Investigating the Inhibition Effect of Portulaca oleracea against SARS-CoV-2 through Molecular Docking Simulation

Research Article

Austin J Anal Pharm Chem. 2021; 8(1): 1132.

Investigating the Inhibition Effect of Portulaca oleracea against SARS-CoV-2 through Molecular Docking Simulation

El-Hoshoudy AN*, Zaki EG and Elsaeed SM

Computational Chemistry Group, Egyptian Petroleum Research Institute, Egypt

*Corresponding author: El-Hoshoudy AN, Computational Chemistry Group, Egyptian Petroleum Research Institute, 11727, Nasr City, Cairo, Egypt

Received: April 08, 2021; Accepted: April 28, 2021; Published: May 05, 2021


Recently a new virus strain designated as SARS coronavirus result in a fatal pandemic known as COVID-19. Bioinformatics and drug screening are directed for the assessment of potential inhibitors before their clinical implementation for the treatment of this fatal pneumonia. One of the expected natural potent inhibitors is Portulaca oleracea which has been assigned as an effective drug to different human ailments throughout the whole world. P. oleracea is widely spread in most areas of Egypt. In the current study, hydrophilic polysaccharides were purified from Portulaca oleracea extracts. Molecular docking simulation is implemented to investigate the antiviral effect of the purified polysaccharides to inhibit COVID-19. The viral protease was downloaded from a Protein Data Bank (PDB# 6y84) then docked with the potent inhibitors. The docking results indicate that the purified polysaccharides can bind tightly to the SARS-CoV-2 viral protease, which indicates that P. oleracea is a potential inhibitor for COVID-19.

Keywords: COVID-19; Homology modeling; Portulaca oleracea; Molecular docking


Coronaviruses (CoVs), comprise four species which divided into a-, β-, d- and γ-coronaviruses [1]. SARS-CoV-2 or synonymously known as (COVID-19) considered a distinct species of β-coronaviruses that infect the whole world with pathogenic viral pneumonia [1- 12] that results in a noteworthy threat to the community health [1]. SARS-CoV-2 is a positive single RNA strand with an external envelope, and gene sequence ranging from 26.0 to 32.0 kilobases [13- 15]. Coronaviruses (CoVs) consist of two distinguishing proteins; the first category is structural proteins which include Nucleocapsid (N), Spike (S), Membrane (M), and hydrophobic Envelope (E) that covers the entire coronavirus surface [16]. The second category is non-structural proteins which comprise RdRp (nsp12) and proteases (nsp3 and nsp5) [6,17]. The transmembrane Spike (S) glycoprotein gives rise to homotrimers projecting from the viral envelope [18] and stimulates virus entrance into the host cell receptors [19,20] in addition to promoting the association of the viral and host receptors [21]. Respiratory blobs and close contact in overcrowded associations are conventional transmission facilities for SARS-CoV-2 [22]. on February 5th, 2020, the first high-resolution crystal structure of SARS-CoV-2 protease released on Protein Data Bank (PDB) Doi: 10.2210/pdb6lu7/pdb [19,23,24]. On 3rd March 2020, 6y84 was designated as SARS-CoV-2 protease with unbonded active site DOI: 10.2210/pdb6y84/pdb.

Currently, medical research continues instantly to identify active antiviral inhibitors that may help to hinder the pandemic spreading of the viral infection. However, no licensed therapeutic vaccine or drug has been targeted till our current times [2,19,25,26]. As a result, the instant approach depends on the utilization of computational methods of bioinformatics, combined structure-assisted drug design, and drug screening [2,27], as well as the establishment of predictive 3D protein structures of SARS-CoV-2 to recognize new inhibiting vaccine for SARS-CoV-2 protease [23,28].

Methods of computer-aided drug discovery have arisen as potent tools in the drug discovery process and have been used lately to study protein-drug/ protein-protein interactions and to identify protein inhibitors [29-31]. The targeting of a potent drug into an approved drug is a time-consuming process. Consequently, a set of computational approaches such as molecular docking, virtual screening, binding free energy evaluation, and molecular dynamics simulation, serves as excellent alternatives for recognizing potential drug agents from compound databank [32]. Cava et al. used in silico gene expression profiles to investigate the mechanism of the Angiotensin-Converting Enzyme 2 (ACE2) using the documented potential drug agents for COVID-19 [33]. Wang et al. investigate the antiviral drugs with high binding affinity against 3CLpro through conducting the virtual screening of the used drugs in clinical trials [34]. Zhang et al. identify potential SARSCoV-2 inhibitors through conducting in silico screening approach for traditional Chinese drugs [35]. Liang et al. conducted a molecular dynamic simulation to validate the binding affinity of a-ketoamide inhibitors to the SARS-CoV-2 main protease. In the current study, molecular docking simulation was conducted on polysaccharides derived from the extract of Portulaca oleracea to assess their ability to inhibit the SARS-CoV-2 protease. Portulaca oleracea (duckweed) is an annual succulent in the Portulacaceae family with slight hogweed or parsley which may reach 16 inches in height [36]. Molecular docking permits rapid screening of the sequences of amino acid through many coronaviruses’ species such as SARS-CoV-2 [23,37]. The reported docking data were promised and suggest a potential inhibition against the newly pandemic COVID-19 from the currently accessible natural plants [19].

Methods and Reagents

All the reported ligands were built up through the builder module in the docking software, subjected to energy minimization before the commencement of the docking study, then saved as an MDB file in the docking database [25]. The selected ligands comprise the polysaccharides derived from the Portulaca oleracea extract. Table 1 summarizes the structure of the compounds used for molecular docking simulation.