ArticleOrganic letters2026
Data-Driven Predictions of Diastereoselectivity in Crystallization-Induced Diastereomer Transformations.
Article in Organic letters, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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Authors and funding
4 authors.
Funding
Abstract
Crystallization-induced diastereomer transformations (CIDTs) enable labile stereogenic center control but remain difficult to predict due to poorly understood structure-selectivity relationships. We report a workflow to featurize product structures and construct statistical models to predict diastereoselectivity, validating the model on six previously untested substrates and achieving predictive accuracy. Feature analysis highlights amide identity, conformational compactness, and local electronic properties as key determinants of stereochemical outcome, providing a mechanistic basis and a predictive framework for CIDT design.
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