IDENTIFICATION AND IN SILICO ANALYSIS OF INHIBITOR ON THE WNT/β-CATENIN SIGNALING PATHWAY AS POTENTIAL DRUG FOR COLON CANCER

SALBIAH RIDWAN; LINDA ERLINA; ANTON BAHTIAR; DEWI SUKMAWATI

doi:10.22159/ijap.2023v15i1.46570

Authors

SALBIAH RIDWAN Department of Pharmacology, Faculty of Pharmacy, Universitas Indonesia, Gedung Fakultas Farmasi Kampus UI Depok 16424, Indonesia https://orcid.org/0000-0001-6035-2268
LINDA ERLINA Department of Medicinal Chemistry, Faculty of Medicine, Universitas Indonesia, Jl. Salemba Raya No. 6, Indonesia
ANTON BAHTIAR Department of Pharmacology, Faculty of Pharmacy, Universitas Indonesia, Gedung Fakultas Farmasi Kampus UI Depok 16424, Indonesia https://orcid.org/0000-0002-2924-3677
DEWI SUKMAWATI Department of Histology, Faculty of Medicine, Universitas Indonesia, Jl. Salemba Raya No. 6, Indonesia

DOI:

https://doi.org/10.22159/ijap.2023v15i1.46570

Keywords:

Colon cancer, Wnt/β-catenin signaling pathway, Protein-protein interaction network, Pharmacophore modeling, DNA, Guanidine, Adenine, 6-aminothiouracil, Hydrazonoyl halides, Thiadiazole, Phenylisocyanate, Molecular docking

Abstract

Objective: We aimed to predict the PPI network and in silico analysis of a drug that can potentially inhibit colon cancer, specifically in the Wnt/β-catenin signaling pathway, based on pharmacophore modeling and molecular docking.

Methods: Target genes involved in colon development were screened for specific genes in the Wnt/b-catenin signaling pathway. Tissue construction and possible signaling pathways were analyzed using protein-protein interactions. Genes with significant centrality and best-grade values were made to feature pharmacophore models and their suitability for potential drugs. Validation was carried out using the molecular docking method for interaction with the best Hits.

Results: Protein-Protein Interaction Network (PPI) revealed BTNNB1, TP53, AXIN, FZD-8, and CDK1 as potential critical targets in the Wnt/β-catenin signaling pathway and from the suitability of pharmacophore features obtained 27 drugs as the best Hit compounds. The therapeutic effects of the drugs we found were shown to be related to the synergistic activity (multitarget and multi-path). GO enrichment analysis revealed 36 GO entries, including 11 biological processes, 10 cellular components, and 15 molecular functions. Molecular docking experiments confirmed the correlation between three drugs (Clofazimine, Closantel, and Sulindac) with the best binding to 4 target proteins (AXIN1, TP53, CDK1, and FZD-8).

Conclusion: In this study, we found a potent drug that can inhibit colon cancer disease in the Wnt/β-catenin signaling pathway and an essential target protein responsible for the efficacy of colon cancer treatment, providing a theoretical basis for further research.

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References

Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F. Cancer statistics in China, 2015. CA Cancer J Clin. 2016;66(2):115-32. doi: 10.3322/caac.21338, PMID 26808342.

Church J. Molecular genetics of colorectal cancer. Semin Colon Rect Surg. 2016;27(4):172-5. doi: 10.1053/j.scrs.2016.04.013.

Dekker E, Tanis PJ, Vleugels JLA, Kasi PM, Wallace MB. Colorectal cancer. Lancet. 2019;394(10207):1467-80, doi: 10.1016/S0140-6736(19)32319-0.

Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209-49. doi: 10.3322/caac.21660, PMID 33538338.

Pangribowo S, Kanker B. di Indonesia. Pus Data Dan Inf Kesehat Kementeri Kesehat RI; 2019. p. 1-16.

Koncina E, Haan S, Rauh S, Letellier E. Prognostic and predictive molecular biomarkers for colorectal cancer: updates and challenges. Cancers (Basel). 2020;12(2):1-25. doi: 10.3390/cancers12020319, PMID 32019056.

Salik B, Yi H, Hassan N, Santiappillai N, Vick B, Connerty P. Targeting RSPO3-LGR4 signaling for leukemia stem cell eradication in acute myeloid leukemia. Cancer Cell. 2020;38(2):263-278.e6. doi: 10.1016/j.ccell.2020.05.014, PMID 32559496.

Soleas JP, D’Arcangelo E, Huang L, Karoubi G, Nostro MC, McGuigan AP. Assembly of lung progenitors into developmentally inspired geometry drives differentiation via cellular tension. Biomaterials. 2020;254(May):120128. doi: 10.1016/j.biomaterials.2020.120128. PMID 32474250.

Zhang Y, Wang X. Targeting the Wnt/β-catenin signaling pathway in cancer. J Hematol Oncol. 2020;13(1):165. doi: 10.1186/s13045-020-00990-3, PMID 33276800.

Xie YH, Chen YX, Fang JY. Comprehensive review of targeted therapy for colorectal cancer. Signal Transduct Target Ther. 2020;5(1):22. doi: 10.1038/s41392-020-0116-z, PMID 32296018.

Safran M, Rosen N, Twik M, BarShir R, Stein TI, Dahary D. The gene cards suite. Pract Guide to Life Sci Databases; 2021. p. 27-56.

Stelzer G, Rosen N, Plaschkes I, Zimmerman S, Twik M, Fishilevich S. The GeneCards suite: from gene data mining to disease genome sequence analyses. Curr Protoc Bioinformatics. 2016;54:1.30.1-1.30.33. doi: 10.1002/cpbi.5, PMID 27322403.

Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498-504. doi: 10.1101/gr.1239303, PMID 14597658.

Jensen LJ, Kuhn M, Stark M, Chaffron S, Creevey C, Muller J. STRING 8-A global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res. 2009;37Suppl 1:D412-6. doi: 10.1093/nar/gkn760, PMID 18940858.

Kuhn M, von Mering C, Campillos M, Jensen LJ, Bork P. STITCH: interaction networks of chemicals and proteins. Nucleic Acids Res. 2008;36Suppl 1:D684-8. doi: 10.1093/nar/gkm795, PMID 18084021.

Kim S, Chen J, Cheng T, Gindulyte A, He J, He S. PubChem in 2021: new data content and improved web interfaces. Nucleic Acids Res. 2021;49(D1):D1388-95. doi: 10.1093/nar/gkaa971, PMID 33151290.

Wolber G, Langer T. LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters. J Chem Inf Model. 2005;45(1):160-9. doi: 10.1021/ci049885e, PMID 15667141.

Kessler D, Mayer M, Zahn SK, Zeeb M, Wohrle S, Bergner A. Getting a grip on the undrugged: targeting β-catenin with fragment-based methods. ChemMedChem. 2021;16(9):1420-4. doi: 10.1002/cmdc.202000839, PMID 33275320.

Fugel W, Oberholzer AE, Gschloessl B, Dzikowski R, Pressburger N, Preu L, et al. Fugel 2013HYDE. J Med Chem. 2012;56(1).

Dai Y, Zhang A, Shan S, Gong Z, Zhou Z. Structural basis for recognition of 53BP1 tandem Tudor domain by TIRR. Nat Commun. 2018;9(1):2123. doi: 10.1038/s41467-018-04557-2, PMID 29844495.

Madej T, Lanczycki CJ, Zhang D, Thiessen PA, Geer RC, Marchler Bauer A. MMDB and VAST+: tracking structural similarities between macromolecular complexes. Nucleic Acids Res. 2014;42:D297-303. doi: 10.1093/nar/gkt1208. PMID 24319143.

Zhao Y, Ren J, Hillier J, Lu W, Jones EY. Antiepileptic drug carbamazepine binds to a novel pocket on the Wnt receptor Frizzled-8. J Med Chem. 2020;63(6):3252-60. doi: 10.1021/acs.jmedchem.9b02020, PMID 32049522.

Scott DE, Ehebauer MT, Pukala T, Marsh M, Blundell TL, Venkitaraman AR. Using a fragment-based approach to target protein-protein interactions. ChemBioChem. 2013;14(3):332-42. doi: 10.1002/cbic.201200521, PMID 23344974.

Dassault Systemes BIOVIA. Discovery studio modeling environment. Release 2021. Dassault Systemes: San Diego. CA; 2021.

Dallakyan S, Olson AJ. Small-molecule library screening by docking with PyRx. Methods Mol Biol. 2015;1263:243-50. doi: 10.1007/978-1-4939-2269-7_19, PMID 25618350.

Chen C, Wang T, Wu F, Huang W, He G, Ouyang L. Combining structure-based pharmacophore modeling, virtual screening, and in silico ADMET analysis to discover novel tetrahydro-quinoline based pyruvate kinase isozyme M2 activators with antitumor activity. Drug Des Devel Ther. 2014;8:1195-210. doi: 10.2147/DDDT.S62921, PMID 25214764.

Zappavigna S, Cossu AM, Grimaldi A, Bocchetti M, Ferraro GA, Nicoletti GF. Anti-inflammatory drugs as anticancer agents. Int J Mol Sci. 2020;21(7):1-29. doi: 10.3390/ijms21072605, PMID 32283655.

Durusu İZ, Husnugil HH, Atas H, Biber A, Gerekci S, Gulec EA. Anti-cancer effect of clofazimine as a single agent and in combination with cisplatin on U266 multiple myeloma cell line. Leuk Res. 2017;55:33-40. doi: 10.1016/j.leukres.2017.01.019, PMID 28122281.

Nowak Sliwinska P, Scapozza L, Ruiz I Altaba A. Drug repurposing in oncology: Compounds, pathways, phenotypes and computational approaches for colorectal cancer. Biochim Biophys Acta Rev Cancer. 2019;1871(2):434-54. doi: 10.1016/j.bbcan.2019.04.005. PMID 31034926.

Zhao R, Coker OO, Wu J, Zhou Y, Zhao L, Nakatsu G. Aspirin reduces colorectal tumor development in mice and gut microbes reduce its bioavailability and chemopreventive effects. Gastroenterology. 2020;159(3):969-83.e4. doi: 10.1053/j.gastro.2020.05.004. PMID 32387495.

Koveitypour Z, Panahi F, Vakilian M, Peymani M, Seyed Forootan F, Nasr Esfahani MH. Signaling pathways involved in colorectal cancer progression. Cell Biosci. 2019;9(1):97. doi: 10.1186/s13578-019-0361-4, PMID 31827763.

Zhang X, Wang L, Qu Y. Targeting the β-catenin signaling for cancer therapy. Pharmacol Res. 2020;160:104794. doi: 10.1016/j.phrs.2020.104794, PMID 32278038.

Nazemalhosseini Mojarad E, Kashfi SMH, Mirtalebi H, Almasi S, Chaleshi V, Kishani Farahani R. Prognostic significance of nuclear β-catenin expression in patients with colorectal cancer from Iran. Iran Red Crescent Med J. 2015;17(7):e22324. doi: 10.5812/ircmj.22324v2, PMID 26421170.

Zhao H, Ming T, Tang S, Ren S, Yang H, Liu M. Wnt signaling in colorectal cancer: pathogenic role and therapeutic target. Mol Cancer. 2022;21(1):144. doi: 10.1186/s12943-022-01616-7, PMID 35836256.

Malumbres M. Cyclin-dependent kinases. Genome Biol. 2014;15(6):122. doi: 10.1186/gb4184, PMID 25180339.

Li J, Wang Y, Wang X, Yang Q. CDK1 and CDC20 overexpression in patients with colorectal cancer are associated with poor prognosis: evidence from integrated bioinformatics analysis. World J Surg Oncol. 2020;18(1):50. doi: 10.1186/s12957-020-01817-8. PMID 32127012.

Dong S, Huang F, Zhang H, Chen Q. Tumor tissues predicts poor survival in pancreatic ductal adenocarcinoma. Gene 2019;15:1-10.

Wu CX, Wang XQ, Chok SH, Man K, Tsang SHY, Chan ACY. Blocking CDK1/PDK1/β-catenin signaling by CDK1 inhibitor RO3306 increased the efficacy of sorafenib treatment by targeting cancer stem cells in a preclinical model of hepatocellular carcinoma. Theranostics. 2018;8(14):3737-50. doi: 10.7150/thno.25487, PMID 30083256.

Huang J, Chen P, Liu K, Liu J, Zhou B, Wu R. CDK1/2/5 inhibition overcomes IFNG-mediated adaptive immune resistance in pancreatic cancer. Gut. 2021;70(5):890-9. doi: 10.1136/gutjnl-2019-320441, PMID 32816920.

Zhu Y, Li K, Zhang J, Wang L, Sheng L, Yan L. Inhibition of cdk1 reverses the resistance of 5-fu in colorectal cancer. Cancer Manag Res. 2020;12:11271-83. doi: 10.2147/CMAR.S255895, PMID 33177877.

Williams DS, Mouradov D, Browne C, Palmieri M, Elliott MJ, Nightingale R. Overexpression of TP53 protein is associated with the lack of adjuvant chemotherapy benefit in patients with stage III colorectal cancer. Mod Pathol. 2020;33(3):483-95. doi: 10.1038/s41379-019-0353-2, PMID 31471586.

Fearon RE, Vogelstein B. A genetic model for colorectal tumorgenesis. G Ital Cardiol. 1990;19(2):170-2.

Alrefaei AF. Frizzled receptors (FZD) play multiple cellular roles in development, in diseases, and as potential therapeutic targets. Journal of King Saud University–Science. 2021;33:101613. doi: 10.1016/j.jksus.2021.101613.

Murillo Garzon V, Gorrono Etxebarria I, Akerfelt M, Puustinen MC, Sistonen L, Nees M. Frizzled-8 integrates Wnt-11 and transforming growth factor-β signaling in prostate cancer. Nat Commun. 2018;9(1):1747. doi: 10.1038/s41467-018-04042-w, PMID 29717114.

Kurnit KC, Kim GN, Fellman BM, Urbauer DL, Mills GB, Zhang W. CTNNB1 (beta-catenin) mutation identifies low grade, early stage endometrial cancer patients at increased risk of recurrence. Mod Pathol. 2017;30(7):1032-41. doi: 10.1038/modpathol.2017.15, PMID 28281553.

Santos VS, Lago NM, Garcia CP, Garcia AP, Apricio LMA. Signaling pathways in CRC. In: Sierra AP, editor. Foundations of colorectal cancer. 1st ed. Academic Press Inc; 2022. p. 519-28.

Farooqi AA, de la Roche M, Djamgoz MBA, Siddik ZH. Overview of the oncogenic signaling pathways in colorectal cancer: mechanistic insights. Semin Cancer Biol. 2019;58:65-79. doi: 10.1016/j.semcancer.2019.01.001. PMID 30633978.