苯甲酰脲类抗肿瘤β微管蛋白抑制剂药效团模型的构建与应用

采用Catalyst软件包, 选择抗急性淋巴白血病细胞系活性相差较大的2种结构类型的17个苯甲酰脲类β微管蛋白抑制剂化合物作为训练集, 经构象分析, 构建出最佳药效团模型, 该模型含有2个疏水中心 (HP) 和2个氢键受体 (HBA), 具有良好的活性预测能力 (RMS = 0.43, Correl = 0.98, Weight = 2.06, Config = 15.97), 有利于设计和改造具有新型结构的β微管蛋白抑制剂。     

聚腺苷二磷酸核糖聚合酶-1抑制剂药效团模型的建立

建立聚腺苷二磷酸核糖聚合酶-1［poly(ADP-ribose)polymerase-1，PARP-1］抑制剂的药效团模型，探讨其与PARP-1的作用机制。利用Catalyst软件系统，选择具有较高体外抑制活性的8种结构类型的38个化合物作为训练集，经构象分析，分子叠合等过程构建出药效团模型。结合PARP-1的作用机制等因素，得到一个含有两个氢键接受体和两个芳香疏水性基团的PARP-1抑制剂药效团模型。本文建立的药效团模型的可靠性较高(RMS=0.46，Correl=0.91，Weight=2.06，Config=15.97)，不但给出了作用位点的相关信息，而且具有良好的活性预测能力，有助于新型结构的PARP-1抑制剂的设计。     

eEF2K蛋白同源模建及其抑制剂小分子的虚拟筛选研究

目的:筛选潜在的真核生物延伸因子2激酶(eEF2K)抑制剂小分子,为eEF2K抑制剂的设计和研发提供参考。方法:采用同源模建技术构建eEF2K蛋白晶体结构模型,并进行Loop优化和分子动力学优化,借助SAVES在线服务器从Verify_3D、EERAT和拉氏图等3个方面对上述模型进行评估。收集55个eEF2K抑制剂小分子,使用InsightⅡ软件以其中的28个(编号为奇数,设为训练集)为基础构建具有活性预测能力的Hypogen药效团模型,以另外27个(编号为偶数,设为测试集)进行验证,通过拟合活性[即半数抑制浓度的负对数(p IC50)]预测值与真实值并借助Ligand profiler热图筛选最优药效团模型。结合上述药效团模型和Lipinski五规则、分子对接方法进行eEF2K抑制剂小分子的虚拟筛选。结果与结论:所建eEF2K蛋白晶体结构模型的整体质量因素得分为93.697,其中83.33%的氨基酸Verify_3D得分≥0.2,且位于不允许区的氨基酸占氨基酸总数的1.7%,其氨基酸构象及骨架结构合理,模型可靠性高。共构建了9个具有活性预测功能的Hypogen药效团模型(02～10号),其中03号药效团模型包含2个氢键受体和2个共轭芳香环,可更好地区分活性及非活性分子,其pIC_(50)预测值与真实值拟合最好(相关系数为0.665 3),具有较好的预测能力和较高的可靠性。通过虚拟筛选最终获得9个潜在的eEF2K抑制剂小分子(pIC_(50)预测值为1.074～1.185,分子与蛋白相互作用的Dcoking-score得分为-9.730～-7.467),其中Pro268、Asp267、Gln171、Phe121、Glu212可能是e EF2K抑制剂与靶点蛋白相互作用的关键氨基酸,作用方式包括氢键、盐桥、疏水等。上述分子有望成为e EF2K抑制剂研发的先导化合物。     

采用药效团模型和分子对接方法筛选新型的组蛋白甲基转移酶G9a抑制剂

目的利用药效团模型和分子对接方法对商业化合物库ChemDiv中的G9afocused-libraries进行筛选,希望发现新骨架结构的G9a抑制剂。方法首先,使用Discovery studio 3.1软件分别构建基于配体的药效团模型和基于配体-受体复合物的药效团模型,并根据构建的2个模型再重新定义2个新的药效团模型。然后,构建测试集并测试药效团模型的预测能力。最后,选取最优药效团模型对G9afocused-libraries进行筛选,对筛选出的化合物使用CDOCKER分子对接进行分析与评价。结果测试结果显示,所构建的药效团模型具有一定的预测能力,通过该药效团筛选得到了2个结构新颖的潜在的G9a抑制剂。结论所构建的药效团模型具有一定的可靠性,虚拟筛选发现的G9a抑制剂还需进一步的实验证明。     

