Biomembrane simulations of 12 lipid types using the general amber force field in a tensionless ensemble

The AMBER family of force fields is one of the most commonly used alternatives to describe proteins and drug-like molecules in molecular dynamics simulations. However, the absence of a specific set of parameters for lipids has been limiting the widespread application of this force field in biomembrane simulations, including membrane protein simulations and drug-membrane simulations. Here, we report the systematic parameterization of 12 common lipid types consistent with the General Amber Force Field (GAFF), with charge-parameters determined with RESP at the HF/6–31G(d) level of theory, to be consistent with AMBER. The accuracy of the scheme was evaluated by comparing predicted and experimental values for structural lipid properties in MD simulations in an NPT ensemble with explicit solvent in 100:100 bilayer systems. Globally, a consistent agreement with experimental reference data on membrane structures was achieved for some lipid types when using the typical MD conditions normally employed when handling membrane proteins and drug-membrane simulations (a tensionless NPT ensemble, 310?K), without the application of any of the constraints often used in other biomembrane simulations (such as the surface tension and the total simulation box area). The present set of parameters and the universal approach used in the parameterization of all the lipid types described here, as well as the consistency with the AMBER force field family, together with the tensionless NPT ensemble used, opens the door to systematic studies combining lipid components with small drug-like molecules or membrane proteins and show the potential of GAFF in dealing with biomembranes.     

Automated force field optimisation of small molecules using a gradient-based workflow package

In this study, the recently developed gradient-based optimisation workflow for the automated development of molecular models is for the first time applied to the parameterisation of force fields for molecular dynamics simulations. As a proof-of-concept, two small molecules (benzene and phosgene) are considered. In order to optimise the underlying intermolecular force field (described by the (12,6)-Lennard-Jones and the Coulomb potential), the energetic and diameter parameters ε and σ are fitted to experimental physical properties by gradient-based numerical optimisation techniques. Thereby, a quadratic loss function between experimental and simulated target properties is minimised with respect to the force field parameters. In this proof-of-concept, the considered physical target properties are chosen to be diverse: density, enthalpy of vapourisation and self-diffusion coefficient are optimised simultaneously at different temperatures. We found that in both cases, the optimisation could be successfully concluded by fulfillment of a pre-defined stopping criterion. Since a fairly small number of iterations were needed to do so, this study will serve as a good starting point for more complex systems and further improvements of the parametrisation task.     

An online parameter and property database for the TraPPE force field

The transferable potentials for phase equilibria (TraPPE) force field aims to be accurate, computationally efficient and applicable to a wide range of chemical compounds, state points and thermophysical properties. When new users wish to implement TraPPE models into their chosen simulation program, they face several obstacles: the TraPPE models are dispersed over many separate publications and misinterpretations of the primary literature are possible; the TraPPE force field makes specific choices for standard conventions that may require non-trivial code modifications for some simulation software. Therefore, the TraPPE developers report here a resource website and online searchable parameter and property database designed to provide new and experienced users with tools for successful implementation and validation (http://www.chem.umn.edu/groups/siepmann/trappe/).     

Validation of molecular force field parameters for peptides including isomerized amino acids

Recently, stereoinversions and isomerizations of amino acid residues in the proteins of living beings have been observed. Because isomerized amino acids cause structural changes and denaturation of proteins, isomerizations of amino acid residues are suspected to cause age‐related diseases. In this study, AMBER molecular force field parameters were tested by using computationally generated nonapeptides and tripeptides including stereoinverted and/or isomerized amino acid residues. Energy calculations by using density functional theory were also performed for comparison. Although the force field parameters were developed by parameter fitting for l ‐α‐amino acids, the accuracy of the computational results for d ‐amino acids and β‐amino acids was comparable to those for l ‐α‐amino acids. The conformational energies for tripeptides calculated by using density functional theory were reproduced more accurately than those for nonapeptides calculated by using the molecular mechanical force field. The evaluations were performed for the ff99SB, ff03, ff12SB, and the latest ff14SB force field parameters.     

