探讨定量构效关系模型在药物及其杂质毒性预测方面的应用

随着定量构效关系（QSAR）模型从二维至多维的不断发展,它被越来越广泛地应用于各个领域,同时也为药品的监管提供了新的参考方案。QSAR模型对于杂质的毒性预测可应用于药品的研发和质量控制过程,有利于控制药品的安全风险,缩减企业的研发成本。QSAR模型的应用程序也在不断优化,以确保QSAR模型可以不断地适用于新药及未知杂质的毒性研究。本文从QSAR模型的建模基础及发展历程出发,对近年来该模型在药物及其杂质毒性预测方面的应用研究报道进行了归纳总结。     

Quantitative structure activity relationships and mixture toxicity studies of alcohols and chlorohydrocarbons: Effects on growth of Daphnia magna

Effects on growth of Daphnia magna were studied for 10 non-reactive organic chemicals such as alcohols and chlorobenzenes. The ‘no observed effect concentration’ (NOEC) was very well correlated with the hydrophobicity (P_oct) of the tested compounds which appeared in a quantitative structure-activity relationship (QSAR) study. With this QSAR the NOEC for 15 other compounds was predicted. The joint toxicity of mixtures of 10 and 25 compounds was also tested. The NOEC of these mixtures was predictable on the basis of concentration-additivity.     

定量结构-活性关系在混合体系毒性预测中的发展(英文)

目的:预测麻醉型化合物卤代苯混合体系的毒性。方法:采用发光细菌对卤代苯的单一体系和混合体系进行毒性试验;利用特定的公式计算了混合物的分配系数;建立了混合体系的定量构效关系。结果:(1)建立了单一化合物的正辛醇/水分配系数与毒性的关系。(2)建立了二元混合体系的分配系数与毒性之间的定量结构模型。(3)用二元混合体系的QSAR模型预测了其它不同组份和不同毒性比例的混合体系毒性。结论:QSAR能很好地预测麻醉型化合物卤代苯混合体系的毒性,并且有助于该类化合物的混合体系毒性作用的评价。     

A comparative molecular field analysis of cytotoxic beta-carboline analogs

INTRODUCTION Beta-carbolines have been reported to possess sig-nificant antitumor activities[1,4,6,9,17], in addition thesecompounds are widely studied for their bioactivity inantibacterial, anti-radialization, anti-trypanosome, andneural activities as well as mutagenic and co-mutagenicproperties. Also they are potent and specific inhibitorsof cyclin-dependent kinases[2,3,5,8-10,12-17]. The extractscontaining beta-carbolines from the plant Peganumharmala have been widely used in Nor…     

基于构效关系的非肽类血管紧张素Ⅱ受体阻滞剂分子设计

目的：研究非肽类血管紧张素Ⅱ（AngⅡ）受体阻滞剂定量构效关系及分子设计。方法：应用半经验量子化学方法和误差反向传播人工神经网络方法建立AngⅡ受体阻滞剂的定量构效关系（QSAR）模型，用该模型预测新设计的化合物的药效参数。结果：系统地计算了70个非肽类血管紧张素Ⅱ受体阻滞剂的18个量化参数，从中筛选出5个建立QSAR模型。随机挑选6个化合物作为验证集，剩余64个化合物作为学习集，验证结果表明：所建立的QSAR模型具有较高的精度。设计并预测了30个新化合物的药效参数，其中5个化合物的预测药效较好。结论：成功建立非肽类AngⅡ受体阻滞剂的QSAR模型，该模型为此类药物的结构改造和新药设计提供了参考意见和有效途径。     

定量构效关系方程对靶向蛋白激酶C-α mRNA的反义药物的活性预测

以往研究对34个针对蛋白激酶C-α mRNA二级结构设计的反义药物（AS-ODNs）进行了定量构效关系（QSAR）分析并得到QSAR方程. 本研究再次设计10个AS-ODNs验证QSAR方程对药物活性预测的可靠性．结果显示其中4个AS-ODNs IC₅₀值明显低于阳性对照ISIS3521（P<0.05）. 8个AS-ODNs与ISIS3521的实测IC₅₀与QSAR方程预测相符,实测与预测IC₅₀之间相关系数为0.76(P<0.05）. 两个AS-ODNs,AP1261(20)和AP0186(20)的实测IC₅₀与预测不符. 结果提 示QSAR方程一定程度上反映了AS ODNs活性与靶结构的关系,对预测反义药物生物活性有益. 但QSAR方程难以解释的其他因素需进一步研究以优化反义药物设计.     

