基于药效团模型的DNA错配修复化合物筛选

目的:找到一种具有DNA错配修复功能的化合物.方法:通过构建大肠埃希菌MutS蛋白受体与内源性配体之间的药效团模型,构建并筛选化合物数据库,使用分子对接和分子动力学模拟的方法,确认具有潜在DNA错配修复功能的先导化合物,并对其与受体蛋白之间的结合作用模式进行分析.结果:筛选得到了化合物52,分子动力学模拟显示该化合物与...     

现代生物学技术在中药药效研究中的应用

现代生物技术的迅猛发展为中药和中药复方药效学的研究搭建了新的平台,本文从动物整体、细胞和分子水平的药物筛选模式和技术,综述了现代生物技术在单味及复方中药的活性成分研究中的应用和展望。     

药效团模型法寻找M1受体激动剂

寻找新的M1受体激动剂先导化合物。在M1受体三维结构未知的情况下，利用距离比较法（DISCO）将10个结构特征具有代表性的M1受体激动剂的分子构象进行叠合，建立了可能的药效团模型，初步验证了该模型的可靠性。利用该模型对ACD-SC数据库进行虚拟筛选，购买了22个与药效团叠合较好、与已知M1受体激动剂结构类型不同的化合物，并对其进行活性测定。结果发现了一个具有M1受体激动活性的化合物，其EC50为4．90μmol／L，最大响应倍数为10．0，值得进行更深入研究。     

Xa因子抑制剂的药效团模型初探

Xa因子是一种丝氨酸蛋白酶，在凝血过程中起关键作用。有关研究显示，Xa因子可以成为一个抗凝作用的新靶点，在口服抗凝血药的开发中扮演着重要角色。本文综述了近年来Xa因子抑制剂抗血凝作用的研究进展并对其药效团模型进行了探索。     

虚拟筛选辅助新药发现方法研究进展

在新药发现过程中, 虚拟筛选的应用可以富集活性化合物, 降低筛选成本, 提高药物筛选的可行性, 因此已成为新药发现的重要方法。虚拟筛选与生物活性筛选的结合, 可以优势互补, 有效地促进新药的发现。本文介绍了非类药化合物排除、假阳性化合物排除、药效团搜索、分子对接计算以及分子相似性分析等几种方法在药物发现中的应用及其发展趋势, 以期更好地应用虚拟筛选方法, 促进新药的快速发现。     

基于受体的抗炎药物药效团模型构建及应用研究

目的构建两种抗炎类药物三维药效团模型,对文献报道的二百余个具抗炎作用的中药化合物进行联合筛选,得到更具研究价值的中药化合物。方法分别以环氧化酶复合物和磷酸二酯酶复合物为基础,构建三维药效团模型;以文献报道的二百余个具抗炎作用的中药化合物为材料,构建三维结构数据库;将两种药效团模型用于对数据库的搜索,分别得到匹配药效团特征的化合物,优化并取交集。结果成功构建了三维药效团模型,对数据库搜索后得到同时符合两种药效团模型特征的中药化合物。结论以环氧化酶和磷酸二酯酶为受体进行三维药效团模型构建并联合筛选数据库,可得到具多靶点作用效应的抗炎中药化合物,该方法可为抗炎药物的设计及构效关系研究提供参考和借鉴。     

中药在抗感染治疗中的应用与研究概况

目的:综合分析中药在抗感染治疗中的应用情况.方法:检索文献,分析归纳相关报道.结果:部分中药具有抗菌、抗病毒、增强抗生素疗效、调节免疫的作用.结论:研究开发中药抗感染新药具有广泛前景.     

Pharmacophore modelling: applications in drug discovery

This review highlights the concept of using pharmacophore models in modern drug research and reviews some important examples as well as success stories. This includes papers from both method-development and application areas. As indicated by the number of publications available, the pharmacophore approach has proven to be extremely useful not only in virtual screening and library design for efficient hit discovery, but also in the optimisation of lead compounds to clinical candidates. Recent studies focus on the use of parallel screening using pharmacophore models for bioactivity profiling and early stage risk assessment of potential side effects and toxicity, due to the interaction of drug candidates with antitargets.     

