Literature DB >> 26589015

Consistent View of Protein Fluctuations from All-Atom Molecular Dynamics and Coarse-Grained Dynamics with Knowledge-Based Force-Field.

Michal Jamroz1, Modesto Orozco2,3, Andrzej Kolinski1, Sebastian Kmiecik1.   

Abstract

It is widely recognized that atomistic Molecular Dynamics (MD), a classical simulation method, captures the essential physics of protein dynamics. That idea is supported by a theoretical study showing that various MD force-fields provide a consensus picture of protein fluctuations in aqueous solution [Rueda, M. et al. Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 796-801]. However, atomistic MD cannot be applied to most biologically relevant processes due to its limitation to relatively short time scales. Much longer time scales can be accessed by properly designed coarse-grained models. We demonstrate that the aforementioned consensus view of protein dynamics from short (nanosecond) time scale MD simulations is fairly consistent with the dynamics of the coarse-grained protein model - the CABS model. The CABS model employs stochastic dynamics (a Monte Carlo method) and a knowledge-based force-field, which is not biased toward the native structure of a simulated protein. Since CABS-based dynamics allows for the simulation of entire folding (or multiple folding events) in a single run, integration of the CABS approach with all-atom MD promises a convenient (and computationally feasible) means for the long-time multiscale molecular modeling of protein systems with atomistic resolution.

Year:  2012        PMID: 26589015     DOI: 10.1021/ct300854w

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  27 in total

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Journal:  Biotechnol Appl Biochem       Date:  2020-05-23       Impact factor: 2.431

3.  Performance of protein-structure predictions with the physics-based UNRES force field in CASP11.

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Journal:  Bioinformatics       Date:  2016-07-04       Impact factor: 6.937

4.  Molecular dynamics of protein A and a WW domain with a united-residue model including hydrodynamic interaction.

Authors:  Agnieszka G Lipska; Steven R Seidman; Adam K Sieradzan; Artur Giełdoń; Adam Liwo; Harold A Scheraga
Journal:  J Chem Phys       Date:  2016-05-14       Impact factor: 3.488

5.  Flexible docking of peptides to proteins using CABS-dock.

Authors:  Mateusz Kurcinski; Aleksandra Badaczewska-Dawid; Michal Kolinski; Andrzej Kolinski; Sebastian Kmiecik
Journal:  Protein Sci       Date:  2019-11-11       Impact factor: 6.725

6.  AGGRESCAN3D (A3D): server for prediction of aggregation properties of protein structures.

Authors:  Rafael Zambrano; Michal Jamroz; Agata Szczasiuk; Jordi Pujols; Sebastian Kmiecik; Salvador Ventura
Journal:  Nucleic Acids Res       Date:  2015-04-16       Impact factor: 16.971

7.  Computational Models for the Study of Protein Aggregation.

Authors:  Nguyen Truong Co; Mai Suan Li; Pawel Krupa
Journal:  Methods Mol Biol       Date:  2022

8.  CABS-flex: Server for fast simulation of protein structure fluctuations.

Authors:  Michal Jamroz; Andrzej Kolinski; Sebastian Kmiecik
Journal:  Nucleic Acids Res       Date:  2013-05-08       Impact factor: 16.971

9.  Functional characterization of two type-1 diacylglycerol acyltransferase (DGAT1) genes from rice (Oryza sativa) embryo restoring the triacylglycerol accumulation in yeast.

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Journal:  Plant Mol Biol       Date:  2020-10-21       Impact factor: 4.076

10.  Combining coarse-grained protein models with replica-exchange all-atom molecular dynamics.

Authors:  Jacek Wabik; Sebastian Kmiecik; Dominik Gront; Maksim Kouza; Andrzej Koliński
Journal:  Int J Mol Sci       Date:  2013-05-10       Impact factor: 5.923

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