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Epitope Mapping with Sidewinder : An XL-MS and Structural Modeling Approach

Ströbaek, Joel LU ; Tang, Di LU orcid ; Gueto-Tettay, Carlos LU ; Gomez Toledo, Alejandro LU ; Olofsson, Berit LU orcid ; Hartman, Erik LU orcid ; Heusel, Moritz LU ; Malmström, Johan LU orcid and Malmström, Lars LU (2025) In International Journal of Molecular Sciences 26(4). p.1-17
Abstract

Antibodies are critical to the host's immune defense against bacterial pathogens. Understanding the mechanisms of antibody-antigen interactions is essential for developing new targeted immunotherapies. Building computational workflows that can identify where an antibody binds its cognate antigen and deconvoluting the interaction interface in a high-throughput manner are critical for advancing this field. Cross-linking mass spectrometry (XL-MS) integrated with structural modeling offers a flexible and high-resolution strategy to map protein-protein interactions from low sample amounts. However, cross-linking and in silico modeling have limitations that require robust analytical workflows to make accurate inferences. In this study, we... (More)

Antibodies are critical to the host's immune defense against bacterial pathogens. Understanding the mechanisms of antibody-antigen interactions is essential for developing new targeted immunotherapies. Building computational workflows that can identify where an antibody binds its cognate antigen and deconvoluting the interaction interface in a high-throughput manner are critical for advancing this field. Cross-linking mass spectrometry (XL-MS) integrated with structural modeling offers a flexible and high-resolution strategy to map protein-protein interactions from low sample amounts. However, cross-linking and in silico modeling have limitations that require robust analytical workflows to make accurate inferences. In this study, we introduce Sidewinder, a modular high-throughput pipeline combining state-of-the-art computational structural prediction and molecular docking with rapid XL-MS analysis, enabling comprehensive interrogation of antibody-antigen systems. We validated this pipeline on antibodies targeting two Streptococcus pyogenes virulence factors. Using recently published data, we identified a well-defined monoclonal antibody epitope on Streptolysin O by generating and querying a large ensemble of interaction models probabilistically. We also showcased the utility of the Sidewinder pipeline by analyzing a more complex system, involving monoclonal antibodies that target the cell wall-anchored M1 protein. The flexibility and robustness of the Sidewinder pipeline provide a powerful framework for future studies of complex antibody-antigen systems, potentially leading to new therapeutic strategies.

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author
; ; ; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Epitope Mapping/methods, Streptococcus pyogenes/immunology, Bacterial Proteins/chemistry, Molecular Docking Simulation, Antibodies, Monoclonal/chemistry, Mass Spectrometry/methods, Epitopes/immunology, Streptolysins/chemistry, Antibodies, Bacterial/immunology
in
International Journal of Molecular Sciences
volume
26
issue
4
article number
1488
pages
1 - 17
publisher
MDPI AG
external identifiers
  • pmid:40003954
  • scopus:85218901966
ISSN
1422-0067
DOI
10.3390/ijms26041488
language
English
LU publication?
yes
id
18960a88-0ea4-4ce7-a6c1-34132a89496d
date added to LUP
2025-02-27 04:39:08
date last changed
2025-05-13 04:54:16
@article{18960a88-0ea4-4ce7-a6c1-34132a89496d,
  abstract     = {{<p>Antibodies are critical to the host's immune defense against bacterial pathogens. Understanding the mechanisms of antibody-antigen interactions is essential for developing new targeted immunotherapies. Building computational workflows that can identify where an antibody binds its cognate antigen and deconvoluting the interaction interface in a high-throughput manner are critical for advancing this field. Cross-linking mass spectrometry (XL-MS) integrated with structural modeling offers a flexible and high-resolution strategy to map protein-protein interactions from low sample amounts. However, cross-linking and in silico modeling have limitations that require robust analytical workflows to make accurate inferences. In this study, we introduce Sidewinder, a modular high-throughput pipeline combining state-of-the-art computational structural prediction and molecular docking with rapid XL-MS analysis, enabling comprehensive interrogation of antibody-antigen systems. We validated this pipeline on antibodies targeting two Streptococcus pyogenes virulence factors. Using recently published data, we identified a well-defined monoclonal antibody epitope on Streptolysin O by generating and querying a large ensemble of interaction models probabilistically. We also showcased the utility of the Sidewinder pipeline by analyzing a more complex system, involving monoclonal antibodies that target the cell wall-anchored M1 protein. The flexibility and robustness of the Sidewinder pipeline provide a powerful framework for future studies of complex antibody-antigen systems, potentially leading to new therapeutic strategies. </p>}},
  author       = {{Ströbaek, Joel and Tang, Di and Gueto-Tettay, Carlos and Gomez Toledo, Alejandro and Olofsson, Berit and Hartman, Erik and Heusel, Moritz and Malmström, Johan and Malmström, Lars}},
  issn         = {{1422-0067}},
  keywords     = {{Epitope Mapping/methods; Streptococcus pyogenes/immunology; Bacterial Proteins/chemistry; Molecular Docking Simulation; Antibodies, Monoclonal/chemistry; Mass Spectrometry/methods; Epitopes/immunology; Streptolysins/chemistry; Antibodies, Bacterial/immunology}},
  language     = {{eng}},
  month        = {{02}},
  number       = {{4}},
  pages        = {{1--17}},
  publisher    = {{MDPI AG}},
  series       = {{International Journal of Molecular Sciences}},
  title        = {{Epitope Mapping with Sidewinder : An XL-MS and Structural Modeling Approach}},
  url          = {{http://dx.doi.org/10.3390/ijms26041488}},
  doi          = {{10.3390/ijms26041488}},
  volume       = {{26}},
  year         = {{2025}},
}