Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites

Abstract

Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.