Dewi, Diana Candra
ORCID: https://orcid.org/0009-0004-7008-3531, Nastiti, Ginanjar Putri
ORCID: https://orcid.org/0009-0003-8468-9385, Syahrir, Achmad, Maulina, Novia, Putra, Galih S., Taek, Maximus M. and Ma'arif, Burhan
ORCID: https://orcid.org/0000-0001-9182-343X
(2026)
Identification of potential receptor targets of alstonia spectabilis using network pharmacology integrated with gene ontology and KEGG pathway enrichment analysis.
Adolescencia e Saude, 12 (7).
pp. 820-831.
ISSN 2177-5281
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Abstract
Malaria is an ancient disease that has not been eradicated until now. The antimalarial drug chloroquine is currently ineffective due to resistance to Plasmodium sp. Therefore, the public urgently needs a new antimalarial drug that is both effective and affordable. In the metabolite profile using gas chromatography mass spectrometry (GC-MS) and ultra-performance liquid chromatography quadrupole time of flight mass spectrometry (ULPC-QToF-MS/MS) instruments, the 70% ethanol extract of A. spectabilis contains compounds that are efficacious as antimalarial, anti-inflammatory, antipyretic, and analgesic, such as macralstonidine, pleiocarpamine, villalstonine, and various other compounds. Compounds obtained from metabolite profiling testing are prepared by physicochemical screening based on Lipinski's Law of Five, predicting the toxicity of the compound and predicting the pharmacokinetics of the compound, and then molecular docking is carried out on the receptor. Molecular dynamics was also carried out on compounds resulting from metabolite profiling on a personal computer (PC) Linux Ubuntu 20.04.1 LTS 64-bit system, NVIDIA Quadro P2200 graphics card, 16 GB RAM, and Intel Xeon(R) W-2223 @ 3.60 GHz octa-core processor with Desmond at Maestro Schrödinger 2021–2. The results of this study revealed that there were 5 potential compounds that bind to PfENR receptor and 5 potential compounds to PfCRT receptor.
| Item Type: | Journal Article |
|---|---|
| Keywords: | alstonia spectabilis; antimalaria; molecular dynamics |
| Subjects: | 03 CHEMICAL SCIENCES > 0304 Medicinal and Biomolecular Chemistry > 030404 Cheminformatics and Quantitative Structure-Activity Relationships |
| Divisions: | Faculty of Mathematics and Sciences > Department of Chemistry |
| Depositing User: | Diana Dewi |
| Date Deposited: | 21 Sep 2026 15:42 |
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