3-Dimensional quantitative structure-activity relationship and molecular docking studies of tetrasubstituted pyrazole derivatives as inhibitors of cyclooxygenase-2
Keywords:
QSAR, Multiple linear regression, Physicochemical descriptors, Docking, COX-2, Scigress explorer, Molegro virtual dockerAbstract
Background:Design and development of new drugs is simplified and made more cost-effective because of the advances in the concepts of Quantitative Structure-Activity Relationship (QSAR) studies. A methodology of QSAR studies is one of the approaches to the rational drug design.
Methods:3-Dimensional QSAR studies were performed on a series of tetrasubstituted pyrazole derivatives by using Scigress Explorer software suite. Docking studies of these compounds were also performed to understand the interactions with amino acid residues of COX-2 protein.
Results:The multiple linear regression analysis was used to correlate the physicochemical descriptors with the COX-2 inhibitory activity of 24 training set of compounds and the best QSAR model was developed. The best model was validated using leave-one-out method and found to be statistically significant, with coefficient of determination (r2) of 0.835. This model was further used to predict the COX-2 inhibitory activity of 10 test set of compounds. Docking analysis revealed that most of the compounds formed H-bond interactions with amino acid residues of COX-2 protein (PDB ID: 1CX2). Predicted pIC50 value of one of the test compounds was 7.048 and it showed H-bond interactions with His90 & Tyr355 residues.
Conclusion:The present study shall help in rational drug design and synthesis of new selective COX-2 inhibitors with predetermined affinity and activity and provides valuable information for the understanding of interactions between COX-2 and the novel tetrasubstituted pyrazole derivative compounds.
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References
Crofford LJ, Lipsky PE, Brooks P, Abramson SB, Simon LS, van de Putte LB. Basic biology and clinical application of specific cyclooxygenase-2 inhibitors. Arthritis Rheum. 2000;43:4-13.
Vane JR. Inhibition of prostaglandin synthesis as a mechanism of action for aspirin-like drugs. Nat New Biol. 1971;231:232-5.
Whittle BJR. Gastrointestinal effects of non-steroidal anti-inflammatory drugs. Fundam Clin Pharmacol. 2003;17:301-13.
Rainsford KD. Profile and mechanisms of gastrointestinal and other side effects of non-steroidal anti-inflammatory drugs (NSAIDs). Am J Med. 1999;107:27S-36S.
Hawkey CJ. COX-2 inhibitors. Lancet. 1999;353:307-14.
Garcia-Rodriguez LA, Cattaruzzi C, Troncon MG, Agostinis L. Risk of hospitalization for upper gastrointestinal tract bleeding associated with ketorolac, other non-steroidal anti-inflammatory drugs, calcium antagonists, and other antihypertensive drugs. Arch Intern Med. 1998;158:33-9.
Garcia Rodriguez LA, Jick H. Risk of upper gastrointestinal bleeding and perforation associated with individual non-steroidal anti-inflammatory drugs. Lancet. 1994;343:769-72.
Hinz B, Brune K. Non-steroidal anti-inflammatory drugs: old and new. In: Isenberg DA, Maddison PJ, Woo P, Glass D, Breedveld FC, eds. Oxford Textbook of Rheumatology. 3rd ed. New York: Oxford University Press; 2004:442-50.
Testa B, Kier LB. The concept of molecular structure in structure-activity relationship studies and drug design. Med Res Rev. 1991;11:35-48.
Thakur A, Thakur M, Kakani N, Joshi A, Thakur A, Gupta A. Application of topological and physicochemical descriptors: QSAR study of phenylamino-acridine derivatives. ARKIVOC. 2004;14:36-43.
Mahajan S, Kamath V, Nayak S, Vaidya S. QSAR analysis of benzophenone derivatives as antimalarial agents. Indian J Pharm Sci. 2012;74:41-7.
Wolf M, Kubiyini H. Drug development research. In: James F. Kerwin Jr., eds. Burger’s Medicinal chemistry and drug discovery. 5th ed. New York: Wiley Interscience Publishers; 1995: 116-117.
Roy PP, Paul S, Mitra I, Roy K. Two novel parameters for validation of predictive QSAR models. Molecules. 2009;14:1660-1701.
Konovalov DA, Llewellyn LE, Heyden YV, Coomans DJ. Robust cross-validation of linear regression QSAR models. Chem Inf Model. 2008;48:2081-94.
Sudha KN, Shakira M, Prasanthi P, Sarika N, Kumar CN, Babu PA. Virtual screening for novel COX-2 inhibitors using the ZINC database. Bioinf. 2008;2:325-9.
Thomsen R, Christensen MH. MolDock: a new technique for high-accuracy molecular docking. J Med Chem. 2006;49:3315-21.
Girish KG, Ajay K. 3D-QSAR studies of some tetrasubstituted pyrazoles as COX-II inhibitors. Acta Poloniae Pharmaceutic-Drug Res. 2012;69:763-72.
Selvaraj C, Tripathi SK, Reddy KK, Singh SK. Tool development for prediction of pIC50 values from the IC50 values: a pIC50 value calculator. Curr Trends Biotechnol Pharm. 2011;5:1104-9.
ACD/ChemSketch Freeware 11.01. Advanced chemistry development, Inc., Toronto, Ontario, Canada, 2013. Available at: www.acdlabs.com.
ACD/3D Viewer. Advanced chemistry development, Inc., Toronto, Ontario, Canada, 2012. Available at: http://www.acdlabs.com/products/draw_nom/draw/chemsketch/3dviewer.php.
Halgren TA. Merck molecular force field: I. Basis, form, scope, parameterization, and performance of MMFF94. J Comput Chem. 1996;17:490-519.
Agrawal VK, Singh J, Mishra KC, Khadikar PV, Jaliwala YA. QSAR study on 5,6-dihydro-2-pyrones as HIV-1 protease inhibitors. ARKIVOC. 2006;2:162-77.
Eriksson L, Jaworska J, Worth AP, Cronin MTD, McDowell RM. Methods for reliability and uncertainty assessment and for applicability evaluations of classification and regression based QSARs. Environ Health Persp. 2003;111:1361-75.
