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.

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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