Bangladesh Journal of Pharmacology Research Article Molecular docking studies on poten- tial PPAR-γ agonist from Rhizophora apiculata BJP Introduction Peroxisome proliferator-activated receptors (PPARs) are well characterized transcription factors that are members of the nuclear hormone receptor super family (Schoonjans et al., 1996). There are three subtypes of PPARs, namely, a, d, and g, that have distinct tissue distribution patterns. PPAR- is mainly present in liver, heart, and kidney (Braissant et al., 1996). PPAR-d is ubiquitously expressed, whereas PPAR is predominantly expressed in adipose tissue and to a lesser extent in spleen, cells of the hemopoietic system, liver, and skeletal muscle (Jain et al., 1998). In contrast to PPAR- , PPAR- plays an important role in the regulation of genes involved in adipocyte differentiation, lipid sto-rage, and glucose metabolism. PPAR- regulates the transcription of adipocyte fatty acid-binding protein, lipoprotein lipase, and phospho- enolpyruvate carboxy kinase in adipose tissue (Spiegel- man, 1998). Additionally, PPAR- activators upregulate the expression of acyl-CoA synthetase, fatty acid transporters, and uncoupling protein-2, and down- regulate the expression of leptin and tumor necrosis factor-a in adipocytes (Kliewer and Willson, 1998). Liver plays a pivotal role in the regulation of fatty acid and lipoprotein metabolism. Although PPAR- is abundantly expressed in liver, basal expression of PPAR- in the liver is very low (Muller, 2011). However, glycosin on the expression of PPAR- in the liver tissues of diabetic rats has not been reported. Differentiation is directly affected by PPAR ligand interactions and indirectly by transcription factors, which have complementary binding sequences on the promoter region of PPAR thereby influencing A Journal of the Bangladesh Pharmacological Society (BDPS) Bangladesh J Pharmacol 2014; 9: 298-302 Journal homepage: www.banglajol.info Abstracted/indexed in Academic Search Complete, Agroforestry Abstracts, Asia Journals Online, Bangladesh Journals Online, Biological Abstracts, BIOSIS Previews, CAB Abstracts, Current Abstracts, Directory of Open Access Journals, EMBASE/Excerpta Medica, Global Health, Google Scholar, HINARI (WHO), International Pharmaceutical Abstracts, Open J-gate, Science Citation Index Expanded, SCOPUS and Social Sciences Citation Index ISSN: 1991-0088 Abstract Peroxisome proliferator-activated receptor gamma (PPAR ) agonists are beneficial in the management of diabetes by increasing insulin sensitivity and inhibiting hepatic gluconeogenesis. The aim of the present study was to isolate and evaluate PPAR- agonist property of phytocompounds from Rhizophora apiculata using in silico approach. 30 g powdered leaves of R. apiculata extracted through acid-base method and subjected to GC-MS analysis. GC-MS results identified 18 phytocompounds, among those major peaks were 1-adamantyl-p-methylbenzalimine, clivorin, 4-butyl pyridine, 1- oxide, acetamide and p-aminodiethylaniline. In silico analysis of major compounds on human PPAR- protein was determined by AutoDock 4.0. Compared to thiazolidinediones, R. apiculata derived ligands acts as a potential agonist with binding energy -4.4, -5.3, -5.3 and -4.3 kcal/mol respec- tively. The molecular interaction of ligands was at residues of TYR473, ILE326, ARG288, HIS323 and ARG 288 to activate the action of PPAR- protein. Article Info Received: 19 May 2014 Accepted: 3 July 2014 Available Online: 20 July 2014 DOI: 10.3329/bjp.v9i3.18915 Cite this article: Selvaraj G, Kaliamurthi S, Thirug- nanasambandam R. Molecular dock- ing studies on potential PPAR- ago- nist from Rhizophora apiculata. Bangladesh J Pharmacol. 2014; 9: 298- 302. This work is licensed under a Creative Commons Attribution 3.0 License. You are free to copy, distribute and perform the work. You must attribute the work in the manner specified by the author or licensor. Molecular docking studies on potential PPAR-γ agonist from Rhizophora apiculata Gurudeeban Selvaraj, Satyavani Kaliamurthi and Ramanathan Thirugnanasambandam Centre of Advanced Study in Marine Biology, Faculty of Marine Sciences, Annamalai University, Parangipettai 608502, Tamil Nadu, India. the expression and activity of PPAR (Zieleniak et al., 2008). Currently, synthetic agonists, such as the thiazo- lidinediones (TZDs) drugs used to treat diabetes, exhibit a greater affinity for PPAR than any other binding ligand (Schneider, 2009). PPAR agonists are beneficial in the management of diabetes by increasing insulin sensitivity in skeletal muscle and inhibiting hepatic gluconeogenesis. Moreover, TZDs reduce plasma free fatty acids by PPAR activation, which enhances the ability of adipocytes to sequester lipids for storage thereby reducing the effects of lipotoxicity in non-adipose tissues (Evans et al., 2008). The increase in fat mass or adiposity within TZD users is accompanied by unfavourable side effects including hepatic toxicity, edema, and cardiovascular disease risk. TZDs have provided an invaluable source of information pertain- ing to the physiological mechanisms of PPAR (Penu- metcha and Santanam, 2012). A better understanding of PPAR ligand interactions is warranted considering the role of PPAR in adipogenesis. Based on these issues the present study aimed to evaluate R.apiculata derived phytocompounds alkaloid on antagonist effect of PPAR by in silico methods. Materials and Methods Plant material: Matured leaves of Rhizophora apiculata were collected from Kodiyampalayam coastal village, Nagapattinam district, Tamil Nadu (Southeast coast of India) during the month of January 2010 and authentic- cated in the herbarium maintained at Centre of Advanced Study in Marine Biology, Annamalai University, India (Voucher No. AUCASMB10/2012). The leaves were washed, shade dried, powdered and stored at air-tight bottles in refrigerator for further experiment. Extraction: One gram sample of plant dried powder of R. apiculata in 10 mL of 40% (v/v) methanol containing 0.1% (v/v) 1N HCl with a Ten Broeck homogenizer. The homogenate was centrifuged at 5000 × g for 3 min and filtered through Whatman No. 2 filter paper in a Buchner funnel. Each sample was diluted four-fold and filtered through a 0.45 pm Millipore filter prior to auto- matic injection. All quantitative determinations were made with duplicate injections and comparisons with authentic standards run intermittently with the un- known samples (James and Denise, 1981). GC-MS analysis : The residue will be then diluted in an appropriate volume of dichloromethane and analyzed by GC-MS. Total alkaloids will be determined by Shimadzu QP-5000 GC/MS instrument equipped with an AOC20i auto sampler (Shimadzu) and a 30 m x 0.25 mm, 0.25 μm, AT-1 ms capillary column (Supelco, Italy). The temperature program will be on 150°C for 5 min, from 150 to 300°C at 5°C/min, then 300°C for 15 min. Analyses will be performed in split mode (split ratio 1:25), the injection volume will be 1 μL, the injection temperature 250°C, the interface temperature 300°C, the acquisition from m/z 50 to 450. The source operated in EI mode at 70eV. Each analysis will be repeated at least four times. Identification of phytocompounds: Identification will be performed by comparisons of RT and mass spectra with Bangladesh J Pharmacol 2014; 9: 298-302 299 Table I Chemical composition of R. apiculata identification using GCMS Peak no. Compounds %Area Retention time (min) Molecular formula 1 N-1-Adamantyl-p-methylbenzalimine 5.0 40.0 C22H24N2O2 2 m-Acetotoluide 4.1 38.4 C9H11NO 3 4-Butylpyridine 1 oxide 2.1 37.8 C9H13NO 4 p-Amino diethylaniline 1.6 43.2 C10H16N2 5 Clivorine 1.7 33.6 C21H28NO7 6 2-Propen-1-one, 3-(4-nitrophenyl)- 0.7 35.0 C15H11NO3 7 Cyclohexanone, 4-(1,1-dimethylethy) 0.9 28.5 C10H18O 8 3-Buten-2-one, 4-(2,6,6-trimethyl-) 2.4 34.1 C13H20O 9 Acetic acid, 17-(1-hydroxy-1-methy) 2.1 35.2 C2H4O2 10 1,6-Octadien-3-ol, 3,7-dimethyl- 3.5 27.8 C10H18O 11 alpha-Ketostearic acid 1.9 34.6 C18H34O3 12 Cyclopropanecarboxylc acid 1.4 42.3 C3H5CO2H 13 1-Adamantyl m-tolyloxyacetate 1.4 35.5 C19H24O3 14 Naphthalene, 2-methoxy- 3.3 36.1 C11H10O 15 2(4H)-Benzofuranone, 5,6,7,7a-tetr 5.3 38.9 C11H16O2 16 Silane, triethyl 2.1 39.1 C9H9F5Si 17 Diethyl phthalate 12.7 39.4 C12H14O4 18 Benzene, 1-(1,1-dimethylethoxy)4- 5.5 41.1 C11H16O authentic samples. Quantitative data were obtained by electronic integration of the TIC peak areas with the use of the internal standard and based on the mass spectral data present in the NIST library. Molecular modelling: The sequence of Peroxisome Proli- ferators Activated Receptor gamma (PPAR- ) protein was retrieved from Swiss-Prot database. The template was obtained and the 3D structure was validated through SAVES. Active site residues were identified using PDB Sum. Preparation and retrieval of ligands: The molecular weight, number of hydrogen donor and acceptors and 3D structure of 1-adamantyl-p-methylbenzalimine, clivorin, 4-butyl pyridine, acetamide, p-aminodiethyl- aniline was retrieved from PubChem (Table I). The pdb structure of these compounds was converted by Open Babel. Molecular docking: Docking analysis was carried out for the modelled PPAR- with the selected phytoligands using AutoDock 4.0. The precalculated grid maps, one for each atom type present in the flexible molecules being docked and its stores the potential energy arising from the interaction with rigid macromolecules. The grid box size was set at 60, 60 and 60 A° (x, y, and z) to include all the amino acid residues. The spacing bet- ween grid points was 0.45 angstroms. The Lamarckian Genetic Algorithm (LGA) 23 was chosen search for the best conformers. Maximum of 10 conformers was considered to the docking process. The population size was set to 150 and the individuals were initialized randomly. AutoDock was compiled and run under Windows XP operating system. AutoDock results were analyzed to study the interactions and the binding energy of the docked structure. The experiments runs were performed in Intel CORETM i5, 64 bit Operating System and 4GB RAM in Lenovo Win 7 PC. Results and Discussion GC-MS analysis results revealed that alkaloid rich fraction (ARF-RA) of R.apiculata was identified 18 bio- active compounds. Among the 18 compounds, 6 com- pounds are alkaloid derivatives, 12 compounds are higher alkanes and few of acids/terpenes. The spectra compounds matched those in the NIST library with retention time, peak area and molecular formula (Table II). Earlier reports, Rhizophora sp. showed the presence of glycosin alkaloids and other phenolic compounds using GC-MS (Gurudeeban, 2013). In the present study observed six alkaloid derivatives and twelve alkane and terpene derivatives. Accordingly, acetamide has been reported to possess centrally acting promising antihypertensive agent (Scholtysik et al., 1975). 1-[a-(1- Adamantyl) benzyl idene] thio major alkaloid derivative also reported in Excoecaria agallocha that have cytotoxic effect in HepG2 cell line (Satyavani et al., 2014). It is clearly indicates that the mangroves are rich 300 Bangladesh J Pharmacol 2014; 9: 298-303 Table II Structure of major alkaloid derivatives from R. apiculata SL. no. Ligand Hydrogen donor / Acceptor Molecular weight (g/mol) Log P 1 N-1-Adamantyl-p-methylbenzalimine 0/1 253.38 4.5 2 Clivorine 1/7 406.45 0.9 3 4-Butyl pyridine, 1-oxide 0/1 151.20 1.7 4 Acetamide, N-(4-methylphenyl)- 1/1 149.18 1.7 5 p-Aminodiethylaniline 1/2 164.24 2.2 6 Thiazolidinediones 1/3 117.13 0.1 Table III Molecular interactions of phytocompounds on PPAR-γ Ligand No. of H bonds Hydrogen bond donor Length of hydrogen bond (A) Binding energy Cluster RMSD Reference RMSD Acetamide, N- (4-methylphenyl)- 2 ILE326 ARG288 2.038 2.116 -5.29 0.0 32.78 4-Butyl pyridine, 1-oxide 1 HIS323 2.011 -5.18 0.32 41.9 Clivorine 1 ARG288 1.994 -4.27 0.89 35.0 p-Aminodiethylaniline 1 TYR473 2.052 -4.41 0.7 42.67 Thiazolidinediones 4 TYR473 SER289 HIS449 HIS323 2.117 2.101 2.116 1.835 -4.28 0.21 42.73 N-1-Adamantyl-p- methylbenzalimine No interaction sources of phenolic compounds and alkaloids. The phthalate ester widely used to manufacture rubber products and the ingredients are safe for topical application in cosmetics. Prabhu et al. (2012) reported the presence of 1,2 diazole pyrazole alkaloids from methanolic extracts of R. apiculata and it used for wider medicinal activities. It refers to both the class of simple aromatic ring organic compounds that is characterized by a ring structure of 3 carbon atoms and 2 nitrogen atoms that are in adjacent positions and also to the unsubstituted parent compound. Moreover, the high presence of bioactive compound in mangrove plant R. apiculata extract added advantage as natural source (Vinod Prabhu et al., 2012). The alkaloid-rich extract of Rhizophora mucronata contains major alkaloids viz., ajmalicine, vindoline, catharanthine, and serpentine have significant antimicrobial potential against human pathogens (Gurudeeban et al., 2013). The modelled PPAR- structure was validated using Bangladesh J Pharmacol 2014; 9: 298-302 301 Table IV TOPKAT toxicity level Compound ID TOPKAT rat male NTP probability TOPKAT rat male NTP enrichment WOE proba- bility WOE enrich- ment WOR score Rat oral LD50 (g/kg body weight) Rat inhala- tional LC50 (mg/m3/h) CD10097348 0.5 0.9 0.3 0.6 -7.4 7.4 4.0 CD10374166 0.5 0.9 0.5 1.0 -0.4 0.7 5.2 CD11106591 0.2 0.4 0.4 0.8 -4.1 5.3 4.5 CD75952907 0.3 0.6 0.3 0.6 -6.6 3.6 9.9 CD76675709 0.4 0.8 0.5 0.9 -1.8 0.8 2.6 CD96875226 0.4 0.7 0.4 0.7 -5.3 17.9 23.7 Figure 1: Molecular interaction of PPAR- with R. apiculata derived ligands. (A) Secondary structure of PPAR- ; (B) Interaction with acetamide, N-(4-methylphenyl)-; (C) Interaction with 4-butyl pyridine, 1-oxide; (D) Interaction with clivorine; (E) Interaction with p-aminodiethylaniline; (F) Interaction with thiazolidinediones; Green balls indicates hydrogen bonds A B C D E F Author Info Gurudeeban Selvaraj (Principal contact) e-mail: gurudeeb99@gmail.com Procheck and from the Ramachandran plot it was inferred that the modelled protein contain 80.3% of amino acid residues in the most favoured region, 5.2% in additional allowed region, 1.8% in general allowed region and only 2.7% of amino acid residues in disallowed region. As the RMSD value is lower than 2.0 and more than 80% of the residues are in most favored region, the modeled structure can be considered to be a good one. The active site residues of the modelled protein obtained using PBD Sum are HIS323, CYS285, BRL503, MET364, LEU330, GLY284, TYR327, HIS449, LEU453, SER289, TYR473, PHE282, LEU469, TYR327 and ILE 326. Molecular docking studies were performed for modeled PPAR- protein with the commercial inhibitor Thiazolidinediones and the selected phytocompounds (Table III). The results were analyzed based on the interaction of H-bonds, interacting residues and binding energy. The better interaction was selected by figuring out the minimum binding energy. The predictions results of all phytoligands were analyzed. The results indicated all the five compounds showed interaction with PPAR- protein than the commercial drug TDZ (Figure 1). Among the five compounds, 4- butyl pyridine, 1-oxide gave the best interaction with the amino acid residues (HIS323) of PPAR- protein with lowest energy level (-5.1 Kcal/mol) on comparison with the drugs and TDZ showed lowest interaction (-4.3 Kcal/mol) with the modelled protein. The present study concluded that four phyto- compounds could be the agonist potential to activate PPAR . The phytocompounds of R. apiculata indicated a better docking simulation and interaction than the existing commercial drug thiazolidinediones. Acknowledgements The authors are grateful to the authorities of Annamalai University, Parangipettai, Tamil Nadu and University Grants Commission, New Delhi, India for providing all support during the study period. References Braissant O, Foufellie F, Scotto C, Dauca M, Wahli W. Differ- ential expression of peroxisome proliferator-activated recep- tors (PPARs): Tissue distribution of PPAR- , - and - in the adult rat. Endocrinology 1996; 137: 354–66. 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