Fang Wu

This paper introduces a deep reinforcement learning framework for designing new antibiotics, producing potent peptides with broad-spectrum activity against bacteria.

BC-DO_SCPLOWESIGNC_SCPLOW improves inverse protein design by integrating continuous physicochemical properties with structural geometry, achieving high sequence recovery and functional design accuracy.

This paper integrates protein language models with geometric deep learning to improve protein representation learning, achieving a 20% performance boost on multiple benchmarks.