Three-dimensional reconstruction of protein networks provides insight into human genetic disease

Xiujuan Wang1,2*, Xiaomu Wei2,3*, Bram Thijssen4*, Jishnu Das1,2*, Steven M Lipkin3 and Haiyuan Yu1,2
Abstract: To better understand the molecular mechanisms and genetic basis of human disease, we systematically examine relationships between 3,949 genes, 62,663 mutations and 3,453 associated disorders by generating a three-dimensional, structurally resolved human interactome. This network consists of 4,222 high-quality binary protein-protein interactions with their atomic-resolution interfaces. We find that in-frame mutations (missense point mutations and in-frame insertions and deletions) are enriched on the interaction interfaces of proteins associated with the corresponding disorders, and that the disease specificity for different mutations of the same gene can be explained by their location within an interface. We also predict 292 candidate genes for 694 unknown disease-to-gene associations with proposed molecular mechanism hypotheses. This work indicates that knowledge of how in-frame disease mutations alter specific interactions is critical to understanding pathogenesis. Structurally resolved interaction networks should be valuable tools for interpreting the wealth of data being generated by large-scale structural genomics and disease association studies. PDF

1Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA
2Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853, USA
3Department of Medicine, Weill Cornell College of Medicine, New York, NY 10021, USA
4Department of Bioinformatics, Maastricht University, 6200 MD Maastricht, The Netherlands
*Equal contributions

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