Discovery of HIV‐1 Integrase Inhibitors: Pharmacophore Mapping,Virtual Screening,Molecular Docking,Synthesis, and Biological Evaluation

HIV‐1 integrase enzyme plays an important role in the life cycle of HIV and responsible for integration of virus into human genome. Here, both computational and synthetic approaches were used to design and synthesize newer HIV‐1 integrase inhibitors. Pharmacophore mapping was performed on 20 chemically diverse molecules using DISCOtech, and refinement was carried out using GASP. Ten pharmacophore models were generated, and model 2, containing four features including two donor sites, one acceptor atom, and one hydrophobic region, was considered the best model as it has the highest fitness score. It was used as a query in NCI and Maybridge databases. Molecules having more than 99% Q_fit value were used to design 30 molecules bearing pteridine ring and were docked on co‐crystal structure of HIV‐1 integrase enzyme. Among these, six molecules, showing good docking score compared with the reference standards, were synthesized by conventional as well as microwave‐assisted methods. All compounds were characterized by physical and spectral data and evaluated for in vitro anti‐HIV activity against the replication of HIV‐1 (IIIB) in MT‐4 cells. The used approach of molecular docking and anti‐HIV activity data of designed molecules will provide significant insights to discover novel HIV‐1 Integrase Inhibitors.     

Pharmacophore modelling and virtual screening for identification of new Aurora-A kinase inhibitors

Aurora-A has been identified as one of the most attractive targets for cancer therapy and a considerable number of Aurora-A inhibitors have been reported recently. In order to clarify the essential structure-activity relationship for the known Aurora-A inhibitors as well as identify new lead compounds against Aurora-A, 3D pharmacophore models were developed based on the known inhibitors. The best hypothesis, Hypo1, was used to screen molecular structural databases, including Specs and China Natural Products Database for potential lead compounds. The hit compounds were subsequently subjected to filtering by Lipinski's rules and docking study to refine the retrieved hits and as a result to reduce the rate of false positive. Finally, 39 compounds were purchased for further in vitro assay against several human tumour cell lines including A549, MCF-7, HepG2 and PC-3, in which Aurora-A is overexpressed. Two compounds show very low micromolar inhibition potency against some of these tumour cells. And they have been selected for further investigation.     

A Specific Pharmacophore Model of Aurora B Kinase Inhibitors and Virtual Screening Studies Based on it

In this study, 3D‐pharmacophore models of Aurora B kinase inhibitors have been developed by using HipHop and HypoGen modules in Catalyst software package. The best pharmacophore model, Hypo1, which has the highest correlation coefficient (0.9911), consists of one hydrogen‐bond acceptor, one hydrogen‐bond donor, one hydrophobic aliphatic moiety and one ring aromatic feature. Hypo1 was validated by test set and cross‐validation methods. And the specificity of Hypo1 to Aurora B inhibitors was examined with the use of selective inhibitors against Aurora B and its paralogue Aurora A. The results clearly indicate that Hypo1 can differentiate selective inhibitors of Aurora B from those of Aurora A, and the ring aromatic feature likely plays some important roles for the specificity of Hypo1. Then Hypo1 was used as a 3D query to screen several databases including Specs, NCI, Maybridge and Chinese Nature Product Database (CNPD) for identifying new inhibitors of Aurora B. The hit compounds were subsequently subjected to filtering by Lipinski’s rule of five and docking studies to refine the retrieved hits, and some compounds selected from the top ranked hits have been suggested for further experimental assay studies.     

Identification of Novel Anaplastic Lymphoma Kinase (ALK) Inhibitors Using a Common Feature Pharmacophore Model Derived from Known Ligands Crystallized with ALK

In this investigation, a common feature pharmacophore model of anaplastic lymphoma kinase inhibitors was developed based on several known anaplastic lymphoma kinase inhibitors that were co‐crystallized with anaplastic lymphoma kinase. The established pharmacophore model Hypo1 was carefully validated and then adopted to screen two in silico chemical databases, Specs (202 408 compounds) and Enamine (1 105 894 compounds), for retrieving novel anaplastic lymphoma kinase inhibitors. The hit compounds were further filtered using a fast bumping‐check tool and molecular docking. Finally, 25 compounds were selected and purchased from market. The bioactivity of these compounds was firstly measured at the cellular level against a typical anaplastic lymphoma kinase mutant‐driven cancer cell line, Karpas299. And six of them showed a good anti‐viability activity. The kinase inhibitory potency against the recombinant human anaplastic lymphoma kinase kinase was tested to the most active compound at the cellular level, T0508‐5181 (from Specs), which gave a half maximal inhibitory concentration (IC₅₀) of 5.3 μm .     

