation on pH-dependent protein binding affinity is important in protein design, especially in the area of protein therapeutics. We propose a novel method for fast in silico mutagenesis of protein-protein complexes to calculate the effect of mutation as a function of pH. The free energy differences between the wild type and mutants are evaluated from a molecular mechanics model, combined with calculations of the equilibria of proton binding. The predicted pH-dependent energy profiles demonstrate excellent agreement with experimentally measured pH-dependency of the effect of mutations on the dissociation constants for the complex of turkey ovomucoid third domain (OMTKY3) and proteinase B. The virtual scanning mutagenesis identifies all hotspots responsible for pH-dependent binding of immunoglobulin G (IgG) to neonatal Fc receptor (FcRn) and the results support the current understanding of the salvage mechanism of the antibody by FcRn based on pH-selective binding. The method can be used to select mutations that change the pH-dependent binding profiles of proteins and guide the time consuming and expensive protein engineering experiments. As an application of this method, we propose a computational strategy to search for mutations that can alter the pH-dependent binding behavior of IgG to FcRn with the aim of improving the half-life of therapeutic antibodies in the target organism. Copyright © 2013 Wiley Periodicals, Inc.
Zeller, Fabian; Zacharias, Martin
2014-02-11
The accurate calculation of potentials of mean force for ligand-receptor binding is one of the most important applications of molecular simulation techniques. Typically, the separation distance between ligand and receptor is chosen as a reaction coordinate along which a PMF can be calculated with the aid of umbrella sampling (US) techniques. In addition, restraints can be applied on the relative position and orientation of the partner molecules to reduce accessible phase space. An approach combining such phase space reduction with flattening of the free energy landscape and configurational exchanges has been developed, which significantly improves the convergence of PMF calculations in comparison with standard umbrella sampling. The free energy surface along the reaction coordinate is smoothened by iteratively adapting biasing potentials corresponding to previously calculated PMFs. Configurations are allowed to exchange between the umbrella simulation windows via the Hamiltonian replica exchange method. The application to a DNA molecule in complex with a minor groove binding ligand indicates significantly improved convergence and complete reversibility of the sampling along the pathway. The calculated binding free energy is in excellent agreement with experimental results. In contrast, the application of standard US resulted in large differences between PMFs calculated for association and dissociation pathways. The approach could be a useful alternative to standard US for computational studies on biomolecular recognition processes.
Free energy landscapes of encounter complexes in protein-protein association.
Camacho, C J; Weng, Z; Vajda, S; DeLisi, C
1999-03-01
We report the computer generation of a high-density map of the thermodynamic properties of the diffusion-accessible encounter conformations of four receptor-ligand protein pairs, and use it to study the electrostatic and desolvation components of the free energy of association. Encounter complex conformations are generated by sampling the translational/rotational space of the ligand around the receptor, both at 5-A and zero surface-to-surface separations. We find that partial desolvation is always an important effect, and it becomes dominant for complexes in which one of the reactants is neutral or weakly charged. The interaction provides a slowly varying attractive force over a small but significant region of the molecular surface. In complexes with no strong charge complementarity this region surrounds the binding site, and the orientation of the ligand in the encounter conformation with the lowest desolvation free energy is similar to the one observed in the fully formed complex. Complexes with strong opposite charges exhibit two types of behavior. In the first group, represented by barnase/barstar, electrostatics exerts strong orientational steering toward the binding site, and desolvation provides some added adhesion within the local region of low electrostatic energy. In the second group, represented by the complex of kallikrein and pancreatic trypsin inhibitor, the overall stability results from the rather nonspecific electrostatic attraction, whereas the affinity toward the binding region is determined by desolvation interactions.
Vosmeer, C Ruben; Kooi, Derk P; Capoferri, Luigi; Terpstra, Margreet M; Vermeulen, Nico P E; Geerke, Daan P
2016-01-01
Recently an iterative method was proposed to enhance the accuracy and efficiency of ligand-protein binding affinity prediction through linear interaction energy (LIE) theory. For ligand binding to flexible Cytochrome P450s (CYPs), this method was shown to decrease the root-mean-square error and standard deviation of error prediction by combining interaction energies of simulations starting from different conformations. Thereby, different parts of protein-ligand conformational space are sampled in parallel simulations. The iterative LIE framework relies on the assumption that separate simulations explore different local parts of phase space, and do not show transitions to other parts of configurational space that are already covered in parallel simulations. In this work, a method is proposed to (automatically) detect such transitions during the simulations that are performed to construct LIE models and to predict binding affinities. Using noise-canceling techniques and splines to fit time series of the raw data for the interaction energies, transitions during simulation between different parts of phase space are identified. Boolean selection criteria are then applied to determine which parts of the interaction energy trajectories are to be used as input for the LIE calculations. Here we show that this filtering approach benefits the predictive quality of our previous CYP 2D6-aryloxypropanolamine LIE model. In addition, an analysis is performed of the gain in computational efficiency that can be obtained from monitoring simulations using the proposed filtering method and by prematurely terminating simulations accordingly.
In Silico Analysis of Epitope-Based Vaccine Candidates against Hepatitis B Virus Polymerase Protein
Zheng, Juzeng; Lin, Xianfan; Wang, Xiuyan; Zheng, Liyu; Lan, Songsong; Jin, Sisi; Ou, Zhanfan; Wu, Jinming
2017-01-01
Hepatitis B virus (HBV) infection has persisted as a major public health problem due to the lack of an effective treatment for those chronically infected. Therapeutic vaccination holds promise, and targeting HBV polymerase is pivotal for viral eradication. In this research, a computational approach was employed to predict suitable HBV polymerase targeting multi-peptides for vaccine candidate selection. We then performed in-depth computational analysis to evaluate the predicted epitopes’ immunogenicity, conservation, population coverage, and toxicity. Lastly, molecular docking and MHC-peptide complex stabilization assay were utilized to determine the binding energy and affinity of epitopes to the HLA-A0201 molecule. Criteria-based analysis provided four predicted epitopes, RVTGGVFLV, VSIPWTHKV, YMDDVVLGA and HLYSHPIIL. Assay results indicated the lowest binding energy and high affinity to the HLA-A0201 molecule for epitopes VSIPWTHKV and YMDDVVLGA and epitopes RVTGGVFLV and VSIPWTHKV, respectively. Regions 307 to 320 and 377 to 387 were considered to have the highest probability to be involved in B cell epitopes. The T cell and B cell epitopes identified in this study are promising targets for an epitope-focused, peptide-based HBV vaccine, and provide insight into HBV-induced immune response. PMID:28509875
Effective Hamiltonian approach to bright and dark excitons in single-walled carbon nanotubes
NASA Astrophysics Data System (ADS)
Choi, Sangkook; Deslippe, Jack; Louie, Steven G.
2009-03-01
Recently, excitons in single-walled carbon nanotubes (SWCNTs) have generated great research interest due to the large binding energies and unique screening properties associated with one-dimensional (1D) materials. Considerable progress in their theoretical understanding has been achieved by studies employing the ab initio GW-Bethe-Salpeter equation methodology. For example, the presence of bright and dark excitons with binding energies of a large fraction of an eV has been predicted and subsequently verified by experiment. Some of these results have also been quantitatively reproduced by recent model calculations using a spatially dependent screened Coulomb interaction between the excited electron and hole, an approach that would be useful for studying large diameter and chiral nanotubes with many atoms per unit cell. However, this previous model neglects the degeneracy of the band states and hence the dark excitons. We present an extension of this exciton model for the SWCNT, incorporating the screened Coulomb interaction as well as state degeneracy, to understand and compute the characteristics of the bright and dark excitons, such as the bright and dark level splittings. Supported by NSF #DMR07-05941, DOE #De-AC02-05CH11231 and computational resources from Teragrid and NERSC.
Computing Curvature Sensitivity of Biomolecules in Membranes by Simulated Buckling.
Elías-Wolff, Federico; Lindén, Martin; Lyubartsev, Alexander P; Brandt, Erik G
2018-03-13
Membrane curvature sensing, where the binding free energies of membrane-associated molecules depend on the local membrane curvature, is a key factor to modulate and maintain the shape and organization of cell membranes. However, the microscopic mechanisms are not well understood, partly due to absence of efficient simulation methods. Here, we describe a method to compute the curvature dependence of the binding free energy of a membrane-associated probe molecule that interacts with a buckled membrane, which has been created by lateral compression of a flat bilayer patch. This buckling approach samples a wide range of curvatures in a single simulation, and anisotropic effects can be extracted from the orientation statistics. We develop an efficient and robust algorithm to extract the motion of the probe along the buckled membrane surface, and evaluate its numerical properties by extensive sampling of three coarse-grained model systems: local lipid density in a curved environment for single-component bilayers, curvature preferences of individual lipids in two-component membranes, and curvature sensing by a homotrimeric transmembrane protein. The method can be used to complement experimental data from curvature partition assays and provides additional insight into mesoscopic theories and molecular mechanisms for curvature sensing.
Accounting for receptor flexibility and enhanced sampling methods in computer-aided drug design.
Sinko, William; Lindert, Steffen; McCammon, J Andrew
2013-01-01
Protein flexibility plays a major role in biomolecular recognition. In many cases, it is not obvious how molecular structure will change upon association with other molecules. In proteins, these changes can be major, with large deviations in overall backbone structure, or they can be more subtle as in a side-chain rotation. Either way the algorithms that predict the favorability of biomolecular association require relatively accurate predictions of the bound structure to give an accurate assessment of the energy involved in association. Here, we review a number of techniques that have been proposed to accommodate receptor flexibility in the simulation of small molecules binding to protein receptors. We investigate modifications to standard rigid receptor docking algorithms and also explore enhanced sampling techniques, and the combination of free energy calculations and enhanced sampling techniques. The understanding and allowance for receptor flexibility are helping to make computer simulations of ligand protein binding more accurate. These developments may help improve the efficiency of drug discovery and development. Efficiency will be essential as we begin to see personalized medicine tailored to individual patients, which means specific drugs are needed for each patient's genetic makeup. © 2012 John Wiley & Sons A/S.
Subsite mapping of enzymes. Depolymerase computer modelling.
Allen, J D; Thoma, J A
1976-01-01
We have developed a depolymerase computer model that uses a minimization routine. The model is designed so that, given experimental bond-cleavage frequencies for oligomeric substrates and experimental Michaelis parameters as a function of substrate chain length, the optimum subsite map is generated. The minimized sum of the weighted-squared residuals of the experimental and calculated data is used as a criterion of the goodness-of-fit for the optimized subsite map. The application of the minimization procedure to subsite mapping is explored through the use of simulated data. A procedure is developed whereby the minimization model can be used to determine the number of subsites in the enzymic binding region and to locate the position of the catalytic amino acids among these subsites. The degree of propagation of experimental variance into the subsite-binding energies is estimated. The question of whether hydrolytic rate coefficients are constant or a function of the number of filled subsites is examined. PMID:999629
Cuya, Teobaldo; Gonçalves, Arlan da Silva; da Silva, Jorge Alberto Valle; Ramalho, Teodorico C; Kuca, Kamil; C C França, Tanos
2017-10-27
The oximes 4-carbamoyl-1-[({2-[(E)-(hydroxyimino) methyl] pyridinium-1-yl} methoxy) methyl] pyridinium (known as HI-6) and 3-carbamoyl-1-[({2-[(E)-(hydroxyimino) methyl] pyridinium-1-yl} methoxy) methyl] pyridinium (known as HS-6) are isomers differing from each other only by the position of the carbamoyl group on the pyridine ring. However, this slight difference was verified to be responsible for big differences in the percentual of reactivation of acetylcholinesterase (AChE) inhibited by the nerve agents tabun, sarin, cyclosarin, and VX. In order to try to find out the reason for this, a computational study involving molecular docking, molecular dynamics, and binding energies calculations, was performed on the binding modes of HI-6 and HS-6 on human AChE (HssAChE) inhibited by those nerve agents.
Protein-Protein Interface Predictions by Data-Driven Methods: A Review
Xue, Li C; Dobbs, Drena; Bonvin, Alexandre M.J.J.; Honavar, Vasant
2015-01-01
Reliably pinpointing which specific amino acid residues form the interface(s) between a protein and its binding partner(s) is critical for understanding the structural and physicochemical determinants of protein recognition and binding affinity, and has wide applications in modeling and validating protein interactions predicted by high-throughput methods, in engineering proteins, and in prioritizing drug targets. Here, we review the basic concepts, principles and recent advances in computational approaches to the analysis and prediction of protein-protein interfaces. We point out caveats for objectively evaluating interface predictors, and discuss various applications of data-driven interface predictors for improving energy model-driven protein-protein docking. Finally, we stress the importance of exploiting binding partner information in reliably predicting interfaces and highlight recent advances in this emerging direction. PMID:26460190
Virtual Screening of Novel Glucosamine-6-Phosphate Synthase Inhibitors.
Lather, Amit; Sharma, Sunil; Khatkar, Anurag
2018-01-01
Infections caused by microorganisms are the major cause of death today. The tremendous and improper use of antimicrobial agents leads to antimicrobial resistance. Various currently available antimicrobial drugs are inadequate to control the infections and lead to various adverse drug reactions. Efforts based on computer-aided drug design (CADD) can excavate a large number of databases to generate new, potent hits and minimize the requirement of time as well as money for the discovery of newer antimicrobials. Pharmaceutical sciences also have made development with advances in drug designing concepts. The current research article focuses on the study of various G-6-P synthase inhibitors from literature cited molecular database. Docking analysis was conducted and ADMET data of various molecules was evaluated by Schrodinger Glide and PreADMET software, respectively. Here, the results presented efficacy of various inhibitors towards enzyme G-6-P synthase. Docking scores, binding energy and ADMET data of various molecules showed good inhibitory potential toward G-6-P synthase as compared to standard antibiotics. This novel antimicrobial drug target G-6-P synthase has not so extensively been explored for its application in antimicrobial therapy, so the work done so far proved highly essential. This article has helped the drug researchers and scientists to intensively explore about this wonderful antimicrobial drug target. The Schrodinger, Inc. (New York, USA) software was utilized to carry out the computational calculations and docking studies. The hardware configuration was Intel® core (TM) i5-4210U CPU @ 2.40GHz, RAM memory 4.0 GB under 64-bit window operating system. The ADMET data was calculated by using the PreADMET tool (PreADMET ver. 2.0). All the computational work was completed in the Laboratory for Enzyme Inhibition Studies, Department of Pharmaceutical Sciences, M.D. University, Rohtak, INDIA. Molecular docking studies were carried out to identify the binding affinities and interaction between the inhibitors and the target proteins (G-6-P synthase) by using Glide software (Schrodinger Inc. U.S.A.-Maestro version 10.2). Grid-based Ligand Docking with Energetic (Glide) is one of the most accurate docking softwares available for ligand-protein, protein-protein binding studies. A library of hundreds of available ligands was docked against targeted proteins G-6-P synthase having PDB ID 1moq. Results of docking are shown in Table 1 and Table 2. Results of G-6-P synthase docking showed that some compounds were found to have comparable docking score and binding energy (kj/mol) as compared to standard antibiotics. Many of the ligands showed hydrogen bond interaction, hydrophobic interactions, electrostatic interactions, ionic interactions and π- π stacking with the various amino acid residues in the binding pockets of G-6-P synthase. The docking study estimated free energy of binding, binding pose andglide score and all these parameters provide a promising tool for the discovery of new potent natural inhibitors of G-6-P synthase. These G-6-P synthase inhibitors could further be used as antimicrobials. Here, a detailed binding analysis and new insights of inhibitors from various classes of molecules were docked in binding cavity of G-6-P synthase. ADME and toxicity prediction of these compounds will further accentuate us to study these compounds in vivo. This information will possibly present further expansion of effective antimicrobials against several microbial infections. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Thermodynamic free energy methods to investigate shape transitions in bilayer membranes.
Ramakrishnan, N; Tourdot, Richard W; Radhakrishnan, Ravi
2016-06-01
The conformational free energy landscape of a system is a fundamental thermodynamic quantity of importance particularly in the study of soft matter and biological systems, in which the entropic contributions play a dominant role. While computational methods to delineate the free energy landscape are routinely used to analyze the relative stability of conformational states, to determine phase boundaries, and to compute ligand-receptor binding energies its use in problems involving the cell membrane is limited. Here, we present an overview of four different free energy methods to study morphological transitions in bilayer membranes, induced either by the action of curvature remodeling proteins or due to the application of external forces. Using a triangulated surface as a model for the cell membrane and using the framework of dynamical triangulation Monte Carlo, we have focused on the methods of Widom insertion, thermodynamic integration, Bennett acceptance scheme, and umbrella sampling and weighted histogram analysis. We have demonstrated how these methods can be employed in a variety of problems involving the cell membrane. Specifically, we have shown that the chemical potential, computed using Widom insertion, and the relative free energies, computed using thermodynamic integration and Bennett acceptance method, are excellent measures to study the transition from curvature sensing to curvature inducing behavior of membrane associated proteins. The umbrella sampling and WHAM analysis has been used to study the thermodynamics of tether formation in cell membranes and the quantitative predictions of the computational model are in excellent agreement with experimental measurements. Furthermore, we also present a method based on WHAM and thermodynamic integration to handle problems related to end-point-catastrophe that are common in most free energy methods.
Deng, Nanjie; Zhang, Bin W.; Levy, Ronald M.
2015-01-01
The ability to accurately model solvent effects on free energy surfaces is important for understanding many biophysical processes including protein folding and misfolding, allosteric transitions and protein-ligand binding. Although all-atom simulations in explicit solvent can provide an accurate model for biomolecules in solution, explicit solvent simulations are hampered by the slow equilibration on rugged landscapes containing multiple basins separated by barriers. In many cases, implicit solvent models can be used to significantly speed up the conformational sampling; however, implicit solvent simulations do not fully capture the effects of a molecular solvent, and this can lead to loss of accuracy in the estimated free energies. Here we introduce a new approach to compute free energy changes in which the molecular details of explicit solvent simulations are retained while also taking advantage of the speed of the implicit solvent simulations. In this approach, the slow equilibration in explicit solvent, due to the long waiting times before barrier crossing, is avoided by using a thermodynamic cycle which connects the free energy basins in implicit solvent and explicit solvent using a localized decoupling scheme. We test this method by computing conformational free energy differences and solvation free energies of the model system alanine dipeptide in water. The free energy changes between basins in explicit solvent calculated using fully explicit solvent paths agree with the corresponding free energy differences obtained using the implicit/explicit thermodynamic cycle to within 0.3 kcal/mol out of ~3 kcal/mol at only ~8 % of the computational cost. We note that WHAM methods can be used to further improve the efficiency and accuracy of the explicit/implicit thermodynamic cycle. PMID:26236174
Deng, Nanjie; Zhang, Bin W; Levy, Ronald M
2015-06-09
The ability to accurately model solvent effects on free energy surfaces is important for understanding many biophysical processes including protein folding and misfolding, allosteric transitions, and protein–ligand binding. Although all-atom simulations in explicit solvent can provide an accurate model for biomolecules in solution, explicit solvent simulations are hampered by the slow equilibration on rugged landscapes containing multiple basins separated by barriers. In many cases, implicit solvent models can be used to significantly speed up the conformational sampling; however, implicit solvent simulations do not fully capture the effects of a molecular solvent, and this can lead to loss of accuracy in the estimated free energies. Here we introduce a new approach to compute free energy changes in which the molecular details of explicit solvent simulations are retained while also taking advantage of the speed of the implicit solvent simulations. In this approach, the slow equilibration in explicit solvent, due to the long waiting times before barrier crossing, is avoided by using a thermodynamic cycle which connects the free energy basins in implicit solvent and explicit solvent using a localized decoupling scheme. We test this method by computing conformational free energy differences and solvation free energies of the model system alanine dipeptide in water. The free energy changes between basins in explicit solvent calculated using fully explicit solvent paths agree with the corresponding free energy differences obtained using the implicit/explicit thermodynamic cycle to within 0.3 kcal/mol out of ∼3 kcal/mol at only ∼8% of the computational cost. We note that WHAM methods can be used to further improve the efficiency and accuracy of the implicit/explicit thermodynamic cycle.
Ligand Binding Pathways and Conformational Transitions of the HIV Protease.
Miao, Yinglong; Huang, Yu-Ming M; Walker, Ross C; McCammon, J Andrew; Chang, Chia-En A
2018-03-06
It is important to determine the binding pathways and mechanisms of ligand molecules to target proteins to effectively design therapeutic drugs. Molecular dynamics (MD) is a promising computational tool that allows us to simulate protein-drug binding at an atomistic level. However, the gap between the time scales of current simulations and those of many drug binding processes has limited the usage of conventional MD, which has been reflected in studies of the HIV protease. Here, we have applied a robust enhanced simulation method, Gaussian accelerated molecular dynamics (GaMD), to sample binding pathways of the XK263 ligand and associated protein conformational changes in the HIV protease. During two of 10 independent GaMD simulations performed over 500-2500 ns, the ligand was observed to successfully bind to the protein active site. Although GaMD-derived free energy profiles were not fully converged because of insufficient sampling of the complex system, the simulations still allowed us to identify relatively low-energy intermediate conformational states during binding of the ligand to the HIV protease. Relative to the X-ray crystal structure, the XK263 ligand reached a minimum root-mean-square deviation (RMSD) of 2.26 Å during 2.5 μs of GaMD simulation. In comparison, the ligand RMSD reached a minimum of only ∼5.73 Å during an earlier 14 μs conventional MD simulation. This work highlights the enhanced sampling power of the GaMD approach and demonstrates its wide applicability to studies of drug-receptor interactions for the HIV protease and by extension many other target proteins.
AlaScan: A Graphical User Interface for Alanine Scanning Free-Energy Calculations.
Ramadoss, Vijayaraj; Dehez, François; Chipot, Christophe
2016-06-27
Computation of the free-energy changes that underlie molecular recognition and association has gained significant importance due to its considerable potential in drug discovery. The massive increase of computational power in recent years substantiates the application of more accurate theoretical methods for the calculation of binding free energies. The impact of such advances is the application of parent approaches, like computational alanine scanning, to investigate in silico the effect of amino-acid replacement in protein-ligand and protein-protein complexes, or probe the thermostability of individual proteins. Because human effort represents a significant cost that precludes the routine use of this form of free-energy calculations, minimizing manual intervention constitutes a stringent prerequisite for any such systematic computation. With this objective in mind, we propose a new plug-in, referred to as AlaScan, developed within the popular visualization program VMD to automate the major steps in alanine-scanning calculations, employing free-energy perturbation as implemented in the widely used molecular dynamics code NAMD. The AlaScan plug-in can be utilized upstream, to prepare input files for selected alanine mutations. It can also be utilized downstream to perform the analysis of different alanine-scanning calculations and to report the free-energy estimates in a user-friendly graphical user interface, allowing favorable mutations to be identified at a glance. The plug-in also assists the end-user in assessing the reliability of the calculation through rapid visual inspection.
Enzyme catalysis by entropy without Circe effect.
Kazemi, Masoud; Himo, Fahmi; Åqvist, Johan
2016-03-01
Entropic effects have often been invoked to explain the extraordinary catalytic power of enzymes. In particular, the hypothesis that enzymes can use part of the substrate-binding free energy to reduce the entropic penalty associated with the subsequent chemical transformation has been very influential. The enzymatic reaction of cytidine deaminase appears to be a distinct example. Here, substrate binding is associated with a significant entropy loss that closely matches the activation entropy penalty for the uncatalyzed reaction in water, whereas the activation entropy for the rate-limiting catalytic step in the enzyme is close to zero. Herein, we report extensive computer simulations of the cytidine deaminase reaction and its temperature dependence. The energetics of the catalytic reaction is first evaluated by density functional theory calculations. These results are then used to parametrize an empirical valence bond description of the reaction, which allows efficient sampling by molecular dynamics simulations and computation of Arrhenius plots. The thermodynamic activation parameters calculated by this approach are in excellent agreement with experimental data and indeed show an activation entropy close to zero for the rate-limiting transition state. However, the origin of this effect is a change of reaction mechanism compared the uncatalyzed reaction. The enzyme operates by hydroxide ion attack, which is intrinsically associated with a favorable activation entropy. Hence, this has little to do with utilization of binding free energy to pay the entropic penalty but rather reflects how a preorganized active site can stabilize a reaction path that is not operational in solution.
Enzyme catalysis by entropy without Circe effect
Kazemi, Masoud; Himo, Fahmi; Åqvist, Johan
2016-01-01
Entropic effects have often been invoked to explain the extraordinary catalytic power of enzymes. In particular, the hypothesis that enzymes can use part of the substrate-binding free energy to reduce the entropic penalty associated with the subsequent chemical transformation has been very influential. The enzymatic reaction of cytidine deaminase appears to be a distinct example. Here, substrate binding is associated with a significant entropy loss that closely matches the activation entropy penalty for the uncatalyzed reaction in water, whereas the activation entropy for the rate-limiting catalytic step in the enzyme is close to zero. Herein, we report extensive computer simulations of the cytidine deaminase reaction and its temperature dependence. The energetics of the catalytic reaction is first evaluated by density functional theory calculations. These results are then used to parametrize an empirical valence bond description of the reaction, which allows efficient sampling by molecular dynamics simulations and computation of Arrhenius plots. The thermodynamic activation parameters calculated by this approach are in excellent agreement with experimental data and indeed show an activation entropy close to zero for the rate-limiting transition state. However, the origin of this effect is a change of reaction mechanism compared the uncatalyzed reaction. The enzyme operates by hydroxide ion attack, which is intrinsically associated with a favorable activation entropy. Hence, this has little to do with utilization of binding free energy to pay the entropic penalty but rather reflects how a preorganized active site can stabilize a reaction path that is not operational in solution. PMID:26755610
A new configurational bias scheme for sampling supramolecular structures
NASA Astrophysics Data System (ADS)
De Gernier, Robin; Curk, Tine; Dubacheva, Galina V.; Richter, Ralf P.; Mognetti, Bortolo M.
2014-12-01
We present a new simulation scheme which allows an efficient sampling of reconfigurable supramolecular structures made of polymeric constructs functionalized by reactive binding sites. The algorithm is based on the configurational bias scheme of Siepmann and Frenkel and is powered by the possibility of changing the topology of the supramolecular network by a non-local Monte Carlo algorithm. Such a plan is accomplished by a multi-scale modelling that merges coarse-grained simulations, describing the typical polymer conformations, with experimental results accounting for free energy terms involved in the reactions of the active sites. We test the new algorithm for a system of DNA coated colloids for which we compute the hybridisation free energy cost associated to the binding of tethered single stranded DNAs terminated by short sequences of complementary nucleotides. In order to demonstrate the versatility of our method, we also consider polymers functionalized by receptors that bind a surface decorated by ligands. In particular, we compute the density of states of adsorbed polymers as a function of the number of ligand-receptor complexes formed. Such a quantity can be used to study the conformational properties of adsorbed polymers useful when engineering adsorption with tailored properties. We successfully compare the results with the predictions of a mean field theory. We believe that the proposed method will be a useful tool to investigate supramolecular structures resulting from direct interactions between functionalized polymers for which efficient numerical methodologies of investigation are still lacking.
Molecular Determinants of Epidermal Growth Factor Binding: A Molecular Dynamics Study
Sanders, Jeffrey M.; Wampole, Matthew E.; Thakur, Mathew L.; Wickstrom, Eric
2013-01-01
The epidermal growth factor receptor (EGFR) is a member of the receptor tyrosine kinase family that plays a role in multiple cellular processes. Activation of EGFR requires binding of a ligand on the extracellular domain to promote conformational changes leading to dimerization and transphosphorylation of intracellular kinase domains. Seven ligands are known to bind EGFR with affinities ranging from sub-nanomolar to near micromolar dissociation constants. In the case of EGFR, distinct conformational states assumed upon binding a ligand is thought to be a determining factor in activation of a downstream signaling network. Previous biochemical studies suggest the existence of both low affinity and high affinity EGFR ligands. While these studies have identified functional effects of ligand binding, high-resolution structural data are lacking. To gain a better understanding of the molecular basis of EGFR binding affinities, we docked each EGFR ligand to the putative active state extracellular domain dimer and 25.0 ns molecular dynamics simulations were performed. MM-PBSA/GBSA are efficient computational approaches to approximate free energies of protein-protein interactions and decompose the free energy at the amino acid level. We applied these methods to the last 6.0 ns of each ligand-receptor simulation. MM-PBSA calculations were able to successfully rank all seven of the EGFR ligands based on the two affinity classes: EGF>HB-EGF>TGF-α>BTC>EPR>EPG>AR. Results from energy decomposition identified several interactions that are common among binding ligands. These findings reveal that while several residues are conserved among the EGFR ligand family, no single set of residues determines the affinity class. Instead we found heterogeneous sets of interactions that were driven primarily by electrostatic and Van der Waals forces. These results not only illustrate the complexity of EGFR dynamics but also pave the way for structure-based design of therapeutics targeting EGF ligands or the receptor itself. PMID:23382875
Nicolaï, Adrien; Delarue, Patrice; Senet, Patrick
2013-01-01
ATP regulates the function of many proteins in the cell by transducing its binding and hydrolysis energies into protein conformational changes by mechanisms which are challenging to identify at the atomic scale. Based on molecular dynamics (MD) simulations, a method is proposed to analyze the structural changes induced by ATP binding to a protein by computing the effective free-energy landscape (FEL) of a subset of its coordinates along its amino-acid sequence. The method is applied to characterize the mechanism by which the binding of ATP to the nucleotide-binding domain (NBD) of Hsp70 propagates a signal to its substrate-binding domain (SBD). Unbiased MD simulations were performed for Hsp70-DnaK chaperone in nucleotide-free, ADP-bound and ATP-bound states. The simulations revealed that the SBD does not interact with the NBD for DnaK in its nucleotide-free and ADP-bound states whereas the docking of the SBD was found in the ATP-bound state. The docked state induced by ATP binding found in MD is an intermediate state between the initial nucleotide-free and final ATP-bound states of Hsp70. The analysis of the FEL projected along the amino-acid sequence permitted to identify a subset of 27 protein internal coordinates corresponding to a network of 91 key residues involved in the conformational change induced by ATP binding. Among the 91 residues, 26 are identified for the first time, whereas the others were shown relevant for the allosteric communication of Hsp70 s in several experiments and bioinformatics analysis. The FEL analysis revealed also the origin of the ATP-induced structural modifications of the SBD recently measured by Electron Paramagnetic Resonance. The pathway between the nucleotide-free and the intermediate state of DnaK was extracted by applying principal component analysis to the subset of internal coordinates describing the transition. The methodology proposed is general and could be applied to analyze allosteric communication in other proteins.
Nicolaï, Adrien; Delarue, Patrice; Senet, Patrick
2013-01-01
ATP regulates the function of many proteins in the cell by transducing its binding and hydrolysis energies into protein conformational changes by mechanisms which are challenging to identify at the atomic scale. Based on molecular dynamics (MD) simulations, a method is proposed to analyze the structural changes induced by ATP binding to a protein by computing the effective free-energy landscape (FEL) of a subset of its coordinates along its amino-acid sequence. The method is applied to characterize the mechanism by which the binding of ATP to the nucleotide-binding domain (NBD) of Hsp70 propagates a signal to its substrate-binding domain (SBD). Unbiased MD simulations were performed for Hsp70-DnaK chaperone in nucleotide-free, ADP-bound and ATP-bound states. The simulations revealed that the SBD does not interact with the NBD for DnaK in its nucleotide-free and ADP-bound states whereas the docking of the SBD was found in the ATP-bound state. The docked state induced by ATP binding found in MD is an intermediate state between the initial nucleotide-free and final ATP-bound states of Hsp70. The analysis of the FEL projected along the amino-acid sequence permitted to identify a subset of 27 protein internal coordinates corresponding to a network of 91 key residues involved in the conformational change induced by ATP binding. Among the 91 residues, 26 are identified for the first time, whereas the others were shown relevant for the allosteric communication of Hsp70 s in several experiments and bioinformatics analysis. The FEL analysis revealed also the origin of the ATP-induced structural modifications of the SBD recently measured by Electron Paramagnetic Resonance. The pathway between the nucleotide-free and the intermediate state of DnaK was extracted by applying principal component analysis to the subset of internal coordinates describing the transition. The methodology proposed is general and could be applied to analyze allosteric communication in other proteins. PMID:24348227
Fukunishi, Yoshifumi
2010-01-01
For fragment-based drug development, both hit (active) compound prediction and docking-pose (protein-ligand complex structure) prediction of the hit compound are important, since chemical modification (fragment linking, fragment evolution) subsequent to the hit discovery must be performed based on the protein-ligand complex structure. However, the naïve protein-compound docking calculation shows poor accuracy in terms of docking-pose prediction. Thus, post-processing of the protein-compound docking is necessary. Recently, several methods for the post-processing of protein-compound docking have been proposed. In FBDD, the compounds are smaller than those for conventional drug screening. This makes it difficult to perform the protein-compound docking calculation. A method to avoid this problem has been reported. Protein-ligand binding free energy estimation is useful to reduce the procedures involved in the chemical modification of the hit fragment. Several prediction methods have been proposed for high-accuracy estimation of protein-ligand binding free energy. This paper summarizes the various computational methods proposed for docking-pose prediction and their usefulness in FBDD.
Prediction of Water Binding to Protein Hydration Sites with a Discrete, Semiexplicit Solvent Model.
Setny, Piotr
2015-12-08
Buried water molecules are ubiquitous in protein structures and are found at the interface of most protein-ligand complexes. Determining their distribution and thermodynamic effect is a challenging yet important task, of great of practical value for the modeling of biomolecular structures and their interactions. In this study, we present a novel method aimed at the prediction of buried water molecules in protein structures and estimation of their binding free energies. It is based on a semiexplicit, discrete solvation model, which we previously introduced in the context of small molecule hydration. The method is applicable to all macromolecular structures described by a standard all-atom force field, and predicts complete solvent distribution within a single run with modest computational cost. We demonstrate that it indicates positions of buried hydration sites, including those filled by more than one water molecule, and accurately differentiates them from sterically accessible to water but void regions. The obtained estimates of water binding free energies are in fair agreement with reference results determined with the double decoupling method.
Energetics of codon-anticodon recognition on the small ribosomal subunit.
Almlöf, Martin; Andér, Martin; Aqvist, Johan
2007-01-09
Recent crystal structures of the small ribosomal subunit have made it possible to examine the detailed energetics of codon recognition on the ribosome by computational methods. The binding of cognate and near-cognate anticodon stem loops to the ribosome decoding center, with mRNA containing the Phe UUU and UUC codons, are analyzed here using explicit solvent molecular dynamics simulations together with the linear interaction energy (LIE) method. The calculated binding free energies are in excellent agreement with experimental binding constants and reproduce the relative effects of mismatches in the first and second codon position versus a mismatch at the wobble position. The simulations further predict that the Leu2 anticodon stem loop is about 10 times more stable than the Ser stem loop in complex with the Phe UUU codon. It is also found that the ribosome significantly enhances the intrinsic stability differences of codon-anticodon complexes in aqueous solution. Structural analysis of the simulations confirms the previously suggested importance of the universally conserved nucleotides A1492, A1493, and G530 in the decoding process.
Computational screening of biomolecular adsorption and self-assembly on nanoscale surfaces.
Heinz, Hendrik
2010-05-01
The quantification of binding properties of ions, surfactants, biopolymers, and other macromolecules to nanometer-scale surfaces is often difficult experimentally and a recurring challenge in molecular simulation. A simple and computationally efficient method is introduced to compute quantitatively the energy of adsorption of solute molecules on a given surface. Highly accurate summation of Coulomb energies as well as precise control of temperature and pressure is required to extract the small energy differences in complex environments characterized by a large total energy. The method involves the simulation of four systems, the surface-solute-solvent system, the solute-solvent system, the solvent system, and the surface-solvent system under consideration of equal molecular volumes of each component under NVT conditions using standard molecular dynamics or Monte Carlo algorithms. Particularly in chemically detailed systems including thousands of explicit solvent molecules and specific concentrations of ions and organic solutes, the method takes into account the effect of complex nonbond interactions and rotational isomeric states on the adsorption behavior on surfaces. As a numerical example, the adsorption of a dodecapeptide on the Au {111} and mica {001} surfaces is described in aqueous solution. Copyright 2009 Wiley Periodicals, Inc.
Rocklin, Gabriel J.; Mobley, David L.; Dill, Ken A.; Hünenberger, Philippe H.
2013-01-01
The calculation of a protein-ligand binding free energy based on molecular dynamics (MD) simulations generally relies on a thermodynamic cycle in which the ligand is alchemically inserted into the system, both in the solvated protein and free in solution. The corresponding ligand-insertion free energies are typically calculated in nanoscale computational boxes simulated under periodic boundary conditions and considering electrostatic interactions defined by a periodic lattice-sum. This is distinct from the ideal bulk situation of a system of macroscopic size simulated under non-periodic boundary conditions with Coulombic electrostatic interactions. This discrepancy results in finite-size effects, which affect primarily the charging component of the insertion free energy, are dependent on the box size, and can be large when the ligand bears a net charge, especially if the protein is charged as well. This article investigates finite-size effects on calculated charging free energies using as a test case the binding of the ligand 2-amino-5-methylthiazole (net charge +1 e) to a mutant form of yeast cytochrome c peroxidase in water. Considering different charge isoforms of the protein (net charges −5, 0, +3, or +9 e), either in the absence or the presence of neutralizing counter-ions, and sizes of the cubic computational box (edges ranging from 7.42 to 11.02 nm), the potentially large magnitude of finite-size effects on the raw charging free energies (up to 17.1 kJ mol−1) is demonstrated. Two correction schemes are then proposed to eliminate these effects, a numerical and an analytical one. Both schemes are based on a continuum-electrostatics analysis and require performing Poisson-Boltzmann (PB) calculations on the protein-ligand system. While the numerical scheme requires PB calculations under both non-periodic and periodic boundary conditions, the latter at the box size considered in the MD simulations, the analytical scheme only requires three non-periodic PB calculations for a given system, its dependence on the box size being analytical. The latter scheme also provides insight into the physical origin of the finite-size effects. These two schemes also encompass a correction for discrete solvent effects that persists even in the limit of infinite box sizes. Application of either scheme essentially eliminates the size dependence of the corrected charging free energies (maximal deviation of 1.5 kJ mol−1). Because it is simple to apply, the analytical correction scheme offers a general solution to the problem of finite-size effects in free-energy calculations involving charged solutes, as encountered in calculations concerning, e.g., protein-ligand binding, biomolecular association, residue mutation, pKa and redox potential estimation, substrate transformation, solvation, and solvent-solvent partitioning. PMID:24320250
Rocklin, Gabriel J; Mobley, David L; Dill, Ken A; Hünenberger, Philippe H
2013-11-14
The calculation of a protein-ligand binding free energy based on molecular dynamics (MD) simulations generally relies on a thermodynamic cycle in which the ligand is alchemically inserted into the system, both in the solvated protein and free in solution. The corresponding ligand-insertion free energies are typically calculated in nanoscale computational boxes simulated under periodic boundary conditions and considering electrostatic interactions defined by a periodic lattice-sum. This is distinct from the ideal bulk situation of a system of macroscopic size simulated under non-periodic boundary conditions with Coulombic electrostatic interactions. This discrepancy results in finite-size effects, which affect primarily the charging component of the insertion free energy, are dependent on the box size, and can be large when the ligand bears a net charge, especially if the protein is charged as well. This article investigates finite-size effects on calculated charging free energies using as a test case the binding of the ligand 2-amino-5-methylthiazole (net charge +1 e) to a mutant form of yeast cytochrome c peroxidase in water. Considering different charge isoforms of the protein (net charges -5, 0, +3, or +9 e), either in the absence or the presence of neutralizing counter-ions, and sizes of the cubic computational box (edges ranging from 7.42 to 11.02 nm), the potentially large magnitude of finite-size effects on the raw charging free energies (up to 17.1 kJ mol(-1)) is demonstrated. Two correction schemes are then proposed to eliminate these effects, a numerical and an analytical one. Both schemes are based on a continuum-electrostatics analysis and require performing Poisson-Boltzmann (PB) calculations on the protein-ligand system. While the numerical scheme requires PB calculations under both non-periodic and periodic boundary conditions, the latter at the box size considered in the MD simulations, the analytical scheme only requires three non-periodic PB calculations for a given system, its dependence on the box size being analytical. The latter scheme also provides insight into the physical origin of the finite-size effects. These two schemes also encompass a correction for discrete solvent effects that persists even in the limit of infinite box sizes. Application of either scheme essentially eliminates the size dependence of the corrected charging free energies (maximal deviation of 1.5 kJ mol(-1)). Because it is simple to apply, the analytical correction scheme offers a general solution to the problem of finite-size effects in free-energy calculations involving charged solutes, as encountered in calculations concerning, e.g., protein-ligand binding, biomolecular association, residue mutation, pKa and redox potential estimation, substrate transformation, solvation, and solvent-solvent partitioning.
NASA Astrophysics Data System (ADS)
Rocklin, Gabriel J.; Mobley, David L.; Dill, Ken A.; Hünenberger, Philippe H.
2013-11-01
The calculation of a protein-ligand binding free energy based on molecular dynamics (MD) simulations generally relies on a thermodynamic cycle in which the ligand is alchemically inserted into the system, both in the solvated protein and free in solution. The corresponding ligand-insertion free energies are typically calculated in nanoscale computational boxes simulated under periodic boundary conditions and considering electrostatic interactions defined by a periodic lattice-sum. This is distinct from the ideal bulk situation of a system of macroscopic size simulated under non-periodic boundary conditions with Coulombic electrostatic interactions. This discrepancy results in finite-size effects, which affect primarily the charging component of the insertion free energy, are dependent on the box size, and can be large when the ligand bears a net charge, especially if the protein is charged as well. This article investigates finite-size effects on calculated charging free energies using as a test case the binding of the ligand 2-amino-5-methylthiazole (net charge +1 e) to a mutant form of yeast cytochrome c peroxidase in water. Considering different charge isoforms of the protein (net charges -5, 0, +3, or +9 e), either in the absence or the presence of neutralizing counter-ions, and sizes of the cubic computational box (edges ranging from 7.42 to 11.02 nm), the potentially large magnitude of finite-size effects on the raw charging free energies (up to 17.1 kJ mol-1) is demonstrated. Two correction schemes are then proposed to eliminate these effects, a numerical and an analytical one. Both schemes are based on a continuum-electrostatics analysis and require performing Poisson-Boltzmann (PB) calculations on the protein-ligand system. While the numerical scheme requires PB calculations under both non-periodic and periodic boundary conditions, the latter at the box size considered in the MD simulations, the analytical scheme only requires three non-periodic PB calculations for a given system, its dependence on the box size being analytical. The latter scheme also provides insight into the physical origin of the finite-size effects. These two schemes also encompass a correction for discrete solvent effects that persists even in the limit of infinite box sizes. Application of either scheme essentially eliminates the size dependence of the corrected charging free energies (maximal deviation of 1.5 kJ mol-1). Because it is simple to apply, the analytical correction scheme offers a general solution to the problem of finite-size effects in free-energy calculations involving charged solutes, as encountered in calculations concerning, e.g., protein-ligand binding, biomolecular association, residue mutation, pKa and redox potential estimation, substrate transformation, solvation, and solvent-solvent partitioning.
Is nuclear matter a quantum crystal?
NASA Technical Reports Server (NTRS)
Canuto, V.; Chitre, S. M.
1973-01-01
A possible alternative to the ordinary gas-like computation for nuclear matter is investigated under the assumption that the nucleons are arranged in a lattice. BCC, FCC and HCP structures are investigated. Only HCP shows a minimum in the energy vs. density curve with a modest binding energy of -1.5 MeV. The very low density limit is investigated and sensible results are obtained only if the tensor force decreases with the density. A study of the elastic properties indicates that the previous structures are mechanically unstable against shearing stresses.
Hu, Guodong; Ma, Aijing; Wang, Jihua
2017-04-24
Riboswitches regulate gene expression through direct and specific interactions with small metabolite molecules. Binding of a ligand to its RNA target is high selectivity and affinity and induces conformational changes of the RNA's secondary and tertiary structure. The structural difference of two purine riboswitches aptamers is caused by only one single mutation, where cytosine 74 in the guanine riboswitch is corresponding to a uracil 74 in adenine riboswitch. Here we employed molecular dynamics (MD) simulation, molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) and thermodynamic integration computational methodologies to evaluate the energetic and conformational changes of ligands binding to purine riboswitches. The snapshots used in MM-PBSA calculation were extracted from ten 50 ns MD simulation trajectories for each complex. These free energy results are in consistent with the experimental data and rationalize the selectivity of the riboswitches for different ligands. In particular, it is found that the loss in binding free energy upon mutation is mainly electrostatic in guanine (GUA) and riboswitch complex. Furthermore, new hydrogen bonds are found in mutated complexes. To reveal the conformational properties of guanine riboswitch, we performed a total of 6 μs MD simulations in both the presence and the absence of the ligand GUA. The MD simulations suggest that the conformation of guanine riboswitch depends on the distance of two groups in the binding pocket of ligand. The conformation is in a close conformation when U51-A52 is close to C74-U75.
NASA Astrophysics Data System (ADS)
Kar, J. K.; Panda, Saswati; Rout, G. C.
2017-05-01
We propose here a tight binding model study of the interplay between charge and spin orderings in the CMR manganites taking anisotropic effect due to electron hoppings and spin exchanges. The Hamiltonian consists of the kinetic energies of eg and t2g electrons of manganese ion. It further includes double exchange and Heisenberg interactions. The charge density wave interaction (CDW) describes an extra mechanism for the insulating character of the system. The CDW gap and spin parameters are calculated using Zubarev's Green's function technique and computed self-consistently. The results are reported in this communication.
Theoretical studies of the electronic spectrum of tellurium monosulfide.
Chattopadhyaya, Surya; Nath, Abhijit; Das, Kalyan Kumar
2013-08-01
Ab initio based multireference singles and doubles configuration interaction (MRDCI) study including spin-orbit coupling is carried out to explore the electronic structure and spectroscopic properties of tellurium monosulfide (TeS) molecule by employing relativistic effective core potentials (RECP) and suitable Gaussian basis sets of the constituent atoms. Potential energy curves correlating with the lowest and second dissociation limit are constructed and spectroscopic constants (T(e), r(e), and ω(e)) of several low-lying bound Λ-S electronic states up to 3.68 eV of energy are computed. The binding energies and electric dipole moments (μ(e)) of the ground and the low-lying excited Λ-S states are also computed. The effects of the spin-orbit coupling on the electronic spectrum of the species are studied in details and compared with the available data. The transition probabilities of some dipole-allowed and spin-forbidden transitions are computed and radiative lifetimes of some excited states at lowest vibrational level are estimated from the transition probability data. Copyright © 2013 Elsevier B.V. All rights reserved.
Hu, Xiao; Maffucci, Irene; Contini, Alessandro
2018-05-13
The inclusion of direct effects mediated by water during the ligand-receptor recognition is a hot-topic of modern computational chemistry applied to drug discovery and development. Docking or virtual screening with explicit hydration is still debatable, despite the successful cases that have been presented in the last years. Indeed, how to select the water molecules that will be included in the docking process or how the included waters should be treated remain open questions. In this review, we will discuss some of the most recent methods that can be used in computational drug discovery and drug development when the effect of a single water, or of a small network of interacting waters, needs to be explicitly considered. Here, we analyse software to aid the selection, or to predict the position, of water molecules that are going to be explicitly considered in later docking studies. We also present software and protocols able to efficiently treat flexible water molecules during docking, including examples of applications. Finally, we discuss methods based on molecular dynamics simulations that can be used to integrate docking studies or to reliably and efficiently compute binding energies of ligands in presence of interfacial or bridging water molecules. Software applications aiding the design of new drugs that exploit water molecules, either as displaceable residues or as bridges to the receptor, are constantly being developed. Although further validation is needed, workflows that explicitly consider water will probably become a standard for computational drug discovery soon. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
A computational study of the open and closed forms of the N-lobe human serum transferrin apoprotein.
Rinaldo, David; Field, Martin J
2003-12-01
Human serum transferrin tightly binds ferric ions in the blood stream but is able to release them in cells by a process involving receptor-mediated endocytosis and decrease in pH. Iron binding and release are accompanied by a large conformation change. In this study, we investigate theoretically the open and closed forms of the N-lobe human serum transferrin apoprotein by performing pKa calculations and molecular dynamics and free-energy simulations. In agreement with the hypothesis based on the x-ray crystal structures, our calculations show that there is a shift in the pKa values of the lysines forming the dilysine trigger when the conformation changes. We argue, however, that simple electrostatic repulsion between the lysines is not sufficient to trigger domain opening and, instead, propose an alternative explanation for the dilysine-trigger effect. Analysis of the molecular dynamics and free-energy results indicate that the open form is more mobile than the closed form and is much more stable at pH 5.3, in large part due to entropic effects. Despite a lower free energy, the dynamics simulation of the open form shows that it is flexible enough to sample conformations that are consistent with iron binding.
Investigation of binding features: effects on the interaction between CYP2A6 and inhibitors.
Ai, Chunzhi; Li, Yan; Wang, Yonghua; Li, Wei; Dong, Peipei; Ge, Guangbo; Yang, Ling
2010-07-15
A computational investigation has been carried out on CYP2A6 and its naphthalene inhibitors to explore the crucial molecular features contributing to binding specificity. The molecular bioactive orientations were obtained by docking (FlexX) these compounds into the active site of the enzyme. And the density functional theory method was further used to optimize the molecular structures with the subsequent analysis of molecular lipophilic potential (MLP) and molecular electrostatic potential (MEP). The minimal MLPs, minimal MEPs, and the band gap energies (the energy difference between the highest occupied molecular orbital and lowest unoccupied molecular orbital) showed high correlations with the inhibition activities (pIC(50)s), illustrating their significant roles in driving the inhibitor to adopt an appropriate bioactive conformation oriented in the active site of CYP2A6 enzyme. The differences in MLPs, MEPs, and the orbital energies have been identified as key features in determining the binding specificity of this series of compounds to CYP2A6 and the consequent inhibitory effects. In addition, the combinational use of the docking, MLP and MEP analysis is also demonstrated as a good attempt to gain an insight into the interaction between CYP2A6 and its inhibitors. Copyright 2010 Wiley Periodicals, Inc.
A Python tool to set up relative free energy calculations in GROMACS
Klimovich, Pavel V.; Mobley, David L.
2015-01-01
Free energy calculations based on molecular dynamics (MD) simulations have seen a tremendous growth in the last decade. However, it is still difficult and tedious to set them up in an automated manner, as the majority of the present-day MD simulation packages lack that functionality. Relative free energy calculations are a particular challenge for several reasons, including the problem of finding a common substructure and mapping the transformation to be applied. Here we present a tool, alchemical-setup.py, that automatically generates all the input files needed to perform relative solvation and binding free energy calculations with the MD package GROMACS. When combined with Lead Optimization Mapper [14], recently developed in our group, alchemical-setup.py allows fully automated setup of relative free energy calculations in GROMACS. Taking a graph of the planned calculations and a mapping, both computed by LOMAP, our tool generates the topology and coordinate files needed to perform relative free energy calculations for a given set of molecules, and provides a set of simulation input parameters. The tool was validated by performing relative hydration free energy calculations for a handful of molecules from the SAMPL4 challenge [16]. Good agreement with previously published results and the straightforward way in which free energy calculations can be conducted make alchemical-setup.py a promising tool for automated setup of relative solvation and binding free energy calculations. PMID:26487189
NASA Astrophysics Data System (ADS)
Niroomand, Sona; Khorasani-Motlagh, Mozhgan; Noroozifar, Meissam; Jahani, Shohreh; Moodi, Asieh
2017-02-01
The binding of the lanthanum(III) complex containing 1,10-phenanthroline (phen), [La(phen)3Cl3·OH2], to DNA is investigated by absorption and emission methods. This complex shows absorption decreasing in a charge transfer band, and fluorescence decrement when it binds to DNA. Electronic absorption spectroscopy (UV-Vis), fluorescence spectra, iodide quenching experiments, salt effect and viscosity measurements, ethidium bromide (EB) competition test, circular dichroism (CD) spectra as well as variable temperature experiments indicate that the La(III) complex binds to fish salmon (FS) DNA, presumably via groove binding mode. The binding constants (Kb) of the La(III) complex with DNA is (2.55 ± 0.02) × 106 M-1. Furthermore, the binding site size, n, the Stern-Volmer constant KSV and thermodynamic parameters; enthalpy change (ΔH0) and entropy change (ΔS0) and Gibb's free energy (ΔG0), are calculated according to relevant fluorescent data and the Van't Hoff equation. The La(III) complex has been screened for its antibacterial activities by the disc diffusion method. Also, in order to supplement the experimental findings, DFT computation and NBO analysis are carried out.
NASA Astrophysics Data System (ADS)
Saurabh, Suman; Sahoo, Anil Kumar; Maiti, Prabal K.
2016-10-01
Experiments and computational studies have established that de-protonated dendrimers (SPL7013 and PAMAM) act as entry-inhibitors of HIV. SPL7013 based Vivagel is currently under clinical development. The dendrimer binds to gp120 in the gp120-CD4 complex, destabilizes it by breaking key contacts between gp120 and CD4 and prevents viral entry into target cells. In this work, we provide molecular details and energetics of the formation of the SPL7013-gp120-CD4 ternary complex and decipher modes of action of the dendrimer in preventing viral entry. It is also known from experiments that the dendrimer binds weakly to gp120 that is not bound to CD4. It binds even more weakly to the CD4-binding region of gp120 and thus cannot directly block gp120-CD4 complexation. In this work, we examine the feasibility of dendrimer binding to the gp120-binding region of CD4 and directly blocking gp120-CD4 complex formation. We find that the process of the dendrimer binding to CD4 can compete with gp120-CD4 binding due to comparable free energy change for the two processes, thus creating a possibility for the dendrimer to directly block gp120-CD4 complexation by binding to the gp120-binding region of CD4.
Yan, Fangfang; Liu, Xinguo; Zhang, Shaolong; Su, Jing; Zhang, Qinggang; Chen, Jianzhong
2017-11-06
Endocellular protein tyrosine phosphatase 1B (PTP1B) is one of the most promising target for designing and developing drugs to cure type-II diabetes and obesity. Molecular dynamics (MD) simulations combined with molecular mechanics generalized Born surface area (MM-GBSA) and solvated interaction energy methods were applied to study binding differences of three inhibitors (ID: 901, 941, and 968) to PTP1B, the calculated results show that the inhibitor 901 has the strongest binding ability to PTP1B among the current inhibitors. Principal component (PC) analysis was also carried out to investigate the conformational change of PTP1B, and the results indicate that the associations of inhibitors with PTP1B generate a significant effect on the motion of the WPD-loop. Free energy decomposition method was applied to study the contributions of individual residues to inhibitor bindings, it is found that three inhibitors can generate hydrogen bonding interactions and hydrophobic interactions with different residues of PTP1B, which provide important forces for associations of inhibitors with PTP1B. This research is expected to give a meaningfully theoretical guidance to design and develop of effective drugs curing type-II diabetes and obesity.
Zhao, Sufang; Zhu, Jingyu; Xu, Lei; Jin, Jian
2017-06-01
Glycogen synthase kinase 3 (GSK3) is a serine/threonine protein kinase which is widely involved in cell signaling and controls a broad number of cellular functions. GSK3 contains α and β isoforms, and GSK3β has received more attention and becomes an attractive drug target for the treatment of several diseases. The binding pocket of cyclin-dependent kinase 2 (CDK2) shares high sequence identity to that of GSK3β, and therefore, the design of highly selective inhibitors toward GSK3β remains a big challenge. In this study, a computational strategy, which combines molecular docking, molecular dynamics simulations, free energy calculations, and umbrella sampling simulations, was employed to explore the binding mechanisms of two selective inhibitors to GSK3β and CDK2. The simulation results highlighted the key residues critical for GSK3β selectivity. It was observed that although GSK3β and CDK2 share the conserved ATP-binding pockets, some different residues have significant contributions to protein selectivity. This study provides valuable information for understanding the GSK3β-selective binding mechanisms and the rational design of selective GSK3β inhibitors. © 2016 John Wiley & Sons A/S.
Hathout, Rania M; Metwally, Abdelkader A
2016-11-01
This study represents one of the series applying computer-oriented processes and tools in digging for information, analysing data and finally extracting correlations and meaningful outcomes. In this context, binding energies could be used to model and predict the mass of loaded drugs in solid lipid nanoparticles after molecular docking of literature-gathered drugs using MOE® software package on molecularly simulated tripalmitin matrices using GROMACS®. Consequently, Gaussian processes as a supervised machine learning artificial intelligence technique were used to correlate the drugs' descriptors (e.g. M.W., xLogP, TPSA and fragment complexity) with their molecular docking binding energies. Lower percentage bias was obtained compared to previous studies which allows the accurate estimation of the loaded mass of any drug in the investigated solid lipid nanoparticles by just projecting its chemical structure to its main features (descriptors). Copyright © 2016 Elsevier B.V. All rights reserved.
Warping Armchair Graphene Nanoribbon Curvature Effect on Sensing Properties: A Computational Study
NASA Astrophysics Data System (ADS)
Sakina, S. H.; Johari, Zaharah; Auzar, Zuriana; Alias, N. Ezaila; Mohamad, Azam; Zakaria, N. Aini
2018-02-01
The aim of this paper is to investigate the interaction between gas molecules and warped armchair graphene nanoribbons (AGNRs) using Extended-Huckel Theory. There are two types of warping known as inward and upward. The sensing properties including binding energy, charge transfer and sensitivity were examined for both warped AGNR cases for 3m+1 configuration and were compared with previous work. Through simulation, it was found that a substantial increase in binding energy by more than 50% was achieved when warped at a higher angle. It is also showed that there was a significant difference in sensitivity for both warping cases when reacting with O2 and NH3 molecules. Interestingly, the ability of the inward warped in sensing O2 and NH3 considerably increases upon warping angle. By applying back gate bias, this shows that current conductivity of the inward warped is twice as high as the upward warped AGNR.
Epa, V. Chandana; Dolezal, Olan; Doughty, Larissa; Xiao, Xiaowen; Jost, Christian; Plückthun, Andreas; Adams, Timothy E.
2013-01-01
Designed Ankyrin Repeat Proteins are a class of novel binding proteins that can be selected and evolved to bind to targets with high affinity and specificity. We are interested in the DARPin H10-2-G3, which has been evolved to bind with very high affinity to the human epidermal growth factor receptor 2 (HER2). HER2 is found to be over-expressed in 30% of breast cancers, and is the target for the FDA-approved therapeutic monoclonal antibodies trastuzumab and pertuzumab and small molecule tyrosine kinase inhibitors. Here, we use computational macromolecular docking, coupled with several interface metrics such as shape complementarity, interaction energy, and electrostatic complementarity, to model the structure of the complex between the DARPin H10-2-G3 and HER2. We analyzed the interface between the two proteins and then validated the structural model by showing that selected HER2 point mutations at the putative interface with H10-2-G3 reduce the affinity of binding up to 100-fold without affecting the binding of trastuzumab. Comparisons made with a subsequently solved X-ray crystal structure of the complex yielded a backbone atom root mean square deviation of 0.84–1.14 Ångstroms. The study presented here demonstrates the capability of the computational techniques of structural bioinformatics in generating useful structural models of protein-protein interactions. PMID:23527120
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shokri, Alireza; Wang, Xue B.; Wang, Yangping
2016-03-17
Flexible acyclic alcohols with 1–5 hydroxyl groups were bound to chloride anion and these complexes were interrogated by negative ion photoelectron spectroscopy and companion density functional theory computations. The resulting vertical detachment energies are reproduced on average to 0.10 eV by M06-2X/aug-cc-pVTZ predictions and range from 4.45 – 5.96 eV. These values are 0.84 – 2.35 eV larger than the adiabatic detachment energy of Cl– as a result of the larger hydrogen bond networks in the bigger polyols. Adiabatic detachment energies of the alcohol–Cl– clusters are more difficult to determine both experimentally and computationally. This is due to the largemore » geometry changes that occur upon photodetachment and the large bond dissociation energy of H–Cl which enables the resulting chlorine atom to abstract a hydrogen from any of the methylene (CH2) or methine (CH) positions. Both ionic and non-ionic hydrogen bonds (i.e., OH•••Cl– and OH•••OH•••Cl–) form in the larger polyols complexes, and are found to be energetically comparable. Subtle structural differences, consequently can lead to the formation of different types of hydrogen bonds and maximizing the ionic ones is not always preferred. Solution equilibrium binding constants between the alcohols and tetrrabuylammonium chloride (TBACl) in acetonitrile at -24.2, 22.0, and 53.6 °C were also determined. The free energies of association are nearly identical for all of the substrates (i.e., ΔG° = -2.8 ± 0.7 kcal mol–1). Compensating enthalpy and entropy values reveal, contrary to expectation and the intrinsic gas-phase preferences, that the bigger systems with more hydroxyl groups are entropically favored and enthalpically disfavored relative to the smaller species. This suggests that more solvent molecules are released upon binding TBACl to alcohols with more hydroxyl groups and is consistent with the measured negative heat capacities. These quantities increase with molecular complexity of the substrate, however, contrary to common interpretation of these values.« less
Catalytic N 2 Reduction to Silylamines and Thermodynamics of N 2 Binding at Square Planar Fe
DOE Office of Scientific and Technical Information (OSTI.GOV)
Prokopchuk, Demyan E.; Wiedner, Eric S.; Walter, Eric D.
The geometric constraints imposed by a tetradentate P 4N 2 ligand play an essential role in stabilizing square planar Fe complexes with changes in metal oxidation state. A combination of high-pressure electrochemistry and variable temperature UV-vis spectroscopy were used to obtain these thermodynamic measurements, while X-ray crystallography, 57Fe Mössbauer spectroscopy, and EPR spectroscopy were used to fully characterize these new compounds. Analysis of Fe 0, FeI, and FeII complexes reveals that the free energy of N 2 binding across three oxidation states spans more than 37 kcal mol -1. The square pyramidal Fe0(N 2)(P 4N 2) complex catalyzes the conversionmore » of N 2 to N(SiR 3) 3 (R = Me, Et) at room temperature, representing the highest turnover number (TON) of any Fe-based N 2 silylation catalyst to date (up to 65 equiv N(SiMe 3) 3 per Fe center). Elevated N 2 pressures (> 1 atm) have a dramatic effect on catalysis, increasing N 2 solubility and the thermodynamic N 2 binding affinity at Fe0(N 2)(P 4N 2). Acknowledgment. This research was supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences. EPR experiments were performed using EMSL, a national scientific user facility sponsored by the DOE’s Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory (PNNL). PNNL is operated by Battelle for the U.S. DOE. Computational resources were provided by the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory. The authors thank Prof. Yisong Alex Guo at Carnegie Mellon University for recording Mössbauer data for some complexes and Emma Wellington and Kaye Kuphal for their assistance with the collection of Mössbauer data at Colgate University, Dr. Katarzyna Grubel for X-ray assistance, and Dr. Rosalie Chu for mass spectrometry assistance. The authors also thank Dr. Aaron Appel and Dr. Alex Kendall for helpful discussions.« less
Mollica, Luca; Conti, Gianluca; Pollegioni, Loredano; Cavalli, Andrea; Rosini, Elena
2015-10-26
The industrial production of higher-generation semisynthetic cephalosporins starts from 7-aminocephalosporanic acid (7-ACA), which is obtained by deacylation of the naturally occurring antibiotic cephalosporin C (CephC). The enzymatic process in which CephC is directly converted into 7-ACA by a cephalosporin C acylase has attracted industrial interest because of the prospects of simplifying the process and reducing costs. We recently enhanced the catalytic efficiency on CephC of a glutaryl acylase from Pseudomonas N176 (named VAC) by a protein engineering approach and solved the crystal structures of wild-type VAC and the H57βS-H70βS VAC double variant. In the present work, experimental measurements on several CephC derivatives and six VAC variants were carried out, and the binding of ligands into the VAC active site was investigated at an atomistic level by means of molecular docking and molecular dynamics simulations and analyzed on the basis of the molecular geometry of encounter complex formation and protein-ligand potential of mean force profiles. The observed significant correlation between the experimental data and estimated binding energies highlights the predictive power of our computational method to identify the ligand binding mode. The present experimental-computational study is well-suited both to provide deep insight into the reaction mechanism of cephalosporin C acylase and to improve the efficiency of the corresponding industrial process.
Analyzing machupo virus-receptor binding by molecular dynamics simulations.
Meyer, Austin G; Sawyer, Sara L; Ellington, Andrew D; Wilke, Claus O
2014-01-01
In many biological applications, we would like to be able to computationally predict mutational effects on affinity in protein-protein interactions. However, many commonly used methods to predict these effects perform poorly in important test cases. In particular, the effects of multiple mutations, non alanine substitutions, and flexible loops are difficult to predict with available tools and protocols. We present here an existing method applied in a novel way to a new test case; we interrogate affinity differences resulting from mutations in a host-virus protein-protein interface. We use steered molecular dynamics (SMD) to computationally pull the machupo virus (MACV) spike glycoprotein (GP1) away from the human transferrin receptor (hTfR1). We then approximate affinity using the maximum applied force of separation and the area under the force-versus-distance curve. We find, even without the rigor and planning required for free energy calculations, that these quantities can provide novel biophysical insight into the GP1/hTfR1 interaction. First, with no prior knowledge of the system we can differentiate among wild type and mutant complexes. Moreover, we show that this simple SMD scheme correlates well with relative free energy differences computed via free energy perturbation. Second, although the static co-crystal structure shows two large hydrogen-bonding networks in the GP1/hTfR1 interface, our simulations indicate that one of them may not be important for tight binding. Third, one viral site known to be critical for infection may mark an important evolutionary suppressor site for infection-resistant hTfR1 mutants. Finally, our approach provides a framework to compare the effects of multiple mutations, individually and jointly, on protein-protein interactions.
Analyzing machupo virus-receptor binding by molecular dynamics simulations
Sawyer, Sara L.; Ellington, Andrew D.; Wilke, Claus O.
2014-01-01
In many biological applications, we would like to be able to computationally predict mutational effects on affinity in protein–protein interactions. However, many commonly used methods to predict these effects perform poorly in important test cases. In particular, the effects of multiple mutations, non alanine substitutions, and flexible loops are difficult to predict with available tools and protocols. We present here an existing method applied in a novel way to a new test case; we interrogate affinity differences resulting from mutations in a host–virus protein–protein interface. We use steered molecular dynamics (SMD) to computationally pull the machupo virus (MACV) spike glycoprotein (GP1) away from the human transferrin receptor (hTfR1). We then approximate affinity using the maximum applied force of separation and the area under the force-versus-distance curve. We find, even without the rigor and planning required for free energy calculations, that these quantities can provide novel biophysical insight into the GP1/hTfR1 interaction. First, with no prior knowledge of the system we can differentiate among wild type and mutant complexes. Moreover, we show that this simple SMD scheme correlates well with relative free energy differences computed via free energy perturbation. Second, although the static co-crystal structure shows two large hydrogen-bonding networks in the GP1/hTfR1 interface, our simulations indicate that one of them may not be important for tight binding. Third, one viral site known to be critical for infection may mark an important evolutionary suppressor site for infection-resistant hTfR1 mutants. Finally, our approach provides a framework to compare the effects of multiple mutations, individually and jointly, on protein–protein interactions. PMID:24624315
Gonzalez, Javier; Torrent-Sucarrat, Miquel; Anglada, Josep M
2010-03-07
The influence of a single water molecule on the gas-phase reactivity of the HO(2) radical has been investigated by studying the reactions of SO(3) with the HO(2) radical and with the H(2)O...HO(2) radical complex. The naked reaction leads to the formation of the HSO(5) radical, with a computed binding energy of 13.81 kcal mol(-1). The reaction with the H(2)O...HO(2) radical complex can give two different products, namely (a) HSO(5) + H(2)O, which has a binding energy that is computed to be 4.76 kcal mol(-1) more stable than the SO(3) + H(2)O...HO(2) reactants (Delta(E + ZPE) at 0K) and an estimated branching ratio of about 34% at 298K and (b) sulfuric acid and the hydroperoxyl radical, which is computed to be 10.51 kcal mol(-1) below the energy of the reactants (Delta(E + ZPE) at 0K), with an estimated branching ratio of about 66% at 298K. The fact that one of the products is H(2)SO(4) may have relevance in the chemistry of the atmosphere. Interestingly, the water molecule acts as a catalyst, [as it occurs in (a)] or as a reactant [as it occurs in (b)]. For a sake of completeness we have also calculated the anharmonic vibrational frequencies for HO(2), HSO(5), the HSO(5)...H(2)O hydrogen bonded complex, H(2)SO(4), and two H(2)SO(4)...H(2)O complexes, in order to help with the possible experimental identification of some of these species.
Synergistic Anion-(π) n-π Catalysis on π-Stacked Foldamers.
Bornhof, Anna-Bea; Bauzá, Antonio; Aster, Alexander; Pupier, Marion; Frontera, Antonio; Vauthey, Eric; Sakai, Naomi; Matile, Stefan
2018-04-11
In this report, we demonstrate that synergistic effects between π-π stacking and anion-π interactions in π-stacked foldamers provide access to unprecedented catalytic activity. To elaborate on anion-(π) n -π catalysis, we have designed, synthesized and evaluated a series of novel covalent oligomers with up to four face-to-face stacked naphthalenediimides (NDIs). NMR analysis including DOSY confirms folding into π stacks, cyclic voltammetry, steady-state and transient absorption spectroscopy the electronic communication within the π stacks. Catalytic activity, assessed by chemoselective catalysis of the intrinsically disfavored but biologically relevant addition reaction of malonate half thioesters to enolate acceptors, increases linearly with the length of the stacks to reach values that are otherwise beyond reach. This linear increase violates the sublinear power laws of oligomer chemistry. The comparison of catalytic activity with ratiometric changes in absorption and decreasing energy of the LUMO thus results in superlinearity, that is synergistic amplification of anion-π catalysis by remote control over the entire stack. In computational models, increasing length of the π-stacked foldamers correlates sublinearly with changes in surface potentials, chloride binding energies, and the distances between chloride and π surface and within the π stack. Computational evidence is presented that the selective acceleration of disfavored but relevant enolate chemistry by anion-π catalysis indeed originates from the discrimination of planar and bent tautomers with delocalized and localized charges, respectively, on π-acidic surfaces. Computed binding energies of keto and enol intermediates of the addition reaction as well as their difference increase with increasing length of the π stack and thus reflect experimental trends correctly. These results demonstrate that anion-(π) n -π interactions exist and matter, ready for use as a unique new tool in catalysis and beyond.
Comparison of the Efficiency of the LIE and MM/GBSA Methods to Calculate Ligand-Binding Energies.
Genheden, Samuel; Ryde, Ulf
2011-11-08
We have evaluated the efficiency of two popular end-point methods to calculate ligand-binding free energies, LIE (linear interaction energy) and MM/GBSA (molecular mechanics with generalized Born surface-area solvation), i.e. the computational effort needed to obtain estimates of a similar precision. As a test case, we use the binding of seven biotin analogues to avidin. The energy terms used by MM/GBSA and LIE exhibit a similar correlation time (∼5 ps), and the equilibration time seems also to be similar, although it varies much between the various ligands. The results show that the LIE method is more effective than MM/GBSA, by a factor of 2-7 for a truncated spherical system with a radius of 26 Å and by a factor of 1.0-2.4 for the full avidin tetramer (radius 47 Å). The reason for this is the cost for the MM/GBSA entropy calculations, which more than compensates for the extra simulation of the free ligand in LIE. On the other hand, LIE requires that the protein is neutralized, whereas MM/GBSA has no such requirements. Our results indicate that both the truncation and neutralization of the proteins may slow the convergence and emphasize small differences in the calculations, e.g., differences between the four subunits in avidin. Moreover, LIE cannot take advantage of the fact that avidin is a tetramer. For this test case, LIE gives poor results with the standard parametrization, but after optimizing the scaling factor of the van der Waals terms, reasonable binding affinities can be obtained, although MM/GBSA still gives a significantly better predictive index and correlation to the experimental affinities.
Patra, Niladri; Ioannidis, Efthymios I.
2016-01-01
Catechol O-methyltransferase (COMT) is a SAM- and Mg2+-dependent methyltransferase that regulates neurotransmitters through methylation. Simulations and experiments have identified divergent catecholamine substrate orientations in the COMT active site: molecular dynamics simulations have favored a monodentate coordination of catecholate substrates to the active site Mg2+, and crystal structures instead preserve bidentate coordination along with short (2.65 Å) methyl donor-acceptor distances. We carry out longer dynamics (up to 350 ns) to quantify interconversion between bidentate and monodentate binding poses. We provide a systematic determination of the relative free energy of the monodentate and bidentate structures in order to identify whether structural differences alter the nature of the methyl transfer mechanism and source of enzymatic rate enhancement. We demonstrate that the bidentate and monodentate binding modes are close in energy but separated by a 7 kcal/mol free energy barrier. Analysis of interactions in the two binding modes reveals that the driving force for monodentate catecholate orientations in classical molecular dynamics simulations is derived from stronger electrostatic stabilization afforded by alternate Mg2+ coordination with strongly charged active site carboxylates. Mixed semi-empirical-classical (SQM/MM) substrate C-O distances (2.7 Å) for the bidentate case are in excellent agreement with COMT X-ray crystal structures, as long as charge transfer between the substrates, Mg2+, and surrounding ligands is permitted. SQM/MM free energy barriers for methyl transfer from bidentate and monodentate catecholate configurations are comparable at around 21–22 kcal/mol, in good agreement with experiment (18–19 kcal/mol). Overall, the work suggests that both binding poses are viable for methyl transfer, and accurate descriptions of charge transfer and electrostatics are needed to provide balanced relative barriers when multiple binding poses are accessible, for example in other transferases. PMID:27564542
Nagy, Gabor; Oostenbrink, Chris; Hritz, Jozef
2017-01-01
The 14-3-3 protein family performs regulatory functions in eukaryotic organisms by binding to a large number of phosphorylated protein partners. Whilst the binding mode of the phosphopeptides within the primary 14-3-3 binding site is well established based on the crystal structures of their complexes, little is known about the binding process itself. We present a computational study of the process by which phosphopeptides bind to the 14-3-3ζ protein. Applying a novel scheme combining Hamiltonian replica exchange molecular dynamics and distancefield restraints allowed us to map and compare the most likely phosphopeptide-binding pathways to the 14-3-3ζ protein. The most important structural changes to the protein and peptides involved in the binding process were identified. In order to bind phosphopeptides to the primary interaction site, the 14-3-3ζ adopted a newly found wide-opened conformation. Based on our findings we additionally propose a secondary interaction site on the inner surface of the 14-3-3ζ dimer, and a direct interference on the binding process by the flexible C-terminal tail. A minimalistic model was designed to allow for the efficient calculation of absolute binding affinities. Binding affinities calculated from the potential of mean force along the binding pathway are in line with the available experimental estimates for two of the studied systems. PMID:28727767
Dobes, Petr; Otyepka, Michal; Strnad, Miroslav; Hobza, Pavel
2006-05-24
The interaction between roscovitine and cyclin-dependent kinase 2 (cdk2) was investigated by performing correlated ab initio quantum-chemical calculations. The whole protein was fragmented into smaller systems consisting of one or a few amino acids, and the interaction energies of these fragments with roscovitine were determined by using the MP2 method with the extended aug-cc-pVDZ basis set. For selected complexes, the complete basis set limit MP2 interaction energies, as well as the coupled-cluster corrections with inclusion of single, double and noninteractive triples contributions [CCSD(T)], were also evaluated. The energies of interaction between roscovitine and small fragments and between roscovitine and substantial sections of protein (722 atoms) were also computed by using density-functional tight-binding methods covering dispersion energy (DFTB-D) and the Cornell empirical potential. Total stabilisation energy originates predominantly from dispersion energy and methods that do not account for the dispersion energy cannot, therefore, be recommended for the study of protein-inhibitor interactions. The Cornell empirical potential describes reasonably well the interaction between roscovitine and protein; therefore, this method can be applied in future thermodynamic calculations. A limited number of amino acid residues contribute significantly to the binding of roscovitine and cdk2, whereas a rather large number of amino acids make a negligible contribution.
Exact kinetic energy enables accurate evaluation of weak interactions by the FDE-vdW method.
Sinha, Debalina; Pavanello, Michele
2015-08-28
The correlation energy of interaction is an elusive and sought-after interaction between molecular systems. By partitioning the response function of the system into subsystem contributions, the Frozen Density Embedding (FDE)-vdW method provides a computationally amenable nonlocal correlation functional based on the adiabatic connection fluctuation dissipation theorem applied to subsystem density functional theory. In reproducing potential energy surfaces of weakly interacting dimers, we show that FDE-vdW, either employing semilocal or exact nonadditive kinetic energy functionals, is in quantitative agreement with high-accuracy coupled cluster calculations (overall mean unsigned error of 0.5 kcal/mol). When employing the exact kinetic energy (which we term the Kohn-Sham (KS)-vdW method), the binding energies are generally closer to the benchmark, and the energy surfaces are also smoother.
Exact kinetic energy enables accurate evaluation of weak interactions by the FDE-vdW method
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sinha, Debalina; Pavanello, Michele, E-mail: m.pavanello@rutgers.edu
2015-08-28
The correlation energy of interaction is an elusive and sought-after interaction between molecular systems. By partitioning the response function of the system into subsystem contributions, the Frozen Density Embedding (FDE)-vdW method provides a computationally amenable nonlocal correlation functional based on the adiabatic connection fluctuation dissipation theorem applied to subsystem density functional theory. In reproducing potential energy surfaces of weakly interacting dimers, we show that FDE-vdW, either employing semilocal or exact nonadditive kinetic energy functionals, is in quantitative agreement with high-accuracy coupled cluster calculations (overall mean unsigned error of 0.5 kcal/mol). When employing the exact kinetic energy (which we term themore » Kohn-Sham (KS)-vdW method), the binding energies are generally closer to the benchmark, and the energy surfaces are also smoother.« less
Computational study of small molecule binding for both tethered and free conditions
2010-01-01
Using a calix[4]arene-benzene complex as a test system we compare the potential of mean force for when the calix[4]arene is tethered versus free. When the complex is in vacuum our results show that the difference between tethered and free is primarily due to the entropic contribution to the potential of mean force resulting in a significant binding free energy difference of 6.6 kJ/mol. By contrast, when the complex is in water our results suggest that there is no appreciable difference between tethered and free. This study elucidates the roles of entropy and enthalpy for this small molecule system and emphasizes the point that tethering the receptor has the potential to dramatically impact the binding properties. These findings should be taken into consideration when using calixarene molecules in nanosensor design. PMID:20369865
NASA Astrophysics Data System (ADS)
Humeniuk, Alexander; Mitrić, Roland
2017-12-01
A software package, called DFTBaby, is published, which provides the electronic structure needed for running non-adiabatic molecular dynamics simulations at the level of tight-binding DFT. A long-range correction is incorporated to avoid spurious charge transfer states. Excited state energies, their analytic gradients and scalar non-adiabatic couplings are computed using tight-binding TD-DFT. These quantities are fed into a molecular dynamics code, which integrates Newton's equations of motion for the nuclei together with the electronic Schrödinger equation. Non-adiabatic effects are included by surface hopping. As an example, the program is applied to the optimization of excited states and non-adiabatic dynamics of polyfluorene. The python and Fortran source code is available at http://www.dftbaby.chemie.uni-wuerzburg.de.
Bryce, Richard A
2011-04-01
The ability to accurately predict the interaction of a ligand with its receptor is a key limitation in computer-aided drug design approaches such as virtual screening and de novo design. In this article, we examine current strategies for a physics-based approach to scoring of protein-ligand affinity, as well as outlining recent developments in force fields and quantum chemical techniques. We also consider advances in the development and application of simulation-based free energy methods to study protein-ligand interactions. Fuelled by recent advances in computational algorithms and hardware, there is the opportunity for increased integration of physics-based scoring approaches at earlier stages in computationally guided drug discovery. Specifically, we envisage increased use of implicit solvent models and simulation-based scoring methods as tools for computing the affinities of large virtual ligand libraries. Approaches based on end point simulations and reference potentials allow the application of more advanced potential energy functions to prediction of protein-ligand binding affinities. Comprehensive evaluation of polarizable force fields and quantum mechanical (QM)/molecular mechanical and QM methods in scoring of protein-ligand interactions is required, particularly in their ability to address challenging targets such as metalloproteins and other proteins that make highly polar interactions. Finally, we anticipate increasingly quantitative free energy perturbation and thermodynamic integration methods that are practical for optimization of hits obtained from screened ligand libraries.
Mechanistic insight into ligand binding to G-quadruplex DNA
Di Leva, Francesco Saverio; Novellino, Ettore; Cavalli, Andrea; Parrinello, Michele; Limongelli, Vittorio
2014-01-01
Specific guanine-rich regions in human genome can form higher-order DNA structures called G-quadruplexes, which regulate many relevant biological processes. For instance, the formation of G-quadruplex at telomeres can alter cellular functions, inducing apoptosis. Thus, developing small molecules that are able to bind and stabilize the telomeric G-quadruplexes represents an attractive strategy for antitumor therapy. An example is 3-(benzo[d]thiazol-2-yl)-7-hydroxy-8-((4-(2-hydroxyethyl)piperazin-1-yl)methyl)-2H-chromen-2-one (compound 1), recently identified as potent ligand of the G-quadruplex [d(TGGGGT)]4 with promising in vitro antitumor activity. The experimental observations are suggestive of a complex binding mechanism that, despite efforts, has defied full characterization. Here, we provide through metadynamics simulations a comprehensive understanding of the binding mechanism of 1 to the G-quadruplex [d(TGGGGT)]4. In our calculations, the ligand explores all the available binding sites on the DNA structure and the free-energy landscape of the whole binding process is computed. We have thus disclosed a peculiar hopping binding mechanism whereas 1 is able to bind both to the groove and to the 3’ end of the G-quadruplex. Our results fully explain the available experimental data, rendering our approach of great value for further ligand/DNA studies. PMID:24753420
Thunyakitpisal, Pasutha; Ruangpornvisuti, Vithaya; Kengkwasing, Pattrawadee; Chokboribal, Jaroenporn; Sangvanich, Polkit
2017-04-01
Acemannan, an acetylated polymannose from Aloe vera, has immunomodulatory effects. We investigated whether acemannan induces IL-6 and -8 expression and NF-κB/DNA binding in human gingival fibroblasts. IL-6 and -8 expression levels were assessed via RT-PCR and ELISA. The NF-κB p50/p65-DNA binding was determined. The structures of acemannan mono-pentamers and Toll-like receptor 5 (TLR5) were simulated. The binding energies between acemannan and TLR5 were identified. We found that acemannan significantly stimulated IL-6/-8 expression at both the mRNA and protein level and significantly increased p50/DNA binding. Preincubation with an anti-TLR5 neutralizing antibody abolished acemannan-induced IL-6/-8 expression and p50/DNA binding, and co-incubation of acemannan with Bay11-7082, a specific NF- κB inhibitor, abolished IL-6/-8 expression. The computer modeling indicated that monomeric/dimeric single stranded acemannan molecules interacted with the TLR5 flagellin recognition sites with a high binding affinity. We conclude that acemannan induces IL-6/-8 expression, and p50/DNA binding in gingival fibroblasts, at least partly, via a TLR5/NF-κB-dependent signaling pathway. Furthermore, acemannan selectively binds with TLR5 ectodomain flagellin recognition sites. Copyright © 2017 Elsevier Ltd. All rights reserved.
A Computational Analysis of ATP Binding of SV40 Large Tumor Antigen Helicase Motor
Shi, Yemin; Liu, Hanbin; Gai, Dahai; Ma, Jianpeng; Chen, Xiaojiang S.
2009-01-01
Simian Virus 40 Large Tumor Antigen (LTag) is an efficient helicase motor that unwinds and translocates DNA. The DNA unwinding and translocation of LTag is powered by ATP binding and hydrolysis at the nucleotide pocket between two adjacent subunits of an LTag hexamer. Based on the set of high-resolution hexameric structures of LTag helicase in different nucleotide binding states, we simulated a conformational transition pathway of the ATP binding process using the targeted molecular dynamics method and calculated the corresponding energy profile using the linear response approximation (LRA) version of the semi-macroscopic Protein Dipoles Langevin Dipoles method (PDLD/S). The simulation results suggest a three-step process for the ATP binding from the initial interaction to the final tight binding at the nucleotide pocket, in which ATP is eventually “locked” by three pairs of charge-charge interactions across the pocket. Such a “cross-locking” ATP binding process is similar to the binding zipper model reported for the F1-ATPase hexameric motor. The simulation also shows a transition mechanism of Mg2+ coordination to form the Mg-ATP complex during ATP binding, which is accompanied by the large conformational changes of LTag. This simulation study of the ATP binding process to an LTag and the accompanying conformational changes in the context of a hexamer leads to a refined cooperative iris model that has been proposed previously. PMID:19779548
Modelling of DNA-protein recognition
NASA Technical Reports Server (NTRS)
Rein, R.; Garduno, R.; Colombano, S.; Nir, S.; Haydock, K.; Macelroy, R. D.
1980-01-01
Computer model-building procedures using stereochemical principles together with theoretical energy calculations appear to be, at this stage, the most promising route toward the elucidation of DNA-protein binding schemes and recognition principles. A review of models and bonding principles is conducted and approaches to modeling are considered, taking into account possible di-hydrogen-bonding schemes between a peptide and a base (or a base pair) of a double-stranded nucleic acid in the major groove, aspects of computer graphic modeling, and a search for isogeometric helices. The energetics of recognition complexes is discussed and several models for peptide DNA recognition are presented.