Improved side‐chain torsion potentials for the Amber ff99SB protein force field

Recent advances in hardware and software have enabled increasingly long molecular dynamics (MD) simulations of biomolecules, exposing certain limitations in the accuracy of the force fields used for such simulations and spurring efforts to refine these force fields. Recent modifications to the Amber and CHARMM protein force fields, for example, have improved the backbone torsion potentials, remedying deficiencies in earlier versions. Here, we further advance simulation accuracy by improving the amino acid side‐chain torsion potentials of the Amber ff99SB force field. First, we used simulations of model alpha‐helical systems to identify the four residue types whose rotamer distribution differed the most from expectations based on Protein Data Bank statistics. Second, we optimized the side‐chain torsion potentials of these residues to match new, high‐level quantum‐mechanical calculations. Finally, we used microsecond‐timescale MD simulations in explicit solvent to validate the resulting force field against a large set of experimental NMR measurements that directly probe side‐chain conformations. The new force field, which we have termed Amber ff99SB‐ILDN, exhibits considerably better agreement with the NMR data. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

On the ability of molecular dynamics force fields to recapitulate NMR derived protein side chain order parameters

Molecular dynamics (MD) simulations have become a central tool for investigating various biophysical questions with atomistic detail. While many different proxies are used to qualify MD force fields, most are based on largely structural parameters such as the root mean square deviation from experimental coordinates or nuclear magnetic resonance (NMR) chemical shifts and residual dipolar couplings. NMR derived Lipari–Szabo squared generalized order parameter (O²) values of amide N? H bond vectors of the polypeptide chain were also often employed for refinement and validation. However, with a few exceptions, side chain methyl symmetry axis order parameters have not been incorporated into experimental reference sets. Using a test set of five diverse proteins, the performance of several force fields implemented in the NAMDD simulation package was examined. It was found that simulations employing explicit water implemented using the TIP3 model generally performed significantly better than those using implicit water in reproducing experimental methyl symmetry axis O² values. Overall the CHARMM27 force field performs nominally better than two implementations of the Amber force field. It appeared that recent quantum mechanics modifications to side chain torsional angles of leucine and isoleucine in the Amber force field have significantly hindered proper motional modeling for these residues. There remained significant room for improvement as even the best correlations of experimental and simulated methyl group Lipari–Szabo generalized order parameters fall below an R² of 0.8.     

Molecular dynamics simulation of hydrated Nafion with a reactive force field for water

We apply a newly parameterized central force field to highlight the problem of proton transport in fuel cell membranes and show that central force fields are potential candidates to describe chemical reactions on a classical level. After a short sketch of the parameterization of the force field, we validate the obtained force field for several properties of water. The experimental and simulated radial distribution functions are reproduced very accurately as a consequence of the applied parameterization procedure. Further properties, geometry, coordination, diffusion coefficient and density, are simulated adequately for our purposes. Afterwards we use the new force field for the molecular dynamics simulation of a swollen polyelectrolyte membrane similar to the widespread Nafion 117. We investigate the equilibrated structures, proton transfer, lifetimes of hydronium ions, the diffusion coefficients, and the conductivity in dependence of water content. In a short movie we demonstrate the ability of the obtained force field to describe the bond breaking/formation, and conclude that this force field can be considered as a kind of a reactive force field. The investigations of the lifetimes of hydronium ions give us the information about the kinetics of the proton transfer in a membrane with low water content. We found the evidence for the second order reaction. Finally, we demonstrate that the model is simple enough to handle the large systems sufficient to calculate the conductivity from molecular dynamics simulations. The detailed analysis of the conductivity reveals the importance of the collective moving of hydronium ions in membrane, which might give an interesting encouragement for further development of membranes. Figure: The structure of water in one pore of the highly hydrated Nafion membranes. Figure The structure of water in one of pore of the highly hydrated Nafion membrane Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Physical scoring function based on AMBER force field and Poisson-Boltzmann implicit solvent for protein structure prediction

