A computational study to target necroptosis via RIPK1 inhibition

References

• 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
• Alvariño, R., Alonso, E., Lacret, R., Oves-Costales, D., Genilloud, O., Reyes, F., Alfonso, A., & Botana, L. M. (2019). Caniferolide A, a macrolide from Streptomyces caniferus, attenuates neuroinflammation, oxidative stress, amyloid-beta, and tau pathology in vitro. Molecular Pharmaceutics, 16(4), 1456–1466. https://doi.org/10.1021/acs.molpharmaceut.8b01090
   PubMed Web of Science ®Google Scholar
• Arnittali, M., Rissanou, A. N., & Harmandaris, V. (2019). Structure Of Biomolecules Through Molecular Dynamics Simulations [Paper presentation]. Procedia Comput. Sci., 8th International Young Scientists Conference on Computational Science, YSC2019, Heraklion, Greece, 24–28 June 2019. 156, 69–78. https://doi.org/10.1016/j.procs.2019.08.181
   Google Scholar
• Berendsen, H. J. C., van der Spoel, D., & van Drunen, R. (1995). GROMACS: A message-passing parallel molecular dynamics implementation. Computer Physics Communications. 91(1–3), 43–56. https://doi.org/10.1016/0010-4655(95)00042-E
   Web of Science ®Google Scholar
• Carroll, A. R., Copp, B. R., Davis, R. A., Keyzers, R. A., & Prinsep, M. R. (2022). Marine natural products. Natural Product Reports, 39(6), 1122–1171. https://doi.org/10.1039/D1NP00076D
   PubMed Web of Science ®Google Scholar
• Chevin, M., & Sébire, G. (2021). Necroptosis in ALS: A hot topic in-progress. Cell Death Discovery, 7(1), 2. https://doi.org/10.1038/s41420-021-00458-4
   PubMed Web of Science ®Google Scholar
• Cougnoux, A., Cluzeau, C., Mitra, S., Li, R., Williams, I., Burkert, K., Xu, X., Wassif, C. A., Zheng, W., & Porter, F. D. (2016). Necroptosis in Niemann–Pick disease, type C1: A potential therapeutic target. Cell Death & Disease, 7, e2147–e2147. https://doi.org/10.1038/cddis.2016.16
   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, 42717. https://doi.org/10.1038/srep42717
   PubMed Web of Science ®Google Scholar
• Daina, A., & Zoete, V. (2016). A BOILED‐egg to predict gastrointestinal absorption and brain penetration of small molecules. Chemmedchem, 11(11), 1117–1121. https://doi.org/10.1002/cmdc.201600182
   PubMed Web of Science ®Google Scholar
• Darding, M., & Meier, P. (2012). IAPs: Guardians of RIPK1. Cell Death and Differentiation, 19(1), 58–66. https://doi.org/10.1038/cdd.2011.163
   PubMed Web of Science ®Google Scholar
• Degterev, A., Huang, Z., Boyce, M., Li, Y., Jagtap, P., Mizushima, N., Cuny, G. D., Mitchison, T. J., Moskowitz, M. A., & Yuan, J. (2005). Chemical inhibitor of nonapoptotic cell death with therapeutic potential for ischemic brain injury. Nature Chemical Biology, 1(2), 112–119. https://doi.org/10.1038/nchembio711
   PubMed Web of Science ®Google Scholar
• Dionísio, P. A., Amaral, J. D., & Rodrigues, C. M. P. (2020). Chapter two - Molecular mechanisms of necroptosis and relevance for neurodegenerative diseases. In Spetz, J.K.E., Galluzzi, L. (Eds.), International Review of Cell and Molecular Biology, Cell Death Regulation in Health And Disease - Part C (pp. 31–82). Academic Press. https://doi.org/10.1016/bs.ircmb.2019.12.006
   Google Scholar
• Dodda, L. S., Cabeza de Vaca, I., Tirado-Rives, J., & Jorgensen, W. L. (2017). LigParGen web server: An automatic OPLS-AA parameter generator for organic ligands. Nucleic Acids Research, 45(W1), W331–W336. https://doi.org/10.1093/nar/gkx312
   PubMed Web of Science ®Google Scholar
• Egan, W. J., Merz, K. M., & Baldwin, J. J. (2000). Prediction of drug absorption using multivariate statistics. Journal of Medicinal Chemistry, 43(21), 3867–3877. https://doi.org/10.1021/jm000292e
   PubMed Web of Science ®Google Scholar
• Elmaaty, A. A., Darwish, K. M., Chrouda, A., Boseila, A. A., Tantawy, M. A., Elhady, S. S., Shaik, A. B., Mustafa, M., & Al-karmalawy, A. A. (2022). In silico and in vitro studies for benzimidazole anthelmintics repurposing as VEGFR-2 antagonists: Novel mebendazole-loaded mixed micelles with enhanced dissolution and anticancer activity. ACS Omega, 7(1), 875–899. https://doi.org/10.1021/acsomega.1c05519
   PubMed Web of Science ®Google Scholar
• El-Demerdash, A., Al-Karmalawy, A. A., Abdel-Aziz, T. M., Elhady, S. S., Darwish, K. M., & Hassan, A. H. E. (2021). Investigating the structure–activity relationship of marine natural polyketides as promising SARS-CoV-2 main protease inhibitors. RSC Advances, 11(50), 31339–31363. https://doi.org/10.1039/d1ra05817g
   PubMed Web of Science ®Google Scholar
• Feoktistova, M., & Leverkus, M. (2015). Programmed necrosis and necroptosis signalling. The FEBS Journal, 282(1), 19–31. https://doi.org/10.1111/febs.13120
   PubMed Web of Science ®Google Scholar
• Festjens, N., Vanden Berghe, T., Cornelis, S., & Vandenabeele, P. (2007). RIP1, a kinase on the crossroads of a cell’s decision to live or die. Cell Death and Differentiation, 14(3), 400–410. https://doi.org/10.1038/sj.cdd.4402085
   PubMed Web of Science ®Google Scholar
• Genheden, S., & Ryde, U. (2015). The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Expert Opinion on Drug Discovery, 10(5), 449–461. https://doi.org/10.1517/17460441.2015.1032936
   PubMed Web of Science ®Google Scholar
• Ghose, A. K., Viswanadhan, V. N., & Wendoloski, J. J. (1999). A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases. Journal of Combinatorial Chemistry, 1(1), 55–68. https://doi.org/10.1021/cc9800071
   PubMedGoogle Scholar
• Grievink, H. W., Heuberger, J., Huang, F., Chaudhary, R., Birkhoff, W. A. J., Tonn, G. R., Mosesova, S., Erickson, R., Moerland, M., Haddick, P. C. G., Scearce-Levie, K., Ho, C., & Groeneveld, G. J. (2020). DNL104, a centrally penetrant RIPK1 inhibitor, inhibits RIP1 kinase phosphorylation in a randomized phase i ascending dose study in healthy volunteers. Clinical Pharmacology and Therapeutics, 107(2), 406–414. https://doi.org/10.1002/cpt.1615
   PubMed Web of Science ®Google Scholar
• Halgren, T. A. (1996). Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94. Journal of Computational Chemistry, 17(5–6), 490–519. https://doi.org/10.1002/(SICI)1096-987X(199604)17:5/6<490::AID-JCC1>3.0.CO;2-P
   Web of Science ®Google Scholar
• Hamed, M. I. A., Darwish, K. M., Soltane, R., Chrouda, A., Mostafa, A., Shama, N. M. A., Elhady, S. S., Abulkhair, H. S., Khodir, A. E., Elmaaty, A. A., & Al-karmalawy, A. A. (2021). β-Blockers bearing hydroxyethylamine and hydroxyethylene as potential SARS-CoV-2 Mpro inhibitors: rational based design, in silico, in vitro, and SAR studies for lead optimization. RSC Advances, 11(56), 35536–35558. https://doi.org/10.1039/d1ra04820a
   PubMed Web of Science ®Google Scholar
• Holler, N., Zaru, R., Micheau, O., Thome, M., Attinger, A., Valitutti, S., Bodmer, J.-L., Schneider, P., Seed, B., & Tschopp, J. (2000). Fas triggers an alternative, caspase-8–independent cell death pathway using the kinase RIP as effector molecule. Nature Immunology, 1(6), 489–495. https://doi.org/10.1038/82732
   PubMed Web of Science ®Google Scholar
• Humphrey, W., Dalke, A., & Schulten, K. (1996). VMD – Visual molecular dynamics. Journal of Molecular Graphics, 14(1), 33–38. https://doi.org/10.1016/0263-7855(96)00018-5
   PubMedGoogle Scholar
• Jiménez, C. (2018). Marine natural products in medicinal chemistry. ACS Medicinal Chemistry Letters, 9(10), 959–961. https://doi.org/10.1021/acsmedchemlett.8b00368
   PubMed Web of Science ®Google Scholar
• Khoury, M. K., Gupta, K., Franco, S. R., & Liu, B. (2020). Necroptosis in the pathophysiology of disease. The American Journal of Pathology, 190(2), 272–285. https://doi.org/10.1016/j.ajpath.2019.10.012
   PubMed Web of Science ®Google Scholar
• Kumari, R., Kumar, R., Open Source Drug Discovery Consortium, & 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
• Lagorce, D., Bouslama, L., Becot, J., Miteva, M. A., & Villoutreix, B. O. (2017). FAF-Drugs4: Free ADME-tox filtering computations for chemical biology and early stages drug discovery. Bioinformatics (Oxford, England), 33(22), 3658–3660. https://doi.org/10.1093/bioinformatics/btx491
   PubMed Web of Science ®Google Scholar
• Li, Y., Yang, X., Ma, C., Qiao, J., & Zhang, C. (2008). Necroptosis contributes to the NMDA-induced excitotoxicity in rat’s cultured cortical neurons. Neuroscience Letters. 447(2–3), 120–123. https://doi.org/10.1016/j.neulet.2008.08.037
   PubMed Web of Science ®Google Scholar
• Linkermann, A., & Green, D. R. (2014). Necroptosis. The New England Journal of Medicine, 370(5), 455–465. https://doi.org/10.1056/NEJMra1310050
   PubMed Web of Science ®Google Scholar
• Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (2001). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings1PII of original article: S0169-409X(96)00423-1. The article was originally published in advanced drug delivery reviews 23 (1997) 3–25.1. Advanced Drug Delivery Reviews, 46(1–3), 3–26. https://doi.org/10.1016/S0169-409X(00)00129-0
   PubMed Web of Science ®Google Scholar
• Martens, S., Hofmans, S., Declercq, W., Augustyns, K., & Vandenabeele, P. (2020). Inhibitors targeting RIPK1/RIPK3: Old and new drugs. Trends in Pharmacological Sciences, 41(3), 209–224. https://doi.org/10.1016/j.tips.2020.01.002
   PubMed Web of Science ®Google Scholar
• Meng, H., Wu, G., Zhao, X., Wang, A., Li, D., Tong, Y., Jin, T., Cao, Y., Shan, B., Hu, S., Li, Y., Pan, L., Tian, X., Wu, P., Peng, C., Yuan, J., Li, G., Tan, L., Wang, Z., & Li, Y. (2021). Discovery of a cooperative mode of inhibiting RIPK1 kinase. Cell Discovery, 7(1), 41–18. https://doi.org/10.1038/s41421-021-00278-x
   PubMed Web of Science ®Google Scholar
• Mifflin, L., Ofengeim, D., & Yuan, J. (2020). Receptor-interacting protein kinase 1 (RIPK1) as a therapeutic target. Nature Reviews. Drug Discovery, 19(8), 553–571. https://doi.org/10.1038/s41573-020-0071-y
   PubMed Web of Science ®Google Scholar
• Mistry, J., Chuguransky, S., Williams, L., Qureshi, M., Salazar, G. A., Sonnhammer, E. L. L., Tosatto, S. C. E., Paladin, L., Raj, S., Richardson, L. J., Finn, R. D., & Bateman, A. (2021). Pfam: The protein families database in 2021. Nucleic Acids Research, 49(D1), D412–D419. https://doi.org/10.1093/nar/gkaa913
   PubMed Web of Science ®Google Scholar
• Molinski, T. F., Dalisay, D. S., Lievens, S. L., & Saludes, J. P. (2009). Drug development from marine natural products. Nature Reviews. Drug Discovery, 8(1), 69–85. https://doi.org/10.1038/nrd2487
   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). 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
• Muegge, I., Heald, S. L., & Brittelli, D. (2001). Simple selection criteria for drug-like chemical matter. Journal of Medicinal Chemistry, 44(12), 1841–1846. https://doi.org/10.1021/jm015507e
   PubMed Web of Science ®Google Scholar
• Mysinger, M. M., Carchia, M., Irwin, J., & Shoichet, B. K. (2012). Directory of useful decoys, enhanced (DUD-E): Better ligands and decoys for better benchmarking. Journal of Medicinal Chemistry, 55(14), 6582–6594. https://doi.org/10.1021/jm300687e
   PubMed Web of Science ®Google Scholar
• O'Boyle, N. M., Banck, M., James, C. A., Morley, C., Vandermeersch, T., & Hutchison, G. R. (2011). Open Babel: An open chemical toolbox. Journal of Cheminformatics, 3, 33. https://doi.org/10.1186/1758-2946-3-33
   PubMed Web of Science ®Google Scholar
• Olajide, O. A., & Sarker, S. D. (2020). Alzheimer’s disease: Natural products as inhibitors of neuroinflammation. Inflammopharmacology, 28(6), 1439–1455. https://doi.org/10.1007/s10787-020-00751-1
   PubMed Web of Science ®Google Scholar
• Oliveira, S. R., Dionísio, P. A., Gaspar, M. M., Ferreira, M. B. T., Rodrigues, C. A. B., Pereira, R. G., Estevão, M. S., Perry, M. J., Moreira, R., Afonso, C. A. M., Amaral, J. D., & Rodrigues, C. M. P. (2021). Discovery of a necroptosis inhibitor improving dopaminergic neuronal loss after MPTP exposure in mice. International Journal of Molecular Sciences, 22(10), 5289. https://doi.org/10.3390/ijms22105289
   PubMed Web of Science ®Google Scholar
• Oñate, M., Catenaccio, A., Salvadores, N., Saquel, C., Martinez, A., Moreno-Gonzalez, I., Gamez, N., Soto, P., Soto, C., Hetz, C., & Court, F. A. (2020). The necroptosis machinery mediates axonal degeneration in a model of Parkinson disease. Cell Death and Differentiation, 27(4), 1169–1185. https://doi.org/10.1038/s41418-019-0408-4
   PubMed Web of Science ®Google Scholar
• Patel, S., Webster, J. D., Varfolomeev, E., Kwon, Y. C., Cheng, J. H., Zhang, J., Dugger, D. L., Wickliffe, K. E., Maltzman, A., Sujatha-Bhaskar, S., Bir Kohli, P., Ramaswamy, S., Deshmukh, G., Liederer, B. M., Fong, R., Hamilton, G., Lupardus, P., Caplazi, P., Lee, W. P., … Vucic, D. (2020). RIP1 inhibition blocks inflammatory diseases but not tumor growth or metastases. Cell Death and Differentiation, 27(1), 161–175. https://doi.org/10.1038/s41418-019-0347-0
   PubMed Web of Science ®Google Scholar
• Pereira, F. (2019). Have marine natural product drug discovery efforts been productive and how can we improve their efficiency? Expert Opinion on Drug Discovery, 14(8), 717–722. https://doi.org/10.1080/17460441.2019.1604675
   PubMed Web of Science ®Google Scholar
• Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. M., Meng, E. C., & Ferrin, T. E. (2004). UCSF Chimera–A visualization system for exploratory research and analysis. Journal of Computational Chemistry, 25(13), 1605–1612. https://doi.org/10.1002/jcc.20084
   PubMed Web of Science ®Google Scholar
• Picon, C., Jayaraman, A., James, R., Beck, C., Gallego, P., Witte, M. E., van Horssen, J., Mazarakis, N. D., & Reynolds, R. (2021). Neuron-specific activation of necroptosis signaling in multiple sclerosis cortical grey matter. Acta Neuropathologica, 141(4), 585–604. https://doi.org/10.1007/s00401-021-02274-7
   PubMed Web of Science ®Google Scholar
• Pinzi, L., & Rastelli, G. (2019). Molecular docking: Shifting paradigms in drug discovery. International Journal of Molecular Sciences, 20(18), 4331. https://doi.org/10.3390/ijms20184331
   PubMed Web of Science ®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
• Poli, G., Granchi, C., Rizzolio, F., & Tuccinardi, T. (2020). Application of MM-PBSA methods in virtual screening. Molecules, 25(8), 1971. https://doi.org/10.3390/molecules25081971
   PubMed Web of Science ®Google Scholar
• Qinli, Z., Meiqing, L., Xia, J., Li, X., Weili, G., Xiuliang, J., Junwei, J., Hailan, Y., Ce, Z., & Qiao, N. (2013). Necrostatin-1 inhibits the degeneration of neural cells induced by aluminum exposure. Restorative Neurology and Neuroscience, 31(5), 543–555. https://doi.org/10.3233/RNN-120304
   PubMed Web of Science ®Google Scholar
• Rahman, M. A., Shuvo, A. A., Bepari, A. K., Apu, M. H., Shill, M. C., Hossain, M., Uddin, M., Islam, M. R., Bakshi, M. K., Hasan, J., Rahman, A., Rahman, G. M. S., & Reza, H. M. (2022). Curcumin improves D-galactose and normal-aging associated memory impairment in mice: In vivo and in silico-based studies. Plos One, 17(6), e0270123. https://doi.org/10.1371/journal.pone.0270123
   PubMed Web of Science ®Google Scholar
• Riebeling, T., Jamal, K., Wilson, R., Kolbrink, B., von Samson-Himmelstjerna, F. A., Moerke, C., Ramos Garcia, L., Dahlke, E., Michels, F., Lühder, F., Schunk, D., Doldi, P., Tyczynski, B., Kribben, A., Flüh, C., Theilig, F., Kunzendorf, U., Meier, P., & Krautwald, S. (2021). Primidone blocks RIPK1-driven cell death and inflammation. Cell Death and Differentiation, 28(5), 1610–1626. https://doi.org/10.1038/s41418-020-00690-y
   PubMed Web of Science ®Google Scholar
• Robertson, M. J., Tirado-Rives, J., & Jorgensen, W. L. (2015). Improved peptide and protein torsional energetics with the OPLS-AA force field. Journal of Chemical Theory and Computation, 11(7), 3499–3509. https://doi.org/10.1021/acs.jctc.5b00356
   PubMed Web of Science ®Google Scholar
• Rosenbaum, D. M., Degterev, A., David, J., Rosenbaum, P. S., Roth, S., Grotta, J. C., Cuny, G. D., Yuan, J., & Savitz, S. I. (2010). Necroptosis, a novel form of caspase-independent cell death, contributes to neuronal damage in a retinal ischemia-reperfusion injury model. Journal of Neuroscience Research, 88(7), 1569–1576. https://doi.org/10.1002/jnr.22314
   PubMed Web of Science ®Google Scholar
• RStudio Team. (2020). RStudio: Integrated development environment for R. RStudio., PBC.
   Google Scholar
• Samdani, A., & Vetrivel, U. (2018). POAP: A GNU parallel based multithreaded pipeline of open babel and AutoDock suite for boosted high throughput virtual screening. Computational Biology and Chemistry, 74, 39–48. https://doi.org/10.1016/j.compbiolchem.2018.02.012
   PubMed Web of Science ®Google Scholar
• Shapovalov, M. V., & Dunbrack, R. L. (2011). A smoothed backbone-dependent rotamer library for proteins derived from adaptive kernel density estimates and regressions. Structure (London, England: 1993), 19(6), 844–858. https://doi.org/10.1016/j.str.2011.03.019
   PubMed Web of Science ®Google Scholar
• Stanger, B. Z., Leder, P., Lee, T. H., Kim, E., & Seed, B. (1995). RIP: A novel protein containing a death domain that interacts with Fas/APO-1 (CD95) in yeast and causes cell death. Cell, 81(4), 513–523. https://doi.org/10.1016/0092-8674(95)90072-1
   PubMed Web of Science ®Google Scholar
• Szklarczyk, D., Gable, A. L., Lyon, D., Junge, A., Wyder, S., Huerta-Cepas, J., Simonovic, M., Doncheva, N. T., Morris, J. H., Bork, P., Jensen, L. J., & Mering, C. v (2019). STRING v11: Protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Research, 47(D1), D607–D613. https://doi.org/10.1093/nar/gky1131
   PubMed Web of Science ®Google Scholar
• Tenev, T., Bianchi, K., Darding, M., Broemer, M., Langlais, C., Wallberg, F., Zachariou, A., Lopez, J., MacFarlane, M., Cain, K., & Meier, P. (2011). The Ripoptosome, a signaling platform that assembles in response to genotoxic stress and loss of IAPs. Molecular Cell, 43(3), 432–448. https://doi.org/10.1016/j.molcel.2011.06.006
   PubMed Web of Science ®Google Scholar
• Torres, P. H. M., Sodero, A. C. R., Jofily, P., & Silva, F. P. Jr, (2019). Key topics in molecular docking for drug design. International Journal of Molecular Sciences, 20(18), 4574. https://doi.org/10.3390/ijms20184574
   PubMed Web of Science ®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
• Veber, D. F., Johnson, S. R., Cheng, H.-Y., Smith, B. R., Ward, K. W., & Kopple, K. D. (2002). Molecular properties that influence the oral bioavailability of drug candidates. Journal of Medicinal Chemistry, 45(12), 2615–2623. https://doi.org/10.1021/jm020017n
   PubMed Web of Science ®Google Scholar
• Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag.
   Google Scholar
• Yang, S.-H., Lee, D. K., Shin, J., Lee, S., Baek, S., Kim, J., Jung, H., Hah, J.-M., & Kim, Y. (2017). Nec-1 alleviates cognitive impairment with reduction of Aβ and tau abnormalities in APP/PS1 mice. EMBO Molecular Medicine, 9(1), 61–77. https://doi.org/10.15252/emmm.201606566
   PubMed Web of Science ®Google Scholar
• Yuan, J., Amin, P., & Ofengeim, D. (2019). Necroptosis and RIPK1-mediated neuroinflammation in CNS diseases. Nature Reviews. Neuroscience, 20(1), 19–33. https://doi.org/10.1038/s41583-018-0093-1
   PubMed Web of Science ®Google Scholar
• Zhang, S., Tang, M., Luo, H., Shi, C., & Xu, Y. (2017). Necroptosis in neurodegenerative diseases: A potential therapeutic target. Cell Death & Disease, 8(6), e2905–e2905. https://doi.org/10.1038/cddis.2017.286
   Google Scholar
• Zhu, S., Zhang, Y., Bai, G., & Li, H. (2011). Necrostatin-1 ameliorates symptoms in R6/2 transgenic mouse model of Huntington’s disease. Cell Death & Disease, 2, e115. https://doi.org/10.1038/cddis.2010.94
   PubMed Web of Science ®Google Scholar