DeepDTAGen for drug-target affinity prediction and target-aware generation
A multitask deep-learning framework models drug-target affinity and target-aware molecule generation to accelerate candidate discovery.
Nature Communications
DeepDTAGen combines affinity prediction and molecule generation to rank candidates for virtual screening and lead design.
Experimental validation still requires biochemical binding, cellular activity, selectivity, pharmacokinetic and toxicity data rather than model scores alone.