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Bridging the gap between target-based and cell-based drug discovery with a graph generative multi-task model
Based on these findings, we utilized a monte carlo based reinforcement learning generative model to generate novel multi-property compounds with both in vitro and in vivo efficacy, thus bridging the gap between target-based and cell-based drug discovery.
A Novel Framework Integrating AI Model and Enzymological Experiments Promotes Identification of SARS-CoV-2 3CL Protease Inhibitors and Activity-based Probe
The identification of protein-ligand interaction plays a key role in biochemical research and drug discovery.
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