Lysostaphin is widely used in clinical settings against Staphylococcus aureus, but its mutants can abolish its killing activity. The difficulty in studies of mutations in lysostaphin is the shortage of data, which may need many decades to collect, although lysostaphin is so important for clinical therapeutics and drug development. In order not to passively wait for the accumulation of new data, in this study 1) the 23,442 mutations in 1408 proteins from databank were used to determine whether the mutations in lysostaphin follow the general mutation trend obtained from the databank, 2) the amino-acid pair predictability was used to explore the underlined mechanism for lysostaphin mutations, and 3) the amino-acid distribution probability was used to associate the mutation with dysfunction of lysostaphin. The results show that the mutations in lysostaphin follow the general trend of mutations in proteins; the underlined mechanism for mutations in lysostaphin is explainable from a viewpoint of randomness, and a mutation with increased distribution probability would have a larger chance to dysfunction lysostaphin. This study provides useful information for future design of anti-S. aureus drug and enzyme engineering.
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