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Metadichol®, a Novel Nano Lipid Formulation that Inhibits SARS-COV-2 and a Multitude of Pathological Viruses in vitro

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New pathogenic virus outbreaks, occurring with increasing regularity, are leading us to explore novel approaches, which will reduce the reliance on time-consuming vaccine modes to halt the outbreaks. The requirement is to find a universal approach to disarm any new and as yet unknown viruses as they appear. A promising approach could be targeting lipid membranes, which are common to all viruses and bacteria. The ongoing pandemic of severe acute respiratory syndrome-coronavirus 2 (SARS-COV-2) has reaffirmed the importance of interactions between components of the host cell plasma membrane and the virus envelope as a critical mechanism of infection. Metadichol®, a nano lipid emulsion, has been examined and shown to be a strong candidate to help stop the proliferation of SARS-COV-2. Naturally derived substances, such as long-chain saturated lipid alcohols, reduce the infectivity of various types of viruses, including coronaviruses such as SARS-COV-2, by modifying lipid-dependent attachment to human host cells. SARS-COV-2 uses the receptor ACE2 for entry and the serine protease TMPRSS2 for S protein priming. Metadichol®, a nano lipid formulation of long-chain alcohols, has been shown to inhibit TMPRSS2 (EC50 96 ng/ml). Compared to the inhibitor camostat mesylate (EC50 26000 ng/ml), it is 270 times more potent. Additionally, Metadichol® is also a extremely weak inhibitor of ACE2 at 31 µg/ml. Further a live virus assay in Caco2 cells, Metadichol® inhibited SARS-CoV-2 replication with an EC90 of 0.16 µg/ml.
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Metadichol®, a Novel Nano Lipid Formulation that
Inhibits SARS-COV-2 and a Multitude of Pathological
Viruses in vitro
Palayakotai Raghavan ( raghavan@nanorxinc.com )
NANORX Inc.
Research
Keywords: Coronavirus, SARS-COV-2, COVID-19, ACE2, TMPRSS2, VDR, Metadichol
DOI: https://doi.org/10.21203/rs.3.rs-34021/v6
License: This work is licensed under a Creative Commons Attribution 4.0 International License. 
Read Full License
Page 2/22
Abstract
New pathogenic virus outbreaks, occurring with increasing regularity, are leading us to explore novel
approaches, which will reduce the reliance on time-consuming vaccine modes to halt the outbreaks. The
requirement is to nd a universal approach to disarm any new and as yet unknown viruses as they
appear. A promising approach could be targeting lipid membranes, which are common to all viruses and
bacteria.
The ongoing pandemic of severe acute respiratory syndrome-coronavirus 2 (SARS-COV-2) has rearmed
the importance of interactions between components of the host cell plasma membrane and the virus
envelope as a critical mechanism of infection. Metadichol®, a nano lipid emulsion, has been examined
and shown to be a strong candidate to help stop the proliferation of SARS-COV-2.
Naturally derived substances, such as long-chain saturated lipid alcohols, reduce the infectivity of various
types of viruses, including coronaviruses such as SARS-COV-2, by modifying lipid-dependent attachment
to human host cells. SARS-COV-2 uses the receptor ACE2 for entry and the serine protease TMPRSS2 for
S protein priming.
Metadichol®, a nano lipid formulation of long-chain alcohols, has been shown to inhibit TMPRSS2 (EC50
96 ng/ml). Compared to the inhibitor camostat mesylate (EC50 26000 ng/ml), it is 270 times more
potent. Additionally, Metadichol® is also a extremely weak inhibitor of ACE2 at 31 µg/ml. Further a live
virus assay in Caco2 cells, Metadichol® inhibitedSARS-CoV-2 replication with an EC90 of 0.16 µg/ml.
Introduction
There is currently an increasing need for a broad-spectrum antimicrobial agent that could inactivate
human pathogens, such as bacteria and viruses. Rapid resistance by microorganisms has propelled this
approach to the development of focused drugs. The most recent trigger is the fear of a future pandemic
caused by new, poorly studied virulent strains, such as the present SARS-COV-2.
Background information on SARS-COV-2
Severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) (causative agent of COVID-19) is causing
a pandemic1 that has produced global havoc within a few months. Medically controlling a rapidly
spreading viral pandemic utilizing specic antivirals and vaccines will prove expensive and time
consuming and is accompanied by compromises on safety and ecacy. An alternative approach is to
test molecules that are already proven safe for effectiveness against SARS-COV-2. Among the candidates
being tested are camostat mesylate (a 35-year-old Japanese drug), Avigan (another Japanese drug) and
Gilead Science Inc.'s remdesivir2.
To enter a host cell, SARS-COV-2 requires transmembrane protease serine 2 (TMPRSS2)3, a serine
protease, and angiotensin-converting enzyme 2 (ACE2)4 to bind and thus facilitate its entry. Blocking both
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receptors can effectively stop the cell entry mechanism used by the virus.
TMPRSS2 is a protease that primes the spike protein of SARS-COV and the Middle East respiratory
syndrome-related coronavirus (MERS-COV). Camostat mesylate (CM), an inhibitor of TMPRSS2, inhibited
SARS-COV in a mouse model5,6. Hoffmann et al.7 determined that SARS-COV-2 requires TMPRSS2. They
showed that CM blocks virus entry into the lungs. To date, there are no clinical data on the use of CM in
patients.
