Jump to main content
Jump to site search
Access to RSC content Close the message box

Continue to access RSC content when you are not at your institution. Follow our step-by-step guide.


Issue 11, 2015
Previous Article Next Article

Phenotypic side effects prediction by optimizing correlation with chemical and target profiles of drugs

Author affiliations

Abstract

Despite technological progresses and improved understanding of biological systems, discovery of novel drugs is an inefficient, arduous and expensive process. Research and development cost of drugs is unreasonably high, largely attributed to the high attrition rate of candidate drugs due to adverse drug reactions. Computational methods for accurate prediction of drug side effects, rooted in empirical data of drugs, have the potential to enhance the efficacy of the drug discovery process. Identification of features critical for specifying side effects would facilitate efficient computational procedures for their prediction. We devised a generalized ordinary canonical correlation model for prediction of drug side effects based on their chemical properties as well as their target profiles. While the former is based on 2D and 3D chemical features, the latter enumerates a systems-level property of drugs. We find that the model incorporating chemical features outperforms that incorporating target profiles. Furthermore we identified the 2D and 3D chemical properties that yield best results, thereby implying their relevance in specifying adverse drug reactions.

Graphical abstract: Phenotypic side effects prediction by optimizing correlation with chemical and target profiles of drugs

Back to tab navigation

Supplementary files

Article information


Submitted
04 May 2015
Accepted
29 Jul 2015
First published
29 Jul 2015

Mol. BioSyst., 2015,11, 2900-2906
Article type
Paper
Author version available

Phenotypic side effects prediction by optimizing correlation with chemical and target profiles of drugs

R. Kanji, A. Sharma and G. Bagler, Mol. BioSyst., 2015, 11, 2900
DOI: 10.1039/C5MB00312A

Search articles by author

Spotlight

Advertisements