Generic placeholder image

Letters in Drug Design & Discovery

Author(s): Vivek Yadav*, Rajiv Kumar Tonk and Ramchander Khatri

DOI: 10.2174/1570180817999201123163617

DownloadDownload PDF Flyer Cite As
Molecular Docking, 3D-QSAR, Fingerprint-Based 2D-QSAR, Analysis of Pyrimidine, and Analogs of ALK (Anaplastic Lymphoma Kinase) Inhibitors as an Anticancer Agent

Page: [509 - 521] Pages: 13

  • * (Excluding Mailing and Handling)

Abstract

Background: ALK inhibitors have become a plausible option for anticancer therapy with the availability of several FDA-approved molecules and clinical trial candidates. Hence, the design of new ALK inhibitors using computational molecular docking studies on the existing inhibitors, is an attractive approach for anticancer drug discovery.

Methods: We generated six types of independent models through structural based molecular docking study, three-dimensional quantitative structure-activity relationship (3D-QSAR) study, and 2DQSAR approaches using different fingerprints, such as dendritic, linear, 2D molprint, and radial.

Results: Comparison of the generated models showed that the hinge region hydrogen bond interacted with amino acids ASP1206, MET1199, and LYS1150 in docking analysis and the hydrophobic interacted with amino acids GLU1210, ARG1209, SER1206, and LYS1205 residues are responsible for the ALK inhibition. In the 3D-QSAR study, the hydrogen bond donor features of 2,4- diaryl aminopyrimidine substituents, isopropyl phenyl ring groups in hydrophobic features, and electron-withdrawing groups matched the generated contour plots. The 2D-QSAR fingerprint studies indicated that higher potency was associated with the 2-hydroxy-5-isopropyl benzamide functional group and substituted phenylamine at the second position of the pyrimidine group.

Conclusion: We conclude that the incorporation of these functional groups in the design of new molecules may result in more potent ALK inhibitors.

Keywords: ALK inhibitor, molecular docking, 3D-QSAR, fingerprint, 2-4-diarylamino pyrimidines, 2D-QSAR, anaplastic lymphoma kinase.

Graphical Abstract

[1]
Higano, C.S.; Chielens, D.; Raskind, W.; Bryant, E.; Flowers, M.E.; Radich, J.; Clift, R.; Appelbaum, F. Use of alpha-2a-interferon to treat cytogenetic relapse of chronic myeloid leukemia after marrow transplantation. Blood, 1997, 90(7), 2549-2554.
[http://dx.doi.org/10.1182/blood.V90.7.2549] [PMID: 9326220]
[2]
Johnson, T.W.; Richardson, P.F.; Bailey, S.; Brooun, A.; Burke, B.J.; Collins, M.R.; Cui, J.J.; Deal, J.G.; Deng, Y.L.; Dinh, D.; Engstrom, L.D.; He, M.; Hoffman, J.; Hoffman, R.L.; Huang, Q.; Kania, R.S.; Kath, J.C.; Lam, H.; Lam, J.L.; Le, P.T.; Lingardo, L.; Liu, W.; McTigue, M.; Palmer, C.L.; Sach, N.W.; Smeal, T.; Smith, G.L.; Stewart, A.E.; Timofeevski, S.; Zhu, H.; Zhu, J.; Zou, H.Y.; Edwards, M.P. Discovery of (10R)-7-amino-12-fluoro-2,10,16-trimethyl-15-oxo-10,15,16,17-tetrahydro-2H-8,4-(metheno)pyrazolo[4,3-h][2,5,11]-benzoxadiazacyclotetradecine-3-carbonitrile (PF-06463922), a macrocyclic inhibitor of anaplastic lymphoma kinase (ALK) and c-ros oncogene 1 (ROS1) with preclinical brain exposure and broad-spectrum potency against ALK-resistant mutations. J. Med. Chem., 2014, 57(11), 4720-4744.
[http://dx.doi.org/10.1021/jm500261q] [PMID: 24819116]
[3]
Du, X.; Shao, Y.; Qin, H.F.; Tai, Y.H.; Gao, H.J. ALK-rearrangement in non-small-cell lung cancer (NSCLC). Thorac. Cancer, 2018, 9(4), 423-430.
[http://dx.doi.org/10.1111/1759-7714.12613] [PMID: 29488330]
[4]
Liu, S.; Jiang, Y.; Yan, R.; Li, Z.; Wan, S.; Zhang, T.; Wu, X.; Hou, J.; Zhu, Z.; Tian, Y.; Zhang, J. Design, synthesis and biological evaluations of 2-amino-4-(1-piperidine) pyridine derivatives as novel anti crizotinib-resistant ALK/ROS1 dual inhibitors. Eur. J. Med. Chem., 2019, 179, 358-375.
[http://dx.doi.org/10.1016/j.ejmech.2019.06.043] [PMID: 31260890]
[5]
Morris, S.W.; Kirstein, M.N.; Valentine, M.B.; Dittmer, K.G.; Shapiro, D.N.; Saltman, D.L.; Look, A.T. Fusion of a kinase gene, ALK, to a nucleolar protein gene, NPM, in non-Hodgkin’s lymphoma. Science, 1994, 263(5151), 1281-1284.
[http://dx.doi.org/10.1126/science.8122112] [PMID: 8122112]
[6]
Soda, M.; Choi, Y.L.; Enomoto, M.; Takada, S.; Yamashita, Y.; Ishikawa, S.; Fujiwara, S.; Watanabe, H.; Kurashina, K.; Hatanaka, H.; Bando, M.; Ohno, S.; Ishikawa, Y.; Aburatani, H.; Niki, T.; Sohara, Y.; Sugiyama, Y.; Mano, H. Identification of the transforming EML4-ALK fusion gene in non-small-cell lung cancer. Nature, 2007, 448(7153), 561-566.
[http://dx.doi.org/10.1038/nature05945] [PMID: 17625570]
[7]
Solomon, B.; Wilner, K.D.; Shaw, A.T. Current status of targeted therapy for anaplastic lymphoma kinase-rearranged non-small cell lung cancer. Clin. Pharmacol. Ther., 2014, 95(1), 15-23.
[http://dx.doi.org/10.1038/clpt.2013.200] [PMID: 24091716]
[8]
Basit, S.; Ashraf, Z.; Lee, K.; Latif, M. First macrocyclic 3rd-generation ALK inhibitor for treatment of ALK/ROS1 cancer: Clinical and designing strategy update of lorlatinib. Eur. J. Med. Chem., 2017, 134, 348-356.
[http://dx.doi.org/10.1016/j.ejmech.2017.04.032] [PMID: 28431340]
[9]
Ren, H.; Tan, Z.P.; Zhu, X.; Crosby, K.; Haack, H.; Ren, J.M.; Beausoleil, S.; Moritz, A.; Innocenti, G.; Rush, J.; Zhang, Y.; Zhou, X.M.; Gu, T.L.; Yang, Y.F.; Comb, M.J. Identification of anaplastic lymphoma kinase as a potential therapeutic target in ovarian cancer. Cancer Res., 2012, 72(13), 3312-3323.
[http://dx.doi.org/10.1158/0008-5472.CAN-11-3931] [PMID: 22570254]
[10]
Sakamoto, H.; Tsukaguchi, T.; Hiroshima, S.; Kodama, T.; Kobayashi, T.; Fukami, T.A.; Oikawa, N.; Tsukuda, T.; Ishii, N.; Aoki, Y. CH5424802, a selective ALK inhibitor capable of blocking the resistant gatekeeper mutant. Cancer Cell, 2011, 19(5), 679-690.
[http://dx.doi.org/10.1016/j.ccr.2011.04.004] [PMID: 21575866]
[11]
Cui, J.J.; Tran-Dubé, M.; Shen, H.; Nambu, M.; Kung, P.P.; Pairish, M.; Jia, L.; Meng, J.; Funk, L.; Botrous, I.; McTigue, M.; Grodsky, N.; Ryan, K.; Padrique, E.; Alton, G.; Timofeevski, S.; Yamazaki, S.; Li, Q.; Zou, H.; Christensen, J.; Mroczkowski, B.; Bender, S.; Kania, R.S.; Edwards, M.P. Structure based drug design of crizotinib (PF-02341066), a potent and selective dual inhibitor of mesenchymal-epithelial transition factor (c-MET) kinase and anaplastic lymphoma kinase (ALK). J. Med. Chem., 2011, 54(18), 6342-6363.
[http://dx.doi.org/10.1021/jm2007613] [PMID: 21812414]
[12]
Levitzki, A. Tyrosine kinases as targets for cancer therapy. Eur. J. Cancer, 2002, 38(Suppl. 5), S11-S18.
[http://dx.doi.org/10.1016/S0959-8049(02)80598-6] [PMID: 12528768]
[13]
Roskoski, R. Jr Anaplastic lymphoma kinase (ALK) inhibitors in the treatment of ALK-driven lung cancers. Pharmacol. Res., 2017, 117, 343-356.
[http://dx.doi.org/10.1016/j.phrs.2017.01.007] [PMID: 28077299]
[14]
Costa, D.B.; Shaw, A.T.; Ou, S.H.I.; Solomon, B.J.; Riely, G.J.; Ahn, M.J.; Zhou, C.; Shreeve, S.M.; Selaru, P.; Polli, A.; Schnell, P.; Wilner, K.D.; Wiltshire, R.; Camidge, D.R.; Crinò, L. Clinical experience with crizotinib in patients with advanced alk-rearranged non-small-cell lung cancer and brain metastases. J. Clin. Oncol., 2015, 33(17), 1881-1888.
[http://dx.doi.org/10.1200/JCO.2014.59.0539] [PMID: 25624436]
[15]
Akamine, T.; Toyokawa, G.; Tagawa, T.; Yamazaki, K.; Seto, T.; Takeo, S.; Mori, M. Lorlatinib for the treatment of patients with non-small cell lung cancer. Drugs Today (Barc), 2019, 55(2), 107-116.
[http://dx.doi.org/10.1358/dot.2019.55.2.2927983] [PMID: 30816885]
[16]
Syed, Y.Y. Lorlatinib: First global approval. Drugs, 2019, 79(1), 93-98.
[http://dx.doi.org/10.1007/s40265-018-1041-0] [PMID: 30604291]
[17]
Geng, K.; Xia, Z.; Ji, Y.; Zhang, R.R.; Sun, D.; Ai, J.; Song, Z.; Geng, M.; Zhang, A. Discovery of 2,4-diarylaminopyrimidines bearing a resorcinol motif as novel ALK inhibitors to overcome the G1202R resistant mutation. Eur. J. Med. Chem., 2018, 144, 386-397.
[http://dx.doi.org/10.1016/j.ejmech.2017.12.060] [PMID: 29288940]
[18]
Liu, Z.; Yue, X.; Song, Z.; Peng, X.; Guo, J.; Ji, Y.; Cheng, Z.; Ding, J.; Ai, J.; Geng, M.; Zhang, A. Design, synthesis and pharmacological evaluation of 2-(thiazol-2-amino)-4-arylaminopyrimidines as potent anaplastic lymphoma kinase (ALK) inhibitors. Eur. J. Med. Chem., 2014, 86(1), 438-448.
[http://dx.doi.org/10.1016/j.ejmech.2014.09.003] [PMID: 25200979]
[19]
Song, Z.; Yang, Y.; Liu, Z.; Peng, X.; Guo, J.; Yang, X.; Wu, K.; Ai, J.; Ding, J.; Geng, M.; Zhang, A. Discovery of novel 2,4-diarylaminopyrimidine analogues (DAAPalogues) showing potent inhibitory activities against both wild-type and mutant ALK kinases. J. Med. Chem., 2015, 58(1), 197-211.
[http://dx.doi.org/10.1021/jm5005144] [PMID: 24785465]
[20]
