Improved Peptide and Protein Torsional Energetics with the OPLSAA Force Field

Significantly Improved Protein Folding Thermodynamics Using a Dispersion-Corrected Water Model and a New Residue-Specific Force Field

An accurate potential energy model is crucial for biomolecular simulations. Despite many recent improvements of classical protein force fields, there are remaining key issues: much weaker temperature dependence of folding/unfolding equilibrium and overly collapsed unfolded or disordered states. For the latter problem, a new water model (TIP4P-D) has been proposed to correct the significantly underestimated water dispersion interactions. Here, using TIP4P-D, we reveal problems in current force fields through failures in folding model systems (a polyalanine peptide, Trp-cage, and the GB1 hairpin). By using residue-specific parameters to achieve better match between amino acid sequences and native structures and adding a small H-bond correction to partially compensate the missing many-body effects in α-helix formation, the new RSFF2+ force field with the TIP4P-D water model can excellently reproduce experimental melting curves of both α-helical and β-hairpin systems. The RSFF2+/TIP4P-D method also gives less collapsed unfolded structures and describes well folded proteins simultaneously.

Advancing Drug Discovery through Enhanced Free Energy Calculations

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.

Improved Description of Sulfur Charge Anisotropy in OPLS Force Fields: Model Development and Parameterization

The atomic point-charge model used in most molecular mechanics force fields does not represent well the electronic anisotropy that is featured in many directional noncovalent interactions. Sulfur participates in several types of such interactions with its lone pairs and σ-holes. The current study develops a new model, via the addition of off-atom charged sites, for a variety of sulfur compounds in the OPLS-AA and OPLS/CM5 force fields to address the lack of charge anisotropy. Parameter optimization is carried out to reproduce liquid-state properties, torsional and noncovalent energetics from reliable quantum mechanical calculations, and electrostatic potentials. Significant improvements are obtained for computed free energies of hydration, reducing the mean unsigned errors from ca. 1.4 to 0.4-0.7 kcal/mol. Enhanced accuracy in directionality and energetics is also obtained for molecular complexes with sulfur-containing hydrogen and halogen bonds. Moreover, the new model reproduces the unusual conformational preferences of sulfur-containing compounds with 1,4-intramolecular chalcogen bonds. Transferability of the new force field parameters to cysteine and methionine is verified via molecular dynamic simulations of blocked dipeptides. The study demonstrates the effectiveness of using off-atom charge sites to address electronic anisotropy, and provides a parametrization methodology that can be applied to other systems.

The GPR139 reference agonists 1a and 7c, and tryptophan and phenylalanine share a common binding site

GPR139 is an orphan G protein-coupled receptor expressed in the brain, in particular in the habenula, hypothalamus and striatum. It has therefore been suggested that GPR139 is a possible target for metabolic disorders and Parkinson's disease. Several surrogate agonist series have been published for GPR139. Two series published by Shi et al. and Dvorak et al. included agonists 1a and 7c respectively, with potencies in the ten-nanomolar range. Furthermore, Isberg et al. and Liu et al. have previously shown that tryptophan (Trp) and phenylalanine (Phe) can activate GPR139 in the hundred-micromolar range. In this study, we produced a mutagenesis-guided model of the GPR139 binding site to form a foundation for future structure-based ligand optimization. Receptor mutants studied in a Ca2+ assay demonstrated that residues F1093×33, H1875×43, W2416×48 and N2717×38, but not E1083×32, are highly important for the activation of GPR139 as predicted by the receptor model. The initial ligand-receptor complex was optimized through free energy perturbation simulations, generating a refined GPR139 model in agreement with experimental data. In summary, the GPR139 reference surrogate agonists 1a and 7c, and the endogenous amino acids L-Trp and L-Phe share a common binding site, as demonstrated by mutagenesis, ligand docking and free energy calculations.

Polarizable Force Field for DNA Based on the Classical Drude Oscillator: I. Refinement Using Quantum Mechanical Base Stacking and Conformational Energetics

Empirical force fields seek to relate the configuration of a set of atoms to its energy, thus yielding the forces governing its dynamics, using classical physics rather than more expensive quantum mechanical calculations that are computationally intractable for large systems. Most force fields used to simulate biomolecular systems use fixed atomic partial charges, neglecting the influence of electronic polarization, instead making use of a mean-field approximation that may not be transferable across environments. Recent hardware and software developments make polarizable simulations feasible, and to this end, polarizable force fields represent the next generation of molecular dynamics simulation technology. In this work, we describe the refinement of a polarizable force field for DNA based on the classical Drude oscillator model by targeting quantum mechanical interaction energies and conformational energy profiles of model compounds necessary to build a complete DNA force field. The parametrization strategy employed in the present work seeks to correct weak base stacking in A- and B-DNA and the unwinding of Z-DNA observed in the previous version of the force field, called Drude-2013. Refinement of base nonbonded terms and reparametrization of dihedral terms in the glycosidic linkage, deoxyribofuranose rings, and important backbone torsions resulted in improved agreement with quantum mechanical potential energy surfaces. Notably, we expand on previous efforts by explicitly including Z-DNA conformational energetics in the refinement.

