药物信息学在新药发现中的应用和研究进展

药物信息学是应用人类基因组计划产生的大量数据和全球分子生物学研究的结果,探讨发现药物的新靶点、新方法,促进药物研究进程的一门新的交叉学科,涉及生物信息学、化学信息学、计算化学、组合化学等多领域学科,

浙江大学药物信息学研究所简介

2003年在潘云鹤校长亲自运筹下，浙江大学药物信息学研究所诞生。2010年该研究所被学校评为浙江大学工业药学与多靶点新药发现理论科技创新团队。作为传承和弘扬求是创新文化的团队，其目标是建一流学科、育一流人才、创一流成果；

从药物信息学角度研究药物协同性的研究进展

目前临床上很多单一药物的使用已经不能满足复杂疾病的治疗需求,而多药物的联合使用,往往可以增强药效或者降低药物的不良反应,从而体现药物联用的协同性优势。因此药物协同性研究不论对于新药创制还是临床治疗方案的优化均具有积极的意义。相对于传统的实验手段,应用药物信息学方法研究药物的协同性,具有“快速、低成本、绿色”的优势。本文从药物信息学的角度对相关的资源数据库(包括药物及疾病的相关信息)、不同的预测模型以及应用情况进行详细描述,从而为开发新的分析模型提供参考。

药物分析信息学的理论研究与实践探索

目的:介绍药物分析信息学的理论和应用。方法:从药物分析信息的解析与挖掘、新型智能化分析仪器的研发、药物分析信息学的最新应用等方面进行阐述。结果:药物分析信息学已取得一定进展,并在分析信息解析、分析仪器智能化、代谢组学研究等方面发挥重要作用。结论:药物分析信息学已成为现代药物分析学科中的重要内容。

PBL教学模式在《药物生物信息学》教学中的应用

《药物生物信息学》是一门新兴交叉学科,它对伴随人类基因组计划产生的海量生物信息进行整理和分析,然后将这些生物信息应用于药物设计和开发,以达到药物合理设计的目的。由于该课程涉及数学、药学、生命科学等多个学科,学生学习时难以完全理解,为此,我们探索并实施了基于问题的教学法,通过引导学生提出问题和解决问题,在具体实践中激发学生的学习兴趣和主观能动性,取得较好的教学效果。

药物生物信息学课程教学探讨

探讨了药物生物信息学本科教学中教材的选择、教学方式的改革及如何在教学当中培养学生的实践能力和创新能力等问题。

药物生物信息学的多媒体教学

药物生物信息学作为一门发展迅速的交叉学科，也是药学课程建设的一门日益重要的课程。本文论述如何结合药物生物信息学学科的特点进行多媒体教学，包括在线网络数据库的介绍，生物大分子三维结构的演示等，以优化该课程的教学模式。

孤儿药研发相关的信息学研究进展

药物研发包括临床前研究和临床研究,在推动医药产业发展中发挥着至关重要的作用。由于研发各阶段投入成本高、周期长,药物毒性作用难预知等原因,新药开发的耗费巨大,成功率平均只有万分之一,周期可长达几年甚至几十年。而罕见病药物研发由于基因异质性高、病理机制未明、可参与临床试验的患者数量少等问题在药物研发上更是具有较大局限性。近年来信息学领域的飞速发展大大推动了药物研发的进程,基于计算机的理性药物设计、海量虚拟筛选、组合化学、高通量反应筛选系统等技术不断发展成熟,在新药研发的各个阶段均起到积极的促进作用;信息技术还有助于药物重定位这一新型药物开发模式的发展,通过药物警戒作用可对药物研发进行有效的反馈、补充。信息技术的发展还促进了药物研发模式向集成式研发转变。这对孤儿药研发起到了积极的促进作用。本文主要对孤儿药研发相关的信息学研究进展进行综述。

研究生教育对药物组学信息学创新型人才培养的重要作用研究

研究生教育是高层次创新型人才培养的重要渠道。研究生导师作为研究生教育的第一责任人,在培养创新型人才的过程中发挥着至关重要的作用。加强导师队伍思想建设,强化导师的使命感和责任感,不断加强专业学习,把握和紧跟学术领域前沿,加快新时代研究生教育改革,激发研究生学习兴趣,缩短学习曲线,打造良好的学术氛围。推进学术平台多元化,加强横向交叉学科联合,引导学生树立理想,加强国际视角。找准新时代信息学专业教育的新方位,努力提升研究生教育的卓越性,开创研究生教育发展新局面,为创新型人才培养做出应有的贡献。

化学组学及其信息学探索研究和初步应用

提出诸如烷烯炔组、醇酚醚组、醛酮醌组、生物碱组、抗生素组、黄酮[醇]组、多寡肽组、萜组、合成药物组、天然药物组、环境激素组、代谢物质组、环境激素组等化学组学新颖概念,犹如基因组、蛋白质组、糖组等生物组学概念一样,对于化学研究与应用具有重要意义,通过大量物质组分子多样性结构表达和化学性能预测,阐述了化学组学方法与技术的广阔应用前景。

第四军医大学药学院

第四军医大学药学院由院机关、化学、药物化学、药物分析学、药理学、药剂学、天然药物学、生物制药学、药物基因组学、药事管理与药物信息学教研室组成。经过多年建设，已经发展成为学科齐全、人才济济、实力雄厚，在全国具有一定影响力的教学、科研、药物研发基地，为我军药学事业做出了很大贡献.

Network Pharmacology-based Analysis on the Molecular Biological Mechanisms of Xin Hui Tong Formula in Coronary Heart Disease Treatment

Objective To investigate the potential molecular mechanism of Xin Hui Tong Formula (XHTF) in the treatment of coronary heart disease (CHD) by using network pharmacology and bioinformatics. Methods The targets network of CHD was constructed through Therapeutic Targets Database (TTD) and Drugbank database;The XHTF pharmacodynamic molecule-targets network and the XHTF pharmacodynamic molecule-CHD targets network were explored by the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP). And the multi-targets mechanism and molecular regulation network of XHTF in the treatment of CHD were explored from multiple perspectives by Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) database pathway enrichment analysis. Results A total of 88 CHD targets were screened out through the Therapeutic Targets and the Drugbank database. 393 compounds and corresponding 205 drug targets of XHTF were retrieved from TCMSP. A total of 13 known targets directly related to the development of CHD were retrieved from the disease-related databases: TP53, MAPK14, NFKB1, HSPA5, PLG, PTGS2, ADRB1, NOS2, CYP3A4, GRIA2, CYP2A6, GRIA1, PTGS1. XHTF also contained 118 drug targets that directly interact with CHD targets. GO enrichment analysis showed that the biological processes of 13 direct targets proteins were found to be mainly enriched in response to drug, cellular response to biotic stimulus, long-chain fatty acid metabolic process, fatty acid metabolic process and regulation of blood pressure. KEGG pathway enrichment analysis found that XHTF participated in the CHD pathological process mainly through retrograde endocannabinoid signaling, regulation of lipolysis in adipocytes, cAMP signaling pathway, chemical carcinogenesis and other pathways. Conclusions XHTF plays a role in the treatment of CHD through multiple targets and multiple pathways, and provides a scientific basis for the theory of "virtual standard" in the treatment of CHD.

Ethnobotany, Pharmacology and Chemistry of Medicinal Orchids from Veracruz

Orchidaceae is a large family of 1,260 species in Mexico, of which 433 grow in the state of Veracruz, Mexico. Although economically important in horticulture because of the beauty of their flowers, researches have done little work regarding their medicinal properties. This paper aimed to present the results of ethnobotanical, pharmacological and active compounds research on Veracruz medicinal orchids. The ethnobotanical information was obtained by consulting the Atlas of the Mexican Traditional Medicine Plants, Veracruz Medicinal Flora Database （CITRO-UV project） and through field work in the Nahuatl community of Cuautlajapa, Veracruz. To obtain pharmacological and active compounds information of registered species, a search was carded out through MEDLINE （USA National Library of Medicine Journal Citation database）. Twelve medicinal orchids were recorded for Veracruz, i.e., Epidendrum chlorocorymbos Schltr., Habenaria floribunda Lindl., Isochillus latibracteatus A. Rich. ＆ Galeotti, lsochillus major Schltdl. ＆ Cham., Mormodes maculata var. unicolor （Hook.） L. O. Williams, Oestlundia luteorosea （A. Rich. ＆ Galeotti） W. E. Higgins, Oncidium ascendens Lindl., Scaphyglottis fasciculata Hook., Sobralia macrantha Lindl., Spiranthes eriophora （Rob. ＆ Greenm.）, Stanhopea oculata （G. Lodd.） Lindl. and Vanilla planifolia Andrews. Only two species have been investigated in terms of their pharmacology and active compounds. Also, information for another five species closely related to already identified ones was obtained. Given the relative poverty of current information on the topic, this paper demonstrates the need to further study the ethnobotanical, pharmacological and chemical aspects of the region＇s medicinal orchids.

In Silico Screening of Potential Drug with Antileishmanial Activty and Validation of their Activity by in Vitro and in Vivo Studies

The research on discovery and development of new treatments for cutaneous leishmaniasis has been declared as priority. Using bioinformatics approaches, this study aimed to identify antileishmanial activity in drugs that are currently used as anti-inflammatory and wound healing by such anti-Leishmania activity was validated by in vitro and in vivo assays. In silico analysis identified 153 compounds from which 87 were selected by data mining of DrugBank database, 22 and 44 were detected by PASS （http：//pass.cribi.unipd.it） and BLAST （http：//blast.ncbi.nlm.nih. gov/） alignment, respectively. The majority of identified drugs are used as skin protector, anti-acne, anti-ulcerative （wound healer） or anti-inflammatory and few of them had specific antileishmanial activity. The efficacy as antileishmanial was validated in vitro in 12/23 tested compounds and in all seven compounds that were evaluated in in vivo assays. Notably, this is the first report of antileishmanial activity for adapalene. In conclusion, bioinformatics tools not only can help to reduce time and cost of the drug discovery process but also may increase the chance that candidates identified in silico which have a validated antileishmanial activity by combining different biological properties.

Exploring the Action Mechanism of Yadanzi(Brucea javanica)in the Treatment of Glioblastoma Based on Bioinformatics and Network Pharmacology

ObjectiveThe aim of the study is to explore the molecular mechanism of Yadanzi(Brucea javanica)in the treatment of glioblastoma(GBM)by using the methods of bioinformatics and network pharmacology.Methods The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP)and literature retrieval method were applied to obtain the active ingredients of Yadanzi(Brucea javanica),and to predict the relevant targets of the active ingredients.The GBM-related targets were retrieved and screened through the Gene Expression Profling Interactive Analysis(GEPIA)database,and mapped to each other with the targets of the components of Yadanzi(Brucea javanica)to obtain the intersection targets.The GBM differentially expressed gene targets were imported into the String database to obtain the protein interaction relationship,the Cytoscape software was used to draw the protein interaction network,the Cytobba and MCODE plug-ins were used to screen the core genes and important protein interaction modules,and the GEPIA database was applied to make survival analysis of the core genes.The network map of“active ingredients-targets”was constructed through the Cytoscape 3.6.1 software.Gene Ontology(GO)biological function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analysis for GBM differentially expressed genes were performed through the DAVID database.ResultsThrough TCMSP and literature retrieval,23 potential active ingredients and 129 related targets were obtained from Yadanzi(Brucea javanica).In the GEPIA database,247 GBM differentially expressed genes were screened,including 113 upregulated genes and 134 downregulated genes.After mapping with the targets related to the active ingredients of Yadanzi(Brucea javanica),six intersection targets were obtained,that is,the potential action targets of Yadanzi(Brucea javanica)in treating GBM,including MMP2,HMOX1,BIRC5,EGFR,CCNB2,and TOP2A.Cytoscape software was applied to build an“active ingredient-action target”network.Two active ingredients and five action targets of β-sitosterol(BS)and luteolin were found,and the targets were mainly concentrated in BS.It was found by KEGG pathway enrichment analysis that GBM differentially expressed genes were mainly involved in signaling pathways related to Staphylococcus aureus infection,phagosome formation,tuberculosis and systemic lupus erythematosus and other infectious and autoimmune diseases.It was found by GO enrichment analysis that the GBM differentially expressed genes mainly involved such biological processes(BP)as the processing and presentation of exogenous antigenic peptides and polysaccharide antigens through MHC Il molecules,y-interferon-mediated signaling pathways,extracellular matrix composition,and chemical synapses transmission;it involved cellular components such as cell junctions,axon terminal buttons,extracellular space,vesicle membranes for endocytosis,and MHC Il protein complexes;molecular functions such as calcium-mediated ionic protein binding,MHC Il molecular receptor activity,immunoglobulin binding,and phospholipase inhibitor activity were also involved.Survival analysis was conducted by GEPIA on the top 37 core targets in degree value,and a total of five genes related to GBM prognosis were obtained.Among them,FN1 and MMP2 were highly expressed while GABRD(v-aminobutyric acid A receptor delta subunit),RBFOX1,and SLC6A7 were expressed at a low level in cancer patients.Conclusion The pathogenesis of GBM is closely related to the human immune system,and BS and luteolin may be the main material basis of Yadanzi(Brucea javanica)for the treatment of GBM and the improvement of prognosis.The molecular mechanism may be related to the physical barrier formed by destroying the tumor cell stromal 68 Treatment of Glioblastoma Based on Bioinformatics and Network Pharmacology Zhao,Si.molecules and its involvement in tumor immune response.

