Interpretable deep-learning pKa prediction for small molecule drugs via atomic sensitivity analysis
Joseph DeCorte,
Benjamin Brown,
Jens Meiler
Abstract:Machine learning (ML) models play a crucial role in predicting properties essential to drug development, such as a drug’s logscale acid-dissociation constant (pKa). Despite recent architectural advances, these models often generalize poorly to novel compounds due to a scarcity of ground-truth data. Further, these models lack interpretability, in part due to a dependence on explicit encodings of input molecules’ molecular substructures. To this end, atomic-resolution information is accessible in chemical struct… Show more
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