Most of the therapeutic approaches are Artemisinin based combination therapies (ACTs) and chloroquine (Fidock et al. Several millions of the people worldwide are infected by the Plasmodium falciparum, leading to death of around 1 million annually (World Malaria Report 2013). The outcomes could be useful for the design and development of the potent inhibitors which after optimization can be potential therapeutics for malaria. QSAR and docking results revealed that studied compounds exhibit good anti-malarial activities and binding affinities. The model was statistically robust and has good predictive power which could be employed for virtual screening of proposed anti-malarial compounds. The four chemical descriptors, namely radius of gyration, mominertia Z, SssNH count and SK Average have been found to be well correlated with anti-malarial activities. Total 239 descriptors have been included in the study as independent variables. The correlation expressed as coefficient of determination (r 2) and prediction accuracy expressed in the form of cross-validated r 2 (q 2) of QSAR model are found 0.9687 and 0.9586, respectively. Moreover, ADMET-related descriptors have been calculated to predict the pharmacokinetic properties of the effective compounds. In the present study, 2D-QSAR model and molecular docking were used to evaluate the Artemisinin compounds and to reveal their binding modes and structural basis of inhibitory activity. To gain more efficacious Artemisinin derivatives, QSAR modeling and docking was performed. Development of resistance in the Plasmodium falciparum to Artemisinin, the most effective anti-malarial compound, threatens malaria elimination tactics.
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