Topological links in predicted protein complex structures reveal limitations of AlphaFold

被引:0
|
作者
Yingnan Hou
Tengyu Xie
Liuqing He
Liang Tao
Jing Huang
机构
[1] Westlake University,Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences
[2] Westlake Laboratory of Life Sciences and Biomedicine,Westlake AI Therapeutics Lab
[3] Westlake Laboratory of Life Sciences and Biomedicine,Center for Infectious Disease Research
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
AlphaFold is making great progress in protein structure prediction, not only for single-chain proteins but also for multi-chain protein complexes. When using AlphaFold-Multimer to predict protein‒protein complexes, we observed some unusual structures in which chains are looped around each other to form topologically intertwining links at the interface. Based on physical principles, such topological links should generally not exist in native protein complex structures unless covalent modifications of residues are involved. Although it is well known and has been well studied that protein structures may have topologically complex shapes such as knots and links, existing methods are hampered by the chain closure problem and show poor performance in identifying topologically linked structures in protein‒protein complexes. Therefore, we address the chain closure problem by using sliding windows from a local perspective and propose an algorithm to measure the topological–geometric features that can be used to identify topologically linked structures. An application of the method to AlphaFold-Multimer-predicted protein complex structures finds that approximately 1.72% of the predicted structures contain topological links. The method presented in this work will facilitate the computational study of protein‒protein interactions and help further improve the structural prediction of multi-chain protein complexes.
引用
收藏
相关论文
共 50 条
  • [21] AlphaFold-predicted Protein Structure vs Experimentally Obtained Protein Structure: An Emphasis on the Side Chains
    Shiono, Daiki
    Yoshidome, Takashi
    JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN, 2022, 91 (06)
  • [22] AIIoMAPS 2: allosteric fingerprints of the AlphaFold and Pfam-trRosetta predicted structures for engineering and design
    Tan, Zhen Wah
    Tee, Wei-Ven
    Guarnera, Enrico
    Berezovsky, Igor N.
    NUCLEIC ACIDS RESEARCH, 2023, 51 (D1) : D345 - D351
  • [23] Benchmarking AlphaFold for protein complex modeling reveals accuracy determinants
    Yin, Rui
    Feng, Brandon Y.
    Varshney, Amitabh
    Pierce, Brian G.
    PROTEIN SCIENCE, 2022, 31 (08)
  • [24] Cryo-EM Structures and AlphaFold3 Models of Histamine Receptors Reveal Diverse Ligand Binding and G Protein Bias
    Chen, Anqi
    Su, Chenxi
    Zhang, Zisu
    Zhang, Haitao
    PHARMACEUTICALS, 2025, 18 (03)
  • [25] Condensin structures chromosomal DNA through topological links
    Sara Cuylen
    Jutta Metz
    Christian H Haering
    Nature Structural & Molecular Biology, 2011, 18 : 894 - 901
  • [26] Condensin structures chromosomal DNA through topological links
    Cuylen, Sara
    Metz, Jutta
    Haering, Christian H.
    NATURE STRUCTURAL & MOLECULAR BIOLOGY, 2011, 18 (08) : 894 - U52
  • [27] Condensin structures chromosomal DNA through topological links
    Cuylen, S.
    Metz, J.
    Haering, C. H.
    MOLECULAR BIOLOGY OF THE CELL, 2011, 22
  • [28] Comparing Native Crystal Structures and AlphaFold2 Predicted Water-Soluble G Protein-Coupled Receptor QTY Variants
    Skuhersky, Michael A.
    Tao, Fei
    Qing, Rui
    Smorodina, Eva
    Jin, David
    Zhang, Shuguang
    LIFE-BASEL, 2021, 11 (12):
  • [29] TURNING POINTS IN PREDICTED PROTEIN STRUCTURES
    GEISOW, M
    NATURE, 1978, 274 (5672) : 642 - 642
  • [30] Chemistry Nobel goes to developers of AlphaFold AI that predicts protein structures
    Ewen Callaway
    Nature, 2024, 634 (8034) : 525 - 526