Accurate prediction of dynamic protein–ligand binding using P‐score ranking

• Published in: Journal of computational chemistry Vol. 45; no. 20; pp. 1762 - 1778
• Main Authors: Ibrahim, Peter E. G. F., Zuccotto, Fabio, Zachariae, Ulrich, Gilbert, Ian, Bodkin, Mike
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 22.04.2024; Wiley Subscription Services, Inc
• Subjects: binding pose prediction; Binding sites; dynamic average quantum mechanics fragment molecular orbital; Ligands; Molecular dynamics; Molecular orbitals; Proteins; P‐score; Quantum mechanics; supervised molecular dynamics; Workflow; supervised molecular dynamics; dynamic average quantum mechanics fragment molecular orbital; P‐score; binding pose prediction
• ISSN: 0192-8651; 1096-987X
• DOI: 10.1002/jcc.27370

Protein–ligand binding prediction typically relies on docking methodologies and associated scoring functions to propose the binding mode of a ligand in a biological target. Significant challenges are associated with this approach, including the flexibility of the protein–ligand system, solvent‐mediated interactions, and associated entropy changes. In addition, scoring functions are only weakly accurate due to the short time required for calculating enthalpic and entropic binding interactions. The workflow described here attempts to address these limitations by combining supervised molecular dynamics with dynamical averaging quantum mechanics fragment molecular orbital. This combination significantly increased the ability to predict the experimental binding structure of protein–ligand complexes independent from the starting position of the ligands or the binding site conformation. We found that the predictive power could be enhanced by combining the residence time and interaction energies as descriptors in a novel scoring function named the P‐score. This is illustrated using six different protein–ligand targets as case studies. The P‐score defines a protein–ligand bound pose is a result of dynamic induced‐fit binding event. Therefore, by combing a ligand protein residence time calculated from molecular dynamics with an interaction energy derived from quantum mechanics a novel scoring function, termed the P‐score, can accurately predict ligand binding for protein–ligand complexes.