Over the last decade, for the first time, substantial efforts have been directed at the development of dedicated in silico platforms for drug repurposing, including initiatives targeting cancers and conditions as diverse as cryptosporidiosis, dengue, dental caries, diabetes, herpes, lupus, malaria, tuberculosis and Covid-19 related respiratory disease. This review outlines some of the exciting advances in the specific applications of in silico approaches to the challenge of drug repurposing and focuses particularly on where these efforts have resulted in the development of generic platform technologies of broad value to researchers involved in programmatic drug repurposing work. Recent advances in molecular docking methodologies and validation approaches, and their combination with machine learning or deep learning approaches are continually enhancing the precision of repurposing efforts. The meaningful integration of better understanding of molecular mechanisms with molecular pathway data and knowledge of disease networks is widening the scope for discovery of repurposing opportunities. The power of Artificial Intelligence is being gainfully exploited to advance progress in an integrated science that extends from the sub-atomic to the whole system level. There are many promising emerging developments but there are remaining challenges to be overcome in the successful integration of the new advances in useful platforms. In conclusion, the essential component requirements for development of powerful and well optimised drug repurposing screening platforms are discussed.
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Review Article| March 14 2022
Drug repurposing in silico screening platforms
Jonathan G.L. Mullins
1Genome and Structural Bioinformatics, Institute of Life Science, Swansea University Medical School, Singleton Park, Swansea SA2 8PP, U.K.
2Moleculomics Ltd, Institute of Life Science, Swansea University Medical School, Singleton Park, Swansea SA2 8PP, U.K.
Correspondence: Jonathan G.L. Mullins (email@example.com)
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Jonathan G.L. Mullins; Drug repurposing in silico screening platforms. Biochem Soc Trans 29 April 2022; 50 (2): 747–758. doi: https://doi.org/10.1042/BST20200967
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