Novel chemical scaffolds of the tumor marker AKR1B10 inhibitors discovered by 3D QSAR pharmacophore modeling

Aim:

Recent evidence suggests that aldo-keto reductase family 1 B10 (AKR1B10) may be a potential diagnostic or prognostic marker of human tumors, and that AKR1B10 inhibitors offer a promising choice for treatment of many types of human cancers. The aim of this study was to identify novel chemical scaffolds of AKR1B10 inhibitors using in silico approaches.

Methods:

The 3D QSAR pharmacophore models were generated using HypoGen. A validated pharmacophore model was selected for virtual screening of 4 chemical databases. The best mapped compounds were assessed for their drug-like properties. The binding orientations of the resulting compounds were predicted by molecular docking. Density functional theory calculations were carried out using B3LYP. The stability of the protein-ligand complexes and the final binding modes of the hit compounds were analyzed using 10 ns molecular dynamics (MD) simulations.

Results:

The best pharmacophore model (Hypo 1) showed the highest correlation coefficient (0.979), lowest total cost (102.89) and least RMSD value (0.59). Hypo 1 consisted of one hydrogen-bond acceptor, one hydrogen-bond donor, one ring aromatic and one hydrophobic feature. This model was validated by Fischer''s randomization and 40 test set compounds. Virtual screening of chemical databases and the docking studies resulted in 30 representative compounds. Frontier orbital analysis confirmed that only 3 compounds had sufficiently low energy band gaps. MD simulations revealed the binding modes of the 3 hit compounds: all of them showed a large number of hydrogen bonds and hydrophobic interactions with the active site and specificity pocket residues of AKR1B10.

Conclusion:

Three compounds with new structural scaffolds have been identified, which have stronger binding affinities for AKR1B10 than known inhibitors.     

Ligand‐based 3D‐QSAR Studies of Physostigmine Analogues as Acetylcholinesterase Inhibitors

Natural alkaloid Physostigmine is one of the most potent pseudo‐irreversible inhibitor of Acetylcholinesterase. It was found to accelerate long‐term memory process, but due to its short half life and variable bioavailability, has inconsistent clinical efficacy. 3D‐QSAR studies based on the comparative molecular field analysis and comparative molecular similarity indices analysis were applied to a set of 40 Physostigmine derivatives which are divided into two classes: A and B. The study was conducted to obtain a highly reliable and extensive dynamic QSAR model based on alignment procedure with co‐crystallized Ganstigmine as template. The strategy yielded significant 3D‐QSAR models with the cross‐validated q² values 0.762 and 0.754 for comparative molecular field analysis and comparative molecular similarity indices analysis, respectively. Resulted models were validated by external set of eight compounds yielding high correlation coefficient r² values of 0.730 and 0.720 for comparative molecular field analysis and comparative molecular similarity indices analysis, respectively. Furthermore, the analysis of comparative molecular field analysis and comparative molecular similarity indices analysis contour maps within the active site of AChE were conducted in order to understand the interactions between the receptor and the Physostigmine derivatives. This study will facilitate the rational design of more potent Physostigmine compounds which might have better activity and reduce toxicity for the treatment of Alzheimer disease.     

Structural Findings of 2-Phenylindole-3-Carbaldehyde Derivatives for Antimitotic Activity by FA-sMLR QSAR Analysis

Antimitotic agents prevent the mitosis process of cell cycle and are generally used for the treatment of cancer with good clinical success. QSAR analysis was performed on 33 reported 2-phenylindole-3-carbaldehyde derivatives to find out the structural requirements of these compounds for higher antimitotic activity. The dataset was divided into test set and training set by k-MCA. Factor analysis-stepwise multiple linear regression (FA-sMLR) method was used to develop statistically significant QSAR equations. QSAR analysis showed importance of topological indices like RTSA indices, structural information content indices, Balaban-type index from van der Waals weighted distance matrix Jhetv, rotatable bond fraction RBF, and Lovasz–Pelikan index LP1 on biological activity. The study also shows significance of electrostatic potential charges of different atoms as well as principal moment of inertia along Y axis and number of nitrogen atoms toward antimitotic activity of these compounds.     

