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J Biomol Struct Dyn. 2015;33(1):56-69. doi: 10.1080/07391102.2013.849618. Epub 2013 Nov 22.

Pharmacophore-similarity-based QSAR (PS-QSAR) for group-specific biological activity predictions.

Author information

1
a Department of Bioinformatics , Applied Botany Centre (ABC), Gujarat University , Ahmedabad 380009 , Gujarat , India.

Abstract

Recent technological breakthroughs in medicinal chemistry arena had ameliorated the perspectives of quantitative structure-activity relationship (QSAR) methods. In this direction, we developed a group-based QSAR method based on pharmacophore-similarity concept which takes into account the 2D topological pharmacophoric descriptors and predicts the group-specific biological activities. This activity prediction may assist the contribution of certain pharmacophore features encoded by respective fragments toward activity improvement and/or detrimental effects. We termed this method as pharmacophore-similarity-based QSAR (PS-QSAR) and studied the activity contribution of fragments from 3-hydroxypyridinones derivatives possessing antimalarial activities.

KEYWORDS:

2D QSAR; antimalarials; group-based QSAR; pharmacophore-similarity-based QSAR (PS-QSAR); topological pharmacophore descriptors

PMID:
24266725
DOI:
10.1080/07391102.2013.849618
[Indexed for MEDLINE]
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