Research Article IN SILICO STUDY TO ELUCIDATE INHIBITORY EFFECT OF THIAZIDES ON PLASMEPSINS: IMPLICATIONS OF NEW ANTIMALARIAL DRUG DESIGN TARUN AGARWAL 1 , SOMYA ASTHANA 1 , PRERAK GUPTA 1 , ASIF KHURSHEED 2 * 1 Department of Biotechnology and Medical Engineering, National Institute of Technology, Rourkela, Odisha, 1 Department of Bioengineering, Integral University, Lucknow, Uttar Pradesh. Email: akhursheed12@gmail.com Received: 25 Jan 2014, Revised and Accepted: 05 Mar 2014 ABSTRACT Objective: Malaria is one of the most deadly diseases existing in the world. Malaria is caused by Plasmodium parasites. These parasites induce the degradation of human hemoglobin and utilize it as nutrition source for their growth and maturation. Plasmepsins, the aspartic proteases are involved in such degradation of hemoglobin. Currently, Plasmepsins have become an attractive target for combating malarial diseases due to their importance in the life cycle and metabolism of Plasmodium species. Methods: In the present study, Lamarckian Genetic Algorithm was applied for molecular docking using Autodock4.2 (version 1.5.6). The Plasmepsins from Plasmodium falciparum, Plasmodium vivax and Plasmodium malariae were virtually screened for their bioaffinity towards Thiazides. A total of 120 three dimensional structures of thiazides were docked onto the selected protein models. Further, the thiazides were evaluated for their molecular properties using Orisis property explorer. Results: Cyclopenthiazide (CID_2904) demonstrated better interactions with all the Plasmepsins in comparision to other thiazide derivatives.. Most of the derivatives formed hydrogen bonds with the catalytic aspartic acid residues Asp34/Asp32 or Asp214/Asp215 present in active site of Plasmepsins. Thiazides derivatives followed Lipnisky’s rule of five and did not possess any mutagenic, toxic or carcinogenic effect. Conclusion: Analyzing the binding patterns of Thiazides may provide hints for the future design of new derivatives with higher potency and specificity. Keywords: Malaria, Plasmodium, Plasmepsins, Thiazides, Molecular Docking, Autodock 4.2. INTRODUCTION Malaria is one of the most common and severe diseases that is infecting people all over the world [1-2]. The agents responsible for causing Malaria are Plasmodium falciparum, Plasmodium vivax and Plasmodium malariae [1]. These parasites convey their infection through bite of a carrier (female anopheles mosquitoes). When the parasite enters into the human body, they multiply in the liver and thereafter infects the red blood cells [3]. These parasites utilize the haemoglobin of the infected erythrocyte for their growth and development during erythrocytic cycle [4]. These parasites express a major group of aspartic acid proteases, Plasmepsins [5]. The Plasmepsins are engaged in the early stages of haemoglobin degradation, in a specialized acidic digestive vacuole [6]. Thus, they have achieved a considerable attention as a potent target for the inhibition of malarial parasitic growth. A number of drugs are present commercially to treat malaria. But lately, the emergence of drug resistant malarial parasites has gained a considerable amount of attentions. Thus, there is a huge urge for exploring the alternatives for the treatment of disease. In this regard, pre-existing drugs for other diseases can also be explored for their efficiency in the treatment of such fatal diseases. Thiazides are FDA approved drugs belonging to class of diuretics, used for treatment of hypertension and edema [7]. In the present investigation, we tried to perform In Silico analysis of the bioaffinity of the thiazides towards the Plasmepsins present in Plasmodium falciparum, Plasmodium vivax and Plasmodium malariae using AutoDock4.2 tool. MATERIALS AND METHODS Protein structure retrieval and active site predictions: The structure and sequence of Plasmepsin (along with its isoforms) present in Plasmodium falciparum, Plasmodium malariae and Plasmodium vivax were retrieved from RCSB Protein Data Bank (http://www.rcsb.org). The protein model with PDB ID: 3QS1, 1SME, 1LS5, 2ANL, 1QS8 were chosen for active site predictions and docking studies (Table 1). For molecular docking, the protein models were cleaned and optimized by removing ligand and other hetero-atoms (water, ions, etc.) using Argus Lab Software. Further, percentage homology between the Plasmepsins was analyzed using EMBL-EBI ClustalW2 Multiple sequence alignment (http://www.ebi.ac.uk/Tools/msa/clustalw2/).The active site residues in the chosen protein models were predicted using Computed Atlas of Surface Topography of proteins (CASTp) (http://stsfw.bioengr.uic.edu/castp/calculation.php). The clue of catalytic amino acids present in the active site was gained from Uniprot (http://www.uniprot.org/). Substrate selection The three dimensional chemical structures of Thiazide and its derivatives, along with commercially available anti-malarial drugs such as Mefloquine, Chloroquine and Hafloquine [8] (reference molecule) were retrieved from PubChem (http://pubchem.ncbi.nlm.nih.gov/) and DrugBank (http://www.drugbank.ca/) databases using PRODRG server [9] (http://davapc1.bioch.dundee.ac.uk/prodrg/). The optimization of ligand structures was carried out based on UFF and Steepest descent algorithm using Argus Lab software. Further, the thiazides were evaluated for their molecular properties using Orisis property explorer. Molecular Docking screening Derivatives of thiazides along with the reference ligands, were docked onto the active site of Plasmepsin proteins using AutoDock4.2 (MGL Tools), following the protocol described by Agarwal et al [10]. Docking was carried out based on standard protocol using Lamarckian Genetic Algorithm [11]. Twenty five independent docking runs were performed for each ligand. Further, protein ligand complex was visualized using UCSF chimera [12] (http://www.cgl.ucsf. edu/chimera) within 5 Ǻ region. Statistical Analysis The statistical analysis of the binding energies of the best molecules was conducted using One way ANOVA (Analysis Of Variance) under 95% confidence using Origin Software. The top five molecules showing the lowest binding energy with each of the protein model were selected for the analysis. International Journal of Pharmacy and Pharmaceutical Sciences ISSN- 0975-1491 Vol 6 Issue 2, 2014 Academic Sciences