Literature DB >> 30682885

Characterizing Solvent Density Fluctuations in Dynamical Observation Volumes.

Zhitong Jiang, Richard C Remsing1, Nicholas B Rego, Amish J Patel.   

Abstract

Hydrophobic effects drive diverse aqueous assemblies, such as micelle formation or protein folding, wherein the solvent plays an important role. Consequently, characterizing the free energetics of solvent density fluctuations can lead to important insights into these processes. Although techniques such as the indirect umbrella sampling (INDUS) method can be used to characterize solvent fluctuations in static observation volumes of various sizes and shapes, characterizing how the solvent mediates inherently dynamic processes, such as self-assembly or conformational change, remains a challenge. In this work, we generalize the INDUS method to facilitate the enhanced sampling of solvent fluctuations in dynamical observation volumes, whose positions and shapes can evolve. We illustrate the usefulness of this generalization by characterizing water density fluctuations in dynamical volumes pertaining to the hydration of flexible solutes, the assembly of small hydrophobes, and conformational transitions in a model peptide. We also use the method to probe the dynamics of hard spheres.

Entities:  

Year:  2019        PMID: 30682885     DOI: 10.1021/acs.jpcb.8b11423

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  2 in total

1.  Identifying hydrophobic protein patches to inform protein interaction interfaces.

Authors:  Nicholas B Rego; Erte Xi; Amish J Patel
Journal:  Proc Natl Acad Sci U S A       Date:  2021-02-09       Impact factor: 11.205

2.  A generalized deep learning approach for local structure identification in molecular simulations.

Authors:  Ryan S DeFever; Colin Targonski; Steven W Hall; Melissa C Smith; Sapna Sarupria
Journal:  Chem Sci       Date:  2019-07-11       Impact factor: 9.825

  2 in total

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