Abstract
Abstract
Context
Since the outbreak of COVID-19 in 2019, the 2019-nCov
coronavirus has appeared diverse mutational characteristics due to its own
flexible conformation. One multiple-mutant strain (Omicron) with surprisingly
infective activity outburst, and affected the biological activities of current
drugs and vaccines, making the epidemic significantly difficult to prevent and
control, and seriously threaten health around the world. Importunately
exploration of mutant characteristics for novel coronavirus Omicron can supply
strong theoretical guidance for learning binding mechanism of mutant viruses.
What’s more, full acknowledgement of key mutated-residues on Omicron strain can
provide new methodology of the novel pathogenic mechanism to human ACE2
receptor, as well as the subsequent vaccine development.
Methods
In this research, 3D structures of 32 single-point mutations
of 2019-nCov were firstly constructed, and 32-sites multiple-mutant Omicron
were finally obtained based one the wild-type virus by homology modeling method.
One total number of 33 2019-nCov/ACE2 complex systems were acquired by
protein-protein docking, and optimized by using preliminary molecular dynamic
simulations. Binding free energies between each 2019-nCov mutation system and
human ACE2 receptor were calculated, and corresponding binding patterns
especially the regions adjacent to mutation site were analyzed. The results
indicated that one total number of 6 mutated sites on the Omicron strain played
crucial role in improving binding capacities from 2019-nCov to ACE2 protein.
Subsequently, we performed long-term molecular dynamic simulations and
protein-protein binding energy analysis for the selected 6 mutations. 3
infected individuals, the mutants T478K, Q493R and G496S with lower binding
energies -66.36, -67.98 and -67.09 kcal/mol also presents the high infectivity.
These findings indicated that the 3 mutations T478K, Q493R and G496S play the
crucial roles in enhancing binding affinity of Omicron to human ACE2 protein.
All these results illuminate important theoretical guidance for future virus
detection of the Omicron epidemic, drug research and vaccine development.
Funder
Beijing-Tianjin-Hebei Special Project of Beijing Natural Science Foundation
CAMS Innovation Fund for Medical Sciences (CIFMS) grant
National Natural Science Foundation of China Grant
R&D Program of Beijing Municipal Education Commission
Publisher
Springer Science and Business Media LLC
Subject
Computational Theory and Mathematics,Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Catalysis