Amino acid positions subject to multiple coevolutionary constraints can be robustly identified by their eigenvector network centrality scores.

ABSTRACT: As proteins evolve, amino acid positions key to protein structure or function are subject to mutational constraints. These positions can be detected by analyzing sequence families for amino acid conservation or for coevolution between pairs of positions. Coevolutionary scores are usually rank-ordered and thresholded to reveal the top pairwise scores, but they also can be treated as weighted networks. Here, we used network analyses to bypass a major complication of coevolution studies: For a given sequence alignment, alternative algorithms usually identify different, top pairwise scores. We reconciled results from five commonly-used, mathematically divergent algorithms (ELSC, McBASC, OMES, SCA, and ZNMI), using the LacI/GalR and 1,6-bisphosphate aldolase protein families as models. Calculat

SUBMITTER: Parente DJ 

PROVIDER: S-EPMC4715571 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature