Simple Coordination Geometry Descriptors Allow to Accurately Predict Metal-Binding Sites in Proteins.

ABSTRACT: With more than a third of the genome encoding for metal-containing biomolecules, the in silico prediction of how metal ions bind to proteins is crucial in chemistry, biology, and medicine. To date, algorithms for metal-binding site prediction are mainly based on sequence analysis. Those methods have reached enough quality to predict the correct region of the protein and the coordinating residues involved in metal-binding, but they do not provide three-dimensional (3D) models. On the contrary, the prediction of accurate 3D models for protein-metal adducts by structural bioinformatics and molecular modeling techniques is still a challenge. Here, we present an update of our multipurpose molecular modeling suite, GaudiMM, to locate metal-binding sites in proteins. The approach is benchmarked o

SUBMITTER: Sciortino G 

PROVIDER: S-EPMC6648054 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature