rRNA Platform Technology for Drug Discovery Methods for Identifying Ligands That Target Plasmodium RNA Structural Motifs

Harrison Ndung’u Mwangi, Francis Jackim Mulaa
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Abstract

Determining the structure of the P. falciparum40s leads to better understanding of the structural basis for its protein-synthesizing roles in the cell. This enables researchers in the field of drug development to run in silico ligand screening experiments using the solved P. falciparum 40S structure as a target against a library of potential anti-malarial compounds. Drug leads identified through this method can lead to further biochemical and In vitro binding studies with the ultimate goal of developing new class of anti-malarial drugs. The use of structure prediction and modeling technologies in this study dramatically reduces the time it takes from target identification to drug lead determination. Furthermore, very many compounds that were previously incapable of being experimentally tested can now be tested in silico against the generated structure. Owing to the increasing utility of bioinformatics and three dimensional structural modeling software, one can accurately build physical models solely from sequence data by unwrapping the information therein on probable motif sites capable of being anchored onto available compounds or aptamers.
用于鉴定疟原虫RNA结构基序配体的药物发现方法的rRNA平台技术
确定恶性疟原虫的结构有助于更好地理解其在细胞中蛋白质合成作用的结构基础。这使得药物开发领域的研究人员能够利用已解决的恶性疟原虫40S结构作为靶标,对潜在的抗疟疾化合物库进行硅配体筛选实验。通过这种方法确定的药物先导物可以引导进一步的生化和体外结合研究,最终目标是开发新型抗疟疾药物。在本研究中,结构预测和建模技术的使用大大减少了从目标识别到药物铅测定所需的时间。此外,许多以前无法进行实验测试的化合物现在可以根据生成的结构在硅中进行测试。由于生物信息学和三维结构建模软件的日益普及,人们可以通过打开序列数据中可能的基序位点的信息来准确地构建物理模型,这些基序位点能够锚定在可用的化合物或适体上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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