FrustraPocket: A protein–ligand binding site predictor using energetic local frustration

• Published in: bioRxiv
• Main Authors: Freiberger, Maria I, Clemente, Camila M, Valero, Eneko, Pombo, Jorge G, Leonetti, Cesar O, Ravetti, Soledad, Rodrigo Gonzalo Parra, Ferreiro, Diego U
• Format: Paper
• Language: English
• Published: Cold Spring Harbor Cold Spring Harbor Laboratory Press 14.12.2022
• Subjects: Free energy; Frustration; Localization
• DOI: 10.1101/2022.12.11.519349

Proteins are evolved polymers that minimize their free energy upon folding to their native states. Still, many folded proteins display energetic conflict between residues in various regions that can be identified as highly frustrated, and these have been shown to be related to several physiological functions. Here we show that small-ligand binding sites are typically enriched in locally frustrated interactions in the unbound state. We built a tool using a simple machine learning algorithm named FrustraPocket that combines the notion of small-molecule binding pockets and the localization of clusters of highly frustrated interactions to identify potential protein-ligand binding sites solely from the unbound forms. Availability and implementation (github): https://github.com/CamilaClemente/FrustraPocket Docker container: https://hub.docker.com/r/proteinphysiologylab/frustrapocketCompeting Interest StatementThe authors have declared no competing interest.Footnotes* https://github.com/CamilaClemente/FrustraPocket/* https://hub.docker.com/r/proteinphysiologylab/frustrapocket