The other receptor used by viruses to enter the host cell is ACE2. SARS-COV-2 has a spike (S) protein on
its viral envelope (exterior) that binds to the transmembrane protein ACE2, which is present on human
cells. ACE2 is essential for viral entry. However, ACE2 also regulates blood pressure and blood volume;
blocking ACE2 would be detrimental to health. An approach that partially regulates ACE2 in concert with
inhibition of TMPRSS2 would thus be an ideal solution.
Lipids and viruses
Viral envelope lipids play a role in both viral stability and infective capabilities. For example, substances
that affect the lipid envelope, such as phospholipases, organic solvents, and surfactants, such as soaps,
have been shown to affect viral infectivity. Causing envelope disintegration, they stop virus transmission
to a new host. Active ingredients8 in a number of cleaning agents, wipes, and tissues target the viral lipid
envelope to render the virions nonviable. Snipes and coworkers9 showed that saturated alcohols could
inactivate viruses with chain lengths from 10 to 14 carbons. Their studies established that inactivation of
enveloped viruses by lipids varies greatly, depending on both the nature of the lipid and the type of virus.
Hilmarsson et al.10-12 studied the virucidal effects of medium- and long-chain (8 to 18 carbon) fatty
alcohols and corresponding lipids against herpes simplex viruses (HSV-1 and HSV-2), respiratory
syncytial virus (RSV), human parainuenza virus type 2 (HPIV2) and enveloped viruses at various
concentrations, times and pH levels. After a 10-minute incubation at 37 °C with a 10 mM concentration,
14 of the lipids tested caused a 100000-fold or more signicant reduction in HSV titre. Testing between
pH 7 and 4.2 showed that a pH of 4.2 caused a more rapid inactivation of HSV-1 virus titre in one minute
than higher pH values. These long-chain alcohols may act by penetrating the envelope of the virus by
hydrophobic effects, making it permeable to small molecules and thus inactivating the virus; the degree
of penetration into lipid membranes is based on the chain length of a lipid compared with the thickness
of the membrane13.
Metadichol ® is a nano lipid formulation of long-chain alcohols14. Metadichol has been shown to inhibit
viruses in vitro and in vivo15-17. Metadichol was tested for its inhibitory actions against ACE2 and
TMPRSS2 and in an antiviral assay with SARS-COV-2.
Discussion
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The results in Table 1 and 2 demonstrate Metadichol's direct antiviral effect against the SARS-COV-2
virus in Caco-2 cells, with an EC90 of 0.15 µg/ml. Comparatively, this result indicates that Metadichol has
a 2000-fold higher effectiveness than Remdesivir and 4000-fold potency over hydroxychloroquine
phosphate18..
A previously published work15 of antiviral data against other viruses is shown in Tables 3 and 4. Raw
data show the cytotoxicity of Metadichol without a virus present in Vero cells was measured by neutral
red assay. When >75% "toxicity" occurred in the absence of virus, no viral CPE value was reported.
These results suggest that it is toxic to cells at concentrations above 5 ug/ml in most cases. However,
Metadichol is not toxic, as the LD50 is 5000 mg/kg19-21. It is likely that Metadichol at higher
concentrations behaves in a soap-mimicking manner by disrupting the lipid membrane, and at lower
concentrations, it neutralizes the virus by a different mechanism. Metadichol is not toxic to cell lines, but
rather, it behaves as a "detergent" in neutralizing SARS-COV-2 and other pathogenic viruses shown in
Table 5. Additionally, Metadichol® targets selectively cancer cells in this case Caco-2 cells. In a previous
study22of Klotho gene expression in the cancer cell lines Mia-Paca, Colo 205, and Panc1, Metadichol was
seen to be toxic to cell lines above 1 µg/ml. It is also toxic at 10 µg/ml in leukaemia cancer cells243
Metadichol also inhibits TMPRSS2 ( Table 6 gure 1,2) and is 270-fold more potent than CM24
Metadichol moderately inhibits ACE2 ( Table 7, gures 3 and 4 ) and, in combination with TMPRSS2
inhibition, likely leads to a pronounced synergistic effect in overcoming viral entry. The reported results
open the gateway to effective and safe therapies for COVID-19. Metadichol is a mild inhibitor of ACE2 (
table 7 and gures 4 and 6 ) but at the same time, not signicant to affect the physiological functions of
the host.
Vitamin D and SARS-COV-2 infection
An uncontrolled inammatory response to SARS-COV-2 is the major cause of disease severity and death
in patients with COVID-1925 and is associated with high levels of circulating cytokines, tumor necrosis
factor (TNF), CCl2, C-reactive protein (CRP), and Ferritin. Metadichol14 is an inhibitor of CCl2 (also known
as MCP-1), TNF, NF-kB, and CRP, which is a surrogate marker for cytokine storms26 and is associated with
vitamin D deciency.
