QSAR, Docking and ADMET studies of Artemisinin derivatives for Antimalarial activity targeting Plasmepsin II, a hemoglobin-degrading enzyme from P. falciparum.

Current Pharmaceutical Design (Impact Factor: 3.45). 06/2012;


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 and A62 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 chemically synthesized, structure elucidated by NMR and in vivo tested in multidrug resistant strain of Plasmodium yoelii nigeriensis infected mice.

8 Reads
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Antiparasitic chemotherapy is an important issue for drug development. Traditionally, novel compounds with antiprotozoan activities have been identified by screening of compound libraries in high-throughput systems. More recently developed approaches employ target-based drug design supported by genomics and proteomics of protozoan parasites. In this chapter, the drug targets in protozoan parasites are reviewed. The gene-expression machinery has been among the first targets for antiparasitic drugs and is still under investigation as a target for novel compounds. Other targets include cytoskeletal proteins, proteins involved in intracellular signaling, membranes, and enzymes participating in intermediary metabolism. In apicomplexan parasites, the apicoplast is a suitable target for established and novel drugs. Some drugs act on multiple subcellular targets. Drugs with nitro groups generate free radicals under anaerobic growth conditions, and drugs with peroxide groups generate radicals under aerobic growth conditions, both affecting multiple cellular pathways. Mefloquine and thiazolides are presented as examples for antiprotozoan compounds with multiple (side) effects. The classic approach of drug discovery employing high-throughput physiological screenings followed by identification of drug targets has yielded the mainstream of current antiprotozoal drugs. Target-based drug design supported by genomics and proteomics of protozoan parasites has not produced any antiparasitic drug so far. The reason for this is discussed and a synthesis of both methods is proposed.
    International review of cell and molecular biology 01/2013; 301:359-401. DOI:10.1016/B978-0-12-407704-1.00007-5 · 3.42 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Due to the high mortality rate in India, the identification of novel molecules is important in the development of novel and potent anticancer drugs. Xanthones are natural constituents of plants in the families Bonnetiaceae and Clusiaceae, and comprise oxygenated heterocycles with a variety of biological activities along with an anticancer effect. To explore the anticancer compounds from xanthone derivatives, a quantitative structure activity relationship (QSAR) model was developed by the multiple linear regression method. The structure-activity relationship represented by the QSAR model yielded a high activity-descriptors relationship accuracy (84%) referred by regression coefficient (r (2)=0.84) and a high activity prediction accuracy (82%). Five molecular descriptors - dielectric energy, group count (hydroxyl), LogP (the logarithm of the partition coefficient between n-octanol and water), shape index basic (order 3), and the solvent-accessible surface area - were significantly correlated with anticancer activity. Using this QSAR model, a set of virtually designed xanthone derivatives was screened out. A molecular docking study was also carried out to predict the molecular interaction between proposed compounds and deoxyribonucleic acid (DNA) topoisomerase IIα. The pharmacokinetics parameters, such as absorption, distribution, metabolism, excretion, and toxicity, were also calculated, and later an appraisal of synthetic accessibility of organic compounds was carried out. The strategy used in this study may provide understanding in designing novel DNA topoisomerase IIα inhibitors, as well as for other cancer targets.
    Drug Design, Development and Therapy 01/2014; 8:183-95. DOI:10.2147/DDDT.S51577 · 3.03 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Malaria, the most virulent parasitic disease, has become a devastating global health issue in tropical and subtropical regions, especially in Africa where the temperature and rainfall are most suitable for the development of the causative vector. Due to the spread of multidrug resistance to the currently available antimalarial drugs including the "magic bullet" artemisinin, discovery and development of new antimalarial drugs is one of the utmost challenges. Different government and non-government chemical regulatory authorities have recommended the application of non-animal, alternative techniques and in particular, in silico, methods to provide information about the basic physicochemical properties of chemicals as well as their ecological and human health effects before they reach into the market for public use. In this aspect, application of chemometric methods along with structure-based approaches may be very helpful for the design and discovery of new antimalarial compounds. The quantitative structure-activity relationship (QSAR) along with molecular docking and pharmacophore modeling techniques plays a crucial role in the field of drug design. QSAR focuses on the chemical attributes influencing the activity and thereby allows synthesis of selective potential candidate molecules. In this communication, we have reviewed the QSAR reports along with some pharmacophore modeling and docking studies of antimalarial agents published during the year 2011 to 2014 and attempted to focus on the importance of physicochemical properties and structural features required for antimalarial activity of different chemical classes of compounds. Note that this is not an exhaustive review and all the given examples should be considered as the representative ones. The reader will gain an insight of the current status of QSAR and related in silico models developed for different classes of antimalarial compounds. This review suggests that combination of both ligand and structure-based drug designing approaches may be a promising tool for the discovery and development of new molecules with potential antimalarial activity.
    Combinatorial Chemistry & High Throughput Screening 12/2014; 18(2). DOI:10.2174/1386207318666141229125527 · 1.22 Impact Factor
Show more