Protein network centralities as descriptor for QM region construction in QM/MM simulations of enzymes

11 July 2023, Version 2
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

The construction of a suitable QM region is the most crucial step in setting up hybrid quantum mechanics / molecular mechanics (QM/MM) simulations for enzymatic reactions. The QM region should ideally include all important amino acids residues, while being as small as possible to save computational effort. Most available methods for systematic QM region construction are based either on the distance of single amino acids to the active site or on their electrostatic effect. Such approaches might miss non-electrostatic and long-range allosteric interactions. Here, we present a proof of concept study for the application of protein network analysis to tackle this problem. Specifically, we explore the use of the protein network centralities as descriptor for QM region construction. We find that protein network centralities, in particular the betweenness centrality, can be a useful descriptor for systematic QM region construction. We show that in combination with our previously developed point charge variation analysis, they can be used to identify important residues that are missed in purely electrostatic approaches.

Keywords

QM/MM

Supplementary materials

Title
Description
Actions
Title
Supporting Information
Description
Extended computational details, additional results for triosephosphate isomerase (TIM), supplementary tables showing descriptor rankings as well as the compositions of the different considered QM regions.
Actions

Supplementary weblinks

Comments

Comments are not moderated before they are posted, but they can be removed by the site moderators if they are found to be in contravention of our Commenting Policy [opens in a new tab] - please read this policy before you post. Comments should be used for scholarly discussion of the content in question. You can find more information about how to use the commenting feature here [opens in a new tab] .
This site is protected by reCAPTCHA and the Google Privacy Policy [opens in a new tab] and Terms of Service [opens in a new tab] apply.