Avery Mitchell A, Alvim-Gaston Maria, Rodrigues Carlos R, Barreiro Eliezer J, Cohen Fred E, Sabnis Yogesh A, Woolfrey John R
Department of Medicinal Chemistry, School of Pharmacy, Thad Cochran National Center for Natural Products Research, University of Mississippi, University, Mississippi 38677, USA.
J Med Chem. 2002 Jan 17;45(2):292-303. doi: 10.1021/jm0100234.
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.
青蒿素（1）是一种独特的倍半萜过氧化物，是青蒿的一种成分。由于青蒿素在治疗耐多药恶性疟原虫方面的有效性及其对脑型疟疾的快速清除作用，临床上用于治疗严重和复杂疟疾的半合成药物（蒿甲醚、青蒿琥酯）迅速得到开发。然而，最近有报道称，蒿甲醚等双氢青蒿素衍生物在动物中具有致命的神经毒性，这促使人们重新努力开发青蒿素的无毒类似物。为了开发更有效、神经毒性更小的药物用于口服治疗耐多药疟疾，我们利用比较分子场分析（CoMFA）和全息定量构效关系（HQSAR），从一系列211种具有已知体外抗疟活性的青蒿素类似物开始。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，我们还研究了在偏最小二乘法（pls）分析中包含或排除外消旋体的影响。在剔除20种化合物的测试集后，将源自原始211种化合物的数据库分为手性（n = 157）、非手性（n = 34）和混合数据库（n = 191）。从生成稳健的定量构效关系模型的潜力方面对HQSAR和CoMFA模型进行了比较。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）。开发的CoMFA和HQSAR模型具有统计学上优异的性质，对测试集化合物也具有良好的预测能力。当在外消旋体定量构效关系分析中排除外消旋体时，获得了最佳模型。因此，对n = 157的数据库进行CoMFA分析给出了具有出色统计性质的优异预测。HQSAR在统计分析方面表现出色，在预测方面也处理得很好。