Vitamin D3 is generated in the skin through the action of UVB radiation, with 7-dehydrocholesterol
generated in the skin, followed by a thermal reaction. Vitamin D3 is converted to 25(OH)D in the liver and
then to 1,25(OH)2D (calcitriol) in the kidneys. Calcitriol binds to the nuclear vitamin D receptor (VDR); a
DNA-binding protein interacts with regulatory sequences near target genes that participate genetically
and epigenetically in the transcriptional output of genes needed for function27. Vitamin D reduces the risk
of infections by mechanisms that include inducing cathelicidins and defensins28, resulting in lowered
viral replication rates and reducing concentrations of pro-inammatory cytokines29. Supplementation
with 4000 IU/d vitamin D decreased dengue virus infection30. Inammatory cytokine levels increase in
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viral and bacterial infections, as seen in COVID-19 patients. Vitamin D can reduce the production of pro-
inammatory Th1 cytokines, such as TNF and interferon (IFN)31.
Vitamin D is a modulator of adaptive immunity32 and suppresses responses mediated by T helper type 1
(Th1) cells primarily by repressing the production of the inammatory cytokines interleukin (IL)-2 and IFN-
gamma33. Additionally, 1,25(OH)2D3 promotes cytokine production by T helper type 2 (Th2) cells, which
helps enhance the indirect suppression of Th1 cells by complementing this suppression with actions
mediated by a multitude of cell types34.
1,25(OH)2D3 promotes T regulatory cell induction, thereby inhibiting inammatory processes35. It is
known that COVID-19 is associated with the increased production of pro-inammatory cytokines, elevated
CRP levels, increased risk of pneumonia, sepsis, acute respiratory distress syndrome (ARDS), and heart
failure36. Case fatality rates (CFRs) in China were 6%-10% for those with cardiovascular disease, chronic
respiratory tract disease, diabetes, and hypertension37. Metadichol is a inverse agonist/protean agonist 14
of VDR ie it binds at the same site as calcitriol but has different properties. It is the only known inverse
agonist to VDR known in medical literature.
Telomerase and viral infections
Metadichol at one picogram increases h-TERT (telomerase) expression by 16-fold38. Viral infection places
a signicant strain on the body. CD8 T cells that mediate adaptive immunity39 to protect the body from
microbial invaders can easily reach their Hayick limit by depleting their telomeres40. This possibility is
more likely if telomeres are already short. Infections put enormous strain on immune cells to replicate.
Naive T and B cells are particularly important when our bodies encounter new pathogens, such as SARS-
COV-2. The quantity of these cells is crucial for useful immune function.
AHR and viral infections
One of the major issues with infected COVID-19 patients has been respiratory failure. It has been
suggested that the aryl hydrocarbon receptor (AHR) is activated during coronavirus infections, impacting
antiviral immunity and lung cells associated with repair41. Signalling via AHR may dampen the immune
response against coronavirus42. It has been reported that although some signalling is needed for
coronavirus replication, excessive activation of this pathway may be deleterious for the virus. AHR limits
activation and interferes with multiple antiviral immune mechanisms, including IFN-I production and
intrinsic immunity. Yamada et al.43 suggested that AHR (the constitutive aryl hydrocarbon receptor)
signalling constrains type I IFN-mediated antiviral innate defence and suggested a need to block
constitutive AHR activity; only an inverse agonist can dampen this activity. We have shown that
Metadichol® binds to AHR as an inverse/protean agonist44 and thus can reduce complications attributed
to uncontrolled inammation and cytokine storms.
Vitamin C and viral infections
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In infectious diseases, there is also a need to boost innate and adaptive immunity. The micronutrients
with the most robust evidence for immune support are vitamins C and D. Vitamin C is essential for a
healthy and functional host defence. The pharmacological application of vitamin C enhances immune
function45. Vitamin C has antiviral properties leading to inhibition of the replication of HSV-1, poliovirus
type 1, inuenza virus type46, and rabies virus in vitro47.
Vitamin C deciency reduces cellular48-52and humoral immune responses, and treatment of healthy
subjects promoted and enhanced natural killer (NK) cell activities53, underlining the immunological
importance of vitamin C54,55 and supporting its role as a crucial player in various aspects of immune cell
functions, such as immune cell proliferation and differentiation, in addition to its anti-inammatory
properties. Moreover, the newly characterized hydroxylase enzymes, which regulate the activity of
hypoxia-inducible factor gene transcription and cell signalling of immune cells, need vitamin C as a
cofactor for optimal activity56-58. Metadichol administration increases vitamin C levels endogenously by
recycling vitamin C and produces levels not reached by oral intake, and those reached bring about
changes in improving diverse biomarkers59-61.
Gene cluster network analysis
The present drug discovery paradigm is based on the idea of one gene-one target, one disease. It has
become clear that it is dicult to achieve single target specicity. Thus, the need to transition from
targeting a single gene to targeting multiple genes is likely to become more attractive, leading to blocking
multiple paths of disease progression62,63. Gene network analysis can provide a minimum set of genes
that can form the basis for targeting diseases. This clustering network of genes can modulate gene
pathways and biological networks. We used www.ctdbase.org64, which has curated genes show in Table
8 relevant to COVID-19. Table 9 lists genes and diseases states that they are involved in.
