In Silico Biological Activity Prediction of Bioactive Compounds from Dumortiera hirsuta (Sw.) Nees. Using Way2Drug PASS Online
In Silico Biological Activity Prediction of Bioactive Compounds from Dumortiera hirsuta (Sw.) Nees. Using Way2Drug PASS Online
Abdillah Maulana Farhan
Laboratory of Botany, Department of Biology, Faculty of Mathematics and Natural Sciences, University of Jember, Jember, Indonesia
Waki'atil Rosida
Laboratory of Botany, Department of Biology, Faculty of Mathematics and Natural Sciences, University of Jember, Jember, Indonesia
Fuad Bahrul Ulum
Laboratory of Botany, Department of Biology, Faculty of Mathematics and Natural Sciences, University of Jember, Jember, Indonesia
DOI: https://doi.org/10.19184/lsb.v3i1.53690
ABSTRACT
The liverwort Dumortiera hirsuta (Sw.) Nees. is recognized as a potential source of pharmacologically active metabolites. Bioactive compounds from D. hirsuta have been previously reported through in vitro metabolomic analyses using gas chromatography–mass spectrometry (GC–MS) and liquid chromatography–mass spectrometry (LC–MS). In this study, the biological activities of the GC-MS-identified metabolites were evaluated in silico using the Way2Drug PASS Online platform. The results indicated that ten metabolites from D. hirsuta exhibit medicinal potential, with Pa values greater than 0.7, suggesting a high probability of biological activity. Among these compounds, stigmasterol (Pa = 0.970) and lathosterol (Pa = 0.960) demonstrated the strongest antihypercholesterolemic potential, indicating their role as natural agents for reducing cholesterol levels. These findings highlight the pharmacological potential of D. hirsuta metabolites and warrant further validation through in vitro cholesterol-lowering assays to confirm their predicted activities.
Keywords: antihypercholesterolemic, Dumortiera hirsuta, in silico, PASS Online.
Published
18-05-2025
Issue
Vol. 3 No. 1 2025: Jurnal Life Science and Biotechnology
Pages
13-19
License
Copyright (c) 2025 Jurnal Life Science and Biotechnology