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Computer-Aided Drug Discovery in Plant Pathology.
The Plant Pathology Journal ( IF 2.3 ) Pub Date : 2017-12-01 , DOI: 10.5423/ppj.rw.04.2017.0084
Gnanendra Shanmugam 1 , Junhyun Jeon 1
Affiliation  

Control of plant diseases is largely dependent on use of agrochemicals. However, there are widening gaps between our knowledge on plant diseases gained from genetic/mechanistic studies and rapid translation of the knowledge into target-oriented development of effective agrochemicals. Here we propose that the time is ripe for computer-aided drug discovery/design (CADD) in molecular plant pathology. CADD has played a pivotal role in development of medically important molecules over the last three decades. Now, explosive increase in information on genome sequences and three dimensional structures of biological molecules, in combination with advances in computational and informational technologies, opens up exciting possibilities for application of CADD in discovery and development of agrochemicals. In this review, we outline two categories of the drug discovery strategies: structure- and ligand-based CADD, and relevant computational approaches that are being employed in modern drug discovery. In order to help readers to dive into CADD, we explain concepts of homology modelling, molecular docking, virtual screening, and de novo ligand design in structure-based CADD, and pharmacophore modelling, ligand-based virtual screening, quantitative structure activity relationship modelling and de novo ligand design for ligand-based CADD. We also provide the important resources available to carry out CADD. Finally, we present a case study showing how CADD approach can be implemented in reality for identification of potent chemical compounds against the important plant pathogens, Pseudomonas syringae and Colletotrichum gloeosporioides.

中文翻译:

植物病理学中的计算机辅助药物发现。

控制植物病害在很大程度上取决于农用化学品的使用。但是,我们从遗传/机理研究中获得的有关植物病害的知识与将知识迅速转化为有效的农用化学品的目标导向型发展之间的差距越来越大。在这里,我们提出分子植物病理学中计算机辅助药物发现/设计(CADD)的时机已经成熟。在过去的三十年中,CADD在医学上重要分子的开发中发挥了关键作用。现在,有关基因组序列和生物分子三维结构信息的爆炸性增长,再加上计算和信息技术的进步,为将CADD应用于农用化学品的发现和开发开辟了令人兴奋的可能性。在这篇评论中 我们概述了药物发现策略的两类:基于结构和配体的CADD,以及在现代药物发现中使用的相关计算方法。为了帮助读者深入了解CADD,我们解释了同源性建模,分子对接,虚拟筛选和基于结构的CADD中的从头配体设计,以及基于配体的CADD的药效团建模,基于配体的虚拟筛选,定量结构活性关系建模和从头配体设计。我们还提供了可用于执行CADD的重要资源。最后,我们提供了一个案例研究,展示了如何在实际中实施CADD方法,以鉴定针对重要植物病原体,丁香假单胞菌Colletotrichum gloeosporioides的有效化合物。
更新日期:2020-08-21
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