RESUMO
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-ß-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 been functionally and/or structurally characterized. Besides, neighborhood connectivity coloring, which measures local network interconnectivity, is introduced for detection of protein families within SSN clusters. This approach provides a clear picture of how many families remain unexplored in the superfamily, while most MBL research is heavily biased towards a few families. Further research is suggested in order to determine the SSN topological properties, which will be instrumental for the improvement of automated sequence annotation methods.
RESUMO
BACKGROUND: Sedolisins are acid proteases that are related to the basic subtilisins. They have been identified in all three superkingdoms but are not ubiquitous, although fungi that secrete acids as part of their lifestyle can have up to six paralogs. Both TriPeptidyl Peptidase (TPP) and endopeptidase activity have been identified and it has been suggested that these correspond to separate subfamilies. RESULTS: We studied eukaryotic sedolisins by computational analysis. A maximum likelihood tree shows one major clade containing non-fungal sequences only and two major as well as two minor clades containing only fungal sequences. One of the major fungal clades contains all known TPPs whereas the other contains characterized endosedolisins. We identified four Cluster Specific Inserts (CSIs) in endosedolisins, of which CSIs 1, 3 and 4 appear as solvent exposed according to structure modeling. Part of CSI2 is exposed but a short stretch forms a novel and partially buried α-helix that induces a conformational change near the binding pocket. We also identified a total of 15 specificity determining positions (SDPs) of which five, identified in two independent analyses, form highly connected SDP sub-networks. Modeling of virtual mutants suggests a key role for the W307A or F307A substitution. The remaining four key SDPs physically interact at the interface of the catalytic domain and the enzyme's prosegment. Modeling of virtual mutants suggests these SDPs are indeed required to compensate the conformational change induced by CSI2 and the A307. One of the two small fungal clades concerns a subfamily that contains 213 sequences, is mostly similar to the major TPP subfamily but differs, interestingly, in position 307, showing mostly isoleucine and threonine. CONCLUSIONS: Analysis confirms there are at least two sedolisin subfamilies in fungi: TPPs and endopeptidases, and suggests a third subfamily with unknown characteristics. Sequence and functional diversification was centered around buried SDP307 and resulted in a conformational change of the pocket. Mutual Information network analysis forms a useful instrument in the corroboration of predicted SDPs.