Modern Technologies of Solution Nuclear Magnetic Resonance Spectroscopy for Three-dimensional Structure Determination of Proteins Open Avenues for Life Scientists

Nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for structural studies of chemical compounds and biomolecules such as DNA and proteins. Since the NMR signal sensitively reflects the chemical environment and the dynamics of a nuclear spin, NMR experiments provide a wealth of structural and dynamic information about the molecule of interest at atomic resolution. In general, structural biology studies using NMR spectroscopy still require a reasonable understanding of the theory behind the technique and experience on how to recorded NMR data. Owing to the remarkable progress in the past decade, we can easily access suitable and popular analytical resources for NMR structure determination of proteins with high accuracy. Here, we describe the practical aspects, workflow and key points of modern NMR techniques used for solution structure determination of proteins. This review should aid NMR specialists aiming to develop new methods that accelerate the structure determination process, and open avenues for non-specialist and life scientists interested in using NMR spectroscopy to solve protein structures.

Experimental conformational energy maps of proteins and peptides

We have presented an extensive analysis of the peptide backbone dihedral angles in the PDB structures and computed experimental Ramachandran plots for their distributions seen under a various constraints on X-ray resolution, representativeness at different sequence identity percentages, and hydrogen bonding distances. These experimental distributions have been converted into isoenergy contour plots using the approach employed previously by F. M. Pohl. This has led to the identification of energetically favored minima in the Ramachandran (ϕ, ψ) plots in which global minima are predominantly observed either in the right-handed α-helical or the polyproline II regions. Further, we have identified low energy pathways for transitions between various minima in the (ϕ,ψ) plots. We have compared and presented the experimental plots with published theoretical plots obtained from both molecular mechanics and quantum mechanical approaches. In addition, we have developed and employed a root mean square deviation (RMSD) metric for isoenergy contours in various ranges, as a measure (in kcal.mol^-1 ) to compare any two plots and determine the extent of correlation and similarity between their isoenergy contours. In general, we observe a greater degree of compatibility with experimental plots for energy maps obtained from molecular mechanics methods compared to most quantum mechanical methods. The experimental energy plots we have investigated could be helpful in refining protein structures obtained from X-ray, NMR, and electron microscopy and in refining force field parameters to enable simulations of peptide and protein structures that have higher degree of consistency with experiments. Proteins 2017; 85:979-1001. © 2017 Wiley Periodicals, Inc.

Electronic absorption spectra of pyridine and nicotine in aqueous solution with a combined molecular dynamics and polarizable QM/MM approach

The electronic absorption spectra of pyridine and nicotine in aqueous solution have been computed using a multistep approach. The computational protocol consists in studying the solute solvation with accurate molecular dynamics simulations, characterizing the hydrogen bond interactions, and calculating electronic transitions for a series of configurations extracted from the molecular dynamics trajectories with a polarizable QM/MM scheme based on the fluctuating charge model. Molecular dynamics simulations and electronic transition calculations have been performed on both pyridine and nicotine. Furthermore, the contributions of solute vibrational effect on electronic absorption spectra have been taken into account in the so called vertical gradient approximation. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Improved Treatment of Nucleosides and Nucleotides in the OPLS-AA Force Field

DFT calculations have been used to develop improved descriptions of the torsional energetics for nucleosides and nucleotides in the OPLS-AA force field. Scans of nucleotide dihedral angles (γ, χ, and β) and methyl phosphates provided the bases for the new torsional parameters. In addition, the angle-bending parameters of phosphodiesters and ribose were updated, and adjustments were made to existing carbohydrate torsions to better capture the sugar puckering landscape of ribose. MD simulations of nucleosides with the new parameters demonstrate a significant improvement in the ribose sugar puckering and χ angle distributions. Additionally, energy-minimization of protein-nucleotide crystal structures with the new parameters produced accurate poses.

Metal Ion Modeling Using Classical Mechanics

Metal ions play significant roles in numerous fields including chemistry, geochemistry, biochemistry, and materials science. With computational tools increasingly becoming important in chemical research, methods have emerged to effectively face the challenge of modeling metal ions in the gas, aqueous, and solid phases. Herein, we review both quantum and classical modeling strategies for metal ion-containing systems that have been developed over the past few decades. This Review focuses on classical metal ion modeling based on unpolarized models (including the nonbonded, bonded, cationic dummy atom, and combined models), polarizable models (e.g., the fluctuating charge, Drude oscillator, and the induced dipole models), the angular overlap model, and valence bond-based models. Quantum mechanical studies of metal ion-containing systems at the semiempirical, ab initio, and density functional levels of theory are reviewed as well with a particular focus on how these methods inform classical modeling efforts. Finally, conclusions and future prospects and directions are offered that will further enhance the classical modeling of metal ion-containing systems.

Nonpolar Solvation Free Energy from Proximal Distribution Functions

Using precomputed near neighbor or proximal distribution functions (pDFs) that approximate solvent density about atoms in a chemically bonded context one can estimate the solvation structures around complex solutes and the corresponding solute-solvent energetics. In this contribution, we extend this technique to calculate the solvation free energies (ΔG) of a variety of solutes. In particular we use pDFs computed for small peptide molecules to estimate ΔG for larger peptide systems. We separately compute the non polar (ΔG_vdW) and electrostatic (ΔG_elec) components of the underlying potential model. Here we show how the former can be estimated by thermodynamic integration using pDF-reconstructed solute-solvent interaction energy. The electrostatic component can be approximated with Linear Response theory as half of the electrostatic solute-solvent interaction energy. We test the method by calculating the solvation free energies of butane, propanol, polyalanine, and polyglycine and by comparing with traditional free energy simulations. Results indicate that the pDF-reconstruction algorithm approximately reproduces ΔG_vdW calculated by benchmark free energy simulations to within ∼ kcal/mol accuracy. The use of transferable pDFs for each solute atom allows for a rapid estimation of ΔG for arbitrary molecular systems.

Complete sampling of an enzyme reaction pathway: a lesson from gas phase simulations

With proper sampling strategy, convergence of free energy profiles of biomolecular reactions in the gas phase can be achieved in microseconds of simulation.

Evaluation of solvation free energies for small molecules with the AMOEBA polarizable force field

The effects of electronic polarization in biomolecular interactions will differ depending on the local dielectric constant of the environment, such as in solvent, DNA, proteins, and membranes. Here the performance of the AMOEBA polarizable force field is evaluated under nonaqueous conditions by calculating the solvation free energies of small molecules in four common organic solvents. Results are compared with experimental data and equivalent simulations performed with the GAFF pairwise-additive force field. Although AMOEBA results give mean errors close to "chemical accuracy," GAFF performs surprisingly well, with statistically significantly more accurate results than AMOEBA in some solvents. However, for both models, free energies calculated in chloroform show worst agreement to experiment and individual solutes are consistently poor performers, suggesting non-potential-specific errors also contribute to inaccuracy. Scope for the improvement of both potentials remains limited by the lack of high quality experimental data across multiple solvents, particularly those of high dielectric constant. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Simulations of disordered proteins and systems with conformational heterogeneity

Intrinsically disordered proteins (IDPs) and protein regions can facilitate a wide variety of complex physiological processes such as binding, signaling, and formation of membraneless organelles. They can however also play pathological roles by aggregating into cytotoxic oligomers and fibrils. Characterizing the structure and function of disordered proteins is an onerous task, primarily because these proteins adopt transient structures, which are difficult to capture in experiments. Simulations have emerged as a powerful tool for interpreting and augmenting experimental measurements of IDPs. In this review we focus on computer simulations of disordered protein structures, functions, assemblies, and emerging questions that, taken together, give an overview of the field as it exists today.

Elucidating Mechanisms of Molecular Recognition Between Human Argonaute and miRNA Using Computational Approaches

MicroRNA (miRNA) and Argonaute (AGO) protein together form the RNA-induced silencing complex (RISC) that plays an essential role in the regulation of gene expression. Elucidating the underlying mechanism of AGO-miRNA recognition is thus of great importance not only for the in-depth understanding of miRNA function but also for inspiring new drugs targeting miRNAs. In this chapter we introduce a combined computational approach of molecular dynamics (MD) simulations, Markov state models (MSMs), and protein-RNA docking to investigate AGO-miRNA recognition. Constructed from MD simulations, MSMs can elucidate the conformational dynamics of AGO at biologically relevant timescales. Protein-RNA docking can then efficiently identify the AGO conformations that are geometrically accessible to miRNA. Using our recent work on human AGO2 as an example, we explain the rationale and the workflow of our method in details. This combined approach holds great promise to complement experiments in unraveling the mechanisms of molecular recognition between large, flexible, and complex biomolecules.

