IDENTIFICATION OF INDONESIAN ETHNOMEDICINAL PLANTS AS POTENTIAL DRUG CANDIDATES FOR ACUTE RESPIRATORY INFECTION USING COMPUTER-AIDED DRUG DESIGN AND SIMRS MODEL
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Abstract
In 2023, Indonesia’s air quality deteriorated, with its Air Quality Index (AQI) tripling clean air standards, causing health sector losses, including a surge in Acute Respiratory Infection (ARI) cases. One of the ARI treatments is the consumption of cefuroxime, yet it can cause side effects. Indonesia’s floral biodiversity in ethnomedicinal plants can be utilized as a more natural drug candidate for ARI drugs. To determine this, an in silico approach is performed through molecular docking, and Pre-ADMET prediction. Based on the compound selection’s results, lanosterol is the most promising compound, with a binding energy value of -8.11 kcal/mol and an efficiency of 78.81%, while cefuroxime as a reference ligand has a binding energy value of -5.92 kcal/mol with an efficiency of 67.87%. After undergoing compound selection, a time series analysis through the Susceptible Infected Medicine Recovered Susceptible (SIMRS) model is conducted. In this analysis, it is found that cefuroxime and lanosterol require the same amount of time, which is 33 days to restore Indonesia to its pre-ARI outbreak condition, indicating that lanosterol can be used as an alternative drug candidate.
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References
Carugo, O. (n.d.). How root.mean-square distance (r.m.s.d.) Values Depend on the Resolution of Protein Structures that are Compared [Review of How
root.mean-square distance (r.m.s.d.) Values Depend on the Resolution of Protein Structures that are Com-pared]. https://www.researchgate.net/publication/250630176_How_root-mean-square_distance_rmsd_values_depend_on_the_resolution_of_protein_structures_that_are_compared.
Gordon, E., Mouz, N., Duee, E., & Dide-berg, O. (2002). The crystal structure of the penicillin-binding protein 2x from Streptococcus pneumoniae and its acyl-enzyme form: implication in drug resistance. DOI: 10.1006/jmbi.2000.3740.
Hariyono, P., Dwiastuti, R., Yusuf, M., Salin, N. H., & Hariono, M. (2021). 2-Phenoxyacetamide derivatives as SARS-CoV-2 main protease inhibitor: In silico studies. DOI: 10.1016/j.rechem.2021.100263.
Indonesia’s Worsening Air Quality and its Impact on Life Expectancy [https://aqli.epic.uchicago.edu/wp-content/uploads/2019/03/Indonesia-Report.pdf], accessed at 18 Septem-ber 2023.
ISPA DKI Jakarta Capai 638 Ribu Kasus per Semester I 2023 [https://databoks.katadata.co.id/datapublish/2023/08/15/ispa-dki-jakarta-capai-638-ribu-kasus-per-seme], ac-cessed at 27 September 2023.
Lipinski, C. A. L. (n.d.). Lipinski, C.A. Lead- and drug-like compounds: the rule-of-five revolution. Drug Discov. Today Technol. 1, 337-341. https://www.researchgate.net/publication/223900692_Lipinski_CA_Lead-_and_drug-like_compounds_the_rule-of-five_revolution_Drug_Discov_Today_Technol_1_337-341.
Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (2001). Experi-mental and computational approaches to estimate solubility and permeability in drug discovery and development settings. DOI: 10.1016/s0169-409x(00)00129-0.
Pires, D. E. V., Bundell, T. L., & Ascher, D. B. (2015, April 10). pkCSM: Predicting
Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures. DOI: 10.1021/acs.jmedchem.5b00104a.
Sun, D., Gao, W., Hu, H., & Zhou, S. (2022). Why 90% of clinical drug de-velopment fails and how to improve it? DOI: 10.1016/j.apsb.2022.02.002.