Discovery of potent IRAK-4 inhibitors as potential anti-inflammatory and anticancer agents using structure-based exploration of IRAK-4 pharmacophoric space coupled with QSAR analyses

Computational Biology and Chemistry

Volumn 79, Issue , 2019, Pages 147-154

  Khanfar, Mohammad A ^a,b   Alqtaishat, Saja ^c  

^a HEINRICH HEINE UNIVERSITY   (Germany)

^b ALFAISAL UNIVERSITY   (Saudi Arabia)

^c UNIVERSITY OF JORDAN   (Jordan)

Author keywords

IRAK 4; Pharmacophore; QSAR; Virtual screening

Indexed keywords

3D MODELING; LINEAR REGRESSION; MOLECULAR GRAPHICS; PHARMACODYNAMICS; SCAFFOLDS;

IRAK-4; MULTIPLE LINEAR REGRESSIONS; PHARMACOPHORES; PHYSIO-CHEMICAL PROPERTIES; PHYSIOCHEMICAL DESCRIPTORS; QSAR; RECEIVER OPERATING CHARACTERISTIC CURVES; VIRTUAL SCREENING;

COMPUTATIONAL CHEMISTRY;

ANTINEOPLASTIC AGENT; INTERLEUKIN 1 RECEPTOR ASSOCIATED KINASE; IRAK4 PROTEIN, HUMAN; NONSTEROID ANTIINFLAMMATORY AGENT; PROTEIN KINASE INHIBITOR;

ANTAGONISTS AND INHIBITORS; CHEMICAL STRUCTURE; CHEMISTRY; DOSE RESPONSE; DRUG DEVELOPMENT; HUMAN; METABOLISM; MOLECULAR MODEL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; RECEIVER OPERATING CHARACTERISTIC; STATISTICAL MODEL; SYNTHESIS;

ANTI-INFLAMMATORY AGENTS, NON-STEROIDAL; ANTINEOPLASTIC AGENTS; DOSE-RESPONSE RELATIONSHIP, DRUG; DRUG DISCOVERY; HUMANS; INTERLEUKIN-1 RECEPTOR-ASSOCIATED KINASES; LINEAR MODELS; MODELS, MOLECULAR; MOLECULAR STRUCTURE; PROTEIN KINASE INHIBITORS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; ROC CURVE;

EID: 85061981089     PISSN: 14769271     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compbiolchem.2019.02.005     Document Type: Article

References (26)

