阿片类药物透过血脑屏障的三维构效研究

目的:建立药物透过血脑屏障的三维构效模型,为药物分子设计提供理论依据。方法与结果:利用比较分子力场分析方法建立了阿片类药物透过血脑屏障的三维定量构效模型,该模型有较高的预测能力,交叉验证系数r²_cv=0.718,相关系数r²=0.978,F₃,7=67.902,标准偏差SE=0.209。结论:根据CoMFA模型系数等势图,解释了该类药物透过血脑屏障的构效关系。     

In vivo,in vitro and in silico methods for small molecule transfer across the BBB

The inability of molecules to permeate the BBB is a significant source of attrition in Central Nervous System (CNS) drug discovery. Given the increasing medical drivers for new and improved CNS drugs, small molecule transfer across the BBB is attracting a heightened awareness within pharmaceutical industry and medical fields. In order to assess the potential for small CNS molecules to permeate the BBB, a variety of methods and models, from in silico to in vivo going through in vitro models are developed as predictive tools in drug discovery. This review gives a comprehensive overview of different approaches currently considered in drug discovery to circumvent the lack of small molecule transfer through the BBB, together with their inherent advantages and disadvantages. Particularly, special attention is drawn to in silico models, with a detailed and contemporary point of view on prediction tools and guidelines for rational design. © 2009 Wiley‐Liss, Inc. and the American Pharmacists Association J Pharm Sci 98:4429–4468, 2009     

A quantitative structure-activity relationship analysis of some 4-aminodiphenyl sulfone antibacterial agents using linear free energy and molecular modeling methods

A set of 36 congeneric 4-aminodiphenyl sulfones with measured inhibition potencies of dihydropteroate synthase were studied by using both linear free energy and molecular modeling methods. The goals of the investigation were to identify the "active" conformation for these compounds as inhibitors and, correspondingly, to contruct a quantitative structure-activity relationship (QSAR). These molecules are quite flexible and possess multiple conformational energy minima. Application of molecular shape analysis (MSA), using all intramolecular energy minima as part of the analysis, was not successful in generating a QSAR. However, the calculated intramolecular conformational entropy of these compounds was found to correlate with inhibition potency leading to a highly significant QSAR. Inhibition potency increases as entropy decreases. A decrease in entropy enhances the population of specific, symmetry-related minimum-energy conformations. In this indirect way, it was possible to postulate an "active" conformation. This investigation illustrates that specific knowledge of the "active" shape of a molecule may not provide the information needed to quantitatively explain the observed structure-activity relationship.     

Toward the quantitative prediction of T-cell epitopes: coMFA and coMSIA studies of peptides with affinity for the class I MHC molecule HLA-A*0201

A set of 102 peptides with affinity for the class I MHC HLA-A0201 molecule was subjected to three-dimensional quantitative structure-affinity relationship (3D QSAR) studies using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). A test set of 50 peptides was used to determine the predictive value of the models. The CoMFA models gave q(2) and r(2)pred below 0.5. The best CoMSIA model has q(2) = 0.542 and r(2)pred = 0.679, and includes hydrophobic, steric, and H-bond donor fields. The hydrophobic interactions play a dominant role in peptide-MHC molecule binding. CoMSIA coefficient contour maps were used to analyze the structural features of the peptides accounting for the affinity in terms of the three positively contributing physicochemical properties: local hydrophobicity, steric bulk and hydrogen-bond-donor ability.     

Structure-activity relationships of the antimalarial agent artemisinin. 6. The development of predictive in vitro potency models using CoMFA and HQSAR methodologies

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.