Abstract:
:Molecular modelling studies were performed to identify the essential structural requirements of quinoline-based derivatives for improving their antimalarial activity. The developed CoMFA, CoMSIA and HQSAR models for a training set comprising 37 derivatives showed good statistical significance in terms of internal cross validation (q(2)) 0.70, 0.69 and 0.80 and non-cross validation (r(2)) 0.80, 0.79 and 0.80. Also, the predicted r(2) values (r(2)pred) of 0.63, 0.61 and 0.72 for a test set consisting of 12 compounds suggested significant predicting ability of the models. Structural features were correlated in terms of steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor interactions. Furthermore, the bioactive conformation was explored and explained by docking compounds #28, 32 and 40 into the active binding site of lactate dehydrogenase of Plasmodium falciparum. The QSAR models, contour map and docking binding affinity obtained could be successfully utilized as a guiding tool for the design and discovery of novel quinoline-based derivatives with potent antimalarial activity.
journal_name
SAR QSAR Environ Resjournal_title
SAR and QSAR in environmental researchauthors
Sharma R,Patil S,Maurya Pdoi
10.1080/1062936X.2013.875484subject
Has Abstractpub_date
2014-01-01 00:00:00pages
189-203issue
3eissn
1062-936Xissn
1029-046Xjournal_volume
25pub_type
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