Visualizing the superfamily of metallo-β-lactamases through sequence similarity network neighborhood connectivity analysis.

ABSTRACT: Protein sequence similarity networks (SSNs) constitute a convenient approach to analyze large polypeptide sequence datasets, and have been successfully applied to study a number of protein families over the past decade. SSN analysis is herein combined with traditional cladistic and phenetic phylogenetic analysis (respectively based on multiple sequence alignments and all-against-all three-dimensional protein structure comparisons) in order to assist the ancestral reconstruction and integrative revision of the superfamily of metallo-β-lactamases (MBLs). It is shown that only 198 out of 15,292 representative nodes contain at least one experimentally obtained protein structure in the Protein Data Bank or a manually annotated SwissProt entry, that is to say, only 1.3 % of the superfamily has b

SUBMITTER: Gonzalez JM 

PROVIDER: S-EPMC7785958 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature