Identifying metal binding amino acids based on backbone geometries as a tool for metalloprotein engineering.

ABSTRACT: Metal cofactors within proteins perform a versatile set of essential cellular functions. In order to take advantage of the diverse functionality of metalloproteins, researchers have been working to design or modify metal binding sites in proteins to rationally tune the function or activity of the metal cofactor. This study has performed an analysis on the backbone atom geometries of metal-binding amino acids among 10 different metal binding sites within the entire protein data bank. A set of 13 geometric parameters (features) was identified that is capable of predicting the presence of a metal cofactor in the protein structure with overall accuracies of up to 97% given only the relative positions of their backbone atoms. The decision tree machine-learning algorithm used can quickly analyze

SUBMITTER: Nguyen H 

PROVIDER: S-EPMC8138524 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature