Searching across hundreds of databases
Mining high-throughput screening (HTS) assays is key for enhancing decisions in the area of drug repositioning and drug discovery. However, many challenges are encountered in the process of developing suitable and accurate methods for extracting useful information from these assays. Virtual screening and a wide variety of databases, methods and solutions proposed to-date, did not completely overcome these challenges. This study is based on a multi-label classification (MLC) technique for modeling correlations between several HTS assays, meaning that a single prediction represents a subset of assigned correlated labels instead of one label. Thus, the devised method provides an increased probability for more accurate predictions of compounds that were not tested in particular assays.
Pubmed ID: 27895719 RIS Download
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Bioinformatics and cheminformatics database that combines detailed drug (i.e. chemical, pharmacological and pharmaceutical) data with comprehensive drug target (i.e. sequence, structure, and pathway) information.
View all literature mentionsCollection of information about chemical structures and biological properties of small molecules and siRNA reagents hosted by the National Center for Biotechnology Information (NCBI).
View all literature mentionsHigh throughput screening services to identify small molecules that can be optimized as chemical probes to study the functions of genes, cells, and biochemical pathways, along with medicinal chemistry and informatics. This will lead to new ways to explore the functions of genes and signaling pathways in health and disease. The NIH Molecular Libraries Initiative NIH is designed to discover small molecules that interact with biologically important proteins and pathways and to provide open access to the bioassay and chemical data generated by its research centers. This will lead to new ways to explore the functions of genes and signaling pathways in health and disease. As these HTS Technologies were not previously available to the public sector, many investigators may not be familiar with the components and requirements of high throughput screening. A key challenge is to identify small molecules effective at modulating a given biological process or disease state. The Molecular Libraries Roadmap, through one of its components, the Molecular Libraries Probe Production Centers Network (MLPCN), offers biomedical researchers access to the large-scale screening capacity, along with medicinal chemistry and informatics necessary to identify chemical probes to study the functions of genes, cells, and biochemical pathways. This will lead to new ways to explore the functions of genes and signaling pathways in health and disease. There are two kinds of data that are available to the scientific community through a dedicated database: Chemical Compounds and Bioassay Results (NCBI). Various types of data, including informative records on substances, compound structures, and biologically active properties of small molecules are housed respectively within PubChem''''s three primary databases: PCSubstance, PCCompound, and PCBioAssay. To date, PubChem contains over 11 million substance records, details about approximately 5.5 million unique compound structures with links to bioassay descriptions, relevant literature, references, and assay data points and over 250 bioassays, a good percentage of which were contributed by the pilot phase of the MLP. The deposition will continue during the current MLPCN phase. NIH anticipates that these projects will also facilitate the development of new drugs, by providing early stage chemical compounds that will enable researchers in the public and private sectors to validate new drug targets, which could then move into the drug-development pipeline. This is particularly true for rare diseases, which may not be attractive for development by the private sector. Funding opportunities are available through the site.
View all literature mentionsOntology (http://www.bioassayontology.org/bao_gpcr) that describes pharmacology, biochemistry and physiology of these important and therapeutically promising class of academic and pharmaceutical research targets. Incorporation and comparison of various small molecule screening data sets, such as those deposited in PubChem, ChEMBL, KEGG, PDSP, and/or IUPHAR databases, requires a formalized electronic organization system. In order to bridge the gap between the overflow of HTS data and the bottleneck of integrated analysis tools, herein, we provide the first comprehensive GPCR ontology. The development and utility of GPCR ontology was based on previously developed BioAssay Ontology (BAO). The GPCR ontology contains information about biochemical, pharmacological, and functional properties of individual GPCRs as well as GPCR-selective ligands inclusive of their HTS screening results and other records. This provides the first all-inclusive GPCR ontology with all available data to model the relationship between the GPCR binding sites and their physiologic and pharmacologic role in physiology via small molecule chemical structures. We developed this system using emerging semantic technologies, by leveraging existing and descriptive domain level ontologies.
View all literature mentionsData and information collection and repository for biological activities of small molecules and small interfering RNAs (siRNAs) hosted by the US National Institutes of Health (NIH). Used to select and summarize the bioactivities of tested substances.
View all literature mentionsThe SciCrunch Infrastructure was developed as a cooperative data platform to be used by diverse communities in making data more FAIR.
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