Mechnetor

• Verfasst von: González Sánchez, Juan Carlos [VerfasserIn]
• Verfasst von: Ibrahim, Mustafa F. R. [VerfasserIn]
• Verfasst von: Leist, Ivo C. [VerfasserIn]
• Verfasst von: Weise, Kyle R. [VerfasserIn]
• Verfasst von: Russell, Robert B. [VerfasserIn]
• Titel: Mechnetor
• Titelzusatz: a web server for exploring protein mechanism and the functional context of genetic variants
• Verf.angabe: Juan Carlos González-Sánchez, Mustafa F.R. Ibrahim, Ivo C. Leist, Kyle R. Weise and Robert B. Russell
• E-Jahr: 2021
• Jahr: 2 June 2021
• Umfang: 9 S.
• Teil: volume:49
• Teil: year:2021
• Teil: number:W1
• Teil: pages:W366-W374
• Teil: extent:9
• Fussnoten: Gesehen am 12.08.2021
• Titel Quelle: Enthalten in: Nucleic acids research
• Ort Quelle: Oxford : Oxford Univ. Press, 1974
• Jahr Quelle: 2021
• Band/Heft Quelle: 49(2021), W1, Seite W366-W374
• ISSN Quelle: 1362-4962
• DOI: doi:10.1093/nar/gkab399
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: catalog
• Sach-SW: channel
• Sach-SW: motif
• Sach-SW: mutations
• Sach-SW: visualization
• K10plus-PPN: 1766552811

Abstract

Advances in DNA sequencing and proteomics mean that researchers must now regularly interrogate thousands of positional gene/protein changes in order to find those relevant for potential clinical application or biological insights. The abundance of already known information on protein interactions, mechanism, and tertiary structure provides the possible means to understand these changes rapidly, though a careful and systematic integration of these diverse datasets is first needed. For this purpose, we developed Mechnetor, a tool that allows users to quickly explore and visualize integrated mechanistic data for proteins or interactions of interest. Central to the system is a careful cataloguing of diverse sources of protein interaction mechanism, and an efficient means to visualize interactions between relevant and/or known protein regions. The result is a finer resolution interaction network that provides more immediate clues as to points of intervention or mechanistic understanding. Users can import protein, interactions, genetic variants or post-translational modifications and see these data in the best known mechanistic context. We demonstrate the tool with topical examples in human genetic diseases and cancer genomics.