Computational Analysis Predicts Correlations among Amino Acids in SARS-CoV-2 Proteomes.

ABSTRACT: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a serious global challenge requiring urgent and permanent therapeutic solutions. These solutions can only be engineered if the patterns and rate of mutations of the virus can be elucidated. Predicting mutations and the structure of proteins based on these mutations have become necessary for early drug and vaccine design purposes in anticipation of future viral mutations. The amino acid composition (AAC) of proteomes and individual viral proteins provide avenues for exploitation since AACs have been previously used to predict structure, shape and evolutionary rates. Herein, the frequency of amino acid residues found in 1637 complete proteomes belonging to 11 SARS-CoV-2 variants/lineages were analyzed. Leucine is the most abunda

SUBMITTER: Broni E 

PROVIDER: S-EPMC9953644 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature