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Issue 2, 2017
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Getting SMARt in drug discovery: chemoinformatics approaches for mining structure–multiple activity relationships

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Abstract

In light of the high relevance of polypharmacology, multi-target screening is a major trend in drug discovery. As such, the increasing amount of available structure–activity data requires the application of chemoinformatic approaches to mine structure–multiple activity relationships. To this end, activity landscape methods, initially developed to explore the structure–activity relationships for compounds screened against one target, have been adapted to mine Structure–Multiple Activity Relationships (SMARt). Herein, we survey advances in the chemoinformatic approaches to retrieve SMARt from screening data sets. Case studies relevant to modern drug discovery are discussed. The methods covered in this survey are general and can be implemented to explore the SMARt of other data sets screened across multiple biologically endpoints.

Graphical abstract: Getting SMARt in drug discovery: chemoinformatics approaches for mining structure–multiple activity relationships

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Publication details

The article was received on 03 Nov 2016, accepted on 06 Dec 2016 and first published on 03 Jan 2017


Article type: Review Article
DOI: 10.1039/C6RA26230A
Citation: RSC Adv., 2017,7, 632-641
  • Open access: Creative Commons BY-NC license
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    Getting SMARt in drug discovery: chemoinformatics approaches for mining structure–multiple activity relationships

    F. I. Saldívar-González, J. J. Naveja, O. Palomino-Hernández and J. L. Medina-Franco, RSC Adv., 2017, 7, 632
    DOI: 10.1039/C6RA26230A

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