Controlling the secondary-structure-forming tendencies of proteins by a backbone torsion-energy term

We examined a new backbone torsion-energy term proposed by us in the force field for protein systems. This torsion-energy term is represented by a double Fourier series in two variables, namely the backbone dihedral angles φ and ψ. It gives a natural representation of the torsion energy in the Ramachandran space in the sense that any two-dimensional energy surface periodic in both φ and ψ can be expanded by the double Fourier series. We can then easily control secondary-structure-forming tendencies by modifying the torsion-energy surface. For instance, we can increase or decrease the α-helix-forming-tendencies by lowering or raising the torsion-energy surface in the α-helix region and likewise increase or decrease the β-sheet-forming tendencies by lowering or raising the surface in the β-sheet region in the Ramachandran space. We applied this torsion-energy modification method to six force fields, AMBER parm94, AMBER parm96, AMBER parm99, CHARMM27, OPLS-AA and OPLS-AA/L, and demonstrated that our modifications of the torsion-energy terms resulted in the expected changes of secondary-structure-forming tendencies by performing folding simulations of α-helical and β-hairpin peptides.     

Folding simulations of three proteins having all α-helix,all β-strand and α/β-structures

We performed folding simulations of three proteins using four force fields, AMBER parm96, AMBER parm99, CHARMM 27 and OPLS-AA/L, in order to examine the features of these force fields. We studied three proteins, protein A (all α-helix), cold-shock protein (all β-strand) and protein G (α/β-structures), for the folding simulations. For the simulation, we used the simulated annealing molecular dynamics method, which was performed 50 times for each protein using the four force fields. The results showed that the secondary-structure-forming tendencies are largely different among the four force fields. AMBER parm96 favours β-bridge structures and extended β-strand structures, and AMBER parm99 favours α-helix structures and 3₁₀-helix structures. CHARMM 27 slightly favours α-helix structures, and there are also π-helix and β-bridge structures. OPLS-AA/L favours α-helix structures and 3₁₀-helix structures.     

Refinement of the AMBER force field for nucleic acids: improving the description of alpha/gamma conformers

We present here the parmbsc0 force field, a refinement of the AMBER parm99 force field, where emphasis has been made on the correct representation of the alpha/gamma concerted rotation in nucleic acids (NAs). The modified force field corrects overpopulations of the alpha/gamma = (g+,t) backbone that were seen in long (more than 10 ns) simulations with previous AMBER parameter sets (parm94-99). The force field has been derived by fitting to high-level quantum mechanical data and verified by comparison with very high-level quantum mechanical calculations and by a very extensive comparison between simulations and experimental data. The set of validation simulations includes two of the longest trajectories published to date for the DNA duplex (200 ns each) and the largest variety of NA structures studied to date (15 different NA families and 97 individual structures). The total simulation time used to validate the force field includes near 1 mus of state-of-the-art molecular dynamics simulations in aqueous solution.     

Towards a molecular dynamics consensus view of B-DNA flexibility

We present a systematic study of B-DNA flexibility in aqueous solution using long-scale molecular dynamics simulations with the two more recent versions of nucleic acids force fields (CHARMM27 and parmbsc0) using four long duplexes designed to contain several copies of each individual base pair step. Our study highlights some differences between pambsc0 and CHARMM27 families of simulations, but also extensive agreement in the representation of DNA flexibility. We also performed additional simulations with the older AMBER force fields parm94 and parm99, corrected for non-canonical backbone flips. Taken together, the results allow us to draw for the first time a consensus molecular dynamics picture of B-DNA flexibility.     

