Abstract
Background: Rho-kinase is an essential downstream target of GTP-binding protein RhoA, and plays a crucial role in the calcium-sensitization pathway. Rho-kinase pathway is critically involved in phosphorylation state of myosin light chain, leading to increased contraction of smooth muscles. Inhibition of this pathway has turned out to be a promising target for several indications such as cardiovascular diseases, glaucoma and inflammatory diseases.
Methods: The present work focuses on a division-based 2D quantitative structure-activity relationship (QSAR) analysis along with a docking study to predict structural features that may be essential for the enhancement of selectivity and potency of the target compounds. Furthermore, a set of indoles and azaindoles were also projected based on the regression equation as novel developments. Molecular docking was applied for exploring the binding sites of the newly predicted set of compounds with the receptor. Results: Results of the docked conformations suggested that introduction of non-bulky and substituted groups in the hinge region of ROCK-II ATP binding pocket would improve the activity by decreasing the bulkiness or length of the compounds. Conclusion: ADME studies were performed to ascertain the novelty and drug-like properties of the designed molecules, respectively.Keywords: Rho Kinase (ROCK) inhibitors, Quantitative Structure-Activity Relationship (QSAR), molecular modelling, ADME studies, GTP-binding, azaindoles.
Graphical Abstract
[1]
Feng, Y.; LoGrasso, V.P.; Defert, O.; Li, R. Rho kinase (ROCK) inhibitors and their therapeutic potential. J. Med. Chem., 2016, 59, 2269-2300.
[2]
Green, J.; Jingrong, C.; Bandarage, K.P.; Gao, H.; Court, J.; Marhefka, C.; Jacobs, M.; Taslimi, P.; Newsome, D.; Nakayama, T.; Shah, S.; Rodems, S. Design, synthesis, and structure-activity relationships of pyridine based rho kinase (ROCK) inhibitors. J. Med. Chem., 2015, 58, 5028-5037.
[3]
Dai, Y.; Luo, W.; Chang, J. Rho kinase signaling and cardiac physiology. Curr. Opin. Physiol, 2018, 1, 14-20.
[4]
Abdel-Magid, F.A. Rho kinase inhibitors: Potentially versatile therapy for the treatment of cardiovascular diseases and more. Med. Chem. Lett, 2015, 6, 371-372.
[5]
Bello, M.; Martínez, A.M.; Correa, B.J. Automated docking for novel drug discovery. Exp Opin. Drug Discov., 2013, 8, 821-834.
[6]
Martínez, A.M.; Bello, M.; Correa, B.J. Design of drugs by filtering through ADMET, physicochemical and ligand-target flexibility properties. Meth Mol. Biol., 2018, 1824, 403-416.
[7]
Choudhary, S.; Sessions, E.H.; Pocas, J.R.; Grant, W.; Schroter, T.; Lin, L.; Ruiz, C.; Cameron, M.D.; Schurer, S.; LoGrasso, P.; Bannister, T.D.; Feng, Y. Discovery and optimization of indoles and 7-azaindoles as rho kinase (ROCK) inhibitors (part-II). Bioorg. Med. Chem. Lett., 2011, 1, 7113-7118.
[8]
Choudhary, S.; Sessions, E.H.; Pocas, J.R.; Grant, W.; Schroter, T.; Lin, L.; Ruiz, C.; Cameron, M.D.; Schurer, S.; LoGrasso, P.; Bannister, T.D.; Feng, Y. Discovery and optimization of indoles and 7-azaindoles as rho kinase (ROCK) inhibitors (part-I). Bioorg. Med. Chem. Lett., 2011, 1, 7107-7112.
[9]
Ruiz, P.; Myshkin, E.; Quigley, P.; Faroon, O.; Wheeler, J.S.; Mumtaz, M.M.; Brennan, R.J. Assessment of hydroxylated metabolites of polychlorinated biphenyls as potential xenoestrogens: A QSAR comparative analysis. SAR QSAR Environ. Res., 2013, 24, 393-416.
[10]
Ojha, P.; Mishra, P.; Kesar, S.; Singh, S. Chemometric and similarity based analysis of DGAT-1 inhibitors. Int. J. Adv. Res., 2016, 4, 780-806.
[11]
Paliwal, S.; Seth, D.; Yadav, D.; Yadav, R. Development of a robust QSAR model to predict the affinity of pyrrolidine analogs for dipeptidyl peptidase IV (DPP- IV). J. Enz Inhib. Med. Chem., 2011, 1, 129-140.
[12]
Castilho, M.S.; Guido, R.V.C.; Andricopulo, A.D. Classical and hologram QSAR studies on a series of tacrine derivatives as butyrylcholinesterase inhibitors. Lett. Drug Des. Discov., 2007, 4, 106-113.
[13]
Kesar, S.; Mishra, P.; Ojha, P.; Singh, S. 2D QSAR study of potent gsk-3β inhibitor for treatment of type II diabetes. Int. J. Pharm. Sci. Res., 2016, 7, 2932-2943.
[14]
Paliwal, S.K.; Verma, A.N.; Paliwal, S. Structure-activity relationship analysis of cationic 2-phenylbenzofurans as potent anti-trypanosomal agents: A multivariate statistical approach. Le Monatshefte, fuer, Chemie., 2011, 28, 1367-1375.
[15]
Kesar, S.; Paliwal, S.K.; Mishra, P.; Chauhan, M. Quantitative structure-activity relationship analysis of selective rho kinase inhibitors as neuro-regenerator agent. Turk. J. Pharm. Sci, 2018. In Press
[16]
Himmelblau, M.D. Accounts of experiences in the application of artificial neural networks in chemical engineering. Ind. Eng. Chem. Res., 2008, 47(16), 5782-5796.
[17]
Eriksson, L.; Jaworska, J.; Worth, A.P.; Cronin, T.D.M.; McDowell, R.M.; Gramatica, P. Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs. Environ. Health Perspect., 2003, 111(10), 1361-1375.
[18]
Weaver, S.; Gleeson, M.P. The importance of the domain of applicability in QSAR modeling. J. Mol. Graph. Model., 2008, 26(8), 1315-1326.
[19]
Sharma, A.; Gupta, S.P.; Siddiqui, A.A. A QSAR study on a series of thiourea derivatives acting as anti-hepatitis C virus agents. Indian J. Biochem. Biophys., 2013, 50(4), 278-283.
[20]
Netzeva, T.I.; Worth, A.; Aldenberg, T. Benigni. R.; Cronin, M.T.; Gramatica, P.; Jaworska, J.S.; Kahn, S.; Klopman, G.; Marchant, C.A.; Myatt, G.; Nikolova-Jeliazkova N.; Patlewicz, G.Y.; Perkins, R.; Roberts, D.; Schultz, T.; Stanton, D.W.; van de Sandt, J.J.; Tong, W.; Veith, G.; Yang, C. Current status of methods for defining the applicability domain of (Quantitative) Structure-Activity Relationships. Altern. Lab. Anim., 2005, 33(2), 1-19.
[21]
Sahlin, U.; Jeliazkova, N.; Oberg, T. Applicability domain dependent predictive uncertainty in QSAR regressions. Mole. Inf, 2014, 33(1), 26-35.
[22]
Shah, S.; Savjani, J. A review on ROCK-II inhibitors: From molecular modelling to synthesis. Bioorg. Med. Chem. Lett., 2016, 26(10), 2383-2391.
Article Metrics
41
1