Computational Prediction of Mutational Effects on SARS-CoV-2 Binding by Relative Free Energy Calculations.
Junjie ZouJian YinLei FangMingjun YangTianyuan WangWeikun WuMichael A BellucciPeiyu ZhangPublished in: Journal of chemical information and modeling (2020)
The ability of coronaviruses to infect humans is invariably associated with their binding strengths to human receptor proteins. Both SARS-CoV-2, initially named 2019-nCoV, and SARS-CoV were reported to utilize angiotensin-converting enzyme 2 (ACE2) as an entry receptor in human cells. To better understand the interplay between SARS-CoV-2 and ACE2, we performed computational alanine scanning mutagenesis on the "hotspot" residues at protein-protein interfaces using relative free energy calculations. Our data suggest that the mutations in SARS-CoV-2 lead to a greater binding affinity relative to SARS-CoV. In addition, our free energy calculations provide insight into the infectious ability of viruses on a physical basis and also provide useful information for the design of antiviral drugs.
Keyphrases
- sars cov
- angiotensin converting enzyme
- respiratory syndrome coronavirus
- angiotensin ii
- protein protein
- density functional theory
- molecular dynamics
- molecular dynamics simulations
- binding protein
- small molecule
- physical activity
- crispr cas
- dna binding
- mental health
- coronavirus disease
- healthcare
- high resolution
- electronic health record
- transcription factor
- health information
- artificial intelligence
- drug induced
- monte carlo