Mapping genetic variations to three-dimensional protein structures to enhance variant interpretation: a proposed framework

Glusman, Gustavo and Rose, Peter W. and Prlić, Andreas and Dougherty, Jennifer and Duarte, José M. and Hoffman, Andrew S. and Barton, Geoffrey J. and Bendixen, Emøke and Bergquist, Timothy and Bock, Christian and Brunk, Elizabeth and Buljan, Marija and Burley, Stephen K. and Cai, Binghuang and Carter, Hannah and Gao, JianJiong and Godzik, Adam and Heuer, Michael and Hicks, Michael and Hrabe, Thomas and Karchin, Rachel and Leman, Julia Koehler and Lane, Lydie and Masica, David L. and Mooney, Sean D. and Moult, John and Omenn, Gilbert S. and Pearl, Frances and Pejaver, Vikas and Reynolds, Sheila M. and Rokem, Ariel and Schwede, Torsten and Song, Sicheng and Tilgner, Hagen and Valasatava, Yana and Zhang, Yang and Deutsch, Eric W.. (2017) Mapping genetic variations to three-dimensional protein structures to enhance variant interpretation: a proposed framework. Genome medicine, 9 (1). p. 113.

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Official URL: https://edoc.unibas.ch/62447/

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The 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.
Faculties and Departments:05 Faculty of Science > Departement Biozentrum > Computational & Systems Biology > Bioinformatics (Schwede)
10 Zentrale universitäre Einrichtungen > sciCORE
UniBasel Contributors:Schwede, Torsten
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:BioMed Central
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:21 Jun 2018 12:56
Deposited On:21 Jun 2018 12:56

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