ESM All-Atom: Multi-scale Protein Language Model for Unified Molecular Modeling

Abstract Protein language models have demonstrated significant potential in the field of protein engineering. However, current protein language models primarily operate at the residue scale, which limits their ability to provide information at the atom level. This limitation prevents us from fully exploiting the capabilities of protein language models for applications involving both proteins and small molecules. In this paper, we propose ESM-AA (ESM All-Atom), a novel approach that enables atom-scale and residue-scale unified molecular modeling. ESM-AA achieves this by pretraining on multi-scale code-switch protein sequences and utilizing a multi-scale position encoding to capture relationships among residues and atoms. Experimental results indicate that ESM-AA surpasses previous methods in proteinmolecule tasks, demonstrating the full utilization of protein language models. Further investigations reveal that through unified molecular modeling, ESM-AA not only gains molecular knowledge but also retains its understanding of proteins.1 Competing Interest Statement The authors have declared no competing interest. Footnotes This work was done during the internship of Kangjie, Siyu, Tianyu, and Junwei at AIR ICML2024 camera-ready, update some experimental results, release the code, fix some typos ↵1 The source codes of ESM-AA are publicly released at https://github.com/zhengkangjie/ESM-AA.