• Vipin Kumar Institute of Pharmaceutical Sciences, Kurukshetra University, Kurukshetra 136119, India.
  • Poonam Taya Institute of Pharmaceutical Sciences, Kurukshetra University, Kurukshetra 136119, India.
  • Neetu Institute of Pharmaceutical Sciences, Kurukshetra University, Kurukshetra 136119, India.


P-glycoprotein, MDR, 3D-QSAR, Pharmacophore hypothesis, Regression coefficient, Squared predictive correlation coefficient


Objective: The present study is wrought to design the 3D QSAR models on pyrrolopyrimidines as p-glycoprotein inhibitors for the treatment of a wide variety of diseases.

Methods: A dataset comprising of 33 pyrrolopyrimidine derivatives have been divided into training set and test set. A three dimensional pharmacophore hypotheses were built from training set (24 compounds) using hydrogen bond acceptor, hydrophobic and aromatic features.

Results: The proposed model possesses high value of regression coefficient (0.9334) and was validated by using test set predictions. The squared predictive correlation coefficient of 0.985 was observed between experimental and predicted activity values of test set molecules.

Conclusion: The nature of fitness and the distance between pharmacophoric features explain the inhibitory activity of pyrollopyrimidines. The proposed pharmacophoric models possess as potential for the design of novel p-glycoprotein inhibitors.


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How to Cite

Kumar, V., P. Taya, and Neetu. “3D QSAR STUDIES ON PYRROLOPYRIMIDINES AS SELECTIVE P-GLYCOPROTEIN ANTAGONIST”. International Journal of Pharmacy and Pharmaceutical Sciences, vol. 6, no. 8, Aug. 2014, pp. 232-9, https://innovareacademics.in/journals/index.php/ijpps/article/view/2769.



Original Article(s)