Pharmacophore and QSAR studies to design novel histone deacetylase 2 inhibitors

One pharmacophore model and three quantitative structure-activity relationship models were developed on a series of benzimidazole and imidazole inhibitors of histone deacetylase 2. The goodness of hit score value of the best pharmacophore model was 0.756, which indicated that it is reliable to be used for virtual screening. The built pharmacophore model was used to search the NCI database. The hit compounds were subjected to molecular docking. The results showed that 25 compounds had high scores and strong interactions with histone deacetylase 2. In three-dimensional quantitative structure-activity relationship studies, good predictive models were obtained using comparative molecular field analysis, comparative molecular similarity indices analysis, and Topomer comparative molecular field analysis. Some putative active compounds were proposed based on compound no. 41. Twenty-six compounds had high scores and good interactions when they were docking into histone deacetylase 2.     

计算机辅助金属酶靶向药物发现的研究进展

金属酶是指含功能必需和(或)结构必需金属离子的酶的统称,广泛参与关键生理和病理过程,是非常重要的药物作用靶标群。金属结合位点的电子和几何结构具有复杂性、多变性和动态性等特点,使得计算机辅助药物设计存在挑战性。本文综述金属结合药效团,基于结构的药物设计,人工智能等策略应用于金属酶靶向药物发现的研究进展、优势和面临挑战,期望能为金属酶靶向创新药物研发提供借鉴和思考。     

Discovery of novel acyl coenzyme a: cholesterol acyltransferase inhibitors: pharmacophore-based virtual screening, synthesis and pharmacology

The present study describes ligand‐based pharmacophore modeling of a series of structurally diverse acyl coenzyme A cholesterol acyltransferase inhibitors. Quantitative pharmacophore models were generated using HypoGen module of Discovery Studio 2.1, whereby the best pharmacophore model possessing two hydrophobic, one ring aromatic, and one hydrogen bond acceptor feature for inhibition of acyl coenzyme A cholesterol acyltransferase showed a very good correlation coefficient (r = 0.942) along with satisfactory cost analysis. Hypo1 was also validated by test set and cross‐validation methods. Developed models were found to be predictive as indicated by low error values for test set molecules. Virtual screening against Maybridge database using Hypo1 was performed. The two most potent compounds ( 47 and 48 ; predicted IC₅₀ = 1 nm ) of the retrieved hits were synthesized and biologically evaluated. These compounds showed 86% and 88% inhibition of acyl coenzyme A cholesterol acyltransferase (at 10 μg/mL) with IC₅₀ value of 3.6 and 2.5 nm , respectively. As evident from the close proximity of biological data to the predicted values, it can be concluded that the generated model (Hypo1) is a reliable and useful tool for lead optimization of novel acyl coenzyme A cholesterol acyltransferase inhibitors.     

3D Pharmacophore Model-Assisted Discovery of Novel CDC7 Inhibitors

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Pharmacophore‐Based Drug Design and Biological Evaluation of Novel ABCB1 Inhibitors

Overexpression of ABCB1 is one of major barriers for multidrug resistance in chemotherapy and limits drug oral bioavailability. Inhibition of ABCB1 would sensitize multidrug resistance in clinical cancer chemotherapy. With this aim, a 3D pharmacophore model was created based on known ABCB1 inhibitors with correlation coefficient of 0.94, comprising three hydrophobic features and one hydrogen bond acceptor. It was further validated and used to search our in‐house 3D database for potential ABCB1 inhibitors. The inhibitory activities of the best hits were evaluated by several biological assays, such as rhodamine 123 accumulation assay, chemosensitization assay, multidrug resistance 1‐Madin‐Darby canine kidney cells/Madin‐Darby canine kidney cells permeability assay. Finally, compounds YZ‐3 and YZ‐16 were identified as potential leads to be developed in the designing of novel potent ABCB1 inhibitors.