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XPlex: an effective, multiplex cross-linking chemistry for acidic residues

Fioramonte, Mariana, de Jesus, Hugo Cesar Ramos, Ferrari, Allan Jhonathan Ramos, Lima, Diogo Borges, Drekener, Roberta Lopes, Correia, Carlos Roque Duarte, Gonzaga De Oliveira, Luciana, Neves-Ferreira, Ana Gisele da Costa, Carvalho, Paulo Costa and Gozzo, Fabio Cesar 2018. XPlex: an effective, multiplex cross-linking chemistry for acidic residues. Analytical Chemistry 90 (10) , pp. 6043-6050. 10.1021/acs.analchem.7b05135

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Cross-linking/Mass spectrometry (XLMS) is a consolidated technique for structural characterization of proteins and protein complexes. Despite its success, the cross-linking chemistry currently used is mostly based on N-hydroxysuccinimide (NHS) esters, which react primarily with lysine residues. One way to expand the current applicability of XLMS into several new areas is to increase the number of cross-links obtainable for a target protein. We introduce a multiplex chemistry (denoted XPlex) that targets Asp, Glu, Lys, and Ser residues. XPlex can generate significantly more cross-links with reactions occurring at lower temperatures and enables targeting proteins that are not possible with NHS ester-based cross-linkers. We demonstrate the effectiveness of our approach in model proteins as well as a target Lys-poor protein, SalBIII. Identification of XPlex spectra requires a search engine capable of simultaneously considering multiple cross-linkers on the same run; to achieve this, we updated the SIM-XL search algorithm with a search mode tailored toward XPlex. In summary, we present a complete chemistry/computational solution for significantly increasing the number of possible distance constraints by mass spectrometry experiments, and thus, we are convinced that XPlex poses as a real complementary approach for structural proteomics studies.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Chemistry
Publisher: American Chemical Society
ISSN: 0003-2700
Date of Acceptance: 22 March 2018
Last Modified: 14 Nov 2022 16:06

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