|Ph.D Student||David Eden Hilda|
|Subject||Computational Approaches for Identifying Novel Drug Binding|
Sites on the Ribosome
|Department||Department of Biology||Supervisor||Professor Yael Mandel-Gutfreun|
|Full Thesis text|
The ribosome represents a major target for antibacterial drugs. In spite of its enormous size, most known drugs bind to few major functional sites. High evolutionary conservation of many rRNA regions on the ribosome suggests that they may have critical roles in protein synthesis, but in many cases their function is unknown. In theory, many of these yet unknown functional sites could also be good candidates for antibiotics action. The main goal of this research was to perform computational analysis in order to identify new functional sites in the ribosome which can potentially serve as new antibiotic target sites.
We modeled the ribosome structure as a network where nucleotides are represented as nodes and intermolecular interactions as edges. As shown previously for proteins, we show that the major functional sites of the ribosome exhibit significantly high centrality. Overall, the network representation is used to characterize functional sites and is suggested as a comparative tool to reveal the unique properties of the ribosome.
In order to study the characteristic of antibiotics binding sites in the ribosome, we compared the properties of known antibiotics binding sites to a collection of computed pockets which could potentially act as binding sites. To this aim we applied an algorithm to extract all pockets in the ribosome that have similar dimensions to known binding sites, and obtained a large number of pockets that are readily accessible to small ligands. Further, we have analyzed the structural, chemical, and evolutionary properties of 64 antibiotic binding sites identified by crystallography. We compared the properties of these sites to the properties of putative small molecule binding pockets extracted from the small and large ribosomal subunits. Based on this analysis, we defined properties of the known drug binding sites, which constitute a signature of a ‘druggable’ site.
In summary, we propose that albeit the different geometric and chemical properties of diverse antibiotics, their binding site tend to have common attributes, possibly reflecting the potency of the pocket for binding small organic molecules. Finally, we utilized the ensemble of found properties to derive a druggability index, which can be used for a systematic identification of new ribosomal sites that could be targeted by small molecular weight ligands, including new antibiotics.