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Updated: Dec 27, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
Binding affinity and dissociation pathway predictions for a series of USP7 inhibitors with pyrimidinone scaffold by
Zhe Wang1, Xuwen Wang1, Yu Kang1
1College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China. tingjunhou@zju.edu.cn.
Abstract:
Ubiquitin specific protease 7 (USP7) has attracted increasing attention because of its multifaceted roles in different tumor types. The crystal structures of USP7-inhibitor complexes resolved recently provide reliable models for computational structure-based drug design (SBDD) towards USP7. How to accurately estimate USP7-ligand binding affinity is quite critical to guarantee the reliability of SBDD. In this study, we assessed the reliability of multiple computational methods to the binding affinity prediction for a series of USP7 inhibitors with the pyrimidinone scaffold, including molecular docking scoring, MM/PB(GB)SA, and umbrella sampling (US). It was found that the accuracy of the evaluated computational methods for binding affinity prediction follows the order: US-based method > MM/PB(GB)SA > Glide XP scoring. The calculation results demonstrate that incorporating protein flexibility through induced-fit docking or ensemble docking cannot improve the performance of the Glide scoring based on rigid-receptor docking. For the MM/PB(GB)SA methods, the choice of the protein structure and the calculation procedure has a marked impact on the predictions. More importantly, we discovered for the first time that there are significant differences in the dissociation pathways of strong-binding inhibitors and weak-binding inhibitors of USP7, which may be used as a new criterion to judge whether an inhibitor is a strong binder or not. It is expected that our work can provide valuable guidance on the design and discovery of potent USP7 inhibitors.
Insights
Computational methods for predicting Ubiquitin specific protease 7 (USP7) inhibitor binding affinity were evaluated. Umbrella sampling (US) proved most accurate, offering insights into inhibitor design.
Area of Science:
- Biochemistry
- Computational Chemistry
- Drug Discovery
Background:
- Ubiquitin specific protease 7 (USP7) is crucial in various cancers.
- USP7 crystal structures enable structure-based drug design (SBDD).
- Accurate binding affinity prediction is vital for reliable SBDD.
Purpose of the Study:
- To assess computational methods for USP7 inhibitor binding affinity prediction.
- To compare molecular docking, MM/PB(GB)SA, and umbrella sampling (US) accuracy.
- To guide the development of potent USP7 inhibitors.
Main Methods:
- Evaluated molecular docking (Glide XP), MM/PB(GB)SA, and umbrella sampling (US).
- Tested various computational approaches including induced-fit and ensemble docking.
- Analyzed dissociation pathways of USP7 inhibitors.
Main Results:
- Umbrella sampling (US) demonstrated the highest accuracy in binding affinity prediction.
- MM/PB(GB)SA accuracy is sensitive to protein structure and calculation procedures.
- Protein flexibility did not enhance Glide XP scoring for rigid-receptor docking.
- Distinct dissociation pathways were identified for strong vs. weak USP7 binders.
Conclusions:
- Umbrella sampling is the most reliable method for USP7 binding affinity prediction.
- Dissociation pathway analysis offers a novel criterion for evaluating inhibitor strength.
- Findings provide guidance for designing effective USP7-targeted therapeutics.
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