Ribosomal History Reveals Origins of Modern Protein Synthesis

The origin and evolution of the ribosome is central to our understanding of the cellular world. Most hypotheses posit that the ribosome originated in the peptidyl transferase center of the large ribosomal subunit. However, these proposals do not link protein synthesis to RNA recognition and do not use a phylogenetic comparative framework to study ribosomal evolution. Here we infer evolution of the structural components of the ribosome. Phylogenetic methods widely used in morphometrics are applied directly to RNA structures of thousands of molecules and to a census of protein structures in hundreds of genomes. We find that components of the small subunit involved in ribosomal processivity evolved earlier than the catalytic peptidyl transferase center responsible for protein synthesis. Remarkably, subunit RNA and proteins coevolved, starting with interactions between the oldest proteins (S12 and S17) and the oldest substructure (the ribosomal ratchet) in the small subunit and ending with the rise of a modern multi-subunit ribosome. Ancestral ribonucleoprotein components show similarities to in vitro evolved RNA replicase ribozymes and protein structures in extant replication machinery. Our study therefore provides important clues about the chicken-or-egg dilemma associated with the central dogma of molecular biology by showing that ribosomal history is driven by the gradual structural accretion of protein and RNA structures. Most importantly, results suggest that functionally important and conserved regions of the ribosome were recruited and could be relics of an ancient ribonucleoprotein world

Computational Approaches to Drug Profiling and Drug-Protein Interactions

Despite substantial increases in R&D spending within the pharmaceutical industry, denovo drug design has become a time-consuming endeavour. High attrition rates led to a long period of stagnation in drug approvals. Due to the extreme costs associated with introducing a drug to the market, locating and understanding the reasons for clinical failure is key to future productivity. As part of this PhD, three main contributions were made in this respect. First, the web platform, LigNFam enables users to interactively explore similarity relationships between ‘drug like’ molecules and the proteins they bind. Secondly, two deep-learning-based binding site comparison tools were developed, competing with the state-of-the-art over benchmark datasets. The models have the ability to predict offtarget interactions and potential candidates for target-based drug repurposing. Finally, the open-source ScaffoldGraph software was presented for the analysis of hierarchical scaffold relationships and has already been used in multiple projects, including integration into a virtual screening pipeline to increase the tractability of ultra-large screening experiments. Together, and with existing tools, the contributions made will aid in the understanding of drug-protein relationships, particularly in the fields of off-target prediction and drug repurposing, helping to design better drugs faster