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I'm writing a thesis on bioinformatics and looking for drug-target databases. I'm implementing a open-source application for a tool called Cytoscape and so far I've used a open-source database called DrugBank to retrieve drug-target data, but I've read a paper on a database called Drug2Gene that combines multiple open databases into a unified format. The paper is from 2014, but all websites are down and I was wondering if someone here knows of any other databases/resources that does this and is maybe up-to-date? I want to utilize as much open-source data on drug to target relation as possible to provide a simple way of accessing all these resources. Drugbank is regularly updated and a good source, but with so many different databases with a decreasing overlap of data I was happy to stumble across Drug2Gene database only to realize I can't get it and it's probably not up-to-date.

I will be very thankful for any tips as I'm purely a Informatician and feeling helpless in finding thing related to biology.

Source: Drug2Gene paper

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There are quite a lot drug databases. I think DGIbd is a good place to start (see below). Further there are a lot of databases which describe drugs and their targets, take a look at these (and the links at the bottom) hopefully you can use several of these in your implementation.

SIDER

SIDER contains information on marketed medicines and their recorded adverse drug reactions. The information is extracted from public documents and package inserts. The available information include side effect frequency, drug and side effect classifications as well as links to further information, for example drug–target relations.


DrugCentral

DrugCentral provides information on active ingredients chemical entities, pharmaceutical products, drug mode of action, indications, pharmacologic action. We monitor FDA, EMA, and PMDA for new drug approval on regular basis to ensure currency of the resource. Limited information on discontinued and drugs approved outside US is also available however regulatory approval information can't be verified.


Therapeutic Target Database

Therapeutic Target Database (TTD) is a database to provide information about the known and explored therapeutic protein and nucleic acid targets, the targeted disease, pathway information and the corresponding drugs directed at each of these targets. Also included in this database are links to relevant databases containing information about target function, sequence, 3D structure, ligand binding properties, enzyme nomenclature and drug structure, therapeutic class, clinical development status. All information provided are fully referenced.


Potential drug target database (PDTD)
NOTE: I think this one is coupled to DrugBank however you can take a look here

PDTD is a dual function database that associates an informatics database to a structural database of known and potential drug targets. PDTD is a comprehensive, web-accessible database of drug targets, and focuses on those drug targets with known 3D-structures.


PharmGKB

The PharmGKB is a pharmacogenomics knowledge resource that encompasses clinical information including dosing guidelines and drug labels, potentially clinically actionable gene-drug associations and genotype-phenotype relationships. PharmGKB collects, curates and disseminates knowledge about the impact of human genetic variation on drug responses through the following activities: Annotate genetic variants and gene-drug-disease relationships via literature reviews Summarize important pharmacogenomic genes, associations between genetic variants and drugs, and drug pathways Curate FDA drug labels containing pharmacogenomic information Enable consortia examining important questions in pharmacogenomics Curate and participate in writing pharmacogenomic-based drug dosing guidelines Contribute to clinical implementation projects for pharmacogenomics through collaborations Publish pharmacogenomic-based drug dosing guidelines, very important pharmacogene summaries and drug-centered pathways Display all information on the website and provide comprehensive downloads


STITCH

To facilitate access to this data, STITCH (‘search tool for interactions of chemicals’) integrates information about interactions from metabolic pathways, crystal structures, binding experiments and drug–target relationships. Inferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals. STITCH further allows exploring the network of chemical relations, also in the context of associated binding proteins. Each proposed interaction can be traced back to the original data sources. Our database contains interaction information for over 68 000 different chemicals, including 2200 drugs, and connects them to 1.5 million genes across 373 genomes and their interactions contained in the STRING database.


SuperTarget and Metador

An easy-to-use query interface enables the user to pose complex queries, for example to find drugs that target a certain pathway, interacting drugs that are metabolized by the same cytochrome P450 or drugs that target the same protein but are metabolized by different enzymes. Furthermore, we provide tools for 2D drug screening and sequence comparison of the targets. The database contains more than 2500 target proteins, which are annotated with about 7300 relations to 1500 drugs; the vast majority of entries have pointers to the respective literature source. A subset of these drugs has been annotated with additional binding information and indirect interactions and is available as a separate resource called Matador.


Pharos

Pharos is the user interface to the Knowledge Management Center (KMC) for the Illuminating the Druggable Genome (IDG) program funded by the National Institutes of Health (NIH) Common Fund. (Grant No. 5U54CA189205-02). The goal of KMC is to develop a comprehensive, integrated knowledge-base for the Druggable Genome (DG) to illuminate the uncharacterized and/or poorly annotated portion of the DG, focusing on four of the most commonly drug-targeted protein families:  G-protein-coupled receptors (GPCRs); nuclear receptors (NRs); ion channels (ICs); and kinases. For more information on opportunities in the druggable human genome see this poster


KEGG drug

KEGG DRUG is a comprehensive drug information resource for approved drugs in Japan, USA, and Europe unified based on the chemical structures and/or the chemical components, and associated with target, metabolizing enzyme, and other molecular interaction network information. All the marketed drugs in Japan, not only the prescription drugs but also the OTC drugs, are fully represented in KEGG DRUG and integrated with the package insert information (labels information). These include crude drugs and TCM (Tradictional Chinese Medicine) drugs.


The IUPHAR/BPS Guide to PHARMACOLOGY (database)

The information in the database is presented at two levels: the initial view or landing pages for each target family provide expert-curated overviews of the key properties and selective ligands and tool compounds available. For selected targets more detailed introductory chapters for each family are available along with curated information on the pharmacological, physiological, structural, genetic and pathophysiogical properties of each target. The database is enhanced with hyperlinks to additional information in other databases including Ensembl, UniProt, PubChem, ChEMBL and DrugBank, as well as curated chemical information and literature citations in PubMed.


DGIbd

The druggable genome can be defined as the genes or gene products that are known or predicted to interact with drugs, ideally with a therapeutic benefit to the patient. Such genes are of particular interest to large-scale cancer profiling efforts such as TCGA, ICGC and others that identify lists of potential cancer driver genes from high-throughput sequence and other genome-wide data. In cancer therapy, the increasing number of targeted drugs--those designed to inactivate proteins carrying activating amino acid changes as determined by mutational analyses--make more compelling the need for a searchable database of drug-gene interactions, available here.


There are a lot more databases, maybe these links will help you:

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