| Popis: |
Inherited genetic variation is critical in defining disease susceptibility. PDs, or pathogenic deviations, are mutations reported to be disease-causing, while SNPs, or single nucleotide polymorphisms, are understood to have a negligible effect on phenotype. With recent developments in biotechnology—most relevant being increased reliability and speed of sequencing—a wealth of information regarding SNPs and PDs has been acquired. Quite apart from the analytical challenge of analysing this information with a view to identifying novel therapies and targets for disease, the challenge of simply storing, mapping and processing these data is significant in itself. This thesis describes the development of a large-scale, automated pipeline that provides hypotheses as to what the structural effects of these genomic variations might be. This includes the development of nine new analyses. Eight of these new methods are structural, identifying mutations that disrupt various aspects of protein structure, including the interface, binding sites, folding mechanics and stability. The final new analysis is a novel method of identifying highly conserved residues from sequence. Here, the distribution of conservation scores from a multiple sequence alignment (MSA) is analysed to generate an MSA-specific threshold for high conservation. In order to construct MSAs for the sequence analysis, a novel method for identifying functionally equivalent proteins has been developed. Further, PDs and SNPs are characterised with respect to these structural analyses, and with respect to basic sequence and structural features. The findings support trends elsewhere in the literature: PDs are more often found in the core of proteins and at highly conserved sites; they most often affect the stability of protein structures; and they more often are between very different amino acids. In addition to the implications for disease therapies, these findings are informative in the more general context of protein structure. |
