ArticleJournal of medicinal chemistry2021
Into Deep Water: Optimizing BCL6 Inhibitors by Growing into a Solvated Pocket.
Article in Journal of medicinal chemistry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Design and synthesis of novelFuture medicinal chemistry · 2025Article
- Decoding BCL6 Inhibitors: Computational Insights into the Impact of Water Networks on Potency.Journal of chemical information and modeling · 2025Article
- How CBX proteins regulate normal and leukemic blood cells.FEBS letters · 2024Review
- High-resolution cryo-EM of the human CDK-activating kinase for structure-based drug design.Nature communications · 2024Article
- Discovery of anJournal of medicinal chemistry · 2023Article
- Improved Binding Affinity and Pharmacokinetics Enable Sustained Degradation of BCL6Journal of medicinal chemistry · 2022Article
- Optimizing Shape Complementarity Enables the Discovery of Potent Tricyclic BCL6 Inhibitors.Journal of medicinal chemistry · 2022Article
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Authors and funding
24 authors.
Funding
Abstract
We describe the optimization of modestly active starting points to potent inhibitors of BCL6 by growing into a subpocket, which was occupied by a network of five stably bound water molecules. Identifying potent inhibitors required not only forming new interactions in the subpocket but also perturbing the water network in a productive, potency-increasing fashion while controlling the physicochemical properties. We achieved this goal in a sequential manner by systematically probing the pocket and the water network, ultimately achieving a 100-fold improvement of activity. The most potent compounds displaced three of the five initial water molecules and formed hydrogen bonds with the remaining two. Compound
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.