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Abstract
Development of resistance in the Plasmodium falciparum to Artemisinin, the most effective anti-malarial compound, threatens malaria elimination tactics. To gain more efficacious Artemisinin derivatives, QSAR modeling and docking was performed. 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. Moreover, ADMET-related descriptors have been calculated to predict the pharmacokinetic properties of the effective compounds. The correlation expressed as coefficient of determination (r2) and prediction accuracy expressed in the form of cross-validated r2 (q2) of QSAR model are found 0.9687 and 0.9586, respectively. Total 239 descriptors have been included in the study as independent variables. 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. The model was statistically robust and has good predictive power which could be employed for virtual screening of proposed anti-malarial compounds. QSAR and docking results revealed that studied compounds exhibit good anti-malarial activities and binding affinities. The outcomes could be useful for the design and development of the potent inhibitors which after optimization can be potential therapeutics for malaria.
Highlights
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 results showed that, studied compounds having minimum binding energy and have good affinity toward the active pocket, they may be considered as good inhibitor of P. falciparum proteases digesting host hemoglobin
The molecular descriptors found in quantitative structure activity relationship (QSAR) equation have encoded information about radius of gyration, mominertia Z, SssNH count and SK Average
Summary
Several millions of the people worldwide are infected by the Plasmodium falciparum, leading to death of around 1 million annually (World Malaria Report 2013). Resistance in parasite to ACTs has been reported in some south-east Asian countries (Kar and Kar 2010). As the P. falciparum resistance to Artemisinin has emerged, development of novel effective anti-malarial drugs is an urgent priority. It prompted to explore further efficient drug like compounds with new mechanisms of action. QSAR modeling became an important tool for drug design and structural optimization (Bhhatarai and Garg 2008; Xiang et al 2009; Basak et al 2010) and is widely used for virtual screening of compounds
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