Abbasian, Mahnaz; (2025) A computational approach to investigate the structural and functional consequences of residue mutations in human disease and protein design. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Genes encode information translated into proteins, essential for biological functions. Genetic mutations alter DNA sequences, potentially modifying protein structures and functions with diverse effects. In nature, mutations drive genetic diversity, enabling beneficial innovations or detrimental changes, including extinction. In health and disease, mutations influence susceptibility, resistance, and disease progression, including cancer. These impacts underscore the importance of mutations in evolution, health, and disease. The first project focused on Ideonella sakaiensis PETase (IsPETase), aiming to discover potent PETases with improved substrate binding affinity. Computational algorithms analysed over a billion metagenomic sequences from the MGnify database, narrowing down a PETase subset. Twenty-seven putative PETase sequences were shortlisted, and three demonstrated in vitro activity, marking a discovery in identifying naturally evolved PETases. The second project examined amino acid changes in human and SARS-CoV-2 proteins affecting binding affinity in human:SARS-CoV-2 complexes. Among 450 human protein missense mutations, sixteen were predicted to enhance binding affinity (ΔΔG ≥ 0.5 kcal/mol) with SARS-CoV-2 proteins, involving cell-entry receptors, immune responses, and translation machinery. Additionally, three SARS-CoV-2 mutations were predicted to strengthen interactions with human proteins. This research highlighted genetic variations' potential role in COVID-19 susceptibility across ethnic groups. The final project studied mutations impacting protein function in lung adenocarcinoma (LUAD), analysing data from the TRACERx database. Using paralog protein structures in CATH, FunVar identified functional impact events (FIEs) in known and novel driver genes. Pre-genome duplication FIEs dominated, while post-duplication FIEs contributed to LUAD specialisation. Genes with FIE mutations revealed enriched metabolic pathways in LUAD, providing insights into tumour evolution. Together, these projects advanced understanding of the role of genetic mutations in enzyme evolution, disease susceptibility, and cancer progression.

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