(1,3)-β-D-葡聚糖合成酶小分子抑制剂药效团模型的构建

目的 开展基于配体的计算机辅助药物设计,构建（1,3）-β-D-葡聚糖合成酶[（1,3）-β-D-Glucan Synthase,GS]小分子抑制剂的药效团模型。方法 选取结构多样、抑酶活性较好的6个小分子构成训练集,利用Catalyst的药效团生成模块中的HipHop算法构建药效团模型,用构建的Decoyset 3D数据库对药效团模型进行评估。结果 药效团模型（pharmacophore）02具有较好的富集率因子以及敏感性、特异性参数。用Decoyset 3D数据库对药效团模型进行验证,该模型具有较好的区分能力。结论 本课题开展基于活性配体的GS小分子抑制剂药效团构建,对新型小分子GS抑制剂的设计和发现具有一定的指导意义。     

基于Hypogen药效团模型发现潜在的PTP1B抑制剂

目的 采用计算机辅助药物设计的方法发现潜在的PTP1B抑制剂。方法 应用3D-QSAR药效团模型中的Hypogen模块构建药效团模型，成本分析、测试集预测和Fisher检验3种方法来验证该模型可用于预测化合物的生物活性的能力。运用该药效团模型对ZINC数据库进行虚拟筛选，得到Fit value值较高的先导化合物ZINC35671983。根据药效团的特征对ZINC35671983进行结构改造得到相应化合物。将化合物用ADMET进行成药预测。结果 ZINC35671983进行结构改造筛选获得92个化合物，筛出对接得分高于ZINC3567198的8个化合物。结论 发现8个潜在的PTP1B抑制剂，这有助于发现新的PTP1B先导化合物。     

L-型钙离子通道抑制剂药效团模型的构建

目的构建L-型钙离子通道抑制剂的药效团模型,为从中药化学成分中发现具有钙离子通道抑制作用的成分提供了新的方法,同时为先导物改造成为活性较好的钙离子通道抑制剂提供思路。方法以来源于NCBI数据库中对新西兰兔心脏L-型钙离子通道具有抑制作用的12个化合物为研究对象,利用HipHop定性药效团模型构建方法,建立L-型钙离子通道拮抗剂的药效团模型,利用数据库搜索方法对药效团模型进行优劣评价。结果获得最优药效团模型具有以下几个特征:2个氢键受体和4个疏水基团,其综合评价指数CAI为2.78。结论构建的定性药效团具有一定的可靠性,可用于开展活性化合物筛选和指导先导化合物的结构改造,有助于指导发现中药中的L-型钙离子通道阻滞剂。     

芪苈强心胶囊中强心有效成分及其作用机理的计算机模拟

目的:通过计算机模拟技术研究芪苈强心胶囊中已知结构化合物的分子特征,分析与强心西药分子结构、理化性质相似的中药成分,并寻找比对中西药分子的作用靶点,以期为新药研发或作用机制研究提供思路。方法:通过中西药的分子集构建,进行中西药分子的理化性质分析和结构比对,同时通过反向药效团搜索进行中西药分子的作用靶点结合的探讨。结果:我们利用软件构建了45个中药成分和3个强心类西药成分的平面结构和三维结构,通过分子结构相似度的比较和反向药效团搜索,发现这45个中药分子整体与洋地黄毒苷的相似度最高,同时中药分子中黄芪苷和人参皂苷与各西药分子的结构相似度最高;理化性质对比分析显示,3个强心西药的相对分子质量并不是最大的,然而其表面极性却最大;通过反向药效团搜索发现,这48个小分子中有10个小分子与66个蛋白药效团模型发生了较好的结合,其中西药地高辛只与一个药效团发生接合,而中药有6个成分都与多个药效团发生结合,其中以丹酚酸A结合的药效团最多。结论:与西药仅结合单一蛋白药效团不同,中药分子更易与多个蛋白药效团发生结合,由此推测其作用靶点和作用途径可能更为多样化。     

甲状旁腺素受体激动剂3D药效团模型的构建与应用

甲状旁腺素能增加人体骨密度和骨强度,是治疗骨质疏松症最有效的多肽类药物之一,但至今缺乏具有相应功能的小分子药物。根据计算机辅助药物设计原理,采用Discovery Studio 2.5软件包,以14个甲状旁腺素(PTH)受体激动剂及其突变类似物为训练集,利用活性构象限制的方法,采用HypoGen算法构建出具有活性预测功能的3D药效团模型。其中最好的药效团模型含有1个阳离子基团(PI),3个疏水中心(H)和1个氢键供体(HBD)。同时应用该模型成功预测出16个测试集分子的活性,经交叉验证表明该模型达到95%的置信水平,具有良好的活性预测能力。该药效团可以用于后续抗骨质疏松症小分子药物的筛选,指导相应的药物优化,同时所采用的限制构象的药效团生产方法为基于多肽的药物设计提供了一个新的思路。     

