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In Vivo Modeling of the Morbid Human Genome using Danio rerio
Published on: August 24, 2013
Structural bioinformatics mutation analysis reveals genotype-phenotype correlations in von Hippel-Lindau disease and
Julia R Forman1, Catherine L Worth, G Richard J Bickerton
1Biocomputing Group, Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, United Kingdom. julia@cryst.bioc.cam.ac.uk
Abstract:
Mutations in the VHL gene lead to von Hippel-Lindau (VHL) disease, a clinically heterogeneous cancer syndrome. Here, we use software and database tools to understand and predict the phenotypes associated with missense mutations in the VHL gene product, pVHL. The protein product pVHL is known to interact with elongin B, elongin C, and the HIF substrate. By analyzing known and predicted interaction sites and predictions of thermodynamic stability change upon mutation, we generate new hypotheses regarding the molecular etiology of renal cell carcinoma (RCC) and pheochromocytoma (PCC) in VHL disease. We find that the molecular causes of RCC and PCC appear to be decoupled. RCC may arise through two distinct mechanisms: disruption of HIF interactions or binding at the elongin B interface. PCC is triggered by mutations which disrupt interactions at the elongin C binding site. These findings have important implications for VHL disease and for nonfamilial RCC, because most cases of clear cell RCC are linked with VHL inactivation. Additionally, predicting effects of genetic variation will be critical as genetic sequencing accelerates; the analytical strategy presented here may elucidate other systems as further data on genetic variation become available.
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