We can lter the 13 genes to a set of 5 genes: TNF, CCL2, ACE2, TMPRSS2 are modulated by Metadichol
and AGT, which is part of the renin-angiotensin system (RAS) network that ACE2 is a part of (Figure 5). A
similar analysis of these network genes shows that they are closely networked in diseases, with a highly
signicant p-value. These ve genes are closely related, and the network generated, is shown in Figure 6,
using www.innatedb.org65. This analysis integrates known interactions and pathways from major public
databases.
The highlighted ones are SIRT1, AR (androgen receptor) , and FOS. Glinsky66 suggested vitamin D as a
potential mitigation agent in preventing SARS-COV-2 entry. Metadichol binds to VDR, which controls the
expression of FOS67. AR also controls the expression of FOS, as well as that of TMPRSS2. Figure 7,
generated below using PACO68, shows the gene network and regulation relationships. VDR controls FOS
expression, FOS controls AGT, AGT controls the expression of AGTR1 and ACE, and AR controls the
expression of TMPRSS2.
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Wambier and Goren69 suggested that SARS-COV-2 infection is likely to be androgen mediated. The rst
step to infection is the priming of the SARS-COV-2 spike proteins by TMPRSS2, which also cleaves ACE2
for augmented viral entry. This pathway is seen in the network (Figure 8). SIRT1 plays an active role in
enhancing immunity in viral infections70
Proteases such as Furin71 and Adam-17 have been described to activate the spike protein in vitro for viral
spread and pathogenesis in infected hosts. VDR controls Furin expression, mediated through its
interaction with SRC72. Adam-17 is regulated via CEPBP73,74, which is involved in the regulation of genes
involved in immune and inammatory responses. Recently, Ulrich and Pillat75 proposed that CD147,
similar to ACE2, is another receptor used for viral entry. CD147 is a known receptor76 for the parasite that
causes malaria in humans,
Plasmodium falciparum
. Metadichol (see Ref6, US patent 9,006,292) inhibits
the malarial parasite.
The key to entry into cells by SARS-COV-2 is ACE2, which, when endocytosed with SARS-COV-2, results in
a reduction in ACE2 on cells and an increase in serum Angiostensin II77. Angiostensin II acts as a
vasoconstrictor and a pro-inammatory cytokine (Figure 9) via AT1R78. The Angiostensin II-AT1R axis
leads to a pro-inammatory state79, leading to infections through activation of NF-KB and to increased IL-
6 levels in multiple inammatory and autoimmune diseases80.
The dysregulation of angiotensin 2 downstream of ACE2 leads to the cytokine release that is seen in
COVID-19 patients, resulting in increased TNF levels that lead to elevated IL-6, CCl2, and CRP levels.
Cytokine storms81 result in ARDS.
Controlling cytokine storms
A cytokine storm develops after an initial immune response by the induction of cytokines. The response
to SARS-COV-2 leads to inammation. There are increased levels of the pro-inammatory cytokines IL-6,
IL-18, TNF, and IL-1-beta by macrophages and of IFN-gamma by NK cells.
Figure 9 was generated, using of PACO (www.pathwcommons.org), shows the cytokine relationship
network. The cytokines can activate T cells, which lead to tissue damage and infection in the lungs.
Inltration of T cells can also result from the upregulation of adhesion molecules, such as ICAM1, by lung
endothelial cells. Metadichol is an inhibitor (see Ref14, US patent 8,722,093) of TNF alpha in vivo, and
ICAM1 and CCl2 depress the hyper inammatory cytokine response caused by SARS-COV-2 and, at the
same time, enhance innate and adaptive immunity through the VDR pathways and increased vitamin C
levels. Metadichol, by its binding to VDR, leads to a network of gene control of the cytokine storms
illustrated in Figure 6, bringing about homeostasis.
Clinical
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A pilot study done by a third party Kasturaba Hospital in Mumbai India, on thirty COVID-19 patients with
minor symptoms showed the absence of a virus in 75% of patients after 4 days of Metadichol treatment
@ 20 mg per day. To validate this further, we have been initiated a larger study in collaboration with
government agencies where we will have Metadichol treatment group and control groups, with only
Standard Care. We hope to communicate these results in the near future.
Summary And Conclusions
Metadichol inhibits SARS-COV-2 entry into host cells by inhibiting TMPRSS2 and partial inhibition of
ACE2 and boosts the antiviral response by enhancing innate and adaptive immunity through the vitamin
D pathway and antiviral activity by endogenously increasing vitamin C levels. In addition, telomerase
activity can also play a key role in maintaining the levels of naive T and B cells needed to ght infections.
Metadichol modulates cytokine storms, as it is an inhibitor of TNF, ICAM1 and CCL2, which, as shown,
play a key role with other cytokines. Co morbidities associated82,83 with COVID-19, such as hypertension
and diabetes84,85, are also controlled by Metadichol, which could certainly improve the long-term
prognosis for the affected patient population. These actions on multiple genes and via multiple pathways
bring about homeostasis and prevent SARS-COV-2 infections. Metadichol's86 actions on multiple genes
and proteins lead to over 2000 unique interactions with other genes and result in a network that helps
bring about homeostasis.
