1
|
Geng H, Chen F, Ye J, Jiang F. Applications of Molecular Dynamics Simulation in Structure Prediction of Peptides and Proteins. Comput Struct Biotechnol J 2019; 17:1162-1170. [PMID: 31462972 PMCID: PMC6709365 DOI: 10.1016/j.csbj.2019.07.010] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 07/07/2019] [Accepted: 07/23/2019] [Indexed: 12/21/2022] Open
Abstract
Compared with rapid accumulation of protein sequences from high-throughput DNA sequencing, obtaining experimental 3D structures of proteins is still much more difficult, making protein structure prediction (PSP) potentially very useful. Currently, a vast majority of PSP efforts are based on data mining of known sequences, structures and their relationships (informatics-based). However, if closely related template is not available, these methods are usually much less reliable than experiments. They may also be problematic in predicting the structures of naturally occurring or designed peptides. On the other hand, physics-based methods including molecular dynamics (MD) can utilize our understanding of detailed atomic interactions determining biomolecular structures. In this mini-review, we show that all-atom MD can predict structures of cyclic peptides and other peptide foldamers with accuracy similar to experiments. Then, some notable successes in reproducing experimental 3D structures of small proteins through MD simulations (some with replica-exchange) of the folding were summarized. We also describe advancements of MD-based refinement of structure models, and the integration of limited experimental or bioinformatics data into MD-based structure modeling.
Collapse
Affiliation(s)
- Hao Geng
- Lab of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Fangfang Chen
- Guangdong and Shenzhen Key Laboratory of Male Reproductive Medicine and Genetics, Peking University Shenzhen Hospital, Shenzhen PKU-HKUST Medical Center, Shenzhen 518036, China
| | - Jing Ye
- Guangdong and Shenzhen Key Laboratory of Male Reproductive Medicine and Genetics, Peking University Shenzhen Hospital, Shenzhen PKU-HKUST Medical Center, Shenzhen 518036, China
| | - Fan Jiang
- Lab of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China
- NanoAI Biotech Co.,Ltd., Silicon Valley Compound, Longhua District, Shenzhen 518109, China
- Corresponding author at: Lab of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China.
| |
Collapse
|
2
|
Pang YP. FF12MC: A revised AMBER forcefield and new protein simulation protocol. Proteins 2016; 84:1490-516. [PMID: 27348292 PMCID: PMC5129589 DOI: 10.1002/prot.25094] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Revised: 06/16/2016] [Accepted: 06/18/2016] [Indexed: 12/25/2022]
Abstract
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 CH 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.
Collapse
Affiliation(s)
- Yuan-Ping Pang
- Computer-Aided Molecular Design Laboratory, Mayo Clinic, Rochester, MN, 55905, USA.
| |
Collapse
|
3
|
Pang YP. Use of multiple picosecond high-mass molecular dynamics simulations to predict crystallographic B-factors of folded globular proteins. Heliyon 2016; 2:e00161. [PMID: 27699282 PMCID: PMC5035356 DOI: 10.1016/j.heliyon.2016.e00161] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2016] [Revised: 08/18/2016] [Accepted: 09/12/2016] [Indexed: 12/22/2022] Open
Abstract
Predicting crystallographic B-factors of a protein from a conventional molecular dynamics simulation is challenging, in part because the B-factors calculated through sampling the atomic positional fluctuations in a picosecond molecular dynamics simulation are unreliable, and the sampling of a longer simulation yields overly large root mean square deviations between calculated and experimental B-factors. This article reports improved B-factor prediction achieved by sampling the atomic positional fluctuations in multiple picosecond molecular dynamics simulations that use uniformly increased atomic masses by 100-fold to increase time resolution. Using the third immunoglobulin-binding domain of protein G, bovine pancreatic trypsin inhibitor, ubiquitin, and lysozyme as model systems, the B-factor root mean square deviations (mean ± standard error) of these proteins were 3.1 ± 0.2–9 ± 1 Å2 for Cα and 7.3 ± 0.9–9.6 ± 0.2 Å2 for Cγ, when the sampling was done for each of these proteins over 20 distinct, independent, and 50-picosecond high-mass molecular dynamics simulations with AMBER forcefield FF12MC or FF14SB. These results suggest that sampling the atomic positional fluctuations in multiple picosecond high-mass molecular dynamics simulations may be conducive to a priori prediction of crystallographic B-factors of a folded globular protein.
