Introducing dysfunctional Protein-Protein Interactome (dfPPI) – A platform for systems-level protein-protein interaction (PPI) dysfunction investigation in disease Review
| Authors: | Chakrabarty, S.; Wang, S.; Roychowdhury, T.; Ginsberg, S. D.; Chiosis, G. |
| Review Title: | Introducing dysfunctional Protein-Protein Interactome (dfPPI) – A platform for systems-level protein-protein interaction (PPI) dysfunction investigation in disease |
| Abstract: | Protein-protein interactions (PPIs) play a crucial role in cellular function and disease manifestation, with dysfunctions in PPI networks providing a direct link between stressors and phenotype. The dysfunctional Protein-Protein Interactome (dfPPI) platform, formerly known as epichaperomics, is a newly developed chemoproteomic method aimed at detecting dynamic changes at the systems level in PPI networks under stressor-induced cellular perturbations within disease states. This review provides an overview of dfPPIs, emphasizing the novel methodology, data analytics, and applications in disease research. dfPPI has applications in cancer research, where it identifies dysfunctions integral to maintaining malignant phenotypes and discovers strategies to enhance the efficacy of current therapies. In neurodegenerative disorders, dfPPI uncovers critical dysfunctions in cellular processes and stressor-specific vulnerabilities. Challenges, including data complexity and the potential for integration with other omics datasets are discussed. The dfPPI platform is a potent tool for dissecting disease systems biology by directly informing on dysfunctions in PPI networks and holds promise for advancing disease identification and therapeutics. © 2024 The Authors |
| Keywords: | review; nonhuman; phenotype; cell function; protein protein interaction; degenerative disease; systems biology; human; omics |
| Journal Title: | Current Opinion in Structural Biology |
| Volume: | 88 |
| ISSN: | 0959-440X |
| Publisher: | Elsevier Inc. |
| Date Published: | 2024-10-01 |
| Start Page: | 102886 |
| Language: | English |
| DOI: | 10.1016/j.sbi.2024.102886 |
| PROVIDER: | scopus |
| PUBMED: | 39003916 |
| DOI/URL: | |
| Notes: | The MSK Cancer Center Support Grant (P30 CA008748) is acknowledged in the PDF. Corresponding MSK author is Gabriela Chiosis -- Source: Scopus |
Altmetric
Citation Impact
BMJ Impact Analytics
MSK Authors
Related MSK Work