A well-behaved physics-based all-atom scoring function for protein structure prediction is analyzed with several widely used all-atom decoy sets. The scoring function, termed AMBER/Poisson-Boltzmann (PB), is based on a refined AMBER force field for intramolecular interactions and an efficient PB model for solvation interactions. Testing on the chosen decoy sets shows that the scoring function, which is designed to consider detailed chemical environments, is able to consistently discriminate all 62 native crystal structures after considering the heteroatom groups, disulfide bonds, and crystal packing effects that are not included in the decoy structures. When NMR structures are considered in the testing, the scoring function is able to discriminate 8 out of 10 targets. In the more challenging test of selecting near-native structures, the scoring function also performs very well: for the majority of the targets studied, the scoring function is able to select decoys that are close to the corresponding native structures as evaluated by ranking numbers and backbone Calpha root mean square deviations. Various important components of the scoring function are also studied to understand their discriminative contributions toward the rankings of native and near-native structures. It is found that neither the nonpolar solvation energy as modeled by the surface area model nor a higher protein dielectric constant improves its discriminative power. The terms remaining to be improved are related to 1-4 interactions. The most troublesome term is found to be the large and highly fluctuating 1-4 electrostatics term, not the dihedral-angle term. These data support ongoing efforts in the community to develop protein structure prediction methods with physics-based potentials that are competitive with knowledge-based potentials.     

Improved model of hydrated calcium ion for molecular dynamics simulations using classical biomolecular force fields

Calcium ions (Ca²⁺) play key roles in various fundamental biological processes such as cell signaling and brain function. Molecular dynamics (MD) simulations have been used to study such interactions, however, the accuracy of the Ca²⁺ models provided by the standard MD force fields has not been rigorously tested. Here, we assess the performance of the Ca²⁺ models from the most popular classical force fields AMBER and CHARMM by computing the osmotic pressure of model compounds and the free energy of DNA–DNA interactions. In the simulations performed using the two standard models, Ca²⁺ ions are seen to form artificial clusters with chloride, acetate, and phosphate species; the osmotic pressure of CaAc₂ and CaCl₂ solutions is a small fraction of the experimental values for both force fields. Using the standard parameterization of Ca²⁺ ions in the simulations of Ca²⁺‐mediated DNA–DNA interactions leads to qualitatively wrong outcomes: both AMBER and CHARMM simulations suggest strong inter‐DNA attraction whereas, in experiment, DNA molecules repel one another. The artificial attraction of Ca²⁺ to DNA phosphate is strong enough to affect the direction of the electric field‐driven translocation of DNA through a solid‐state nanopore. To address these shortcomings of the standard Ca²⁺ model, we introduce a custom model of a hydrated Ca²⁺ ion and show that using our model brings the results of the above MD simulations in quantitative agreement with experiment. Our improved model of Ca²⁺ can be readily applied to MD simulations of various biomolecular systems, including nucleic acids, proteins and lipid bilayer membranes. © 2016 Wiley Periodicals, Inc. Biopolymers 105: 752–763, 2016.     

Modeling of human M1 aminopeptidases for in silico screening of potential Plasmodium falciparum alanine aminopeptidase (PfA-M1) specific inhibitors

Plasmodium falciparum alanine M1-aminopeptidase (PfA-M1) is a validated target for anti-malarial drug development. Presence ofsignificant similarity between PfA-M1 and human M1-aminopeptidases, particularly within regions of enzyme active site leads toproblem of non-specificity and off-target binding for known aminopeptidase inhibitors. Molecular docking based in silico screeningapproach for off-target binding has high potential but requires 3D-structure of all human M1-aminopeptidaes. Therefore, in thepresent study 3D structural models of seven human M1-aminopeptidases were developed. The robustness of docking parametersand quality of predicted human M1-aminopeptidases structural models was evaluated by stereochemical analysis and docking oftheir respective known inhibitors. The docking scores were in agreement with the inhibitory concentrations elucidated in enzymeassays of respective inhibitor enzyme combinations (r2≈0.70). Further docking analysis of fifteen potential PfA-M1 inhibitors(virtual screening identified) showed that three compounds had less docking affinity for human M1-aminopeptidases as comparedto PfA-M1. These three identified potential lead compounds can be validated with enzyme assays and used as a scaffold fordesigning of new compounds with increased specificity towards PfA-M1.     

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 sp³ atom, and (iii) reduced 1–4 interaction scaling factors of torsions ? 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.     