Chemomics and drug innovation

Chemomics is an interdisciplinary study using approaches from chemoinformatics,bioinformatics,synthetic chemistry,and other related disciplines.Biological systems make natural products from endogenous small molecules (natural product building blocks) through a sequence of enzyme catalytic reactions.For each reaction,the natural product building blocks may contribute a group of atoms to the target natural product.We describe this group of atoms as a chemoyl.A chemome is the complete set of chemoyls in an organism.Chemomics studies chemomes and the principles of natural product syntheses and evolutions.Driven by survival and reproductive demands,biological systems have developed effective protocols to synthesize natural products in order to respond to environmental changes;this results in biological and chemical diversity.In recent years,it has been realized that one of the bottlenecks in drug discovery is the lack of chemical resources for drug screening.Chemomics may solve this problem by revealing the rules governing the creation of chemical diversity in biological systems,and by developing biomimetic synthesis approaches to make quasi natural product libraries for drug screening.This treatise introduces chemomics and outlines its contents and potential applications in the fields of drug innovation.

Integrating bioinformatics to identify and analyze feature genes of acute myocardial infarction and potential Chinese medicine prediction

In the present study,the Gene Expression Omnibus(GEO)dataset combined with machine learning was used to study differential genes in acute myocardial infarction(AMI)and to predict potential components and herbal medicines with regulatory effects.The human genome datasets of AMI(GSE66360 and GSE61145)were downloaded from the GEO database,and GSE66360 was used as the test set.After correction by normalization Between Arrays package of R,the limma package was used to obtain differentially expressed genes(DEGs).Then,we carried out Gene Ontology(GO),Kyoto Encyclopedia of Genes and Genomes(KEGG),and Disease Ontology(DO)enrichment analysis of DEGs.The feature genes were screened by SVM and random forest tree method,and the obtained feature genes were verified by the GSE61145 dataset.The components of traditional Chinese medicine(TCM)corresponding to AMI feature genes were found by the CTD database,and the corresponding TCM components were mapped by the Coremine database.According to the Dictionary of Traditional Chinese Medicine,Chinese Materia Medica,and Chinese Pharmacopoeia,the frequency,the four qi,five flavors,and meridian tropism of the obtained TCM were summarized.Through the analysis of the GSE66360 dataset,317 DEGs were obtained,of which 306 were up-regulated,and 11 were down-regulated.GO and KEGG enrichment analyses showed that the DEGs of AMI were mainly involved in neutrophil-mediated inflammation and immune response,abnormal lipid metabolism,lipid,and atherosclerosis-related pathways.DO enrichment analysis showed that the DEGs were closely related to atherosclerotic cardiovascular diseases and lung diseases.Six feature genes were obtained by SVM and random forest tree method,including ZFP36,GADD45A,PELI1,METRNL,MMP9,and CXCL16.Moreover,we found that the treatment of AMI Chinese medicine to sweet,bitter,and warm mostly attributed to the spleen,stomach,and liver.Besides,the components corresponding to the feature genes regulating AMI(ZFP36,GADD45A,PELI1,METRNL,MMP9,CXCL16)mainly included benzo(a)pyrene,tetrachlorodibenzodioxin,acetaminophen,and so on,and the corresponding TCMs included Camellia sinensis,Curcumaaromatica Salisb,Panax ginseng,and so on.In addition,a sweet taste,bitter taste,warm taste,and channel entry mainly belonged to the spleen,stomach,and liver meridians.