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      Crowding in Cellular Environments at an Atomistic Level from Computer Simulations

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          Abstract

          The effects of crowding in biological environments on biomolecular structure, dynamics, and function remain not well understood. Computer simulations of atomistic models of concentrated peptide and protein systems at different levels of complexity are beginning to provide new insights. Crowding, weak interactions with other macromolecules and metabolites, and altered solvent properties within cellular environments appear to remodel the energy landscape of peptides and proteins in significant ways including the possibility of native state destabilization. Crowding is also seen to affect dynamic properties, both conformational dynamics and diffusional properties of macromolecules. Recent simulations that address these questions are reviewed here and discussed in the context of relevant experiments.

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          Monte Carlo free energy estimates using non-Boltzmann sampling: Application to the sub-critical Lennard-Jones fluid

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            Is Open Access

            New ways to boost molecular dynamics simulations

            We describe a set of algorithms that allow to simulate dihydrofolate reductase (DHFR, a common benchmark) with the AMBER all‐atom force field at 160 nanoseconds/day on a single Intel Core i7 5960X CPU (no graphics processing unit (GPU), 23,786 atoms, particle mesh Ewald (PME), 8.0 Å cutoff, correct atom masses, reproducible trajectory, CPU with 3.6 GHz, no turbo boost, 8 AVX registers). The new features include a mixed multiple time‐step algorithm (reaching 5 fs), a tuned version of LINCS to constrain bond angles, the fusion of pair list creation and force calculation, pressure coupling with a “densostat,” and exploitation of new CPU instruction sets like AVX2. The impact of Intel's new transactional memory, atomic instructions, and sloppy pair lists is also analyzed. The algorithms map well to GPUs and can automatically handle most Protein Data Bank (PDB) files including ligands. An implementation is available as part of the YASARA molecular modeling and simulation program from www.YASARA.org. © 2015 The Authors Journal of Computational Chemistry Published by Wiley Periodicals, Inc.
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              System-Size Dependence of Diffusion Coefficients and Viscosities from Molecular Dynamics Simulations with Periodic Boundary Conditions

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                Author and article information

                Journal
                J Phys Chem B
                J Phys Chem B
                jp
                jpcbfk
                The Journal of Physical Chemistry. B
                American Chemical Society
                1520-6106
                1520-5207
                30 June 2017
                31 August 2017
                : 121
                : 34
                : 8009-8025
                Affiliations
                []Department of Biochemistry and Molecular Biology, Michigan State University , East Lansing, Michigan, United States
                []Quantitative Biology Center, RIKEN , Kobe, Japan
                [§ ]Theoretical Molecular Science Laboratory, RIKEN , Wako, Japan
                []iTHES Research Group, RIKEN , Wako, Japan
                []Advanced Institute for Computational Science, RIKEN , Kobe, Japan
                Author notes
                [* ]Address: 603 Wilson Road, Room BCH 218, East Lansing, MI, 48824. E-mail: feig@ 123456msu.edu . Phone: +1 (517) 432-7439. Fax: +1 (517) 353-9334.
                Article
                10.1021/acs.jpcb.7b03570
                5582368
                28666087
                f06032d8-973e-4259-bf1d-33f6ab2d1392
                Copyright © 2017 American Chemical Society

                This is an open access article published under an ACS AuthorChoice License, which permits copying and redistribution of the article or any adaptations for non-commercial purposes.

                History
                : 15 April 2017
                : 15 June 2017
                Categories
                Feature Article
                Custom metadata
                jp7b03570
                jp-2017-03570f

                Physical chemistry
                Physical chemistry

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