Structure-activity relationships of the antimalarial agent artemisinin. 6. The development of predictive in vitro potency models using CoMFA and HQSAR methodologies
Structure-activity relationships of the antimalarial agent artemisinin. 6. The development of predictive in vitro potency models using CoMFA and HQSAR methodologies
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DOI：
10.1021/jm0100234
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发表时间：
2002-01-17
影响因子：
7.3
通讯作者：
Woolfrey, JR
中科院分区：
文献类型：
--
作者：
Avery, MA;Alvim-Gaston, M;Woolfrey, JR
青蒿素（1）是黄花蒿（ArtemisiaannuaL.）中一种独特的过氧化倍半萜。由于青蒿素在治疗抗药性恶性疟原虫方面的有效性及其对脑型疟疾的快速清除，临床上有用的治疗严重和复杂疟疾的半合成药物（蒿甲醚、青蒿琥酯）的开发迅速。然而，最近关于双氢青蒿素衍生物（如蒿甲醚）对动物的致命神经毒性的报道，促使人们重新努力开发青蒿素的无毒类似物。在我们努力开发更有效，更少的神经毒性药物口服治疗耐药疟疾，我们利用比较分子场分析（CoMFA）和全息QSAR（HQSAR），开始与一系列的211青蒿素类似物与已知的体外抗疟活性。CoMFA模型基于两种构象假设：（a）青蒿素的X射线结构代表分子的生物活性形状或（B）血红素对接构象是药物的生物活性形式。此外，我们还考察了在偏最小二乘（pls）分析中包含或排除外消旋体的影响。在排除20种化合物的测试集后，将来自原始211的数据库分为手性（n = 157），非手性（n = 34）和混合数据库（n = 191）。HQSAR和CoMFA模型进行了比较，其潜力，以产生强大的QSAR模型。r（2）和q（2）（交叉验证的r（2））用于评估我们模型的统计质量。还生成了另一个统计参数，即标准误差与活性范围的比值（s/AR）。CoMFA和HQSAR模型具有良好的统计特性，对测试集化合物也具有良好的预测能力。当从QSAR分析中排除外消旋体时，获得最佳模型。因此，CoMFA的n = 157数据库给出了出色的预测与突出的统计特性。HQSAR在统计分析方面做得很出色，而且预测也做得很好。
Artemisinin (1) is a unique sesquiterpene peroxide occurring as a constituent of Artemisia annua L. Because of the effectiveness of Artemisinin in the treatment of drug-resistant Plasmodium falciparum and its rapid clearance of cerebral malaria, development of clinically useful semisynthetic drugs for severe and complicated malaria (artemether, artesunate) was prompt. However, recent reports of fatal neurotoxicity in animals with dihydroartemisinin derivatives such as artemether have spawned a renewed effort to develop nontoxic analogues of artemisinin. In our effort to develop more potent, less neurotoxic agents for the oral treatment of drug-resistant malaria, we utilized comparative molecular field analysis (CoMFA) and hologram QSAR (HQSAR), beginning with a series of 211 artemisinin analogues with known in vitro antimalarial activity. CoMFA models were based on two conformational hypotheses: (a) that the X-ray structure of artemisinin represents the bioactive shape of the molecule or (b) that the hemin-docked conformation is the bioactive form of the drug. In addition, we examined the effect of inclusion or exclusion of racemates in the partial least squares (pls) analysis. Databases derived from the original 211 were split into chiral (n = 157), achiral (n = 34), and mixed databases (n = 191) after leaving out a test set of 20 compounds. HQSAR and CoMFA models were compared in terms of their potential to generate robust QSAR models. The r(2) and q(2) (cross-validated r(2)) were used to assess the statistical quality of our models. Another statistical parameter, the ratio of the standard error to the activity range (s/AR), was also generated. CoMFA and HQSAR models were developed having statistically excellent properties, which also possessed good predictive ability for test set compounds. The best model was obtained when racemates were excluded from QSAR analysis. Thus, CoMFA of the n = 157 database gave excellent predictions with outstanding statistical properties. HQSAR did an outstanding job in statistical analysis and also handled predictions well.