Browsing by Author "Jaafari, Hana"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
Item Evolutionary Fitness of Non-Coding Genetic Elements(2024-04-19) Jaafari, Hana; Wolynes, Peter GProper protein structure and function are integral to cellular homeostasis. The wide array of known natural protein sequences are a product of millions of years of evolutionary pressure maintaining physical stability and biological function. The evolutionary process occurs via random instances of structural and sequence variations in the genome. While typically neutral in protein-coding genes, such variations can result in the loss of function of a protein-coding gene or produce a novel protein-coding gene. A former protein-coding gene can behave as a reservoir for novel protein-coding genes or variants of known proteins. This dissertation features work that examines the evolutionary fitness of two classes of genetic elements, pseudogenes and exons, that may encode functional amino acid sequences. In Chapter 1 of this dissertation, we introduce the concepts and tools employed in later chapters. We provide a conceptual overview of pseudogenes and exons, as well as review past works that examine the physical stabilities of their encoded amino acid sequences. We also discuss the energy landscape theory and the physical energy function-- the Associative Memory, Water Mediated, Structure and Energy Model (AWSEM)--informed by the theory's principles. We finally discuss the Direct Coupling Analysis (DCA) model, which, when used alongside the AWSEM Hamiltonian, provides information on the physical stability and biological function of a protein sequence. In Chapter 2 of this dissertation, we present work characterizing the physical and evolutionary energy landscapes of pseudogenes, former protein coding genes found in many eukaryotes that cannot be translated due to debilitating mutations. Given these genetic elements previously experienced selection pressure to fold, pseudogenes are an intriguing example of protein devolution. We systematically studied pseudogenes associated with an array of proteins varying in biological function and size. We found that, if translated, pseudogene sequences are typically destabilized relative to their former native state as a function of evolutionary time. Pseudogene sequences that inversely become more physically stable as a result of their mutations have diminished or altered functional abilities that may result in pathological conditions. In Chapter 3 of this dissertation, we present work that evaluates the physical energy landscapes of exons, genetic elements that encode amino acid sequences in eukaryotic genes. If exons encode independently foldable structural units, naturally occurring or engineered exon shuffling can quickly produce novel protein coding genes. Using publicly available databases of annotated protein sequences and gene structures, we identify conserved exons in multiple protein families. We find that conserved exons tend to be minimally frustrated, with these exons' boundaries coinciding with secondary structural element boundaries. Our findings support previous works suggesting exons can encode physically stable protein segments.Item Pseudogene Energy Landscapes: A Frustrating Case of Neutral Evolution?(2020-10-07) Jaafari, Hana; Wolynes, PeterFunctional proteins are optimized by evolution over the course of millions of years to quickly fold into their native three-dimensional structures. Evolution exerts a strong selection pressure on protein sequences to maintain foldability and stability, resulting in minimally frustrated folding energy landscapes. Pseudogenes, genetic elements homologous to coding genes, are evolutionary relics of the genome experiencing little or no selection pressure. Pseudogenes are ideal candidates to examine the energy landscapes of devolving genetic elements. This thesis project is the first to quantify the “evolutionary” energies, measured with Direct Coupling Analysis (DCA), of pseudogenes across multiple protein families. The DCA energies of pseudogenes, their parent proteins, and other proteins within each family were examined, and the results of these studies suggest that pseudogenes become less well optimized from an evolutionary standpoint over time. Indeed, analyses of the DCA energies of mutants generated in silico indicated that pseudogenes devolve just as rapidly as completely randomly mutated parent genes.