| Pharmaceutical innovation plays a key role in improving the quality of human life.But traditional drug discovery and development process suffered two bottlenecks.First,the chemical scaffolds of screenable compounds trends to saturation and the number of new chemical entity(NCE)drugs approved by FDA is decreasing year by year.Second,although drugs research and development(R&D)spending in pharma is increasing,in contrast,the success rate of drugs R&D is decreasing year by year.To remedy the defect of traditional drugs R&D method,researchers pay more attention to the existing drugs to seek new indications in pharmaceutical innovations.Some new strategies for drugs R&D based on the existing drugs include recombinant old drugs,drug repositioning,and generic drugs.Among these strategies,drug repositioning has been attracted in drugs R&D projects because it can reduce the cost and shorten the developing period.Moreover,the existing drugs are very safety due to its' clearly information of pharmacokinetic and clinical trial.Drug repositioning can be carried out by two mainly methods,namely accidental discovery and systematic prediction.To our best acknowledge,accidental discovery seems to be unstable and un-predictable,systematic prediction for the discovery of new indication of the existing drugs is the most popular approach in the field.Constructing systematic prediction models need to collect a large number of effective and relevant research data.Unfortunately,the relevant research data for the existing drugs are scattered in the published papers and/or bioinformatics databases.Besides,the amount of data is so large and casually described so as to it cannot be used directly.Researchers need to spend much time to collect and screen the required data.There are some influential databases for the existing drugs,which are not related the new indications for the old drugs.Therefore,it is necessary to collect and integrate the drug repositioning research data validated by experiment,and then build a systematic database in the field of drug repositioning.The purpose of this study is to construct a drug repositioning database(DRD)and to develop a DRD website to provide data support for drug repositioning researchers.The database is constructed based on FDA-approved small molecule drugs and withdrawn drugs.The contents of this project include the integration of drug repositioning information and the development of DRD website as follows:(1)Drug repositioning information: the new assay types of the existing drugs in target level,cell level,animal level,and drug clinical trial.(2)DRD website development module: Home,Search,Browse,Network,Download,FAQ,Contact,and Data upload.The detailed data items are stored in the DRD as follows: a total of 2,128 small molecule drugs(102 withdrawn drugs);a total of 3,775 targets for the existing drugs;a total of 972 relevant diseases;a total of 40,390 repositioning activity data records,including 34,676 data records in target level,4,011 data records in cell level,1,703 activity data in animal level,1,612 relevant pathway maps,20,000 clinical trial data,and 2,128 established drug-target-disease network.To show the usage of drug repositioning database,metformin was taken as an example.In addition to the treatment of diabetes and polycystic ovary syndrome,metformin could be used to treat a variety of malignant tumors,obesity,autoimmune diseases as well as metabolic disorders.All of these results demonstrated that the established drug repositioning database is effective and can provide deep-ideas for drug repositioning.In conclusion,we first established a drug repositioning database in the present study,including comprehensive and effective DRD data collection and integration,DRD website development,and building a series of tree-like network of drug-new targets-diseases based on repositioning targets. |
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