Research line

We are exploring the use of pyDock energy-based function to describe the energetics of protein-protein interactions. The goal is to improve the identification of protein-protein interactions from AlphaFold models.

We are also developing different strategies with pyDock energy for estimating the energetic impact of mutations, using our tool pyDockEneRes (https://life.bsc.es/pid/pydockeneres) for mutations to alanine, and the well-known SCWRL program from Dunbrack’s lab (https://dunbrack.fccc.edu/lab/scwrl) for modeling other mutations based on x-ray structures, MD conformations, and AF2-MM models of the WT complexes.

We are working on new methodologies for the identification of suitable cavities at protein-protein interfaces, built upon our previously developed protocol [Rosell & Fernández-Recio 2020], which used molecular dynamics (MD) with AMBER, cavity detection with Fpocket, and prediction of hot-spot residues with pyDock NIP. The use of PockDrug from Camproux’ lab (https://pockdrug.rpbs.univ-paris-diderot.fr/) can provide relevant information about the druggability of the identified pockets.