Agarwal, Shivangi; Verma, Ekta; Kumar, Vivek; Lall, Namrita; Sau, Samaresh; Iyer, Arun K; Kashaw, Sushil K
2018-05-03
Tuberculosis is an infectious chronic disease caused by obligate pathogen Mycobacterium tuberculosis that affects millions of people worldwide. Although many first and second line drugs are available for its treatment, but their irrational use has adversely lead to the emerging cases of multiple drug resistant and extensively drug-resistant tuberculosis. Therefore, there is an intense need to develop novel potent analogues for its treatment. This has prompted us to develop potent analogues against TB. The Mycobacterium tuberculosis genome provides us with number of validated targets to combat against TB. Study of Mtb genome disclosed six epoxide hydrolases (A to F) which convert harmful epoxide into diols and act as a potential drug target for rational drug design. Our current strategy is to develop such analogues which inhibits epoxide hydrolase enzyme present in Mtb genome. To achieve this, we adopted an integrated computational approach involving QSAR, pharmacophore mapping, molecular docking and molecular dynamics simulation studies. The approach envisaged vital information about the role of molecular descriptors, essential pharmacophoric features and binding energy for compounds to bind into the active site of epoxide hydrolase. Molecular docking analysis revealed that analogues exhibited significant binding to Mtb epoxide hydrolase. Further, three docked complexes 2s, 37s and 15s with high, moderate and low docking scores respectively were selected for molecular dynamics simulation studies. RMSD analysis revealed that all complexes are stable with average RMSD below 2 Å throughout the 10 ns simulations. The B-factor analysis showed that the active site residues of epoxide hydrolase are flexible enough to interact with inhibitor. Moreover, to confirm the binding of these urea derivatives, MM-GBSA binding energy analysis were performed. The calculations showed that 37s has more binding affinity (ΔGtotal = -52.24 kcal/mol) towards epoxide hydrolase compared to 2s (ΔGtotal = -51.70 kcal/mol) and 15s (ΔGtotal = -49.97 kcal/mol). The structural features inferred in our study may provide the future directions to the scientists towards the discovery of new chemical entity exhibiting anti-TB property. Copyright © 2018 Elsevier Inc. All rights reserved.
Kaus, Joseph W; Harder, Edward; Lin, Teng; Abel, Robert; McCammon, J Andrew; Wang, Lingle
2015-06-09
Recent advances in improved force fields and sampling methods have made it possible for the accurate calculation of protein–ligand binding free energies. Alchemical free energy perturbation (FEP) using an explicit solvent model is one of the most rigorous methods to calculate relative binding free energies. However, for cases where there are high energy barriers separating the relevant conformations that are important for ligand binding, the calculated free energy may depend on the initial conformation used in the simulation due to the lack of complete sampling of all the important regions in phase space. This is particularly true for ligands with multiple possible binding modes separated by high energy barriers, making it difficult to sample all relevant binding modes even with modern enhanced sampling methods. In this paper, we apply a previously developed method that provides a corrected binding free energy for ligands with multiple binding modes by combining the free energy results from multiple alchemical FEP calculations starting from all enumerated poses, and the results are compared with Glide docking and MM-GBSA calculations. From these calculations, the dominant ligand binding mode can also be predicted. We apply this method to a series of ligands that bind to c-Jun N-terminal kinase-1 (JNK1) and obtain improved free energy results. The dominant ligand binding modes predicted by this method agree with the available crystallography, while both Glide docking and MM-GBSA calculations incorrectly predict the binding modes for some ligands. The method also helps separate the force field error from the ligand sampling error, such that deviations in the predicted binding free energy from the experimental values likely indicate possible inaccuracies in the force field. An error in the force field for a subset of the ligands studied was identified using this method, and improved free energy results were obtained by correcting the partial charges assigned to the ligands. This improved the root-mean-square error (RMSE) for the predicted binding free energy from 1.9 kcal/mol with the original partial charges to 1.3 kcal/mol with the corrected partial charges.
2016-01-01
Recent advances in improved force fields and sampling methods have made it possible for the accurate calculation of protein–ligand binding free energies. Alchemical free energy perturbation (FEP) using an explicit solvent model is one of the most rigorous methods to calculate relative binding free energies. However, for cases where there are high energy barriers separating the relevant conformations that are important for ligand binding, the calculated free energy may depend on the initial conformation used in the simulation due to the lack of complete sampling of all the important regions in phase space. This is particularly true for ligands with multiple possible binding modes separated by high energy barriers, making it difficult to sample all relevant binding modes even with modern enhanced sampling methods. In this paper, we apply a previously developed method that provides a corrected binding free energy for ligands with multiple binding modes by combining the free energy results from multiple alchemical FEP calculations starting from all enumerated poses, and the results are compared with Glide docking and MM-GBSA calculations. From these calculations, the dominant ligand binding mode can also be predicted. We apply this method to a series of ligands that bind to c-Jun N-terminal kinase-1 (JNK1) and obtain improved free energy results. The dominant ligand binding modes predicted by this method agree with the available crystallography, while both Glide docking and MM-GBSA calculations incorrectly predict the binding modes for some ligands. The method also helps separate the force field error from the ligand sampling error, such that deviations in the predicted binding free energy from the experimental values likely indicate possible inaccuracies in the force field. An error in the force field for a subset of the ligands studied was identified using this method, and improved free energy results were obtained by correcting the partial charges assigned to the ligands. This improved the root-mean-square error (RMSE) for the predicted binding free energy from 1.9 kcal/mol with the original partial charges to 1.3 kcal/mol with the corrected partial charges. PMID:26085821
Modeling of a Tröger’s tweezer and its complexation properties
NASA Astrophysics Data System (ADS)
Parchaňský, Václav; Matějka, Pavel; Dolenský, Bohumil; Havlík, Martin; Bouř, Petr
2009-09-01
Molecular tweezers attracted attention because of their potential to selectively bind important chemicals, which can be utilized in medicine or in pollution treatment. In this study, the aromatic binding properties of a recently synthesized tweezer based on the Tröger's base and its complex with nitrobenzene are investigated ab initio, using the DFT and MP2 computations. The predicted geometries and energies of the complex with nitrobenzene are well comparable with the experimental data. The B3LYP and BPW91 functionals did not provide a stable binding, in contrast to the observation. Only addition of the empirical Grimme correction for the van der Waals forces, not present in conventional DFT, yielded results consistent with the experiment, MP2 computations, and similar benchmark models. The correction also caused minor improvements of the Raman and infrared spectra, but not in the entire region of vibrational frequencies. The results suggest that the role of the electrostatic interaction in the investigated complex is minor and the interaction stabilization is driven by the contact area between the polarizable aromatic systems. The vdW-DFT method thus provides an efficient tool for the rational synthesis of the complexes.
Sampling and energy evaluation challenges in ligand binding protein design
Dou, Jiayi; Doyle, Lindsey; Jr. Greisen, Per; Schena, Alberto; Park, Hahnbeom; Johnsson, Kai; Stoddard, Barry L.
2017-01-01
Abstract The steroid hormone 17α‐hydroxylprogesterone (17‐OHP) is a biomarker for congenital adrenal hyperplasia and hence there is considerable interest in development of sensors for this compound. We used computational protein design to generate protein models with binding sites for 17‐OHP containing an extended, nonpolar, shape‐complementary binding pocket for the four‐ring core of the compound, and hydrogen bonding residues at the base of the pocket to interact with carbonyl and hydroxyl groups at the more polar end of the ligand. Eight of 16 designed proteins experimentally tested bind 17‐OHP with micromolar affinity. A co‐crystal structure of one of the designs revealed that 17‐OHP is rotated 180° around a pseudo‐two‐fold axis in the compound and displays multiple binding modes within the pocket, while still interacting with all of the designed residues in the engineered site. Subsequent rounds of mutagenesis and binding selection improved the ligand affinity to nanomolar range, while appearing to constrain the ligand to a single bound conformation that maintains the same “flipped” orientation relative to the original design. We trace the discrepancy in the design calculations to two sources: first, a failure to model subtle backbone changes which alter the distribution of sidechain rotameric states and second, an underestimation of the energetic cost of desolvating the carbonyl and hydroxyl groups of the ligand. The difference between design model and crystal structure thus arises from both sampling limitations and energy function inaccuracies that are exacerbated by the near two‐fold symmetry of the molecule. PMID:28980354
Sundar, Durai; Thorat, Sunil S.
2014-01-01
Swertia chirayita, a medicinal herb inhabiting the challenging terrains and high altitudes of the Himalayas, is a rich source of essential phytochemical isolates. Amarogentin, a bitter secoiridoid glycoside from S. chirayita, shows varied activity in several patho-physiological conditions, predominantly in leishmaniasis and carcinogenesis. Experimental analysis has revealed that amarogentin downregulates the cyclooxygenase-2 (COX-2) activity and helps to curtail skin carcinogenesis in mouse models; however, there exists no account on selective inhibition of the inducible cyclooxygenase (COX) isoform by amarogentin. Hence the computer-aided drug discovery methods were used to unravel the COX-2 inhibitory mechanism of amarogentin and to check its selectivity for the inducible isoform over the constitutive one. The generated theoretical models of both isoforms were subjected to molecular docking analysis with amarogentin and twenty-one other Food and Drug Authority (FDA) approved lead molecules. The post-docking binding energy profile of amarogentin was comparable to the binding energy profiles of the FDA approved selective COX-2 inhibitors. Subsequent molecular dynamics simulation analysis delineated the difference in the stability of both complexes, with amarogentin-COX-2 complex being more stable after 40ns simulation. The total binding free energy calculated by MMGBSA for the amarogentin-COX-2 complex was −52.35 KCal/mol against a binding free energy of −8.57 KCal/mol for amarogentin-COX-1 complex, suggesting a possible selective inhibition of the COX-2 protein by the natural inhibitor. Amarogentin achieves this potential selectivity by small, yet significant, structural differences inherent to the binding cavities of the two isoforms. Hypothetically, it might block the entry of the natural substrates in the hydrophobic binding channel of the COX-2, inhibiting the cyclooxygenation step. To sum up briefly, this work highlights the mechanism of the possible selective COX-2 inhibition by amarogentin and endorses the possibility of obtaining efficient, futuristic and targeted therapeutic agents for relieving inflammation and malignancy from this phytochemical source. PMID:24603686
Kobyłecka, Monika; Gu, Jiande; Rak, Janusz; Leszczynski, Jerzy
2008-01-28
The propensity of four representative conformations of 2(')-deoxyadenosine-5(')-monophosphate (5(')-dAMPH) to bind an excess electron has been studied at the B3LYP6-31++G(d,p) level. While isolated canonical adenine does not support stable valence anions in the gas phase, all considered neutral conformations of 5(')-dAMPH form adiabatically stable anions. The type of an anionic 5(')-dAMPH state, i.e., the valence, dipole bound, or mixed (valence/dipole bound), depends on the internal hydrogen bond(s) pattern exhibited by a particular tautomer. The most stable anion results from an electron attachment to the neutral syn-south conformer. The formation of this anion is associated with a barrier-free proton transfer triggered by electron attachment and the internal rotation around the C4(')-C5(') bond. The adiabatic electron affinity of the a_south-syn anion is 1.19 eV, while its vertical detachment energy is 1.89 eV. Our results are compared with the photoelectron spectrum (PES) of 5(')-dAMPH(-) measured recently by Stokes et al., [J. Chem. Phys. 128, 044314 (2008)]. The computational VDE obtained for the most stable anionic structure matches well with the experimental electron binding energy region of maximum intensity. A further understanding of DNA damage might require experimental and computational studies on the systems in which purine nucleotides are engaged in hydrogen bonding.
NASA Astrophysics Data System (ADS)
Kobyłecka, Monika; Gu, Jiande; Rak, Janusz; Leszczynski, Jerzy
2008-01-01
The propensity of four representative conformations of 2'-deoxyadenosine-5'-monophosphate (5'-dAMPH) to bind an excess electron has been studied at the B3LYP /6-31++G(d,p) level. While isolated canonical adenine does not support stable valence anions in the gas phase, all considered neutral conformations of 5'-dAMPH form adiabatically stable anions. The type of an anionic 5'-dAMPH state, i.e., the valence, dipole bound, or mixed (valence/dipole bound), depends on the internal hydrogen bond(s) pattern exhibited by a particular tautomer. The most stable anion results from an electron attachment to the neutral syn-south conformer. The formation of this anion is associated with a barrier-free proton transfer triggered by electron attachment and the internal rotation around the C4'-C5' bond. The adiabatic electron affinity of the a&barbelow;south-syn anion is 1.19eV, while its vertical detachment energy is 1.89eV. Our results are compared with the photoelectron spectrum (PES) of 5'-dAMPH- measured recently by Stokes et al., [J. Chem. Phys. 128, 044314 (2008)]. The computational VDE obtained for the most stable anionic structure matches well with the experimental electron binding energy region of maximum intensity. A further understanding of DNA damage might require experimental and computational studies on the systems in which purine nucleotides are engaged in hydrogen bonding.
Empirical optimization of DFT + U and HSE for the band structure of ZnO.
Bashyal, Keshab; Pyles, Christopher K; Afroosheh, Sajjad; Lamichhane, Aneer; Zayak, Alexey T
2018-02-14
ZnO is a well-known wide band gap semiconductor with promising potential for applications in optoelectronics, transparent electronics, and spintronics. Computational simulations based on the density functional theory (DFT) play an important role in the research of ZnO, but the standard functionals, like Perdew-Burke-Erzenhof, result in largely underestimated values of the band gap and the binding energies of the Zn 3d electrons. Methods like DFT + U and hybrid functionals are meant to remedy the weaknesses of plain DFT. However, both methods are not parameter-free. Direct comparison with experimental data is the best way to optimize the computational parameters. X-ray photoemission spectroscopy (XPS) is commonly considered as a benchmark for the computed electronic densities of states. In this work, both DFT + U and HSE methods were parametrized to fit almost exactly the binding energies of electrons in ZnO obtained by XPS. The optimized parameterizations of DFT + U and HSE lead to significantly worse results in reproducing the ion-clamped static dielectric tensor, compared to standard high-level calculations, including GW, which in turn yield a perfect match for the dielectric tensor. The failure of our XPS-based optimization reveals the fact that XPS does not report the ground state electronic structure for ZnO and should not be used for benchmarking ground state electronic structure calculations.
Empirical optimization of DFT + U and HSE for the band structure of ZnO
NASA Astrophysics Data System (ADS)
Bashyal, Keshab; Pyles, Christopher K.; Afroosheh, Sajjad; Lamichhane, Aneer; Zayak, Alexey T.
2018-02-01
ZnO is a well-known wide band gap semiconductor with promising potential for applications in optoelectronics, transparent electronics, and spintronics. Computational simulations based on the density functional theory (DFT) play an important role in the research of ZnO, but the standard functionals, like Perdew-Burke-Erzenhof, result in largely underestimated values of the band gap and the binding energies of the Zn3d electrons. Methods like DFT + U and hybrid functionals are meant to remedy the weaknesses of plain DFT. However, both methods are not parameter-free. Direct comparison with experimental data is the best way to optimize the computational parameters. X-ray photoemission spectroscopy (XPS) is commonly considered as a benchmark for the computed electronic densities of states. In this work, both DFT + U and HSE methods were parametrized to fit almost exactly the binding energies of electrons in ZnO obtained by XPS. The optimized parameterizations of DFT + U and HSE lead to significantly worse results in reproducing the ion-clamped static dielectric tensor, compared to standard high-level calculations, including GW, which in turn yield a perfect match for the dielectric tensor. The failure of our XPS-based optimization reveals the fact that XPS does not report the ground state electronic structure for ZnO and should not be used for benchmarking ground state electronic structure calculations.
Peptide docking of HIV-1 p24 with single chain fragment variable (scFv) by CDOCKER algorithm
NASA Astrophysics Data System (ADS)
Karim, Hana Atiqah Abdul; Tayapiwatana, Chatchai; Nimmanpipug, Piyarat; Zain, Sharifuddin M.; Rahman, Noorsaadah Abdul; Lee, Vannajan Sanghiran
2014-10-01
In search for the important residues that might have involve in the binding interaction between the p24 caspid protein of HIV-1 fragment (MET68 - PRO90) with the single chain fragment variable (scFv) of FAB23.5, modern computational chemistry approach has been conducted and applied. The p24 fragment was initially taken out from the 1AFV protein molecule consisting of both light (VL) and heavy (VH) chains of FAB23.5 as well as the HIV-1 caspid protein. From there, the p24 (antigen) fragment was made to dock back into the protein pocket receptor (antibody) by using the CDOCKER algorithm to conduct the molecular docking process. The score calculated from the CDOCKER gave 15 possible docked poses with various docked ligand's positions, the interaction energy as well as the binding energy. The best docked pose that imitates the original antigen's position was determined and further processed to the In Situ minimization to obtain the residues interaction energy as well as to observe the hydrogen bonds interaction in the protein-peptide complex. Based on the results demonstrated, the specific residues in the complex that have shown immense lower interaction energies in the 5Å vicinity region from the peptide are from the heavy chain (VH:TYR105) and light chain (VL: ASN31, TYR32, and GLU97). Those residues play vital roles in the binding mechanism of Antibody-Antigen (Ab-Ag) complex of p24 with FAB23.5.
