Communications in Information and Systems

Volume 19 (2019)

Number 4

Reproducing ensemble averaged electrostatics with Super-Gaussian-based smooth dielectric function: application to electrostatic component of binding energy of protein complexes

Pages: 405 – 423

DOI: https://dx.doi.org/10.4310/CIS.2019.v19.n4.a4

Authors

Shailesh K. Panday (Department of Physics and Astronomy, Clemson University, Clemson, South Carolina, U.S.A.)

Mihiri H. B. Shashikala (Department of Physics and Astronomy, Clemson University, Clemson, South Carolina, U.S.A.)

Arghya Chakravorty (Department of Physics and Astronomy, Clemson University, Clemson, South Carolina, U.S.A.)

Shan Zhao (Department of Mathematics, University of Alabama, Tuscaloosa, Ala., U.S.A.)

Emil Alexov (Department of Physics and Astronomy, Clemson University, Clemson, South Carolina, U.S.A.)

Abstract

Proteins constantly sample various conformations as they carry their biological function, including interacting with their partners, and this should be taken into account in any numerical protocol aiming at computing their thermodynamic properties. Here we report an application of previously reported Super-Gaussian-based smooth dielectric function (J Math Biol., 2019 Jul; 79(2):631–672) to reproduce ensemble averaged electrostatics. This is an important achievement, since it dramatically reduces the computational demand for MM/PBSA applications and bypasses the necessity of long molecular dynamics simulations. Instead, a single frame, typically energy-minimized structure, in conjunction of Super-Gaussian-based smooth dielectric function, as implemented in DelPhi, can deliver ensemble averaged quantities. The approach is tested against ensemble averaged electrostatic component of binding free energy of protein-protein complexes. It is demonstrated that Super-Gaussian-based smooth dielectric function reproduces ensemble averaged quantities, resulting in correlation coefficients of about $0.8$ and slope of the fitting line of $1.0$.

Full Text (PDF format)

Received 22 October 2019

Published 15 April 2020