应用神经网络方法研究3-甲基芬太尼类似物的定量构-效关系(英文)

目的:应用神经网络这种新型的信息处理系统研究定量构-效关系.方法:应用自编的逆传播神经网络算法,结合偏最小二乘法,研究了25个3-甲基芬太尼类似物的量子化学指数和镇痛活性之间的定量关系.结果:得到了良好的QSAR模型,3-甲基芬太尼类似物的量子化学指数即N_1和O_(16)上净电荷、C_(10)-C_9-N_8-C_4二面角、C_7-PhA中心的距离与镇痛活性之间具有很好的相关性,并根据计算结果,提出了芬太尼类似物与阿片受体的结合模式.结论:神经网络方法研究结果优于单纯偏最小二乘法的结果,且能对化合物活性进行准确的预测.     

靶向HER-2 mRNA模拟二级结构中局部保守序列的反义药物优化设计及QSAR分析(英文)

目的:验证mRNA二级结构保守性在反义药物设计中的作用,获得靶向HER-2 mRNA的优于已报道阳性药物的序列。方法:RNAstructure用于模拟HER-2 mRNA二级结构,设计21个反义硫代寡脱氧核苷酸(S-ODN)。用SK-BR-3乳腺癌细胞评价S-ODN体外活性,SPSS进行定量构效关系(QSAR)分析,RT-PCR检测S-ODN对HER-2表达的影响。结果:11个靶向模拟二级结构完全保守局域(LM)的S-ODN中,有9个获得低于或相似于HA4的IC_(50)值,且其IC_(50)值显著低于靶向部分保守与非保守LM的AS-ODN(P<0.05),靶二级结构单元膨胀环的碱基数,靶结构自由能在QSAR方程中有统计意义,多元回归R=0.967,P=0.005)。结论:针对模拟靶mRNA二级结构中高度保守LM部位进行反义药物设计可提高阳性率,并获得优于阳性对照的S-ODN。     

Combined 3D‐QSAR Modeling and Molecular Docking Study on Quinoline Derivatives as Inhibitors of P‐selectin

P‐selectin is a promising target for developing novel atherosclerosis drugs. To understand the structure–activity correlation of quinolines‐based P‐selectin inhibitors, we have carried out a combined molecular docking and three‐dimensional quantitative structure–activity relationship (3D‐QSAR) modeling study. The study has resulted in two types of satisfactory 3D‐QSAR models, including the CoMFA model (r², 0.863; q², 0.589) and CoMSIA model (r², 0.866; q², 0.636), to predict the biological activity of new compounds. The detailed microscopic structures of P‐selectin binding with inhibitors have been studied by molecular docking. We have also developed docking based 3D‐QSAR models (CoMFA with r², 0.934; q², 0.591; CoMSIA with r², 0.896; q², 0.573). The contour maps obtained from the 3D‐QSAR models in combination with the docked binding structures help to better interpret the structure–activity relationship. All of the structural insights obtained from both the 3D‐QSAR contour maps and molecular docking are consistent with the available experimental activity data. The satisfactory results strongly suggest that the developed 3D‐QSAR models and the obtained P‐selectin‐inhibitor binding structures are reasonable for the prediction of the activity of new inhibitors and in future drug design.     

基于分子对接、定量构效关系和分子动力学研究筛选小分子SIRT1抑制剂

为了寻找和发现靶向SIRT1的治疗AML的新型先导化合物,本研究利用分子对接与MM-GBSA结合自由能计算进行虚拟筛选,从231511个天然小分子类药分子库中筛选出8个潜在的SIRT1抑制剂,通过对已有的SIRT1抑制剂分子作为训练集和测试集进行QSAR建模,对筛选出的潜在SIRT1抑制剂分子进行活性预测,随后进行分子动力学模拟验证这些潜在抑制剂与SIRT1蛋白的结合模式与稳定性,最后通过OCI-AML2、OCI-AML3和MV4-11三种AML细胞增殖实验和SIRT1酶活性验证了这些分子的生物活性,发现其中5个分子对3种AML细胞具有不同程度的抑制作用,其中活性最强的化合物ZINC000001774455对AML细胞OCI-AML2的IC50达到2.29±0.09μmol·L^-1μmol·L^-1浓度下对SIRT1抑制率为65.33%,可作为SIRT1抑制剂先导化合物进行结构修饰,为开发新的AML治疗药物奠定了前期基础。