Virtual screening of Indonesian herbal compounds as COVID-19 supportive therapy: machine learning and pharmacophore modeling approaches

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Linda Erlina, Rafika Indah Paramita, Wisnu Ananta Kusuma, Fadilah Fadilah, Aryo Tedjo, Irandi Putra Pratomo, Nabila Sekar Ramadhanti, Ahmad Kamal Nasution, Fadhlal Khaliq Surado, Aries Fitriawan, Khaerunissa Anbar Istiadi, Arry Yanuar

2022 BMC Complementary Medicine and Therapies Vol. 22 Issue 1 Article Cited by 30 SDG 3SDG 17 Quartile

Abstract

Background: The number of COVID-19 cases continues to grow in Indonesia. This phenomenon motivates researchers to find alternative drugs that function for prevention or treatment. Due to the rich biodiversity of Indonesian medicinal plants, one alternative is to examine the potential of herbal medicines to support COVID therapy. This study aims to identify potential compound candidates in Indonesian herbal using a machine learning and pharmacophore modeling approaches. Methods: We used three classification methods that had different decision-making processes: support vector machine (SVM), multilayer perceptron (MLP), and random forest (RF). For the pharmacophore modeling approach, we performed a structure-based analysis on the 3D structure of the main protease SARS-CoV-2 (3CLPro) and repurposed SARS, MERS, and SARS-CoV-2 drugs identified from the literature as datasets in the ligand-based method. Lastly, we used molecular docking to analyze the interactions between the 3CLpro and 14 hit compounds from the Indonesian Herbal Database (HerbalDB), with lopinavir as a positive control. Results: From the molecular docking analysis, we found six potential compounds that may act as the main proteases of the SARS-CoV-2 inhibitor: hesperidin, kaempferol-3,4'-di-O-methyl ether (Ermanin); myricetin-3-glucoside, peonidin 3-(4’-arabinosylglucoside); quercetin 3-(2G-rhamnosylrutinoside); and rhamnetin 3-mannosyl-(1-2)-alloside. Conclusions: Our layered virtual screening with machine learning and pharmacophore modeling approaches provided a more objective and optimal virtual screening and avoided subjective decision making of the results. Herbal compounds from the screening, i.e. hesperidin, kaempferol-3,4'-di-O-methyl ether (Ermanin); myricetin-3-glucoside, peonidin 3-(4’-arabinosylglucoside); quercetin 3-(2G-rhamnosylrutinoside); and rhamnetin 3-mannosyl-(1-2)-alloside are potential antiviral candidates for SARS-CoV-2. Moringa oleifera and Psidium guajava that consist of those compounds, could be an alternative option as COVID-19 herbal preventions. © 2022, The Author(s).

Affiliations

Department of Medical Chemistry, Faculty of Medicine, Universitas Indonesia, Jalan Salemba Raya number 4, Jakarta, 10430, Indonesia; Bioinformatics Core Facilities - IMERI, Faculty of Medicine, Universitas Indonesia, Jalan Salemba Raya number 6, Jakarta, 10430, Indonesia; Department of Computer Science, Faculty of Mathematics and Natural Science, IPB University, Jalan Meranti Wing 20 level 5 Kampus IPB, West Java, Bogor, 16680, Indonesia; Tropical Biopharmaca Research Center, Institute of Research and Community Empowerment, IPB University, Jalan Taman Kencana number 3, West Java, Bogor, 16128, Indonesia; Department of Pulmonology and Respiratory Medicine, Faculty of Medicine, Universitas Indonesia – Universitas Indonesia Hospital, West Java, Depok, 16424, Indonesia; Department of Biology, Institut Teknologi Sumatera, Lampung, Bandar Lampung, 35365, Indonesia; Biomedical Computational and Drug Design Laboratory, Faculty of Pharmacy, Universitas Indonesia, Kampus Baru UI, West Java, Depok, 16424, Indonesia

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