Computational optimization of angiotensin-converting enzyme 2 for SARS-CoV-2 Spike molecular recognition.

ABSTRACT: Since the beginning of the Covid19 pandemic, many efforts have been devoted to identifying approaches to neutralize SARS-CoV-2 replication within the host cell. A promising strategy to block the infection consists of using a mutant of the human receptor angiotensin-converting enzyme 2 (ACE2) as a decoy to compete with endogenous ACE2 for the binding to the SARS-CoV-2 Spike protein, which decreases the ability of the virus to enter the host cell. Here, using a computational framework based on the 2D Zernike formalism we investigate details of the molecular binding and evaluate the changes in ACE2-Spike binding compatibility upon mutations occurring in the ACE2 side of the molecular interface. We demonstrate the efficacy of our method by comparing our results with experimental binding affini

SUBMITTER: Di Rienzo L 

PROVIDER: S-EPMC8116125 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature