MOLECULAR DOCKING STUDIES OF SOME NOVEL HYBRID TETRAOXAQUINES & DISPIROTETRAOXANES AS ANTIMALARIAL AGENTS
HTML Full TextMOLECULAR DOCKING STUDIES OF SOME NOVEL HYBRID TETRAOXAQUINES & DISPIROTETRAOXANES AS ANTIMALARIAL AGENTS
Mukesh Kumar Kumawat *1, 2 and Chetia Dipak 1
Department of Pharmaceutical Sciences *1, Dibrugarh University, Dibrugarh - 786004, Assam, India.
Anand College of Pharmacy 2, Keetham, Agra, Uttar Pradesh - 282007, India
ABSTRACT: In the present study, total fifteen compounds of 1,2,4,5-tetraoxane derivatives were docked. Two series of 1,2,4,5-tetraoxane derivatives were taken for molecular docking studies, one tetraoxaquines, a hybrid of two pharmacophores such as 4-aminoquinoline & 1,2,4,5-tetraoxane, and other dispirotetraoxanes. The docking studies were performed into the binding pocket of a falcipain-3 protein (pdb: 3bwk – hydrolase) by using the Ligand fit module within docking server. The results showed a better binding affinity of hybrid tetraoxaquines compared to dispirotetraoxanes at the active site of falcipain-3 because of very low binding energies for falcipain-3 protein (pdb: 3bwk – hydrolase). Therefore, hybrid tetraoxaquines are better Cysteine proteases (falcipains) inhibitors. They would be potent antimalarial agents. So the proposed inhibitors in the future could be more effective to treat malaria
Key words: |
Molecular Docking Studies, dispirotetraoxanes, hybrid tetraoxaquines, falcipain-3 protein, Antimalarial Agents
INTRODUCTION: Malaria is a life-threatening parasitic disease transmitted by mosquitoes. Malaria is caused by four parasite species of the genus Plasmodium within the phylum Apicomplexa, class Sporozoa and Suborder haemosporina; P. vivax, P. malariae, P. ovale and P. falciparum, the most deadly of these being P. falciparum 1, 2. Today, approximately 40% of the world's population, mostly those living in the world's poorest countries, is at risk of malaria. In India, over the past two decades, malaria incidence has been fluctuating between 2 to 3 million cases per year.
India contributes 40% of all cases outside Africa. The prevention of malaria is complicated by the spread of the antimalarial drug resistant strains of the plasmodium species 3, 4.
The severity of the disease caused by P. falciparum results primarily from its ability to modify the surface of infected red blood cells by inserting parasite proteins. The enzymes in parasite digestive vacuole (cysteine and aspartic proteinases) break down hemoglobin into amino-acids and heme. While all amino-acid contents is used for building parasite proteins, only a small portion of heme is incorporated into parasite hemoproteins; the rest of heme is detoxified (polymerized) caused by parasite enzymes. A number of drugs have been investigated for their efficacy in the treatment of malaria; however, the appearance of resistant strains of P. falciparum to some of those drugs has made necessary further investigation of new classes of compounds which might have effective action against them. Also, computational (molecular docking) and quantitative structure-activity relationship (QSAR) studies of any of those drugs have been done aiming to unravel its mechanisms of action and guidelines for the syntheses of new derivatives with improved efficiency 5.
The molecular docking simulation process allows for faster and cheaper identification of promising subsequently, in vitro test can be performed to further evaluate the screening is founded on the principle that computationally obtaining the three-dimensional structure of protein and ligand complexes is feasible. With regard to biologically inspired logarithms (BIAs), molecular docking simulation is a computational problem that may benefit from such methodologies. In molecular docking simulations, the main goal is to find the fittest solution (pose) using a fitness function (scoring function). The many docking programs currently in use are DOCK, AUTODOCK, GOLD, FLEXX, ZDOCKMCDOCK, GLIDE, GEMDOCK and MOLDOCK etc 6,7.
Cysteine proteases (falcipains), a papain-family of enzymes of Plasmodium falciparum, are responsible for haemoglobin degradation and thus necessary for its survival during asexual life cycle phase inside the human red blood cells while remaining non-functional for the human body. The falcipains (FP) comprised four peptidases- FP-1, FP-2, FP-2’ and FP-3. FP-1 was reported as not essential to the erythrocytic stage of P. falciparum. FP-2 and FP-2’ are ~96% identical; share ~68% identity with FP-3. The ratio of concentration of falcipain-II is 1.8 times higher than falcipain-III concentration in trophozoites stage. The cleaving capacity of falcipain-III is nearly twice as falcipain-II for haemoglobin. Therefore, FP-2 & FP-3 are proteins may be ideal targets for antimalarial therapy using new approaches in rational drug design.