Metadichol is a safe, nontoxic product made from renewable sources and have been commercially
available for the last six years, with no reported side effects. This unique property allows for the use of
Metadichol as an immune modulator to prevent future occurrence of SARS-COV-2 and possibly other
infections being predicted, facilitating a rapid return to normal human social and economic activity
worldwide.
Abbreviations
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Gene Description
VDR vitamin D receptor
AHR aryl hydrocarbon receptor
TERT telomerase reverse transcriptase
KL klotho
PAI1 (SERPINE1) serpin family E member 1
HIF 1 alpha hypoxia-inducible factor 1-alpha
CCL2 C-C motif chemokine ligand 2
ICAM1 intercellular adhesion molecule 1
TNF tumour necrosis factor
ACE angiotensin I-converting enzyme
ACE2 angiotensin I-converting enzyme 2
AGTR1 (ANG1) angiotensin II receptor type 1
AGTR2 (ANG2) angiotensin II receptor type 2
TMPRSS2 transmembrane serine protease 2
SIRT1 sirtuin 1
TNF tumour necrosis factor
FURIN furin, paired basic amino acid cleaving enzyme
CD 147 (BSG) Basigin (BSG), also known as extracellular matrix metalloproteinase inducer
IL6 interleukin 6
IL10 interleukin 10
CCL3 C-C motif chemokine ligand 3
IL2 interleukin 2
IL7 interleukin 7
CSF3 Colony-stimulating factor 3
IL2RA interleukin 2 receptor subunit alpha
CXCL8 C-X-C motif chemokine ligand 8
Declarations
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Competing interest: Author has no competing interests
Correspondence and requests for materials should be addressed to raghavan@nanorxinc.com
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Page 15/22
Methods
All assays were on a fee-for-service contract basis and outsourced to bioanalytical testing companies
worldwide. SARS-COV-2 antiviral assays were performed by a bio-safety level 3 (BSL3) facility at the Anti-
viral research Institute at Utah State University in the USA. The other assays were performed at Southern
Research Infectious Disease Research Facility in Frederick, Maryland, USA and IBT Bio services in
Rockville, Maryland, USA. ACE2 and TMPRSS2 Assays were carried out by Skanda Life Sciences Pvt Ltd
Bangalore , India.
Antiviral assay
Metadichol was serially diluted using eight half-log dilutions in test medium (MEM supplemented with 2%
FBS and 50 µg/mL gentamicin) so that the starting (high) test concentration was 100 µg/ml. Each
dilution was added to 5 wells of a 96-well plate with 80-100% conuent Caco-2 cells.
Three wells of each dilution were inoculated with virus, with two wells uninoculated (as toxicity controls);
six wells were inoculated and untreated (as virus controls); and six wells were uninoculated and untreated
(as cell controls). SARS-COV-2 was prepared to achieve the lowest possible multiplicity of infection (MOI)
that would yield >80% cytopathic effect (CPE) within ve days. M128533 (protease specic for SARS-
COV) was tested in parallel as a positive control. The plates were incubated at 37±2°C and 5% CO2. On
day three post-infection, once untreated virus control wells reached maximum CPE, plates were stained
with neutral red dye for approximately 2 hours (±15 minutes). The supernatant dye was removed, and the
wells were rinsed with PBS. The incorporated dye was extracted in 50:50 Sorensen citrate buffer/ethanol
for >30 minutes, and the optical density was read on a spectrophotometer at 540 nm.
Optical densities were converted to percent of that of cell controls, and the concentration of compound
that would cause 50% cell death (CC50) in the absence of virus was calculated by regression analysis.
The selective index (SI) is the CC50 divided by the EC90. The results are shown in Table 7.
For a virus yield reduction (VYR) assay, the supernatant uid from each compound concentration was
collected on day three post-infection before neutral red staining (3 wells pooled) and tested for virus titre
using a standard endpoint dilution CCID50 assay in Vero 76 cells and titre calculations via the Reed-
Muench (1948) equation. The concentration of compound required to reduce virus yield by one log10 was
calculated by regression analysis (EC90).
As shown in Table 2 the virus reduction assay did not follow a typical dose-response relationship, with
virus reduction seen at concentrations of 0.3 µg/ml and 3.2 µg/ml but no reduction seen at a
concentration of 1 µg/ml. It was assumed that breakthrough of the virus at 1 µg/ml was an outlier. The
calculated SI was 20 (Table 1), indicating an EC90 of 0.15 µg/ml.
The results for other viruses shown in Table 3 and 4 and 5 were carried out in a similar procedure by
various labs using Vero cells.
Page 16/22
TMPRSS2 inhibition assay
Procedure
TMPRSS puried from LNCaP cells (ATCC) was used as an enzyme source. The reaction mixture
contained puried TMPRSS2 protease in TBS with or without a range of various concentrations from
1.56 to 100 ng/ml of test sample or inhibitor. The reaction mixture was incubated for 10 minutes at 37°C.
To the reaction mixture, 1 µl of 10 mM the uorogenic trypsin substrate Cbz-Gly-Gly-Arg-AMC was added,
and kinetic uorescence readings were recorded after 2 minutes of incubation at 37°C at Ex383 nm and
Em455 nm at 5-10 minutes using a SpectraMax i3X (Molecular Devices). The change in uorescence
(delta RFU) was calculated to determine the inhibitory effects of the test sample. CM ( Cayman
Chemicals) at a two-fold range of concentrations from 1.56 to 100 nM was used as a positive control for
TMPRSS2 protease inhibition.