整合素αvβ3受体拮抗剂药效团模型的研究

为构建可靠的整合素α_vβ₃受体选择性拮抗剂的药效团模型并根据模型设计小分子活性化合物,选择对α_vβ₃受体具有较高抑制活性（IC₅₀ < 110 nmol·L^-1）的4个类型（分别以酰胺、哌嗪、哌啶、γ-戊内酰胺为中间连接基）的30个化合物为训练集,利用Catalyst软件构建整合素α_vβ₃受体选择性拮抗剂药效团模型,并在数据库中寻找具有活性的母体结构,对母体结构进行修饰和改造及类药性分析得到先导化合物。得到的药效团模型相关系数好、预测能力高,可较准确的预测相关化合物的活性。优化模型含1个芳环中心（RA）、1个可阴离子化部位（NI）和2个疏水作用基（HP）,其相关系数与权重值分别为：RMS = 0.73, Correl = 0.90, Weight = 1.17, Config = 14.00。所设计的目标化合物预测活性强且结构简单,易于合成,噻唑类为未见报道的一类母体结构化合物。
     

Tubulin inhibitors： pharmacophore modeling,virtua screening and molecular docking

Aim： To construct a quantitative pharmacophore model of tubulin inhibitors and to discovery new leads with potent antitumor activities. Methods： Ligand-based pharmacophore modeling was used to identify the chemical features responsible for inhibiting tubulin polymerization. A set of 26 training compounds was used to generate hypothetical pharmacophores using the HypoGen algorithm. The structures were further validated using the test set, Fischer randomization method, leave-one-out method and a decoy set, and the best model was chosen to screen the Specs database. Hit compounds were subjected to molecular docking study using a Molecular Operating Environment （MOE） software and to biological evaluation in vitro. Results： Hypol was demonstrated to be the best pharmacophore model that exhibited the highest correlation coefficient （0.9582）, largest cost difference （70.905） and lowest RMSD value （0.6977）. Hypol consisted of one hydrogen-bond acceptor, a hydrogen-bond donor, a hydrophobic feature, a ring aromatic feature and three excluded volumes. Hypol was validated with four different methods and had a goodness-of-hit score of 0.81. When Hypol was used in virtual screening of the Specs database, 952 drug-like compounds were revealed. After docking into the colchicine-binding site of tubulin, 5 drug-like compounds with the required interaction with the critical amino acid residues and the binding free energies 〈-4 kcal/mol were selected as representative leads. Compounds 1 and 3 exhibited inhibitory activity against MCF-7 human breast cancer cells in vitro. Conclusion： Hypol is a quantitative pharmacophore model for tubulin inhibitors, which not only provides a better understanding of their interaction with tubulin, but also assists in discovering new potential leads with antitumor activities.     

Qualitative study of the interaction mechanism of estrogenic drugs with tubulin

Synthetic estrogenic drugs (E-diethylstilbestrol, erythro-hexestrol and E,E-dienestrol) inhibit tubulin assembly and erythro-hexestrol and E,E-dienestrol lead to the formation of twisted ribbon structures. For the inhibitory effect on tubulin assembly, estrogenic drugs seem to interact directly with tubulin 6S on site(s) analogous to the colchicine-site, but independent of the GTP- and vinblastine-sites. This binding does not involve tubulin tryptophanyl residues or sulfhydryl groups. The influence of temperature, calcium and magnesium on the formation of twisted ribbon structures induced by the binding of estrogenic drugs to microtubular protein and tubulin has also been studied. This formation is strongly magnesium-dependent whereas preformed twisted ribbon structures are calcium- and chilling-insensitive.     

作用于秋水仙碱位点的微管蛋白抑制剂的研究进展

微管是细胞骨架的主要组成部分,在维持细胞形态、细胞分裂、信号转导等过程中起着重要作用,因此,微管蛋白是一个非常有前景的新型化疗药物的靶标。秋水仙素结合位点抑制剂(CBSIs)通过抑制微管蛋白聚合和抑制微管形成发挥生物效应。近年来,人们对作用于此靶点的抑制剂开展了一系列的研究,并且取得了一定的进展,本文总结了多种不同结构类型的作用于秋水仙碱位点的抑制剂及其研究概况。     

Three-dimensional quantitative structure-activity relationship analysis of human CYP51 inhibitors.

