Residue Cluster Classes: A Unified Protein Representation for Efficient Structural and Functional Classification.

ABSTRACT: Proteins are characterized by their structures and functions, and these two fundamental aspects of proteins are assumed to be related. To model such a relationship, a single representation to model both protein structure and function would be convenient, yet so far, the most effective models for protein structure or function classification do not rely on the same protein representation. Here we provide a computationally efficient implementation for large datasets to calculate residue cluster classes (RCCs) from protein three-dimensional structures and show that such representations enable a random forest algorithm to effectively learn the structural and functional classifications of proteins, according to the CATH and Gene Ontology criteria, respectively. RCCs are derived from residue cont

SUBMITTER: Fontove F 

PROVIDER: S-EPMC7516957 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature