ESM All-Atom: Multi-scale Protein Language Model for Unified Molecular Modeling
Kangjie ZhengiD, Siyu LongiD, Tianyu Lu, Junwei YangiD, Xinyu DaiiD, Ming ZhangiD, Zaiqing NieiD, Wei‐Ying MaiD, Hao ZhouiD
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
02 /Specification & Classification
Click any tag to browse matching papersReproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- RAG-ESM: Improving pretrained protein language models via sequence retrieval
Damiano Sgarbossa, Anne‐Florence Bitbol·PRX LifePeer-reviewed·Jul 30, 2025
- xTrimoPGLM: Unified 100B-Scale Pre-trained Transformer for Deciphering the Language of Protein
Bo Chen, Xingyi Cheng, … Le Song·bioRxiv·Jul 5, 2023
- Prot2Token: A multi-task framework for protein language processing using autoregressive language modeling
Mahdi Pourmirzaei, Farzaneh Esmaili, … Dong He Xu·bioRxiv·May 31, 2024
- Efficient and accurate sequence generation with small-scale protein language models
Yaiza Serrano, Sergi Rodà, … Alexis Molina·bioRxiv·Aug 4, 2023
- Scaling down protein language modeling with MSA Pairformer
Yo Akiyama, Zhidian Zhang, … Sergey Ovchinnikov·bioRxiv·Aug 2, 2025
- ProSST: Protein Language Modeling with Quantized Structure and Disentangled Attention
Mingchen Li, Yang Tan, … Liang Hong·neural information processing systemsPeer-reviewed·Jan 1, 2024