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Current Chemical Biology

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ISSN (Print): 2212-7968
ISSN (Online): 1872-3136

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Research Article

Investigating Structural Requirements of Some Pyrimidine-linked Benzimidazole Derivatives as Anticancer Agents Against MCF-7 Cancerous Cell Line Through the use of 2D and 3D QSARs

Author(s): Kale Mayura*, Khan Sharuk and Hature Jyoti

Volume 13, Issue 3, 2019

Page: [232 - 249] Pages: 18

DOI: 10.2174/2212796813666190207144407

Price: $65

Abstract

Background: Cancer is an extremely fast, unrestrained and pathological propagation of cells. Yet there is no cancer treatment that is 100% efficient against scattered cancer. Heterocycles have been considered as a boon to treat several cancers of which pyrimidine is a core nucleus and holds an important place in cancer chemotherapy which is reflected in the use of drugs such as 5-fluorouracil, erlotinib, gefitinib and caneratinib. Also, many good antitumor active agents possess benzimidazoleas its core nucleus.

Objective: To design novel pyrimidine-linked benzimidazoles and to explore their structural requirements related to anticancer potential.

Methods: 2D and 3D Quantitative structure–activity relationship (QSAR) studies were carried out on a series of already synthesized 27 pyrimidine-benzimidazole derivatives.

Results: Statistically significant and optimum 2D-QSAR model was developed by using step-wise variable multiple linear regression method, yielding correlation coefficient r2 = 0.89, cross-validated squared correlation coefficient q2 = 0.79 and external predictive ability of pred_r2 = 0.73 Best 3D-QSAR model was developed by employing molecular field analysis using step-wise variable k-nearest neighbor method which showed good correlative and predictive abilities in terms of q2 =0.77 and pred_r2= 0.93.

Conclusion: These 2D and 3D models were found to give dependable indications which helped to optimize the pyrimidine-benzimidazole derivatives of the data set. The data yielded by 2D- QSAR and 3D-QSAR models will aid in giving better perceptions about structural requirements for developing newer anticancer agents.

Keywords: MCF-7, 2D-QSAR, 3D-QSAR, MLR, kNN-MFA, anticancer activity.

