| Grant number: | 20/00144-6 |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| Start date: | July 01, 2020 |
| End date: | June 30, 2023 |
| Field of knowledge: | Biological Sciences - Biochemistry - Chemistry of Macromolecules |
| Principal Investigator: | Fabio Cesar Gozzo |
| Grantee: | Rafael Douglas Clemente Gallo |
| Host Institution: | Instituto de Química (IQ). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil |
| Associated research grant: | 14/17264-3 - New frontiers in structural proteomics: characterizing protein and protein complex structures by mass spectrometry, AP.TEM |
Abstract The structure determination of proteins and their interactions with other proteins are key informations in the elucidation of the mechanism of action of these macromolecules. The combinationof cross-linking with Mass Spectrometry (MS) is a strategy that allows the structural characterization of proteins and protein complexes, especially when high resolution techniques cannot be employed. Mass spectrometry analysis can be considered a universal technique, which can be applied to a large variety of proteins. In addition, this strategy benefits from all the advantages of MS, such as high sensibility, fast analysis and ease of use. Although many protein-protein complexes have been already successfully resolved, there are limitations yet to be addressed, in order to make the cross-linking/MS a more general strategy. Among the greatest challenges in the field, the detection and identification of cross-linked species is of special importance. The current project aims at the development of new Cross-Linking Agents (CLAs) for resolving the problems mentioned above, therefore allowing the enrichment of the number of modified species, thus overcoming their challenging detection. The new CLAs are expected to facilitate the identification of these species due to the use of markers containing mass defects, which should allow a clear distinction between modified and non-modified species. The new families of CLAs proposed here have the potential to generate a great advancement on the quality of the data obtained, and significantly increase the applicability of this technique. (AU) | |
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