1
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Shimono Y, Hakamada M, Mabuchi M. NPEX: Never give up protein exploration with deep reinforcement learning. J Mol Graph Model 2024; 131:108802. [PMID: 38838617 DOI: 10.1016/j.jmgm.2024.108802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 05/05/2024] [Accepted: 05/24/2024] [Indexed: 06/07/2024]
Abstract
Elucidating unknown structures of proteins, such as metastable states, is critical in designing therapeutic agents. Protein structure exploration has been performed using advanced computational methods, especially molecular dynamics and Markov chain Monte Carlo simulations, which require untenably long calculation times and prior structural knowledge. Here, we developed an innovative method for protein structure determination called never give up protein exploration (NPEX) with deep reinforcement learning. The NPEX method leverages the soft actor-critic algorithm and the intrinsic reward system, effectively adding a bias potential without the need for prior knowledge. To demonstrate the method's effectiveness, we applied it to four models: a double well, a triple well, the alanine dipeptide, and the tryptophan cage. Compared with Markov chain Monte Carlo simulations, NPEX had markedly greater sampling efficiency. The significantly enhanced computational efficiency and lack of prior domain knowledge requirements of the NPEX method will revolutionize protein structure exploration.
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Affiliation(s)
- Yuta Shimono
- Graduate School of Energy Science, Kyoto University, Yoshidahonmachi, Sakyo-ku, Kyoto, 606-8501, Japan
| | - Masataka Hakamada
- Graduate School of Energy Science, Kyoto University, Yoshidahonmachi, Sakyo-ku, Kyoto, 606-8501, Japan.
| | - Mamoru Mabuchi
- Graduate School of Energy Science, Kyoto University, Yoshidahonmachi, Sakyo-ku, Kyoto, 606-8501, Japan
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2
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Heilmann N, Wolf M, Kozlowska M, Sedghamiz E, Setzler J, Brieg M, Wenzel W. Sampling of the conformational landscape of small proteins with Monte Carlo methods. Sci Rep 2020; 10:18211. [PMID: 33097750 PMCID: PMC7585447 DOI: 10.1038/s41598-020-75239-7] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Accepted: 10/12/2020] [Indexed: 12/24/2022] Open
Abstract
Computer simulation provides an increasingly realistic picture of large-scale conformational change of proteins, but investigations remain fundamentally constrained by the femtosecond timestep of molecular dynamics simulations. For this reason, many biologically interesting questions cannot be addressed using accessible state-of-the-art computational resources. Here, we report the development of an all-atom Monte Carlo approach that permits the modelling of the large-scale conformational change of proteins using standard off-the-shelf computational hardware and standard all-atom force fields. We demonstrate extensive thermodynamic characterization of the folding process of the α-helical Trp-cage, the Villin headpiece and the β-sheet WW-domain. We fully characterize the free energy landscape, transition states, energy barriers between different states, and the per-residue stability of individual amino acids over a wide temperature range. We demonstrate that a state-of-the-art intramolecular force field can be combined with an implicit solvent model to obtain a high quality of the folded structures and also discuss limitations that still remain.
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Affiliation(s)
- Nana Heilmann
- Institute of Nanotechnology (INT), Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany
| | - Moritz Wolf
- Institute of Nanotechnology (INT), Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany
| | - Mariana Kozlowska
- Institute of Nanotechnology (INT), Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany
| | - Elaheh Sedghamiz
- Institute of Nanotechnology (INT), Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany
| | - Julia Setzler
- Institute of Nanotechnology (INT), Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany
| | - Martin Brieg
- Institute of Nanotechnology (INT), Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany
| | - Wolfgang Wenzel
- Institute of Nanotechnology (INT), Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany.
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3
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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: 43] [Impact Index Per Article: 8.6] [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.
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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.
