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mCSM-AB: a web server for predicting antibody-antigen affinity changes upon mutation with graph-based signatures.

Douglas E V Pires1, David B Ascher2

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Predicting antibody-antigen binding affinity changes from mutations is challenging. mCSM-AB, a new web server using graph-based signatures, accurately predicts these effects, improving antibody engineering and escape mutation analysis.

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Area of Science:

  • Computational biology
  • Structural biology
  • Immunology

Background:

  • Predicting the impact of mutations on antibody-antigen binding affinity is crucial for antibody engineering and understanding immune escape.
  • Traditional computational methods often lack the accuracy needed for reliable prediction of these affinity changes.

Purpose of the Study:

  • To develop and present mCSM-AB, a novel web server for accurate prediction of antibody-antigen binding affinity changes upon mutation.
  • To provide a user-friendly tool that outperforms existing methods in antibody engineering applications.

Main Methods:

  • Utilized graph-based signatures to represent antibody-antigen complexes.
  • Developed a computational model, mCSM-AB, implemented as a web server.
  • Benchmarked mCSM-AB against existing computational methods for predicting binding affinity changes.

Main Results:

  • mCSM-AB demonstrates superior performance compared to previously used methods for antibody engineering.
  • The web server provides accurate predictions of affinity changes caused by mutations in antibody-antigen interactions.
  • Graph-based signatures effectively capture the complex effects of mutations on binding affinity.

Conclusions:

  • mCSM-AB offers a significant advancement in predicting mutation-induced affinity changes in antibody-antigen complexes.
  • The tool enhances the capabilities of antibody engineering and the identification of escape mutations.
  • mCSM-AB is readily accessible via a web server for broader scientific use.