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[1]
Mullen LMA, Duchowicz PR, Castro EA. QSAR Treatment on a new class of triphenylmethyl-containing compounds as potent anticancer agents. Chemom Intell Lab Syst 2011; 107(2): 269-75.
[http://dx.doi.org/10.1016/j.chemolab.2011.04.011]
[2]
Nepali K, Sharma S, Sharma M, Bedi PMS, Dhar KL. Rational approaches, design strategies, structure activity relationship and mechanistic insights for anticancer hybrids. Eur J Med Chem 2014; 77: 422-87.
[http://dx.doi.org/10.1016/j.ejmech.2014.03.018] [PMID: 24685980]
[3]
Aziz MA, Serya RAT, Lasheen DS, Abouzid KAM. Furo[2,3-D]pyrimidine based derivatives as kinase inhibitors and anticancer agents. Futur J Pharm Sci 2016; 1(2): 33-41.
[http://dx.doi.org/10.1016/j.fjps.2015.12.001]
[4]
Gokhale N, Dalimba U, Kumsi M. Facile synthesis of indole-pyrimidine hybrids and evaluation of their anticancer and antimicrobial activity. J Saudi Chem Soc 2015.
[5]
Singla P, Luxami V, Singh R, Tandon V, Paul K. Novel pyrazolo[3,4-D]pyrimidine with 4-(1H-Benzimidazol-2-Yl)-Phenylamine as broad spectrum anticancer agents: Synthesis, cell based assay, topoisomerase inhibition, DNA intercalation and bovine serum albumin studies. Eur J Med Chem 2017; 126: 24-35.
[http://dx.doi.org/10.1016/j.ejmech.2016.09.093] [PMID: 27744184]
[6]
Xiao Q, Qu R, Gao D, et al. Discovery of 5- (Methylthio) pyrimidine derivatives as L858R / T790M mutant selective epidermal growth factor receptor (EGFR) Inhibitors. Bioorg Med Chem 2016.
[http://dx.doi.org/10.1016/j.bmc.2016.04.032]
[7]
Shao K-P, Zhang X-Y, Chen P-J, et al. Synthesis and biological evaluation of novel pyrimidine-benzimidazol hybrids as potential anticancer agents. Bioorg Med Chem Lett 2014; 24(16): 3877-81.
[http://dx.doi.org/10.1016/j.bmcl.2014.06.050] [PMID: 25001482]
[8]
Akhtar W, Khan MF, Verma G, et al. Therapeutic evolution of benzimidazole derivatives in the last quinquennial period. Eur J Med Chem 2017; 126: 705-53.
[http://dx.doi.org/10.1016/j.ejmech.2016.12.010] [PMID: 27951484]
[9]
Bansal Y, Silakari O. The therapeutic journey of benzimidazoles: A review. Bioorg Med Chem 2012; 20(21): 6208-36.
[http://dx.doi.org/10.1016/j.bmc.2012.09.013] [PMID: 23031649]
[10]
Neochoritis CG, Zarganes-Tzitzikas T, Tsoleridis CA, et al. One-pot microwave assisted synthesis under green chemistry conditions, antioxidant screening, and cytotoxicity assessments of benzimidazole Schiff bases and pyrimido[1,2-a]benzimidazol-3(4H)-ones. Eur J Med Chem 2011; 46(1): 297-306.
[http://dx.doi.org/10.1016/j.ejmech.2010.11.018] [PMID: 21146903]
[11]
Mukesh B, Rakesh K. Molecular docking : A review. Int J Res Ayurveda Pharm 2011; 2(6): 1746-51.
[12]
Nantasenamat C, Isarankura-Na-Ayudhya C, Naenna T, Prachayasittikul V. A practical overview of quantitative structure-activity relationship. EXCLI J 2009; 8: 74-88.
[13]
Sharma MC, Kohli DV. Insight into the structural requirement of substituted quinazolinone biphenyl acylsulfonamides derivatives as angiotensin II AT1 receptor antagonist: 2D and 3D QSAR approach. J Saudi Chem Soc 2014; 18(1): 35-45.
[http://dx.doi.org/10.1016/j.jscs.2011.05.011]
[14]
Ahmed SA. bdalla; de Hoog, G. S.; Stevens, D. A.; Fahal, A. H.; van de Sande, W. W. J. 3D-QSAR and Docking Studies on 4-Anilinoquinazoline and 4-Anilinoquinoline Epidermal Growth Factor Receptor (EGFR) Tyrosine Kinase Inhibitors. Med Mycol 2015; 53(3): 295-301.
[http://dx.doi.org/10.1093/mmy/myu098] [PMID: 25631481]
[15]
Chakraborti AK, Gopalakrishnan B, Sobhia ME, Malde A. 3D-QSAR studies of indole derivatives as phosphodiesterase IV inhibitors. Eur J Med Chem 2003; 38(11-12): 975-82.
[http://dx.doi.org/10.1016/j.ejmech.2003.09.001] [PMID: 14642329]
[16]
Nandi S, Bagchi MC. 3D-QSAR and molecular docking studies of 4-anilinoquinazoline derivatives: a rational approach to anticancer drug design. Mol Divers 2010; 14(1): 27-38.
[http://dx.doi.org/10.1007/s11030-009-9137-9] [PMID: 19330460]
[17]
Halgren TA. MMFF VII. Characterization of MMFF94, MMFF94s, and other widely available force fields for conformational energies and for intermolecular-interaction energies and geometries. J Comput Chem 1999; 20(7): 730-48.
[http://dx.doi.org/10.1002/(SICI)1096-987X(199905) 20:7<730:AID-JCC8>3.0.CO;2-T]
[18]
Halgren TA. Merck molecular force field. J Comput Chem 1996; 17(5-6): 490-519.
[http://dx.doi.org/10.1002/(SICI)1096-987X(199604) 17:5/6<490:AID-JCC1>3.0.CO;2-P]
[19]
Halgren TA. MMFF VI. MMFF94s option for energy minimization studies. J Comput Chem 1999; 20(7): 720-9.
[http://dx.doi.org/10.1002/(SICI)1096-987X(199905) 20:7<720:AID-JCC7>3.0.CO;2-X]
[20]
Peters T, Meyer B, Stuike-Prill R, Somorjai R, Brisson JR. A monte carlo method for conformational analysis of saccharides. Carbohydr Res 1993; 238(C): 49-73.
[http://dx.doi.org/10.1016/0008-6215(93)87005-D] [PMID: 8431939]
[21]
Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH, Teller E. Equation of state calculations by fast computing machines. J Chem Phys 1953; 21(6): 1087-92.
[http://dx.doi.org/10.1063/1.1699114]
[22]
Sharma MC, Sharma S, Sahu NK, Kohli DV. 3D QSAR kNN-MFA studies on 6-substituted benzimidazoles derivatives as nonpeptide angiotensin II receptor antagonists: A rational approach to antihypertensive agents. J Saudi Chem Soc 2013; 17(2): 167-76.
[http://dx.doi.org/10.1016/j.jscs.2011.03.005]
[23]
Wang J, Hou T, Chen L, Xu X. Conformational analysis of peptides using monte carlo simulations combined with the genetic algorithm. Chemom Intell Lab Syst 1999; 45(1-2): 347-51.
[http://dx.doi.org/10.1016/S0169-7439(98)00142-7]
[24]
Chang G, Guida WC, Still WC. An internal-coordinate monte carlo method for searching conformational space. J Am Chem Soc 1989; 111: 4379-86.
[http://dx.doi.org/10.1021/ja00194a035]
[25]
Golbraikh A, Tropsha A. Beware of q2! J Mol Graph Model 2002; 20(4): 269-76.
[http://dx.doi.org/10.1016/S1093-3263(01)00123-1] [PMID: 11858635]
[26]
Pérez C, Pastor M, Ortiz AR, Gago F. Comparative binding energy analysis of HIV-1 protease inhibitors: incorporation of solvent effects and validation as a powerful tool in receptor-based drug design. J Med Chem 1998; 41(6): 836-52.
[http://dx.doi.org/10.1021/jm970535b] [PMID: 9526559]
[27]
Tropsha A, Golbraikh A. Predictive QSAR modeling workflow, model applicability domains, and virtual screening. Curr Pharm Des 2007; 13(34): 3494-504.
[http://dx.doi.org/10.2174/138161207782794257] [PMID: 18220786]
[28]
Sharma MC, Kohli DV. A Comprehensive structure-activity analysis 2,3,5-Trisubstituted 4,5-Dihydro-4-Oxo-3H-Imidazo [4,5-c] pyridine derivatives as angiotensin II receptor antagonists: Using 2D- and 3D-QSAR approach. Med Chem Res 2013; 22(2): 588-605.
[http://dx.doi.org/10.1007/s00044-012-0040-z]
[29]
Tanneeru K, Reddy BM, Guruprasad L. Three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis and molecular docking of ATP-competitive triazine analogs of human mTOR inhibitors. Med Chem Res 2012; 21(7): 1207-17.
[http://dx.doi.org/10.1007/s00044-011-9629-x]
[30]
Jiménez Villalobos TP, Gaitán Ibarra R, Montalvo Acosta JJ. 2D, 3D-QSAR and molecular docking of 4(1H)-quinolones analogues with antimalarial activities. J Mol Graph Model 2013; 46: 105-24.
[http://dx.doi.org/10.1016/j.jmgm.2013.10.002] [PMID: 24185373]
[31]
Li J, Li S, Bai C, Liu H, Gramatica P. Structural requirements of 3-carboxyl-4(1H)-quinolones as potential antimalarials from 2D and 3D QSAR analysis. J Mol Graph Model 2013; 44: 266-77.
[http://dx.doi.org/10.1016/j.jmgm.2013.07.004] [PMID: 23911994]
[32]
Ajmani S, Jadhav K, Kulkarni SA. Three-dimensional QSAR using the k-nearest neighbor method and its interpretation. J Chem Inf Model 2006; 46(1): 24-31.
[http://dx.doi.org/10.1021/ci0501286] [PMID: 16426036]
[33]
Hawkins DM, Basak SC, Mills D. Assessing model fit by cross-validation. J Chem Inf Comput Sci 2003; 43(2): 579-86.
[http://dx.doi.org/10.1021/ci025626i] [PMID: 12653524]
[34]
Yan H, Pan X, Tan N, Fan J, Zeng G, Han H. 2D- and 3D-QSAR studies on 54 anti-tumor Rubiaceae-type cyclopeptides. Eur J Med Chem 2009; 44(9): 3425-32.
[http://dx.doi.org/10.1016/j.ejmech.2009.02.005] [PMID: 19303172]
[35]
Hirashima A, Eiraku T, Kuwano E, Eto M. Molecular design. Internet Electron J Mol Des 2003; 2: 511-26.
[36]
Gasteiger J, Marsili M. Iterative partial equalization of orbital electronegativity-a rapid access to atomic charges. Tetrahedron 1980; 36(3219): 3219-88.
[37]
Roy K, Kar S. Das R N. Statistical methods in QSAR/QSPR. In: A primer on QSAR/QSPR modeling Springer Briefs in Molecular Science. Springer, Cham. 2015; pp. 37-59.
[38]
Sahu NK. QSAR studies of some side chain modified 7-Chloro-4-Aminoquinolines as antimalarial agents. Arab J Chem 2014; 7(5): 701-7.
[39]
Guyon I. An introduction to variable and feature selection 1 introduction. J Mach Learn Res 2003; 3: 1157-82.
[40]
Jain SK, Nag S. 3D QSAR analysis on arylbenzofuran derivatives as histamine H 3 receptor inhibitors using K nearest neighbor molecular field analysis (KNNMFA). Int J Pharm Tech Res 2012; 4(4): 1691-702.
[41]
Hasegawa K, Kimura T, Funatsu KGA. Strategy for variable selection in QSAR studies: Enhancement of comparative molecular binding energy analysis by GA-Based PLS method. Quant Struct Act Relat 1999; 18: 262-72.
[http://dx.doi.org/10.1002/(SICI)1521-3838(199907) 18:3<262:AID-QSAR262>3.0.CO;2-S]
[42]
Zheng W, Tropsha A. Novel variable selection quantitative structure--property relationship approach based on the k-nearest-neighbor principle. J Chem Inf Comput Sci 2000; 40(1): 185-94.
[http://dx.doi.org/10.1021/ci980033m] [PMID: 10661566]
[43]
Hasegawa K, Funatsu K. Partial least squares modeling and genetic algorithm optimization in quantitative structure-activity relationships. SAR QSAR Environ Res 2000; 11(3-4): 189-209.
[http://dx.doi.org/10.1080/10629360008033231] [PMID: 10969871]
[44]
Thombare ST, Gonsalves SI, Shaikh AR. 2D and 3D QSAR using kNN-MFA method of pyrazolyl-thiazolinone derivatives as potential EGFR and HER-2 kinase inhibitors. J Comput Methods Mol Des 2012; 2(3): 107-21.
[45]
Cramer RD, Patterson DE, Bunce JD. Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. J Am Chem Soc 1988; 110(18): 5959-67.
[http://dx.doi.org/10.1021/ja00226a005] [PMID: 22148765]
[46]
Eriksson SWL. Statistical validation of QSAR results. van de WH, ed, Chemometric methods in molecular design VCH Verlagsgesellschaft mbH 1995; 309-8.
[47]
Shen M, Xiao Y, Golbraikh A, Gombar VK, Tropsha A. Development and validation of k-nearest-neighbor QSPR models of metabolic stability of drug candidates. J Med Chem 2003; 46(14): 3013-20.
[http://dx.doi.org/10.1021/jm020491t] [PMID: 12825940]
[48]
Golbraikh A, Tropsha A. QSAR modeling using chirality descriptors derived from molecular topology. J Chem Inf Comput Sci 2003; 43(1): 144-54.
[http://dx.doi.org/10.1021/ci025516b] [PMID: 12546547]
[49]
Singh K, Kumawat NK, Bhavthankar SV, et al. Exploring 2D and 3D QSARs of benzimidazole derivatives as transient receptor potential melastatin 8 (trpm8) antagonists using MLR and kNN-MFA methodology. J Saudi Chem Soc 2016; 20: S256-70.
[http://dx.doi.org/10.1016/j.jscs.2012.11.001]

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