1. Bahia, M.S., Kaur, M., Silakari, P., Silakari, O., Interleukin-1 receptor associated kinase inhibitors: potential therapeutic agents for inflammatory- and immune-related disorders. Cell Signal. 27:6 (2015), 1039–1055.
2. Buckley, G.M., Gowers, L., Higueruelo, A.P., Jenkins, K., Mack, S.R., Morgan, T., Parry, D.M., Pitt, W.R., Rausch, O., Richard, M.D., Sabin, V., Fraser, J.L., IRAK-4 inhibitors. Part 1: a series of amides. Bioorg. Med. Chem. Lett. 18:11 (2008), 3211–3214.
3. Buckley, G.M., Ceska, T.A., Fraser, J.L., Gowers, L., Groom, C.R., Higueruelo, A.P., Jenkins, K., Mack, S.R., Morgan, T., Parry, D.M., Pitt, W.R., Rausch, O., Richard, M.D., Sabin, V., IRAK-4 inhibitors. Part II: a structure-based assessment of imidazo[1,2-a]pyridine binding. Bioorg. Med. Chem. Lett. 18:11 (2008), 3291–3295.
4. Buckley, G.M., Fosbeary, R., Fraser, J.L., Gowers, L., Higueruelo, A.P., James, L.A., Jenkins, K., Mack, S.R., Morgan, T., Parry, D.M., Pitt, W.R., Rausch, O., Richard, M.D., Sabin, V., IRAK-4 inhibitors. Part III: a series of imidazo[1,2-a]pyridines. Bioorg. Med. Chem. Lett. 18:12 (2008), 3656–3660.
5. Chaudhary, D., Robinson, S., Romero, D.L., Recent advances in the discovery of small molecule inhibitors of interleukin-1 receptor-associated kinase 4 (IRAK4) as a therapeutic target for inflammation and oncology disorders. J. Med. Chem. 58:1 (2015), 96–110.
6. Flannery, S., Bowie, A.G., The interleukin-1 receptor-associated kinases: critical regulators of innate immune signalling. Biochem. Pharmacol. 80:12 (2010), 1981–1991.
7. Jain, A., Kaczanowska, S., Davila, E., IL-1 receptor-associated kinase signaling and its role in inflammation, cancer progression, and therapy resistance. Front. Immunol., 5, 2014, 553.
8. Kawagoe, T., Sato, S., Matsushita, K., Kato, H., Matsui, K., Kumagai, Y., Saitoh, T., Kawai, T., Takeuchi, O., Akira, S., Sequential control of Toll-like receptor-dependent responses by IRAK1 and IRAK2. Nat. Immunol. 9:6 (2008), 684–691.
9. Khanfar, M.A., Taha, M.O., Elaborate ligand-based modeling coupled with multiple linear regression and k nearest neighbor QSAR analyses unveiled new nanomolar mTOR inhibitors. J. Chem. Inf. Model. 53:10 (2013), 2587–2612.
10. Khanfar, M.A., Taha, M.O., Unsupervised pharmacophore modeling combined with QSAR analyses revealed novel low micromolar SIRT2 inhibitors. J. Mol. Recognit., 30(9), 2017.
11. Khanfar, M.A., Al-Qtaishat, S., Habash, M., Taha, M.O., Discovery of potent adenosine A2a antagonists as potential anti-Parkinson disease agents. Non-linear QSAR analyses integrated with pharmacophore modeling. Chem. Biol. Interact. 254 (2016), 93–101.
12. Khanfar, M.A., Banat, F., Alabed, S., Alqtaishat, S., Discovery of potent NEK2 inhibitors as potential anticancer agents using structure-based exploration of NEK2 pharmacophoric space coupled with QSAR analyses. Mol. Divers. 21:1 (2017), 187–200.
13. Li, S., Strelow, A., Fontana, E.J., Wesche, H., IRAK-4: a novel member of the IRAK family with the properties of an IRAK-kinase. Proc. Natl. Acad. Sci. U. S. A. 99:8 (2002), 5567–5572.
14. 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. 46:1–3 (2001), 3–26.
15. Medvedev, A.E., Lentschat, A., Kuhns, D.B., Blanco, J.C., Salkowski, C., Zhang, S., Arditi, M., Gallin, J.I., Vogel, S.N., Distinct mutations in IRAK-4 confer hyporesponsiveness to lipopolysaccharide and interleukin-1 in a patient with recurrent bacterial infections. J. Exp. Med. 198:4 (2003), 521–531.
16. Mera, W.A., Alzihlif, M., Taha, M.O., Khanfar, M.A., Discovery of potent Bruton's tyrosine kinase inhibitors using ligand based modeling. Anticancer Agents Med. Chem. 17:2 (2017), 265–275.
17. Ojha, P.K., Mitra, I., Das, R.N., Roy, K., Further exploring rm2 metrics for validation of QSPR models dataset. Chemom. Intell. Lab. Syst. 107:1 (2011), 194–205.
18. Roy, K., Mitra, I., Kar, S., Ojha, P.K., Das, R.N., Kabir, H., Comparative studies on some metrics for external validation of QSPR models. J. Chem. Inf. Model. 52:2 (2012), 396–408.
19. Shoichet, B.K., Interpreting steep dose-response curves in early inhibitor discovery. J. Med. Chem. 49:25 (2006), 7274–7277.
20. Srivastava, R., Geng, D., Liu, Y., Zheng, L., Li, Z., Joseph, M.A., McKenna, C., Bansal, N., Ochoa, A., Davila, E., Augmentation of therapeutic responses in melanoma by inhibition of IRAK-1,-4. Cancer Res. 72:23 (2012), 6209–6216.
21. Suhir, H., Etzioni, A., The role of Toll-like receptor signaling in human immunodeficiencies. Clin. Rev. Allergy Immunol. 38:1 (2010), 11–19.
22. Suzuki, N., Suzuki, S., Duncan, G.S., Millar, D.G., Wada, T., Mirtsos, C., Takada, H., Wakeham, A., Itie, A., Li, S., Penninger, J.M., Wesche, H., Ohashi, P.S., Mak, T.W., Yeh, W.C., Severe impairment of interleukin-1 and Toll-like receptor signalling in mice lacking IRAK-4. Nature 416:6882 (2002), 750–756.
23. Triballeau, N., Acher, F., Brabet, I., Pin, J.P., Bertrand, H.O., Virtual screening workflow development guided by the “receiver operating characteristic” curve approach. Application to high-throughput docking on metabotropic glutamate receptor subtype 4. J. Med. Chem. 48:7 (2005), 2534–2547.
24. 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. 45:12 (2002), 2615–2623.
25. Verdonk, M.L., Berdini, V., Hartshorn, M.J., Mooij, W.T., Murray, C.W., Taylor, R.D., Watson, P., Virtual screening using protein-ligand docking: avoiding artificial enrichment. J Chem. Inf. Comput. Sci. 44:3 (2004), 793–806.
26. Wang, Z., Wesche, H., Stevens, T., Walker, N., Yeh, W.C., IRAK-4 inhibitors for inflammation. Curr. Top. Med. Chem. 9:8 (2009), 724–737.