2013Journal of Biomolecular Structure and DynamicsOpen access

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

Sivakumar Prasanth Kumar, Yogesh T. Jasrai, Himanshu Pandya, Rakesh Rawal

Open full text 13 citations

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.

About this research paper

What this paper is about

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.

Why it matters

OpenAlex reports 13 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available 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.

Key concepts: Pharmacophore, Quantitative structure–activity relationship, Similarity (geometry), Chemistry, Group (periodic table), Molecular descriptor, Computational biology, Stereochemistry

Related papers

Back to paper searchBrowse research topicsOriginal source
Pharmacophore-similarity-based QSAR (PS-QSAR) for group-specific biological activity predictions — Research Paper | ScholarLens