Literature DB >> 32155062

Capturing the Effects of Explicit Waters in Implicit Electrostatics Modeling: Qualitative Justification of Gaussian-Based Dielectric Models in DelPhi.

Arghya Chakravorty1, Shailesh Panday1, Swagata Pahari1, Shan Zhao2, Emil Alexov1.   

Abstract

Our group has implemented a smooth Gaussian-based dielectric function in DelPhi (J. Chem. Theory Comput. 2013, 9 (4), 2126-2136) which models the solute as an object with inhomogeneous dielectric permittivity and provides a smooth transition of dielectric permittivity from surface-bound water to bulk solvent. Although it is well-understood that the protein hydrophobic core is less polarizable than the hydrophilic protein surface, less attention is paid to the polarizability of water molecules inside the solute and on its surface. Here, we apply explicit water simulations to study the behavior of water molecules buried inside a protein and on the surface of that protein and contrast it with the behavior of the bulk water. We selected a protein that is experimentally shown to have five cavities, most of which are occupied by water molecules. We demonstrate through molecular dynamics (MD) simulations that the behavior of water in the cavity is drastically different from that in the bulk. These observations were made by comparing the mean residence times, dipole orientation relaxation times, and average dipole moment fluctuations. We also show that the bulk region has a nonuniform distribution of these tempo-spatial properties. From the perspective of continuum electrostatics, we argue that the dielectric "constant" in water-filled cavities of proteins and the space close to the molecular surface should differ from that assigned to the bulk water. This provides support for the Gaussian-based smooth dielectric model for solving electrostatics in the Poisson-Boltzmann equation framework. Furthermore, we demonstrate that using a well-parametrized Gaussian-based model with a single energy-minimized configuration of a protein can also reproduce its ensemble-averaged polar solvation energy. Thus, we argue that the Gaussian-based smooth dielectric model not only captures accurate physics but also provides an efficient way of computing ensemble-averaged quantities.

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Year:  2020        PMID: 32155062     DOI: 10.1021/acs.jcim.0c00151

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  4 in total

1.  Design, Simulation, and Development of a BioSensor for Viruses Detection Using FPGA.

Authors:  M Abdallah
Journal:  IEEE J Transl Eng Health Med       Date:  2021-02-01       Impact factor: 3.316

2.  BION-2: Predicting Positions of Non-Specifically Bound Ions on Protein Surface by a Gaussian-Based Treatment of Electrostatics.

Authors:  H B Mihiri Shashikala; Arghya Chakravorty; Shailesh Kumar Panday; Emil Alexov
Journal:  Int J Mol Sci       Date:  2020-12-29       Impact factor: 5.923

3.  Protein-Protein Binding Free Energy Predictions with the MM/PBSA Approach Complemented with the Gaussian-Based Method for Entropy Estimation.

Authors:  Shailesh Kumar Panday; Emil Alexov
Journal:  ACS Omega       Date:  2022-03-22

4.  Identification of Potential ACE2-Derived Peptide Mimetics in SARS-CoV-2 Omicron Variant Therapeutics using Computational Approaches.

Authors:  Stanly Paul; Swathi Nadendla; M Elizabeth Sobhia
Journal:  J Phys Chem Lett       Date:  2022-08-05       Impact factor: 6.888

  4 in total

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