In-silico evidence of ADAM metalloproteinase pathology in cancer signaling networks

Reference

• Abraham, M. J., Murtola, T., Schulz, R., Páll, S., Smith, J. C., Hess, B., & Lindahl, E. (2015). Gromacs: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX, 1–2, 19–25. https://doi.org/10.1016/j.softx.2015.06.001
   Google Scholar
• Barabási, A. L., & Oltvai, Z. N. (2004). Network biology: Understanding the cell's functional organization. Nature Reviews. Genetics, 5(2), 101–113. https://doi.org/10.1038/nrg1272
   PubMed Web of Science ®Google Scholar
• Bozkulak, E. C., & Weinmaster, G. (2009). Selective use of ADAM10 and ADAM17 in activation of Notch1 signaling. Molecular and Cellular Biology, 29(21), 5679–5695. https://doi.org/10.1128/MCB.00406-09
   PubMed Web of Science ®Google Scholar
• Daina, A., Michielin, O., & Zoete, V. (2017). SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific Reports, 7(1), 1–1. https://doi.org/10.1038/srep42717
   PubMed Web of Science ®Google Scholar
• Dannenberg, J. J. (1998). An introduction to hydrogen bonding. Jounal of the American Chemical Society, 123(39), 1009–1011.
   Google Scholar
• Dasgupta, S., Murumkar, P. R., Giridhar, R., & Yadav, M. R. (2009). Current perspective of TACE inhibitors: A review. Bioorganic & Medicinal Chemistry, 17(2), 444–459. https://doi.org/10.1016/j.bmc.2008.11.067
   PubMed Web of Science ®Google Scholar
• Franceschini, A., Szklarczyk, D., Frankild, S., Kuhn, M., Simonovic, M., Roth, A., Lin, J., Minguez, P., Bork, P., von Mering, C., & Jensen, L. J. (2013). STRING v9.1: Protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Research, 41(Database issue), D808–D815. https://doi.org/10.1093/nar/gks1094
   PubMed Web of Science ®Google Scholar
• Gee, J. M. W., & Knowlden, J. M. (2003). ADAM metalloproteases and EGFR SIGNALLING. Breast Cancer Research: BCR, 5(5), 223–224. https://doi.org/10.1186/bcr637
   PubMed Web of Science ®Google Scholar
• Hartmann, D., de Strooper, B., Serneels, L., Craessaerts, K., Herreman, A., Annaert, W., Umans, L., Lübke, T., Lena Illert, A., von Figura, K., & Saftig, P. (2002). The disintegrin/metalloprotease ADAM 10 is essential for notch signalling but not for alpha-secretase activity in fibroblasts. Human Molecular Genetics, 11(21), 2615–2624. https://doi.org/10.1093/hmg/11.21.2615
   PubMed Web of Science ®Google Scholar
• Heath, E. I., Burtness, B. A., Kleinberg, L., Salem, R. R., Yang, S. C., Heitmiller, R. F., Canto, M. I., Knisely, J. P. S., Topazian, M., Montgomery, E., Tsottles, N., Pithavala, Y., Rohmiller, B., Collier, M., & Forastiere, A. A. (2006). Phase II, parallel-design study of preoperative combined modality therapy and the matrix metalloprotease (Mmp) inhibitor prinomastat in patients with esophageal adenocarcinoma. Investigational New Drugs, 24(2), 135–140. https://doi.org/10.1007/s10637-006-5934-5
   PubMed Web of Science ®Google Scholar
• Kumari, R., Kumar, R., & Lynn, A. (2014). g_mmpbsa-a GROMACS tool for high-throughput MM-PBSA calculations. Journal of Chemical Information and Modeling, 54(7), 1951–1962. https://doi.org/10.1021/ci500020m
   PubMed Web of Science ®Google Scholar
• Lemkul, J. (2019). From proteins to perturbed hamiltonians: A suite of tutorials for the GROMACS-2018 molecular simulation package. Living Journal of Computational Molecular Science, 1(1), 1–53. https://doi.org/10.33011/livecoms.1.1.5068
   Google Scholar
• Levin, J. I., Chen, J. M., Laakso, L. M., Du, M., Schmid, J., Xu, W., Cummons, T., Xu, J., Jin, G., Barone, D., & Skotnicki, J. S. (2006). Acetylenic TACE inhibitors. Part 3: Thiomorpholine sulfonamide hydroxamates. Bioorganic & Medicinal Chemistry Letters, 16(6), 1605–1609. https://doi.org/10.1016/j.bmcl.2005.12.020
   PubMed Web of Science ®Google Scholar