CYP51 fulfills an essential requirement for all cells, by catalyzing three sequential mono-oxidations within the cholesterol biosynthesis cascade. Inhibition of fungal CYP51 is used as a therapy for treating fungal infections, whereas inhibition of human CYP51 has been considered as a pharmacological approach to treat dyslipidemia and some forms of cancer. To predict the interaction of inhibitors with the active site of human CYP51, a three-dimensional quantitative structure-activity relationship model was constructed. This pharmacophore model of the common structural features of CYP51 inhibitors was built using the program Catalyst from multiple inhibitors (n = 26) of recombinant human CYP51-mediated lanosterol 14alpha-demethylation. The pharmacophore, which consisted of one hydrophobe, one hydrogen bond acceptor, and two ring aromatic features, demonstrated a high correlation between observed and predicted IC(50) values (r = 0.92). Validation of this pharmacophore was performed by predicting the IC(50) of a test set of commercially available (n = 19) and CP-320626-related (n = 48) CYP51 inhibitors. Using predictions below 10 microM as a cutoff indicative of active inhibitors, 16 of 19 commercially available inhibitors (84%) and 38 of 48 CP-320626-related inhibitors (79.2%) were predicted correctly. To better understand how inhibitors fit into the enzyme, potent CYP51 inhibitors were used to build a Cerius(2) receptor surface model representing the volume of the active site. This study has demonstrated the potential for ligand-based computational pharmacophore modeling of human CYP51 and enables a high-throughput screening system for drug discovery and data base mining.     

Investigation of potential glycogen synthase kinase 3 inhibitors using pharmacophore mapping and virtual screening

Glycogen synthase kinase-3 is a serine/threonine kinase that has attracted significant drug discovery attention in recent years. To investigate the identification of new potential glycogen synthase kinase-3 inhibitors, a pharmacophore mapping study was carried out using a set of 21 structurally diverse glycogen synthase kinase-3 inhibitors. A hypothesis containing four features: two hydrophobic, one hydrogen bond donor and another hydrogen bond acceptor was found to be the best from the 10 common feature hypotheses produced by HipHop module of Catalyst. The best hypothesis has a high cost of 156.592 and higher best fit values were obtained for the 21 inhibitors using this best hypothesis than the other HipHop hypotheses. The best hypothesis was then used to screen electronically the NCI2000 database. The hits obtained were docked into glycogen synthase kinase-3beta active site. A total of five novel potential leads were proposed after: (i) visual examination of how well they dock into the glycogen synthase kinase-3beta-binding site, (ii) comparative analysis of their FlexX, G-Score, PMF-Score, ChemScore and D-Scores values, (iii) comparison of their best fit value with the known inhibitors and (iv) examination of the how the hits retain interactions with the important amino acid residues of glycogen synthase kinase-3beta-binding site.     

Binding and interaction of dinitroanilines with apicomplexan and kinetoplastid alpha-tubulin

Despite years of use as commercial herbicides, it is still unclear how dinitroanilines interact with tubulin, how they cause microtubule disassembly, and why they are selectively active against plant and protozoan tubulin. In this work, through a series of computational studies, a common binding site of oryzalin, trifluralin, and GB-II-5 on apicomplexan and kinetoplastid alpha-tubulin is proposed. Furthermore, to investigate how dinitroanilines affect tubulin dynamics, molecular dynamics simulations of Leishmania alpha-tubulin with and without a bound dinitroaniline are performed. The results obtained provide insight into the molecular mechanism by which these compounds interact with tubulin and function to prevent microtubule assembly. Finally, to aid in the design of effective parasitic microtubule inhibitors, several novel dinitroaniline analogues are evaluated. The location of the binding site and the relative binding affinities of the dinitroanilines all agree well with experimental data.     

