Rallapalli, PM; (2014) Interactive locus-specific databases and evolutionary aspects of the mutations in coagulation proteins. Doctoral thesis , UCL (University College London).

Abstract

Blood coagulation occurs through a cascade of enzymes and cofactors that produces a fibrin clot, while otherwise maintaining haemostasis. The 11 human coagulation factors (FG, FII-FXIII) are associated with thousands of mutations. Variations caused by these mutations are the basis for evolutionary consequences and several of these mutations are also associated with clinically diagnosable bleeding disorders. Trailing the success of sequencing and diagnostic methods, increasing numbers of mutations are being compiled in order to present a more detailed patient-specific description of the disease. This thesis describes an interactive locus-specific database system in which the mutations in patients with haemophilia (A and B) are presented in searchable formats, and viewed in comparisons against protein structures and sequence alignments. The approach used within these databases are set up in a way that they could be extended and combined with a database management system to design a mutation database for the other bleeding disorders of the coagulation system. Our main focus was to correlate the protein sequence and structure with their functional interactions, also keeping in mind the evolutionary selective pressure at the mutation sites. We evaluated the strength of selective pressures on the 11 coagulation factors during vertebrate evolution, and compared these with human mutations in FVIII, FIX and FXI. We have showed that the coagulation system in vertebrates was under strong selective pressures, perhaps to adapt against blood-invading pathogens. It was concluded that when a site was under positive selection, it was less likely to be associated with disease-causing mutations. In contrast, sites under negative selection were more likely to be associated with disease-causing mutations and be destabilizing. The scientific design of the databases with improved understanding of evolutionary changes will lead to a more comprehensive comparative understanding of the genetic factors that influence bleeding risk thus providing optimised genetic services.

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