• Liao, Y., Wang, J., Jaehnig, E. J., Shi, Z., & Zhang, B. (2019). WebGestalt 2019: Gene set analysis toolkit with revamped UIs and APIs. Nucleic Acids Research, 47(W1), W199–W205. https://doi.org/10.1093/nar/gkz401
   PubMed Web of Science ®Google Scholar
• Lin, C.-Y., Chin, C.-H., Wu, H.-H., Chen, S.-H., Ho, C.-W., & Ko, M.-T. (2008). Hubba: Hub objects analyzer-A framework of interactome hubs identification for network biology. Nucleic Acids Research, 36(Web Server issue), W438–W443. https://doi.org/10.1093/nar/gkn257
   PubMedGoogle Scholar
• Lowe, P. R., & N. Corvaia. (2016). ADAM17: A gatekeeper in immune-oncology? International Journal of Cancer and Clinical Research, 3, 058. https://doi.org/10.23937/2378-3419/3/3/1058
   Google Scholar
• Lu, H.-Y., Zu, Y.-X., Jiang, X.-W., Sun, X.-T., Liu, T.-Y., Li, R.-L., Wu, Q., Zhang, Y.-S., & Zhao, Q.-C. (2019). Novel ADAM-17 inhibitor ZLDI-8 inhibits the proliferation and metastasis of chemo-resistant non-small-cell lung cancer by reversing notch and epithelial mesenchymal transition in vitro and in vivo. Pharmacological Research, 148, 104406. https://doi.org/10.1016/j.phrs.2019.104406
   PubMed Web of Science ®Google Scholar
• Mittal, S., Sharma, A., Balaji, S. A., Gowda, M. C., Dighe, R. R., Kumar, R. V., & Rangarajan, A. (2014). Coordinate hyperactivation of Notch1 and Ras/MAPK pathways correlates with poor patient survival: Novel therapeutic strategy for aggressive breast cancers. Molecular Cancer Therapeutics, 13(12), 3198–3209. https://doi.org/10.1158/1535-7163.MCT-14-0280
   PubMed Web of Science ®Google Scholar
• Mochizuki, S., & Okada, Y. (2007). ADAMs in cancer cell proliferation and progression. Cancer Science, 98(5), 621–628. https://doi.org/10.1111/j.1349-7006.2007.00434.x
   PubMed Web of Science ®Google Scholar
• Morris, G. M., Huey, R., Lindstrom, W., Sanner, M. F., Belew, R. K., Goodsell, D. S., & Olson, A. J. (2009). Software news and updates AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. Journal of Computational Chemistry, 30(16), 2785–2791. https://doi.org/10.1002/jcc.21256
   PubMed Web of Science ®Google Scholar
• Mullooly, M. (2015). ADAM10: A new player in breast cancer progression?. 945–951. https://doi.org/10.1038/bjc.2015.288
   Google Scholar
• Mullooly, M., McGowan, P. M., Crown, J., & Duffy, M. J. (2016). The ADAMs family of proteases as targets for the treatment of cancer. Cancer Biology & Therapy, 17(8), 870–880. https://doi.org/10.1080/15384047.2016.1177684
   PubMed Web of Science ®Google Scholar
• Murumkar, P. R., Giridhar, R., & Yadav, M. R. (2013). Novel methods and strategies in the discovery of TACE inhibitors. Expert Opinion on Drug Discovery, 8(2), 157–181. https://doi.org/10.1517/17460441.2013.744745
   PubMed Web of Science ®Google Scholar
• Nelson, F. C., & Zask, A. (1999). The therapeutic potential of small molecule TACE inhibitors. Expert Opinion on Investigational Drugs, 8(4), 383–392. https://doi.org/10.1517/13543784.8.4.383
   PubMedGoogle Scholar
• Niu, X., Umland, S., Ingram, R., Beyer, B. M., Liu, Y.-H., Sun, J., Lundell, D., & Orth, P. (2006). IK682, a tight binding inhibitor of TACE. Archives of Biochemistry and Biophysics, 451(1), 43–50. https://doi.org/10.1016/j.abb.2006.03.034
   PubMed Web of Science ®Google Scholar
• Özgür, A., Vu, T., Erkan, G., & Radev, D. R. (2008). Identifying gene-disease associations using centrality on a literature mined gene-interaction network. Bioinformatics (Oxford, England), 24(13), i277–i285. https://doi.org/10.1093/bioinformatics/btn182
   PubMed Web of Science ®Google Scholar
• Shannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., Amin, N., Schwikowski, B. & Ideker, T. (1971). Cytoscape: A software environment for integrated models. Genome Research, 13(22), 426. https://doi.org/10.1101/gr.1239303.metabolite
   Google Scholar
