治疗慢性肾病中药计算机网络药理学研究

药物分子和靶标之间的相互作用是其药理作用的基础.运用分子对接和复杂网络分析技术研究治疗慢性肾病中药所含化学成分和靶标之间的相互作用.结果显示治疗慢性肾病中药所含化学成分-靶标相互作用网络与西药的化学成分-靶标相互作用网络存在较大的差异,这说明中药的作用机制和西药的作用机制不完全相同.研究还发现补益类中药所含化学成分-靶标相互作用网络与攻逐类中药所含化学成分-靶标相互作用网络也存在较大差异,这从复杂网络研究视角阐释了古老的中药分类理论.这种研究方法可以快速筛选出治疗慢性肾病中药中的有效成分群及其关键靶标,为组分中药的研发提供实验数据.     

精制透骨消痛颗粒防治骨性关节炎的计算机药理学

采用分子相似性分析、化学空间、分子对接、生物网络技术和药代动力学性质预测等计算机药理学方法研究中药精制透骨消痛颗粒中514个化合物的药理学机制. 结果表明: 该复方所含化合物在化学结构上具有多样性及大部分化合物在化学空间上具有类药性质; 通过514 与35个骨性关节炎疾病相关的公认靶标的相互作用及它们在靶空间的分布上阐明了精制透骨消痛颗粒防治骨性关节炎的可能作用机理, 发现了一些潜在的活性分子; 通过分析药物库中骨性关节炎的药物-靶点的作用网络及精制透骨消痛颗粒中分子-靶点的作用网络的异质性值、特征路径长度等特征, 揭示精制透骨消痛颗粒的多药物、多靶点、多途径分子作用机制. 结果有助于理解中药精制透骨消痛颗粒的复杂作用机制.     

辛味中药与嗅觉受体相互作用的分子模拟

采用分子模拟的方法, 在Schrdinger软件平台上, 用同源模建的方法构建了嗅觉受体OR1D2, OR7D4和OR51E1的三维结构模型. 运用分子动力学模块Desmond将与激动剂以及抑制剂分别对接的嗅觉受体复合物置于磷脂双膜中进行模拟. 最后将辛味中药的小分子分别对接到嗅觉受体中, 并与苦味中药的对接结果相对照, 依据实验结果, 讨论辛味中药发挥作用的分子机制. 该研究着重于同源模建、分子动力学和分子对接技术的综合应用, 探讨辛味中药化学成分与嗅觉受体的相互作用及其分子机理, 为从分子层面揭示辛味中药的药效物质基础提供帮助, 也为中药药性的研究提供了新的思路和方法.     

乙型肝炎病毒表面抗原三维结构的同源模建及功能预测

结合生物信息学方法及分子模拟手段, 通过同源模建方法构建了乙型肝炎病毒表面抗原(HBsAg)Pres12的三维空间结构, 并结合生物实验在分子水平上探讨了乙型肝炎病毒表面抗原Pres12作为抗乙型肝炎病毒重要靶标的机理. 研究结果表明, HBsAg三维空间结构是由构型性的Pres1和线性的Pres2组成, 此结构由疏水氨基酸形成3个α-螺旋结构及Loop结构域, 并且N端由Pres1中残基构成了一个开裂, 形成了HBsAg可能的活性部位. 静电势分析结果证实, N端可能的活性部位具有较大的静电势分布, 因而具有与受体细胞蛋白相互作用的能力, 这为HBV病毒抑制剂药物分子的设计提供了有益帮助.     

芪参益气滴丸治疗心血管疾病的计算药理学研究

利用计算药理学方法研究了中药芪参益气滴丸中含1729个化合物在化学空间分布,结果表明大部分化合物具有较好的类药性质．利用分子对接方法研究了1729个与26个心血管疾病相关的公认靶标的相互作用及它们在靶空间的分布,阐明了芪参益气滴丸抗血管疾病的可能作用机理及活性分子．     

识别手性六螺烯分子的计算机模拟

手性拆分分子与手性分子间的短程相互作用会形成非对映异构体的接触对,从而导致的立体选择作用很难传统实验方法进行研究^[1]。蛋白质－核酸识别机理和研究表明,计算机模拟可以很好地研究这个问题^[2]。用高分子分离性分子的计算机模拟尚未见报道。     

