Compounds containing corticosteroids have anti-inflammatory effects and can also suppress the immune system to work effectively. The use of corticosteroid derivatives is limited because certain doses are very toxic to the body. With the development of science, the properties of absorption, distribution, metabolism, excretion, and toxicity or the so-called ADME-Tox of bioactive corticosteroid compounds can be predicted using in silico research methods, so as to minimize the use of test animals in in vivo studies. In addition, in silico can also predict bioactive corticosteroid compounds that can become receptor inhibitors of COVID-19. This study aims to determine the absorption, distribution, metabolism, excretion, and toxicity of corticosteroid derivatives and the interaction of COVID-19 receptors with corticosteroid derivatives in silico so that the potential of corticosteroid derivatives as drug candidates for COVID-19 can be predicted. The in silico analysis method uses the FAFDrugs web application and the UCSF Chimera software. The results showed that corticosteroid derivatives, namely methylprednisolone, and prednisolone, have good absorption, distribution, metabolism, excretion, and toxicity properties and have the same docking score and are close to the docking score of positive control compounds so that they have the potential to become a COVID-19 drug. This research requires a further in vitro and in vivo test phase as a step to validate the potential of the COVID-19 drug from methylprednisolone and prednisolone compounds.
Glowacka, I., Bertram, S., Herzog, P., et al. (2010). Differential Downregulation of ACE2 by the Spike Proteins of Severe Acute Respiratory Syndrome Coronavirus and Human Coronavirus NL63. Journal of Virology. https://doi.org/10.1128/jvi.01248-09
Kim, S., Chen, J., Cheng, T., et al. (2019). PubChem 2019 update: Improved access to chemical data. Nucleic Acids Research. https://doi.org/10.1093/nar/gky1033
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. https://doi.org/10.1093/bioinformatics/btx491
Li, P., A. (2001). Screening for human ADME/Tox drug properties in drug discovery. Drug Discovery Today, 6(7), 357–366. https://doi.org/https://doi.org/10.1016/S1359 6446(01)01712-3
Lipinski, C. A. (2004). Lead- and drug-like compounds: The rule-of-five revolution. Drug Discovery Today: Technologies. https://doi.org/10.1016/j.ddtec.2004.11.007
Lipinski, C. A. (2016). Rule of five in 2015 and beyond: Target and ligand structural limitations, ligand chemistry structure and drug discovery project decisions. Advanced Drug Delivery Reviews. https://doi.org/10.1016/j.addr.2016.04.029
Lipinski, C. A., Dominy, B. W., & Feeney, P. J. (1997). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews.
Malchers, F., Ercanoglu, M., Schütte, D., et al. (2017). Mechanisms of primary drug resistance in FGFR1-amplified lung cancer. Clinical Cancer Research. https://doi.org/10.1158/1078-0432.CCR-17-0478
Moroy, G., Martiny, V. Y., Vayer, P., Villoutreix, B. O., & Miteva, M. A. (2012). Toward in silico structure-based ADMET prediction in drug discovery. Drug Discovery Today. https://doi.org/10.1016/j.drudis.2011.10.023
Novian DR. (2019). Anthelmintic Potential Of Moringa Oleifera As Inhibitor Mitochondrial Rhodoquinol-Fumarate Reductase From Ascaris Suum Using The Docking Method, Jurnal Farmasi Sains dan Praktis 5 (2), 106-114.
Novian DR., dan Winarso A. (2019). Studi in silico potensi anthelmintik rambusa (Passiflora foetida) sebagai inhibitor produksi ATP pada Ascaris suum. ARSHI Veterinary Letters 3 (4), 79-80.
Protein Data Bank. (2020). RCSB PDB: Homepage.
Pubchem. (2020). http://pubchem.ncbi.nlm.nih.gov. (Diakses pada September 2020)
Russell, B., Moss, C., Rigg, A., & Van Hemelrijck, M. (2020). COVID-19 and treatment with NSAIDs and corticosteroids: Should we be limiting their use in the clinical setting? Ecancermedicalscience. https://doi.org/10.3332/ecancer.2020.1023
Samuel, S., Nguyen, T., & Choi, H. A. (2017). Pharmacologic Characteristics of Corticosteroids. Journal of Neurocritical Care. https://doi.org/10.18700/jnc.170035
Supandi, Yeni, & Merdekawati, F. (2018). In silico study of pyrazolylaminoquinazoline toxicity by lazar, protox, and admet predictor. Journal of Applied Pharmaceutical Science. https://doi.org/10.7324/JAPS.2018.8918
Wan, Y., Shang, J., Graham, R., Baric, R. S., & Li, F. (2020). Receptor recognition by novel coronavirus from Wuhan: An analysis based on decade-long structural studies of SARS. Journal of Virology, 94(7), 1–9. https://doi.org/10.1128/jvi.00127-20
Wang, C., Horby, P. W., Hayden, F. G., & Gao, G. F. (2020). A novel coronavirus outbreak of global health concern. The Lancet. https://doi.org/10.1016/S0140-6736(20)30185-9
Wong, M. C., Cregeen, S. J. J., Ajami, N. J., & Petrosino, J. F. (2020). Evidence of recombination in coronaviruses implicating pangolin origins of nCoV-2019. BioRxiv. https://doi.org/10.1101/2020.02.07.939207
Yang, Z., Lasker, K., Schneidman-Duhovny, D., Webb, B., Huang, C. C., Pettersen, E. F., … Ferrin, T. E. (2012). UCSF Chimera, MODELLER, and IMP: An integrated modeling system. Journal of Structural Biology. https://doi.org/10.1016/j.jsb.2011.09.006
Zhang, H., Penninger, J. M., Li, Y., Zhong, N., & Slutsky, A. S. (2020). Angiotensin-converting enzyme 2 (ACE2) as a SARS-CoV-2 receptor: molecular mechanisms and potential therapeutic target. Intensive Care Medicine, 46(4), 586–590. https://doi.org/10.1007/s00134-020-05985-9