[1]
Paulis, L.; Rajkovicova, R.; Simko, F. New developments in the pharmacological treatment of hypertension: Dead-end or a glimmer at the horizon? Curr. Hypertens. Rep., 2015, 17(6), 557.
[2]
Noncommunicable diseases progress monitor, 2017. Geneva: World
Health Organization. 2017. Licence: CC BY-NC-SA 3.0 IGO
[3]
Saraceno, B. World Health Day. Acta Psychiatr. Scand., 2001, 103(2), 83.
[4]
Campbell, D. Renin inhibitors-mechanisms of action. Aust. Prescr., 2009, 32(5), 132-135.
[5]
Holsworth, D.D.; Cai, C.; Cheng, X-M.; Cody, W.L.; Downing, D.M.; Erasga, N.; Lee, C.; Powell, N.A.; Edmunds, J.J.; Stier, M.; Jalaie, M.; Zhang, E.; McConnell, P.; Ryan, M.J.; Bryant, J.; Li, T.; Kasani, A.; Hall, E.; Subedi, R.; Rahim, M.; Maiti, S. Ketopiperazine-based renin inhibitors: Optimization of the “C” ring. Bioorg. Med. Chem. Lett., 2006, 16(9), 2500-2504.
[6]
Calixto, A.R.; Bras, N.F.; Fernandes, P.A.; Ramos, M.J. Reaction mechanism of human renin studied by quantum mechanics/molecular mechanics(QM/MM) Calculations. ACS Catal., 2014, 4(11), 3869-3876.
[7]
Pool, J.L. Direct renin inhibition: Focus on aliskiren. J. Manag. Care Pharm., 2007, 13(8)(Suppl. B), 21-33.
[8]
Tani, S.; Kushiro, T.; Takahashi, A.; Kawamata, H.; Ohkubo, K.; Nagao, K.; Hirayama, A. Antihypertensive efficacy of the direct renin inhibitor aliskiren as add-on therapy in patients with poorly controlled hypertension. Intern. Med., 2016, 55(5), 427-435.
[9]
Desjarlais, M.; Dussault, S.; Dhahri, W.; Mathieu, R.; Rivard, A. direct renin inhibition with aliskiren improves ischemia-induced neovascularization: Blood pressure-independent effect. Atherosclerosis, 2015, 242(2), 450-460.
[10]
Buczko, W.; Hermanowicz, J.M. Pharmacokinetics and pharmacodynamics of aliskiren, an oral direct renin inhibitor. Pharmacol. Rep., 2008, 60(5), 623-631.
[11]
McMurray, J.J.V.; Krum, H.; Abraham, W.T.; Dickstein, K.; Køber, L.V.; Desai, A.S.; Solomon, S.D.; Greenlaw, N.; Ali, M.A.; Chiang, Y.; Shao, Q.; Tarnesby, G.; Massie, B.M. Aliskiren, enalapril, or aliskiren and enalapril in heart failure. N. Engl. J. Med., 2016, 374(16), 1521-1532.
[12]
Prescrire, R. Towards better patient care: Drugs to avoid in 2015. Prescrire Int., 2014, 23(150), 161-165.
[13]
Webb, R.L.; Schiering, N.; Sedrani, R.; Maibaum, J. Direct renin inhibitors as a new therapy for hypertension. J. Med. Chem., 2010, 53(21), 7490-7520.
[14]
Nakamura, Y.; Sugita, C.; Meguro, M.; Miyazaki, S.; Tamaki, K.; Takahashi, M.; Nagai, Y.; Nagayama, T.; Kato, M.; Suemune, H.; Nishi, T. Design and optimization of novel(2S,4S,5S)-5-amino-6-(2,2-dimethyl-5-oxo-4-phenylpiperazin-1-yl)-4-hydroxy-2-isopropylhexanamides as renin inhibitors. Bioorg. Med. Chem. Lett., 2012, 22(14), 4561-4566.
[15]
Mori, Y.; Ogawa, Y.; Mochizuki, A.; Nakamura, Y.; Sugita, C.; Miyazaki, S.; Tamaki, K.; Matsui, Y.; Takahashi, M.; Nagayama, T.; Nagai, Y.; Inoue, S.I.; Nishi, T. Design and discovery of new(3s,5r)-5-[4-(2-chlorophenyl)-2,2-dimethyl-5-oxopiperazin-1-yl]piperidine-3-carboxamides as potent renin inhibitors. Bioorg. Med. Chem. Lett., 2012, 22(24), 7677-7682.
[16]
Li, Y.; Wang, Y.; Zhang, F. Pharmacophore modeling and 3d-qsar analysis of phosphoinositide 3-kinase p110alpha inhibitors. J. Mol. Model., 2010, 16(9), 1449-1460.
[17]
Dixon, S.L.; Smondyrev, A.M.; Knoll, E.H.; Rao, S.N.; Shaw, D.E.; Friesner, R.A. PHASE: A new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results. J. Comput. Aided Mol. Des., 2006, 20(10-11), 647-671.
[18]
Selvaraman, N.; Selvam, S.K.; Muthusamy, K. The binding mode prediction and similar ligand potency in the active site of vitamin D receptor with QM/MM interaction, MESP, and MD simulation. Chem. Biol. Drug Des., 2016, 88(2), 272-280.
[19]
Bhattacherjee, D.; Bhabak, K.P. Atom based 3D-QSAR studies on 2,4-dioxopyrimidine-1-carboxamide analogs: Validation of experimental inhibitory potencies towards acid ceramidase. Eur. J. Pharm. Sci., 2016, 83, 8-18.
[20]
Nagamani, S.; Muthusamy, K.; Kirubakaran, P.; Singh, K.D.; Krishnasamy, G. Theoretical studies on benzimidazole derivatives as E. coli biotin carboxylase inhibitors. Med. Chem. Res., 2012, 21(9), 2169-2180.
[21]
Roy, K.; Das, R.N.; Ambure, P.; Aher, R.B. Be Aware of Error Measures. Further Studies on Validation of Predictive QSAR Models; Elsevier B.V., 2016, Vol. 152, .
[22]
Friesner, R.A.; Murphy, R.B.; Repasky, M.P.; Frye, L.L.; Greenwood, J.R.; Halgren, T.A.; Sanschagrin, P.C.; Mainz, D.T. Extra precision glide: Docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes. J. Med. Chem., 2006, 49(21), 6177-6196.
[23]
van der Spoel, D.; Drunen, R.V.; Berendsen, H.J.C. GROMACS :
Groningen Machine for Chemical Simulations User Manual
Version 3.3.3; , 1994.
[24]
Schüttelkopf, A.W.; Van Aalten, D.M.F. PRODRG: A tool for high-throughput crystallography of protein-ligand complexes. Acta
Crystallogr. Sect. D Biol. Crystallogr, 2004, 60(8), 1355-1363.
[25]
Gharaghani, S.; Khayamian, T.; Keshavarz, F. Docking, molecular dynamics simulation studies, and structurebased QSAR model on cytochrome P450 2A6 inhibitors. Struct. Chem., 2012, 23(2), 341-350.
[26]
Genheden, S.; Ryde, U. The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Expert Opin. Drug Discov., 2015, 10(5), 449-461.
[27]
Misini-Ignjatovic, M.; Caldararu, O.; Dong, G.; Munoz-Gutierrez, C.; Adasme-Carreno, F.; Ryde, U. Binding-affinity predictions of HSP90 in the D3R grand challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations. J. Comput. Aided Mol. Des., 2016, 30(9), 707-730.
[28]
Wan, J.; Zhang, L.; Yang, G.; Zhan, C.G. Quantitative structure-activity relationship for cyclic imide derivatives of protoporphyrinogen oxidase inhibitors: A study of quantum chemical descriptors from density functional theory. J. Chem. Inf. Comput. Sci., 2004, 44(6), 2099-2105.
[29]
Kirubakaran, P.; Karthikeyan, M. Pharmacophore modeling, 3D-QSAR and DFT studies of IWR small-molecule inhibitors of wnt response. J. Recept. Signal Transduct. Res., 2013, 33(5), 276-285.
[30]
Gupta, M.K.; Misra, K. Atom-based 3D-QSAR, molecular docking and molecular dynamics simulation assessment of inhibitors for thyroid hormone receptor α and β. J. Mol. Model., 2014, 20(6), 2286.
[31]
Wood, J.M.; Maibaum, J.; Rahuel, J.; Grütter, M.G.; Cohen, N.C.; Rasetti, V.; Rüger, H.; Göschke, R.; Stutz, S.; Fuhrer, W.; Schilling, W.; Rigollier, P.; Yamaguchi, Y.; Cumin, F.; Baum, H.P.; Schnell, C.R.; Herold, P.; Mah, R.; Jensen, C.; O’Brien, E.; Stanton, A.; Bedigian, M.P. Structure-based design of aliskiren, a novel orally effective renin inhibitor. Biochem. Biophys. Res. Commun., 2003, 308(4), 698-705.
[32]
Politi, A.; Durdagi, S.; Moutevelis-Minakakis, P.; Kokotos, G.; Mavromoustakos, T. Development of accurate binding affinity predictions of novel renin inhibitors through molecular docking studies. J. Mol. Graph. Model., 2010, 29(3), 425-435.
[33]
Lorthiois, E.; Breitenstein, W.; Cumin, F.; Ehrhardt, C.; Francotte, E.; Jacoby, E.; Ostermann, N.; Sellner, H.; Kosaka, T.; Webb, R.L.; Rigel, D.F.; Hassiepen, U.; Richert, P.; Wagner, T.; Maibaum, J. The discovery of novel potent trans-3,4-disubstituted pyrrolidine inhibitors of the human aspartic protease renin from in silico three-dimensional(3D) pharmacophore searches. J. Med. Chem., 2013, 56(6), 2207-2217.
[34]
Lipinski, C.A.; Lombardo, F.; Dominy, B.W.; Feeney, P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development setting. Adv. Drug Deliv. Rev., 2012, 64, 4-17.
25
1