Design of efficient computational workflows for in silico drug repurposing. Issue 2 (February 2017)

• Record Type: Journal Article
• Authors: Vanhaelen, Quentin; Mamoshina, Polina; Aliper, Alexander M.; Artemov, Artem; Lezhnina, Ksenia; Ozerov, Ivan; Labat, Ivan; Zhavoronkov, Alex
• Is Part Of: Drug discovery today. Volume 22:Issue 2(2017)
• Page Start: 210
• Page End: 222
• Publication Date: 2017-02
• Subjects: Drugs -- Design -- Periodicals; Drugs -- Research -- Periodicals; 615.1
• DOI: 10.1016/j.drudis.2016.09.019
• Languages: English
• ISSNs: 1359-6446

Abstract

Highlights: Conceptual foundations of the drug repurposing paradigm are reviewed. Description of the technological trends behind the raise of in silico repurposing. The different classes of in silico repurposing algorithms are reviewed. A modular description of the key steps of the in silico repurposing is presented. 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. Abstract : This review provides a comprehensive description of the conceptual foundation and computational developments in the field of in silico repurposing. Furthermore, a generic modular description for repurposing workflows is described.