Decoding viral protein sequences by large language models.

Tianyi Fei, Siqi Li, Ziyue Yang, Kaitao Zhou, Yixue Li, Tao Zeng

Journal: Briefings in bioinformatics 2026;27(4):

PMID: 42467985

Abstract

Large language models (LLMs) for biological sequences are transforming computational biology, enabling a nuanced understanding of protein and nucleotide sequence data. Recent models, including ESM2, ESM3, AlphaGenome, Evo-1, and Evo-2, adapt natural language processing principles to the biological domain by learning high-dimensional hidden representations that capture evolutionary constraints, structural patterns, and functional motifs. This mini-review summarizes recent developments in devising and applying such models, emphasizing viral protein analysis. We highlight studies that have leveraged sequence-based LLMs in the protein domain (i.e. protein language models, or PLMs) for important application tasks such as viral protein annotation, variant effect prediction, and immune escape characterization. Additionally, we present a benchmark evaluation of these state-of-the-art protein language models to evaluate their core ability to capture evolutionary relationships between viral protein sequences. By discussing the opportunities and challenges of PLMs, the review outlines a road map for the potential application of LLMs in empowering virology research and pathogen surveillance.

Address: GMU-GIBH Joint School of Life Sciences, Guangdong Provincial Key Laboratory of Protein Modification and Disease, The Guangdong-Hong Kong-Macao Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China.; Guangzhou National Laboratory, No. 9 XingDaoHuanBei Road, Guangzhou International Bio Island, Guangzhou 510005, Guangdong Province, China.; School of Life Sciences and Technology, ShanghaiTech University, No. 393 Middle Huaxia Road, Shanghai 201210, China.; GMU-GIBH Joint School of Life Sciences, Guangdong Provincial Key Laboratory of Protein Modification and Disease, The Guangdong-Hong Kong-Macao Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China.; Guangzhou National Laboratory, No. 9 XingDaoHuanBei Road, Guangzhou International Bio Island, Guangzhou 510005, Guangdong Province, China.; Guangzhou National Laboratory, No. 9 XingDaoHuanBei Road, Guangzhou International Bio Island, Guangzhou 510005, Guangdong Province, China.; School of Life Sciences and Technology, ShanghaiTech University, No. 393 Middle Huaxia Road, Shanghai 201210, China.; Guangzhou National Laboratory, No. 9 XingDaoHuanBei Road, Guangzhou International Bio Island, Guangzhou 510005, Guangdong Province, China.; School of Automation Science and Engineering, South China University of Technology, 381 Wushan Road, Tianhe District, Guangzhou 510641, Guangdong Province, China.

DOI: 10.1093/bib/bbag377

MeSH Terms: Large Language Models, Viral Proteins, Computational Biology, Amino Acid Sequence, Humans