• Pires, D. E. V., Blundell, T. L., & Ascher, D. B. (2015). PkCSM: Predicting small-molecule pharmacokinetic and toxicity properties using graph-based signatures. Journal of Medicinal Chemistry, 58(9), 4066–4072. https://doi.org/10.1021/acs.jmedchem.5b00104
   PubMed Web of Science ®Google Scholar
• Rhodes, D. R., Yu, J., Shanker, K., Deshpande, N., Varambally, R., Ghosh, D., Barrette, T., Pandey, A., & Chinnaiyan, A. M. (2004). ONCOMINE: A cancer microarray database and integrated data-mining platform. Neoplasia (New York, N.Y.), 6(1), 1–6. https://doi.org/10.1016/s1476-5586(04)80047-2
   PubMed Web of Science ®Google Scholar
• Saad, M. I., Rose-John, S., & Jenkins, B. J. (2019). ADAM17: An emerging therapeutic target for lung cancer. Cancers, 11(9), 1218. https://doi.org/10.3390/cancers11091218
   Google Scholar
• Scheau, C., Badarau, I. A., Costache, R., Caruntu, C., Mihai, G. L., Didilescu, A. C., Constantin, C., & Neagu, M. (2019). The role of matrix metalloproteinases in the epithelial-mesenchymal transition of hepatocellular carcinoma. Analytical Cellular Pathology (Amsterdam), 2019, 10. https://doi.org/10.1155/2019/9423907
   Google Scholar
• Trifonova R., Small, D., Kacer, D., Kovalenko, D., Kolev, V., Mandinova, A., Soldi, R., Liaw, L., Prudovsky, I., & Maciag, T. (2004). The non-transmembrane form of Delta1, but not of Jagged1, behavior accompanied by fibroblast growth factor receptor 1-dependent transformation. Journal of Biological Chemistry, 279(14), 13285–13288. https://doi.org/10.1074/jbc.C300564200
   Google Scholar
• Trott, O., & Olson, A. J. (2010). AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of Computational Chemistry, 31(2), 455–461. https://doi.org/10.1002/jcc.21334
   PubMed Web of Science ®Google Scholar
• Voudouri, K., Berdiaki, A., Tzardi, M., Tzanakakis, G. N., & Nikitovic, D. (2015). Insulin-like growth factor and epidermal growth factor signaling in breast cancer cell growth: Focus on endocrine resistant disease. Analytical Cellular Pathology (Amsterdam), 2015, 975495. https://doi.org/10.1155/2015/975495
   PubMedGoogle Scholar
• Witters, L., Scherle, P., Friedman, S., Fridman, J., Caulder, E., Newton, R., & Lipton, A. (2008). Synergistic inhibition with a dual epidermal growth factor receptor/HER-2/Neu tyrosine kinase inhibitor and a disintegrin and metalloprotease inhibitor. Cancer Research, 68(17), 7083–7089. https://doi.org/10.1158/0008-5472.CAN-08-0739
   PubMed Web of Science ®Google Scholar
• Xue, C. B., He, X., Corbett, R. L., Roderick, J., Wasserman, Z. R., Liu, R. Q., Jaffee, B. D., Covington, M. B., Qian, M., Trzaskos, J. M., Newton, R. C., Magolda, R. L., Wexler, R. R., & Decicco, C. P. (2001). Discovery of macrocyclic hydroxamic acids containing biphenylmethyl derivatives at P1', a series of selective TNF-alpha converting enzyme inhibitors with potent cellular activity in the inhibition of TNF-alpha release. Journal of Medicinal Chemistry, 44(21), 3351–3354. https://doi.org/10.1021/jm0155502
   PubMed Web of Science ®Google Scholar
• Zhang, Y., Li, D., Jiang, Q., Cao, S., Sun, H., Chai, Y., Li, X., Ren, T., Yang, R., Feng, F., Li, B.-A., & Zhao, Q. (2018). Novel ADAM-17 inhibitor ZLDI-8 enhances the in vitro and in vivo chemotherapeutic effects of sorafenib on hepatocellular carcinoma cells. Cell Death & Disease, 9(7), 743. https://doi.org/10.1038/s41419-018-0804-6
   PubMedGoogle Scholar
• Zhu, X., Gerstein, M., & Snyder, M. (2007). Getting connected: Analysis and principles of biological networks. Genes & Development, 21(9), 1010–1024. https://doi.org/10.1101/gad.1528707
   PubMed Web of Science ®Google Scholar
• Zolkiewska, A. (2009). ADAM proteases: Ligand processing and modulation of the notch pathway. Cellular and Molecular Life Sciences, 65(13), 2056–2068. https://doi.org/10.1007/s00018-008-7586-4.ADAM
   Google Scholar