EFFECT OF pH ON STRUCTURE AND STABILITY OF COLLAGEN-LIKE PEPTIDE: INSIGHT FROM MOLECULAR DYNAMICS SIMULATION
7
Citation
20
Reference
10
Related Paper
Citation Trend
Abstract:
Molecular dynamics simulations were carried out to investigate the effect of pH on structure and stability of collagen-like peptide. All simulations were performed using the consistent valence force field (CVFF) molecular mechanical force field and isothermal-isobaric ensemble (NPT). The initial geometries of the collagen-like peptide were from an X-ray crystallographic structure. Some analyses from the molecular dynamics trajectories have been completed. The results show that the diameter of collagen-like peptide increases and the volume swells obviously in basic environment; however, the size of peptide changes slightly in acidic environment. The stability of collagen-like peptide decreases in acid and basic environment comparing to neutral environment based on root mean square deviation (RMSD). The number of hydrogen bond formed by peptide has a tendency to decrease in both acidic and basic environment. The average of intra-molecular H-bond is minimal under basic condition, and the average of inter-molecular H-bond between amino acid residues and water molecules is minimal under acid condition. The radial distribution function (RDF) shows that side-chain oxygen atoms are easier to form hydrogen bonds with water than side-chain nitrogen atoms. The interaction of various amino acid residues with water is position dependent. Distance between two triple helices increases markedly under highly basic condition, but changes slightly under highly acidic condition.Keywords:
Side chain
Force Field
Structural Stability
Machine-learned coarse-grained (CG) models have the potential for simulating large molecular complexes beyond what is possible with atomistic molecular dynamics. However, training accurate CG models remains a challenge. A widely used methodology for learning bottom-up CG force fields maps forces from all-atom molecular dynamics to the CG representation and matches them with a CG force field on average. We show that there is flexibility in how to map all-atom forces to the CG representation and that the most commonly used mapping methods are statistically inefficient and potentially even incorrect in the presence of constraints in the all-atom simulation. We define an optimization statement for force mappings and demonstrate that substantially improved CG force fields can be learned from the same simulation data when using optimized force maps. The method is demonstrated on the miniproteins chignolin and tryptophan cage and published as open-source code.
Force Field
Granularity
Representation
Code (set theory)
Cite
Citations (20)
Abstract Our recent studies revealed that none of the selected widely used force field parameters and molecular dynamics simulation techniques yield structural properties for the intrinsically disordered α‐synuclein that are in agreement with various experiments via testing different force field parameters. Here, we extend our studies on the secondary structure properties of the disordered amyloid‐β(1–40) peptide in aqueous solution. For these purposes, we conducted extensive replica exchange molecular dynamics simulations and obtained extensive molecular dynamics simulation trajectories from David E. Shaw group. Specifically, these molecular dynamics simulations were conducted using various force field parameters and obtained results are compared to our replica exchange molecular dynamics simulations and experiments. In this study, we calculated the secondary structure abundances and radius of gyration values for amyloid‐β(1–40) that were simulated using varying force field parameter sets and different simulation techniques. In addition, the intrinsic disorder propensity, as well as sequence‐based secondary structure predisposition of amyloid‐β(1–40) and compared the findings with the results obtained from molecular simulations using various force field parameters and different simulation techniques. Our studies clearly show that the epitope region identification of amyloid‐β(1–40) depends on the chosen simulation technique and chosen force field parameters. Based on comparison with experiments, we find that best computational results in agreement with experiments are obtained using the a99sb*‐ildn, charmm36m, and a99sb‐disp parameters for the amyloid‐β(1–40) peptide in molecular dynamics simulations without parallel tempering or via replica exchange molecular dynamics simulations.
Force Field
Radius of gyration
Parallel tempering
Cite
Citations (17)
Abstract The proper matching of force field and solvent is critical to obtain correct result in molecular dynamics simulation of bio-molecules. This problem has been intensively investigated for protein but not for RNA yet. In this paper, we use standard molecular dynamics and replica exchange molecular dynamics to take a series of tests on the RNA stability under different combinations of Amber force field parameters (ff98, ff99 and ff99bsc0) and the general Born implicit solvent models (igb1, igb2 and igb5). It is found that only ff98 and ff99bsc0 with igb1 can keep the native conformations of RNA hairpin and duplex. Our results suggest that ff98 plus igb1 may be reasonable choice for molecular dynamics simulation of RNA dynamics.
