IMProv: A Resource for Cross-link-Driven Structure Modeling that Accommodates Protein Dynamics

Ziemianowicz, Daniel S.; Saltzberg, Daniel J.; Pells, Troy J.; Crowder, David A.; Schräder, Christoph U.; Hepburn, Morgan; Šali, Andrej; Schriemer, David C.

doi:10.1016/j.mcpro.2021.100139

Cited by 7 publications

(4 citation statements)

References 77 publications

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“…However, almost half ( 21 ) of the densely cross-linked complexes were missing structural information for at least one PPI for which we found cross-linking evidence. These complexes could benefit from integrative structural modeling approaches, such as the cross-link guided modeling pipelines used in Assembline ( 62 ) and IMProv ( 63 ).…”

Section: Resultsmentioning

confidence: 99%

Cross-linking mass spectrometry discovers, evaluates, and corroborates structures and protein–protein interactions in the human cell

Bartolec

Vázquez-Campos

Norman

et al. 2023

Proc. Natl. Acad. Sci. U.S.A.

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Significant recent advances in structural biology, particularly in the field of cryoelectron microscopy, have dramatically expanded our ability to create structural models of proteins and protein complexes. However, many proteins remain refractory to these approaches because of their low abundance, low stability, or—in the case of complexes—simply not having yet been analyzed. Here, we demonstrate the power of using cross-linking mass spectrometry (XL-MS) for the high-throughput experimental assessment of the structures of proteins and protein complexes. This included those produced by high-resolution but in vitro experimental data, as well as in silico predictions based on amino acid sequence alone. We present the largest XL-MS dataset to date, describing 28,910 unique residue pairs captured across 4,084 unique human proteins and 2,110 unique protein–protein interactions. We show that models of proteins and their complexes predicted by AlphaFold2, and inspired and corroborated by the XL-MS data, offer opportunities to deeply mine the structural proteome and interactome and reveal mechanisms underlying protein structure and function.

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Section: Resultsmentioning

confidence: 99%

Cross-linking mass spectrometry discovers, evaluates, and corroborates structures and protein–protein interactions in the human cell

Bartolec

Vázquez-Campos

Norman

et al. 2023

Proc. Natl. Acad. Sci. U.S.A.

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show abstract

“…However, almost half (21) of the densely cross-linked complexes were missing structural information for at least one PPI for which we found cross-linking evidence. These complexes could benefit from integrative structural modelling approaches, such as the cross-link guided modelling pipelines used in Assembline (61) and IMProv (62).…”

Section: Resultsmentioning

confidence: 99%

Cross-linking mass spectrometry discovers, evaluates, and validates the experimental and predicted structural proteome

Bartolec

Vázquez-Campos

Norman

et al. 2022

Preprint

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Significant recent advances in structural biology, particularly in the field of cryo-electron microscopy, have dramatically expanded our ability to create structural models of proteins and protein complexes. However, many proteins remain refractory to these approaches because of their low abundance, low stability or - in the case of complexes - simply not having yet been analysed. Here, we demonstrate the power of combining cross-linking mass spectrometry (XL-MS) with artificial intelligence-based structure prediction to discover and experimentally substantiate models for protein and protein complex structures at proteome scale. We present the deepest XL-MS dataset to date, describing 28,910 unique residue pairs captured across 4,084 unique human proteins and 2,110 unique protein-protein interactions. We show that integrative models of complexes driven by AlphaFold Multimer and inspired and corroborated by the XL-MS data offer new opportunities to deeply mine the structural proteome and interactome and reveal new mechanisms underlying protein structure and function.

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“…Different integrative modeling platforms have been designed to account for different sources of experimental data coming from several in-solution structural techniques to bias docking simulations. IMP/IMProv (Integrative Modeling Platform) and HADDOCK , (High Ambiguity Driven protein–protein DOCKing) are two examples of widely used software solutions for integrating various experimental restraints into final models. The latter has been widely adopted in the structural biology community for its versatility in integrating different flavors of experimental information (each type with different structural resolution) and dealing with ambiguous and/or noisy data.…”

Section: Discussionmentioning

confidence: 99%

Leveraging Cross-Linking Mass Spectrometry for Modeling Antibody–Antigen Complexes

Di Ianni,

Cowan

et al. 2024

J. Proteome Res.

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Elucidating antibody–antigen complexes at the atomic level is of utmost interest for understanding immune responses and designing better therapies. Cross-linking mass spectrometry (XL-MS) has emerged as a powerful tool for mapping protein–protein interactions, suggesting valuable structural insights. However, the use of XL-MS studies to enable epitope/paratope mapping of antibody–antigen complexes is still limited up to now. XL-MS data can be used to drive integrative modeling of antibody–antigen complexes, where cross-links information serves as distance restraints for the precise determination of binding interfaces. In this approach, XL-MS data are employed to identify connections between binding interfaces of the antibody and the antigen, thus informing molecular modeling. Current literature provides minimal input about the impact of XL-MS data on the integrative modeling of antibody–antigen complexes. Here, we applied XL-MS to retrieve information about binding interfaces of three antibody–antigen complexes. We leveraged XL-MS data to perform integrative modeling using HADDOCK (active-passive residues and distance restraints strategies) and AlphaLink2. We then compared these three approaches with initial predictions of investigated antibody–antigen complexes by AlphaFold Multimer. This work emphasizes the importance of cross-linking data in resolving conformational dynamics of antibody–antigen complexes, ultimately enhancing the design of better protein therapeutics and vaccines.

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IMProv: A Resource for Cross-link-Driven Structure Modeling that Accommodates Protein Dynamics

Cited by 7 publications

References 77 publications

Cross-linking mass spectrometry discovers, evaluates, and corroborates structures and protein–protein interactions in the human cell

Cross-linking mass spectrometry discovers, evaluates, and corroborates structures and protein–protein interactions in the human cell

Cross-linking mass spectrometry discovers, evaluates, and validates the experimental and predicted structural proteome

Leveraging Cross-Linking Mass Spectrometry for Modeling Antibody–Antigen Complexes

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