Recent advances in drug repurposing using machine learning

Drug repurposing aims to find new uses for already existing and approved drugs. We now provide a brief overview of recent developments in drug repurposing using machine learning alongside other computational approaches for comparison. We also highlight several applications for cancer using kinase in...

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Bibliographic Details
Published in:Current opinion in chemical biology Vol. 65; pp. 74 - 84
Main Authors: Urbina, Fabio, Puhl, Ana C., Ekins, Sean
Format: Journal Article
Language:English
Published: England Elsevier Ltd 01.12.2021
Subjects:
Alzheimer Disease - drug therapy
Antineoplastic Agents - therapeutic use
Antiviral Agents - therapeutic use
Clemastine - pharmacology
Computational Biology - methods
COVID-19 - drug therapy
Dipyridamole - pharmacology
Drug discovery
Drug Repositioning - trends
Drug repurposing
Humans
Hydroxychloroquine - pharmacology
Lenalidomide - pharmacology
Machine Learning
Neoplasms - drug therapy
Neuroprotective Agents - therapeutic use
Piperazines - pharmacology
Piperidines - pharmacology
Protein Kinase Inhibitors - pharmacology
BACE1
Aβ
GSK3β
FDA
AD
DNN
CMap
Machine learning
Drug repurposing
Drug discovery
ISSN:1367-5931, 1879-0402, 1879-0402
Online Access:Get full text
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Summary:Drug repurposing aims to find new uses for already existing and approved drugs. We now provide a brief overview of recent developments in drug repurposing using machine learning alongside other computational approaches for comparison. We also highlight several applications for cancer using kinase inhibitors, Alzheimer’s disease as well as COVID-19. [Display omitted] •Machine learning for drug repurposing was increasing before 2020.•It has been applied to model small molecule screening data, transcriptomics and proteomics.•Computationally repurposed approved kinase inhibitors have been identified by several groups.•Computational repurposing can be used in areas of difficult drug discovery e.g. antibiotics and Alzheimer 's disease.
Bibliography:ObjectType-Article-1
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ISSN:1367-5931
1879-0402
1879-0402
DOI:10.1016/j.cbpa.2021.06.001