Computational modeling of protein conformational changes - Application to the opening SARS-CoV-2 spike

Anna Kucherova; Selma Strango; Shahar Sukenik; Maxime Theillard

doi:10.1016/j.jcp.2021.110591

Computational modeling of protein conformational changes - Application to the opening SARS-CoV-2 spike

J Comput Phys. 2021 Nov 1:444:110591. doi: 10.1016/j.jcp.2021.110591. Epub 2021 Jul 26.

Authors

Anna Kucherova¹, Selma Strango¹, Shahar Sukenik², Maxime Theillard¹

Affiliations

¹ Department of Applied Mathematics, University of California, Merced, CA 95343, USA.
² Department of Chemistry and Chemical Biology, University of California, Merced, CA 95343, USA.

Abstract

We present a new approach to compute and analyze the dynamical electro-geometric properties of proteins undergoing conformational changes. The molecular trajectory is obtained from Markov state models, and the electrostatic potential is calculated using the continuum Poisson-Boltzmann equation. The numerical electric potential is constructed using a parallel sharp numerical solver implemented on adaptive Octree grids. We introduce novel a posteriori error estimates to quantify the solution's accuracy on the molecular surface. To illustrate the approach, we consider the opening of the SARS-CoV-2 spike protein using the recent molecular trajectory simulated through the Folding@home initiative. We analyze our results, focusing on the characteristics of the receptor-binding domain and its vicinity. This work lays the foundation for a new class of hybrid computational approaches, producing high-fidelity dynamical computational measurements serving as a basis for protein bio-mechanism investigations.

Keywords: Covid-19; Molecular trajectory; Multiscale modeling; Poisson-Boltzmann; SARS-CoV-2; Spike protein.