ACE2 Inhibition assay
An ACE2 Inhibitor Screening Assay Kit, catalogue no. 79923 (BPS Biosciences, San Diego, USA), was
used to measure the exopeptidase activity of ACE2 and inhibition by Metadichol and the control inhibitor
DX600. The inhibitory activity was measured based on the uorescence emitted by the cleavage of a
chromogenic substrate.
Procedure
Enzyme (ACE2) stocks were prepared from the supplied kit. Twenty micro litres of enzyme solution (0.5
ng/µl) was added to all the wells designated for the assay. DX600, a potent ACE2 inhibitor, was used as a
positive control for ACE2 inhibition at various concentrations ranging from 0.0156 µg/ml to 1 µg/ml. The
test sample at concentrations ranging from 0.125 µg/ml to 40 µg/ml was used. To each well containing
the enzyme solution, 5 µl of inhibitor solution was added to the respective designated wells. The reaction
mixture was incubated at room temperature for 5 minutes. After incubation, 25 µl of ACE2 substrate was
added to the mixture and incubated for 1 hour at room temperature. The RFU due to cleavage of the
substrate were read at Ex555 nm and Em585 nm using a SpectraMax i3x (Molecular Devices). The IC50
values were calculated based on the readings obtained.
Tables
Table 1.In vitro antiviral assay results
CC50 EC90 S I90
Metadichol (µg/ml) 4 0.15 20
M128533 (µg/ml) >10 0.2 >33
CC50: 50% cytotoxic concentration of compound without virus added;
Page 17/22
EC50: 50% effective antiviral concentration;
EC90: calculated concentration to reduce virus yield by 1 log (90%);
SI: CC50/EC50.
Table 2.Cytotoxicity and virus yield data for each concentration of Metadichol tested
Metadichol Concentration (µg/ml)  Cytotoxicity (%) Virus Titre (CCID50 per 0.1 ml)
100 100% <0.7
32 100% <0.7
10 83% <0.7
3.2 54% 0.7
1 17% 4.3
0.3 26% 1.5
0.1 26% 5.7
0.03 26% 5.3
Table 3.Raw data for cytotoxicity of Metadichol without virus present, as measured by neutral red assay
Units are µg/ml unless
noted
 
Metadichol (µg/ml) Adenovirus Tacaribe Rift
valley
SARS Japanese
encephalitis
West Nile
virus
Yellow fever 
Powassan virus
500 95% 98% 96% 96% 100% 100% 100% 100%
160 92% 98% 96% 95% 100% 100% 100% 100%
50 90% 97% 97% 95% 100% 100% 100% 100%
16 85% 95% 81% 92% 88% 77% 98% 100%
5 0% 23% 26% 35% 33% 28% 35% 44%
1.6 0% 2% 10% 15% 12% 14% 19% 6%
0.5 0% 3% 9% 0% 2% 3% 2% 0%
0.16 0% 17% 3% 0% 0% 0% 4% 0%
CC50 9.90 7.30 8.40 6.70 7.20 8.50 5.00 5.1
Page 18/22
Table 4 Anti viral assa y of Metadichol against various viruses, as measured by neutral red assa y
Metadichol
(µg/ml)
Adenovirus Tacaribe Rift valley
fever
SARS Japanese
encephalitis
West
Nil e
Yellow fever
 
Powassan
5 100% 31% 100% 0% 56% 84% 70% 53%
1.6 100% 69% 100% 52% 87% 100% 73% 100%
0.5 100% 97% 100% 100% 100% 100% 95% 100%
0.16 100% 100% 100% 100% 100% 100% 96% 100%
EC50 >9.9 2.8 >8.4 1.7 >7.2 >8.5 >5 >5.1
Table 5. List of viruses inhibited by Metadichol in vitro
Adenovirus Rift valley
Japanese encephalitis Marburg
Tacaribe SARS
Powassan Respiratory syncytial virus
Zika Chikungunya
Ebola Influenza A (H1N1)
Yellow fever Dengue
West Nile virus HIV
Table 6. TMPRSS2 assay data
Page 19/22
Sample Concentration RFU % Inhibition IC50
Control
0 43233358 0.00
Metadichol (ng/ml)
1.56 41305150 4.46 96.65 ng/ml
3.12 39329385 9.03
6.25 36713767 15.08
12.5 33778222 21.87
25 30695684 29.00
50 26087008 39.66
100 16009312 62.97
 
Camostat mesylate (µg/ml)
0.78 37984828 12.14 26.46 ug/ml
1.56 35235186 18.50
3.125 31685728 26.71
6.25 29234396 32.38
12.5 23276839 46.16
25 18931887 56.21
50 8797988 79.65

Table 7ACE2 assay data
Page 20/22
Sample Concentration (µg/ml) RFU % Inhibition IC50 (µg/ml)
Control 0 308315546 0.00
Metadichol 0.125 290309918 5.84 30.15
0.25 260064163 15.65
0.5 249149792 19.19
1 240301136 22.06
10 212275253 31.15
20 187702504 39.12
40 139821100 54.65
 
DX600 0.0156 252855648 17.99 0.1027
0.031 231028864 25.07
0.0625 193810784 37.14
0.125 145881248 52.68
0.25 127485752 58.65
0.5 111498760 63.84
Table 8. COVID-19 and 13 curated genes