Effects of different force fields on the structural character of α synuclein β-hairpin peptide (35–56) in aqueous environment

The hallmark of Parkinson’s disease (PD) is the intracellular protein aggregation forming Lewy Bodies (LB) and Lewy neuritis which comprise mostly of a protein, alpha synuclein (α-syn). Molecular dynamics (MD) simulation methods can augment experimental techniques to understand misfolding and aggregation pathways with atomistic resolution. The quality of MD simulations for proteins and peptides depends greatly on the accuracy of empirical force fields. The aim of this work is to investigate the effects of different force fields on the structural character of β hairpin fragment of α-syn (residues 35–56) peptide in aqueous solution. Six independent MD simulations are done in explicit solvent using, AMBER03, AMBER99SB, GROMOS96 43A1, GROMOS96 53A6, OPLS-AA, and CHARMM27 force fields with CMAP corrections. The performance of each force field is assessed from several structural parameters such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent accessible surface area (SASA), formation of β-turn, the stability of folded β-hairpin structure, and the favourable conformations obtained for different force fields. In this study, CMAP correction of CHARMM27 force field is found to overestimate the helical conformation, while GROMOS96 53A6 is found to most successfully capture the conformational dynamics of α-syn β-hairpin fragment as elicited from NMR.     

AMBER force-field parameters for phosphorylated amino acids in different protonation states: phosphoserine, phosphothreonine, phosphotyrosine, and phosphohistidine

We report a consistent set of AMBER force-field parameters for the most common phosphorylated amino acids, phosphoserine, phosphothreonine, phosphotyrosine, and phosphohistidine in different protonation states. The calculation of atomic charges followed the original restrained electrostatic potential fitting procedure used to determine the charges for the parm94/99 parameter set, taking α-helical and β-strand conformations of the corresponding ACE-/NME-capped model peptide backbone into account. Missing force-field parameters were taken directly from the general AMBER force field (gaff) and the parm99 data set with minor modifications, or were newly generated based on ab initio calculations for model systems. Final parameters were validated by geometry optimizations and molecular-dynamics simulations. Template libraries for the phosphorylated amino acids in Leap format and corresponding frcmod parameter files are made available. Figure Schematic illustration of the systems used for parameter generation. Acid hydrogens are shown in red Electronic Supplementary Material Supplementary material is available for this article at     

Optimisation of OPLS–UA force-field parameters for protein systems using protein data bank

We have previously proposed a method for refining force-field parameters of protein systems, which consists of minimising the summation of the square of the force acting on each atom in the proteins with the structures from the protein data bank (PDB). The results showed that the modified force-field parameters for all-atom model gave structures more consistent with the experimental implications than the original force fields. In this work, we applied this method and a new method to the OPLS–UA force field. In the new method, we perform a minimisation of the average of the root-mean-square deviation of various protein structures from the native structure. We selected some torsion-energy parameters for this optimisation, and 100 molecules from the PDB were used. The results imply that the new force-field parameters gave structures of two peptides more consistent with the experimental implications for the secondary structure-forming tendencies than the original OPLS–UA force field.     

Peptide Free Energy Landscapes Calibrated by Molecular Orbital Calculations

Free energy landscapes of peptide conformations werecalibrated by ab initiomolecular orbital calculations, after enhancedconformational sampling using the multicanonical molecular dynamicssimulations. Three different potentials of mean force for an isolateddipeptide were individually obtained using the conventional force fields,AMBER parm94, AMBER parm96, and CHARMm22. Each potential ofmean force was calibrated based on the umbrella sampling algorithm fromthe adiabatic energy map that was calculated separately by the abinitiomolecular orbital method. All the calibrated potentials of mean forcecoincided well. The calibration was applied to a peptide in explicit water,and the calibrated free energy landscapes did not depend on the force fieldused in conformational sampling, as far as the conformational space waswell sampled.     

Comparison of the structural characteristics of Cu2+-bound and unbound α-syn12 peptide obtained in simulations using different force fields

