In silico identification of natural products from Centella asiatica as severe acute respiratory syndromecoronavirus 2 main protease inhibitor

Exploring the therapeutic potential of Thai medicinal plants: in vitro screening and in silico docking of phytoconstituents for novel anti-SARS-CoV-2 agents

BACKGROUND

The high virulence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for coronavirus disease 2019 (COVID-19), has triggered global health and economic concerns. The absence of specific antiviral treatments and the side effects of repurposed drugs present persistent challenges. This study explored a promising antiviral herbal extract against SARS-CoV-2 from selected Thai medicinal plants based on in vitro efficacy and evaluated its antiviral lead compounds by molecular docking.

METHODS

Twenty-two different ethanolic-aqueous crude extracts (CEs) were rapidly screened for their potential activity against porcine epidemic diarrhea virus (PEDV) as a surrogate using a plaque reduction assay. Extracts achieving ≥ 70% anti-PEDV efficacy proceeded to the anti-SARS-CoV-2 activity test using a 50% tissue culture infectious dose method in Vero E6 cells. Molnupiravir and extract-free media served as positive and negative controls, respectively. Potent CEs underwent water/ethyl acetate fractionation to enhance antiviral efficacy, and the fractions were tested for anti-SARS-CoV-2 performance. The fraction with the highest antiviral potency was identified using liquid chromatography-high-resolution mass spectrometry (LC-HRMS). Molecular docking analyses of these compounds against the main protease (Mpro) of SARS-CoV-2 (6LU7) were performed to identify antiviral lead molecules. The top three hits were further evaluated for their conformational stability in the docked complex using molecular dynamics (MD) simulation.

RESULTS

The water fraction of mulberry (Morus alba Linn.) leaf CE (WF-MLCE) exhibited the most potent anti-SARS-CoV-2 efficacy with low cytotoxicity profile (CC50 of ~ 0.7 mg/mL), achieving 99.92% in pre-entry mode and 99.88% in postinfection treatment mode at 0.25 mg/mL. Flavonoids and conjugates were the predominant compounds identified in WF-MLCE. Molecular docking scores of several flavonoids against SARS-CoV-2 Mpro demonstrated their superior antiviral potency compared to molnupiravir. Remarkably, myricetin-3-O-β-D-galactopyranoside, maragrol B, and quercetin 3-O-robinobioside exhibited binding energies of ~  - 9 kcal/mol. The stability of each ligand-protein complex of these compounds with the Mpro system showed stability during MD simulation. These three molecules were pronounced as antiviral leads of WF-MLCE. Given the low cytotoxicity and high antiviral potency of WF-MLCE, it holds promise as a candidate for future therapeutic development for COVID-19 treatment, especially considering its economic and pharmacological advantages.

Computational analysis of phytocompounds in Centella asiatica for its antifibrotic and drug-likeness properties - Herb to drug study

Oral submucous fibrosis (OSMF) is a potentially malignant disorder with no permanent cure that affects the quality of life due to trismus. Computational pharmacology has accelerated the discovery of drug candidates for the treatment of incurable diseases. The present study aimed to screen the compounds of the miracle herb Centella asiatica with drug-likeness properties based on the absorption, distribution, metabolism, and excretion (ADME) properties. The pharmacological actions of these screened compounds against OSMF were identified by network pharmacology, gene ontology, pathway enrichment analysis, molecular docking, and simulation. Fifteen drug-like ligands were identified after virtual screening viz; asiatic acid, kaempferol, quercetin, luteolin, apigenin, bayogenin, gallic acid, isothankunic acid, madecassic acid, madasiatic acid, arjunolic acid, terminolic acid, catechin, epicatechin, and nobiletin. 850 potential targets were predicted for the ligands, which were analyzed against 354 proteins associated with OSMF. Compound pathway analysis and disease pathway analysis identified 53 common proteins. The GO enrichment analysis identified 472 biological process terms, 76 molecular function terms, and 44 cellular component terms. Pathway enrichment analysis predicted 142 KEGG pathways, 35 Biocarta pathways, and 236 Reactome pathways for the target proteins. The analysis revealed that the herb targets crucial events of fibrosis such as inflammation, oxidative stress, apoptosis, collagen deposition, and epithelial-mesenchymal transition. The common 53 proteins were used for protein-protein interaction (PPI) network analysis, which revealed 4 key proteins interacting with the phytocompounds viz; transforming growth factor-β1 (TGF-β1), mothers against decapentaplegic-3 (SMAD-3), mitogen-activated protein kinase-1 (MAPK-1) and proto-oncogene tyrosine-protein kinase (SRC). Molecular docking revealed that all ligands had a good binding affinity to the target proteins. Bayogenin had the highest binding affinity towards MAPK-1 (-9.7 kcal/mol), followed by isothankunic acid towards SRC protein (-9.3 kcal/mol). Madasiatic acid had the highest binding affinity to SMAD-3 (-7.6 kcal/mol) and TGF-β1 (-7.1 kcal/mol). Molecular dynamics simulation demonstrated stable ligand protein interactions of bayogenin and MAPK complex, isothankunic acid and SRC complex. This in silico study is the first to identify potential phytochemicals present in Centella asiatica and their target molecules, which might be responsible for reversing OSMF.

Dipeptidyl peptidase IV inhibition of phytocompounds from Artocarpus champeden (Lour.) Stokes: In silico molecular docking study and ADME-Tox prediction approach

The present study examines the potential activity prediction based on free binding energy (ΔG) and interaction confirmation of phytocompounds from Artocarpus champeden (Lour.) Stokes with macromolecule protein receptor of dipeptidyl peptidase IV (DPP-IV) using in silico molecular docking studies and physicochemical and pharmacokinetic properties (ADME-Tox) prediction approaches. The active subsites of the DPP-IV receptor macromolecule protein Protein Data Bank (ID: 1 × 70) were docked using Autodock v4.2.6 (100 docking runs). A grid box of 52 × 28 × 26 Å points spaced by 0.37 Å was centered on the active site of x = 40.926 Å; y = 50.522 Å; z = 35.031 Å. For ADME-Tox prediction, Swiss ADME online-based application programs were used. The results show that 12 pythocompounds from A. champeden have the potential as DPP-IV inhibitors based on ΔG value and interaction conformation. There are five pythocompounds with lower ΔG values and inhibition constants than the native ligand and seven pythocompounds with ΔG values and inhibition constants close to the native ligand. The 12 compounds form an interaction conformation at the active subsites of the DPP-IV receptor. At the same time, the results of the ADME-Tox prediction analysis showed that the 12 compounds had different physicochemical and pharmacokinetic properties.