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DOI 10.1021/acs.jcim.5c01188

Медицинская библиотека · Journal of chemical information and modeling · 2025

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

Hares Daniella E, Scarpino Andrea, Bodnarchuk Michael S, Hoelder Swen

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Аннотация

Water molecules in the binding site can have a critical role in small molecule binding to proteins and are an important consideration in structure-based drug design. Water networks have additional complexity as displacing one water molecule has subsequent effects on the remaining network. Modification of a lead compound that disrupts a water network can have beneficial or detrimental impacts on potency and this outcome is impossible to determine experimentally without time-consuming synthesis of the new compound. Computational methods are ideally suited to study the interplay between ligand optimization and water displacement by predicting the effect of structural changes on both the activity of the compound and the stability of neighboring water molecules. We used Grand Canonical Monte Carlo (GCMC) simulations and alchemical free energy calculations to retrospectively study a series of B-cell Lymphoma 6 (BCL6) inhibitors that sequentially displaced water molecules from a network. The methods were used to rationalize the structure-activity relationship of the compounds by quantifying the individual contributions to the binding affinity from the changes in the water network and new interactions with the protein. GCMC simulations are well-suited for studying water networks in the binding site and were able to reproduce 94% of the experimentally observed water sites from the crystal structures in a subpocket of BCL6. Using the BCL6 project as an example, we show the power of these computational methods to study water networks and how they can provide insights that are able to guide drug discovery projects.

Для цитирования: Hares Daniella E, Scarpino Andrea, Bodnarchuk Michael S, Hoelder Swen. Decoding BCL6 Inhibitors: Computational Insights into the Impact of Water Networks on Potency.. Journal of chemical information and modeling. 2025. DOI: 10.1021/acs.jcim.5c01188.

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