Article Artificial intelligence-based HDX (AI-HDX) prediction reveals fundamental characteristics to protein dynamics: Mechanisms on SARS-CoV-2 immune escape

Yu J., Uzuner U., Long B., Wang Z., Yuan J. S., Dai S. Y.

ISCIENCE, cilt.26, sa.4, 2023 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 26 Sayı: 4
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1016/j.isci.2023.106282
  • Dergi Adı: ISCIENCE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Directory of Open Access Journals
  • Anahtar Kelimeler: Immunology, Virology
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

Three-dimensional structure and dynamics are essential for protein function. Ad-vancements in hydrogen-deuterium exchange (HDX) techniques enable probing protein dynamic information in physiologically relevant conditions. HDX-coupled mass spectrometry (HDX-MS) has been broadly applied in pharmaceutical indus-tries. However, it is challenging to obtain dynamics information at the single amino acid resolution and time consuming to perform the experiments and pro-cess the data. Here, we demonstrate the first deep learning model, artificial intel-ligence-based HDX (AI-HDX), that predicts intrinsic protein dynamics based on the protein sequence. It uncovers the protein structural dynamics by combining deep learning, experimental HDX, sequence alignment, and protein structure prediction. AI-HDX can be broadly applied to drug discovery, protein engineer-ing, and biomedical studies. As a demonstration, we elucidated receptor-binding domain structural dynamics as a potential mechanism of anti-severe acute respi-ratory syndrome coronavirus 2 (SARS-CoV-2) antibody efficacy and immune escape. AI-HDX fundamentally differs from the current AI tools for protein analysis and may transform protein design for various applications.