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4
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Wang Y, Tian P, Boomsma W, Lindorff-Larsen K. Monte Carlo Sampling of Protein Folding by Combining an All-Atom Physics-Based Model with a Native State Bias. J Phys Chem B 2018; 122:11174-11185. [DOI: 10.1021/acs.jpcb.8b06335] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Yong Wang
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, DK-2200 Copenhagen N, Denmark
| | - Pengfei Tian
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, DK-2200 Copenhagen N, Denmark
- Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - Wouter Boomsma
- Department of Computer Science, University of Copenhagen, 2100 Copenhagen Ø, Denmark
| | - Kresten Lindorff-Larsen
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, DK-2200 Copenhagen N, Denmark
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5
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Frigori RB. Be positive: optimizing pramlintide from microcanonical analysis of amylin isoforms. Phys Chem Chem Phys 2018; 19:25617-25633. [PMID: 28905065 DOI: 10.1039/c7cp04074a] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Amylin, or human islet amyloid polypeptide (hIAPP), is a 37-residue hormone synergistic to insulin and co-secreted with it by β-cells in the pancreas. The deposition of its cytotoxic amyloid fibrils is strongly related to the progression of Type II diabetes (T2D) and islet graft failures. Notably, isoforms from some mammalian species, such as rats (rIAPP) and porcine (pIAPP), present a few key mutations preventing aggregation. This has lead to biotechnological development of drugs for adjunct therapies of T2D, such as pramlintide, a variant of hIAPP inspired by rIAPP whose proline substitutions have β-strand fibril-breaking properties. Ideally, such a drug should be formulated with insulin and co-administered, but this has been prevented by a poor solubility profile at the appropriate pH. Hopefully, this could be improved with appropriate point mutations, increasing the molecular net charge. Despite experimental progress, preliminary screening during rational drug design can greatly benefit from thermodynamic insight derived from molecular simulations. So we introduce microcanonical thermostatistics analysis of multicanonical (MUCA) simulations of wild-type amylin isoforms as a systematic assessment of protein thermostability. As a consequence of this comprehensive investigation, the most suitable single-point mutations able to optimize pramlintide are located among the wild-type amylin isoforms. In particular, we find that aggregation inhibition and increased solubility are inherited by pramlintide through further S20R substitution typical of pIAPP. Thus, we provide a consistent thermostatistical methodology to aid the design of improved adjunct therapies for T2D according to current clinical knowledge.
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Affiliation(s)
- Rafael B Frigori
- Universidade Tecnológica Federal do Paraná, Rua Cristo Rei 19, 85902-490, Toledo, PR, Brazil.
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6
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Ho S. Design of Aggregate Structures and Molecular Capture by Using Molecular-Cluster-Assembly Method. MACROMOL THEOR SIMUL 2015. [DOI: 10.1002/mats.201500041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Shirun Ho
- Research & Development Group; Hitachi, Ltd.; Kokubunji Tokyo 185-8601 Japan
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7
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Shao Q. Important roles of hydrophobic interactions in folding and charge interactions in misfolding of α-helix bundle protein. RSC Adv 2015. [DOI: 10.1039/c4ra14265a] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
An enhanced-sampling molecular dynamics simulation is presented to quantitatively demonstrate the important roles of hydrophobic and charge interactions in the folding and misfolding of α-helix bundle protein, respectively.