CCL2 IL6 IL7
TNF TMPRSS2 ACE2
IL10 CCL3 AGT
IL2 IL8 IL2RA
CSF3  
Table9. Dise ase network of the 13 curated genes
Page 21/22
Disease name Disease categories Corrected
P-value
Annotated
gene
quantity
Annotated genes
COVID-19 Respiratory tract disease, viral
disease
3.10E-47 13 ACE2, AGT, CCL2, CCL3, CSF3, CXCL10,
IL10, IL2, IL2RA, IL6, IL7, TMPRSS2,
TNF
Pneumonia, viral Respiratory tract disease, viral
disease
4.34E-46 13 ACE2, AGT, CCL2, CCL3, CSF3, CXCL10,
IL10, IL2, IL2RA, IL6, IL7, TMPRSS2,
TNF
Coronavirida e
infections
Viral disease 1.74E-44 13 ACE2, AGT, CCL2, CCL3, CSF3, CXCL10,
IL10, IL2, IL2RA, IL6, IL7, TMPRSS2,
TNF
Coronavirus
infections
Viral disease 1.74E-44 13 ACE2, AGT, CCL2, CCL3, CSF3, CXCL10,
IL10, IL2, IL2RA, IL6, IL7, TMPRSS2,
TNF
Nidovirales
infections
Viral disease 1.74E-44 13 ACE2, AGT, CCL2, CCL3, CSF3, CXCL10,
IL10, IL2, IL2RA, IL6, IL7, TMPRSS2,
TNF
RNA virus
infections
Viral disease 4.92E-27 13 ACE2, AGT, CCL2, CCL3, CSF3, CXCL10,
IL10, IL2, IL2RA, IL6, IL7, TMPRSS2,
TNF
Virus dise ases Viral dise ase 1.73E-25 13 ACE2, AGT, CCL2, CCL3, CSF3, CXCL10,
IL10, IL2, IL2RA, IL6, IL7, TMPRSS2,
TNF
Sexually
transmitted
diseases, viral
Viral disease 1.38E-12 7 CCL2, CCL3, IL10, IL2, IL2RA, IL6, TNF
HIV infections Immune system disease , viral disease 1.56E-12 7 CCL2, CCL3, IL10, IL2, IL2RA, IL6, TNF
Lentivirus
infections
Viral disease 1.56E-12 7 CCL2, CCL3, IL10, IL2, IL2RA, IL6, TNF
Retroviridae
infections
Viral disease 1.56E-12 7 CCL2, CCL3, IL10, IL2, IL2RA, IL6, TNF
HIV wasting
syndrome
Immune system disease, metaboli c
disease, nutrition disorder, viral
disease
4.00E-04 2 IL6, TNF
Coxsackievirus
infections
Viral disease 0.001 2 IL6, TNF
Enterovirus
infections
Viral disease 0.0044 2 IL6, TNF
Picornaviridae
infections
Viral disease 0.00519 2 IL6, TNF
Page 22/22
Table 10. Dise ase network of genes implicated in SARS-COV-2 infection
Disease name P-value Corrected P-value Ge nes Annotated genes
COVID-19 1E-18 5.44E-16 5 ACE2, AGT, CCL2, TMPRSS2, TNF
Pneumonia, viral 1.56E-18 8.46E-16 5 ACE2, AGT, CCL2, TMPRSS2, TNF
Coronavirida e infections 3.4E-18 1.85E-15 5 ACE2, AGT, CCL2, TMPRSS2, TNF
Coronavirus infections 3.4E-18 1.85E-15 5 ACE2, AGT, CCL2, TMPRS S2, TNF
Nidovirales infections 3.4E-18 1.85E-15 5 ACE2, AGT, CCL2, TMPRSS2, TNF
Pneumonia 9.42E-15 5.11E-12 5 ACE2, AGT, CCL2, TMPRSS2, TNF
Respiratory tract infections 3.13E-13 1.7E-10 5 ACE2, AGT, CCL2, TMPRSS2, TNF
RNA virus infections 2.46E-12 1.34E-09 5 ACE2, AGT, CCL2, TMPRSS2, TNF
Virus dise ases 9.48E-12 5.15E-09 5 ACE2, AGT, CCL2, TMPRSS2, TNF
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Aim To figure out whether diabetes is a risk factor influencing the progression and prognosis of 2019 novel coronavirus disease (COVID‐19). Materials and Methods A total of 174 consecutive patients confirmed with COVID‐19 were studied. Demographic data, medical history, symptoms and signs, laboratory findings, chest computed tomography (CT) as well we treatment measures were collected and analyzed. Results We found that COVID‐19 patients without other comorbidities but with diabetes (n=24) were at higher risk of severe pneumonia, release of tissue injury‐related enzymes, excessive uncontrolled inflammation responses and hypercoagulable state associated with dysregulation of glucose metabolism. Furthermore, serum levels of inflammation related biomarkers such as IL‐6, C‐reactive protein, serum ferritine and coagulation index, D‐dimer, were significantly higher (p< 0.01) in diabetic patients compared with those without, suggesting that patients with diabetes are more susceptible to an inflammatory storm eventually leading to rapid deterioration of COVID‐19. Conclusions Our data support the notion that diabetes should be considered as a risk factor for a rapid progression and bad prognosis of COVID‐19. More intensive attention should be paid to patients with diabetes, in case of rapid deterioration. This article is protected by copyright. All rights reserved.
