Generic placeholder image

Current Computer-Aided Drug Design

Editor-in-Chief

ISSN (Print): 1573-4099
ISSN (Online): 1875-6697

Research Article

Molecular Docking Analysis of Caspase-3 Activators as Potential Anticancer Agents

Author(s): Sushil K. Kashaw*, Shivangi Agarwal, Mitali Mishra, Samaresh Sau and Arun K. Iyer

Volume 15, Issue 1, 2019

Page: [55 - 66] Pages: 12

DOI: 10.2174/1573409914666181015150731

Price: $65

Abstract

Introduction: Caspase-3 plays a leading role in apoptosis and on activation, it cleaves many protein substrates in cells and causes cell death. Since many chemotherapeutics are known to induce apoptosis in cancer cells, promotion or activation of apoptosis via targeting apoptosis regulators has been suggested as a promising strategy for anticancer drug discovery. In this paper, we studied the interaction of 1,2,4-Oxadiazoles derivatives with anticancer drug target enzymes (PDB ID 3SRC).

Methods: Molecular docking studies were performed on a series of 1,2,4-Oxadiazoles derivatives to find out molecular arrangement and spatial requirements for their binding potential for caspase-3 enzyme agonistic affinity to treat cancer. The Autodock 4.2 and GOLD 5.2 molecular modeling suites were used for the molecular docking analysis to provide information regarding important drug receptor interaction.

Results and Conclusion: Both suites explained the spatial disposition of the drug with the active amino acid in the ligand binding domain of the enzyme. The amino acid asparagine 273 (ASN 273) of target has shown hydrogen bond interaction with the top ranked ligand.

Keywords: Molecular docking, caspase, anti-cancer, binding affinity, Autodock 4.2, asparagine.

Graphical Abstract
[1]
Torre, L.A.; Bray, F.; Siegel, R.L.; Ferlay, J.; Lortet-Tieulent, J.; Jemal, A. Global cancer statistics, 2012. CA Cancer J. Clin., 2015, 65(2), 87-108.
[2]
Ravez, M.S.; Spillier, Q.; Marteau, R.; Feron, O.; Freeick, R.L. Challenges and opportunities in the development of serine synthetic pathway inhibitors for cancer therapy. J. Med. Chem., 2017, 60(4), 1227-1237.
[3]
Kettle, J.G.; Alwan, H.; Bista, M.; Breed, J.; Davies, N.L.; Eckersley, K.; Fillery, S.; Foote, K.M.; Goodwin, L.; Jones, D.R.; Käck, H.; Lau, A.; Nissink, J.W.; Read, J.; Scott, J.S.; Taylor, B.; Walker, G.; Wissler, L.; Wylot, M. Potent and selective inhibitors of MTH1 probe its role in cancer cell survival. J. Med. Chem., 2016, 59(6), 2346-2361.
[4]
Korzhnev, D.M.; Hadden, M.K. Targeting the translesion synthesis pathway for the development of anti-cancer Chemotherapeutics. J. Med. Chem., 2016, 59(20), 9321-9336.
[5]
Heffron, T.P. Small molecule kinase inhibitors for the treatment of brain cancer. J. Med. Chem., 2016, 59(22), 10030-10066.
[6]
Ghislain, I.; Zikos, E.; Coens, C. Health-related quality of life in locally advanced and metastatic breast cancer: Methodological and clinical issues in randomised controlled trials. Lancet Oncol., 2016, 17(7), e294-e304.
[7]
Uttley, L.; Whiteman, B.L.; Woods, H.B.; Harman, S.; Philips, S.T.; Cree, I.A. Building the evidence base of blood-based biomarkers for early detection of cancer: A rapid systematic mapping review. EBioMedicine, 2016, 10, 164-173.
[8]
Hollestelle, A.; VanderBaan, F.H.; Brechuck, A. No clinical utility of KRAS variant rs61764370 for ovarian or breast cancer. Gynecologic Oncology, 2016, 141, 381-401.
[9]
Li, Y.; Li, F.; Jiang, F.; Lv, X.; Zhang, R.; Lu, A.; Zhang, Ge. A mini-review for cancer immunotherapy: Molecular understanding of PD-1/PD-L1 pathway & translational blockade of immune checkpoints. Int. J. Mol. Sci., 2016, 17, 1151.
[10]
Sau, S.; Alsaab, H.O.; Kashaw, S.K.; Tatiparti, K.; Iyer, A.K. Small molecule targeting ligand to antibody drug conjugate: A potent regimen for cancer therapy. Drug Discovery. Today, 2017, 22(10), 1547-1556.
[11]
Tatiparti, K.; Sau, S.; Kashaw, S.K.; Iyer, A.K. siRNA Delivery Strategies: A comprehensive review of recent developments. Nanomaterials , 2017, 7(4), 77.
[12]
Sau, S.; Iyer, A.K. Antibody drug conjugate: A new era of targeted cancer therapy. Ann. Pharmacol. Pharm, 2017, 2(5), 1032.
[13]
Kemnitzer, W.; Jiang, S.; Zhang, H.; Kasibhatla, S.; Crogan-Grundy, C.; Blais, C.; Attardo, G.; Denis, R.; Lamothe, S.; Gourdeau, H.; Tseng, B.; Drewe, J.; Cai, S.X. Discovery of 4-aryl-2-oxo-2H-chromenes as a new series of apoptosis inducers using a cell- and caspase-based high-throughput screening assay. Bioorg. Med. Chem. Lett., 2008, 15(20), 5571-5575.
[14]
Sau, S.; Banerjee, R. Cationic lipid-conjugated dexamethasone as a selective antitumor agent. Eur. J. Med. Chem., 2014, 83, 433-447.
[15]
Sau, S.; Mondal, S.K.; Kashaw, S.K.; Iyer, A.K.; Banerjee, R. Combination of cationic dexamethasone derivative and STAT3 inhibitors (WP1066) for aggressive melanoma: A strategy for repurposing phase I clinical trial drug. Mol. Cell. Biochem., 2017, 436(1-2), 119-136.
[16]
Ursi, P.; Guariento, S.; Trombetti, G.; Orro, A.; Cichero, E.; Milanesi, E.; Fossa, P.; Bruno, O. Further insights in the binding mode of selective inhibitors to human PDE4D enzyme combining docking and molecular dynamics. Mol. Informatics., 2016, 35, 369-381.
[17]
Kumar, B.R.P.; Nanjan, M.J. Comparative molecular similarity indices analysis for predicting the antihyperglycemic activity of thioglitazones. Med. Chem. Res., 2010, 19(8), 1000-1010.
[18]
Kemnitzer, W.; Drewe, J.; Jiang, S.; Zhang, H.; Zhao, J.; Crogan-Grundy, C.; Xu, L.; Lamothe, S.; Gourdeau, H.; Denis, R.; Tseng, B.; Kasibhatla, S.; Cai, S.X. Discovery of 4-aryl-4H-chromenes as a new series of apoptosis inducers using a cell- and caspase-based high-throughput screening assay. 3. Structure-activity relationships of fused rings at the 7,8-positions. J. Med. Chem., 2007, 14(12), 2858-2864.
[19]
Morris, G.M.; Huey, R.; Lindstrom, W.; Sanner, M.F.; Belew, R.K.; Goodsell, D.S.; Olson, A.J. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J. Comput. Chem., 2009, 30, 2785-2791.
[20]
GOLD Version 5.2; Cambridge crystallographic data centre: Cambridge, UK, 2009. .
[21]
Tanchuk1, V.V.Y.; Tanin1, V.O.; Vovk A.I.; Poda G. A new improved hybrid scoring function for molecular docking and scoring based on autodock and autodock. Chem. Biol. Drug Des., 2016, 87, 618-625.
[22]
Yu, V.; Tanchuk, V.; Tanin, A.I.V.; Poda, G. A New scoring function for molecular docking based on autodock and autodock vina. Curr. Drug Dis. Technol., 2015, 12, 170-178.

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy