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Mapping genetic variations to three- dimensional protein structures to enhance variant interpretation: a proposed framework
journal contribution
posted on 2023-06-09, 14:24 authored by Gustavo Glusman, Peter W Rose, Andrea Prlic, Jennifer Dougherty, José M Duarte, Andrew S Hoffmann, Geoffery J Barton, Emøke Bendixen, Timothy Bergquist, Christian Bock, Elizabeth Brunk, Marija Buljan, Stephen K Burley, Binguang Cai, Hannah Carter, JiangJong Gao, Adam Godzik, Michael Heuer, Michael Hicks, Thomas Hrabe, Rachel Karchin, Julia Kohler Leman, Lydie Lane, David L Masica, Sean D Mooney, John Moult, Gilbert S Omenn, Frances PearlFrances Pearl, Vikas Pejavar, Sheila M Reynolds, Ariel Rokem, Torsten Schwede, Sicheng Song, Hagen Tilger, Yana Valasatava, Yang Zhang, Eric W DeutschThe translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods.
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Publication status
- Published
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- Published version
Journal
Genome MedicineISSN
1756-994XPublisher
BioMed CentralExternal DOI
Issue
113Volume
9Page range
1-10Department affiliated with
- Biochemistry Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2018-08-07First Open Access (FOA) Date
2018-08-07First Compliant Deposit (FCD) Date
2018-08-06Usage metrics
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