ArticleBioinformatics (Oxford, England)2026
PCIM-DTA: pairwise conditional interaction modeling for drug-target affinity prediction under cold-start scenarios.
Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Research on assessment and adaptive correction technology of power system protection fixed value mismatch.Scientific reports · 2026Article
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4 authors.
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Abstract
motivationCold-start drug-target affinity prediction remains challenging because static interaction mechanisms cannot adapt to individual drug-target pairs.
resultsWe propose PCIM-DTA, which constructs pair-level interaction representations and derives a pair-specific condition vector from global drug and target features. The condition vector modulates attention, pair-token features, distribution-aware recalibration, and regression parameters, while graph message passing captures higher-order dependencies. Experiments on Davis and BindingDB-Kd show that PCIM-DTA achieves competitive or superior performance under Warm, Cold-drug, Cold-target, Cold-both, and Scaffold-drug settings. Ablation studies support the contribution of each component. AVAILABILITY AND IMPLEMENTATION: The datasets used in this study are publicly available, including the Davis and BindingDB-Kd datasets. The implementation code of PCIM-DTA is publicly available at https://github.com/1322469934/PCIM-DTA.
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