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Affiliation(s)
- Qiang Shao
- Drug Discovery and Design Center
- Shanghai Institute of Materia Medica
- Chinese Academy of Sciences
- Shanghai
- China
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8
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Shao Q. Probing Sequence Dependence of Folding Pathway of α-Helix Bundle Proteins through Free Energy Landscape Analysis. J Phys Chem B 2014; 118:5891-900. [DOI: 10.1021/jp5043393] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Qiang Shao
- Drug Discovery and Design
Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
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9
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Ho S, Aoyagi M. Molecular-Cluster-Assembly Method for Analysis of High-Dimensional Structures of p
-Cresol Chains in Phenolic Polymers. MACROMOL THEOR SIMUL 2013. [DOI: 10.1002/mats.201300101] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- Shirun Ho
- Central Research Laboratory; Hitachi, Ltd., Hatoyama; Saitama 350-0395 Japan
- Graduate School and Faculty of Information Science and Electrical Engineering; Kyushu University; Hakozaki, Higashi-ku Fukuoka 812-8581 Japan
| | - Mutsumi Aoyagi
- Graduate School and Faculty of Information Science and Electrical Engineering; Kyushu University; Hakozaki, Higashi-ku Fukuoka 812-8581 Japan
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10
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Mohanty S, Meinke JH, Zimmermann O. Folding of Top7 in unbiased all-atom Monte Carlo simulations. Proteins 2013; 81:1446-56. [DOI: 10.1002/prot.24295] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2012] [Revised: 03/05/2013] [Accepted: 03/17/2013] [Indexed: 02/04/2023]
Affiliation(s)
- Sandipan Mohanty
- Jülich Supercomputing Centre; Institute for Advanced Simulation; Forschungszentrum Jülich; D-52425; Jülich; Germany
| | - Jan H. Meinke
- Jülich Supercomputing Centre; Institute for Advanced Simulation; Forschungszentrum Jülich; D-52425; Jülich; Germany
| | - Olav Zimmermann
- Jülich Supercomputing Centre; Institute for Advanced Simulation; Forschungszentrum Jülich; D-52425; Jülich; Germany
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11
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Tang W, Zhou Q. Finding multiple minimum-energy conformations of the hydrophobic-polar protein model via multidomain sampling. PHYSICAL REVIEW. E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS 2012; 86:031909. [PMID: 23030946 DOI: 10.1103/physreve.86.031909] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2012] [Indexed: 06/01/2023]
Abstract
We demonstrate the efficiency of the multidomain sampler (MDS) in finding multiple distinct global minima and low-energy local minima in the hydrophobic-polar (HP) lattice protein model. Extending the idea of partitioning energy space in the Wang-Landau algorithm, our approach introduces an additional partitioning scheme to divide the protein conformation space into local basins of attraction. This double-partitioning design is very powerful in guiding the sampler to visit the basins of unexplored local minima. An H-residue subchain distance is used to merge the basins of similar local minima into one domain, which increases the diversity among identified minimum-energy conformations. Moreover, a visit-enhancement factor is introduced for long protein chains to facilitate jumps between basins. Results on three benchmark protein sequences reveal that our approach is capable of finding multiple global minima and hundreds of low-energy local minima of great diversity.
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Affiliation(s)
- Wei Tang
- Department of Materials Science and Engineering, University of California, Los Angeles, California 90095, USA
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12
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Folding helical proteins in explicit solvent using dihedral-biased tempering. Proc Natl Acad Sci U S A 2012; 109:8139-44. [PMID: 22573819 DOI: 10.1073/pnas.1112143109] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Using a single-trajectory-based tempering method with a high-temperature dihedral bias, we repeatedly folded four helical proteins [α(3)D (PDB ID: 2A3D, 73 residues), α(3)W (1LQ7, 67 residues), Fap1-NR(α) (2KUB, 81 residues) and S-836 (2JUA, 102 residues)] and some of the mutants in explicit solvent within several microseconds. The lowest root-mean-square deviations of backbone atoms from the experimentally determined structures were 1.9, 1.4, 1.0, and 2.1 Å, respectively. Cluster analyses of folding trajectories showed the native conformation usually occupied the most populated cluster. The simulation protocol can be applied to large-scale simulations of other helical proteins on commonly accessible computing platforms.
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13
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Singh P, Sarkar SK, Bandyopadhyay P. Understanding the applicability and limitations of Wang–Landau method for biomolecules: Met-enkephalin and Trp-cage. Chem Phys Lett 2011. [DOI: 10.1016/j.cplett.2011.08.053] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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14
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Chen H, Kihara D. Effect of using suboptimal alignments in template-based protein structure prediction. Proteins 2011; 79:315-34. [PMID: 21058297 PMCID: PMC3058269 DOI: 10.1002/prot.22885] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Computational protein structure prediction remains a challenging task in protein bioinformatics. In the recent years, the importance of template-based structure prediction is increasing because of the growing number of protein structures solved by the structural genomics projects. To capitalize the significant efforts and investments paid on the structural genomics projects, it is urgent to establish effective ways to use the solved structures as templates by developing methods for exploiting remotely related proteins that cannot be simply identified by homology. In this work, we examine the effect of using suboptimal alignments in template-based protein structure prediction. We showed that suboptimal alignments are often more accurate than the optimal one, and such accurate suboptimal alignments can occur even at a very low rank of the alignment score. Suboptimal alignments contain a significant number of correct amino acid residue contacts. Moreover, suboptimal alignments can improve template-based models when used as input to Modeller. Finally, we use suboptimal alignments for handling a contact potential in a probabilistic way in a threading program, SUPRB. The probabilistic contacts strategy outperforms the partly thawed approach, which only uses the optimal alignment in defining residue contacts, and also the re-ranking strategy, which uses the contact potential in re-ranking alignments. The comparison with existing methods in the template-recognition test shows that SUPRB is very competitive and outperforms existing methods.