Insights from the predicted structural analysis of carborane substituted withaferin A with Indoleamine - 2,3-dioxygenase as a potent inhibitor

Indoleamine-2,3-dioxygenase (IDO) an immunoregulatory enzyme and emerging as a new therapeutic drug target for the treatment of cancer. Carboranes, an icosahedral arrangement of eleven boron atoms plus one carbon atom with unique pharmacological properties such low toxicity, isosterism with phenyl ring and stability to hydrolysis. On the other hand, carboranes are known to increase the interaction of ligand with non-polar region of the protein provides an excellent platform to explore these carboranes towards designing and development of novel, potent and target specific drug candidates with further enhanced binding affinities. Despite of their many potential applications, molecular modeling studies of carborane-substituted ligands with macromolecules have been rarely reported. Previously, we have demonstrated the promising high binding affinity of Withaferin-A (WA) for IDO. In this present study, we investigated the effect of carborane substitutions on WA compound towards developing novel analogs for target specific IDO inhibition with better potency. Interesting docked poses and molecular interactions for the carborane substituted WA ligands were elucidated. Based on our In-silico studies, carborane substituted at various position of WA has shown enhanced binding affinity towards IDO, worth of considering for further studies.

Elucidating a chemical defense mechanism of Antarctic sponges: A computational study

In 2000, a novel secondary metabolite (erebusinone, Ereb) was isolated from the Antarctic sea sponge, Isodictya erinacea. The bioactivity of Ereb was investigated, and it was found to inhibit molting when fed to the arthropod species Orchomene plebs. Xanthurenic acid (XA) is a known endogenous molt regulator present in arthropods. Experimental studies have confirmed that XA inhibits molting by binding to either (or both) of two P450 enzymes (CYP315a1 or CYP314a1) that are responsible for the final two hydroxylations in the production of the molt-inducing hormone, 20-hydroxyecdysone (20E). The lack of crystal structures and biochemical assays for CYP315a1 or CYP314a1, has prevented further experimental exploration of XA and Ereb's molt inhibition mechanisms. Herein, a wide array of computational techniques - homology modeling, molecular dynamics simulations, binding site bioinformatics, flexible receptor-flexible ligand docking, and molecular mechanics-generalized Born surface area calculations - have been employed to elucidate the structure-function relationships between the aforementioned P450s and the two described small molecule inhibitors (Ereb and XA). Results indicate that Ereb likely targets CYP315a1 by interacting with a network of aromatic residues in the binding site, while XA may inhibit both CYP315a1 and CYP314a1 because of its aromatic, as well as charged nature.

Calculating binding free energies of host-guest systems using the AMOEBA polarizable force field

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.

Multiscale implementation of infinite-swap replica exchange molecular dynamics

Replica exchange molecular dynamics (REMD) is a popular method to accelerate conformational sampling of complex molecular systems. The idea is to run several replicas of the system in parallel at different temperatures that are swapped periodically. These swaps are typically attempted every few MD steps and accepted or rejected according to a Metropolis-Hastings criterion. This guarantees that the joint distribution of the composite system of replicas is the normalized sum of the symmetrized product of the canonical distributions of these replicas at the different temperatures. Here we propose a different implementation of REMD in which (i) the swaps obey a continuous-time Markov jump process implemented via Gillespie's stochastic simulation algorithm (SSA), which also samples exactly the aforementioned joint distribution and has the advantage of being rejection free, and (ii) this REMD-SSA is combined with the heterogeneous multiscale method to accelerate the rate of the swaps and reach the so-called infinite-swap limit that is known to optimize sampling efficiency. The method is easy to implement and can be trivially parallelized. Here we illustrate its accuracy and efficiency on the examples of alanine dipeptide in vacuum and C-terminal β-hairpin of protein G in explicit solvent. In this latter example, our results indicate that the landscape of the protein is a triple funnel with two folded structures and one misfolded structure that are stabilized by H-bonds.

