Literature DB >> 25443957

Recent advances in transferable coarse-grained modeling of proteins.

Parimal Kar1, Michael Feig2.   

Abstract

Computer simulations are indispensable tools for studying the structure and dynamics of biological macromolecules. Biochemical processes occur on different scales of length and time. Atomistic simulations cannot cover the relevant spatiotemporal scales at which the cellular processes occur. To address this challenge, coarse-grained (CG) modeling of the biological systems is employed. Over the last few years, many CG models for proteins continue to be developed. However, many of them are not transferable with respect to different systems and different environments. In this review, we discuss those CG protein models that are transferable and that retain chemical specificity. We restrict ourselves to CG models of soluble proteins only. We also briefly review recent progress made in the multiscale hybrid all-atom/CG simulations of proteins.
© 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Coarse graining; Force field; Molecular dynamics; Multiscale; Protein folding; Protein–protein interactions

Mesh:

Substances:

Year:  2014        PMID: 25443957      PMCID: PMC5366245          DOI: 10.1016/bs.apcsb.2014.06.005

Source DB:  PubMed          Journal:  Adv Protein Chem Struct Biol        ISSN: 1876-1623            Impact factor:   3.507


  142 in total

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Authors:  Gia G Maisuradze; Adam Liwo; Harold A Scheraga
Journal:  J Chem Theory Comput       Date:  2010-02-09       Impact factor: 6.006

6.  Differential mismatch recognition specificities of eukaryotic MutS homologs, MutSα and MutSβ.

Authors:  Monika Sharma; Alexander V Predeus; Nicholas Kovacs; Michael Feig
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Authors:  Qiang Shi; Sergei Izvekov; Gregory A Voth
Journal:  J Phys Chem B       Date:  2006-08-10       Impact factor: 2.991

8.  Parameterization of PACE Force Field for Membrane Environment and Simulation of Helical Peptides and Helix-Helix Association.

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Journal:  J Chem Theory Comput       Date:  2011-12-01       Impact factor: 6.006

9.  Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone φ, ψ and side-chain χ(1) and χ(2) dihedral angles.

Authors:  Robert B Best; Xiao Zhu; Jihyun Shim; Pedro E M Lopes; Jeetain Mittal; Michael Feig; Alexander D Mackerell
Journal:  J Chem Theory Comput       Date:  2012-07-18       Impact factor: 6.006

10.  The power of coarse graining in biomolecular simulations.

Authors:  Helgi I Ingólfsson; Cesar A Lopez; Jaakko J Uusitalo; Djurre H de Jong; Srinivasa M Gopal; Xavier Periole; Siewert J Marrink
Journal:  Wiley Interdiscip Rev Comput Mol Sci       Date:  2014-05
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  7 in total

1.  Enhanced Sampling of Coarse-Grained Transmembrane-Peptide Structure Formation from Hydrogen-Bond Replica Exchange.

Authors:  Tristan Bereau; Markus Deserno
Journal:  J Membr Biol       Date:  2014-10-14       Impact factor: 1.843

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Review 3.  Unifying coarse-grained force fields for folded and disordered proteins.

Authors:  Andrew P Latham; Bin Zhang
Journal:  Curr Opin Struct Biol       Date:  2021-09-15       Impact factor: 7.786

4.  Hybrid All-Atom/Coarse-Grained Simulations of Proteins by Direct Coupling of CHARMM and PRIMO Force Fields.

Authors:  Parimal Kar; Michael Feig
Journal:  J Chem Theory Comput       Date:  2017-10-19       Impact factor: 6.006

5.  Characterizing the function of domain linkers in regulating the dynamics of multi-domain fusion proteins by microsecond molecular dynamics simulations and artificial intelligence.

Authors:  Bo Wang; Zhaoqian Su; Yinghao Wu
Journal:  Proteins       Date:  2021-03-27

6.  Crowding in Cellular Environments at an Atomistic Level from Computer Simulations.

Authors:  Michael Feig; Isseki Yu; Po-Hung Wang; Grzegorz Nawrocki; Yuji Sugita
Journal:  J Phys Chem B       Date:  2017-07-12       Impact factor: 2.991

Review 7.  Modeling of Disordered Protein Structures Using Monte Carlo Simulations and Knowledge-Based Statistical Force Fields.

Authors:  Maciej Pawel Ciemny; Aleksandra Elzbieta Badaczewska-Dawid; Monika Pikuzinska; Andrzej Kolinski; Sebastian Kmiecik
Journal:  Int J Mol Sci       Date:  2019-01-31       Impact factor: 5.923

  7 in total

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