Scholarlink

Protein language models (PLMs) enable functional analysis of divergent viral sequences without homology alignment. This review covers PLM architectures from sequence encoders through structure-aware architectures to generative models and assesses their application to orphan protein structure resolution, virosphere-wide functional classification, host factor identification, and therapeutic antibody optimization. Finally, the limitations of the current model in terms of interpretability and insufficient data representation are discussed while exploring future trends toward multimodal integration and the “dry-wet” experimental loop to accelerate the adoption of artificial intelligence in precision virology.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Protein Language Models in Virology: A Review of Advances and Applications

  • 实验方案

  • 发表日期：

    2026年

查看全文
  • Lingxin Luo,
  • Yixue Li,
  • Tao Huang

摘要

Protein language models (PLMs) enable functional analysis of divergent viral sequences without homology alignment. This review covers PLM architectures from sequence encoders through structure-aware architectures to generative models and assesses their application to orphan protein structure resolution, virosphere-wide functional classification, host factor identification, and therapeutic antibody optimization. Finally, the limitations of the current model in terms of interpretability and insufficient data representation are discussed while exploring future trends toward multimodal integration and the “dry-wet” experimental loop to accelerate the adoption of artificial intelligence in precision virology.