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A review of computational drug repositioning: strategies, approaches, opportunities, challenges, and directions

Journal of cheminformatics, 2020-07, Vol.12 (1), p.46-46, Article 46 [Peer Reviewed Journal]

The Author(s) 2020 ;COPYRIGHT 2020 BioMed Central Ltd. ;The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1758-2946 ;EISSN: 1758-2946 ;DOI: 10.1186/s13321-020-00450-7 ;PMID: 33431024

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  • Title:
    A review of computational drug repositioning: strategies, approaches, opportunities, challenges, and directions
  • Author: Jarada, Tamer N. ; Rokne, Jon G. ; Alhajj, Reda
  • Subjects: Biomedical data ; Chemistry ; Chemistry and Materials Science ; Comparative analysis ; Computational Biology/Bioinformatics ; Computational drug repositioning ; Computer applications ; Computer Applications in Chemistry ; Data mining ; Documentation and Information in Chemistry ; Drug discovery ; Drug repositioning strategies ; Drugs ; Health aspects ; Machine learning ; Network analysis ; Respiratory system agents ; Review ; Reviews ; Theoretical and Computational Chemistry
  • Is Part Of: Journal of cheminformatics, 2020-07, Vol.12 (1), p.46-46, Article 46
  • Description: Drug repositioning is the process of identifying novel therapeutic potentials for existing drugs and discovering therapies for untreated diseases. Drug repositioning, therefore, plays an important role in optimizing the pre-clinical process of developing novel drugs by saving time and cost compared to the traditional de novo drug discovery processes. Since drug repositioning relies on data for existing drugs and diseases the enormous growth of publicly available large-scale biological, biomedical, and electronic health-related data along with the high-performance computing capabilities have accelerated the development of computational drug repositioning approaches. Multidisciplinary researchers and scientists have carried out numerous attempts, with different degrees of efficiency and success, to computationally study the potential of repositioning drugs to identify alternative drug indications. This study reviews recent advancements in the field of computational drug repositioning. First, we highlight different drug repositioning strategies and provide an overview of frequently used resources. Second, we summarize computational approaches that are extensively used in drug repositioning studies. Third, we present different computing and experimental models to validate computational methods. Fourth, we address prospective opportunities, including a few target areas. Finally, we discuss challenges and limitations encountered in computational drug repositioning and conclude with an outline of further research directions.
  • Publisher: Cham: Springer International Publishing
  • Language: English
  • Identifier: ISSN: 1758-2946
    EISSN: 1758-2946
    DOI: 10.1186/s13321-020-00450-7
    PMID: 33431024
  • Source: GFMER Free Medical Journals
    PubMed Central
    Springer Nature OA/Free Journals
    Coronavirus Research Database
    ROAD: Directory of Open Access Scholarly Resources
    ProQuest Central
    DOAJ Directory of Open Access Journals
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