Intergrating Bioinformatics Mechanism - Based Screening Into Kinetoplastids Antiprotozoan rRna Targets Compound Discovery Paradigm

Abstract

Kinetoplastids are human pathogens with devastating economic and health effects, which include Leishmania and Trypanosoma species from flagellated protozoans. 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. In addition, using several novel and transformative technologies we have developed, we demonstrate that the modular nature of rRNA facilitates the development of in vitro assays, structure determination, molecular-modeling, and compound screening studies for drug design. We employ computational homology and de novo modeling to reveal an atomic-level view of 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 and the natural product 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.