van Westen Gerard J P, Bender Andreas, Overington John P
European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD United Kingdom.
Unilever Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW United Kingdom.
J Chem Biol. 2014 May 15;7(4):119-23. doi: 10.1007/s12154-014-0112-2. eCollection 2014 Oct.
Resistance to pesticides is an increasing problem in agriculture. Despite practices such as phased use and cycling of 'orthogonally resistant' agents, resistance remains a major risk to national and global food security. To combat this problem, there is a need for both new approaches for pesticide design, as well as for novel chemical entities themselves. As summarized in this opinion article, a technique termed 'proteochemometric modelling' (PCM), from the field of chemoinformatics, could aid in the quantification and prediction of resistance that acts via point mutations in the target proteins of an agent. The technique combines information from both the chemical and biological domain to generate bioactivity models across large numbers of ligands as well as protein targets. PCM has previously been validated in prospective, experimental work in the medicinal chemistry area, and it draws on the growing amount of bioactivity information available in the public domain. Here, two potential applications of proteochemometric modelling to agrochemical data are described, based on previously published examples from the medicinal chemistry literature.
对农药产生抗性在农业领域是一个日益严重的问题。尽管采取了诸如分阶段使用和轮换“正交抗性”药剂等措施，但抗性仍然是国家和全球粮食安全的重大风险。为了解决这一问题，既需要新的农药设计方法，也需要新型化学实体本身。正如这篇观点文章所总结的，化学信息学领域的一种称为“蛋白质化学计量学建模”（PCM）的技术，有助于量化和预测通过药剂靶蛋白中的点突变起作用的抗性。该技术结合了化学和生物领域的信息，以生成大量配体以及蛋白质靶标的生物活性模型。PCM此前已在药物化学领域的前瞻性实验工作中得到验证，并且它利用了公共领域中越来越多的生物活性信息。在此，基于药物化学文献中先前发表的实例，描述了蛋白质化学计量学建模在农用化学品数据方面的两个潜在应用。
