Beyond Docking: A Multi-Tier Computational Pipeline for USP7 Inhibitor Optimization.

Abstract

Ubiquitin-specific protease 7 (USP7) is a key deubiquitinating enzyme involved in tumor suppression, DNA repair, and epigenetic regulation. Given its critical role in cancer progression, USP7 has emerged as an attractive therapeutic target. In this study, we employed a multi-tier computational approach, integrating ligand-based virtual screening, molecular docking, MD simulations, MM/GBSA binding free energy calculations, binary QSAR modeling, and steered MD simulations to identify and optimize novel USP7 inhibitors. Using SwissSimilarity-based ligand screening, we selected structurally related analogs of previously identified and validated hit compounds by our research group and performed grid-based docking simulations, prioritizing molecules with high binding affinity (docking scores < -8.0 kcal/mol). The top-ranked candidates were refined through long-term MD simulations and MM/GBSA free energy calculations to assess their structural stability and interaction patterns with key USP7 residues. Binary QSAR analysis further evaluated the anticancer potential of these compounds, filtering those with high predicted therapeutic activity (normalized therapeutic activity value > 0.5). Furthermore, to investigate selectivity of the potent compounds, we performed cross-docking against multiple USP family members. Finally, sMD simulations provided insights into the mechanical stability of ligand-protein interactions. The identified candidates hold promise for further in vitro studies, advancing USP7-targeted therapies for cancer treatment.