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Drug Discov Today. 2017 Feb;22(2):210-222. doi: 10.1016/j.drudis.2016.09.019. Epub 2016 Sep 28.

Design of efficient computational workflows for in silico drug repurposing.

Author information

1
Insilico Medicine Inc., Johns Hopkins University, ETC, B301, MD 21218, USA. Electronic address: vanhaelen@insilicomedicine.com.
2
Insilico Medicine Inc., Johns Hopkins University, ETC, B301, MD 21218, USA.
3
BioTime Inc., 1010 Atlantic Avenue, 102, Alameda, CA 94501, USA.

Abstract

Here, we provide a comprehensive overview of the current status of in silico repurposing methods by establishing links between current technological trends, data availability and characteristics of the algorithms used in these methods. Using the case of the computational repurposing of fasudil as an alternative autophagy enhancer, we suggest a generic modular organization of a repurposing workflow. We also review 3D structure-based, similarity-based, inference-based and machine learning (ML)-based methods. We summarize the advantages and disadvantages of these methods to emphasize three current technical challenges. We finish by discussing current directions of research, including possibilities offered by new methods, such as deep learning.

PMID:
27693712
DOI:
10.1016/j.drudis.2016.09.019
[Indexed for MEDLINE]

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