Geng, K.; Liu, H.; Song, Z.; Zhang, C.; Zhang, M.; Yang, H.; Cao, J.; Geng, M.; Shen, A.; Zhang, A. Design, synthesis and pharmacological evaluation of ALK and Hsp90 dual inhibitors bearing resorcinol and 2,4-diaminopyrimidine motifs. Eur. J. Med. Chem., 2018, 152, 76-86.
[http://dx.doi.org/10.1016/j.ejmech.2018.04.019] [PMID: 29698859]
[21]
Release, S. 2019-4: Maestro; Schrödinger, LLC: New York, NY, 2019.
[22]
Release, S. 2019-4: LigPrep; Schrödinger, LLC: New York, NY, 2019.
[23]
Greenwood, J.R.; Calkins, D.; Sullivan, A.P.; Shelley, J.C. Towards the comprehensive, rapid, and accurate prediction of the favorable tautomeric states of drug-like molecules in aqueous solution. J. Comput. Aided Mol. Des., 2010, 24(6-7), 591-604.
[http://dx.doi.org/10.1007/s10822-010-9349-1] [PMID: 20354892]
[24]
Shelley, J.C.; Cholleti, A.; Frye, L.L.; Greenwood, J.R.; Timlin, M.R.; Uchimaya, M. Epik: A software program for pK(a) prediction and protonation state generation for drug-like molecules. J. Comput. Aided Mol. Des., 2007, 21(12), 681-691.
[http://dx.doi.org/10.1007/s10822-007-9133-z] [PMID: 17899391]
[25]
Harder, E.; Damm, W.; Maple, J.; Wu, C.; Reboul, M.; Xiang, J.Y.; Wang, L.; Lupyan, D.; Dahlgren, M.K.; Knight, J.L.; Kaus, J.W.; Cerutti, D.S.; Krilov, G.; Jorgensen, W.L.; Abel, R.; Friesner, R.A. OPLS3: A force field providing broad coverage of drug-like small molecules and proteins. J. Chem. Theory Comput., 2016, 12(1), 281-296.
[http://dx.doi.org/10.1021/acs.jctc.5b00864] [PMID: 26584231]
[26]
Protein Data bank. Available at: https://www.rcsb.org/structure/4MKC Accessed 2019.
[27]
Sastry, G.M.; Adzhigirey, M.; Day, T.; Annabhimoju, R.; Sherman, W. Protein and ligand preparation: Parameters, protocols, and influence on virtual screening enrichments. J. Comput. Aided Mol. Des., 2013, 27(3), 221-234.
[http://dx.doi.org/10.1007/s10822-013-9644-8] [PMID: 23579614]
[28]
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.
[http://dx.doi.org/10.1021/jm051256o] [PMID: 17034125]
[29]
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.
[http://dx.doi.org/10.1007/s10822-006-9087-6] [PMID: 17124629]
[30]
Duan, J.; Sastry, M.; Dixon, S.L.; Lowrie, J.F.; Sherman, W. Analysis and comparison of 2D fingerprints: Insights into database screening performance using eight fingerprint methods. J. Cheminform., 2011, 3(Suppl. 1), 2946.
[http://dx.doi.org/10.1186/1758-2946-3-S1-P1]
[31]
Sastry, M.; Lowrie, J.F.; Dixon, S.L.; Sherman, W. Large-scale systematic analysis of 2D fingerprint methods and parameters to improve virtual screening enrichments. J. Chem. Inf. Model., 2010, 50(5), 771-784.
[http://dx.doi.org/10.1021/ci100062n] [PMID: 20450209]
[32]
Bender, A.; Mussa, H.Y.; Glen, R.C.; Reiling, S. Molecular similarity searching using atom environments, information-based feature selection, and a naïve Bayesian classifier. J. Chem. Inf. Comput. Sci., 2004, 44(1), 170-178.
[http://dx.doi.org/10.1021/ci034207y] [PMID: 14741025]
[33]
Bender, A.; Mussa, H.Y.; Glen, R.C.; Reiling, S. Similarity searching of chemical databases using atom environment descriptors (MOLPRINT 2D): Evaluation of performance. J. Chem. Inf. Comput. Sci., 2004, 44(5), 1708-1718.
[http://dx.doi.org/10.1021/ci0498719] [PMID: 15446830]
[34]
Rogers, D.; Brown, R.D.; Hahn, M. Using extended-connectivity fingerprints with Laplacian-modified Bayesian analysis in high-throughput screening follow-up. J. Biomol. Screen., 2005, 10(7), 682-686.
[http://dx.doi.org/10.1177/1087057105281365] [PMID: 16170046]