Ligand Based Pharmacophore Modeling Followed by Biological Screening Lead to Discovery of Novel PDK1 Inhibitors as Anticancer Agents

Iman       Mansi; Mahmoud    A.   Al-Sha'er; Nizar       Mhaidat; Mutasem       Taha

doi:10.2174/1871520620666191224110600

Abstract

Background: Phosphoinositide-Dependent Kinase-1 (PDK1) is a serine/threonine kinase, which belongs to AGC kinase family required by cancer cells.

Methods: Pharmacophoric space of 86 PDK1 inhibitors using six diverse sets of inhibitors was explored to identify high-quality pharmacophores. The best combination of pharmacophoric models and physicochemical descriptors was selected by genetic algorithm-based QSAR analysis that can elucidate the variation of bioactivity within the training inhibitors. Two successful orthogonal pharmacophores emerged in the optimum QSAR equation (r2 69 = 0.90, r2 LOO= 0.86, F= 51.92, r2 PRESS against 17 test inhibitors = 0.79). Receiver Operating Characteristic (ROC) curve analyses were used to estimate the QSAR-selected pharmacophores.

Results: 5 out of 11 compounds tested had shown potential intracellular PDK1 inhibition with the highest inhibition percent for compounds 92 and 93 as follows; 90 and 92% PDK1 inhibition, respectively.

Conclusion: PDK1 inhibitors are potential anticancer agents that can be discovered by combination method of ligand based design with QSAR and ROC analysis.

Keywords: PDK1, anticancer, 3D-QSAR, pharmacophores, ROC analysis, ligand based design.

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[1] 
Johnson, M.C.; Hu, Q.; Lingardo, L.; Ferre, R.A.; Greasley, S.; Yan, J.; Kath, J.; Chen, P.; Ermolieff, J.; Alton, G. Novel isoquinolone PDK1 inhibitors discovered through fragment-based lead discovery. J. Comput. Aided Mol. Des.,  2011, 25(7), 689-698.
[http://dx.doi.org/10.1007/s10822-011-9456-7] [PMID: 21779981] 
[2] 
Peifer, C.; Alessi, D.R. Small-molecule inhibitors of PDK1. ChemMedChem,  2008, 3(12), 1810-1838.
[http://dx.doi.org/10.1002/cmdc.200800195] [PMID: 18972468] 
[3] 
Fyffe, C.; Falasca, M. 3-Phosphoinositide-dependent protein kinase-1 as an emerging target in the management of breast cancer. Cancer Manag. Res.,  2013, 5, 271-280.
[http://dx.doi.org/10.2147/CMAR.S35026] [PMID: 24039447] 
[4] 
Messoussi, A.; Peyronnet, L.; Feneyrolles, C.; Chevé, G.; Bougrin, K.; Yasri, A. Structural elucidation of the DFG-Asp in and DFG-Asp out states of TAM kinases and insight into the selectivity of their inhibitors. Molecules,  2014, 19(10), 16223-16239.
[http://dx.doi.org/10.3390/molecules191016223] [PMID: 25310149] 
[5] 
Murphy, S.T.; Alton, G.; Bailey, S.; Baxi, S.M.; Burke, B.J.; Chappie, T.A.; Ermolieff, J.; Ferre, R.; Greasley, S.; Hickey, M.; Humphrey, J.; Kablaoui, N.; Kath, J.; Kazmirski, S.; Kraus, M.; Kupchinsky, S.; Li, J.; Lingardo, L.; Marx, M.A.; Richter, D.; Tanis, S.P.; Tran, K.; Vernier, W.; Xie, Z.; Yin, M.J.; Yu, X.H. Discovery of novel, potent, and selective inhibitors of 3-phosphoinositide-dependent kinase (PDK1). J. Med. Chem.,  2011, 54(24), 8490-8500.
[http://dx.doi.org/10.1021/jm201019k] [PMID: 22040023] 
[6] 
Du, J.; Yang, M.; Chen, S.; Li, D.; Chang, Z.; Dong, Z. PDK1 promotes tumor growth and metastasis in a spontaneous breast cancer model. Oncogene,  2016, 35(25), 3314-3323.
[http://dx.doi.org/10.1038/onc.2015.393] [PMID: 26455327] 
[7] 
Kirubakaran, P.; Muthusamy, K.; Singh, K.H.; Nagamani, S. Ligand-based pharmacophore modeling; atom-based 3D-QSAR analysis and molecular docking studies of phosphoinositide-dependent kinase-1 inhibitors. Indian J. Pharm. Sci.,  2012, 74(2), 141-151.
[http://dx.doi.org/10.4103/0250-474X.103846] [PMID: 23325995] 
[8] 
Zhang, W.; Zhou, L.; Li, Z.C. 3D QSAR pharmacophore-based virtual screening and molecular docking studies for the discovery of potential PDK1 inhibitors. Med. Chem. Res.,  2013, 22, 3416-3427.
[http://dx.doi.org/10.1007/s00044-012-0338-x] 
[9] 
Gopalsamy, A.; Shi, M.; Boschelli, D.H.; Williamson, R.; Olland, A.; Hu, Y.; Krishnamurthy, G.; Han, X.; Arndt, K.; Guo, B. Discovery of dibenzo[c,f][2,7]naphthyridines as potent and selective 3-phosphoinositide-dependent kinase-1 inhibitors. J. Med. Chem.,  2007, 50(23), 5547-5549.
[http://dx.doi.org/10.1021/jm070851i] [PMID: 17941624] 
[10] 
Islam, I.; Brown, G.; Bryant, J.; Hrvatin, P.; Kochanny, M.J.; Phillips, G.B.; Yuan, S.; Adler, M.; Whitlow, M.; Lentz, D.; Polokoff, M.A.; Wu, J.; Shen, J.; Walters, J.; Ho, E.; Subramanyam, B.; Zhu, D.; Feldman, R.I.; Arnaiz, D.O. Indolinone based phosphoinositide-dependent kinase-1 (PDK1) inhibitors. Part 2: optimization of BX-517. Bioorg. Med. Chem. Lett.,  2007, 17(14), 3819-3825.
[http://dx.doi.org/10.1016/j.bmcl.2007.05.060] [PMID: 17544272] 
[11] 
Islam, I.; Bryant, J.; Chou, Y.L.; Kochanny, M.J.; Lee, W.; Phillips, G.B.; Yu, H.; Adler, M.; Whitlow, M.; Ho, E.; Lentz, D.; Polokoff, M.A.; Subramanyam, B.; Wu, J.M.; Zhu, D.; Feldman, R.I.; Arnaiz, D.O. Indolinone based phosphoinositide-dependent kinase-1 (PDK1) inhibitors. Part 1: design, synthesis and biological activity. Bioorg. Med. Chem. Lett.,  2007, 17(14), 3814-3818.
[http://dx.doi.org/10.1016/j.bmcl.2007.04.071] [PMID: 17531483] 
[12] 
Kurogi, Y.; Güner, O.F. Pharmacophore modeling and three-dimensional database searching for drug design using catalyst. Curr. Med. Chem.,  2001, 8(9), 1035-1055.
[http://dx.doi.org/10.2174/0929867013372481] [PMID: 11472240] 
[13] 
Sutter, J.M.; Güner, O.F.; Hoffmann, R.; Waldman, M. Effect of variable weights and tolerances on predictive model generation.Pharmacophore Perception, Dev; Guner, O.F., Ed.; Use Drug Des.,
International University Line: La Jolla, California, United states, 2000, pp. 501-511.
[14] 
Catalyst User Guide. Biovia Software, 2016.www.accelarys.com
[15] 
Sheridan, R.P.; Kearsley, S.K. Why do we need so many chemical similarity search methods? Drug Discov. Today,  2002, 7(17), 903-911.
[http://dx.doi.org/10.1016/S1359-6446(02)02411-X] [PMID: 12546933] 
[16] 
Bersuker, I.B.; Bahceci, S.; Boggs, J.E. The electronconformational
method of identification of pharmacophore and
anti- pharmacophore shielding.Pharmacophore Perception, Dev; Guner, O.F., Ed.; Use Drug Des., International University Line: La
Jolla, California, United states, 2000, pp. 457-473.
[17] 
Poptodorov, K.; Luu, T.; Hoffmann, R. Methods and principles in Medicinal Chemistry, Pharmacophores and Pharmacophores Searches; Wiley-VCH: Weinheim, Germany, 2006, Vol. 2, . 
[18] 
Li, H.; Sutter, J.M.; Hoffmann, R. HypoGen: An automated system
for generating predictive 3D pharmacophore models.Pharmacophore
Perception, Dev; Guner, O.F., Ed.; Use Drug Des., International
University Line: La Jolla, California, United states, 2000, pp. 173-189.
[19] 
CERIUS2 QSAR Users’ Manual. Biovia Inc., 2016.
[20] 

Catalyst 4.10, Ligandfit User Manual; Accelrys Inc.: San Diego, CA, 2000. 
[21] 
Fisher, R. The Principle of Experimentation, Illustrated by a Psycho-Physical Experiment. Des. Exp, 8th ed; Hafner Publishing Co.: New York, USA, 1966, pp. 11-26.
[22] 
Taha, M.O.; Atallah, N.; Al-Bakri, A.G.; Paradis-Bleau, C.; Zalloum, H.; Younis, K.S.; Levesque, R.C. Discovery of new MurF inhibitors via pharmacophore modeling and QSAR analysis followed by in-silico screening. Bioorg. Med. Chem.,  2008, 16(3), 1218-1235.
[http://dx.doi.org/10.1016/j.bmc.2007.10.076] [PMID: 17988876] 
[23] 
Taha, M.O.; Bustanji, Y.; Al-Bakri, A.G.; Yousef, A.M.; Zalloum, W.A.; Al-Masri, I.M.; Atallah, N. Discovery of new potent human protein tyrosine phosphatase inhibitors via pharmacophore and QSAR analysis followed by in silico screening. J. Mol. Graph. Model.,  2007, 25(6), 870-884.
[http://dx.doi.org/10.1016/j.jmgm.2006.08.008] [PMID: 17035054] 
[24] 
Taha, M.O.; Bustanji, Y.; Al-Ghussein, M.A.S.; Mohammad, M.; Zalloum, H.; Al-Masri, I.M.; Atallah, N. Pharmacophore modeling, quantitative structure-activity relationship analysis, and in silico screening reveal potent glycogen synthase kinase-3beta inhibitory activities for cimetidine, hydroxychloroquine, and gemifloxacin. J. Med. Chem.,  2008, 51(7), 2062-2077.
[http://dx.doi.org/10.1021/jm7009765] [PMID: 18324764] 
[25] 
Irwin, J.J.; Shoichet, B.K. ZINC--a free database of commercially available compounds for virtual screening. J. Chem. Inf. Model.,  2005, 45(1), 177-182.
[http://dx.doi.org/10.1021/ci049714+] [PMID: 15667143] 
[26] 
Triballeau, N.; Acher, F.; Brabet, I.; Pin, J.; Bertrand, H. Virtual
Screening Workflow Development Guided by the. “Receiver Operating
Characteristic” Curve Approach. Application to High-
Throughput Docking on Metabotropic Glutamate Receptor Subtype
4 Virtual Screening Workflow Development Guided by the “Receiver,  2005, 2534-2547.
[http://dx.doi.org/10.1021/jm049092j] 
[27] 
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 settings. Adv. Drug Deliv. Rev.,  2001, 46(1-3), 3-26.
[http://dx.doi.org/10.1016/S0169-409X(00)00129-0] [PMID: 11259830] 
[28] 
Veber, D.F.; Johnson, S.R.; Cheng, H.Y.; Smith, B.R.; Ward, K.W.; Kopple, K.D. Molecular properties that influence the oral bioavailability of drug candidates. J. Med. Chem.,  2002, 45(12), 2615-2623.
[http://dx.doi.org/10.1021/jm020017n] [PMID: 12036371] 
[29] 
Thermofisher. http://www.lifetechnologies.com2019.
[30] 
Mhaidat, N.M.; Abdul-Razzak, K.K.; Alkofahi, A.S.; Alsarhan, A.M.; Aldaher, A.N.; Thorne, R.F. Altholactone induces apoptotic cell death in human colorectal cancer cells. Phytother. Res.,  2012, 26(6), 926-931.
[http://dx.doi.org/10.1002/ptr.3666] [PMID: 22105918] 
[31] 
Mhaidat, N.M.; Zhang, X.D.; Jiang, C.C.; Hersey, P. Docetaxel-induced apoptosis of human melanoma is mediated by activation of c-Jun NH2-terminal kinase and inhibited by the mitogen-activated protein kinase extracellular signal-regulated kinase 1/2 pathway. Clin. Cancer Res.,  2007, 13(4), 1308-1314.
[http://dx.doi.org/10.1158/1078-0432.CCR-06-2216] [PMID: 17317842] 
[32] 
Abu Hammad, A.M.; Taha, M.O. Pharmacophore modeling, quantitative structure-activity relationship analysis, and shape-complemented in silico screening allow access to novel influenza neuraminidase inhibitors. J. Chem. Inf. Model.,  2009, 49(4), 978-996.
[http://dx.doi.org/10.1021/ci8003682] [PMID: 19341295] 
[33] 
Al-Masri, I.M.; Mohammad, M.K.; Taha, M.O. Discovery of DPP IV inhibitors by pharmacophore modeling and QSAR analysis followed by in silico screening. ChemMedChem,  2008, 3(11), 1763-1779.
[http://dx.doi.org/10.1002/cmdc.200800213] [PMID: 18989859] 
[34] 
Al-Nadaf, A.; Abu Sheikha, G.; Taha, M.O. Elaborate ligand-based pharmacophore exploration and QSAR analysis guide the synthesis of novel pyridinium-based potent β-secretase inhibitory leads. Bioorg. Med. Chem.,  2010, 18(9), 3088-3115.
[http://dx.doi.org/10.1016/j.bmc.2010.03.043] [PMID: 20378363] 
[35] 
Al-Sha’er, M.A.; Taha, M.O. Discovery of novel CDK1 inhibitors by combining pharmacophore modeling, QSAR analysis and in silico screening followed by in vitro bioassay. Eur. J. Med. Chem.,  2010, 45(9), 4316-4330.
[http://dx.doi.org/10.1016/j.ejmech.2010.06.034] [PMID: 20638755] 
[36] 
Al-Sha’er, M.A.; VanPatten, S.; Al-Abed, Y.; Taha, M.O. Elaborate ligand-based modeling reveal new migration inhibitory factor inhibitors. J. Mol. Graph. Model.,  2013, 42, 104-114.
[http://dx.doi.org/10.1016/j.jmgm.2013.03.003] [PMID: 23603608] 
[37] 
Al-Sha’er, M.A.; Taha, M.O. Elaborate ligand-based modeling reveals new nanomolar heat shock protein 90α inhibitors. J. Chem. Inf. Model.,  2010, 50(9), 1706-1723.
[http://dx.doi.org/10.1021/ci100222k] [PMID: 20831219] 
[38] 
Al-Sha’er, M.A.; Khanfar, M.A.; Taha, M.O. Discovery of novel urokinase plasminogen activator (uPA) inhibitors using ligand-based modeling and virtual screening followed by in vitro analysis. J. Mol. Model.,  2014, 20(1), 2080.
[http://dx.doi.org/10.1007/s00894-014-2080-4] [PMID: 24469103] 
[39] 
Taha, M.O.; Dahabiyeh, L.A.; Bustanji, Y.; Zalloum, H.; Saleh, S. Combining ligand-based pharmacophore modeling, quantitative structure-activity relationship analysis and in silico screening for the discovery of new potent hormone sensitive lipase inhibitors. J. Med. Chem.,  2008, 51(20), 6478-6494.
[http://dx.doi.org/10.1021/jm800718k] [PMID: 18808096] 
[40] 
Shahin, R.; Mansi, I.; Swellmeen, L.; Alwidyan, T.; Al-Hashimi, N.; Al-Qarar’h, Y.; Shaheen, O. Ligand-based computer aided drug design reveals new tropomycin receptor kinase a (TrkA) inhibitors. J. Mol. Graph. Model.,  2018, 80, 327-352.
[http://dx.doi.org/10.1016/j.jmgm.2018.01.004] [PMID: 29454290] 
[41] 
Al-Sha’er, M.A.; Khanfar, M.A.; Taha, M.O. Discovery of Check Point Kinase 1 (Chk1) inhibitors as potential anticancer agents using ligand-based modelling and virtual screening. J. Silico Vitr. Pharmacol.,  2015, 1, 1-11.
[http://dx.doi.org/10.21767/2469-6692.10006] 
[42] 
Najafov, A.; Sommer, E.M.; Axten, J.M.; Deyoung, M.P.; Alessi, D.R. Characterization of GSK2334470, a novel and highly specific inhibitor of PDK1. Biochem. J.,  2011, 433(2), 357-369.
[http://dx.doi.org/10.1042/BJ20101732] [PMID: 21087210] 
[43] 
Gu, Y.; Liu, S-L.; Ju, W.Z.; Li, C.Y.; Cao, P. Analgesic-antitumor peptide induces apoptosis and inhibits the proliferation of SW480 human colon cancer cells. Oncol. Lett.,  2012, 5, 483-488.

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DOI https://dx.doi.org/10.2174/1871520620666191224110600	Print ISSN 1871-5206
Publisher Name Bentham Science Publisher	Online ISSN 1875-5992

Anti-Cancer Agents in Medicinal Chemistry

Ligand Based Pharmacophore Modeling Followed by Biological Screening Lead to Discovery of Novel PDK1 Inhibitors as Anticancer Agents

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