ArticleACS medicinal chemistry letters2025
Active Learning FEP Using 3D-QSAR for Prioritizing Bioisosteres in Medicinal Chemistry.
Article in ACS medicinal chemistry letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- The computationally guided design of selective targeters of multiple proteins (STaMPs) as a new opportunity for small molecule drug discovery.Frontiers in pharmacology · 2025Review
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Authors and funding
3 authors.
Funding
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Abstract
Bioisostere replacement is a powerful and popular tool used to optimize the potency and selectivity of candidate molecules in drug discovery. Selecting the right bioisosteres to invest resources in for synthesis and subsequent optimization is key to an efficient drug discovery project. Here we demonstrate how 3D-quantitative structure-activity relationship (3D-QSAR) and relative binding free energy calculations can be combined into an active learning workflow to prioritize molecules from a pool of hundreds of bioisosteres. We demonstrate on a human aldose reductase test case that the use of this workflow can rapidly locate the strongest-binding bioisosteric replacements with a relatively modest computational cost.
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Registered trials
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