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Elucidating Common Structural Features of Human Pathogenic Variations Using Large‐Scale Atomic‐Resolution Protein Networks
Author(s) -
Das Jishnu,
Lee Hao Ran,
Sagar Adithya,
Fragoza Robert,
Liang Jin,
Wei Xiaomu,
Wang Xiujuan,
Mort Matthew,
Stenson Peter D.,
Cooper David N.,
Yu Haiyuan
Publication year - 2014
Publication title -
human mutation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 162
eISSN - 1098-1004
pISSN - 1059-7794
DOI - 10.1002/humu.22534
Subject(s) - interactome , biology , computational biology , interface (matter) , interaction network , structural genomics , domain (mathematical analysis) , resolution (logic) , scale (ratio) , protein–protein interaction , atomic units , inference , systems biology , protein structure , genetics , computer science , physics , gene , artificial intelligence , biochemistry , pulmonary surfactant , mathematical analysis , quantum mechanics , gibbs isotherm , mathematics
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.