The objective of the present work was to design novel antimalarial derivatives by generating key interaction site and receptor based pharmacophore for 1,2,4,5-tetraoxane in order to generate its derivatives leading to better inhibitors for deadly disease malaria.
MATERIALS AND METHODS:
Chemistry:
Design of ligands:
Series-A
Series-B
TABLE 1: LIST OF THE DESIGNED COMPOUNDS
TABLE 2: LIST OF THE DESIGNED COMPOUNDS
Molecular Docking Studies:
The 3D X-ray crystal structure of falcipain-3 protein (pdb: 3bwk – hydrolase) was used as the starting model for this study 8, 9. The protein was prepared, docked and the molecular dynamics simulation carried out. All computational analysis was carried out using docking server (www.dockingserver.com).
(i) Preparation of Protein:
Protein structures were ploaded rom a file or download them from the Protein Data Bank using docking server by providing the entry code or by text search. The protein chain, heteroatom and ligands were selected present in the protein pdb file that important in docking calculation in the process of protein setup. Known binding sites selected through a co-crystallized ligand. Then the center of mass of the box center was selected. These coordinates of the box center were selected. mino acid residues were selected that define the binding site. Molecular docking server calculated necessary map files for each atom type and prepares the input files for docking calculations.
(ii) Preparation of Ligand: The ligand drawn using Java applet and uploaded it. The chemical structure drawn by Marvin Sketch. A ligand uploaded in MDL MOL, PDB, or SMILES format. Various parameters were set up during the simulation such as described pH, structure optimization and partial charge calculation using molecular mechanics or semi empirical quantum chemical methods. Rotable bonds and atoms were set up automatically or modify manually. Downloaded the attached file formats including mol, pdb, mol2, and pdbqt. The ligand organized into self-defines folder. This way the ligands saved for later docking calculation.
(iii) Setup ligand protein docking calculations: A protein and a ligand selected from the library. The advanced parameters modified during the simulation, such as number of runs, number of evaluations etc.
(iv) Computational Methods: Docking calculations were carried out using Docking Server 10. The MMFF94 force field11 was used for energy minimization of ligand molecule using Docking Server. Gasteiger partial charges were added to the ligand atoms. Non-polar hydrogen atoms were merged, and rotatable bonds were defined. Docking calculations were carried out on falcipain-3 (pdb: 3bwk – hydrolase) protein model. Essential hydrogen atoms, Kollman united atom type charges, and solvation parameters were added with the aid of AutoDock tools 12. Affinity (grid) maps of 20×20×20 Å grid points and 0.375 Å spacing were generated using the Autogrid program13. AutoDock parameter set and distance dependent dielectric functions were used in the calculation of the van der Waals and the electrostatic terms, respectively. Docking simulations were performed using the Lamarckian genetic algorithm (LGA) and the Solis & Wets local search method14. Initial position, orientation, and torsions of the ligand molecules were set randomly. Each docking experiment was derived from 10 different runs that were set to terminate after a maximum of 250000 energy evaluations 15. The population size was set to 150. During the search, a translational step of 0.2 Å, and quaternion and torsion steps of 5 were applied.
RESULTS AND DISCUSSION:
1,2,4,5-tetraoxanes were proved to inhibit the growth of the malaria parasite via inhibition of falcipains, which considered as a critical step in the survival of the parasite. Hence, it was worthwhile to perform the docking study of targeted 1,2,4,5-tetraoxane derivatives developed in the present study with the falcipain-3 binding pocket residues. The present study was carried out to explain the inhibitory activity of 1,2,4,5-tetraoxanes on the basis of molecular interactions established with falcipain-3. The molecular docking server was used to perform docking experiments, where top ranking posses of ligand selected according to their scoring functions. The docked complexes of ligands were visually and analyzed for hydrophobic interactions, which leads to the stability of ligands in the active site for effective inhibition.
The docking studies of the target compounds were performed into the binding pocket of an falcipain-3 (pdb: 3bwk – hydrolase). The docking results and docked conformations of the ligands in the active site were illustrated in Table3 and Fig. 1 &2, Fig. 3 & 4, Fig. 5 & 6, Fig. 7 & 8.
These results showed that the targeted molecules were snugly fitted into the active pose with considerable and diverse binding affinities towards the falcipain-3 (pdb: 3bwk – hydrolase) along with the formation of numerous hydrophobic, hydrogen, halogen, polar and other interactions.The hybrid tetraoxaquines found to have hydrophobic interactions with CYS51, HIS183, ALA184, TRP215, TYR93, ALA180, PRO181, ALA61, ALA166, TRP52 and ALA161 of S1, S1’ and S2 site of the binding pocket. Particularly, compound A10, engages ALA161, ALA166, TRP215 via hydrophobic interaction (Fig. 1 & Fig. 2) with lowest binding energy -9.46 Kcal/mol & Ki 116.72 µM. In the case of A5, hydrophobic interactions (Fig. 3 & Fig. 4) CYS51, ALA61, ALA166, TRP215, TRP215 of S1, S1’ and S2 site of the binding pocket increased but binding energy also increased as -6.11 Kcal/mol with Ki 33.28 µM.
Dispirotetraoxanes found to have hydrophobic interactions with CYS51, TYR93, ILE94, TRP52, PRO181 and ALA184 of S1, S1’ and S2 site of the binding pocket. Compound B4, engages CYS51,TRP52, TYR93, ILE94 & ALA184 via hydrophobic interaction (Fig. 5 & Fig. 6) with lowest binding energy in the series -6.68 Kcal/mol & Ki 12.62 µM. In the case of B5, hydrophobic interactions (Fig. 7 & Fig. 8) found to be very minimum only with ILE94 of S2 site of the binding pocket and binding energy highest among the series as -5.62 Kcal/mol with Ki 75.62 µM. As depicted from Table 3, these ligands effectively engages vital catalytic residues and deeply buried in the S1’, S1, S2 and S3 pocket of the active site via formation of numerous interactions.
The results disclosed that hybrid tetraoxaquines (binding energies -9.46 to -6.11 Kcal/mol) compared dispirotetraoxanes (binding energies -6.68 to -5.62 Kcal/mol) will exhibit high antimalarial activity because of very low binding energies for falcipain-3 protein (3bwk.pdb). Among all 15 ligands, all tetraoxaquines except A5 and two dispirotetraoxanes as B2, B4, showed very good interaction to protein with minimum binding energies. These results corroborate the idea that the creation of hydrophobic interactions is the main predictor for the activity of the ligands. Finally, the native ligands were allowed to dock into the active site of falcipain-3 protein (3bwk.pdb) for the validation of the docking protocol.
TABLE 3: DOCKING INTERACTION AND SCORING OF COMPOUNDS IN FALCIPAIN-3 (PDB: 3BWK) BINDING SITE#
S. N. | CompCode | Hydro-phobic | Hydrogen bonds | Halogen bond | Polar | Pi-Pi | Other | Est. Free Energy of Binding
(kcal/mol) |
Est. Inhibition Constant Ki (µM) | vdW+ Hbond+desolv Energy
(kcal/mol) |
Electrostatic Energy
(kcal/mol) |
Total Intermol. Energy
(kcal/mol) |
Inter-action Surface |
1 | A1 | None | TYR90, TYR93 | GLY92 | none | TYR93 | TYR93 | -6.51 | 16.81 | -5.65 | -1.02 | -6.67 | 672.616 |
2 | A2 | CYS51, HIS183, ALA184, TRP215 | ASN182, CYS51 | GLU243 | GLN45, HIS183 | none | GLN45, CYS51, ASN182, TRP215 | -7.69 | 2.30 | -8.91 | -0.92 | -9.83 | 824.224 |
3 | A3 | HIS183, ALA184, CYS51, TRP215 | ASN182, CYS51, ASN182
|
GLU243 | ASN182 | none | ILE94, GLN45, ASN182, HIS183 | -6.99 | 7.50 | -8.09 | -1.08 | -9.17 | 758.604 |
4 | A4 | TYR93, ALA180, PRO181, ALA184 | PRO181 | ASN182 | GLU243 | none | TYR93, SER158, PRO181, ASN182, GLU243 | -7.39 | 3.80 | -7.49 | -0.89 | -8.38 | 694.581 |
5 | A5 | CYS51, ALA61, ALA166, TRP215, TRP215 | none | LEU47 | TRP215 | TYR90 | GLN45, TYR90, ASN182, TRP215
|
-6.11 | 33.28 | -7.58 | -0.67 | -8.24 | 755.809 |
6 | A6 | None | ASN182 | SER162 | none | none | ALA161, ASN182, TRP215 | -8.86 | 323.00 | -8.45 | +0.02 | -8.42 | 789.636 |
7 | A7 | CYS51, ALA161, TRP215 | GLY92, ASN182 | GLU243 | ASN182 | TRP52 | GLN45, CYS51, ASN182, HIS183 | -9.11 | 209.41 | -9.24 | -0.03 | -9.28 | 807.97 |
8 | A8 | HIS183, TRP215 | none | ALA46 | ASN182 | none | GLN45, LEU47, ASN182,
TRP215 |
-6.94 | 8.14 | -6.59 | -0.01 | -6.59 | 629.604 |
9 | A9 | CYS51, TRP52, PRO181 | PRO181 | none | none | none | CYS51, TYR93, SER158, ASN182, GLU243 | -9.09 | 218.33 | -8.15 | -0.04 | -8.18 | 691.518 |
10 | A10 | ALA161, ALA166, TRP215 | none | ALA166 | GLN45, ASN182, TRP215 | TRP215 | GLN45, ALA166, ASN182, HIS183, TRP215 | -9.46 | 116.72 | -8.55 | +0.03 | -8.51 | 737.96 |
11 | B1 | TRP52, ILE94, PRO181, ALA184 | none | none | GLU243 | none | TYR93, SER158, PRO181, GLU243 | -6.27 | 25.49 | -6.28 | +0.01 | -6.27 | 472.071 |
12 | B2 | CYS51, TRP52, TYR93 ILE94, ALA184 | none | none | GLU243 | none | TYR93, SER158, PRO181, GLU243 | -6.62 | 14.02 | -6.64 | +0.02 | -6.62 | 510.494 |
13 | B3 | CYS51, TRP52, TYR93, ILE94, ALA184 | none | none | GLU243 | none | TYR93, SER158, PRO181, GLU243 | -6.45 | 18.62 | -6.48 | +0.02 | -6.45 | 492.619 |
14 | B4 | CYS51,TRP52, TYR93, ILE94, ALA184 | none | none | none | none | TYR93, SER158,PRO181, GLU243 | -6.68 | 12.62 | -6.66 | -0.02 | -6.68 | 510.034 |
15 | B5 | ILE94 | none | none | none | none | CYS51, SER158, GLU243 | -5.62 | 75.62 | -6.49 | +0.01 | -6.47 | 588.745 |
Where # is
Binding Site: S1, S1’, S2, S3 pockets
S1 subsite: CYS51, CYS 84, ALA61, ALA166, TYR 83,
S1’ subsite: ALA 156, ALA161, ALA180, ALA184, TYR161, TYR93
S2 subsite: PRO174, PRO181, ASN 175, GLU 236, LEU 86, ILE 87
S3 subsite: ASN 81, LYS 80
FIG. 1: DOCKED COMPLEX OF COMPOUND A10 IN THE BINDING POCKET OF FALCIPAIN-3 PROTEIN (PDB: 3BWK – HYDROLASE) IN 2D.
FIG. 2: DOCKED COMPLEX OF COMPOUND A10 IN THE BINDING POCKET OF FALCIPAIN-3 PROTEIN (PDB: 3BWK – HYDROLASE) IN 3D
FIG. 3: DOCKED COMPLEX OF COMPOUND A5 IN THE BINDING POCKET OF FALCIPAIN-3 PROTEIN (PDB: 3BWK – HYDROLASE) IN 2D
FIG. 4: DOCKED COMPLEX OF COMPOUND A5 IN THE BINDING POCKET OF FALCIPAIN-3 PROTEIN (PDB: 3BWK – HYDROLASE) IN 3D.
FIG. 5: DOCKED COMPLEX OF COMPOUND B4 IN THE BINDING POCKET OF FALCIPAIN-3 PROTEIN (PDB: 3BWK – HYDROLASE) IN 2D
FIG. 6: DOCKED COMPLEX OF COMPOUND B4 IN THE BINDING POCKET OF FALCIPAIN-3 PROTEIN (PDB: 3BWK – HYDROLASE) IN 3D.
FIG. 7: DOCKED COMPLEX OF COMPOUND B5 IN THE BINDING POCKET OF FALCIPAIN-3 PROTEIN (PDB: 3BWK – HYDROLASE) IN 2D.
FIG. 8: DOCKED COMPLEX OF COMPOUND B5 IN THE BINDING POCKET OF FALCIPAIN-3 PROTEIN (PDB: 3BWK – HYDROLASE) IN 3D
CONCLUSION: The docking studies of 15 compounds of 1,2,4,5-tetraoxane derivatives were performed into the binding pocket of a falcipain-3 protein (pdb: 3bwk – hydrolase) by using the Ligand fit module within docking server. Two series of 1,2,4,5-tetraoxane derivatives were taken for molecular docking studies, one tetraoxaquines, a hybrid of two pharmacophores such as 4-aminoquinoline & 1,2,4,5-tetraoxane, and other dispirotetraoxanes. Among all 15 ligands, all tetraoxaquines except A5 and two dispirotetraoxanes as B2, B4, showed very good interaction with falcipain-3 protein (pdb: 3bwk – hydrolase) with minimum binding energies. Additional studies to synthesize these potent compounds and evaluate their antimalarial activity may help to the researchers in their effort to make new antimalarial compounds in the future. Authors are also working in the same field and findings will published very soon.
CONFLICTS OF INTEREST: Authors have no any conflicts of interest.
REFERENCES:
- Lee MR: Plants Against Malaria Part 2: Artemisia annua (Qinghaosu or the sweet wormwood). The Journal of the Royal College of Physicians of Edinburgh 2002; 32: 300.
- Kumawat MK, Singh UP, Singh B, Prakash A and Chetia D: Synthesis and antimalarial activity evaluation of 3-(3-(7-chloroquinolin-4-ylamino)propyl)-1,3-thiazinan-4-one derivatives. Arabian Journal of Chemistry 2011; doi:10.1016/j.arabjc.2011.07.007.
- rbm.who.int/ what is malaria? Roll Back Malaria, World Health Organization, Geneva.
- De Azevedo WF and Dias R: Computational methods for calculation ligand-binding affinity. Current Drug Targets 2008; 9: 1031-1039.
- Pinheiro JC, Kiralj R and Ferreira MMC: Artemisinin derivatives with antimalarial activity against Plasmodium falciparum designed with the aid of quantum chemical and partial least squares methods. QSAR & Combinatorial Science 2003; 22: 830-842.
- Friesner RA, Banks JL, Murphy RB and Halgren TA: A new approach for rapid, accurate docking and scoring method and assessment of docking accuracy. Journal Medicinal Chemistry 2004; 10: 1739-1749.
- De Azevedo WF: Structure-based virtual screening. Current Drug Targets 2010; 11: 261-263.
- Ramjee MK, Flinn NS, Pemberton TP, Quibell M, Wang Y and Watts JP: Substrate mapping and inhibitor profiling of falcipain-2, falcipain-3 and berghepain-2: implications for peptidase anti-malarial drug discovery. Biochemical Journal 2006; 399 (1): 47-57.
- Kesharwani RK, Singh DV and Misra K: Computation based virtual screening for designing novel antimalarial drugs by targeting falcipain-III: A structure-based drug designing approach. Journal of Vector Borne Diseases 2013; 50: 93–102.
- Bikadi Z and Hazai E: Application of the PM6 semi-empirical method to modeling proteins enhances docking accuracy of AutoDock. Journal of Cheminformatics 2009; 1: 15.
- Morris GM and Goodsell DS: Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. Journal of Computational Chemistry 1998; 19 (14): 1639-1662.
- Solis FJ and Wets RJB: Minimization by Random Search Techniques. Mathematics of Operations Research 1981; 6 (1): 19-30.
- Bikadi Z, Demko L and Hazai E: Functional and structural characterization of a protein based on analysis of its hydrogen bonding network by hydrogen bonding plot. Archives of Biochemistry and Biophysics 2007; 461: 225-234.
- McDonald IK and Thornton JM: Satisfying hydrogen bonding potential in proteins. JMB 1994; 238: 777-793.
- Halgren TA: Merck molecular force field. I. Basis, form, scope, parametrization, and performance of MMFF94. Journal of Computational Chemistry 1998; 17 (5-6): 490-519.
How to cite this article:
Kumar KM and Dipak C: Molecular Docking Studies of Some Novel Hybrid Tetraoxaquines & Dispirotetraoxanes as Antimalarial Agents. Int J Pharm Sci Res 2016; 7(3): 1348-59.doi: 10.13040/IJPSR.0975-8232.7(3).1353-64
All © 2013 are reserved by International Journal of Pharmaceutical Sciences and Research. This Journal licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
Article Information
57
1348-59
897
1457
English
IJPSR
Kumawat Mukesh Kumar * and Chetia Dipak
Department of Pharmaceutical Sciences , Dibrugarh University, Dibrugarh, Assam, India.
phmukesh@gmail.com
28 August, 2015
21 February, 2016
27 February, 2016
10.13040/IJPSR.0975-8232.7(3).1348-59
01 March, 2016