Tessel Bio Releases Sesame, a Generative Chemistry Model That Fills Any Protein Pocket

Tessel Bio released Sesame, a diffusion-based generative chemistry model that designs drug-like molecules in any protein pocket, de novo or from a chemist's scaffold, with a preprint on arXiv.

Tessel Bio Releases Sesame, a Generative Chemistry Model That Fills Any Protein Pocket Tessel Bio released Sesame, a diffusion-based generative chemistry model that designs drug-like molecules in any protein pocket, de novo or from a chemist's scaffold, with a preprint on arXiv. Aaron Rafferty June 29, 2026 Key Takeaways: Tessel Bio released Sesame, a diffusion-based generative chemistry model that designs drug-like molecules to fit any protein pocket, either from scratch or by growing a chemist's scaffold. A new spatial pairformer module reads both a partial molecule and the surrounding protein pocket as continuous spatial density maps, handling de novo design and lead optimization in one system. Tessel published Sesame openly in a preprint on arXiv, adding to a growing wave of AI tools built to speed early drug discovery. Tessel Bio released Sesame on June 26, a generative chemistry model that designs drug-like molecules to fill any protein pocket, the company laid out in a preprint posted to arXiv . The model works two ways, building a molecule from nothing or growing one from a fragment a chemist supplies. Sesame, short for Spatial Evoformer for a Structure-Aware Molecular Engine, is built on diffusion, the same class of method behind modern image generators. Its core addition is a spatial pairformer module that reads a partial molecule and the shape of the protein pocket around it as continuous density maps, then fills in atom types, bond types, and positions together. That single mechanism covers two jobs that usually need separate tools. A medicinal chemist can prune a promising hit down to a scaffold and have Sesame grow it in new directions, which is the central move in lead optimization. The authors also describe a training step that learns from the mo