Decoding BCL6 Inhibitors: Computational Insights into the Impact of Water Networks on Potency

Area of Science:

• Computational chemistry
• Structural biology
• Drug discovery

Background:

• Water molecules in protein binding sites are crucial for small molecule interactions and drug design.
• Disrupting water networks during ligand modification can unpredictably alter drug potency.
• Experimental evaluation of these changes requires extensive synthesis and testing.

Purpose of the Study:

• To investigate the role of water networks in ligand binding using computational methods.
• To rationalize structure-activity relationships of B-cell Lymphoma 6 (BCL6) inhibitors.
• To demonstrate the utility of computational approaches in guiding drug discovery.

Main Methods:

• Grand Canonical Monte Carlo (GCMC) simulations to study water networks.
• Alchemical free energy calculations to quantify binding contributions.
• Retrospective analysis of BCL6 inhibitors displacing water molecules.

Main Results:

• GCMC simulations accurately reproduced experimentally observed water sites in a BCL6 subpocket (94% accuracy).
• Computational methods quantified the impact of water network changes and new protein interactions on binding affinity.
• The study successfully rationalized the structure-activity relationship of the BCL6 inhibitors.

Conclusions:

• Computational methods, specifically GCMC, are effective for studying water networks in protein binding sites.
• These methods provide valuable insights into ligand optimization and water displacement effects.
• The approach can guide drug discovery projects by predicting the impact of structural modifications.