Title:QSAR, Docking and ADMET Studies of Artemisinin Derivatives for Antimalarial Activity Targeting Plasmepsin II, a Hemoglobin-Degrading Enzyme from P. falciparum
Volume: 18
Issue: 37
Author(s): Tabish Qidwai, Dharmendra K. Yadav, Feroz Khan, Sangeeta Dhawan and R. S. Bhakuni
Affiliation:
Keywords:
Artemisinin, antimalarial activity, Plasmodium falciparum, QSAR, docking, drug likeness, eADMET, toxicity risk assessment, derivatives, resistant strain.
Abstract: This work presents the development of quantitative structure activity relationship (QSAR) model to predict the antimalarial activity
of artemisinin derivatives. The structures of the molecules are represented by chemical descriptors that encode topological, geometric,
and electronic structure features. Screening through QSAR model suggested that compounds A24, A24a, A53, A54, A62 and A64
possess significant antimalarial activity. Linear model is developed by the multiple linear regression method to link structures to their reported
antimalarial activity. The correlation in terms of regression coefficient (r2) was 0.90 and prediction accuracy of model in terms of
cross validation regression coefficient (rCV2) was 0.82. This study indicates that chemical properties viz., atom count (all atoms), connectivity
index (order 1, standard), ring count (all rings), shape index (basic kappa, order 2), and solvent accessibility surface area are well
correlated with antimalarial activity. The docking study showed high binding affinity of predicted active compounds against antimalarial
target Plasmepsins (Plm-II). Further studies for oral bioavailability, ADMET and toxicity risk assessment suggest that compound A24,
A24a, A53, A54, A62 and A64 exhibits marked antimalarial activity comparable to standard antimalarial drugs. Later one of the predicted
active compound A64 was chemically synthesized, structure elucidated by NMR and in vivo tested in multidrug resistant strain of
Plasmodium yoelii nigeriensis infected mice. The experimental results obtained agreed well with the predicted values.