Cheng, Cheng; Kamiya, Motoshi; Uchida, Yoshihiro; Hayashi, Shigehiko
2015-10-21
Color variants of human cellular retinol binding protein II (hCRBPII) created by protein engineering were recently shown to exhibit anomalously wide photoabsorption spectral shifts over ∼200 nm across the visible region. The remarkable phenomenon provides a unique opportunity to gain insight into the molecular basis of the color tuning of retinal binding proteins for understanding of color vision as well as for engineering of novel color variants of retinal binding photoreceptor proteins employed in optogenetics. Here, we report a theoretical investigation of the molecular mechanism underlying the anomalously wide spectral shifts of the color variants of hCRBPII. Computational modeling of the color variants with hybrid molecular simulations of free energy geometry optimization succeeded in reproducing the experimentally observed wide spectral shifts, and revealed that protein flexibility, through which the active site structure of the protein and bound water molecules is altered by remote mutations, plays a significant role in inducing the large spectral shifts.
Mahajanakatti, Arpitha Badarinath; Murthy, Geetha; Sharma, Narasimha; Skariyachan, Sinosh
2014-03-01
Various types of cancer accounts for 10% of total death worldwide which necessitates better therapeutic strategies. Curcumin, a curcuminoid present in Curcuma longa, shown to exhibit antioxidant, anti-inflammatory and anticarcinogenic properties. Present study, we aimed to analyze inhibitory properties of curcumin towards virulent proteins for various cancers by computer aided virtual screening. Based on literature studies, twenty two receptors were selected which have critical virulent functions in various cancer. The binding efficiencies of curcumin towards selected targets were studied by molecular docking. Out of all, curcumin showed best results towards epidermal growth factor (EGF), virulent protein of gastric cancer; glutathione-S-transferase Pi gene (GST-PI), virulent protein for prostate cancer; platelet-derived growth factor alpha (PDGFA), virulent protein for mesothelioma and glioma compared with their natural ligands. The calculated binding energies of their docked conformations with curcumin found to be -7.59 kcal/mol, -7.98 kcal/mol and -7.93 kcal/mol respectively. Further, a comparative study was performed to screen binding efficiency of curcumin with two conventional antitumor agents, litreol and triterpene. Docking studies revealed that calculated binding energies of docked complex of litreol and EGF, GST-PI and PDGFA were found to be -5.08 kcal/mol, -3.69 kcal/mol and -1.86 kcal/mol respectively. The calculated binding energies of triterpene with EGF and PDGFA were found to be -4.02 kcal/mol and -3.11 kcal/mol respectively, whereas GST-PI showed +6.07 kcal/mol, indicate poor binding. The predicted pharmacological features of curcumin found to be better than litreol and triterpene. Our study concluded that curcumin has better interacting properties towards these cancer targets than their normal ligands and conventional antitumor agents. Our data pave insight for designing of curcumin as novel inhibitors against various types of cancer.
NASA Astrophysics Data System (ADS)
Gresh, Nohad; Perrée-fauvet, Martine
1999-03-01
On the basis of theoretical computations, we have recently synthesised [Perrée-Fauvet, M. and Gresh, N., Tetrahedron Lett., 36 (1995) 4227] a bisarginyl conjugate of a tricationic porphyrin (BAP), designed to target, in the major groove of DNA, the d(GGC GCC)2 sequence which is part of the primary binding site of the HIV-1 retrovirus site [Wain-Hobson, S. et al., Cell, 40 (1985) 9]. In the theoretical model, the chromophore intercalates at the central d(CpG)2 step and each of the arginyl arms targets O6/N7belonging to guanine bases flanking the intercalation site. Recent IR and UV-visible spectroscopic studies have confirmed the essential features of these theoretical predictions [Mohammadi, S. et al., Biochemistry, 37 (1998) 6165]. In the present study, we compare the energies of competing intercalation modes of BAP to several double-stranded oligonucleotides, according to whether one, two or three N- methylpyridinium rings project into the major groove. Correspondingly, three minor groove binding modes were considered, the arginyl arms now targeting N3, O2 sites belonging to the purine or pyrimidine bases flanking the intercalation site. This investigation has shown that: (i) in both the major and minor grooves, the best-bound complexes have the three N-methylpyridinium rings in the groove opposite to that of the phenyl group bearing the arginyl arms; (ii) major groove binding is preferred over minor groove binding by a significant energy (29 kcal/mol); and (iii) the best-bound sequence in the major groove is d(GGC GCC)2 with two successive guanines upstream from the intercalation. On the other hand, due to the flexibility of the arginyl arms, other GC-rich sequences have close binding energies, two of them being less stable than it by less than 8 kcal/mol. These results serve as the basis for the design of derivatives of BAP with enhanced sequence selectivities in the major groove.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Beckham, G. T.; Payne, C. M.; Bu, L.
2012-01-01
The Trichoderma reesei Family 7 cellulase (Cel7A) is a key industrial enzyme in the production of biofuels from lignocellulosic biomass. It is a multi-modular enzyme with a Family 1 carbohydrate-binding module, a flexible O-glycosylated linker, and a large catalytic domain. We have used simulation to elucidate new functions for the 3 sub-domains, which suggests new routes to increase the activity of this central enzyme. These findings include new roles for glycosylation, which we have shown can be used to tune the binding affinity. We have also examined the structures of the catalytically-active complex of Cel7A and its non-processive counterpart, Cel7B,more » engaged on cellulose, which suggests allosteric mechanisms involved in chain binding when these cellulases are complexed on cellulose. Our computational results also suggest that product inhibition varies significantly between Cel7A and Cel7B, and we offer a molecular-level explanation for this observation. Finally, we discuss simulations of the absolute and relative binding free energy of cellulose ligands and various mutations along the CD tunnel, which will affect processivity and the ability of Cel7A (and related enzymes) to digest cellulose. These results highlight new considerations in protein engineering for processive and non-processive cellulases for production of lignocellulosic biofuels.« less
Saíz-Urra, Liane; Cabrera, Miguel Angel; Froeyen, Matheus
2011-02-01
Currently, bacterial diseases cause a death toll around 2 million people a year encouraging the search for new antimicrobial agents. DNA gyrase is a well-established antibacterial target consisting of two subunits, GyrA and GyrB, in a heterodimer A(2)B(2). GyrA is involved in DNA breakage and reunion and GyrB catalyzes the hydrolysis of ATP. The GyrB subunit from Escherichia coli has been investigated, namely the ATP binding pocket both considering the protein without ligands and bound with the inhibitors clorobiocin, novobiocin and 5'-adenylyl-β-γ-imidodiphosphate. The stability of the systems was studied by molecular dynamics simulation with the further analysis of the time dependent root-mean-square coordinate deviation (RMSD) from the initial structure, and temperature factors. Moreover, exploration of the conformational space of the systems during the MD simulation was carried out by a clustering data mining technique using the average-linkage algorithm. Recognizing the key residues in the binding site of the enzyme that are involved in the binding mode with the aforementioned inhibitors was investigated by using two techniques: free energy decomposition and computational alanine scanning. The results from these simulations highlight the important residues in the ATP binding site and can be useful in the design process of potential new inhibitors. Copyright © 2010 Elsevier Inc. All rights reserved.
Wu, Miao; Beckham, Gregg T.; Larsson, Anna M.; Ishida, Takuya; Kim, Seonah; Payne, Christina M.; Himmel, Michael E.; Crowley, Michael F.; Horn, Svein J.; Westereng, Bjørge; Igarashi, Kiyohiko; Samejima, Masahiro; Ståhlberg, Jerry; Eijsink, Vincent G. H.; Sandgren, Mats
2013-01-01
Carbohydrate structures are modified and degraded in the biosphere by a myriad of mostly hydrolytic enzymes. Recently, lytic polysaccharide mono-oxygenases (LPMOs) were discovered as a new class of enzymes for cleavage of recalcitrant polysaccharides that instead employ an oxidative mechanism. LPMOs employ copper as the catalytic metal and are dependent on oxygen and reducing agents for activity. LPMOs are found in many fungi and bacteria, but to date no basidiomycete LPMO has been structurally characterized. Here we present the three-dimensional crystal structure of the basidiomycete Phanerochaete chrysosporium GH61D LPMO, and, for the first time, measure the product distribution of LPMO action on a lignocellulosic substrate. The structure reveals a copper-bound active site common to LPMOs, a collection of aromatic and polar residues near the binding surface that may be responsible for regio-selectivity, and substantial differences in loop structures near the binding face compared with other LPMO structures. The activity assays indicate that this LPMO primarily produces aldonic acids. Last, molecular simulations reveal conformational changes, including the binding of several regions to the cellulose surface, leading to alignment of three tyrosine residues on the binding face of the enzyme with individual cellulose chains, similar to what has been observed for family 1 carbohydrate-binding modules. A calculated potential energy surface for surface translation indicates that P. chrysosporium GH61D exhibits energy wells whose spacing seems adapted to the spacing of cellobiose units along a cellulose chain. PMID:23525113
Quantum chemistry of the minimal CdSe clusters
NASA Astrophysics Data System (ADS)
Yang, Ping; Tretiak, Sergei; Masunov, Artëm E.; Ivanov, Sergei
2008-08-01
Colloidal quantum dots are semiconductor nanocrystals (NCs) which have stimulated a great deal of research and have attracted technical interest in recent years due to their chemical stability and the tunability of photophysical properties. While internal structure of large quantum dots is similar to bulk, their surface structure and passivating role of capping ligands (surfactants) are not fully understood to date. We apply ab initio wavefunction methods, density functional theory, and semiempirical approaches to study the passivation effects of substituted phosphine and amine ligands on the minimal cluster Cd2Se2, which is also used to benchmark different computational methods versus high level ab initio techniques. Full geometry optimization of Cd2Se2 at different theory levels and ligand coverage is used to understand the affinities of various ligands and the impact of ligands on cluster structure. Most possible bonding patterns between ligands and surface Cd/Se atoms are considered, including a ligand coordinated to Se atoms. The degree of passivation of Cd and Se atoms (one or two ligands attached to one atom) is also studied. The results suggest that B3LYP/LANL2DZ level of theory is appropriate for the system modeling, whereas frequently used semiempirical methods (such as AM1 and PM3) produce unphysical results. The use of hydrogen atom for modeling of the cluster passivating ligands is found to yield unphysical results as well. Hence, the surface termination of II-VI semiconductor NCs with hydrogen atoms often used in computational models should probably be avoided. Basis set superposition error, zero-point energy, and thermal corrections, as well as solvent effects simulated with polarized continuum model are found to produce minor variations on the ligand binding energies. The effects of Cd-Se complex structure on both the electronic band gap (highest occupied molecular orbital-lowest unoccupied molecular orbital energy difference) and ligand binding energies are systematically examined. The role played by positive charges on ligand binding is also explored. The calculated binding energies for various ligands L are found to decrease in the order OPMe3>OPH3>NH2Me>=NH3>=NMe3>PMe3>PH3 for neutral clusters and OPMe3>OPH3>PMe3>=NMe3>=NH2Me>=NH3>PH3 and OPMe3>OPH3>NH2Me>=NMe3>=PMe3>=NH3>PH3 for single and double ligations of positively charged Cd2Se22+ cluster, respectively.
Computational insight into small molecule inhibition of cyclophilins.
Sambasivarao, Somisetti V; Acevedo, Orlando
2011-02-28
Cyclophilins (Cyp) are a family of cellular enzymes possessing peptidyl-prolyl isomerase activity, which catalyze the cis-trans interconversion of proline-containing peptide bonds. The two most abundant family members, CypA and CypB, have been identified as valid drug targets for a wide range of diseases, including HCV, HIV, and multiple cancers. However, the development of small molecule inhibitors that possess nM potency and high specificity for a particular Cyp is difficult given the complete conservation of all active site residues between the enzymes. Monte Carlo statistical sampling coupled to free energy perturbation theory (MC/FEP) calculations have been carried out to elucidate the origin of the experimentally observed nM inhibition of CypA by acylurea-based derivatives and the >200-fold in vitro selectivity between CypA and CypB from aryl 1-indanylketone-based μM inhibitors. The computed free-energies of binding were in close accord with those derived from experiments. Binding affinity values for the inhibitors were determined to be dependent upon the stabilization strength of the nonbonded interactions provided toward two catalytic residues: Arg55 and Asn102 in CypA and the analogous Arg63 and Asn110 residues in CypB. Fine-tuning of the hydrophobic interactions allowed for enhanced potency among derivatives. The aryl 1-indanylketones are predicted to differentiate between the cyclophilins by using distinct binding motifs that exploit subtle differences in the active site arrangements. Ideas for the development of new selective compounds with the potential for advancement to low-nanomolar inhibition are presented.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sun, Jianwei; Remsing, Richard C.; Zhang, Yubo
2016-06-13
One atom or molecule binds to another through various types of bond, the strengths of which range from several meV to several eV. Although some computational methods can provide accurate descriptions of all bond types, those methods are not efficient enough for many studies (for example, large systems, ab initio molecular dynamics and high-throughput searches for functional materials). Here, we show that the recently developed non-empirical strongly constrained and appropriately normed (SCAN) meta-generalized gradient approximation (meta-GGA) within the density functional theory framework predicts accurate geometries and energies of diversely bonded molecules and materials (including covalent, metallic, ionic, hydrogen and vanmore » der Waals bonds). This represents a significant improvement at comparable efficiency over its predecessors, the GGAs that currently dominate materials computation. Often, SCAN matches or improves on the accuracy of a computationally expensive hybrid functional, at almost-GGA cost. SCAN is therefore expected to have a broad impact on chemistry and materials science.« less
Sun, Jianwei; Remsing, Richard C; Zhang, Yubo; Sun, Zhaoru; Ruzsinszky, Adrienn; Peng, Haowei; Yang, Zenghui; Paul, Arpita; Waghmare, Umesh; Wu, Xifan; Klein, Michael L; Perdew, John P
2016-09-01
One atom or molecule binds to another through various types of bond, the strengths of which range from several meV to several eV. Although some computational methods can provide accurate descriptions of all bond types, those methods are not efficient enough for many studies (for example, large systems, ab initio molecular dynamics and high-throughput searches for functional materials). Here, we show that the recently developed non-empirical strongly constrained and appropriately normed (SCAN) meta-generalized gradient approximation (meta-GGA) within the density functional theory framework predicts accurate geometries and energies of diversely bonded molecules and materials (including covalent, metallic, ionic, hydrogen and van der Waals bonds). This represents a significant improvement at comparable efficiency over its predecessors, the GGAs that currently dominate materials computation. Often, SCAN matches or improves on the accuracy of a computationally expensive hybrid functional, at almost-GGA cost. SCAN is therefore expected to have a broad impact on chemistry and materials science.
Tertiary structure-based analysis of microRNA–target interactions
Gan, Hin Hark; Gunsalus, Kristin C.
2013-01-01
Current computational analysis of microRNA interactions is based largely on primary and secondary structure analysis. Computationally efficient tertiary structure-based methods are needed to enable more realistic modeling of the molecular interactions underlying miRNA-mediated translational repression. We incorporate algorithms for predicting duplex RNA structures, ionic strength effects, duplex entropy and free energy, and docking of duplex–Argonaute protein complexes into a pipeline to model and predict miRNA–target duplex binding energies. To ensure modeling accuracy and computational efficiency, we use an all-atom description of RNA and a continuum description of ionic interactions using the Poisson–Boltzmann equation. Our method predicts the conformations of two constructs of Caenorhabditis elegans let-7 miRNA–target duplexes to an accuracy of ∼3.8 Å root mean square distance of their NMR structures. We also show that the computed duplex formation enthalpies, entropies, and free energies for eight miRNA–target duplexes agree with titration calorimetry data. Analysis of duplex–Argonaute docking shows that structural distortions arising from single-base-pair mismatches in the seed region influence the activity of the complex by destabilizing both duplex hybridization and its association with Argonaute. Collectively, these results demonstrate that tertiary structure-based modeling of miRNA interactions can reveal structural mechanisms not accessible with current secondary structure-based methods. PMID:23417009
Kroeger Smith, M. B.; Rouzer, C. A.; Taneyhill, L. A.; Smith, N. A.; Hughes, S. H.; Boyer, P. L.; Janssen, P. A.; Moereels, H.; Koymans, L.; Arnold, E.
