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Pharmacophore-similarity-based QSAR (PS-QSAR) for group-specific biological activity predictions
Sivakumar Prasanth Kumar1, Yogesh T Jasrai, Himanshu A Pandya
1a 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.
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