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PXD043347

PXD043347 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleEpitope and Paratope Mapping of TNFα/Infliximab complex by cross-linking mass spectrometry and integrative modeling reveals high level of interaction specificity
DescriptionMass spectrometry (MS) has become one of the core technologies to study protein structures, protein-ligand and protein-protein interactions. Chemical cross-linking combined with mass spectrometry (XL-MS) is quickly spreading over different biochemistry laboratories for the continuous increase of its biological applications and standardized protocols that make it attractive for academia and industry research scientists. In recent years, XL-MS has developed as a powerful technique in structural biology, from studying structures of purified proteins in vitro to deciphering intricate protein-protein interaction (PPI) networks in cells, organelles and tissues on a system-wide scale. However, the number of XL-MS studies for the inves-tigation of epitope/paratope mapping of antigen-antibody complexes is still limited up to now. In this manuscript, we devel-oped a simple, fast and automated workflow to define the interaction interface between the chimeric antibody Infliximab (IFX) and its own target, the Tumor Necrosis Factor alpha (TNFα). This workflow integrates XL-MS data to identify areas in proximity to the binding regions and epitope/paratope probability calculation to pinpoint the antigen-antibody binding sites. The data are combined to generate refined 3D models of the antigen-antibody complex which closely resemble the X-ray IFX/TNFα structure and capture their correct interaction surface. The present workflow can be applied to investigate any antigen-antibody complex, even when no previous structural knowledge is available. This strategy is a fascinating oppor-tunity to thoroughly characterize antigen-antibody interactions and to allow the understanding of their binding mechanisms in order to properly design better antibody therapeutics in the future
HostingRepositoryPRIDE
AnnounceDate2024-02-27
AnnouncementXMLSubmission_2024-02-27_07:34:05.767.xml
DigitalObjectIdentifier
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
PrimarySubmitterAndrea Di Ianni
SpeciesList scientific name: Escherichia coli; NCBI TaxID: 562;
ModificationListNo PTMs are included in the dataset
InstrumentQ Exactive
Dataset History
RevisionDatetimeStatusChangeLog Entry
02023-06-27 10:28:17ID requested
12024-02-27 07:34:06announced
Publication List
10.1021/acs.jproteome.3c00816;
Di Ianni A, Di Ianni A, Cowan K, Barbero LM, Sirtori FR, Leveraging Cross-Linking Mass Spectrometry for Modeling Antibody-Antigen Complexes. J Proteome Res, 23(3):1049-1061(2024) [pubmed]
Keyword List
submitter keyword: Cross-linking mass spectrometry
Monoclonal antibodies
Integrative modeling
Epitope/Paratope mapping
Contact List
Luca Barbero
contact affiliationNBE-DMPK Innovative BioAnalytics, Merck Serono RBM S.p.A., an affiliate of Merck KGaA, Darmstadt, Germany, Via Ribes 1, 10010 Colleretto Giacosa (TO)
contact emailluca.barbero@merckgroup.com
lab head
Andrea Di Ianni
contact affiliationMerck KGaA
contact emailandrea.di-ianni@external.merckgroup.com
dataset submitter
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Dataset FTP location
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