Article ; Online: Mass spectrometry-based protein-protein interaction networks for the study of human diseases.
2021 Volume 17, Issue 1, Page(s) e8792
Abstract: A better understanding of the molecular mechanisms underlying disease is key for expediting the development of novel therapeutic interventions. Disease mechanisms are often mediated by interactions between proteins. Insights into the physical rewiring of ...
| Abstract | A better understanding of the molecular mechanisms underlying disease is key for expediting the development of novel therapeutic interventions. Disease mechanisms are often mediated by interactions between proteins. Insights into the physical rewiring of protein-protein interactions in response to mutations, pathological conditions, or pathogen infection can advance our understanding of disease etiology, progression, and pathogenesis and can lead to the identification of potential druggable targets. Advances in quantitative mass spectrometry (MS)-based approaches have allowed unbiased mapping of these disease-mediated changes in protein-protein interactions on a global scale. Here, we review MS techniques that have been instrumental for the identification of protein-protein interactions at a system-level, and we discuss the challenges associated with these methodologies as well as novel MS advancements that aim to address these challenges. An overview of examples from diverse disease contexts illustrates the potential of MS-based protein-protein interaction mapping approaches for revealing disease mechanisms, pinpointing new therapeutic targets, and eventually moving toward personalized applications. |
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| MeSH term(s) | Disease/genetics ; Gene Regulatory Networks ; Humans ; Mass Spectrometry ; Protein Interaction Mapping/methods |
| Language | English |
| Publishing date | 2021-01-12 |
| Publishing country | England |
| Document type | Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S. ; Review |
| ZDB-ID | 2193510-5 |
| ISSN | 1744-4292 ; 1744-4292 |
| ISSN (online) | 1744-4292 |
| ISSN | 1744-4292 |
| DOI | 10.15252/msb.20188792 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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