Drug2Gene: an exhaustive resource to explore effectively the drug-target relation network

BMC Bioinformatics

Helge G Roider²  Nadia Pavlova¹  Ivaylo Kirov¹  Stoyan Slavov¹  Todor Slavov¹  Zlatyo Uzunov¹  Bertram Weiss² 

[1] Metalife AG, Im Metapark 1, 79297 Winden, Germany

[2] Bayer Pharma AG, Müllerstr 178, 13342 Berlin, Germany

关键词: Bioactivity;    Biological effect;    Tool compounds;    Knowledge base;    Drug repositioning;    Drug discovery;    Drug development;    Compound-protein relations;    Drug-target relations;   

Others  :  1087601
DOI  :  10.1186/1471-2105-15-68

 received in 2013-11-18, accepted in 2014-03-03,  发布年份 2014

【 摘 要 】

Background

Information about drug-target relations is at the heart of drug discovery. There are now dozens of databases providing drug-target interaction data with varying scope, and focus. Therefore, and due to the large chemical space, the overlap of the different data sets is surprisingly small. As searching through these sources manually is cumbersome, time-consuming and error-prone, integrating all the data is highly desirable. Despite a few attempts, integration has been hampered by the diversity of descriptions of compounds, and by the fact that the reported activity values, coming from different data sets, are not always directly comparable due to usage of different metrics or data formats.

Description

We have built Drug2Gene, a knowledge base, which combines the compound/drug-gene/protein information from 19 publicly available databases. A key feature is our rigorous unification and standardization process which makes the data truly comparable on a large scale, allowing for the first time effective data mining in such a large knowledge corpus. As of version 3.2, Drug2Gene contains 4,372,290 unified relations between compounds and their targets most of which include reported bioactivity data. We extend this set with putative (i.e. homology-inferred) relations where sufficient sequence homology between proteins suggests they may bind to similar compounds. Drug2Gene provides powerful search functionalities, very flexible export procedures, and a user-friendly web interface.

Conclusions

Drug2Gene v3.2 has become a mature and comprehensive knowledge base providing unified, standardized drug-target related information gathered from publicly available data sources. It can be used to integrate proprietary data sets with publicly available data sets. Its main goal is to be a ‘one-stop shop’ to identify tool compounds targeting a given gene product or for finding all known targets of a drug. Drug2Gene with its integrated data set of public compound-target relations is freely accessible without restrictions at http://www.drug2gene.com webcite.

【 授权许可】

   
2014 Roider et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

【 参考文献 】

• [1]Gaulton A, Bellis LJ, Bento AP, Chambers J, Davies M, Hersey A, Light Y, McGlinchey S, Michalovich D, Al-Lazikani B, Overington JP: ChEMBL: a large-scale bioactivity database for drug discovery. Nucleic Acids Res 2011, 40:D1100-D1107.
• [2]ChEMBL 17 release notes ftp://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_17/chembl_17_release_notes.txt
• [3]Liu T, Lin Y, Wen X, Jorissen RN, Gilson MK: BindingDB: a web-accessible database of experimentally determined protein-ligand binding affinities. Nucleic Acids Res 2007, 35:D198-D201.
• [4]BindingDB Website - Info http://www.bindingdb.org/bind/info.jsp webcite
• [5]Knox C, Law V, Jewison T, Liu P, Ly S, Frolkis A, Pon A, Banco K, Mak C, Neveu V, Djoumbou Y, Eisner R, Guo AC, Wishart DS: DrugBank 3.0: a comprehensive resource for “Omics” research on drugs. Nucleic Acids Res 2010, 39:D1035-D1041.
• [6]Wassermann AM, Bajorath J: BindingDB and ChEMBL: online compound databases for drug discovery. Expert Opin Drug Discov 2011, 6:683-687.
• [7]Kuhn M, Szklarczyk D, Franceschini A, von Mering C, Jensen LJ, Bork P: STITCH 3: zooming in on protein-chemical interactions. Nucleic Acids Res 2011, 40:D876-D880.
• [8]Hecker N, Ahmed J, von Eichborn J, Dunkel M, Macha K, Eckert A, Gilson MK, Bourne PE, Preissner R: SuperTarget goes quantitative: update on drug-target interactions. Nucleic Acids Res 2011, 40:D1113-D1117.
• [9]Chen B, Ding Y, Wild DJ: Assessing drug target association using semantic linked data. PLoS Comput Biol 2012, 8:e1002574.
• [10]Sugaya N, Kanai S, Furuya T: Dr. PIAS 2.0: an update of a database of predicted druggable protein-protein interactions. Database J Biol Databases Curation 2012, 2012:bas034.
• [11]Von Eichborn J, Murgueitio MS, Dunkel M, Koerner S, Bourne PE, Preissner R: PROMISCUOUS: a database for network-based drug-repositioning. Nucleic Acids Res 2010, 39:D1060-D1066.
• [12]Fu C, Jin G, Gao J, Zhu R, Ballesteros-villagrana E, Wong STC: DrugMap Central: an on-line query and visualization tool to facilitate drug repositioning studies. Bioinformatics 2013, 29:1834-1836.
• [13]Aksoy BA, Gao J, Dresdner G, Wang W, Root A, Jing X, Cerami E, Sander C: PiHelper: an open source framework for drug-target and antibody-target data. Bioinformatics 2013, 29:2071-2072.
• [14]Gong J, Cai C, Liu X, Ku X, Jiang H, Gao D, Li H: ChemMapper: a versatile web server for exploring pharmacology and chemical structure association based on molecular 3D similarity method. Bioinformatics 2013, 29:1827-1829.
• [15]NCBI Resource Coordinators: Database resources of the National Center for Biotechnology Information. Nucleic Acids Res 2012, 41:D8-D20.
• [16]Nicola G, Liu T, Gilson MK: Public domain databases for medicinal chemistry. J Med Chem 2012, 55:6987-7002.
• [17]The NCI Cancer Gene Data Curation Pilot https://wiki.nci.nih.gov/display/caBIO/caBIO+Data+Sources#caBIODataSources-CancerGeneIndexProject webcite
• [18]Davis AP, Murphy CG, Johnson R, Lay JM, Lennon-Hopkins K, Saraceni-Richards C, Sciaky D, King BL, Rosenstein MC, Wiegers TC, Mattingly CJ: The Comparative Toxicogenomics Database: update 2013. Nucleic Acids Res 2012, 41:D1104-D1114.
• [19]Sharman JL, Mpamhanga CP, Spedding M, Germain P, Staels B, Dacquet C, Laudet V, Harmar AJ, NC-IUPHAR: IUPHAR-DB: new receptors and tools for easy searching and visualization of pharmacological data. Nucleic Acids Res 2010, 39:D534-D538.
• [20]Molecular Imaging and Contrast Agent Database (MICAD) http://www.ncbi.nlm.nih.gov/books/NBK5330/ webcite
• [21]Roth BL, Lopez E, Patel S, Kroeze WK: The Multiplicity of Serotonin Receptors: Uselessly Diverse Molecules or an Embarrassment of Riches? Neuroscientist 2000, 6:252-262.
• [22]McDonagh EM, Whirl-Carrillo M, Garten Y, Altman RB, Klein TE: From pharmacogenomic knowledge acquisition to clinical applications: the PharmGKB as a clinical pharmacogenomic biomarker resource. Biomark Med 2011, 5:795-806.
• [23]Zhu F, Shi Z, Qin C, Tao L, Liu X, Xu F, Zhang L, Song Y, Liu X, Zhang J, Han B, Zhang P, Chen Y: Therapeutic target database update 2012: a resource for facilitating target-oriented drug discovery. Nucleic Acids Res 2012, 40:D1128-D1136.
• [24]The UniProt Consortium: Reorganizing the protein space at the Universal Protein Resource (UniProt). Nucleic Acids Res 2012, 40:D71-D75.
• [25]Feng Z, Chen L, Maddula H, Akcan O, Oughtred R, Berman HM, Westbrook J: Ligand Depot: a data warehouse for ligands bound to macromolecules. Bioinformatics 2004, 20:2153-2155.
• [26]Seal RL, Gordon SM, Lush MJ, Wright MW, Bruford EA: genenames.org: the HGNC resources in 2011. Nucleic Acids Res 2011, 39:D514-D519.
• [27]Laskowski RA: PDBsum new things. Nucleic Acids Res 2009, 37:D355-D359.
• [28]De Matos P, Alcántara R, Dekker A, Ennis M, Hastings J, Haug K, Spiteri I, Turner S, Steinbeck C: Chemical Entities of Biological Interest: an update. Nucleic Acids Res 2010, 38:D249-D254.
• [29]Bolton EE, Wang Y, Thiessen PA, Bryant SH: Chapter 12 PubChem: Integrated Platform of Small Molecules and Biological Activities. Annu Reports Comput Chem 2008, 4:217-241.
• [30]Wang Y, Xiao J, Suzek TO, Zhang J, Wang J, Zhou Z, Han L, Karapetyan K, Dracheva S, Shoemaker BA, Bolton E, Gindulyte A, Bryant SH: PubChem’s BioAssay Database. Nucleic Acids Res 2012, 40:D400-D412.
• [31]Dalby A, Nourse JG, Hounshell WD, Gushurst AKI, Grier DL, Leland BA, Laufer J: Description of several chemical structure file formats used by computer programs developed at molecular design limited. J Chem Inf Comput Sci 1992, 32:244-255.
• [32]Cerami EG, Gross BE, Demir E, Rodchenkov I, Babur Ö, Anwar N, Schultz N, Bader GD, Sander C: Pathway Commons, a web resource for biological pathway data. Nucleic Acids Res 2011, 39:D685-D690.
• [33]Xu M, Hou Y, Sheng L, Peng J: Therapeutic effects of thalidomide in hematologic disorders: a review. Front Med 2013, 7:290-300.