SysGen Seminar – David Ascher – 23rd June, 2017
Bio21 & School of Biomedical Sciences, University of Melbourne
Friday 23rd June
Theatre 2 (Room 219), Level 2, 200 Berkeley Street, The University of Melbourne
Unravelling the molecular mechanisms behind mutations and their link to phenotypes using graph-based signatures
The vast majority of coding variants are rare, and assessment of the contribution of rare variants is hampered by low statistical power and limited functional data. Elucidating the molecular mechanisms linking a mutation’s impact with phenotype is very often non-trivial, and functional interpretation of mutation data has consequently lagged behind generation of the data from modern high-throughput techniques. This is complicated by the multitude of effects a mutation may have on a proteins function.
We have developed a suite of programs that uses graph-based signatures to represent the wild-type environment of a residue in order to predict the effects of a mutation on protein stability and affinity for protein partners, nucleic acids, metal ions and small molecules, including drugs and ligands. We present here a novel knowledge-guided integrated, scalable computational workflow designed to evaluate the effects of missense mutations on protein structure and interactions, and associate these effects with phenotypic data.
Using this pipeline, we have analysed hundreds of mutations generated in saturation mutagenesis studies of DBR1 and Gal4 and show that the experimental phenotypes correlate well with the predictions for over 80% of the mutations. This methodology has also allowed us to correlate mutations in VHL with the risk of developing renal cell carcinoma to guide patient treatment; analysis of the consequences of mutations in the Mendelian disease Alkaptonuria, which are being used to guide clinical trial analysis; and led to the automatic characterisation of drug resistance mutations from whole-genomic sequencing of Tuberculosis. These examples highlight that structural bioinformatics tools, when applied in a systematic, integrated way, can provide a powerful and scalable approach for predicting structural and functional consequences of mutations in order to reveal molecular mechanisms leading to clinical and experimental phenotypes.
David Ascher is an NHMRC CJ Martin Fellow and Head of the Structural Biology and Bioinformatics Laboratory in the Department of Biochemistry and Molecular Biology. After obtaining his PhD in protein crystallography and enzyme kinetics from the University of Melbourne in 2013, David took up independent fellowships at the University of Cambridge, returning to Australia in 2016. His laboratory’s research focusses on unravelling the link between genotype and phenotype, using computational and experimental approaches to understand the effects of mutations on protein structure and function. They have developed a platform of over 14 widely used programs, which have been used in experimental design, drug development, and the optimisation of biotechnological processes. This work has provided insights into the development of drug resistance and genetic diseases, which has been implemented at Addenbrooke’s Hospital for patient management of renal carcinomas.
Enquiries: Andrew Siebel (email@example.com)