A combined bioinformatics and experimental approach towards the molecular phenotype of disease-causing single point mutations.

• Main Author: Lim, Radiance Hui Ting.
• Other Authors: School of Biological Sciences
• Format: Final Year Project
• Language: English
• Published: 2010
• Subjects: DRNTU::Science::Biological sciences::Biochemistry
• Online Access: http://hdl.handle.net/10356/40118
• Institution: Nanyang Technological University

Towards unravelling the enigmatic sequence-structure-function relationship, this study presents a computational-experimental strategy to characterise the effects of disease mutations on protein structure stability and misfolding phenotypes. Firstly, suitable candidates from normally secreted human proteins with a disease-associated non-synonymous single nucleotide polymorphism within a domain of known structure were shortlisted through a newly developed bioinformatics workflow. To predict changes in stability upon mutation, a ΔΔG was calculated for each candidate using the FoldX force field. The two selected candidates are defective lysosomal exoglycohydrolases implicated in Fabry disease: α-galactosidase A C202W and S297F. The native and mutated proteins were overexpressed in model cell lines and changes in subcellular distribution and secretion observed. Intriguingly, the C202W mutant was secreted although at a lower level than the native protein while the S297F mutant was fully retained in the cell. Lysosomal targeting and catalytic function were most efficient in the native protein and significantly impaired in the S297F mutant. As additional control, an I91V mutant with minimal ΔΔG was examined and indeed its phenotype and function were close to native. Therefore, this work illustrates the power of a combined bioinformatics and experimental approach towards understanding the molecular mechanisms underpinning protein folding and disease pathogenesis.