离子液与蛋白质和核酸相互作用的研究

离子液因其具有良好的生物兼容性和独特的理化性质,近年来在生物催化和生物大分子蛋白质与核酸的分离分析领域得到广泛应用。离子液与生物大分子相互作用的研究是离子液相关理论与应用研究的基础,有关离子液与蛋白质和核酸相互作用的机理研究受到关注。本文简要介绍了常用离子液的分类,离子液与蛋白质分子作用的机理,离子液与核酸分子作用的机理,以及离子液在酶催化反应、生物分子分离、生物分子电化学分析和毛细管电泳分析中的应用,并主要综述了近年的相关研究和应用进展。     

药物发现中常用化合物库特征描述与对比分析

随着计算技术的发展和分子模拟软件的日趋成熟, 虚拟筛选已经在药物发现过程中发挥着越来越重要的作用. 在虚拟筛选过程中, 所使用化合物库的质量对先导化合物发现的成功率起着至关重要的作用. 本文通过对已知药物库、天然产物库、中药原植物化学成分库、筛选常用商业化合物库以及研究者所在实验室建立的化合物库的分析比较, 从化合物库的分子多样性、化学空间和分子骨架等多个方面提取并对比每一种化合物库的特征, 发现了已知药物库与中药原植物化学成分库的特征相似性, 揭示了中药原植物化学成分库作为筛选库的类药性优势, 并且深化了对几种筛选用化合物库特征的认识和理解.     

小分子靶标的核酸适配体筛选的研究进展

核酸适配体(aptamer)是通过指数富集配体系统进化(SELEX)技术筛选得到的核糖核酸(RNA)或单链脱氧核糖核酸(ssDNA)。核酸适配体通过高亲和力特异性地识别小分子、蛋白质、细胞、微生物等多种靶标,在生物、医药、食品和环境检测等领域的应用日渐增多。但目前实际可用的核酸适配体有限,其筛选过程复杂,筛选难度大,制约了其应用。与生物大分子、细胞和微生物等靶标不同,小分子靶标与核酸分子的结合位点少、亲和力弱,且靶标通常需要固定在载体上。此外,小分子靶标结合核酸形成的复合物与核酸自身的大小、质量、电荷性质等方面差异较小,二者的分离难度大。故小分子靶标的核酸适配体筛选过程与大分子和细胞等复合靶标相比有明显差异,筛选难度更大。因此需要根据其自身结构特点和核酸适配体的应用目的选定靶标或核酸库的固定方法,优化靶标核酸复合物的分离方法。本文介绍了不同类型小分子(具有基团差异的单分子、含相同基团分子和手性分子等)靶标的选择及其核酸适配体的筛选方法,并对核酸库的设计、与靶标结合的核酸的分离方法和亲和作用表征方法进行了介绍,列出了自2008年以来报道的40余种小分子靶标的核酸适配体序列和复合物的平衡解离常数(K_d)。     

基于高分辨质谱技术的农药与生物大分子相互作用的分析方法

建立了检测农药小分子与生物大分子(BSA蛋白,SOD酶)相互作用的高分辨质谱分析方法.对相应结合产物进行质谱检测,结果表明,BSA蛋白与甲基对硫磷分子在开始相互作用30 min后达到饱和,且每个蛋白分子最多与5个甲基对硫磷分子结合;BSA蛋白与甲维盐不存在相互作用.通过对SOD酶与敌敌畏,阿维菌素及噻呋酰胺结合产物的质谱检测发现每个SOD酶最多结合2个敌敌畏分子,1个阿维菌素分子,且不与噻呋酰胺相互作用.此外,实验表明,SOD酶与阿维菌素分子作用30 min后达到平衡,与敌敌畏分子作用20 min后达到平衡.通过对两种蛋白结合农药小分子过程的时间分辨分析发现,两种生物大分子结合农药小分子的机理过程存在差异.本方法与相关标准方法(荧光光谱法,NBT试剂盒法)及分子模拟对接结果比对说明,本方法切实可靠.本方法具有耗样量少、检测速度快、可提供多方面信息等优点,在新农药的研发及其安全性评价方面具有实用价值.     

Exploration of the mechanism of Zisheng Shenqi decoction against gout arthritis using network pharmacology

BackgroundIn this study, the network pharmacological methods were used to predict the target of effective components of compounds in Zisheng Shenqi Decoction (ZSD, or Nourishing Kidney Qi Decoction) in the treatment of gouty arthritis (GA).MethodThe main effective components and corresponding key targets of herbs in the ZSD were discerned through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis (TCMSP), Bioinformatics Analysis Tool for Molecular mechanism of Traditional Chinese Medicine (BATMAN-TCM) database. UniProt database and Swiss Target Prediction (STP) database was used to rectify and unify the target names and supply the target information. The targets related to GA were obtained by using GeneCards database. After we discovered the potential common targets between ZSD and GA, the interaction network diagram of “ZSD-component-GA-target” was constructed by Cytoscape software (Version 3.7.1). Subsequently, the Protein-protein interaction (PPI) network of ZSD effective components-targets and GA-related targets was constructed by Search Tool for the Retrieval of Interacting Genes Database (STRING). Bioconductor package “org.Hs.eg.db” and “cluster profiler” package were installed in R software (Version 3.6.0) which used for Gene Ontology analysis and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis.Results146 components and 613 targets of 11 herbal medicines in the ZSD were got from TCMSP database and BATMAN-TCM database. 987 targets of GA were obtained from GeneCards database. After intersected and removed duplications, 132 common targets between ZSD and GA were screened out by Cytoscape software (Version 3.7.1). These common targets derived from 81 effective components of 146 components, such as quercetin, stigmasterol and kaempferol. They were closely related to anti-inflammatory, analgesic and anti oxidative stress and the principal targets comprised of Purinergic receptor P2X, ligand-gated ion channel 7 (P2x7R), Nod-like receptor protein 3 (NLRP3) and IL-1β. GO enrichment analysis and KEGG pathway enrichment analysis by R software (Version 3.6.0) showed that the key target genes had close relationship with oxidative stress, reactive oxygen species (ROS) metabolic process and leukocyte migration in aspects of biological process, cell components and molecular function. It also indicated that ZSD could decrease inflammatory reaction, alleviate ROS accumulation and attenuate pain by regulating P2 × 7R and NOD like receptor signaling pathway of inflammatory reaction.ConclusionA total of 81 effective components and 132 common target genes between ZSD and GA were screened by network pharmacology. The PPI network, GO enrichment analysis and KEGG pathway enrichment analysis suggested that ZSD can exerte anti-inflammatory and analgesic effects on the treatment of GA by reducing decreasing inflammatory reaction, alleviating ROS accumulation, and attenuating pain. The possible molecular mechanism of it mainly involved multiple components, multiple targets and multiple signaling pathways, which provided a comprehensive understanding for further study. In general, the network pharmacological method applied in this study provides an alternative strategy for the mechanism of ZSD in the treatment of GA.     

A multivariate insight into the in vitro antitumour screen database of the National Cancer Institute: classification of compounds, similarities among cell lines and the influence of molecular targets

A multivariate insight into the in vitro antitumour screen database of the NCI by means of the SIMCA package allows to propose hypotheses on the mechanism of action of novel anticancer compounds. As an example, the application of multivariate analysis to the NCI standard database provided clues to the classification of drugs whose mechanism is either unknown or controversial. Moreover, the influence of intrinsic biochemical cell line properties (molecular targets) on the sensitivity to drug treatment could be evaluated simultaneously for classes of compounds which act by the same mechanism. Interestingly, the present approach can also provide a correlation between the molecular targets and the therapeutical fingerprint of novel active compounds thus suggesting specific biochemical studies for the investigation of new mechanisms of drug action and resistance. The statistical approach reported here represents a valuable tool for handling theenormous data sets deriving from recent genome-wide investigations of gene expression in the NCI cell lines.     

The measurement of molecular diversity by receptor site interaction simulation

The assembly of large compound libraries for the purpose of screening against various receptor targets to identify chemical leads for drug discovery programs has created a need for methods to measure the molecular diversity of such libraries. The method described here, for which we propose the acronym RESIS (for Receptor Site Interaction Simulation), relates directly to this use. A database is built of three-dimensional representations of the compounds in the library and a set of three-point three-dimensional theoretical receptor sites is generated based on putative hydrophobic and polar interactions. A series of flexible, three-dimensional searches is then performed over the database, using each of the theoretical sites as the basis for one such search. The resulting pattern of hits across the grid of theoretical receptor sites provides a measure of the molecular diversity of the compound library. This can be conveniently displayed as a density map which provides a readily comprehensible visual impression of the library diversity characteristics. A library of 7500 drug compounds derived from the CIPSLINEPC databases was characterized with respect to molecular diversity using the RESIS method. Some specific uses for the information obtained from application of the method are discussed. A comparison was made of the results from the RESIS method with those from a recently published two-dimensional approach for assessing molecular diversity using sets of compounds from the Maybridge database (MAY).     

