Dataset Information

Therapeutic target database 2020: enriched resource for facilitating research and early development of targeted therapeutics.

ABSTRACT: Knowledge of therapeutic targets and early drug candidates is useful for improved drug discovery. In particular, information about target regulators and the patented therapeutic agents facilitates research regarding druggability, systems pharmacology, new trends, molecular landscapes, and the development of drug discovery tools. To complement other databases, we constructed the Therapeutic Target Database (TTD) with expanded information about (i) target-regulating microRNAs and transcription factors, (ii) target-interacting proteins, and (iii) patented agents and their targets (structures and experimental activity values if available), which can be conveniently retrieved and is further enriched with regulatory mechanisms or biochemical classes. We also updated the TTD with the recently released International Classification of Diseases ICD-11 codes and additional sets of successful, clinical trial, and literature-reported targets that emerged since the last update. TTD is accessible at http://bidd.nus.edu.sg/group/ttd/ttd.asp. In case of possible web connectivity issues, two mirror sites of TTD are also constructed (http://db.idrblab.org/ttd/ and http://db.idrblab.net/ttd/).

SUBMITTER: Wang Y

PROVIDER: S-EPMC7145558 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Therapeutic target database 2020: enriched resource for facilitating research and early development of targeted therapeutics.

Wang Yunxia Y Zhang Song S Li Fengcheng F Zhou Ying Y Zhang Ying Y Wang Zhengwen Z Zhang Runyuan R Zhu Jiang J Ren Yuxiang Y Tan Ying Y Qin Chu C Li Yinghong Y Li Xiaoxu X Chen Yuzong Y Zhu Feng F

Nucleic acids research 20200101 D1

Knowledge of therapeutic targets and early drug candidates is useful for improved drug discovery. In particular, information about target regulators and the patented therapeutic agents facilitates research regarding druggability, systems pharmacology, new trends, molecular landscapes, and the development of drug discovery tools. To complement other databases, we constructed the Therapeutic Target Database (TTD) with expanded information about (i) target-regulating microRNAs and transcription fac ...[more]

PMID: 31691823

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Project description:BackgroundIn France, the Ministry of Health has implemented a comprehensive program for rare diseases (RD) that includes an epidemiological program as well as the establishment of expert centers for the clinical care of patients with RD. Since 2007, most of these centers have entered the data for patients with developmental disorders into the CEMARA population-based registry, a national online data repository for all rare diseases. Through the CEMARA web portal, descriptive demographic data, clinical data, and the chronology of medical follow-up can be obtained for each center. We address the interest and ongoing challenges of this national data collection system 10 years after its implementation.MethodsSince 2007, clinicians and researchers have reported the "minimum dataset (MDS)" for each patient presenting to their expert center. We retrospectively analyzed administrative data, demographic data, care organization and diagnoses.ResultsOver 10 years, 228,243 RD patients (including healthy carriers and family members for whom experts denied any suspicion of RD) have visited an expert center. Among them, 167,361 were patients affected by a RD (median age 11 years, 54% children, 46% adults, with a balanced sex ratio), and 60,882 were unaffected relatives (median age 37 years). The majority of patients (87%) were seen no more than once a year, and 52% of visits were for a diagnostic procedure. Among the 2,869 recorded rare disorders, 1,907 (66.5%) were recorded in less than 10 patients, 802 (28%) in 10 to 100 patients, 149 (5.2%) in 100 to 1,000 patients, and 11 (0.4%) in > 1,000 patients. Overall, 45.6% of individuals had no diagnosis and 6.7% had an uncertain diagnosis. Children were mainly referred by their pediatrician (46%; n = 55,755 among the 121,136 total children referrals) and adults by a medical specialist (34%; n = 14,053 among the 41,564 total adult referrals). Given the geographical coverage of the centers, the median distance from the patient's home was 25.1 km (IQR = 6.3 km-64.2 km).ConclusionsCEMARA provides unprecedented support for epidemiological, clinical and therapeutic studies in the field of RD. Researchers can benefit from the national scope of CEMARA data, but also focus on specific diseases or patient subgroups. While this endeavor has been a major collective effort among French RD experts to gather large-scale data into a single database, it provides tremendous potential to improve patient care.

Project description:BackgroundThe use of swine in biomedical research has increased dramatically in the last decade. Diverse genomic- and proteomic databases have been developed to facilitate research using human and rodent models. Current porcine gene databases, however, lack the robust annotation to study pig models that are relevant to human studies and for comparative evaluation with rodent models. Furthermore, they contain a significant number of errors due to their primary reliance on machine-based annotation. To address these deficiencies, a comprehensive literature-based survey was conducted to identify certain selected genes that have demonstrated function in humans, mice or pigs.ResultsThe process identified 13,054 candidate human, bovine, mouse or rat genes/proteins used to select potential porcine homologs by searching multiple online sources of porcine gene information. The data in the Porcine Translational Research Database (( http://www.ars.usda.gov/Services/docs.htm?docid=6065 ) is supported by >5800 references, and contains 65 data fields for each entry, including >9700 full length (5' and 3') unambiguous pig sequences, >2400 real time PCR assays and reactivity information on >1700 antibodies. It also contains gene and/or protein expression data for >2200 genes and identifies and corrects 8187 errors (gene duplications artifacts, mis-assemblies, mis-annotations, and incorrect species assignments) for 5337 porcine genes.ConclusionsThis database is the largest manually curated database for any single veterinary species and is unique among porcine gene databases in regard to linking gene expression to gene function, identifying related gene pathways, and connecting data with other porcine gene databases. This database provides the first comprehensive description of three major Super-families or functionally related groups of proteins (Cluster of Differentiation (CD) Marker genes, Solute Carrier Superfamily, ATP binding Cassette Superfamily), and a comparative description of porcine microRNAs.

Dataset Information

Therapeutic target database 2020: enriched resource for facilitating research and early development of targeted therapeutics.

Publications

Therapeutic target database 2020: enriched resource for facilitating research and early development of targeted therapeutics.

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