SOURCE-LINKED INTELLIGENCE
Chemical and geometric representation fidelity improves drug--target affinity prediction
Predicting drug--target binding affinity (DTA) requires models to distinguish subtle chemical and structural determinants underlying molecular recognition. Although recent approaches increasingly incorporate richer drug and protein information, such information may be compressed, homogenized or discretized during representation construction, causing affinity-relevant distinctions to be lost before interaction modelling. We hypothesized that this representation-stage information loss constitutes an upstream bottleneck that cannot be reliably overcome by increasingly complex interaction predicto
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-02T08:37:36.000Z
First collected: 2026-09-21T05:32:15.665Z. This is not the publication date.