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

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

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Antimalarials / chemistry*
  • Antimalarials / pharmacology
  • Chemistry, Pharmaceutical / methods
  • Drug Design*
  • Iron Chelating Agents / chemistry
  • Iron Chelating Agents / pharmacology
  • Models, Chemical
  • Molecular Structure
  • Plasmodium falciparum / drug effects
  • Plasmodium falciparum / growth & development
  • Pyridones / chemistry*
  • Pyridones / pharmacology
  • Quantitative Structure-Activity Relationship*

Substances

  • Antimalarials
  • Iron Chelating Agents
  • Pyridones
  • 3-hydroxy-4-pyridone