Pharmacology & Drug Development Congress
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Accepted Abstracts

Development of In Silico Sequence Based Method for Homology Modeling of High Resolution Three Dimensional Ribosome Structure, and its Application in Virtual Screening and Validation of Potential Lead Compound Targeting RNA

Francis Mulaa*, Harrison Ndungu Mwangi, Peter Waiganjo Wagacha, Accadius Lunayo and Fredrick Sijenyi
University of Nairobi, Kenya

Citation: Mulaa F, Mwangi HN, Wagacha PW, Lunayo A, Sijenyi F (2020) Development of In Silico Sequence Based Method for Homology Modeling of High Resolution Three Dimensional Ribosome Structure, and its Application in Virtual Screening and Validation of Potential Lead Compound Targeting RNA. SciTech Central Pharma 2020. Maurituis 

Received: January 13, 2020         Accepted: January 20, 2020         Published: January 20, 2020

Abstract

Presented is a method of producing reliable high resolution atomic level 3D-models of RNA structures efficiently and cheaply, using sequence information only implemented in silico. This includes obtaining a manually curated digital 3-D models and for generating RNA motifs. Because the functionally important regions of rRNA are conserved among eukaryotes and prokaryotes, motifs generated using the said method, can be used to screen for drug leads developed against conserved targets in the eukaryote and prokaryote system which may produce broad-spectrum anti-infectives. However, in order to develop a system to produce narrow-spectrum anti-infectives, we present methods and compositions for screening, generating high resolution atomic level rRNA structures of eukaryote and 18S rRNA and prokaryote 16S rRNA. The generated high resolution homology 18S and 16S rRNA ribosome structures can be mutated in silico to mimic mutations under drug resistance, replace the natural motifs region with the corresponding region of the rRNA, as encountered in functional ribosomes in host cells and use of generated 3D atomic structures as targets to probe ligands. With the developed technology platform, that allows the generation of high atomic level resolution of pathogen ribosome’s crystal structures, we demonstrate that rRNA is a target of choice for the development of next-generation drugs.
 
We employ computational homology and de novo modeling to reveal an atomic-level view of Plasmodium, Leishmania and Trypanosoma ribosome and use the information of the rRNA structure and movement to design anti-infective-like compounds that target biologically functional ribosome RNA motifs in a predictable manner. This was performed by screening the pathogen box compounds and microbial natural products databases where we got the best 40 compounds that bind well to the predicted motifs. Further analysis was conducted and mode of action of how the binding happens explained at the conclusion.  Therefore, developing additional measures to control these “neglected tropical diseases” becomes increasingly clear, and we believe that the opportunities for developing drugs, diagnostics, vaccines, and other tools necessary to expand the knowledge base to combat these diseases have never been better.