InterPepRank: Assessment of Docked Peptide Conformations by a Deep Graph Network.

ABSTRACT: Peptide-protein interactions between a smaller or disordered peptide stretch and a folded receptor make up a large part of all protein-protein interactions. A common approach for modeling such interactions is to exhaustively sample the conformational space by fast-Fourier-transform docking, and then refine a top percentage of decoys. Commonly, methods capable of ranking the decoys for selection fast enough for larger scale studies rely on first-principle energy terms such as electrostatics, Van der Waals forces, or on pre-calculated statistical potentials. We present InterPepRank for peptide-protein complex scoring and ranking. InterPepRank is a machine learning-based method which encodes the structure of the complex as a graph; with physical pairwise interactions as edges and evolutionary

SUBMITTER: Johansson-Akhe I 

PROVIDER: S-EPMC9581042 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature