1
Drug repurposing to face Covid-19: Celastrol, a potential leading drug capable of
inhibiting SARS-CoV-2 replication and induced inflammation
Carlos A. Fuzo
1
, Ronaldo B. Martins
2
, Thais F.C. Fraga-Silva
3
,
Martin K. Amstalden
1
, Thais Canassa De Leo
1
,
Juliano P. Souza
2
, Thais M. Lima
2
, Lucia H. Faccioli
1
, Suzelei C. França
4
, Vania L.D. Bonato
3*
, Eurico
Arruda
2*
,
Marcelo Dias-Baruffi
1,
§*
1
Departamento de Análises Clínicas, Toxicológicas e Bromatológicas.
Faculdade de Ciências Farmacêuticas
de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brazil.
2
Departamento de Biologia Celular e Molecular e Bioagentes Patogênicos, Faculdade de Medicina de Ribeirão
Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brazil.
3
Departamento de Bioquímica e Imunologia. Faculdade de Medicina de Ribeirão Preto, Universidade de São
Paulo, Ribeirão Preto, SP, Brazil.
4
Unidade de Biotecnologia, Universidade de Ribeirão Preto, Ribeirão Preto, SP, Brazil.
*These authors contributed equally to this work.
§
Corresponding author: Marcelo Dias-Baruffi (mdbaruff@fcfrp.usp.br)
Abstract
The global emergence of Covid-19 has caused huge human casualties. Clinical manifestations of the disease
vary from asymptomatic to lethal, and the symptomatic form can be associated with cytokine storm and non-
homeostatic inflammatory response. In face of the urgent demand for effective drugs to treat Covid-19, we
have searched for candidate compounds using a drug repurposing approach based on in silico analysis
followed by biological validation. Here we identified celastrol, a pentacyclic triterpene isolated from
Tripterygium wilfordii Hook F – a plant used in traditional Chinese medicine – as one of the best compounds
out of 39 repurposed drug candidates. Celastrol reverted gene expression signature from SARS-CoV-2-
infected cells; bound with high-affinity energy to viral molecular targets such as main protease (M
pro
) and
receptor-biding domain (RBD); inhibited SARS-CoV-2 replication in monkey (Vero and Vero-ACE2) and
human (Caco-2 and Calu-3) cell lines; and decreased interleukin-6 (IL-6) secretion in SARS-CoV-2-infected
human cell lines. Interestingly, celastrol acted in a concentration-dependent manner, with undetectable signs
of cytotoxicity. Therefore, celastrol is a promising lead drug candidate to treat Covid-19 due to its ability to
suppress SARS-CoV-2 replication and IL-6 production in infected cells, two critical events in the
pathophysiology of this disease.
Keywords: Covid-19, SARS-CoV-2, drug repurposing, reverse gene signature, molecular docking, celastrol
(which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
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2
1. Introduction
Covid-19 (Coronavirus Disease 2019), caused by the β-coronavirus SARS-CoV-2 (Severe Acute
Respiratory Syndrome Coronavirus 2), was first reported to the World Health Organization in January 2020
after a local pneumonia outbreak of unknown etiology in Wuhan, China
1,2
. SARS-CoV-2 has been rapidly and
effectively transmitted from human-to-human and became a worldwide pandemic that affected more than 137
million people in April 2021
3,4
.
The devastating effects of Covid-19 on global public health and economy have demanded urgent
efforts to discover potential drug and vaccine candidates to prevent and treat this disease. Many immunization
strategies have been studied since the beginning of the pandemic, demonstrating the fast and extraordinary
achievement of pharmaceutical companies in the development of vaccines for Covid-19. Although there are
289 vaccine candidates under development, from which 20 were under phase 3 clinical trial in February 2021
5–
7
, there are many challenges to achieve an efficient global immunization, such as production limitations,
efficacy levels, restrictions on use, dosing procedures, storage requirements, price, emergence of SARS-CoV-
2 mutants, and promotion of durable immunological memory
7–12
.
Despite the availability of effective vaccines, the quick discovery of drugs to prevent and treat SARS-
CoV-2 infection is a critical demand to face Covid-19
13
. The drug reuse strategy accelerates the discovery of
candidate compounds with known activities associated with reducing the SARS-CoV-2 viral load or
promoting a better clinical evolution of Covid-19
14,15
. One aspect of the immunopathology of this disease that
stands out is non-hemostatic inflammation associated with cytokine storm involving by several mediators,
including interleukin-6 (IL-6), which is a severity biomarker of this illness
16–18
.
In this sense, bioinformatics and computational biology are powerful and multidimensional in silico tools
for drug discovery and repurposing of compounds approved or under clinical trial
19–22
. Some of the currently
employed strategies to find drugs applicable in Covid-19 have focused on (i) host or virus targets, such as the
receptor-binding domain (RBD) present in spike glycoprotein and angiotensin-converting enzyme II (ACE2),
which mediate virus-host cell interaction
23,24
; (ii) proteins/enzymes from virus biosynthesis machinery, such
as main protease (M
pro
) and RNA-dependent RNA polymerase (RdRp)
25–27
; and (iii) reversion of the host gene
expression signature of SARS-CoV-2-infected cells
15,28,29
. This study used in silico predictions to repurpose
drug candidates that could concomitantly reverse the SARS-CoV-2 gene expression induced in host cells,
including IL-6, and target proteins/enzymes essential to the SARS-CoV-2 life cycle, followed by biological
validation of the best candidate drug repurposed.
(which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for this preprintthis version posted April 20, 2021. ; https://doi.org/10.1101/2021.04.20.439992doi: bioRxiv preprint
3
2. Models and Methods
2.1. Identification of signatures from SARS-CoV-2 in vitro infection model and search for drugs with
reversed viral infection signature
The gene expression signature from SARS-CoV-2-infected primary human lung epithelium cell line
(NHBE) was obtained from Blanco-Melo and co-authors
30
, by filtering differentially expressed genes (DEGs)
after differential expression analysis from independent biological triplicates of SARS-CoV-2 (USA-
WA1/2020 strain)-infected and mock-treated cells. The signature was constructed based on DEGs with
absolute value of fold change in log
2
scale greater than 1 (|log
2
(FC)| > 1), and significance accepted at adjusted
p-value (p
adj
) smaller than 0.05 (p
adj
< 0.05), as determined by the Benjamini and Hochberg (BH) method
31
.
The obtained signature containing up- and downregulated genes was used to search for drugs with
reversed gene expression signature in comparison to viral infection. The best-ranked drugs (Q
score
) from the
signatures of small molecule expression profiles in LINCS L1000 dataset
32
from Characteristic Direction
Signatures Search Engine (L1000CDS
2
) were listed
33
(https://amp.pharm.mssm.edu/L1000CDS2/). The
signature was submitted to over-representation analysis using Reactome pathways
34
and clusterProfiler R
package
35
to find biological pathways that were enriched due to viral infection, within BH adjusted p-value <
0.05. The DEGs from enriched pathways were used to construct a biological score (B
score
) for each drug
ranging from 0 to 1, where 0 indicated no reversion and 1 indicated total reversion of the main enriched
pathways. A weighting factor was calculated for each DEG by multiplying their occurrence by |log
2
(FC)|.
B
score
was the sum of DEG weighting factors and it was normalized by the sum of all weighting factors. The
graphical representation of drug signatures data and scores were generated with pheatmap
36
and ggplot2
packages
37
in R software
38
.
2.2. Docking of selected drugs on SARS-CoV-2 protein targets
The compounds capable of reversing SARS-CoV-2 infection signature (selected in Section 2.1) were
submitted to molecular docking on three SARS-CoV-2 protein targets: the catalytic site of M
pro
, the RNA
binding site of RdRp, and the RBD domain of spike glycoprotein, using multiple structural conformations.
Here we used ensemble docking to increase the sampling and avoid unique conformational bias. We have
previously generated the representative structures for RBD (unpublished results) using ten centroid clusters
obtained from a 600 ns trajectory, with the aid of molecular dynamics simulation based on the deposited co-
crystal RDB/ACE2 structure (PDB id 6M0J)
39
. The multiple structures of M
pro
and RdRp were obtained from
Protein Data Bank (PDB)
40
(Table S1). The heteroatoms were removed from M
pro
and RdRp structures, the
resulting structures were repaired, and the energy was minimized with FoldX
41
. AutoDockTools
42
was used to
prepare drug and protein input structures for docking analysis and grid box definitions (Table S1). Docking
analysis was carried out using Autodock Vina
43
with exhaustiveness parameter equal to 20. Graphical
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4
representations of energy results were plotted with ggplot2 R package and molecular model structures were
drawn with Pymol
44
and Discovery Studio Visualizer
®
(version-2020)
45
.
2.3. The rationale for selecting a predictable candidate lead drug for experimental validation
In silico analysis guided the selection of a candidate drug for biological validation, considering the
drug's ability to reverse the genetic signature of SARS-CoV-2 infection and its binding affinities to molecular
viral targets. Briefly, the ten best repurposed drugs were selected based on Q
score
values. A compound with
high predicted median binding affinity energy for RBD, M
Pro
, and RdRp – and thereby with strong potential
to inhibit the functions of these molecular targets – was selected using molecular docking data.
2.4. Preparation of viral stock
To obtain SARS-CoV-2 viral stock, clinical isolates (SARS-CoV-2 Brazil/SPBR-02/2020 strain) from
RT-PCR-confirmed Covid-19 patients were propagated using monkey Vero CCL-81 cells (kidney), under
strict biosafety level 3 (BSL3) conditions. Briefly, for initial viral passages, Vero CCL-81 cells were cultured
in Dulbecco minimal essential medium (DMEM) supplemented with 10% heat-inactivated fetal bovine serum
(FBS) and antibiotic/antimycotic mix (10,000 U/mL penicillin and 10,000 μg/mL streptomycin). Viral
inoculum (1:100 ratio) was added to the cells, and the culture was incubated (48 hours, 37 °C, 5% CO
2
humidified atmosphere) in DMEM without FBS but supplemented with antibiotic/antimycotic mix and
trypsin-protease inhibitor, L-1-tosylamide-2-phenylethylchloromethyl ketone (TPCK) host cell treatment (1
μg/μL) to optimize virus adsorption to the cells
46
. After confirming the cytopathic effects of the viral
preparation using an inverted Olympus ix51 microscope, infected Vero CCL-81 cells were detached by
scraping, harvested, and centrifuged (10000 ×g, 10 minutes, room temperature). The resulting supernatants
were stored at -80 °C until use. Finally, virus titration was performed on Vero CCL81 cells using standard
limiting dilution to determine the 50% tissue culture infectious dose (TCID50) of viral stock
47,48
.
2.5. In vitro SARS-CoV-2 infection
SARS-CoV-2 infection was assessed in vitro in four cell lines: Vero CCL-81, human ACE2-
transfected Vero CCL-81 (Vero CCL-81-ACE2), human Calu-3 (lung), and human Caco-2 (colon). Cells were
seeded into 24-well plates (80,000 cells/well) to ensure 90% of confluence on the day of inoculation/infection.
The four cell lines were infected with SARS-CoV-2 and treated with celastrol. Cells were infected with SARS-
CoV-2 at multiplicity of infection (MOI) 1.0 in 500 µL of infection media composed of DMEM without FBS,
1% antibiotic/antimycotic mix, and 1 μg/μL trypsin-TPCK. After 2 hours of incubation, supernatant
containing SARS-CoV-2 was removed and replaced by celastrol (125, 250, 500, and 1,000 nM) or vehicle
(0.05% DMSO) diluted in fresh medium, followed by 48 hours of incubation at 37 °C and under 5% CO
2
.
Photomicrographs were taken using the Olympus ix51 inverted microscope and analyzed using the QCapture
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5
Pro 6.0 software under 200× magnification (QImaging)
49
, in order to examine whether celastrol interfered
with SARS-CoV-2 cytopathic effects in Vero CCL-81 cells. The supernatants were collected for RNA
extraction and viral load was quantified using a standard curve. All the infections were conducted in technical
triplicate.
2.6. Cell viability
Cytotoxicity of celastrol (Sigma-Aldrich) to Vero CCL-81, Vero CCL-81-ACE2, Calu-3, and Caco-2
was determined using the Alamar Blue Cell Viability protocol (Thermo Scientific, Waltham, USA), according
to the manufacturer's instructions. Briefly, the cells were seeded into a 96-well plate to grow as monolayers
and treated with celastrol (250 or 1000 nM) in DMSO (0.05%) or DMSO (5%, v/v; cell death reference) for
24 hours. Alamar Blue reagent (10% v/v) was added to the cells, and the plate was incubated at 37 °C, for 4
hours. Median fluorescence intensity was measured using the SpectraMax i-3 (Molecular Devices) microplate
reader, with excitation and emission wavelengths set at 530 and 590 nm, respectively. The mean value from
the control (untreated cells) was set as 100%, and the viability of cells from each treatment condition was
calculated relative to this value, in triplicate.
2.7. RT-PCR for SARS-CoV-2
The SARS-CoV-2 genome was quantified using primer-probe sets for N2 and RNAse-P housekeeping
gene, following USA-CDC protocols (Table 1)
50
. To determine the genome viral load from in vitro infection
assays, N2 and RNAse-P gene were tested by one-step real-time RT-PCR using total nucleic acids extracted
with Trizol
®
(Invitrogen, CA, EUA) from 250 µL of culture supernatants. All RT-PCR tests were carried out
using the Step-One Plus real-time PCR thermocycler (Applied Biosystems, Foster City, CA, USA). Briefly,
100 ng of RNA were used for genome amplification, mixed with specific primers (20 µM), probe (5 µM), and
TaqPath 1-Step qRT-PCR Master Mix (Applied Biosystems, Foster City, CA, USA). The following reaction
parameters were used: 25 °C for 2 minutes, 50 °C for 15 minutes, 95 °C for 2 minutes, followed by 45 cycles
of 95 °C for 3 seconds and 55 °C for 30 seconds.
A plasmid standard curve was plotted to determine SARS-CoV-2 viral load. A 944 bp amplicon was
inserted into a TA cloning vector (PTZ57R/T CloneJetTM Cloning Kit Thermo Fisher
®
), starting from residue
14 of N gene, which includes all three sets of primers/probe designed by the CDC protocol (N1, N2, and N3).
To quantify the amount of virus produced, a tenfold serial dilution of the plasmid was prepared in the range
from 10
6
to 1 plasmid copy. The coefficient of determination (R
2
) for the plasmid standard curve was 0.999,
with efficiency above 91% reached using any set of primers/probe
51
.
2.8. Interleukin 6 quantification
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