Comparative molecular surface analysis (CoMSA) for virtual combinatorial library screening of styrylquinoline HIV-1 blocking agents

We used comparative molecular surface analysis to design molecules for the synthesis as part of the search for new HIV-1 integrase inhibitors. We analyzed the virtual combinatorial library (VCL) constituted from various moieties of styrylquinoline and styrylquinazoline inhibitors. Since imines can be applied in a strategy of dynamic combinatorial chemistry (DCC), we also tested similar compounds in which the -C=N- or -N=C- linker connected the heteroaromatic and aromatic moieties. We then used principal component analysis (PCA) or self-organizing maps (SOM), namely, the Kohonen neural networks to obtain a clustering plot analyzing the diversity of the VCL formed. Previously synthesized compounds of known activity, used as molecular probes, were projected onto this plot, which provided a set of promising virtual drugs. Moreover, we further modified the above mentioned VCL to include the single bond linker -C-N- or -N-C-. This allowed increasing compound stability but expanded also the diversity between the available molecular probes and virtual targets. The application of the CoMSA with SOM indicated important differences between such compounds and active molecular probes. We synthesized such compounds to verify the computational predictions.     

In silico identification of natural products with anticancer activity using a chemo-structural database of Brazilian biodiversity

Cancer is one of the leading causes of death worldwide, and the number of patients has only increased each year, despite the considerable efforts and investments in scientific research. Since natural products (NPs) may serve as suitable sources for drug development, the cytotoxicity against cancer cells of 2221 compounds from the Nuclei of Bioassays, Ecophysiology, and Biosynthesis of Natural Products Database (NuBBE_DB) was predicted using CDRUG algorithm. Molecular modeling, chemoinformatics, and chemometric tools were then used to analyze the structural and physicochemical properties of these compounds. We compared the positive NPs with FDA-approved anticancer drugs and predicted the molecular targets involved in the anticancer activity. In the present study, 46 families comprising potential anticancer compounds and at least 19 molecular targets involved in oncogenesis. To the best of our knowledge, this is the first large-scale study conducted to evaluate the potentiality of NPs sourced from Brazilian biodiversity as anticancer agents, using in silico approaches. Our results provided interesting insights about the mechanism of action of these compounds, and also suggested that their structural diversity may aid structure-based optimization strategies for developing novel drugs for cancer therapy.     

Uncovering the pharmacological mechanism of motherwort (Leonurus japonicus Houtt.) for treating menstrual disorders: A systems pharmacology approach

Leonurus japonicus (motherwort) is a traditional Chinese medicine that is widely used to treat menstrual disorders (MDs). However, the pharmacological mechanisms that underlie its clinical application remain unclear. In this study, a network pharmacology-based approach was used that integrated drug-likeness evaluation, oral bioavailability prediction, target exploration, network construction, bioinformatic annotation and molecular docking to investigate the mechanisms that underlie motherwort treatment for MDs. In total, 29 bioactive compounds were collected from 51 compounds in motherwort, which shared 17 common MDs-related targets. Network analysis indicated that motherwort played a therapeutic role in MDs treatment through multiple components that acted on multiple targets. Pathway enrichment analysis showed that the putative targets of motherwort were primarily involved in various pathways associated with the endocrine system, cancers, vascular system, and anti-inflammation process. Notably, five targets (i.e., AKT1, PTGS2, ESR1, AR and PPARG) were screened as hub genes based on a degree algorithm. Moreover, most of the bioactive components in motherwort had good binding ability with these genes, implying that motherwort could regulate their biological function. Collectively, this study elucidated the molecular mechanisms that underlay the efficiency of motherwort against MDs and demonstrated the potential of network pharmacology as an approach to uncover the action mechanism of herbal medicines.     

Diversity-oriented synthesis: producing chemical tools for dissecting biology

Small molecule modulators of biological function can be discovered by the screening of compound libraries. However, it became apparent that some human disease related targets could not be addressed by the libraries commonly used which typically are comprised of large numbers of structurally similar compounds. The last decade has seen a paradigm shift in library construction, with particular emphasis now being placed on increasing a library's structural, and thus functional diversity, rather than only its size. Diversity-oriented synthesis (DOS) aims to generate such structural diversity efficiently. This tutorial review has been written to introduce the subject to a broad audience and recent achievements in both the preparation and the screening of structurally diverse compound collections against so-called 'undruggable' targets are highlighted.