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<p>ProTrek unifies protein sequence, structure and natural language function in a trimodal language model through contrastive learning, enabling comprehensive searches between any two modalities, including within modality. ProTrek surpasses current alignment tools (for example, Foldseek and MMseqs2) in speed and accuracy for identifying functionally related proteins. Computational and wet-lab experimental validations show that the ProTrek server (<a href="http://www.search-protrek.com">www.search-protrek.com</a>), with precomputed embeddings for over 5 billion proteins, efficiently processes and analyzes large-scale protein repositories.</p>

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A trimodal protein language model enables advanced protein searches

  • 期刊论文

  • 发表日期：

    2025年10月2日

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  • Jin Su,
  • Yan He,
  • Shiyang You,
  • Shiyu Jiang,
  • Xibin Zhou,
  • Xuting Zhang,
  • Yuxuan Wang,
  • Xining Su,
  • Igor Tolstoy,
  • Xing Chang,
  • Hongyuan Lu,
  • Fajie Yuan

摘要

ProTrek unifies protein sequence, structure and natural language function in a trimodal language model through contrastive learning, enabling comprehensive searches between any two modalities, including within modality. ProTrek surpasses current alignment tools (for example, Foldseek and MMseqs2) in speed and accuracy for identifying functionally related proteins. Computational and wet-lab experimental validations show that the ProTrek server (www.search-protrek.com), with precomputed embeddings for over 5 billion proteins, efficiently processes and analyzes large-scale protein repositories.