Force Field
Cite
Citations (44)
Recent improvements of the protein backbone force-field parameters in AMBER99SB have allowed accurate simulation of backbone dynamics, but the consequences for side-chain dynamics have been unclear. It is demonstrated for Ca2+-bound calbindin D9k and ubiquitin that the methyl group dynamics, as assessed by deuterium relaxation measurements of 13CH2D groups, is well-reproduced across the protein by molecular dynamics (MD) simulation. Direct analysis of simulated spectral density functions and fitted S2 order parameters yield remarkably good agreement. These results provide important benchmarks for amino acid specific improvements of side-chain force fields.
Side chain
Dynamics
Force Field
Protein Dynamics
Chain (unit)
Cite
Citations (70)
Force Field
Cite
Citations (14)
Force Field
Helix (gastropod)
Dynamics
Cite
Citations (7)
The sensitivity of molecular dynamics simulations to variations in the force field has been examined in relation to a set of 36 structures corresponding to 31 proteins simulated by using different versions of the GROMOS force field. The three parameter sets used (43a1, 53a5, and 53a6) differ significantly in regard to the nonbonded parameters for polar functional groups and their ability to reproduce the correct solvation and partitioning behavior of small molecular analogues of the amino acid side chains. Despite the differences in the force field parameters no major differences could be detected in a wide range of structural properties such as the root-mean-square deviation from the experimental structure, radii of gyration, solvent accessible surface, secondary structure, or hydrogen bond propensities on a 5 to 10 ns time scale. The small differences that were observed correlated primarily with the presence of charged residues as opposed to residues that differed most between the parameter sets. The work highlights the variation that can be observed in nanosecond simulations of protein systems and implications of this for force field validation, as well as for the analysis of protein simulations in general.
Force Field
Radius of gyration
Nanosecond
Root mean square
Accessible surface area
Cite
Citations (17)
A new force field for fast molecular dynamics simulations in flexible aluminosilicates is presented. Starting from a force field previously developed in our laboratory, an adaptation to CHARMM functional form and a subsequent optimization are performed. The obtained force field is validated checking its ability to correctly reproduce the crystallographic structures and the vibrational properties for silicalite and zeolites Na A, Ca A, Na Y, and Na X. This new force field allows the execution of large-scale simulations in a parallel environment via the most common packages available.
Force Field
Cite
Citations (26)
Machine-learned coarse-grained (CG) models have the potential for simulating large molecular complexes beyond what is possible with atomistic molecular dynamics. However, training accurate CG models remains a challenge. A widely used methodology for learning CG force-fields maps forces from all-atom molecular dynamics to the CG representation and matches them with a CG force-field on average. We show that there is flexibility in how to map all-atom forces to the CG representation, and that the most commonly used mapping methods are statistically inefficient and potentially even incorrect in the presence of constraints in the all-atom simulation. We define an optimization statement for force mappings and demonstrate that substantially improved CG force-fields can be learned from the same simulation data when using optimized force maps. The method is demonstrated on the miniproteins Chignolin and Tryptophan Cage and published as open-source code.
Force Field
Granularity
Representation
Code (set theory)
Dynamics
Cite
Citations (1)
Abstract The dynamics and thermodynamics character of H1 peptide in aqueous solution has been investigated through temperature replica exchange molecular dynamics (T-REMD) simulations using two different force fields (OPLS-AA and GROMOS 43A1). The two independent T-REMD simulations were completed starting from initial conformations a-helix and β-sheet, respectively. Each replica was run for 300 ns. The performance of each force field was assessed from the parameters such as the distributions of backbone dihedral angles, the number of native hydrogen bond, root mean square deviations (RMSD) of Ca atoms and all heavy atoms, formation of β-turn, the stability of folded β-hairpin structure and the favorite conformations of different force fields. The simulation using GROMOS 43A1 force field starting from a-helix structure sampled the conformation cluster which Ca RMSD was 0.05 nm from β-sheet structure and the cluster contains 39% of all conformations. The simulation using OPLS-AA force field produced more sampling in PII region than in GROMOS 43A1 force field. The both force field simulations produced some sampling in the a region, but the probabilities of the conformations including any helical content were only 1–2%. Under the both force fields, the β-turn structures exhibited higher stability than a-helix structures and the folded β-hairpin structures. In the GROMOS 43A1 force field, the free energy change from the unfolded state to the hairpin state was in good agreement with the results of several experiments about some β-peptides (not the H1 peptide) and the other molecular dynamics simulations of H1 peptide. However, the folded β-hairpin structure was more destabilized in the OPLS-AA force field than in the GROMOS 43A1 force field and experiments. Key words: Peptide simulationReplica exchangeThermodynamics and structural character
Dynamics
Force Field
Cite
Citations (38)