Collapse
Affiliation(s)
- Yuan-Ping Pang
- Computer-Aided Molecular Design Laboratory, Mayo Clinic, Rochester, MN 55905, USA
| |
Collapse
|
4
|
Jayaram B, Dhingra P, Mishra A, Kaushik R, Mukherjee G, Singh A, Shekhar S. Bhageerath-H: a homology/ab initio hybrid server for predicting tertiary structures of monomeric soluble proteins. BMC Bioinformatics 2014; 15 Suppl 16:S7. [PMID: 25521245 PMCID: PMC4290660 DOI: 10.1186/1471-2105-15-s16-s7] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The advent of human genome sequencing project has led to a spurt in the number of protein sequences in the databanks. Success of structure based drug discovery severely hinges on the availability of structures. Despite significant progresses in the area of experimental protein structure determination, the sequence-structure gap is continually widening. Data driven homology based computational methods have proved successful in predicting tertiary structures for sequences sharing medium to high sequence similarities. With dwindling similarities of query sequences, advanced homology/ ab initio hybrid approaches are being explored to solve structure prediction problem. Here we describe Bhageerath-H, a homology/ ab initio hybrid software/server for predicting protein tertiary structures with advancing drug design attempts as one of the goals. RESULTS Bhageerath-H web-server was validated on 75 CASP10 targets which showed TM-scores ≥ 0.5 in 91% of the cases and Cα RMSDs ≤ 5 Å from the native in 58% of the targets, which is well above the CASP10 water mark. Comparison with some leading servers demonstrated the uniqueness of the hybrid methodology in effectively sampling conformational space, scoring best decoys and refining low resolution models to high and medium resolution. CONCLUSION Bhageerath-H methodology is web enabled for the scientific community as a freely accessible web server. The methodology is fielded in the on-going CASP11 experiment.
Collapse
|
5
|
Kovalskyy DB, Ivanov DN. Recognition of the HIV capsid by the TRIM5α restriction factor is mediated by a subset of pre-existing conformations of the TRIM5α SPRY domain. Biochemistry 2014; 53:1466-76. [PMID: 24506064 DOI: 10.1021/bi4014962] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The binding of the TRIM5α restriction factor to the HIV capsid is mediated by the C-terminal SPRY domain of TRIM5α. Atomic-level details of this host-pathogen interaction, which involves mobile variable loops of the SPRY domain, remain unclear. Some of the key determinants of restriction are encompassed by the long and disordered v1 loop of the SPRY domain. We applied molecular modeling to elucidate the conformational repertoire of the v1 loop and its role in the interaction with the capsid. All-atom replica exchange molecular dynamics revealed multiple transient, interconverting states of the v1 loop consistent with the intrinsic disorder observed experimentally. The docking of the SPRY conformations representing 10 most populated states onto the high-resolution model of the assembled HIV-1 capsid revealed that a subset of v1 conformations produced plausible binding poses, in which the SPRY domain binds close to the pseudo-2-fold symmetry axis and the v1 loop spans the interhexamer gap. Such binding mode is well supported by the NMR binding data and known escape mutants. We speculate that the binding mode that involves interaction of the capsid with a subset of preexisting SPRY conformations arising from the intrinsic disorder of the v1 loop may explain the remarkable ability of TRIM5α to resist viral evasion by mutagenesis and to restrict divergent retroviruses.
Collapse
Affiliation(s)
- Dmytro B Kovalskyy
- Department of Biochemistry and Cancer Therapy and Research Center, University of Texas Health Science Center at San Antonio , 7703 Floyd Curl Drive, San Antonio, Texas 78229, United States
| | | |
Collapse
|
6
|
Mirjalili V, Noyes K, Feig M. Physics-based protein structure refinement through multiple molecular dynamics trajectories and structure averaging. Proteins 2014; 82 Suppl 2:196-207. [PMID: 23737254 PMCID: PMC4212311 DOI: 10.1002/prot.24336] [Citation(s) in RCA: 87] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2013] [Revised: 04/30/2013] [Accepted: 05/09/2013] [Indexed: 12/26/2022]
Abstract
We used molecular dynamics (MD) simulations for structure refinement of Critical Assessment of Techniques for Protein Structure Prediction 10 (CASP10) targets. Refinement was achieved by selecting structures from the MD-based ensembles followed by structural averaging. The overall performance of this method in CASP10 is described, and specific aspects are analyzed in detail to provide insight into key components. In particular, the use of different restraint types, sampling from multiple short simulations versus a single long simulation, the success of a quality assessment criterion, the application of scoring versus averaging, and the impact of a final refinement step are discussed in detail.
