Literature DB >> 22678152

On developing coarse-grained models for biomolecular simulation: a review.

Sereina Riniker1, Jane R Allison, Wilfred F van Gunsteren.   

Abstract

So-called coarse-grained models are a popular type of model for accessing long time scales in simulations of biomolecular processes. Such models are coarse-grained with respect to atomic models. But any modelling of processes or substances involves coarse-graining, i.e. the elimination of non-essential degrees of freedom and interactions from a more fine-grained level of modelling. The basic ingredients of developing coarse-grained models based on the properties of fine-grained models are reviewed, together with the conditions that must be satisfied in order to preserve the correct physical mechanisms in the coarse-graining process. This overview should help the reader to determine how realistic a coarse-grained model of a biomolecular system is, i.e. whether it reflects the underlying physical mechanisms or merely provides a set of pretty pictures of the process or substances of interest.

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Year:  2012        PMID: 22678152     DOI: 10.1039/c2cp40934h

Source DB:  PubMed          Journal:  Phys Chem Chem Phys        ISSN: 1463-9076            Impact factor:   3.676


  27 in total

1.  Tabulation as a high-resolution alternative to coarse-graining protein interactions: Initial application to virus capsid subunits.

Authors:  Justin Spiriti; Daniel M Zuckerman
Journal:  J Chem Phys       Date:  2015-12-28       Impact factor: 3.488

Review 2.  Metal Ion Modeling Using Classical Mechanics.

Authors:  Pengfei Li; Kenneth M Merz
Journal:  Chem Rev       Date:  2017-01-03       Impact factor: 60.622

3.  Hydration Properties and Solvent Effects for All-Atom Solutes in Polarizable Coarse-Grained Water.

Authors:  Xin Cindy Yan; Julian Tirado-Rives; William L Jorgensen
Journal:  J Phys Chem B       Date:  2016-03-01       Impact factor: 2.991

4.  Coarse-grained simulations of protein-protein association: an energy landscape perspective.

Authors:  Krishnakumar M Ravikumar; Wei Huang; Sichun Yang
Journal:  Biophys J       Date:  2012-08-22       Impact factor: 4.033

5.  Characterization of Lipid-Protein Interactions and Lipid-Mediated Modulation of Membrane Protein Function through Molecular Simulation.

Authors:  Melanie P Muller; Tao Jiang; Chang Sun; Muyun Lihan; Shashank Pant; Paween Mahinthichaichan; Anda Trifan; Emad Tajkhorshid
Journal:  Chem Rev       Date:  2019-04-12       Impact factor: 60.622

6.  A multiscale biomechanical model of platelets: Correlating with in-vitro results.

Authors:  Peng Zhang; Li Zhang; Marvin J Slepian; Yuefan Deng; Danny Bluestein
Journal:  J Biomech       Date:  2016-11-11       Impact factor: 2.712

7.  Multiscale Particle-Based Modeling of Flowing Platelets in Blood Plasma Using Dissipative Particle Dynamics and Coarse Grained Molecular Dynamics.

Authors:  Peng Zhang; Chao Gao; Na Zhang; Marvin J Slepian; Yuefan Deng; Danny Bluestein
Journal:  Cell Mol Bioeng       Date:  2014-12-01       Impact factor: 2.321

8.  A phenomenological particle-based platelet model for simulating filopodia formation during early activation.

Authors:  Seetha Pothapragada; Peng Zhang; Jawaad Sheriff; Mark Livelli; Marvin J Slepian; Yuefan Deng; Danny Bluestein
Journal:  Int J Numer Method Biomed Eng       Date:  2015-03       Impact factor: 2.747

9.  Coarse-grained model for colloidal protein interactions, B(22), and protein cluster formation.

Authors:  Marco A Blanco; Erinc Sahin; Anne S Robinson; Christopher J Roberts
Journal:  J Phys Chem B       Date:  2013-12-10       Impact factor: 2.991

10.  Parametrization of Backbone Flexibility in a Coarse-Grained Force Field for Proteins (COFFDROP) Derived from All-Atom Explicit-Solvent Molecular Dynamics Simulations of All Possible Two-Residue Peptides.

Authors:  Tamara Frembgen-Kesner; Casey T Andrews; Shuxiang Li; Nguyet Anh Ngo; Scott A Shubert; Aakash Jain; Oluwatoni J Olayiwola; Mitch R Weishaar; Adrian H Elcock
Journal:  J Chem Theory Comput       Date:  2015-04-30       Impact factor: 6.006

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