1995-01-01
Computer modeling studies have been carried out on three nonnucleoside inhibitors complexed with human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT), using crystal coordinate data from a subset of the protein surrounding the binding pocket region. Results from the minimizations of solvated complexes of 2-cyclopropyl-4-methyl-5,11-dihydro-5H-dipyrido[3,2-b :2',3'-e][1,4] diazepin-6-one (nevirapine), alpha-anilino-2, 6-dibromophenylacetamide (alpha-APA), and 8-chloro-tetrahydro-imidazo(4,5,1-jk)(1,4)-benzodiazepin-2(1H)-thi one (TIBO) show that all three inhibitors maintain a very similar conformational shape, roughly overlay each other in the binding pocket, and appear to function as pi-electron donors to aromatic side-chain residues surrounding the pocket. However, side-chain residues adapt to each bound inhibitor in a highly specific manner, closing down around the surface of the drug to make tight van der Waals contacts. Consequently, the results from the calculated minimizations reveal that only when the inhibitors are modeled in a site constructed from coordinate data obtained from their particular RT complex can the calculated binding energies be relied upon to predict the correct orientation of the drug in the pocket. In the correct site, these binding energies correlate with EC50 values determined for all three inhibitors in our laboratory. Analysis of the components of the binding energy reveals that, for all three inhibitors, solvation of the drug is endothermic, but solvation of the protein is exothermic, and the sum favors complex formation. In general, the protein is energetically more stable and the drug less stable in their complexes as compared to the reactant conformations. For all three inhibitors, interaction with the protein in the complex is highly favorable. Interactions of the inhibitors with individual residues correlate with crystallographic and site-specific mutational data. pi-Stacking interactions are important in binding and correlate with drug HOMO RHF/6-31G* energies. Modeling results are discussed with respect to the mechanism of complex formation and the design of nonnucleoside inhibitors that will be more effective against mutants of HIV-1 RT that are resistant to the currently available drugs. PMID:8535257
Xu, Fengqi; Tanaka, Shigenori; Watanabe, Hirofumi; Shimane, Yasuhiro; Iwasawa, Misako; Ohishi, Kazue; Maruyama, Tadashi
2018-05-03
Measles virus (MV) causes an acute and highly devastating contagious disease in humans. Employing the crystal structures of three human receptors, signaling lymphocyte-activation molecule (SLAM), CD46, and Nectin-4, in complex with the measles virus hemagglutinin (MVH), we elucidated computationally the details of binding energies between the amino acid residues of MVH and those of the receptors with an ab initio fragment molecular orbital (FMO) method. The calculated inter-fragment interaction energies (IFIEs) revealed a number of significantly interacting amino acid residues of MVH that played essential roles in binding to the receptors. As predicted from previously reported experiments, some important amino-acid residues of MVH were shown to be common but others were specific to interactions with the three receptors. Particularly, some of the (non-polar) hydrophobic residues of MVH were found to be attractively interacting with multiple receptors, thus indicating the importance of the hydrophobic pocket for intermolecular interactions (especially in the case of Nectin-4). In contrast, the electrostatic interactions tended to be used for specific molecular recognition. Furthermore, we carried out FMO calculations for in silico experiments of amino acid mutations, finding reasonable agreements with virological experiments concerning the substitution effect of residues. Thus, the present study demonstrates that the electron-correlated FMO method is a powerful tool to search exhaustively for amino acid residues that contribute to interactions with receptor molecules. It is also applicable for designing inhibitors of MVH and engineered MVs for cancer therapy.
Computational Analysis of Gynura bicolor Bioactive Compounds as Dipeptidyl Peptidase-IV Inhibitor
Abdullah Zawawi, Muhammad Redha; Ahmad, Muhamad Aizuddin; Jaganath, Indu Bala
2017-01-01
The inhibition of dipeptidyl peptidase-IV (DPPIV) is a popular route for the treatment of type-2 diabetes. Commercially available gliptin-based drugs such as sitagliptin, anagliptin, linagliptin, saxagliptin, and alogliptin were specifically developed as DPPIV inhibitors for diabetic patients. The use of Gynura bicolor in treating diabetes had been reported in various in vitro experiments. However, an understanding of the inhibitory actions of G. bicolor bioactive compounds on DPPIV is still lacking and this may provide crucial information for the development of more potent and natural sources of DPPIV inhibitors. Evaluation of G. bicolor bioactive compounds for potent DPPIV inhibitors was computationally conducted using Lead IT and iGEMDOCK software, and the best free-binding energy scores for G. bicolor bioactive compounds were evaluated in comparison with the commercial DPPIV inhibitors, sitagliptin, anagliptin, linagliptin, saxagliptin, and alogliptin. Drug-likeness and absorption, distribution, metabolism, and excretion (ADME) analysis were also performed. Based on molecular docking analysis, four of the identified bioactive compounds in G. bicolor, 3-caffeoylquinic acid, 5-O-caffeoylquinic acid, 3,4-dicaffeoylquinic acid, and trans-5-p-coumaroylquinic acid, resulted in lower free-binding energy scores when compared with two of the commercially available gliptin inhibitors. The results revealed that bioactive compounds in G. bicolor are potential natural inhibitors of DPPIV. PMID:28932239
Nuclear structure of bound states of asymmetric dark matter
NASA Astrophysics Data System (ADS)
Gresham, Moira I.; Lou, Hou Keong; Zurek, Kathryn M.
2017-11-01
Models of asymmetric dark matter (ADM) with a sufficiently attractive and long-range force give rise to stable bound objects, analogous to nuclei in the Standard Model, called nuggets. We study the properties of these nuggets and compute their profiles and binding energies. Our approach, applicable to both elementary and composite fermionic ADM, utilizes relativistic mean field theory, and allows a more systematic computation of nugget properties, over a wider range of sizes and force mediator masses, compared to previous literature. We identify three separate regimes of nugget property behavior corresponding to (1) nonrelativistic and (2) relativistic constituents in a Coulomb-like limit, and (3) saturation in an anti-Coulomb limit when the nuggets are large compared to the force range. We provide analytical descriptions for nuggets in each regime. Through numerical calculations, we are able to confirm our analytic descriptions and also obtain smooth transitions for the nugget profiles between all three regimes. We also find that over a wide range of parameter space, the binding energy in the saturation limit is an O (1 ) fraction of the constituent's mass, significantly larger than expectations in the nonrelativistic case. In a companion paper, we apply our results to the synthesis of ADM nuggets in the early Universe.
Camacho, Carlos J
2005-08-01
The CAPRI-II experiment added an extra level of complexity to the problem of predicting protein-protein interactions by including 5 targets for which participants had to build or complete the 3-dimensional (3D) structure of either the receptor or ligand based on the structure of a close homolog. In this article, we describe how modeling key side-chains using molecular dynamics (MD) in explicit solvent improved the recognition of the binding region of a free energy- based computational docking method. In particular, we show that MD is able to predict with relatively high accuracy the rotamer conformation of the anchor side-chains important for molecular recognition as suggested by Rajamani et al. (Proc Natl Acad Sci USA 2004;101:11287-11292). As expected, the conformations are some of the most common rotamers for the given residue, while latch side-chains that undergo induced fit upon binding are forced into less common conformations. Using these models as starting conformations in conjunction with the rigid-body docking server ClusPro and the flexible docking algorithm SmoothDock, we produced valuable predictions for 6 of the 9 targets in CAPRI-II, missing only the 3 targets that underwent significant structural rearrangements upon binding. We also show that our free energy- based scoring function, consisting of the sum of van der Waals, Coulombic electrostatic with a distance-dependent dielectric, and desolvation free energy successfully discriminates the nativelike conformation of our submitted predictions. The latter emphasizes the critical role that thermodynamics plays on our methodology, and validates the generality of the algorithm to predict protein interactions.
Protein pharmacophore selection using hydration-site analysis
Hu, Bingjie; Lill, Markus A.
2012-01-01
Virtual screening using pharmacophore models is an efficient method to identify potential lead compounds for target proteins. Pharmacophore models based on protein structures are advantageous because a priori knowledge of active ligands is not required and the models are not biased by the chemical space of previously identified actives. However, in order to capture most potential interactions between all potentially binding ligands and the protein, the size of the pharmacophore model, i.e. number of pharmacophore elements, is typically quite large and therefore reduces the efficiency of pharmacophore based screening. We have developed a new method to select important pharmacophore elements using hydration-site information. The basic premise is that ligand functional groups that replace water molecules in the apo protein contribute strongly to the overall binding affinity of the ligand, due to the additional free energy gained from releasing the water molecule into the bulk solvent. We computed the free energy of water released from the binding site for each hydration site using thermodynamic analysis of molecular dynamics (MD) simulations. Pharmacophores which are co-localized with hydration sites with estimated favorable contributions to the free energy of binding are selected to generate a reduced pharmacophore model. We constructed reduced pharmacophore models for three protein systems and demonstrated good enrichment quality combined with high efficiency. The reduction in pharmacophore model size reduces the required screening time by a factor of 200–500 compared to using all protein pharmacophore elements. We also describe a training process using a small set of known actives to reliably select the optimal set of criteria for pharmacophore selection for each protein system. PMID:22397751
A Mixed QM/MM Scoring Function to Predict Protein-Ligand Binding Affinity
Hayik, Seth A.; Dunbrack, Roland; Merz, Kenneth M.
2010-01-01
Computational methods for predicting protein-ligand binding free energy continue to be popular as a potential cost-cutting method in the drug discovery process. However, accurate predictions are often difficult to make as estimates must be made for certain electronic and entropic terms in conventional force field based scoring functions. Mixed quantum mechanics/molecular mechanics (QM/MM) methods allow electronic effects for a small region of the protein to be calculated, treating the remaining atoms as a fixed charge background for the active site. Such a semi-empirical QM/MM scoring function has been implemented in AMBER using DivCon and tested on a set of 23 metalloprotein-ligand complexes, where QM/MM methods provide a particular advantage in the modeling of the metal ion. The binding affinity of this set of proteins can be calculated with an R2 of 0.64 and a standard deviation of 1.88 kcal/mol without fitting and 0.71 and a standard deviation of 1.69 kcal/mol with fitted weighting of the individual scoring terms. In this study we explore using various methods to calculate terms in the binding free energy equation, including entropy estimates and minimization standards. From these studies we found that using the rotational bond estimate to ligand entropy results in a reasonable R2 of 0.63 without fitting. We also found that using the ESCF energy of the proteins without minimization resulted in an R2 of 0.57, when using the rotatable bond entropy estimate. PMID:21221417
Extended Fenske-Hall LCAO MO calculations of core-level shifts in solid P compounds
NASA Astrophysics Data System (ADS)
Franke, R.; Chassé, T.; Reinhold, J.; Streubel, P.; Szargan, R.
1997-08-01
Extended Fenske-Hall LCAO-MO ΔSCF calculations on solids modelled as H-pseudoatom saturated clusters are reported. The computational results verify the experimentally obtained initial-state (effective atomic charges, Madelung potential) and relaxation-energy contributions to the XPS phosphorus core-level binding energy shifts measured in Na 3PO 3S, Na 3PO 4, Na 2PO 3F and NH 4PF 6 in reference to red phosphorus. It is shown that the different initial-state contributions observed in the studied phosphates are determined by local and nonlocal terms while the relaxation-energy contributions are mainly dependent on the nature of the nearest neighbors of the phosphorus atom.
Kubli-Garfias, Carlos; Vázquez-Ramírez, Ricardo; Trejo-Muñoz, Cynthia; Berber, Arturo
2017-01-01
Imidazoquinolines are powerful immunostimulants (IMMS) that function through Toll-like receptors, particularly TLR7 and TLR8. In addition to enhancing the immune response, IMMS also function as antineoplastic drugs and vaccine adjuvants. These small compounds display almost the same molecular structure, except in some cases in which atom in position 1 varies and changes the imidazole characteristics. A variable acyclic side chain is also always attached at atom in position 2, while another chain may be attached at atom in position 1. These structural differences alter immune responses, such as the production of interferon regulatory factor and nuclear factor-κB (IRF-NFκB). In this work, quantum mechanics theory and computational chemistry methods were applied to study the physicochemical properties of the crystal binding site of TLR8 complexed with the following six IMMS molecules: Hybrid-2, XG1-236, DS802, CL075, CL097 and R848 (resiquimod). The PDB IDs of the crystals were: 4R6A, 4QC0, 4QBZ, 3W3K, 3W3J, and 3W3N respectively. Thus, were calculated, the total energy, solvation energy, interaction energy (instead of free energy) of the system and interaction energy of the polar region of the IMMS. Additionally, the dipole moment, electrostatic potential, polar surface, atomic charges, hydrogen bonds, and polar and hydrophobic interactions, among others, were assessed. Together, these properties revealed important differences among the six TLR8-immunostimulant complexes, reflected as different interaction energies and therefore different electrostatic environments and binding energies. Remarkably, the interaction energy of a defined polar region composed of the highly polarized N3, N5 atoms and the N11 amino group, acted as a polar pharmacophore that correlates directly with the reported immunopharmacological potency of the six complexed molecules. Based on these results, it was concluded that accurate physicochemical analysis of the crystal binding site could reveal the binding energy (measured as interaction energy) and associated molecular mechanism of action between IMMS and TLR8. These findings may facilitate the development and design of improved small molecules with IMMS properties that are targeted to the TLR system and have enhanced pharmacological effectiveness and reduced toxicity.
Kubli-Garfias, Carlos; Vázquez-Ramírez, Ricardo; Trejo-Muñoz, Cynthia; Berber, Arturo
2017-01-01
Imidazoquinolines are powerful immunostimulants (IMMS) that function through Toll-like receptors, particularly TLR7 and TLR8. In addition to enhancing the immune response, IMMS also function as antineoplastic drugs and vaccine adjuvants. These small compounds display almost the same molecular structure, except in some cases in which atom in position 1 varies and changes the imidazole characteristics. A variable acyclic side chain is also always attached at atom in position 2, while another chain may be attached at atom in position 1. These structural differences alter immune responses, such as the production of interferon regulatory factor and nuclear factor-κB (IRF-NFκB). In this work, quantum mechanics theory and computational chemistry methods were applied to study the physicochemical properties of the crystal binding site of TLR8 complexed with the following six IMMS molecules: Hybrid-2, XG1-236, DS802, CL075, CL097 and R848 (resiquimod). The PDB IDs of the crystals were: 4R6A, 4QC0, 4QBZ, 3W3K, 3W3J, and 3W3N respectively. Thus, were calculated, the total energy, solvation energy, interaction energy (instead of free energy) of the system and interaction energy of the polar region of the IMMS. Additionally, the dipole moment, electrostatic potential, polar surface, atomic charges, hydrogen bonds, and polar and hydrophobic interactions, among others, were assessed. Together, these properties revealed important differences among the six TLR8-immunostimulant complexes, reflected as different interaction energies and therefore different electrostatic environments and binding energies. Remarkably, the interaction energy of a defined polar region composed of the highly polarized N3, N5 atoms and the N11 amino group, acted as a polar pharmacophore that correlates directly with the reported immunopharmacological potency of the six complexed molecules. Based on these results, it was concluded that accurate physicochemical analysis of the crystal binding site could reveal the binding energy (measured as interaction energy) and associated molecular mechanism of action between IMMS and TLR8. These findings may facilitate the development and design of improved small molecules with IMMS properties that are targeted to the TLR system and have enhanced pharmacological effectiveness and reduced toxicity. PMID:28582454
Plazinska, Anita; Plazinski, Wojciech
2017-05-02
The β 2 -adrenergic receptor (β 2 -AR) is one of the most studied G-protein-coupled receptors. When interacting with ligand molecules, it exhibits a binding characteristic that is strongly dependent on ligand stereoconfiguration. In particular, many experimental and theoretical studies confirmed that stereoisomers of an important β 2 -AR agonist, fenoterol, are associated with diverse mechanisms of binding and activation of β 2 -AR. The objective of the present study was to explore the stereoselective binding of fenoterol to β 2 -AR through the application of an advanced computational methodology based on enhanced-sampling molecular dynamics simulations and potentials of interactions tailored to investigate the stereorecognition effects. The results remain in very good, quantitative agreement with the experimental data (measured in the context of ligand-receptor affinities and their dependence on the temperature), which provides an additional validation for the applied computational protocols. Additionally, our results contribute to the understanding of stereoselective agonist binding by β 2 -AR. Although the significant role of the N293 6.55 residue is confirmed, we additionally show that stereorecognition does not depend solely on the N293-ligand interactions; the stereoselective effects rely on the co-operation of several residues located on both the 6th and 7th transmembrane domains and on extracellular loops. The magnitude and character of the contributions of these residues may be very diverse and result in either enhancing or reducing the stereoselective effects. The same is true when considering the enthalpic and entropic contributions to the binding free energies, which also are dependent on the ligand stereoconfiguration.
OSPREY Predicts Resistance Mutations Using Positive and Negative Computational Protein Design.
Ojewole, Adegoke; Lowegard, Anna; Gainza, Pablo; Reeve, Stephanie M; Georgiev, Ivelin; Anderson, Amy C; Donald, Bruce R
2017-01-01
Drug resistance in protein targets is an increasingly common phenomenon that reduces the efficacy of both existing and new antibiotics. However, knowledge of future resistance mutations during pre-clinical phases of drug development would enable the design of novel antibiotics that are robust against not only known resistant mutants, but also against those that have not yet been clinically observed. Computational structure-based protein design (CSPD) is a transformative field that enables the prediction of protein sequences with desired biochemical properties such as binding affinity and specificity to a target. The use of CSPD to predict previously unseen resistance mutations represents one of the frontiers of computational protein design. In a recent study (Reeve et al. Proc Natl Acad Sci U S A 112(3):749-754, 2015), we used our OSPREY (Open Source Protein REdesign for You) suite of CSPD algorithms to prospectively predict resistance mutations that arise in the active site of the dihydrofolate reductase enzyme from methicillin-resistant Staphylococcus aureus (SaDHFR) in response to selective pressure from an experimental competitive inhibitor. We demonstrated that our top predicted candidates are indeed viable resistant mutants. Since that study, we have significantly enhanced the capabilities of OSPREY with not only improved modeling of backbone flexibility, but also efficient multi-state design, fast sparse approximations, partitioned continuous rotamers for more accurate energy bounds, and a computationally efficient representation of molecular-mechanics and quantum-mechanical energy functions. Here, using SaDHFR as an example, we present a protocol for resistance prediction using the latest version of OSPREY. Specifically, we show how to use a combination of positive and negative design to predict active site escape mutations that maintain the enzyme's catalytic function but selectively ablate binding of an inhibitor.