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Targeting Ubiquitin-Specific Protease 7 (USP7): A Pharmacophore-Guided Drug Repurposing and Physics-based Molecular Simulations Study
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Abstract
Ubiquitin-Specific Protease 7 (USP7) has emerged as a critical therapeutic target in cancer due to its regulatory roles of tumor suppressors, oncoproteins, and epigenetic modifiers. In this study, we present a comprehensive drug repurposing strategy to identify potential USP7 inhibitors from a curated library of 6,654 FDA-approved and investigational small molecules. Using structure-based pharmacophore models derived from USP7-inhibitor crystal structures, we conducted virtual screening to select candidates with favorable pharmacophoric alignment. The top 100 hits were subjected to short 10 ns molecular dynamics (MD) simulations and MM/GBSA binding energy calculations, narrowing down to 36 promising ligands. These were further evaluated through longer (100 ns) MD simulations, binding energy refinement, ligand clustering based on molecular fingerprints, and cancer-specific activity predictions using a binary QSAR model. Twelve compounds demonstrated favorable binding profiles, structural diversity, and high predicted anticancer activity, such as xantifibrate, etofylline clofibrate, and carafiban. This multi-tiered hybrid virtual screening pipeline highlights the potential of drug repurposing for the rapid identification of USP7 inhibitors, offering a cost-effective path toward novel anticancer therapeutics.
Title: Targeting Ubiquitin-Specific Protease 7 (USP7): A Pharmacophore-Guided Drug Repurposing and Physics-based Molecular Simulations Study
Description:
Abstract
Ubiquitin-Specific Protease 7 (USP7) has emerged as a critical therapeutic target in cancer due to its regulatory roles of tumor suppressors, oncoproteins, and epigenetic modifiers.
In this study, we present a comprehensive drug repurposing strategy to identify potential USP7 inhibitors from a curated library of 6,654 FDA-approved and investigational small molecules.
Using structure-based pharmacophore models derived from USP7-inhibitor crystal structures, we conducted virtual screening to select candidates with favorable pharmacophoric alignment.
The top 100 hits were subjected to short 10 ns molecular dynamics (MD) simulations and MM/GBSA binding energy calculations, narrowing down to 36 promising ligands.
These were further evaluated through longer (100 ns) MD simulations, binding energy refinement, ligand clustering based on molecular fingerprints, and cancer-specific activity predictions using a binary QSAR model.
Twelve compounds demonstrated favorable binding profiles, structural diversity, and high predicted anticancer activity, such as xantifibrate, etofylline clofibrate, and carafiban.
This multi-tiered hybrid virtual screening pipeline highlights the potential of drug repurposing for the rapid identification of USP7 inhibitors, offering a cost-effective path toward novel anticancer therapeutics.
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