Pheng Ann Heng

Subsampling MSAs based on energetic frustration can dramatically enhance the recovery of alternative protein conformations, outperforming traditional sequence-based methods.

AlloGen reveals that conformational selectivity in protein binder design can be learned and optimized, not just assumed.

Reward models optimized for single-step generation can fail spectacularly when integrated into multi-stage LLM pipelines, but pipeline-aware training can fix this.

Chemical modifications to proteins, often missed by standard protein language models, can now be accurately captured and leveraged for improved biomolecule design, thanks to a new framework that fuses atomic-level details with broader sequence context.