CAGenMol uses condition-aware discrete diffusion coupled with reinforcement learning to generate valid molecules meeting multiple heterogeneous constraints, outperforming prior methods on binding affinity, drug-likeness, and success rate benchmarks.
Meng Liu, Youzhi Luo, Kanji Uchino, Koji Maruhashi, and Shuiwang Ji
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CAGenMol: Condition-Aware Diffusion Language Model for Goal-Directed Molecular Generation
CAGenMol uses condition-aware discrete diffusion coupled with reinforcement learning to generate valid molecules meeting multiple heterogeneous constraints, outperforming prior methods on binding affinity, drug-likeness, and success rate benchmarks.