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Jingyang Ge

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Jul 2026

PSDTA: An Approach to Drug-Target Binding Affinity Prediction by Integrating Physicochemical and Structural Information to Reduce Feature Redundancy.

This work proposes a DTA prediction method, PSDTA, which integrates physicochemical properties into the initial feature representations and explicitly incorporates structural information on amino acids, thereby avoiding the risk of information leakage caused by directly using coordinates as features and enhancing the model's generalization capability.

Shuang Wang, Mao Li, Peifu Han et al. · 0 citations