Cortes-Ciriano Isidro, Murrell Daniel S, van Westen Gerard Jp, Bender Andreas, Malliavin Thérèse E
Département de Biologie Structurale et Chimie, Institut Pasteur, Unité de Bioinformatique Structurale; CNRS UMR 3825, 25, rue du Dr Roux, Paris, 75015 France.
Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Cambridge, UK.
J Cheminform. 2015 Jan 16;7:1. doi: 10.1186/s13321-014-0049-z. eCollection 2015.
Cyclooxygenases (COX) are present in the body in two isoforms, namely: COX-1, constitutively expressed, and COX-2, induced in physiopathological conditions such as cancer or chronic inflammation. The inhibition of COX with non-steroideal anti-inflammatory drugs (NSAIDs) is the most widely used treatment for chronic inflammation despite the adverse effects associated to prolonged NSAIDs intake. Although selective COX-2 inhibition has been shown not to palliate all adverse effects (e.g. cardiotoxicity), there are still niche populations which can benefit from selective COX-2 inhibition. Thus, capitalizing on bioactivity data from both isoforms simultaneously would contribute to develop COX inhibitors with better safety profiles. We applied ensemble proteochemometric modeling (PCM) for the prediction of the potency of 3,228 distinct COX inhibitors on 11 mammalian cyclooxygenases. Ensemble PCM models ([Formula: see text], and RMSEtest = 0.71) outperformed models exclusively trained on compound ([Formula: see text], and RMSEtest = 1.09) or protein descriptors ([Formula: see text] and RMSEtest = 1.10) on the test set. Moreover, PCM predicted COX potency for 1,086 selective and non-selective COX inhibitors with [Formula: see text] and RMSEtest = 0.76. These values are in agreement with the maximum and minimum achievable [Formula: see text] and RMSEtest values of approximately 0.68 for both metrics. Confidence intervals for individual predictions were calculated from the standard deviation of the predictions from the individual models composing the ensembles. Finally, two substructure analysis pipelines singled out chemical substructures implicated in both potency and selectivity in agreement with the literature. Graphical AbstractPrediction of uncorrelated bioactivity profiles for mammalian COX inhibitors with Ensemble Proteochemometric Modeling.
环氧化酶(COX)在体内以两种同工型存在,即:COX-1,组成性表达;以及COX-2,在诸如癌症或慢性炎症等生理病理条件下被诱导表达。尽管长期服用非甾体抗炎药(NSAIDs)会产生不良反应,但用NSAIDs抑制COX仍是治疗慢性炎症最广泛使用的方法。尽管选择性COX-2抑制已被证明不能缓解所有不良反应(如心脏毒性),但仍有特定人群可从选择性COX-2抑制中获益。因此,同时利用两种同工型的生物活性数据将有助于开发具有更好安全性的COX抑制剂。我们应用集成蛋白质化学计量学建模(PCM)来预测3228种不同的COX抑制剂对11种哺乳动物环氧化酶的效力。在测试集上,集成PCM模型([公式:见原文],RMSEtest = 0.71)优于仅基于化合物训练的模型([公式:见原文],RMSEtest = 1.09)或仅基于蛋白质描述符训练的模型([公式:见原文],RMSEtest = 1.10)。此外,PCM预测了1086种选择性和非选择性COX抑制剂的COX效力,[公式:见原文],RMSEtest = 0.76。这些值与两种指标的最大和最小可实现[公式:见原文]和RMSEtest值(约为0.68)一致。根据组成集成模型的各个模型预测的标准差计算单个预测的置信区间。最后,两个子结构分析流程确定了与效力和选择性相关的化学子结构,这与文献一致。图形摘要:用集成蛋白质化学计量学建模预测哺乳动物COX抑制剂的不相关生物活性谱。