Conservation of Hot Spots and Ligand Binding Sites in Protein Models by AlphaFold2.

ABSTRACT: The neural network-based program AlphaFold2 (AF2) provides high accuracy structure prediction for a large fraction of globular proteins. An important question is whether these models are accurate enough for reliably docking small ligands. Several recent papers and the results of CASP15 reveal that local conformational errors reduce the success rates of direct ligand docking. Here, we focus on the ability of the models to conserve the location of binding hot spots, regions on the protein surface that significantly contribute to the binding free energy of the protein-ligand interaction. Clusters of hot spots predict the location and even the druggability of binding sites, and hence are important for computational drug discovery. The hot spots are determined by protein mapping that is based o

SUBMITTER: Bekar-Cesaretli AA 

PROVIDER: S-EPMC10922769 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature