Login Register Cart 0
Generic placeholder image

Mini-Reviews in Medicinal Chemistry

Editor-in-Chief

ISSN (Print): 1389-5575
ISSN (Online): 1875-5607

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Perspective

Discoidin Domain Receptor 1 Inhibitors: Advances and Future Directions for Novel Therapeutics with Aid of DNA Encoded Library Screens and Artificial Intelligence

Author(s): Rahul Sanawar*, Vinodh J. Sahayasheela, Praseetha Sarath and Vipin Mohan Dan*

Volume 23, Issue 15, 2023

Published on: 02 February, 2023

Page: [1507 - 1513] Pages: 7

DOI: 10.2174/1389557523666230125114921

Abstract

Discoidin domain receptor (DDR) 1, a collagen binding receptor kinase, is an intensively researched therapeutic target for cancer, fibrosis and other diseases. The majority of early known DDR1 inhibitors targeted the ATP binding pocket of this enzyme that shares structural similarities with other kinase pockets across the biological system. This structural similarity of DDR1 kinase with other protein kinases often leads to “off target “toxicity issues. Understanding of uniqueness in DDR:ATP–phosphate-binding loop (P-loop), DNA encoded library screen, structure-guided optimization studies, and machine learning drug design platforms that come under the umbrella of artificial intelligence has led to the discovery of a new array of inhibitors that are highly selective for DDR1 over DDR2 and other similar kinases. Most of the drug discovery platforms concentrated on the ATP binding region of DDR1 kinase and never looked beyond this region for novel therapeutic options. Recent findings have disclosed the kinase-independent functions of DDR1 in immune exclusion, which resides in the extracellular collagen-binding domain, thus opening avenues for the development of inhibitors that veer away from targeting ATP binding pockets. This recent understanding of the functional modalities of DDR1 opens the complexity of targeting this transmembrane protein as per its functional prominence in the respective disease and thus demands the development of specific novel therapeutics. The perspective gives a short overview of recent developments of DDR1 inhibitors with the aid of the latest technologies, future directions for therapeutic development, and possibility of combinational therapeutic treatments to completely disengage functions of DDR1.

Keywords: Discoidin, domain receptor, collagen, artificial intelligence, cancer, fibrosis, kinase.

« Previous Next »
Graphical Abstract

[1]
Moll, S.; Desmoulière, A.; Moeller, M.J.; Pache, J.C.; Badi, L.; Arcadu, F.; Richter, H.; Satz, A.; Uhles, S.; Cavalli, A.; Drawnel, F.; Scapozza, L.; Prunotto, M. DDR1 role in fibrosis and its pharmacological targeting. Biochim. Biophys. Acta Mol. Cell Res., 2019, 1866(11), 118474.
[http://dx.doi.org/10.1016/j.bbamcr.2019.04.004] [PMID: 30954571]
[2]
Chen, L.; Kong, X.; Fang, Y.; Paunikar, S.; Wang, X.; Brown, J.A.L.; Bourke, E.; Li, X.; Wang, J. Recent advances in the role of discoidin domain receptor tyrosine kinase 1 and discoidin domain receptor tyrosine kinase 2 in breast and ovarian cancer. Front. Cell Dev. Biol., 2021, 9, 747314.
[http://dx.doi.org/10.3389/fcell.2021.747314] [PMID: 34805157]
[3]
Humphreys, B.D. Mechanisms of renal fibrosis. Annu. Rev. Physiol., 2018, 80(1), 309-326.
[http://dx.doi.org/10.1146/annurev-physiol-022516-034227] [PMID: 29068765]
[4]
Borza, C.M.; Bolas, G.; Bock, F.; Zhang, X.; Akabogu, F.C.; Zhang, M.Z.; de Caestecker, M.; Yang, M.; Yang, H.; Lee, E.; Gewin, L.; Fogo, A.B.; McDonald, W.H.; Zent, R.; Pozzi, A. DDR1 contributes to kidney inflammation and fibrosis by promoting the phosphorylation of BCR and STAT3. JCI Insight, 2022, 7(3), e150887.
[http://dx.doi.org/10.1172/jci.insight.150887] [PMID: 34941574]
[5]
Chiusa, M.; Hu, W.; Liao, H.J.; Su, Y.; Borza, C.M.; de Caestecker, M.P.; Skrypnyk, N.I.; Fogo, A.B.; Pedchenko, V.; Li, X.; Zhang, M.Z.; Hudson, B.G.; Basak, T.; Vanacore, R.M.; Zent, R.; Pozzi, A. The extracellular matrix receptor discoidin domain receptor 1 regulates collagen transcription by translocating to the nucleus. J. Am. Soc. Nephrol., 2019, 30(9), 1605-1624.
[http://dx.doi.org/10.1681/ASN.2018111160] [PMID: 31383731]
[6]
Das, S.; Ongusaha, P.P.; Yang, Y.S.; Park, J.M.; Aaronson, S.A.; Lee, S.W. Discoidin domain receptor 1 receptor tyrosine kinase induces cyclooxygenase-2 and promotes chemoresistance through nuclear factor-kappaB pathway activation. Cancer Res., 2006, 66(16), 8123-8130.
[http://dx.doi.org/10.1158/0008-5472.CAN-06-1215] [PMID: 16912190]
[7]
Matada, G.S.P.; Das, A.; Dhiwar, P.S.; Ghara, A. DDR1 and DDR2: A review on signaling pathway and small molecule inhibitors as an anticancer agent. Med. Chem. Res., 2021, 30(3), 535-551.
[http://dx.doi.org/10.1007/s00044-020-02694-2]
[8]
Henriet, E.; Sala, M.; Abou Hammoud, A.; Tuariihionoa, A.; Di Martino, J.; Ros, M.; Saltel, F. Multitasking discoidin domain receptors are involved in several and specific hallmarks of cancer. Cell Adhes. Migr., 2018, 12(4), 1-15.
[http://dx.doi.org/10.1080/19336918.2018.1465156] [PMID: 29701112]
[9]
Murray, C.W.; Berdini, V.; Buck, I.M.; Carr, M.E.; Cleasby, A.; Coyle, J.E.; Curry, J.E.; Day, J.E.H.; Day, P.J.; Hearn, K.; Iqbal, A.; Lee, L.Y.W.; Martins, V.; Mortenson, P.N.; Munck, J.M.; Page, L.W.; Patel, S.; Roomans, S.; Smith, K.; Tamanini, E.; Saxty, G. Fragment-based discovery of potent and selective DDR1/2 inhibitors. ACS Med. Chem. Lett., 2015, 6(7), 798-803.
[http://dx.doi.org/10.1021/acsmedchemlett.5b00143] [PMID: 26191369]
[10]
Wang, Z.; Bian, H.; Bartual, S.G.; Du, W.; Luo, J.; Zhao, H.; Zhang, S.; Mo, C.; Zhou, Y.; Xu, Y.; Tu, Z.; Ren, X.; Lu, X.; Brekken, R.A.; Yao, L.; Bullock, A.N.; Su, J.; Ding, K. Structure-based design of tetrahydroisoquinoline-7-carboxamides as selective discoidin domain receptor 1 (DDR1) inhibitors. J. Med. Chem., 2016, 59(12), 5911-5916.
[http://dx.doi.org/10.1021/acs.jmedchem.6b00140] [PMID: 27219676]
[11]
Skaper, S.D. The neurotrophin family of neurotrophic factors: An overview. Methods Mol. Biol., 2012, 846, 1-12.
[http://dx.doi.org/10.1007/978-1-61779-536-7_1] [PMID: 22367796]
[12]
Zhu, D.; Huang, H.; Pinkas, D.M.; Luo, J.; Ganguly, D.; Fox, A.E.; Arner, E.; Xiang, Q.; Tu, Z.C.; Bullock, A.N.; Brekken, R.A.; Ding, K.; Lu, X. 2-Amino-2,3-dihydro-1 H -indene-5-carboxamide-based discoidin domain receptor 1 (DDR1) Inhibitors: Design, synthesis, and in vivo antipancreatic cancer efficacy. J. Med. Chem., 2019, 62(16), 7431-7444.
[http://dx.doi.org/10.1021/acs.jmedchem.9b00365] [PMID: 31310125]
[13]
Gironda-Martínez, A.; Donckele, E.J.; Samain, F.; Neri, D. DNA-encoded chemical libraries: A comprehensive review with succesful stories and future challenges. ACS Pharmacol. Transl. Sci., 2021, 4(4), 1265-1279.
[http://dx.doi.org/10.1021/acsptsci.1c00118] [PMID: 34423264]
[14]
Richter, H.; Satz, A.L.; Bedoucha, M.; Buettelmann, B.; Petersen, A.C.; Harmeier, A.; Hermosilla, R.; Hochstrasser, R.; Burger, D.; Gsell, B.; Gasser, R.; Huber, S.; Hug, M.N.; Kocer, B.; Kuhn, B.; Ritter, M.; Rudolph, M.G.; Weibel, F.; Molina-David, J.; Kim, J.J.; Santos, J.V.; Stihle, M.; Georges, G.J.; Bonfil, R.D.; Fridman, R.; Uhles, S.; Moll, S.; Faul, C.; Fornoni, A.; Prunotto, M. DNA-encoded library-derived DDR1 inhibitor prevents fibrosis and renal function loss in a genetic mouse model of alport syndrome. ACS Chem. Biol., 2019, 14(1), 37-49.
[http://dx.doi.org/10.1021/acschembio.8b00866] [PMID: 30452219]
[15]
Hackler, A.L.; FitzGerald, F.G.; Dang, V.Q.; Satz, A.L.; Paegel, B.M. Off-DNA DNA-encoded library affinity screening. ACS Comb. Sci., 2020, 22(1), 25-34.
[http://dx.doi.org/10.1021/acscombsci.9b00153] [PMID: 31829554]
[16]
Zhavoronkov, A.; Ivanenkov, Y.A.; Aliper, A.; Veselov, M.S.; Aladinskiy, V.A.; Aladinskaya, A.V.; Terentiev, V.A.; Polykovskiy, D.A.; Kuznetsov, M.D.; Asadulaev, A.; Volkov, Y.; Zholus, A.; Shayakhmetov, R.R.; Zhebrak, A.; Minaeva, L.I.; Zagribelnyy, B.A.; Lee, L.H.; Soll, R.; Madge, D.; Xing, L.; Guo, T.; Aspuru-Guzik, A. Deep learning enables rapid identification of potent DDR1 kinase inhibitors. Nat. Biotechnol., 2019, 37(9), 1038-1040.
[http://dx.doi.org/10.1038/s41587-019-0224-x] [PMID: 31477924]
[17]
Walters, W.P.; Murcko, M. Assessing the impact of generative AI on medicinal chemistry. Nat. Biotechnol., 2020, 38(2), 143-145.
[http://dx.doi.org/10.1038/s41587-020-0418-2] [PMID: 32001834]
[18]
Tan, X.; Li, C.; Yang, R.; Zhao, S.; Li, F.; Li, X.; Chen, L.; Wan, X.; Liu, X.; Yang, T.; Tong, X.; Xu, T.; Cui, R.; Jiang, H.; Zhang, S.; Liu, H.; Zheng, M. Discovery of pyrazolo[3,4- d]pyridazinone derivatives as selective DDR1 inhibitors via deep learning based design, synthesis, and biological evaluation. J. Med. Chem., 2022, 65(1), 103-119.
[http://dx.doi.org/10.1021/acs.jmedchem.1c01205] [PMID: 34821145]
[19]
Arús-Pous, J.; Johansson, S.V.; Prykhodko, O.; Bjerrum, E.J.; Tyrchan, C.; Reymond, J.L.; Chen, H.; Engkvist, O. Randomized SMILES strings improve the quality of molecular generative models. J. Cheminform., 2019, 11(1), 71.
[http://dx.doi.org/10.1186/s13321-019-0393-0] [PMID: 33430971]
[20]
Li, X.; Li, Z.; Wu, X.; Xiong, Z.; Yang, T.; Fu, Z.; Liu, X.; Tan, X.; Zhong, F.; Wan, X.; Wang, D.; Ding, X.; Yang, R.; Hou, H.; Li, C.; Liu, H.; Chen, K.; Jiang, H.; Zheng, M. Deep learning enhancing kinome-wide polypharmacology profiling: Model construction and experiment validation. J. Med. Chem., 2020, 63(16), 8723-8737.
[http://dx.doi.org/10.1021/acs.jmedchem.9b00855] [PMID: 31364850]
[21]
Wang, Y.; Dai, Y.; Wu, X.; Li, F.; Liu, B.; Li, C.; Liu, Q.; Zhou, Y.; Wang, B.; Zhu, M.; Cui, R.; Tan, X.; Xiong, Z.; Liu, J.; Tan, M.; Xu, Y.; Geng, M.; Jiang, H.; Liu, H.; Ai, J.; Zheng, M. Discovery and development of a series of pyrazolo[3,4- d]pyridazinone compounds as the novel covalent fibroblast growth factor receptor inhibitors by the rational drug design. J. Med. Chem., 2019, 62(16), 7473-7488.
[http://dx.doi.org/10.1021/acs.jmedchem.9b00510] [PMID: 31335138]
[22]
Méndez-Lucio, O.; Baillif, B.; Clevert, D.A.; Rouquié, D.; Wichard, J. De novo generation of hit-like molecules from gene expression signatures using artificial intelligence. Nat. Commun., 2020, 11(1), 10.
[http://dx.doi.org/10.1038/s41467-019-13807-w] [PMID: 31900408]
[23]
Goodfellow, I.J. Generative Adversarial Nets. In: Part of Advances in Neural Information Processing Systems; MIT Press, 2014; Vol. 27, pp. 2672-2680.
[24]
Lim, S.; Lee, S.; Piao, Y.; Choi, M.; Bang, D.; Gu, J.; Kim, S. On modeling and utilizing chemical compound information with deep learning technologies: A task-oriented approach. Comput. Struct. Biotechnol. J., 2022, 20, 4288-4304.
[http://dx.doi.org/10.1016/j.csbj.2022.07.049] [PMID: 36051875]
[25]
Vo, T.H.; Nguyen, N.T.K.; Kha, Q.H.; Le, N.Q.K. On the road to explainable AI in drug-drug interactions prediction: A systematic review. Comput. Struct. Biotechnol. J., 2022, 20, 2112-2123.
[http://dx.doi.org/10.1016/j.csbj.2022.04.021] [PMID: 35832629]
[26]
Sun, X.; Wu, B.; Chiang, H.C.; Deng, H.; Zhang, X.; Xiong, W.; Liu, J.; Rozeboom, A.M.; Harris, B.T.; Blommaert, E.; Gomez, A.; Garcia, R.E.; Zhou, Y.; Mitra, P.; Prevost, M.; Zhang, D.; Banik, D.; Isaacs, C.; Berry, D.; Lai, C.; Chaldekas, K.; Latham, P.S.; Brantner, C.A.; Popratiloff, A.; Jin, V.X.; Zhang, N.; Hu, Y.; Pujana, M.A.; Curiel, T.J.; An, Z.; Li, R. Tumour DDR1 promotes collagen fibre alignment to instigate immune exclusion. Nature, 2021, 599(7886), 673-678.
[http://dx.doi.org/10.1038/s41586-021-04057-2] [PMID: 34732895]
[27]
Dan, V.M.; Sengodan, S.K.; Sarath, P.; Sanawar, R. Discoidin domain receptor 1 as modifier of collagen in tumor extracellular matrix: Recent advances and therapeutic possibilities. Curr. Mol. Biol. Rep., 2022, 8(4), 35-41.
[http://dx.doi.org/10.1007/s40610-022-00150-1]
[28]
Henke, E.; Nandigama, R.; Ergün, S. Extracellular matrix in the tumor microenvironment and its impact on cancer therapy. Front. Mol. Biosci., 2020, 6, 160.
[http://dx.doi.org/10.3389/fmolb.2019.00160] [PMID: 32118030]

Rights & Permissions Print Cite
Article Metrics
49
2
© 2024 Bentham Science Publishers | Privacy Policy