Exploring active compounds of kelor (Moringa oleifera Lam.) leaves as an alternative medicine to improve immunity in facing COVID-19 via in silico study

Agus Mohammad Hikam; Nurul Jadid Mubarakati; Rasyadan Taufiq Probojati; Muhammad Hermawan Widyananda; Viol Dhea Kharisma; Arif Nur Muhammad Ansori

doi:10.55655/genbinesia.v1i1.7

Agus Mohammad Hikam Faculty of Mathematics and Natural Sciences, Universitas Islam Malang, Malang, Indonesia
Nurul Jadid Mubarakati Faculty of Mathematics and Natural Sciences, Universitas Islam Malang, Malang, Indonesia
Rasyadan Taufiq Probojati Department of Agrotechnology, Faculty of Agriculture, Universitas Kadiri, Kediri, Indonesia
Muhammad Hermawan Widyananda Faculty of Mathematics and Natural Sciences, Universitas Brawijaya, Malang, Indonesia
Viol Dhea Kharisma Faculty of Mathematics and Natural Sciences, Universitas Brawijaya, Malang, Indonesia
Arif Nur Muhammad Ansori Faculty of Veterinary Medicine, Universitas Airlangga, Surabaya, Indonesia

DOI: https://doi.org/10.55655/genbinesia.v1i1.7

Keywords: Antiviral, COVID-19, In Silico Analysis, M. Oleifera

Abstract

SARS-CoV-2 is a new strain of coronavirus (CoV) that was identified in Wuhan in 2019. This virus is known to have the ability to reduce human immunity. Kelor (Moringa oleifera) is a potential natural resource in Indonesia, which is very abundant and contains several metabolic compounds such as phenolics, flavonoids, saponins, cytokines, and caffeoylquinic acid, which was reported to show antioxidants, antibacterial and antiviral. This study aims to predict the biological activity, physicochemical properties, toxicity, and affinity-interactions of the active compounds of M. oleifera leave. The active compounds of M. oleifera were obtained from the KNApSAcK and PubChem. Analysis of the bioactivity of the compounds using the Way2Drug Pass Online. Analysis of drug-likeness and toxicity using the Lipinski web server and pkCSM. Docking is done using Autodock vina software to analyze the interaction of the compounds with M^pro. The results indicate that the compound astragalin is the compound with the highest affinity value, namely -8.7 (kcal/mol), compared to lopinavir as a control compound with an affinity value -6.6 (kcal/mol). The types of bonds in astragalin compounds are hydrogen bonds with amino acids Glutamine 127 and Arginine 298. From these results, it is predicted that astragalin compounds have the highest potential as alternative drugs to increase body immunity against the COVID-19.

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Author Biographies

Agus Mohammad Hikam, Faculty of Mathematics and Natural Sciences, Universitas Islam Malang, Malang, Indonesia

Faculty of Mathematics and Natural Sciences

Nurul Jadid Mubarakati, Faculty of Mathematics and Natural Sciences, Universitas Islam Malang, Malang, Indonesia

Faculty of Mathematics and Natural Sciences

Rasyadan Taufiq Probojati, Department of Agrotechnology, Faculty of Agriculture, Universitas Kadiri, Kediri, Indonesia

Department of Agrotechnology

Muhammad Hermawan Widyananda, Faculty of Mathematics and Natural Sciences, Universitas Brawijaya, Malang, Indonesia

Faculty of Mathematics and Natural Sciences

Viol Dhea Kharisma, Faculty of Mathematics and Natural Sciences, Universitas Brawijaya, Malang, Indonesia

Faculty of Mathematics and Natural Sciences

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