Pharmacophore modeling for protein tyrosine phosphatase 1B inhibitors

A three dimensional chemical feature based pharmacophore model was developed for the inhibitors of protein tyrosine phosphatase 1B (PTP1B) using the CATALYST software, which would provide useful knowledge for performing virtual screening to identify new inhibitors targeted toward type II diabetes and obesity. A dataset of 27 inhibitors, with diverse structural properties, and activities ranging from 0.026 to 600 microM, was selected as a training set. Hypol, the most reliable quantitative four featured pharmacophore hypothesis, was generated from a training set composed of compounds with two H-bond acceptors, one hydrophobic aromatic and one ring aromatic features. It has a correlation coefficient, RMSD and cost difference (null cost-total cost) of 0.946, 0.840 and 65.731, respectively. The best hypothesis (Hypol) was validated using four different methods. Firstly, a cross validation was performed by randomizing the data using the Cat-Scramble technique. The results confirmed that the pharmacophore models generated from the training set were valid. Secondly, a test set of 281 molecules was scored, with a correlation of 0.882 obtained between the experimental and predicted activities. Hypol performed well in correctly discriminating the active and inactive molecules. Thirdly, the model was investigated by mapping on two PTP1B inhibitors identified by different pharmaceutical companies. The Hypol model correctly predicted these compounds as being highly active. Finally, docking simulations were performed on few compounds to substantiate the role of the pharmacophore features at the binding site of the protein by analyzing their binding conformations. These multiple validation approaches provided confidence in the utility of this pharmacophore model as a 3D query for virtual screening to retrieve new chemical entities showing potential as potent PTP1B inhibitors.     

作用于秋水仙碱结合位点的微管蛋白抑制剂研究进展

微管是细胞骨架的主要组成部分并在细胞分裂过程中起着重要作用,因此微管蛋白成为抗癌药物的重要靶点之一,作用于微管系统的微管蛋白抑制剂现已成为一类有效的抗肿瘤药物。由于微管蛋白上秋水仙碱位点的空腔体积较小且相应抑制剂的结构较为简单,因而近年来关于其抑制剂的研究也备受关注。本文总结了多种不同结构类型的作用于秋水仙碱位点的抑制剂及其近年来的一些研究进展。     

Pharmacophore mapping of a series of 2,4-diamino-5-deazapteridine inhibitors of Mycobacterium avium complex dihydrofolate reductase.

Pharmacophore hypotheses were developed for a series of 2,4-diamino-5-deazapteridine inhibitors of Mycobacterium avium complex (MAC) and human dihydrofolate reductase (hDHFR). Training sets consisting of 20 inhibitors were selected in each case on the basis of the information content of the structures and activity data as required by the HypoGen program in the Catalyst software. In the case of MAC DHFR inhibitors, the best pharmacophore in terms of statistics and predictive value consisted of four features: two hydrogen bond acceptors (HA), one hydrophobic (HY) feature, and one ring aromatic (RA) feature. The selected pharmacophore hypothesis yielded an rms deviation of 0.730 and a correlation coefficient of 0.967 with a cost difference (null cost minus total cost) of approximately 52. The pharmacophore was validated on a large set of test inhibitors. For the test series, a classification scheme was used to distinguish highly active from moderately active and inactive compounds on the basis of activity ranges. This classification scheme is more practical than actual estimated values because these values have no meaning for compounds yet to be tested except that they indicate whether the compounds will be active or inactive in a biological assay. For the training set, the success rate for predicting active and inactive compounds was 100%. For the test set, the success rate in predicting active compounds was greater than 92% while about 7% of the inactive compounds were predicted to be active. This successful prediction was further validated on three structurally diverse compounds active against MAC DHFR. Two compounds mapped well onto three of the four features of the pharmacophore. The third compound was mapped to all four features of the pharmacophore. This validation study provided confidence for the usefulness of the selected pharmacophore model to identify compounds with diverse structures from a database search. Comparison of pharmacophores for inhibitors of human and MAC DHFR is expected to reveal fundamental differences between these two pharmacophores that may be effectively exploited to identify and design compounds with high selectivity for MAC DHFR.     

A common pharmacophore for a diverse set of colchicine site inhibitors using a structure-based approach

Modulating the structure and function of tubulin and microtubules is an important route to anticancer therapeutics, and therefore, small molecules that bind to tubulin and cause mitotic arrest are of immense interest. A large number of synthetic and natural compounds with diverse structures have been shown to bind at the colchicine site, one of the major binding sites on tubulin, and inhibit tubulin assembly. Using the recently determined X-ray structure of the tubulin:colchicinoid complex as the template, we employed docking studies to determine the binding modes of a set of structurally diverse colchicine site inhibitors. These binding models were subsequently used to construct a comprehensive, structure-based pharmacophore that in combination with molecular dynamics simulations confirms and extends our understanding of binding interactions at the colchicine site.