A small molecule compound berberine as an orally active therapeutic candidate against COVID-19 and SARS: A computational and mechanistic study

Abstract

The novel coronavirus disease, COVID-19, has grown into a global pandemic and a major public health threat since its breakout in December 2019. To date, no specific therapeutic drug or vaccine for treating COVID-19 and SARS has been FDA approved. Previous studies suggest that berberine, an isoquinoline alkaloid, has shown various biological activities that may help against COVID-19 and SARS, including antiviral, anti-allergy and inflammation, hepatoprotection against drug- and infection-induced liver injury, as well as reducing oxidative stress. In particular, berberine has a wide range of antiviral activities such as anti-influenza, anti-hepatitis C, anti-cytomegalovirus, and anti-alphavirus. As an ingredient recommended in guidelines issued by the China National Health Commission for COVID-19 to be combined with other therapy, berberine is a promising orally administered therapeutic candidate against SARS-CoV and SARS-CoV-2. The current study comprehensively evaluates the potential therapeutic mechanisms of berberine in preventing and treating COVID-19 and SARS using computational modeling, including target mining, gene ontology enrichment, pathway analyses, protein-protein interaction analysis, and in silico molecular docking. An orally available immunotherapeutic-berberine nanomedicine, named NIT-X, has been developed by our group and has shown significantly increased oral bioavailability of berberine, increased IFN-γ production by CD8+ T cells, and inhibition of mast cell histamine release in vivo, suggesting a protective immune response. We further validated the inhibition of replication of SARS-CoV-2 in lung epithelial cells line in vitro (Calu3 cells) by berberine. Moreover, the expression of targets including ACE2, TMPRSS2, IL-1α, IL-8, IL-6, and CCL-2 in SARS-CoV-2 infected Calu3 cells were significantly suppressed by NIT-X. By supporting protective immunity while inhibiting pro-inflammatory cytokines; inhibiting viral infection and replication; inducing apoptosis; and protecting against tissue damage, berberine is a promising candidate in preventing and treating COVID-19 and SARS. Given the high oral bioavailability and safety of berberine nanomedicine, the current study may lead to the development of berberine as an orally, active therapeutic against COVID-19 and SARS.

Keywords: COVID-19 and SARS; anti-viral; apoptosis; berberine; computational modeling.

FIGURE 1

The workflow of computational modeling used for analysis of berberine as a promising candidate against COVID‐19 and SARS. TTD: therapeutic target database; GAD: genetic association database; SEA: similarity ensemble approach; PPI: protein‐protein interactions; ACE2: angiotensin‐converting enzyme 2; TMPRSS2: transmembrane serine protease 2; PLpro: Papain‐like Protease; 3CLpro: coronavirus main proteinase; RdRp: RNA‐dependent RNA polymerase. First, a total of 254 genes for SARS and 247 genes for COVID‐19 were selected as possible targets for berberine. Separately, 109 inflammatory and biological targets of berberine were collected based on literatures and following published databases: hitpick, swiss target prediction, SEA, pubchem, and drugbank. Mining berberine targets onto identified disease targets uncovers that berberine might potentially regulate 21 targets for both COVID‐19 and SARS, 4 targets for SARS specifically, and 19 targets for COVID‐19 specifically. With biological targets of berberine for the prevention and treatment of COVID‐19 and SARS established, GO, KEGG pathway, and PPI analysis were conducted to uncover the mechanistic details of berberine regulation in key pathways. Moreover, hub host proteins are determined for further molecular docking analysis. Combining crucial virus proteins and vital host receptor proteins in virus infection and duplication process, molecular docking was further applied to investigate the possible binding modes of berberine to these targets. Based on the lung target mining and molecular docking results, the inhibition of berberine on ACE2, TMPRSS2, IL1α, IL6, IL8, and CCL2 were further validated

FIGURE 2

Venn diagram showing shared targets between berberine, COVID‐19, and SARS. Among them, 21 shared targets are identified for berberine with both COVID‐19 and SARS, 19 shared targets for berberine and COVID, and 4 shared targets for berberine and SARS

FIGURE 3

Gene ontology (GO) biological process (BP) analyses and pathway analyses of the targets. A, GO BP analyses; B, Pathway analysis; Y‐axis: top 15 biological processes (A) and top 15 pathway (B) relevant to the enriched targets; X‐axis: significance of each term ranked with –log (false discovery rate) (FDR)

FIGURE 4

Compound‐Target‐Pathway‐Disease (C‐T‐P‐D) network of the berberine for COVID‐19 and SARS treatment. Squares, circles, diamonds, and triangles represent berberine, common targets, pathways and diseases, respectively. Node size and node color (ie, from green (lowest) to red (highest) indicate a measure of degree. Black lines represent interaction between nodes

FIGURE 5

Protein‐protein interactions. Circles represent the targets. Black lines represent the interaction between nodes. Node size is proportional to its degree in network

FIGURE 6

Binding explorations of complex MAPK3‐berberine, TNF‐Berberine, BAX‐berberine, BAX‐berberine, NFκB1‐berberine, CHUK‐berberine, ACE2‐berberine, TMPRSS2 ‐berberine, and 3CLpro‐berberine. Predicted lowest‐energy binding mode of berberine with the following proteins: A, MAPK3; B, TNF; C, BAX; D, NFκB1; E, CHUK; F, ACE2; G,TMPRSS2; H, 3CLpro. For berberine, the C, O, and N are highlighted in yellow, red, and blue, respectively. For residues of proteins, the green, red, and blue stand for C, O, and N, respectively. The green, purple, and orange lines stand for hydrogen binding, hydrophobic interaction, and anion‐π interaction between berberine and residues, respectively

FIGURE 7

Effect of BBR (berberine/NIT‐X) on ACE2, TMPRSS2 expression in infected Calu‐3 cells. Calu‐3 cells were seeded in six well plates with 5 × 10⁵ cells per well. After 24 hours, cells were incubated in media containing 20 µg/mL, 40 µg/mL BBR/NIT‐X or DMSO (v/v 1:1000). After 3 days incubation, cells were infected with SARS‐CoV‐2 (MOI = 0.005) or mock (‐) for 1hr and grown in indicated media for 24 hours. One day post infection, total RNA were for cDNA synthesis. Real Time‐PCR was performed with the primer for SARS‐CoV‐2 (A) gRNA of SARS‐CoV2, (B) ACE2, and (C) TMPRSS2. Data were normalized to HPRT and presented as 2‐ΔCT. Data represent two sets of qPCR with six readouts. D, Cytotoxicity was performed using commercial CCK8 toxicity kit, *P < .05 versus infected, but not treated. ^# P < .05 versus uninfected/untreated

FIGURE 8

Effect of BBR (berberine/NIT‐X) cytokine expression in infected Calu‐3 cells. Calu‐3 cells were cultured, treated, infected and qPCR were performed. *P < .05,**P < .01 versus infected, but not treated. Data represent two sets of qPCR with six readouts. ^# P < .05 versus uninfected/untreated