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Kawamoto S, Liu H, Miyazaki Y, Seo S, Dixit M, DeVane R, MacDermaid C, Fiorin G, Klein ML, Shinoda W. SPICA Force Field for Proteins and Peptides. J Chem Theory Comput 2022; 18:3204-3217. [PMID: 35413197 DOI: 10.1021/acs.jctc.1c01207] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
A coarse-grained (CG) model for peptides and proteins was developed as an extension of the Surface Property fItting Coarse grAined (SPICA) force field (FF). The model was designed to examine membrane proteins that are fully compatible with the lipid membranes of the SPICA FF. A preliminary version of this protein model was created using thermodynamic properties, including the surface tension and density in the SPICA (formerly called SDK) FF. In this study, we improved the CG protein model to facilitate molecular dynamics (MD) simulations with a reproduction of multiple properties from both experiments and all-atom (AA) simulations. An elastic network model was adopted to maintain the secondary structure within a single chain. The side-chain analogues reproduced the transfer free energy profiles across the lipid membrane and demonstrated reasonable association free energy (potential of mean force) in water compared to those from AA MD. A series of peptides/proteins adsorbed onto or penetrated into the membrane simulated by the CG MD correctly predicted the penetration depths and tilt angles of peripheral and transmembrane peptides/proteins as comparable to those in the orientations of proteins in membranes (OPM) database. In addition, the dimerization free energies of several transmembrane helices within a lipid bilayer were comparable to those from experimental estimation. Application studies on a series of membrane protein assemblies, scramblases, and poliovirus capsids demonstrated the good performance of the SPICA FF.
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Affiliation(s)
- Shuhei Kawamoto
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
| | - Huihui Liu
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
| | - Yusuke Miyazaki
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan.,Research Institute for Interdisciplinary Science, Okayama University, 3-1-1 Tsushima-naka, Kita-ku, Okayama 700-8530, Japan
| | - Sangjae Seo
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan.,Korea Institute of Science and Technology Information, 245 Daehak-ro, Daejeon 34141, Republic of Korea
| | - Mayank Dixit
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
| | - Russell DeVane
- Modeling & Simulation, Corporate Research & Development, The Procter and Gamble Company, West Chester, Ohio 45069, United States
| | - Christopher MacDermaid
- Institute for Computational Molecular Science, Temple University, 1925 North 12th Street, Philadelphia, Pennsylvania 19122, United States
| | - Giacomo Fiorin
- Institute for Computational Molecular Science, Temple University, 1925 North 12th Street, Philadelphia, Pennsylvania 19122, United States
| | - Michael L Klein
- Institute for Computational Molecular Science, Temple University, 1925 North 12th Street, Philadelphia, Pennsylvania 19122, United States
| | - Wataru Shinoda
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan.,Research Institute for Interdisciplinary Science, Okayama University, 3-1-1 Tsushima-naka, Kita-ku, Okayama 700-8530, Japan.,Department of Chemistry, Faculty of Science, Okayama University, 3-1-1 Tsushima-naka, Kita-ku, Okayama 700-8530, Japan
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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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Kapoor A, Travesset A. Mechanism of the exchange reaction in HRAS from multiscale modeling. PLoS One 2014; 9:e108846. [PMID: 25272152 PMCID: PMC4182752 DOI: 10.1371/journal.pone.0108846] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2014] [Accepted: 08/28/2014] [Indexed: 11/28/2022] Open
Abstract
HRAS regulates cell growth promoting signaling processes by cycling between active (GTP-bound) and inactive (GDP-bound) states. Understanding the transition mechanism is central for the design of small molecules to inhibit the formation of RAS-driven tumors. Using a multiscale approach involving coarse-grained (CG) simulations, all-atom classical molecular dynamics (CMD; total of 3.02 µs), and steered molecular dynamics (SMD) in combination with Principal Component Analysis (PCA), we identified the structural features that determine the nucleotide (GDP) exchange reaction. We show that weakening the coupling between the SwitchI (residues 25–40) and SwitchII (residues 59–75) accelerates the opening of SwitchI; however, an open conformation of SwitchI is unstable in the absence of guanine nucleotide exchange factors (GEFs) and rises up towards the bound nucleotide to close the nucleotide pocket. Both I21 and Y32, play a crucial role in SwitchI transition. We show that an open SwitchI conformation is not necessary for GDP destabilization but is required for GDP/Mg escape from the HRAS. Further, we present the first simulation study showing displacement of GDP/Mg away from the nucleotide pocket. Both SwitchI and SwitchII, delays the escape of displaced GDP/Mg in the absence of GEF. Based on these results, a model for the mechanism of GEF in accelerating the exchange process is hypothesized.
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Affiliation(s)
- Abhijeet Kapoor
- Physics and Astronomy, Iowa State University, Ames, Iowa, United States of America
- * E-mail:
| | - Alex Travesset
- Physics and Astronomy, Iowa State University, Ames, Iowa, United States of America
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Sterpone F, Melchionna S, Tuffery P, Pasquali S, Mousseau N, Cragnolini T, Chebaro Y, St-Pierre JF, Kalimeri M, Barducci A, Laurin Y, Tek A, Baaden M, Nguyen PH, Derreumaux P. The OPEP protein model: from single molecules, amyloid formation, crowding and hydrodynamics to DNA/RNA systems. Chem Soc Rev 2014; 43:4871-93. [PMID: 24759934 PMCID: PMC4426487 DOI: 10.1039/c4cs00048j] [Citation(s) in RCA: 120] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The OPEP coarse-grained protein model has been applied to a wide range of applications since its first release 15 years ago. The model, which combines energetic and structural accuracy and chemical specificity, allows the study of single protein properties, DNA-RNA complexes, amyloid fibril formation and protein suspensions in a crowded environment. Here we first review the current state of the model and the most exciting applications using advanced conformational sampling methods. We then present the current limitations and a perspective on the ongoing developments.
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Affiliation(s)
- Fabio Sterpone
- Laboratoire de Biochimie Théorique, UPR 9080 CNRS, Université Paris Diderot, Sorbonne Paris Cité, IBPC, 13 rue Pierre et Marie Curie, 75005, Paris, France.
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