Collapse
Affiliation(s)
- Vahid Mirjalili
- Department of Mechanical Engineering Michigan State University East Lansing, MI 48824; USA
- Department of Biochemistry and Molecular Biology Michigan State University East Lansing, MI 48824; USA
| | - Keenan Noyes
- Department of Chemistry Michigan State University East Lansing, MI 48824; USA
| | - Michael Feig
- Department of Biochemistry and Molecular Biology Michigan State University East Lansing, MI 48824; USA
- Department of Chemistry Michigan State University East Lansing, MI 48824; USA
| |
Collapse
|
7
|
Nugent T, Cozzetto D, Jones DT. Evaluation of predictions in the CASP10 model refinement category. Proteins 2014; 82 Suppl 2:98-111. [PMID: 23900810 PMCID: PMC4282348 DOI: 10.1002/prot.24377] [Citation(s) in RCA: 88] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2013] [Revised: 06/19/2013] [Accepted: 06/28/2013] [Indexed: 12/24/2022]
Abstract
Here we report on the assessment results of the third experiment to evaluate the state of the art in protein model refinement, where participants were invited to improve the accuracy of initial protein models for 27 targets. Using an array of complementary evaluation measures, we find that five groups performed better than the naïve (null) method—a marked improvement over CASP9, although only three were significantly better. The leading groups also demonstrated the ability to consistently improve both backbone and side chain positioning, while other groups reliably enhanced other aspects of protein physicality. The top-ranked group succeeded in improving the backbone conformation in almost 90% of targets, suggesting a strategy that for the first time in CASP refinement is successful in a clear majority of cases. A number of issues remain unsolved: the majority of groups still fail to improve the quality of the starting models; even successful groups are only able to make modest improvements; and no prediction is more similar to the native structure than to the starting model. Successful refinement attempts also often go unrecognized, as suggested by the relatively larger improvements when predictions not submitted as model 1 are also considered. Proteins 2014; 82(Suppl 2):98–111.
Collapse
Affiliation(s)
- Timothy Nugent
- Department of Computer Science Bioinformatics Group, University College London, London, WC1E 6BT, United Kingdom
| | | | | |
Collapse
|
8
|
Olson MA, Lee MS. Application of replica exchange umbrella sampling to protein structure refinement of nontemplate models. J Comput Chem 2013; 34:1785-93. [PMID: 23703032 DOI: 10.1002/jcc.23325] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2012] [Revised: 03/12/2013] [Accepted: 04/21/2013] [Indexed: 12/30/2022]
Abstract
We provide an assessment of a computational strategy for protein structure refinement that combines self-guided Langevin dynamics with umbrella-potential biasing replica exchange using the radius of gyration as a coordinate (Rg -ReX). Eight structurally nonredundant proteins and their decoys were examined by sampling conformational space at room temperature using the CHARMM22/GBMV2 force field to generate the ensemble of structures. Two atomic statistical potentials (RWplus and DFIRE) were analyzed for structure identification and compared to the simulation force-field potential. The results show that, while the Rg -ReX simulations were able to sample conformational basins that were more structurally similar to the X-ray crystallographic structures than the starting first-order ranked decoys, the potentials failed to detect these basins from refinement. Of the three potential functions, RWplus yielded the highest accuracy for recognition of structures that refined to an average of nearly 20% increase in native contacts relative to the starting decoys. The overall performance of Rg -ReX is compared to an earlier study of applying temperature-based replica exchange to refine the same decoy sets and highlights the general challenge of achieving consistently the sampling and detection threshold of 70% fraction of native contacts.
Collapse
Affiliation(s)
- Mark A Olson
- Department of Cell Biology and Biochemistry, USAMRIID, Fredrick, Maryland 21702, USA.
| | | |
Collapse
|
9
|
Mirjalili V, Feig M. Protein Structure Refinement through Structure Selection and Averaging from Molecular Dynamics Ensembles. J Chem Theory Comput 2013; 9:1294-1303. [PMID: 23526422 PMCID: PMC3603382 DOI: 10.1021/ct300962x] [Citation(s) in RCA: 70] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
A molecular dynamics (MD) simulation based protocol for structure refinement of template-based model predictions is described. The protocol involves the application of restraints, ensemble averaging of selected subsets, interpolation between initial and refined structures, and assessment of refinement success. It is found that sub-microsecond MD-based sampling when combined with ensemble averaging can produce moderate but consistent refinement for most systems in the CASP targets considered here.
Collapse
Affiliation(s)
- Vahid Mirjalili
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824; USA
- Department of Mechanical Engineering, Michigan State University, East Lansing, MI 48824; USA
| | - Michael Feig
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824; USA
- Department of Chemistry, Michigan State University, East Lansing, MI 48824; USA
| |
Collapse
|