Literature DB >> 24599843

Elucidating common structural features of human pathogenic variations using large-scale atomic-resolution protein networks.

Jishnu Das1, Hao Ran Lee, Adithya Sagar, Robert Fragoza, Jin Liang, Xiaomu Wei, Xiujuan Wang, Matthew Mort, Peter D Stenson, David N Cooper, Haiyuan Yu.   

Abstract

With the rapid growth of structural genomics, numerous protein crystal structures have become available. However, the parallel increase in knowledge of the functional principles underlying biological processes, and more specifically the underlying molecular mechanisms of disease, has been less dramatic. This notwithstanding, the study of complex cellular networks has made possible the inference of protein functions on a large scale. Here, we combine the scale of network systems biology with the resolution of traditional structural biology to generate a large-scale atomic-resolution interactome-network comprising 3,398 interactions between 2,890 proteins with a well-defined interaction interface and interface residues for each interaction. Within the framework of this atomic-resolution network, we have explored the structural principles underlying variations causing human-inherited disease. We find that in-frame pathogenic variations are enriched at both the interface and in the interacting domain, suggesting that variations not only at interface "hot-spots," but in the entire interacting domain can result in alterations of interactions. Further, the sites of pathogenic variations are closely related to the biophysical strength of the interactions they perturb. Finally, we show that biochemical alterations consequent to these variations are considerably more disruptive than evolutionary changes, with the most significant alterations at the protein interaction interface.
© 2014 WILEY PERIODICALS, INC.

Entities:  

Keywords:  network systems biology; pathogenic variations; protein-protein interactions; structural biology

Mesh:

Year:  2014        PMID: 24599843      PMCID: PMC4876038          DOI: 10.1002/humu.22534

Source DB:  PubMed          Journal:  Hum Mutat        ISSN: 1059-7794            Impact factor:   4.878


  50 in total

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