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Penambatan Molekuler Terhadap Target antiinflamasi, Network pharmacology Profiling ADMET, dan Pemodelan Klirens QSPR Polifenol Chromolaena odorata
Abstract
Pendahuluan: Inflamasi merupakan respons biologis penting, tetapi aktivasi yang berlebihan dapat berkontribusi terhadap berbagai gangguan patologis sehingga diperlukan pencarian kandidat antiinflamasi baru dari bahan alam. Tujuan: Penelitian ini bertujuan mengevaluasi potensi antiinflamasi enam senyawa terpilih yang relevan dengan Chromolaena odorata L., yaitu genkwanin, sakuranetin, isosakuranetin, eupatilin, quercetin, dan 4,6′-dihidroksi-2′,3′,4′-trimetoksi chalcone, melalui pendekatan in silico. Metode: Penelitian dilakukan menggunakan PASS Online untuk prediksi aktivitas biologis awal, SwissTargetPrediction dan GeneCards untuk identifikasi target protein dan gen terkait inflamasi, STRING, STITCH, dan Cytoscape untuk analisis jejaring biologis, pkCSM untuk prediksi ADMET, ProTox-II untuk prediksi toksikologi, molecular docking terhadap cyclooxygenase-2 (COX-2), serta analisis quantitative structure–property relationship (QSPR). Hasil: Seluruh senyawa menunjukkan nilai probability of activity lebih tinggi dibandingkan probability of inactivity untuk aktivitas antiinflamasi. Analisis target menunjukkan keterlibatan beberapa protein yang relevan dengan inflamasi, terutama MMP2, MMP9, EGFR, ABCB1, GSK3B, dan PPARG. Prediksi pkCSM menunjukkan variasi profil ADME antar-senyawa, sedangkan ProTox-II menunjukkan profil toksikologi yang tidak seragam. Pada molecular docking, quercetin dan eupatilin menunjukkan afinitas pengikatan tertinggi terhadap COX-2, masing-masing sebesar −9,19 dan −9,1 kcal/mol. Analisis QSPR menunjukkan bahwa molar refractivity merupakan deskriptor yang paling informatif terhadap variasi clearance pada dataset yang digunakan. Kesimpulan: Keenam senyawa memiliki potensi awal sebagai kandidat antiinflamasi, dengan quercetin dan eupatilin menunjukkan profil in silico yang paling menonjol, meskipun seluruh temuan masih memerlukan validasi eksperimental lebih lanjut.
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Stankov S V. Definition of Inflammation, Causes of Inflammation and Possible Anti-inflammatory Strategies. Open Inflamm J 2012;5:1–9. https://doi.org/10.2174/1875041901205010001.
Lucas GNC, Leitaõ ACC, Alencar RL, Xavier RMF, Daher EDF, Silva GB Da. Pathophysiological aspects of nephropathy caused by non-steroidal anti-inflammatory drugs. Brazilian Journal of Nephrology 2019;41. https://doi.org/10.1590/2175-8239-JBN-2018-0107.
Bindu S, Mazumder S, Bandyopadhyay U. Non-steroidal anti-inflammatory drugs (NSAIDs) and organ damage: A current perspective. Biochem Pharmacol 2020;180. https://doi.org/10.1016/j.bcp.2020.114147.
Cahyo ASD, Oktavia S, Ifora I. Anti-Inflammatory and Analgesic Potential of Chromolaena odorata: A Review. International Journal of Pharmaceutical Sciences and Medicine 2021;6. https://doi.org/10.47760/ijpsm.2021.v06i09.002.
Ishak N, Usaizan N, Raffi A. Phytochemical and Antibacterial Screening of Chromolaena odorata Leaf Extract. Journal of Science and Mathematics Letters 2023;11. https://doi.org/10.37134/jsml.vol11.sp.12.2023.
Bunkaew N, Saensena P, Boonpeng P, Sumranmak P, Hanpipatsatian T, Pan-utai W. Antioxidant and antibacterial potential of Chromolaena odorata (L.) medicinal plant extracts. Journal of Biological Research (Italy) 2025;98. https://doi.org/10.4081/jbr.2025.12500.
Ajay A, Rupesh K, Shamal B, Blainy B, Abhishek K, Sanjay KG, et al. Pharmacological Importance of Chromolaena odorata: a review. International Journal of Pharmaceutics and Drug Analysis 2021;9.
Aziz NA. The Pharmacological Properties and Medicinal Potential of Chromolaena odorata: A Review. International Journal of Pharmaceuticals, Nutraceuticals and Cosmetic Science 2020;2. https://doi.org/10.24191/ijpnacs.v2.04.
Olawale F, Olofinsan K, Iwaloye O. Biological activities of Chromolaena odorata: A mechanistic review. South African Journal of Botany 2022;144. https://doi.org/10.1016/j.sajb.2021.09.001.
Nur Qamarina Hazian, Nur Ainun Mokhtar, Nurulbahiyah Ahmad Khairudin. In Silico Molecular Docking Simulation of Chromolaena Odorata Phytoconstituents Against Matrix Metalloproteinase Proteins – 9 (MMP-9). Journal of Research in Nanoscience and Nanotechnology 2023;7. https://doi.org/10.37934/jrnn.7.1.16.
Mokhtar NA, Tap FM, Talib SZA, Khairudin NA. Docking study for assessment of wound healing potential of isosakuratenin isolated from Chromolaena odorata: An In-silico approach. IOP Conf Ser Mater Sci Eng 2021;1051. https://doi.org/10.1088/1757-899x/1051/1/012078.
Sivapria AS, Kariyil BJ, Menon PK, Sankar HVJ. In silico screening of phytoconstituents of Cissus quadrangularis and Chromolaena odorata against proteins of antimicrobial resistance and wound healing. Plant Science Today 2024;11. https://doi.org/10.14719/pst.3016.
Illian DN, Widiyana AP, Hasana AR, Maysarah H, Al Mustaniroh SS, Basyuni M. In silico approach: Prediction of ADMET, molecular docking, and QSPR of secondary metabolites in Mangroves. J Appl Pharm Sci 2022;12:021–9. https://doi.org/10.7324/JAPS.2022.121103.
Osman W, Shantier S, Mohamed N, Abdalla S, Mohamed M, Umar Y, et al. Prediction of ADMET, molecular docking, DFT, and QSPR of potential phytoconstituents from Ambrosia maritima L. targeting xanthine oxidase. Pharmacia 2024;71:1–10. https://doi.org/10.3897/pharmacia.71.e127845.
Widiyana AP, Widiandani T, Siswodihardjo S. Molecular docking and QSPR of 5-O-acetylpinostrobin derivatives that inhibit ERα as breast cancer drug candidates. Journal of Medicinal and Pharmaceutical Chemistry Research 2023;5:1194–203. https://doi.org/10.48309/jmpcr.2023.182473.
Masfria, Lucida H, Atifah Y, Syahputra H, Sihombing HM. Inhibition Activity of Liquid Smoke Cocos Nucifera L. on DPP-IV and AGE-Rage in Silico and in Vitro: Antidiabetic and Anti-Inflammatory Activity. International Journal of Applied Pharmaceutics 2024;16:275–82. https://doi.org/10.22159/IJAP.2024V16I5.51231.
Wang Z, Yang H, Huang Y. Integrating Network Pharmacology and Traditional Chinese Medicine for Effective Inflammation Treatment. Asian Journal of Medicine and Health 2024;22. https://doi.org/10.9734/ajmah/2024/v22i71062.
Wang K, Yin J, Chen J, Ma J, Si H, Xia D. Inhibition of inflammation by berberine: Molecular mechanism and network pharmacology analysis. Phytomedicine 2024;128. https://doi.org/10.1016/j.phymed.2023.155258.
Praditapuspa EN, Siswandono, Widiandani T. In silico analysis of pinostrobin derivatives from boesenbergia pandurata on ErbB4 kinase target and QSPR linear models to predict drug clearance for searching anti-breast cancer drug candidates. Pharmacognosy Journal 2021;13:1143–9. https://doi.org/10.5530/pj.2021.13.147.
Chen Y, Lu M, Lin M, Gao Q. Network pharmacology and molecular docking to elucidate the common mechanism of hydroxychloroquine treatment in lupus nephritis and IgA nephropathy. Lupus 2024;33. https://doi.org/10.1177/09612033241230377.
Wu D, Hong L, Xu S, Zhong Z, Gong Q, Wang Q, et al. Integrating network pharmacology and experimental validation via PPAR signaling to ameliorate rheumatoid arthritis: Insights from Corydalis Decumbentis Rhizoma (Xiatianwu). Fitoterapia 2025;183. https://doi.org/10.1016/j.fitote.2025.106541.
Boonyong C, Powthong P. Prediction of primary human targets and toxicity mechanisms of imidacloprid using integrative In Silico approaches. Toxicol Rep 2026;16. https://doi.org/10.1016/j.toxrep.2026.102199.
Jurowski K, Niżnik Ł, Frydrych A, Kobylarz D, Noga M, Krośniak A, et al. Toxicological profile of Acovenoside A as an active pharmaceutical ingredient – prediction of missing key toxicological endpoints using in silico toxicology methodology. Chem Biol Interact 2025;408. https://doi.org/10.1016/j.cbi.2025.111404.
DOI: https://doi.org/10.33085/jdf.v10i2.6921
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