GRaSP-web: a machine learning strategy to predict binding sites based on residue neighborhood graphs.

ABSTRACT: Proteins are essential macromolecules for the maintenance of living systems. Many of them perform their function by interacting with other molecules in regions called binding sites. The identification and characterization of these regions are of fundamental importance to determine protein function, being a fundamental step in processes such as drug design and discovery. However, identifying such binding regions is not trivial due to the drawbacks of experimental methods, which are costly and time-consuming. Here we propose GRaSP-web, a web server that uses GRaSP (Graph-based Residue neighborhood Strategy to Predict binding sites), a residue-centric method based on graphs that uses machine learning to predict putative ligand binding site residues. The method outperformed 6 state-of-the-art

SUBMITTER: Santana CA 

PROVIDER: S-EPMC9252730 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature