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Current Drug Discovery Technologies


ISSN (Print): 1570-1638
ISSN (Online): 1875-6220

Research Article

Molecular Docking, G-QSAR Studies, Synthesis and Anticancer Screening of Some New 2-Phenazinamines as Bcr-Abl Tyrosine Kinase Inhibitors

Author(s): Mayura A. Kale* and Gajanan M. Sonwane

Volume 17, Issue 2, 2020

Page: [213 - 224] Pages: 12

DOI: 10.2174/1570163815666180913122542

Price: $65


Background: The computational studies on 2-phenazinamines with their protein targets have been carried out to design compounds with potential anticancer activity. This strategy of designing compounds possessing selectivity over specific tyrosine kinase has been achieved through G-QSAR and molecular docking studies.

Methods: The objective of this research has been to design newer 2-phenazinamine derivatives as Bcr-Abl tyrosine kinase inhibitors by G-QSAR, molecular docking studies followed by wet lab studies along with evaluation of their anticancer potential. Computational chemistry was done by using VLife MDS 4.3 and Autodock 4.2 followed by wet lab experiments for synthesizing 2- phenazinamine derivatives. The chemical structures of ligands in 2D were drawn by employing Chemdraw 2D Ultra 8.0 and were converted into 3D. These were optimised by using semiempirical method called MOPAC. The protein structure was retrieved from RCSC protein data bank as PDB file. The binding interactions of protein and ligands were done by using PYMOL. The molecular properties of the designed compounds were predicted in silico by using Osiris property explorer. Later, we synthesized novel 13 2-phenazinamine derivatives by treating parent compound with various aldehydes in the presence of dicyclohexylcarbodiimide (DCC) and urea to afford 2-(2-chlorophenyl)-3-(phenazin-2-yl) thiazolidin-4-one and another series of derivatives synthesized with different aldehydes in the presence of p-toluylsulphonic acid, diphydropyridine and benzene sulfonyl chloride to afford benzenesulfonyl-N-(2-chlorobenzyl)-phenazin-2-amine. All the derivatives were tested for invitro anticancer activity on K562 human chronic myelogenous leukemia cell line by employing MTT assay method.

Results: The developed G-QSAR models were found to be statistically significant with respect to training (r2=0.8074), cross-validation (q2=0.6521), and external validation (pred_r2=0.5892). The best developed G-QSAR model suggested that the XlogP values of phenazinamine derivatives were found to be highly influential in determining biological activity. The standard drug was found to exhibit binding energy - 6.79 kcal/mol and the derivatives 5b and 6c exhibited binding energy of - 7.46 and - 8.51; respectively.

Conclusion: Compounds 5b, 6c were observed to possess good lipophilicity and were found to exhibit better activity than other compounds in the series, although less than standard doxorubicin. The synthesis of these 2-phenazinamine derivatives (5a-m) is reported to be obtained from 2,4- dinitrodiphenylamine by applying appropriate synthetic route. Compounds 5b and 6c showed better cytotoxic activity against K562 cancer cell line when compared to other compounds of the series, although less than standard doxorubicin.

Keywords: Anticancer activity, autodock 4.2, computer aided drug design, G-QSAR, K562, osiris property explorer, phena-zinamine

Graphical Abstract
Rutten LJ, Squiers L, Hesse B. Cancer related information seeking: hints from the 2003 Health Information National Trends Survey (HINTS). J Health Commun 2006; 11(Suppl. 1): 147-56.
[] [PMID: 16641080]
Vanneman M, Dranoff G. Combining immunotherapy and targeted therapies in cancer treatment. Nat Rev Cancer 2012; 12(4): 237-51.
[] [PMID: 22437869]
Testa B. QSAR: Hansch analysis and related approaches. Trends Pharmacol Sci 1995; 16: 280.
Doweyko AM. QSAR: dead or alive? J Comput Aided Mol Des 2008; 22(2): 81-9.
[] [PMID: 18189157]
de Cerqueira Lima P, Golbraikh A, Oloff S, Xiao Y, Tropsha A. Combinatorial QSAR modeling of P-glycoprotein substrates. J Chem Inf Model 2006; 46(3): 1245-54.
[] [PMID: 16711744]
Scotti L, Bezerra Mendonça Junior FJ, Magalhaes Moreira DR, da Silva MS, Pitta IR, Scotti MT. SAR, QSAR and docking of anticancer flavonoids and variants: a review. Curr Top Med Chem 2012; 12(24): 2785-809.
[] [PMID: 23368103]
Gao X, Lu Y, Xing Y, et al. A novel anticancer and antifungus phenazine derivative from a marine actinomycete BM-17. Microbiol Res 2012; 167(10): 616-22.
[] [PMID: 22494896]
Jensen PR, Mincer TJ, Williams PG, Fenical W. Marine actinomycete diversity and natural product discovery. Antonie van Leeuwenhoek 2005; 87(1): 43-8.
[] [PMID: 15726290]
Dembitsky VM, Gloriozova TA, Poroikov VV. Novel antitumor agents: marine sponge alkaloids, their synthetic analogs and derivatives. Mini Rev Med Chem 2005; 5(3): 319-36.
[] [PMID: 15777266]
Suarez-Jimenez GM, Burgos-Hernandez A, Ezquerra-Brauer JM. Bioactive peptides and depsipeptides with anticancer potential: sources from marine animals. Mar Drugs 2012; 10(5): 963-86.
[] [PMID: 22822350]
Gao X, Lu Y, Fang L, et al. Synthesis and anticancer activity of some novel 2-phenazinamine derivatives. Eur J Med Chem 2013; 69: 1-9.
[] [PMID: 23995213]
Stewart JJP. MOPAC: a semiempirical molecular orbital program. J Comput Aided Mol Des 1990; 4(1): 1-105.
[] [PMID: 2197373]
Seeliger D, de Groot BL. Ligand docking and binding site analysis with PyMOL and Autodock/Vina. J Comput Aided Mol Des 2010; 24(5): 417-22.
[] [PMID: 20401516]
Trott O, Olson AJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 2010; 31(2): 455-61.
[PMID: 19499576]
Holt PA, Chaires JB, Trent JO. Molecular docking of intercalators and groove-binders to nucleic acids using Autodock and Surflex. J Chem Inf Model 2008; 48(8): 1602-15.
[] [PMID: 18642866]
Bursulaya BD, Totrov M, Abagyan R, Brooks CL III. Comparative study of several algorithms for flexible ligand docking. J Comput Aided Mol Des 2003; 17(11): 755-63.
[] [PMID: 15072435]
Morris GM, Huey R, Olson AJ. Using AutoDock for ligand-receptor docking.Curr Protoc Bioinformatics . 2008. Chapter 8: 14.
[PMID: 19085980]
Sandeep G, Nagasree KP, Hanisha M, Kumar MM. AUDocker LE: A GUI for virtual screening with AUTODOCK Vina. BMC Res Notes 2011; 4: 445.
[] [PMID: 22026969]
Pavani P. Protein-ligand interaction studies on 2, 4, 6-trisubstituted triazine derivatives as anti-malarial DHFR agents using AutoDock. Res J Biotechnol 2008; 3: 18-23.
Namasivayam V, Günther R. pso@autodock: a fast flexible molecular docking program based on Swarm intelligence. Chem Biol Drug Des 2007; 70(6): 475-84.
[] [PMID: 17986206]
Swank-Hill P, Needham LK, Schnaar RL. Carbohydrate-specific cell adhesion directly to glycosphingolipids separated on thin-layer chromatography plates. Anal Biochem 1987; 163(1): 27-35.
[] [PMID: 3619028]
Poole CF. Instrumental Thin-Layer Chromatography.Instrumental Thin-Layer Chromatography Edition 1st (ed) Elsevier Ireland Ltd. 2014; pp. 1-654.
Layer T. Thin-Layer (Planar) Chromatography. J Chromatogr A 1956; 1: 1956-73.
Chromatography T. Thin layer chromatography. J Chromatogr A 1987; 403: 395.
Poole CF. Thin-layer chromatography: challenges and opportunities. J Chromatogr A 2003; 1000(1-2): 963-84.
[] [PMID: 12877208]
Taylor R. Interpretation of the Correlation Coefficient: A basic review. J Diagn Med Sonogr 1990; 6: 35-9.
Asuero AG, Sayago A, González AG. The Correlation Coefficient: An Overview. Crit Rev Anal Chem 2006; 36: 41-59.
Hennig C, Cooper D. Brief communication: the relation between standard error of the estimate and sample size of histomorphometric aging methods. Am J Phys Anthropol 2011; 145(4): 658-64.
[] [PMID: 21590752]
Vandaele W. Wald, likelihood ratio, and Lagrange multiplier tests as an F test. Econ Lett 1981; 8: 361-5.
Browne MW. Cross-Validation Methods. J Math Psychol 2000; 44(1): 108-32.
[] [PMID: 10733860]
Taylor R. Performance Standards for Antimicrobial Susceptibility Testing. 28th Edition. 2007; p. M100.
Grebien F, Hantschel O, Wojcik J, et al. Targeting the SH2-kinase interface in Bcr-Abl inhibits leukemogenesis. Cell 2011; 147(2): 306-19.
[] [PMID: 22000011]
Druker BJ, Talpaz M, Resta DJ, et al. Efficacy and safety of a specific inhibitor of the BCR-ABL tyrosine kinase in chronic myeloid leukemia. N Engl J Med 2001; 344(14): 1031-7.
[] [PMID: 11287972]
O’Dwyer ME, Druker BJ. STI571: an inhibitor of the BCR-ABL tyrosine kinase for the treatment of chronic myelogenous leukaemia. Lancet Oncol 2000; 1: 207-11.
[] [PMID: 11905636]
Druker BJ, Tamura S, Buchdunger E, et al. Effects of a selective inhibitor of the Abl tyrosine kinase on the growth of Bcr-Abl positive cells. Nat Med 1996; 2(5): 561-6.
[] [PMID: 8616716]
Hollas JM. Modern Spectroscopy In: J Chem Educ 4th Edition. 2005. 82: p. 43.
Gorman AM, Samali A, McGowan AJ, Cotter TG. Use of flow cytometry techniques in studying mechanisms of apoptosis in leukemic cells. Cytometry 1997; 29(2): 97-105.
[<97:AID-CYTO1>3.0.CO;2-J] [PMID: 9332815]

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