The effects of Cu²⁺ binding and the utilization of different force fields when modeling the structural characteristics of α-syn12 peptide were investigated. To this end, we performed extensive temperature replica exchange molecular dynamics (T-REMD) simulations on Cu²⁺-bound and unbound α-syn12 peptide using the GROMOS 43A1, OPLS-AA, and AMBER03 force fields. Each replica was run for 300 ns. The structural characteristics of α-syn12 peptide were studied based on backbone dihedral angle distributions, free-energy surfaces obtained with different reaction coordinates, favored conformations, the formation of different Turn structures, and the solvent exposure of the hydrophobic residues. The findings show that AMBER03 prefers to sample helical structures for the unbound α-syn12 peptide and does not sample any β-hairpin structure for the Cu²⁺-bound α-syn12 peptide. In contrast, the central structure of the major conformational clusters for the Cu²⁺-bound and unbound α-syn12 peptide according to simulations performed using the GROMOS 43A1 and OPLS-AA force fields is a β-hairpin with Turn_9-6. Cu²⁺ can also promote the formation of the β-hairpin and increase the solvent exposure of hydrophobic residues, which promotes the aggregation of α-syn12 peptide. This study can help us to understand the mechanisms through which Cu²⁺ participates in the fibrillation of α-syn12 peptide at the atomic level, which in turn represents a step towards elucidating the nosogenesis of Parkinson’s disease.

Structural equilibrium of DNA represented with different force fields.

We have recently indicated preliminary evidence of different equilibrium average structures with the CHARMM and AMBER force fields in explicit solvent molecular dynamics simulations on the DNA duplex d(C5T5) . d(A5G5) (Feig, M. and B.M. Pettitt, 1997, Experiment vs. Force Fields: DNA conformation from molecular dynamics simulations. J. Phys. Chem. B. (101:7361-7363). This paper presents a detailed comparison of DNA structure and dynamics for both force fields from extended simulation times of 10 ns each. Average structures display an A-DNA base geometry with the CHARMM force field and a base geometry that is intermediate between A- and B-DNA with the AMBER force field. The backbone assumes B form on both strands with the AMBER force field, while the CHARMM force field produces heterogeneous structures with the purine strand in A form and the pyrimidine strand in dynamical equilibrium between A and B conformations. The results compare well with experimental data for the cytosine/guanine part but fail to fully reproduce an overall B conformation in the thymine/adenine tract expected from crystallographic data, particularly with the CHARMM force field. Fluctuations between A and B conformations are observed on the nanosecond time scale in both simulations, particularly with the AMBER force field. Different dynamical behavior during the first 4 ns indicates that convergence times of several nanoseconds are necessary to fully establish a dynamical equilibrium in all structural quantities on the time scale of the simulations presented here.     

Free energy landscape of protein folding in water: explicit vs. implicit solvent

The Generalized Born (GB) continuum solvent model is arguably the most widely used implicit solvent model in protein folding and protein structure prediction simulations; however, it still remains an open question on how well the model behaves in these large-scale simulations. The current study uses the beta-hairpin from C-terminus of protein G as an example to explore the folding free energy landscape with various GB models, and the results are compared to the explicit solvent simulations and experiments. All free energy landscapes are obtained from extensive conformation space sampling with a highly parallel replica exchange method. Because solvation model parameters are strongly coupled with force fields, five different force field/solvation model combinations are examined and compared in this study, namely the explicit solvent model: OPLSAA/SPC model, and the implicit solvent models: OPLSAA/SGB (Surface GB), AMBER94/GBSA (GB with Solvent Accessible Surface Area), AMBER96/GBSA, and AMBER99/GBSA. Surprisingly, we find that the free energy landscapes from implicit solvent models are quite different from that of the explicit solvent model. Except for AMBER96/GBSA, all other implicit solvent models find the lowest free energy state not the native state. All implicit solvent models show erroneous salt-bridge effects between charged residues, particularly in OPLSAA/SGB model, where the overly strong salt-bridge effect results in an overweighting of a non-native structure with one hydrophobic residue F52 expelled from the hydrophobic core in order to make better salt bridges. On the other hand, both AMBER94/GBSA and AMBER99/GBSA models turn the beta-hairpin in to an alpha-helix, and the alpha-helical content is much higher than the previously reported alpha-helices in an explicit solvent simulation with AMBER94 (AMBER94/TIP3P). Only AMBER96/GBSA shows a reasonable free energy landscape with the lowest free energy structure the native one despite an erroneous salt-bridge between D47 and K50. Detailed results on free energy contour maps, lowest free energy structures, distribution of native contacts, alpha-helical content during the folding process, NOE comparison with NMR, and temperature dependences are reported and discussed for all five models.     