Comparison of force fields for Alzheimer's A : A case study for intrinsically disordered proteins

Intrinsically disordered proteins are essential for biological processes such as cell signalling, but are also associated to devastating diseases including Alzheimer's disease, Parkinson's disease or type II diabetes. Because of their lack of a stable three‐dimensional structure, molecular dynamics simulations are often used to obtain atomistic details that cannot be observed experimentally. The applicability of molecular dynamics simulations depends on the accuracy of the force field chosen to represent the underlying free energy surface of the system. Here, we use replica exchange molecular dynamics simulations to test five modern force fields, OPLS, AMBER99SB, AMBER99SB*ILDN, AMBER99SBILDN‐NMR and CHARMM22*, in their ability to model Aβ₄₂, an intrinsically disordered peptide associated with Alzheimer's disease, and compare our results to nuclear magnetic resonance (NMR) experimental data. We observe that all force fields except AMBER99SBILDN‐NMR successfully reproduce local NMR observables, with CHARMM22* being slightly better than the other force fields.     

Simulation of an all-beta 3-icosapeptide containing the 20 proteinogenic side chains: effect of temperature, pH, counterions, solvent, and force field on helix stability

Simulations of various beta-peptides have in the last years clarified several issues concerning peptide folding equilibria and interpretation of experimental data, especially from NMR and CD spectroscopy. These simulations involved different temperatures, pH-values, ionic strengths, solvents, and force-field parameters, but a variation of these factors for one beta-peptide has not yet been done. To investigate the influence of varying these factors, we analyze the helix stability of an all-beta3-icosapeptide bearing all 20 proteinogenic amino acid side chains, which is experimentally observed to fold into a 3(14)-helix in methanol but not in water. Structural aspects, such as hydrogen-bonded rings and salt bridges, are discussed and a comparison with NMR primary (NOE distance bounds and 3J-values) and secondary (NMR derived model structures) data is made. We further investigate the reasons for the 3(14)-helix stability/instability in methanol/water. Of all factors studied, the presence of counterions seems to be the one inducing most significant effects in the simulations.     

Structure determination of a pseudotripeptide zinc complex with the COSMOS-NMR force field and DFT methods

A His-X-His pseudotripeptide zinc complex (X is a N-alkyl glycine derivative) similar to the catalytic center of the carbonic anhydrase was computer designed and experimentally synthesized. Using 2D-NMR techniques, all proton, carbon chemical shifts and nuclear overhauser effect signals were assigned. The three-dimensional structure of the complex was determined with the COSMOS (computer simulation of molecular structures) force field by applying ¹³C bond polarization theory chemical shift pseudo forces and restrictions for NOE distances. From molecular dynamics, simulated annealing simulations and geometry optimizations, the three best force field structures were taken for a final investigation by density functional theory calculations.     

Molecular simulations of physical and chemical adsorption under gas and liquid environments using force field- and quantum mechanics-based methods

Here we review our simulations of adsorption on metal–organic frameworks (MOFs) and platinum (Pt) catalysts, focusing on the modelling methods required to understand these two very different systems. MOFs are porous, crystalline materials with large surface areas, which are promising for a variety of adsorption applications. We review our simulations of gas uptake in PCN-53 (porous coordination network) as well as gas storage in MOFs functionalised with metal alkoxide sites. While fluid–solid interactions in both systems can be modelled quite well using algebraic force fields, the alkoxide sites in the functionalised MOFs require specialised versions, in order to describe the stronger adsorption energies. We discuss grand canonical Monte Carlo (GCMC) simulations of both systems. Pt is a common catalyst, and simulations have proven quite useful for providing molecular level details to understand its functionality. This involves understanding adsorption phenomena, which often requires quantum mechanical calculations. We describe our periodic boundary condition density functional theory (DFT) simulations of Pt-catalysed NO oxidation, focusing on adsorbate geometries and coverage effects. Finally, we describe one of the current ‘grand challenges’ in molecular simulations of adsorption, modelling catalytic activity in aqueous phase, which requires a combination of algebraic force fields, DFT and GCMC.     

Computation techniques in the conformational analysis of carbohydrates

A growing number of modern studies of carbohydrates is devoted to spatial mechanisms of their participation in the cell recognition processes and directed design of inhibitors of these processes. No progress in this field is possible without the development of theoretical conformational analysis of carbohydrates. In this review, we generalize literature data on the potentialities of using various molecular-mechanic force fields, the methods of quantum mechanics, and molecular dynamics to study the conformation of glycoside linkage. A possibility of analyzing the reactivity of carbohydrates with the computation techniques is also discussed in brief.     

