In silico analysis of the interactions of certain flavonoids with the receptor-binding domain of 2019 novel coronavirus and cellular proteases and their pharmacokinetic properties

Abstract

Coronavirus Disease 2019 (COVID-19) has infected more than thirty five million people worldwide and caused nearly 1 million deaths as of October 2020. The microorganism causing COVID-19 was named as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2 or 2019-nCoV). The aim of this study was to investigate the interactions of twenty-three phytochemicals belonging to different flavonoid subgroups with the receptor binding domain (RBD) of the spike glycoprotein of 2019-nCoV, and cellular proteases [transmembrane serine protease 2 (TMPRSS2), cathepsin B and L (CatB/L)]. The compounds interacted more strongly with CatB and CatL than with the other proteins. Van der Waals and hydrogen bonds played an important role in the receptor-ligand interactions. As a result of RBCI (relative binding capacity index) analysis conducted to rank flavonoids in terms of their interactions with the target proteins, (-) -epicatechin gallate interacted strongly with all the proteins studied. The results obtained from molecular dynamics and molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) methods also supported this data. According to Lipinski's rule of five, (-) -epicatechin gallate showed drug-likeness properties. Although this molecule is not capable of crossing the blood-brain barrier (BBB), it was concluded that (-) -epicatechin gallate can be evaluated as a candidate molecule in drug development studies against 2019-nCoV since it was not the substrate of P-gp (P-glycoprotein), did not inhibit any of the cytochrome Ps, and did not show AMES toxicity or hepatotoxicity on eukaryotic cells.

New perspectives on natural flavonoids on COVID‐19‐induced lung injuries

“…Studies using molecular docking showed that rutin, which was approved by NMPA (National Medical Products Administration), exhibited the best effect in the binding affinity to inhibit SARS‐CoV‐2 compared to other compounds (Xu et al, 2020). Some authors have also shown that certain flavonoids can interact with the receptor binding of the SARS‐CoV‐2 using in silico analysis (Istifli et al, 2020). In this computational study, the group of flavonoids anthocyanidins, isoflavones, and flavanones showed improved interaction with the target proteins, in special (−)‐epicatechin gallate.…”

Targeting Neurological Manifestations of Coronaviruses by Candidate Phytochemicals: A Mechanistic Approach

“…Papyriflavonol A as a prenylated flavone inhibited the PLpro and 3CLpro of SARS-CoV at 3.7 and 103.6 µM, respectively ( Park et al, 2017 ). Also, Ryu and co-workers showed that a biflavonoid, amentoflavone, blocked the 3CLpro at 8.3 µM while apigenin, luteolin, and quercetin inhibited the enzyme at 280.8, 20.2, and 23.8 µM, respectively ( Ryu et al, 2010a ; Yao et al, 2018 ; Istifli et al, 2020 ). Oolonghomobisflavan-A ( Bhardwaj et al, 2020 ), narcissin ( Owis et al, 2020 ), isolophirachalcone ( Parvez et al, 2020 ), fortunellin ( Panagiotopoulos et al, 2020 ), dieckol ( Park et al, 2013 ), gallocatechin-3-gallate ( Ghosh et al, 2020 ) are other polyphenols with inhibitory effects on SARS-CoV-2 proteases.…”

Molecular interactions of some phenolics with 2019-nCoV and related pathway elements

“…Since, the crystallographic structure of human TMPRSS2 enzyme has not still been defined, using SWISS-MODEL, we generated a homology model of this enzyme to utilize in further molecular docking analyses. The details of the homology modeling procedure can be found in the study of Istifli et al (2020). The PROCHECK web server was utilized whether our generated model has an energetically favorable conformation (Figure S1) and the ERRAT web-based tool was also employed to calculate the protein overall quality factor (OQF) (Figure S2) (Colovos & Yeates, 1993;Laskowski et al, 1996).…”

“…In this study, the relative binding capacity index (RBCI) was applied to statistically rank the activity potentials of phytochemicals using the binding free energy values obtained from the binding analysis (Figure 2 and Table S1) (Istifli et al, 2020). Using RBCI, it is possible to compare statistically relevant data with different scientific meanings.…”