Examination of the quality of various force fields and solvation models for the equilibrium simulations of GA88 and GB88

Elucidating the relationship between sequence and conformation is essential for the understanding of functions of proteins. While sharing 88 % sequence identity and differing by only seven residues, GA88 and GB88 have completely different structures and serve as ideal systems for investigating the relationship between sequence and function. Benefiting from the continuous advancement of the computational ability of modern computers, molecular dynamics (MD) simulation is now playing an increasingly important role in the study of proteins. However, the reliability of MD simulations is limited by the accuracy of the force fields and solvent model approximations. In this work, several AMBER force fields (AMBER03, AMBER99SB, AMBER12SB, AMBER14SB, AMBER96) and solvent models (TIP3P, IGB5, IGB7, IGB8) have been employed in the simulations of GA88 and GB88. The statistical results from 19 simulations show that GA88 and GB88 both adopt more compact structures than the native structures. GB88 is more stable than GA88 regardless of the force fields and solvent models utilized. Most of the simulations overestimated the salt bridge interaction. The combination of AMBER14SB force field and IGB8 solvent model shows the best overall performance in the simulations of both GA88 and GB88. AMBER03 and AMBER12SB also yield reasonable results but only in the TIP3P explicit solvent model.     

Force field influences in beta-hairpin folding simulations

All-atom force fields are now routinely used for more detailed understanding of protein folding mechanisms. However, it has been pointed out that use of all-atom force fields does not guarantee more accurate representations of proteins; in fact, sometimes it even leads to biased structural distributions. Indeed, several issues remain to be solved in force field developments, such as accurate treatment of implicit solvation for efficient conformational sampling and proper treatment of backbone interactions for secondary structure propensities. In this study, we first investigate the quality of several recently improved backbone interaction schemes in AMBER for folding simulations of a beta-hairpin peptide, and further study their influences on the peptide's folding mechanism. Due to the significant number of simulations needed for a thorough analysis of tested force fields, the implicit Poisson-Boltzmann solvent was used in all simulations. The chosen implicit solvent was found to be reasonable for studies of secondary structures based on a set of simulations of both alpha-helical and beta-hairpin peptides with the TIP3P explicit solvent as benchmark. Replica exchange molecular dynamics was also utilized for further efficient conformational sampling. Among the tested AMBER force fields, ff03 and a revised ff99 force field were found to produce structural and thermodynamic data in comparably good agreement with the experiment. However, detailed folding pathways, such as the order of backbone hydrogen bond zipping and the existence of intermediate states, are different between the two force fields, leading to force field-dependent folding mechanisms.     

Blind Test of Physics-Based Prediction of Protein Structures

We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences.     

Energy landscape of a peptide consisting of alpha-helix, 3(10)-helix, beta-turn, beta-hairpin, and other disordered conformations

The energy landscape of a peptide [Ace-Lys-Gln-Cys-Arg-Glu-Arg-Ala-Nme] in explicit water was studied with a multicanonical molecular dynamics simulation, and the AMBER parm96 force field was used for the energy calculation. The peptide was taken from the recognition helix of the DNA-binding protein, c-MYB: A rugged energy landscape was obtained, in which the random-coil conformations were dominant at room temperature. The CD spectra of the synthesized peptide revealed that it is in the random state at room temperature. However, the 300 K canonical ensemble, Q(300K), contained alpha-helix, 3(10)-helix, beta-turn, and beta-hairpin structures with small but notable probabilities of existence. The complete alpha-helix, imperfect alpha-helix, and random-coil conformations were separated from one another in the conformational space. This means that the peptide must overcome energy barriers to form the alpha-helix. The overcoming process may correspond to the hydrogen-bond rearrangements from peptide-water to peptide-peptide interactions. The beta-turn, imperfect 3(10)-helix, and beta-hairpin structures, among which there are no energy barriers at 300 K, were embedded in the ensemble of the random-coil conformations. Two types of beta-hairpin with different beta-turn regions were observed in Q(300K). The two beta-hairpin structures may have different mechanisms for the beta-hairpin formation. The current study proposes a scheme that the random state of this peptide consists of both ordered and disordered conformations. In contrast, the energy landscape obtained from the parm94 force field was funnel like, in which the peptide formed the helical conformation at room temperature and random coil at high temperature.     

