EMNLP 20250 citations

Protein Large Language Models: A Comprehensive Survey

Yijia Xiao, Wanjia Zhao, Junkai Zhang, Yiqiao Jin, Han Zhang, Zhicheng Ren, Renliang Sun, Haixin Wang

Abstract

Protein-specific large language models (ProteinLLMs) are revolutionizing protein science by enabling more efficient protein structure prediction, function annotation, and design. While existing surveys focus on specific aspects or applications, this work provides the first comprehensive overview of ProteinLLMs, covering their architectures, training datasets, evaluation metrics, and diverse applications. Through a systematic analysis of over 100 articles, we propose a structured taxonomy of state-of-the-art ProteinLLMs, analyze how they leverage large-scale protein sequence data for improved accuracy, and explore their potential in advancing protein engineering and biomedical research. Additionally, we discuss key challenges and future directions, positioning ProteinLLMs as essential tools for scientific discovery in protein science. Resources are maintained at https://github.com/Yijia-Xiao/Protein-LLM-Survey.

BibTeX
@inproceedings{emnlp2025_proteinlargelang,
  title = {Protein Large Language Models: A Comprehensive Survey},
  author = {Yijia Xiao and Wanjia Zhao and Junkai Zhang and Yiqiao Jin and Han Zhang and Zhicheng Ren and Renliang Sun and Haixin Wang and Guancheng Wan and Pan Lu and Xiao Luo and Yu Zhang and James Zou and Yizhou Sun and Wei Wang},
  booktitle = {EMNLP 2025},
  year = {2025}
}