PT  - JOURNAL ARTICLE
AU  - Daniele Granata
AU  - Luca Ponzoni
AU  - Cristian Micheletti
AU  - Vincenzo Carnevale
TI  - From Sequence to Function: Coevolving Amino Acids Encode Structural and Functional Domains
AID  - 10.1101/109397
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 109397
4099  - http://biorxiv.org/content/early/2017/02/17/109397.short
4100  - http://biorxiv.org/content/early/2017/02/17/109397.full
AB  - Amino acids interactions within protein families are so optimized that the sole analysis of evolutionary co-mutations can identify pairs of contacting residues. It is also known that evolution conserves functional dynamics, i.e., the concerted motion or displacement of large protein regions or domains. Is it, therefore, possible to use a pure sequence-based analysis to identify these dynamical domains? To address this question, we introduce here a general co-evolutionary coupling analysis strategy and apply it to a curated sequence database of hundreds of protein families. For most families, the sequence-based method partitions amino acids into few clusters. When viewed in the context of the native structure, these clusters have the signature characteristics of viable protein domains: they are spatially separated but individually compact. They have a direct functional bearings too, as shown for various reference cases. We conclude that even large-scale structural and functionally-related properties can be recovered from inference methods applied to evolutionary-related sequences. The method introduced here is available as a software package and web server (http://spectrus.sissa.it/spectrus-evo_webserver).