Simulation Studies on the Stabilities of Aggregates Formed by Fibril-Forming Segments of α-Synuclein

Abstract

We performed molecular dynamics simulations for various oligomers with different β-sheet conformations consisting of α-Synuclein 71–82 residues using an all atom force field and explicit water model. Tetramers of antiparallel β-sheet are shown to be stable, whereas parallel sheets are highly unstable due to the repulsive interactions between bulky and polar side chains as well as the weaker backbone hydrogen bonds. We also investigated the stabilities of double antiparallel β-sheets stacked with asymmetric and symmetric geometries. Our results show that this 12 amino acid residue peptide can form stable β-sheet conformers at 320K and higher temperatures. The backbone hydrogen bonds in β-sheet and the steric packing between hydrophobic side chains between β-sheets are shown to give conformational stabilities.     

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.     

Peptoid conformational free energy landscapes from implicit-solvent molecular simulations in AMBER

To test the accuracy of existing AMBER force field models in predicting peptoid conformation and dynamics, we simulated a set of model peptoid molecules recently examined by Butterfoss et al. (JACS 2009, 131, 16798-16807) using QM methods as well as three peptoid sequences with experimentally determined structures. We found that AMBER force fields, when used with a Generalized Born/Surface Area (GBSA) implicit solvation model, could accurately reproduce the peptoid torsional landscape as well as the major conformers of known peptoid structures. Enhanced sampling by replica exchange molecular dynamics (REMD) using temperatures from 300 to 800 K was used to sample over cis-trans isomerization barriers. Compared to (Nrch)5 and cyclo-octasarcosyl, the free energy of N-(2-nitro-3-hydroxyl phenyl)glycine-N-(phenyl)glycine has the most "foldable" free energy landscape, due to deep trans-amide minima dictated by N-aryl sidechains. For peptoids with (S)-N (1-phenylethyl) (Nspe) side chains, we observe a discrepancy in backbone dihedral propensities between molecular simulations and QM calculations, which may be due to force field effects or the inability to capture n --> n* interactions. For these residues, an empirical phi-angle biasing potential can "rescue" the backbone propensities seen in QM. This approach can serve as a general strategy for addressing force fields without resorting to a complete reparameterization. Overall, this study demonstrates the utility of implicit-solvent REMD simulations for efficient sampling to predict peptoid conformational landscapes, providing a potential tool for first-principles design of sequences with specific folding properties.     

Molecular dynamics studies of a DNA-binding protein: 1. A comparison of the trp repressor and trp aporepressor aqueous simulations.

The results of two 30-ps molecular dynamics simulations of the trp repressor and trp aporepressor proteins are presented in this paper. The simulations were obtained using the AMBER molecular mechanical force field and in both simulations a 6-A shell of TIP3P waters surrounded the proteins. The trp repressor protein is a DNA-binding regulatory protein and it utilizes a helix-turn-helix (D helix-turn-E helix) motif to interact with DNA. The trp aporepressor, lacking two molecules of the L-tryptophan corepressor, cannot bind specifically to DNA. Our simulations show that the N- and C-termini and the residues in and near the helix-turn-helix motifs are the most mobile regions of the proteins, in agreement with the X-ray crystallographic studies. Our simulations also find increased mobility of the residues in the turn-D helix-turn regions of the proteins. We find the average distance separating the DNA-binding motifs to be larger in the repressor as compared to the aporepressor. In addition to examining the protein residue fluctuations and deviations with respect to X-ray structures, we have also focused on backbone dihedral angles and corepressor hydrogen-bonding patterns in this paper.