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Enhanced antibody-antigen structure prediction from molecular docking using AlphaFold2.

Francis Gaudreault1, Christopher R Corbeil1, Traian Sulea2,3

  • 1Human Health Therapeutics Research Centre, National Research Council Canada, 6100 Royalmount Avenue, Montreal, QC, H4P 2R2, Canada.

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|September 13, 2023
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Summary
This summary is machine-generated.

This study enhances antibody-antigen complex structure prediction by combining physics-based docking with AlphaFold2 (AF2) rescoring. The novel AF2 composite score significantly improves the accuracy of predicting these crucial biomedical structures.

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Area of Science:

  • Structural Biology
  • Computational Biology
  • Immunology

Background:

  • Predicting antibody-antigen complex structures is vital for biomedical research but challenging.
  • While AlphaFold2 (AF2) excels at protein structure prediction, its application to antibody-antigen complexes is limited by a lack of co-evolutionary data.

Purpose of the Study:

  • To improve the prediction accuracy of antibody-antigen complex structures.
  • To develop and validate a novel rescoring method for protein-protein docking using AF2.

Main Methods:

  • Generated decoy sets of potential antibody-antigen complex structures using physics-based protein docking.
  • Applied AF2 to refine structures and calculated a composite score using normalized pLDDT and pTMscore metrics.
  • Evaluated the AF2 composite score for classifying correct and incorrect docking poses and improving success rates.

Main Results:

  • The AF2 composite score effectively rescores docking poses, improving the classification of native-like structures.
  • Significant gains in prediction success rates were observed, particularly in early enrichment of correct models.
  • Medium-quality docking models, not necessarily top-ranked by docking methods, benefited most from AF2 rescoring.

Conclusions:

  • The proposed AF2-based rescoring method substantially enhances antibody-antigen unbound docking performance.
  • This approach achieves unprecedented performance levels without requiring new methodologies or calibration.
  • The findings offer a promising strategy for advancing the prediction of antibody-antigen complex structures.