Evidence map›Paper›PMID 40875598›Full record

ArticleJournal of chemical information and modeling2025

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

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

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Daniella E HaresCentre for Cancer Drug Discovery, The Institute of Cancer Research, London SM2 5NG, U.K.ORCID 0000-0002-6023-7371
Andrea ScarpinoCentre for Cancer Drug Discovery, The Institute of Cancer Research, London SM2 5NG, U.K.ORCID 0000-0003-3287-6210
Michael S BodnarchukOncology R&D, AstraZeneca, Cambridge Biomedical Campus, Cambridge CB2 0AA, U.K.ORCID 0000-0002-9172-1203
Swen HoelderCentre for Cancer Drug Discovery, The Institute of Cancer Research, London SM2 5NG, U.K.ORCID 0000-0001-8636-1488

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Proto-Oncogene Proteins c-bcl-6WaterBinding SitesHumansLigandsMolecular Dynamics SimulationMonte Carlo MethodProtein BindingStructure-Activity RelationshipThermodynamicsBCL6 protein, humanLigandsProto-Oncogene Proteins c-bcl-6Water

Identifiers

PMID40875598
PMCPMC12458693

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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.