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Gathers detailed drug, drug-target, drug action and drug interaction information about drugs. DrugBank is a web resource that contains information about FDA-approved drugs as well as experimental drugs going through the FDA approval process. The database also includes pharmaco-omic data covering the influence of drugs on metabolite levels, gene expression levels and protein expression levels, as well as data on investigational drug clinical trials and drug repurposing trials, and thousands of up-to-date drug images of approved drugs.
STITCH / Search Tool for Interactions of Chemicals
A resource to explore known and predicted interactions of chemicals and proteins. Chemicals are linked to other chemicals and proteins by evidence derived from experiments, databases and the literature. STITCH contains interactions for between 300,000 small molecules and 2.6 million proteins from 1133 organisms. In addition to the increased scope of the database, we have implemented a new network view that gives the user the ability to view binding affinities of chemicals in the interaction network. This enables the user to get a quick overview of the potential effects of the chemical on its interaction partners. For each organism, STITCH provides a global network; however, not all proteins have the same pattern of spatial expression. Therefore, only a certain subset of interactions can occur simultaneously.
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Includes information on 5153 putative drug–target pairs for 150 human pathogens derived from available drug–target crystallographic complexes. The TIPs database has been developed with the aim of facilitating the identification of new therapeutic targets in organisms responsible for human infections. All entries are thoroughly annotated with both sequence and functional information. The database can be queried by organism name, protein family or function. The query returns a sortable table providing information about both known and predicted drug–target pairs and links to visualize specific information on the drug(s) physicochemical properties, structure, indication and side effects, the target(s) and to visually analyse or download their 3D complexes.
Contains a comprehensive collection of approved drugs in Japan, USA and Europe unified based on chemical structures and/or chemical components. KEGG DRUG is a database which contains information about molecular networks, such as targets, metabolizing enzymes and drug–drug interactions. All the marketed drugs in Japan, the prescription drugs but also the over-the-counter (OTC) drugs, are represented in the database, including crude drugs and Traditional Chinese Medicine (TCM) drugs.
Integrates drug-related information associated with medical indications, adverse drug effects, drug metabolism, pathways and Gene Ontology (GO) terms for target proteins. At present, the updated database contains >6,000 target proteins, which are annotated with >330,000 relations to 196,000 compounds (including approved drugs); the vast majority of interactions include binding affinities and pointers to the respective literature sources. The user interface provides tools for drug screening and target similarity inclusion. A 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 proteins within a certain affinity range.
A comprehensive knowledgebase for drug-target relationships related to cancer as well as for supporting information or experimental data. CancerResource contains about 91 000 drug-target relations, more than 2000 cancer cell lines and drug sensitivity data for about 50 000 drugs. CancerResource enables the capability of uploading external expression and mutation data and comparing them to the database's cell lines. Target genes and compounds are projected onto cancer-related pathways to get a better overview about how drug-target interactions benefit the treatment of cancer. Features like cellular fingerprints comprising of mutations, expression values and drug-sensitivity data can promote the understanding of genotype to drug sensitivity associations. Ultimately, these profiles can also be used to determine the most effective drug treatment for a cancer cell line most similar to a patient's tumor cells.
A resource for protein-chemical interactions. MATADOR differs from other resources such as DrugBank in its inclusion of as many direct and indirect interactions as we could find. In contrast, DrugBank usually contains only the main mode of interaction. The manually annotated list of direct (binding) and indirect interactions between proteins and chemicals was assembled by automated text-mining followed by manual curation. Each interaction contains links to PubMed abstracts or OMIM entries that were used to deduce the interaction.
Displays a comprehensive network for exploring the connection between angiogenesis and diseases at multilevels including protein-protein interaction, drug-target, disease-gene and signaling pathways among various cells and animal models recorded through text-mining. To enlarge the scope of the PubAngioGen application, the database also links to other common resources including STRING, DrugBank and OMIM databases, which will facilitate understanding the underlying molecular mechanisms of angiogenesis and drug development in clinical therapy.
Gathers data about drugs, their targets and associated ortholog predictions for over 640 eukaryotic species. ECOdrug is composed of two main panels: (i) the drug panel displays related information about drugs such as its target conservation in taxonomic group and species and; (ii) the drug target panel provides features including a graphic display of drug target conservation and a search functionality that can be queried by HGNC symbols, ensembl gene IDs or ensembl peptide IDs.
NetwoRx / Connecting Drugs to Networks and Phenotypes in Saccharomyces Cerevisiae
Compiles information about yeast chemogenomic screening data. NetwoRx integrates three larges chemogenomic experiments, covering nearly 6000 yeast genes and about 460 drugs. Moreover, the database includes pathways and phenotypes targeted by drugs, computes drug–drug similarity metrics for mode of action analysis and build drug–phenotype networks extracted from fours genes sets collections. Users can also query new gene lists against the entire collection of drug profiles to retrieve the drugs that target them.
Facilitates identification and prioritization of candidate targets suitable for new drug development projects. Target-Pathogen is an online resource that allows genome wide based target ranking and identification. This resource can help users to computationally apply a set of filters to obtain a short list of proteins that fulfils user predefined criteria such as protein function, metabolic role, off-targeting, structural drugg ability, essentiality and omic experiments.
PDID / Protein-Drug Interaction Database
Provides access to a comprehensive set of putative and native protein-drug interactions in the structural human proteome. The structural human proteome includes about 10,000 human and human-like (with high sequence similarity to human proteins) proteins with known 3-D structures. The database includes data for popular, FDA-approved drugs. The corresponding protein-drug interactions were generated with three predictors, and were collected from and linked with three related databases of known protein-drug interactions.
GDISC / Gene-Drug Interaction for Survival in Cancer
Provides a searchable set of survival analyses for the discovery of cancer. GDISC contains the integrative analysis on gene copy number data, drug exposure data and survival data of all 32 cancer types in The Cancer Genome Atlas (TCGA), which generated hypotheses of gene-drug interactions that may impact cancer patient survival. This resource allows biologists and clinicians to specify their cancer, drug and/or gene of interest and returns the identified interaction associated with their query. It also offers a cleaned list of drug names found in all cancer types, patient numbers analysed and other summary tablehttps://gdisc.bme.gatech.edu/ .
Offers access to drug-labeling data and facilitates their use in regulatory science, drug development, scientific research, and clinical application. FDALabel contains over 95 000 full-text Structured Product Labelings (SPLs) that include human prescription drugs and biological products, and human over-the-counter (OTC) drugs. Users can employ the database to get access to drug indications and warnings, as a pharmaceutical company for drug development, or as a researcher studying drug safety.
ExCAPE-DB / Exascale Compound Activity Prediction Engine DataBase
Provides a database established for sharing active and inactive compounds from both PubChem and ChEMBL. ExCAPE-DB is a searchable open access database that serves as a data hub for giving researchers around world easy access to a publicly available standardized chemogenomics dataset, with the data and accompanying software available under open licenses. This dataset can be used as a comprehensive benchmark set to evaluate the performance of various machine-learning algorithms in the ExCAPE project.
CSCTT / Cancer Stem Cells Therapeutic Target Database
Provides users with biological tools and the hyperlinks to various biological databases, including UniProt, Protein Data Bank (PDB), KEGG, and PubChem. The CSCTT is a database that consists of two major types of data: (i) therapeutic targets for cancer stem cells (CSCs) and (ii) therapeutic methods for CSCs. It provides users with a brief summary of protein targets and available therapeutic methods used for CSCs with documented evidence.
HCSGD / Human Cellular Senescence Gene Database
Assists users on human cellular senescence. HCSGD combines multiple online published data sources into a senescence gene annotation platform. Genes are annotated with gene ontology (GO) annotation and microRNA/drug/compound target information. This software provides features like visualization of cellular senescence gene networks, browsing annotated functional information and the recovering senescence-associated genes with a web interface.
Hosts a knowledgebase designed for drug discovery. The Integrity database contains a large collection of drugs which are annotated with information on their respective drug targets, the diseases they are associated with, and the clinical phases of the drugs. Drug targets are assigned a status in Integrity, which can be ‘Validated’, ‘Candidate’, ‘Exploratory’, or none. Validated drug targets are associated with drugs under active development in clinical phases or with launched drugs for the disease of interest. Candidate drug targets are associated with drugs that are no longer under active development for the respective disease. Exploratory drug targets are associated with drugs that are currently under biological investigation for the disease. In Integrity, drugs are not directly linked to genes. Instead, drugs are linked to internal target IDs and these targets are then linked to Entrez Gene identifiers.
MPD3 / Medicinal Plants Database for Drug Designing
Merges activities of phytochemicals from medicinal plants, their targets and literature references. MPD3 contains information about more than 5000 phytochemicals from around 1000 medicinal plants with 80 different activities, more than 900 literature references and 200 plus targets. It gives information about medicinal plants regarding classification, genus, phytochemicals, their activities, targets, literature references and offers freely ready-to-dock library to find out therapeutic capability of medicinal plants against different targets.
An integrated database and software suite for site specific targeting of transcription factors of cancer genes. Onco-Regulon combines into a single platform (i) a database of functional regulatory motifs in 937 cancer causing genes and (ii) developed a software USP (Unique Sequence Predictor) to predict unique target motifs for drug binding in a gene specific manner. We believe that Onco-Regulon will help researchers to design drugs which will bind to an exclusive site in the genome with no off-target effects, theoretically.
DrumPID / Drug-minded Protein Interaction Database
Gathers information on drugs and their protein networks including indications, protein targets and side-targets. DrumPID allows users to understand and screen compounds for their effects in protein interaction networks. It is useful for: (1) exploring potential antibiotic lead structures; (2) optimizing predictions from animal tests; and (3) exploring the chemical space around a compound together with protein interaction networks. Additionally, users can observe individual pathways or protein interactions, as well as potential targets in various organisms.
Albumin binding prediction
Predicts Human Serum Albumin (HAS) binding site of a ligand. Albumin binding prediction enables the users (i) to predict if albumin binds the query ligand, (ii) to determine the probable ligand binding site (site 1 or site 2), (iii) to select the albumin X-ray structure which is complexed with the most similar ligand and (iv) to calculate complex geometry using molecular docking calculations. It facilitates our understanding of the conformational features of ligand molecules in HSA-bound state as well as experimental displacement data by comparison of docked ligand–HSA structures with experimentally resolved complexes.
UCDB / Ulcerative Colitis Database
Catalogs the genes showing evidence in ulcerative colitis (UC) pathogenesis (UC GENE), drugs used in chemotherapy (UC DRUG), UC susceptibility single nucleotide polymorphism (SNP) loci (UC LOCUS), and microarray data (UC ANALYSIS). UCDB provides search facility for querying the database. It also contains tools for various analysis such as gene expression correlation, clustering, differential expression, and gene set enrichment analysis (GSEA).
MTLD / Multiple Target Ligand Database
A database derived from Protein Data Bank. The MTLD collects the ligands which may bind to multiple different targets that have been verified by 3D-structures. This database contains 1,732 multiple-target ligands (MTLs) which bind to 14,996 binding sites extracted from 12,759 PDB structures. It could be an extremely useful tool in the development of polypharmacological drugs. It also sheds light on the side effects of drugs through anticipation of their multiple functions and similarities in the binding sites of multiple targets.
A comprehensive drug target database for lymphatic filariasis (Lf), one of the oldest and most debilitating tropical diseases. FiloBase models and stores therapeutic targets for Lf. In addition, forty drug targets of Brugia malayi were modelled and incorporated in FiloBase. In order to supplement and make it more informative, other significant filarial information such as expressed sequence tags, potential epitopes, experimental drugs, experimental structures of nematode proteins were incorporated in FiloBase by extensive literature survey which was in demand to facilitate the drug discovery process of Lf. At present, FiloBase contains 119 potential drug targets for Lf; we hope that FiloBase will be worthwhile to expedite the process of drug discovery for the better treatment of Lf.
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