ArticleiScience2026
BoltzOmics: Predicting genetic variant effects on drug binding with Boltz-2.
Article in iScience, 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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Abstract
A mechanistic understanding of how genetic variants alter drug-receptor binding is central to precision medicine, drug response prediction, and drug development. Yet, experimental mutation-drug profiling remains slow and expensive, while existing computational approaches often trade accuracy for scalability. We developed BoltzOmics, an interactive, open-source platform that integrates Boltz-2, a deep learning model for biomolecular structure prediction, to rapidly assess mutation effects on drug binding. Starting from amino acid sequences, the workflow queries databases for genetic variants, generates wild-type and mutant protein structures, and screens multiple drugs across variants to predict binding affinity changes. We evaluated BoltzOmics across four targets: hERG, Na
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