FF12MC: A revised AMBER forcefield and new protein simulation protocol

Specialized to simulate proteins in molecular dynamics (MD) simulations with explicit solvation, FF12MC is a combination of a new protein simulation protocol employing uniformly reduced atomic masses by tenfold and a revised AMBER forcefield FF99 with (i) shortened CH bonds, (ii) removal of torsions involving a nonperipheral sp(3) atom, and (iii) reduced 1-4 interaction scaling factors of torsions ϕ and ψ. This article reports that in multiple, distinct, independent, unrestricted, unbiased, isobaric-isothermal, and classical MD simulations FF12MC can (i) simulate the experimentally observed flipping between left- and right-handed configurations for C14-C38 of BPTI in solution, (ii) autonomously fold chignolin, CLN025, and Trp-cage with folding times that agree with the experimental values, (iii) simulate subsequent unfolding and refolding of these miniproteins, and (iv) achieve a robust Z score of 1.33 for refining protein models TMR01, TMR04, and TMR07. By comparison, the latest general-purpose AMBER forcefield FF14SB locks the C14-C38 bond to the right-handed configuration in solution under the same protein simulation conditions. Statistical survival analysis shows that FF12MC folds chignolin and CLN025 in isobaric-isothermal MD simulations 2-4 times faster than FF14SB under the same protein simulation conditions. These results suggest that FF12MC may be used for protein simulations to study kinetics and thermodynamics of miniprotein folding as well as protein structure and dynamics. Proteins 2016; 84:1490-1516. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

The cellular membrane as a mediator for small molecule interaction with membrane proteins

The cellular membrane constitutes the first element that encounters a wide variety of molecular species to which a cell might be exposed. Hosting a large number of structurally and functionally diverse proteins associated with this key metabolic compartment, the membrane not only directly controls the traffic of various molecules in and out of the cell, it also participates in such diverse and important processes as signal transduction and chemical processing of incoming molecular species. In this article, we present a number of cases where details of interaction of small molecular species such as drugs with the membrane, which are often experimentally inaccessible, have been studied using advanced molecular simulation techniques. We have selected systems in which partitioning of the small molecule with the membrane constitutes a key step for its final biological function, often binding to and interacting with a protein associated with the membrane. These examples demonstrate that membrane partitioning is not only important for the overall distribution of drugs and other small molecules into different compartments of the body, it may also play a key role in determining the efficiency and the mode of interaction of the drug with its target protein. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg.

Promiscuous antibodies characterised by their physico-chemical properties: From sequence to structure and back

Human B cells produce antibodies, which bind to their cognate antigen based on distinct molecular properties of the antibody CDR loop. We have analysed a set of 10 antibodies showing a clear difference in their binding properties to a panel of antigens, resulting in two subsets of antibodies with a distinct binding phenotype. We call the observed binding multiplicity ‘promiscuous’ and selected physico-chemical CDRH3 characteristics and conformational preferences may characterise these promiscuous antibodies. To classify CDRH3 physico-chemical properties playing a role in their binding properties, we used statistical analyses of the sequences annotated by Kidera factors. To characterise structure-function requirements for antigen binding multiplicity we employed Molecular Modelling and Monte Carlo based coarse-grained simulations. The ability to predict the molecular causes of promiscuous, multi-binding behaviour would greatly improve the efficiency of the therapeutic antibody discovery process.

Computational methods to design cyclic peptides

Cyclic peptides (CPs) are promising modulators of protein-protein interactions (PPIs), but their application remains challenging. It is currently difficult to predict the structures and bioavailability of CPs. The ability to design CPs using computer modeling would greatly facilitate the development of CPs as potent PPI modulators for fundamental studies and as potential therapeutics. Herein, we describe computational methods to generate CP libraries for virtual screening, as well as current efforts to accurately predict the conformations adopted by CPs. These advances are making it possible to envision robust computational design of active CPs. However, unique properties of CPs pose significant challenges associated with sampling CP conformational space and accurately describing CP energetics. These major obstacles to structure prediction likely must be solved before robust design of active CPs can be reliably achieved.

Performance of Protein-Ligand Force Fields for the Flavodoxin-Flavin Mononucleotide System

The ability to accurately perform molecular dynamics and free energy perturbation calculations for protein-ligand systems is of broad interest to the biophysical and pharmaceutical sciences. In this work, several popular force fields are evaluated for reproducing experimental properties of the flavodoxin/flavin mononucleotide system. Calculated (3)J couplings from molecular dynamics simulations probing φ and χ1 dihedral angles are compared to over 1000 experimental measurements. Free energy perturbation calculations were also executed between different protein mutants for comparison with experimental data for relative free energies of binding. Newer versions of popular protein force fields reproduced (3)J backbone and side chain couplings with good accuracy, with RMSD values near or below one hertz in most cases. OPLS-AA/M paired with CM5 charges for the ligand performed particularly well, both for the (3)J couplings and FEP results, with a mean unsigned error for relative free energies of binding of 0.36 kcal/mol.

General van der Waals potential for common organic molecules

This work presents a systematic development of a new van der Waals potential (vdW2016) for common organic molecules based on symmetry-adapted perturbation theory (SAPT) energy decomposition. The Buf-14-7 function, as well as Cubic-mean and Waldman-Hagler mixing rules were chosen given their best performance among other popular potentials. A database containing 39 organic molecules and 108 dimers was utilized to derive a general set of vdW parameters, which were further validated on nucleobase stacking systems and testing organic dimers. The vdW2016 potential is anticipated to significantly improve the accuracy and transferability of new generations of force fields for organic molecules.

Further along the Road Less Traveled: AMBER ff15ipq, an Original Protein Force Field Built on a Self-Consistent Physical Model

We present the AMBER ff15ipq force field for proteins, the second-generation force field developed using the Implicitly Polarized Q (IPolQ) scheme for deriving implicitly polarized atomic charges in the presence of explicit solvent. The ff15ipq force field is a complete rederivation including more than 300 unique atomic charges, 900 unique torsion terms, 60 new angle parameters, and new atomic radii for polar hydrogens. The atomic charges were derived in the context of the SPC/E_b water model, which yields more-accurate rotational diffusion of proteins and enables direct calculation of nuclear magnetic resonance (NMR) relaxation parameters from molecular dynamics simulations. The atomic radii improve the accuracy of modeling salt bridge interactions relative to contemporary fixed-charge force fields, rectifying a limitation of ff14ipq that resulted from its use of pair-specific Lennard-Jones radii. In addition, ff15ipq reproduces penta-alanine J-coupling constants exceptionally well, gives reasonable agreement with NMR relaxation rates, and maintains the expected conformational propensities of structured proteins/peptides, as well as disordered peptides—all on the microsecond (μs) time scale, which is a critical regime for drug design applications. These encouraging results demonstrate the power and robustness of our automated methods for deriving new force fields. All parameters described here and the mdgx program used to fit them are included in the AmberTools16 distribution.

Assessment of refinement of template-based models in CASP11

CASP11 (the 11th Meeting on the Critical Assessment of Protein Structure Prediction) ran a blind experiment in the refinement of protein structure predictions, the fourth such experiment since CASP8. As with the previous experiments, the predictors were provided with one starting structure from the server models of each of a selected set of template-based modeling targets and asked to refine the coordinates of the starting structure toward native. We assessed the refined structures with the Z-scores of the standard CASP measures, which compare the model-target similarities of the models from all the predictors. Furthermore, we assessed the refined structures with "relative measures," which compare the improvement in accuracy of each model with respect to the starting structure. The latter provides an assessment of the extent to which each predictor group is able to improve the starting structures toward native. We utilized heat maps to display improvements in the Calpha-Calpha distance matrix for each model. The heat maps labeled with each element of secondary structure helped us to identify regions of refinement toward native in each model. Most positively scoring models show modest improvements in multiple regions of the structure, while in some models we were able to identify significant repositioning of N/C-terminal segments and internal elements of secondary structure. The best groups were able to improve more than 70% of the targets from the starting models, and by an average of 3-5% in the standard CASP measures. Proteins 2016; 84(Suppl 1):260-281. © 2016 Wiley Periodicals, Inc.

Insights into enzyme point mutation effect by molecular simulation: phenylethylamine oxidation catalyzed by monoamine oxidase A

The I335Y point mutation effect on the kinetics of phenylethylamine decomposition catalyzed by monoamine oxidase A was elucidated by means of molecular simulation. The established empirical valence bond methodology was used in conjunction with the free energy perturbation sampling technique and a classical force field representing the state of reactants and products. The methodology allows for the simulation of chemical reactions, in the present case the breaking of the α-C-H bond in a phenylethylamine substrate and the subsequent hydrogen transfer to the flavin cofactor, resulting in the formation of the N-H bond on flavin. The empirical parameters were calibrated against the experimental data for the simulated reaction in a wild type protein and then used for the calculation of the reaction free energy profile in the I335Y mutant. In very good agreement with the measured kinetic data, mutation increases the free energy barrier for the rate limiting step by slightly more than 1 kcal mol(-1) and consequently decreases the rate constant by about an order of magnitude. The magnitude of the computed effect slightly varies with simulation settings, but always remains in reasonable agreement with the experiment. Analysis of trajectories reveals a major change in the interaction between phenyl rings of the substrate and the neighboring Phe352 residue upon the I335Y mutation due to the increased local polarity, leading to an attenuated quadrupole interaction between the rings and destabilization of the transition state. Additionally, the increased local polarity in the mutant allows for a larger number of water molecules to be present near the active site, effectively shielding the catalytic effect of the enzyme and contributing to the increased barrier.

Biomolecular Force Field Parameterization via Atoms-in-Molecule Electron Density Partitioning

Molecular mechanics force fields, which are commonly used in biomolecular modeling and computer-aided drug design, typically treat nonbonded interactions using a limited library of empirical parameters that are developed for small molecules. This approach does not account for polarization in larger molecules or proteins, and the parametrization process is labor-intensive. Using linear-scaling density functional theory and atoms-in-molecule electron density partitioning, environment-specific charges and Lennard-Jones parameters are derived directly from quantum mechanical calculations for use in biomolecular modeling of organic and biomolecular systems. The proposed methods significantly reduce the number of empirical parameters needed to construct molecular mechanics force fields, naturally include polarization effects in charge and Lennard-Jones parameters, and scale well to systems comprised of thousands of atoms, including proteins. The feasibility and benefits of this approach are demonstrated by computing free energies of hydration, properties of pure liquids, and the relative binding free energies of indole and benzofuran to the L99A mutant of T4 lysozyme.

Data including GROMACS input files for atomistic molecular dynamics simulations of mixed, asymmetric bilayers including molecular topologies, equilibrated structures, and force field for lipids compatible with OPLS-AA parameters

In this Data in Brief article we provide a data package of GROMACS input files for atomistic molecular dynamics simulations of multicomponent, asymmetric lipid bilayers using the OPLS-AA force field. These data include 14 model bilayers composed of 8 different lipid molecules. The lipids present in these models are: cholesterol (CHOL), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine (POPC), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylethanolamine (POPE), 1-stearoyl-2-oleoyl-sn-glycero-3-phosphatidyl-ethanolamine (SOPE), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylserine (POPS), 1-stearoyl-2-oleoyl-sn-glycero-3-phosphatidylserine (SOPS), N-palmitoyl-D-erythro-sphingosyl-phosphatidylcholine (SM16), and N-lignoceroyl-D-erythro-sphingosyl-phosphatidylcholine (SM24). The bilayers׳ compositions are based on lipidomic studies of PC-3 prostate cancer cells and exosomes discussed in Llorente et al. (2013) [1], showing an increase in the section of long-tail lipid species (SOPS, SOPE, and SM24) in the exosomes. Former knowledge about lipid asymmetry in cell membranes was accounted for in the models, meaning that the model of the inner leaflet is composed of a mixture of PC, PS, PE, and cholesterol, while the extracellular leaflet is composed of SM, PC and cholesterol discussed in Van Meer et al. (2008) [2]. The provided data include lipids׳ topologies, equilibrated structures of asymmetric bilayers, all force field parameters, and input files with parameters describing simulation conditions (md.mdp). The data is associated with the research article “Interdigitation of Long-Chain Sphingomyelin Induces Coupling of Membrane Leaflets in a Cholesterol Dependent Manner” (Róg et al., 2016) [3].

Development of a True Transition State Force Field from Quantum Mechanical Calculations

Transition state force fields (TSFF) treated the TS structure as an artificial minimum on the potential energy surface in the past decades. The necessary parameters were developed either manually or by the Quantum-to-molecular mechanics method (Q2MM). In contrast with these approaches, here we propose to model the TS structures as genuine saddle points at the molecular mechanics level. Different methods were tested on small model systems of general chemical reactions such as protonation, nucleophilic attack, and substitution, and the new procedure led to more accurate models than the Q2MM-type parametrization. To demonstrate the practicality of our approach, transferrable parameters have been developed for Mo-catalyzed olefin metathesis using quantum mechanical properties as reference data. Based on the proposed strategy, any force field can be extended with true transition state force field (TTSFF) parameters, and they can be readily applied in several molecular mechanics programs as well.

Efficient preparation and analysis of membrane and membrane protein systems

Molecular dynamics (MD) simulations have become a highly important technique to consider lipid membrane systems, and quite often they provide considerable added value to laboratory experiments. Rapid development of both software and hardware has enabled the increase of time and size scales reachable by MD simulations to match those attainable by several accurate experimental techniques. However, until recently, the quality and maturity of software tools available for building membrane models for simulations as well as analyzing the results of these simulations have seriously lagged behind. Here, we discuss the recent developments of such tools from the end-users' point of view. In particular, we review the software that can be employed to build lipid bilayers and other related structures with or without embedded membrane proteins to be employed in MD simulations. Additionally, we provide a brief critical insight into force fields and MD packages commonly used for membrane and membrane protein simulations. Finally, we list analysis tools that can be used to study the properties of membrane and membrane protein systems. In all these points we comment on the respective compatibility of the covered tools. We also share our opinion on the current state of the available software. We briefly discuss the most commonly employed tools and platforms on which new software can be built. We conclude the review by providing a few ideas and guidelines on how the development of tools can be further boosted to catch up with the rapid pace at which the field of membrane simulation progresses. This includes improving the compatibility between software tools and promoting the openness of the codes on which these applications rely. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg.

The S66x8 benchmark for noncovalent interactions revisited: explicitly correlated ab initio methods and density functional theory

The S66x8 dataset for noncovalent interactions of biochemical relevance has been re-examined by means of CCSD(F12*)(T), DFT, and SAPT methods.

Molecular Dynamics Assisted Mechanistic Study of Isoniazid-Resistance against Mycobacterium tuberculosis InhA

Examination of InhA mutants I16T, I21V, I47T, S94A, and I95P showed that direct and water mediated H-bond interactions between NADH and binding site residues reduced drastically. It allowed conformational flexibility to NADH, particularly at the pyrophosphate region, leading to weakening of its binding at dinucleotide binding site. The highly scattered distribution of pyrophosphate dihedral angles and chi1 side chain dihedral angles of corresponding active site residues therein confirmed weak bonding between InhA and NADH. The average direct and water mediated bridged H-bond interactions between NADH and mutants were observed weaker as compared to wild type. Further, estimated NADH binding free energy in mutants supported the observed weakening of InhA-NADH interactions. Similarly, per residue contribution to NADH binding was also found little less as compared to corresponding residues in wild type. This investigation clearly depicted and supported the effect of mutations on NADH binding and can be accounted for isoniazid resistance as suggested by previous biochemical and mutagenic studies. Further, structural analysis of InhA provided the crucial points to enhance the NADH binding affinity towards InhA mutants in the presence of direct InhA inhibitors to combat isoniazid drug resistance. This combination could be a potential alternative for treatment of drug resistant tuberculosis.

OPLS3: A Force Field Providing Broad Coverage of Drug-like Small Molecules and Proteins

The parametrization and validation of the OPLS3 force field for small molecules and proteins are reported. Enhancements with respect to the previous version (OPLS2.1) include the addition of off-atom charge sites to represent halogen bonding and aryl nitrogen lone pairs as well as a complete refit of peptide dihedral parameters to better model the native structure of proteins. To adequately cover medicinal chemical space, OPLS3 employs over an order of magnitude more reference data and associated parameter types relative to other commonly used small molecule force fields (e.g., MMFF and OPLS_2005). As a consequence, OPLS3 achieves a high level of accuracy across performance benchmarks that assess small molecule conformational propensities and solvation. The newly fitted peptide dihedrals lead to significant improvements in the representation of secondary structure elements in simulated peptides and native structure stability over a number of proteins. Together, the improvements made to both the small molecule and protein force field lead to a high level of accuracy in predicting protein-ligand binding measured over a wide range of targets and ligands (less than 1 kcal/mol RMS error) representing a 30% improvement over earlier variants of the OPLS force field.

Hierarchical atom type definitions and extensible all-atom force fields

The extensibility of force field is a key to solve the missing parameter problem commonly found in force field applications. The extensibility of conventional force fields is traditionally managed in the parameterization procedure, which becomes impractical as the coverage of the force field increases above a threshold. A hierarchical atom-type definition (HAD) scheme is proposed to make extensible atom type definitions, which ensures that the force field developed based on the definitions are extensible. To demonstrate how HAD works and to prepare a foundation for future developments, two general force fields based on AMBER and DFF functional forms are parameterized for common organic molecules. The force field parameters are derived from the same set of quantum mechanical data and experimental liquid data using an automated parameterization tool, and validated by calculating molecular and liquid properties. The hydration free energies are calculated successfully by introducing a polarization scaling factor to the dispersion term between the solvent and solute molecules. © 2015 Wiley Periodicals, Inc.

Topologies, structures and parameter files for lipid simulations in GROMACS with the OPLS-aa force field: DPPC, POPC, DOPC, PEPC, and cholesterol

In this data article we provide topologies and force field parameters files for molecular dynamics simulations of lipids in the OPLS-aa force field using the GROMACS package. This is the first systematic parameterization of lipid molecules in this force field. Topologies are provided for four phosphatidylcholines: saturated DPPC, mono-cis unsaturated POPC and DOPC, and mono-trans unsaturated PEPC. Parameterization of the phosphatidylcholines was achieved in two steps: first, we supplemented the OPLS force field parameters for DPPC with new parameters for torsion angles and van der Waals parameters for the carbon and hydrogen atoms in the acyl chains, as well as new partial atomic charges and parameters for torsion angles in the phosphatidylcholine and glycerol moieties [1]. Next, we derived parameters for the cis and trans double bonds and the neighboring them single bonds [2]. Additionally, we provide GROMACS input files with parameters describing simulation conditions (md.mdp), which are strongly recommended to be used with these lipids models. The data are associated with the research article “Cis and trans unsaturated phosphatidylcholine bilayers: a molecular dynamics simulation study” [2] and provided as supporting materials.