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Affiliation(s)
- Hao Chen
- Department of Biological Sciences College of Science, Purdue University, West Lafayette, IN, 47907, USA
| | - Daisuke Kihara
- Department of Biological Sciences College of Science, Purdue University, West Lafayette, IN, 47907, USA
- Department of Computer Science College of Science, Purdue University, West Lafayette, IN, 47907, USA
- Markey Center for Structural Biology College of Science, Purdue University, West Lafayette, IN, 47907, USA
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15
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Underwood R, Tomlinson-Phillips J, Ben-Amotz D. Are Long-Chain Alkanes Hydrophilic? J Phys Chem B 2010; 114:8646-51. [PMID: 20553015 DOI: 10.1021/jp912089q] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Robin Underwood
- Purdue University, Department of Chemistry, 560 Oval Drive, West Lafayette, Indiana 47907
| | | | - Dor Ben-Amotz
- Purdue University, Department of Chemistry, 560 Oval Drive, West Lafayette, Indiana 47907
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16
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Bilsel M, Arkin H. Residue length and solvation model dependency of elastinlike polypeptides. PHYSICAL REVIEW. E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS 2010; 81:051906. [PMID: 20866260 DOI: 10.1103/physreve.81.051906] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/11/2010] [Indexed: 05/29/2023]
Abstract
We have performed exhaustive multicanonical Monte Carlo simulations of elastinlike polypeptides with a chain including amino acids (valine-proline-glycine-valine-glycine)n or in short (VPGVG)n, where n changes from 1 to 4, in order to investigate the thermodynamic and structural properties. To predict the characteristic secondary structure motifs of the molecules, Ramachandran plots were prepared and analyzed as well. In these studies, we utilized a realistic model where the interactions between all types of atoms were taken into account. Effects of solvation were also simulated by using an implicit-solvent model with two commonly used solvation parameter sets and compared with the vacuum case.
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Affiliation(s)
- Mustafa Bilsel
- Department of Physics Engineering, Ankara University, Tandoğan, Ankara 06100, Turkey.
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17
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Betancourt MR. Coarse-grained protein model with residue orientation energies derived from atomic force fields. J Phys Chem B 2010; 113:14824-30. [PMID: 19817469 DOI: 10.1021/jp906710c] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Coarse-grained models for protein simulations can potentially access longer time scales in larger protein systems than atomic-level models. Here, a coarse-grained residue pair potential, with distance and orientation dependency, is derived from equilibrium ensembles of residue pairs generated by molecular dynamics (MD). In particular, the Boltzmann inversion method is used to determine the energies. The residue pair potential is combined with local dihedral angle potentials for the backbone and side chains and used in the folding simulations of six small proteins, (28-67 residues) containing a variety of secondary structures. For the proteins tested, folding simulations by Monte Carlo methods generate structures similar to the native ones. However, these native-like structures were among the lowest in energy for alpha helical proteins but not for proteins containing extended beta structures. It is also found that a careful balance between local and nonlocal interactions is essential. Possibilities for improving coarse-grained models derived from atomic force fields are discussed.
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Affiliation(s)
- Marcos R Betancourt
- Department of Physics, Indiana University Purdue University Indianapolis, 402 North Blackford Street LD156-J, Indianapolis, Indiana 46202, USA.
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