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The COVID-19 pandemic caused by infection with SARS-CoV-2 has led to more than 200,000 deaths worldwide. Several studies have now established that the hyperinflammatory response induced by SARS-CoV-2 is a major cause of disease severity and death in infected patients. Macrophages are a population of innate immune cells that sense and respond to microbial threats by producing inflammatory molecules that eliminate pathogens and promote tissue repair. However, a dysregulated macrophage response can be damaging to the host, as is seen in the macrophage activation syndrome induced by severe infections, including in infections with the related virus SARS-CoV. Here we describe the potentially pathological roles of macrophages during SARS-CoV-2 infection and discuss ongoing and prospective therapeutic strategies to modulate macrophage activation in patients with COVID-19. This Progress article from Merad and Martin examines our current understanding of the excessive inflammatory responses seen in patients with severe COVID-19. The authors focus on the emerging pathological roles of monocytes and macrophages and discuss the inflammatory pathways that are currently being targeted in the clinic.
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The pandemic coronavirus infectious disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is rapidly spreading across the globe. In this issue of the JCI, Chen and colleagues compared the clinical and immunologic characteristics between moderate versus severe COVID-19. The authors found that respiratory distress on admission is associated with unfavorable outcomes. Increased cytokine levels (IL-6, IL-10 and TNFα), lymphopenia (in CD4+ and CD8+ T cells), and decreased IFNγ expression in CD4+ T cells are associated with severe COVID-19. Overall, this study characterized the cytokine storm in severe COVID-19 and provides insights into immune therapeutics and vaccine design.
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Importance Coronavirus disease 2019 (COVID-19) is an emerging infectious disease that was first reported in Wuhan, China, and has subsequently spread worldwide. Risk factors for the clinical outcomes of COVID-19 pneumonia have not yet been well delineated. Objective To describe the clinical characteristics and outcomes in patients with COVID-19 pneumonia who developed acute respiratory distress syndrome (ARDS) or died. Design, Setting, and Participants Retrospective cohort study of 201 patients with confirmed COVID-19 pneumonia admitted to Wuhan Jinyintan Hospital in China between December 25, 2019, and January 26, 2020. The final date of follow-up was February 13, 2020. Exposures Confirmed COVID-19 pneumonia. Main Outcomes and Measures The development of ARDS and death. Epidemiological, demographic, clinical, laboratory, management, treatment, and outcome data were also collected and analyzed. Results Of 201 patients, the median age was 51 years (interquartile range, 43-60 years), and 128 (63.7%) patients were men. Eighty-four patients (41.8%) developed ARDS, and of those 84 patients, 44 (52.4%) died. In those who developed ARDS, compared with those who did not, more patients presented with dyspnea (50 of 84 [59.5%] patients and 30 of 117 [25.6%] patients, respectively [difference, 33.9%; 95% CI, 19.7%-48.1%]) and had comorbidities such as hypertension (23 of 84 [27.4%] patients and 16 of 117 [13.7%] patients, respectively [difference, 13.7%; 95% CI, 1.3%-26.1%]) and diabetes (16 of 84 [19.0%] patients and 6 of 117 [5.1%] patients, respectively [difference, 13.9%; 95% CI, 3.6%-24.2%]). In bivariate Cox regression analysis, risk factors associated with the development of ARDS and progression from ARDS to death included older age (hazard ratio [HR], 3.26; 95% CI 2.08-5.11; and HR, 6.17; 95% CI, 3.26-11.67, respectively), neutrophilia (HR, 1.14; 95% CI, 1.09-1.19; and HR, 1.08; 95% CI, 1.01-1.17, respectively), and organ and coagulation dysfunction (eg, higher lactate dehydrogenase [HR, 1.61; 95% CI, 1.44-1.79; and HR, 1.30; 95% CI, 1.11-1.52, respectively] and D-dimer [HR, 1.03; 95% CI, 1.01-1.04; and HR, 1.02; 95% CI, 1.01-1.04, respectively]). High fever (≥39 °C) was associated with higher likelihood of ARDS development (HR, 1.77; 95% CI, 1.11-2.84) and lower likelihood of death (HR, 0.41; 95% CI, 0.21-0.82). Among patients with ARDS, treatment with methylprednisolone decreased the risk of death (HR, 0.38; 95% CI, 0.20-0.72). Conclusions and Relevance Older age was associated with greater risk of development of ARDS and death likely owing to less rigorous immune response. Although high fever was associated with the development of ARDS, it was also associated with better outcomes among patients with ARDS. Moreover, treatment with methylprednisolone may be beneficial for patients who develop ARDS.
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