CATH functional families predict functional sites in proteins | Zendy

Sayoni Das | Zendy; Harry Scholes | Zendy; Neeladri Sen | Zendy; Christine Orengo | Zendy

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CATH functional families predict functional sites in proteins

Author(s) -

Sayoni Das,

Harry Scholes,

Neeladri Sen,

Christine Orengo

Publication year - 2020

Publication title -

bioinformatics

Language(s) - Uncategorized

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btaa937

Subject(s) - computer science , functional analysis , identification (biology) , sequence (biology) , computational biology , machine learning , artificial intelligence , data mining , biology , genetics , gene , botany

Identification of functional sites in proteins is essential for functional characterization, variant interpretation and drug design. Several methods are available for predicting either a generic functional site, or specific types of functional site. Here, we present FunSite, a machine learning predictor that identifies catalytic, ligand-binding and protein-protein interaction functional sites using features derived from protein sequence and structure, and evolutionary data from CATH functional families (FunFams).

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