Evolutionary analysis of the mammalian M1 aminopeptidases reveals conserved exon structure and gene death

The members of the M1 aminopeptidase family share conserved domains, yet show functional divergence within the family as a whole. In order to better understand this family, this study analyzed the mammalian members in depth at exon, gene, and protein levels. The twelve human members, eleven rat members, and eleven mouse members were first analyzed in multiple alignments to visualize both reported and unreported conserved domains. Phylogenetic trees were then generated for humans, rats, mice, and all mammals to determine how closely related the homologs were and to gain insight to the divergence in the family members. This produced three groups with similarity within the family. Next, a synteny study was completed to determine the present locations of the genes and changes that had occurred. It became apparent that gene death likely resulted in the lack of one member in mouse and rat. Finally, an in-depth analysis of the exon structure revealed that nine members of the human family and eight in mouse, are highly conserved within the exon structure. Taken together, these results indicate that the M1 aminopeptidase family is a divergent family with three subgroups and that genetic evidence mirrors categorization of the family by enzymatic function.     

Red fluorescent protein DsRed: Parametrization of its chromophore as an amino acid residue for computer modeling in the OPLS-AA force field

Topology of the neutral form of the DsRed fluorescent protein chromophore as a residue of [(4-cis)-2-[(1-cis)-4-amino-4-oxobutanimidoyl]-4-(4-hydroxybenzylidene)-5-oxo-4,5-dihydro-1H-imidazol-1-yl]acetic acid was calculated with OPLS-AA force field. Use of this topology and molecular dynamics simulation allows calculating the parameters of proteins that contain such residue in their polypeptide chains. The chromophore parameters were obtained by ab initio (RHF/6-31G**) quantum chemical calculations applying density functional theory (B3LYP). Using this chromophore, we have calculated the molecular dynamics trajectory of tetrameric fluorescent protein DsRed in solution at 300 K (4 nsec). Correctness of the chromophore parametrization was revealed by comparison of quantitative characteristics of the chromophore structure obtained from the molecular dynamic simulations of DsRed protein with the quantitative characteristics of the chromophore based on the crystallographic X-ray data of fluorescent protein DsRed (PDB ID: 1ZGO, 1G7K, and 1GGX), and also with the quantitative characteristics of the chromophore obtained by quantum chemical calculations. Inclusion of the neutral form of DsRed protein chromophore topology into the OPLS-AA force field yielded the extended force field OPLS-AA/DsRed. This force field can be used for molecular dynamics calculations of proteins containing the DsRed chromophore. The parameter set presented in this study can be applied for similar extension in any other force fields.     

Ab initio construction of polypeptide fragments: Accuracy of loop decoy discrimination by an all-atom statistical potential and the AMBER force field with the Generalized Born solvation model

The accuracy of model selection from decoy ensembles of protein loop conformations was explored by comparing the performance of the Samudrala-Moult all-atom statistical potential (RAPDF) and the AMBER molecular mechanics force field, including the Generalized Born/surface area solvation model. Large ensembles of consistent loop conformations, represented at atomic detail with idealized geometry, were generated for a large test set of protein loops of 2 to 12 residues long by a novel ab initio method called RAPPER that relies on fine-grained residue-specific phi/psi propensity tables for conformational sampling. Ranking the conformers on the basis of RAPDF scores resulted in selected conformers that had an average global, non-superimposed RMSD for all heavy mainchain atoms ranging from 1.2 A for 4-mers to 2.9 A for 8-mers to 6.2 A for 12-mers. After filtering on the basis of anchor geometry and RAPDF scores, ranking by energy minimization of the AMBER/GBSA potential energy function selected conformers that had global RMSD values of 0.5 A for 4-mers, 2.3 A for 8-mers, and 5.0 A for 12-mers. Minimized fragments had, on average, consistently lower RMSD values (by 0.1 A) than their initial conformations. The importance of the Generalized Born solvation energy term is reflected by the observation that the average RMSD accuracy for all loop lengths was worse when this term is omitted. There are, however, still many cases where the AMBER gas-phase minimization selected conformers of lower RMSD than the AMBER/GBSA minimization. The AMBER/GBSA energy function had better correlation with RMSD to native than the RAPDF. When the ensembles were supplemented with conformations extracted from experimental structures, a dramatic improvement in selection accuracy was observed at longer lengths (average RMSD of 1.3 A for 8-mers) when scoring with the AMBER/GBSA force field. This work provides the basis for a promising hybrid approach of ab initio and knowledge-based methods for loop modeling.