WO2022232161A1 - Inhibitors of nsp1 for treatment of sars-cov-2 - Google Patents

Abstract

The present invention provides inhibitors of Nspl (Non-Structural Protein 1), pharmaceutical compositions, and methods of use thereof to treat subjects having or at risk of having a severe acute respiratory syndrome coronavirus (SARS-CoV), e.g., severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

Description

INHIBITORS OF NSP1 FOR TREATMENT OF SARS-COV-2

RELATED APPLICATIONS

This application is an International Application which claims the benefit of U.S. Provisional Application No. 63/179,909, filed on April 26, 2021, and U.S. Provisional Application No. 63/306,911, filed on February 4, 2022. The entire contents of each of the foregoing applications are incorporated herein by reference.

BACKGROUND

SARS-CoV-2 is the vims causative for COVID-19 [1], which in most infected individuals begins as a respiratory illness, but is capable of infecting other organs and causing an array of clinical symptoms. SARS-CoV-2 is a member of the beta-coronavirus family, which contain related viruses known to cause human disease, including SARS, MERS, bronchitis, and the common cold. In late 2019, COVID-19 rapidly advanced from an epidemic to a pandemic, and as of January 28, 2022 the World Health Organization (WHO) has reported 360,578,392 confirmed cases and 5,620,865 deaths (https://covidl9.who.int). Although treatments and vaccines have been developed to promote immune protection against infection, there are SARS-CoV-2 variants that evade current monoclonal antibody treatments. These variants can partially escape protection induced by mRNA vaccines. Further, the long-term effectiveness of available treatments is currently unclear, given the waning immunity from vaccines. Thus, there is a clear need for therapeutic interventions that act outside of the immune system to curb the threat of COVID-19.

SUMMARY

Accordingly in one aspect, the present disclosure provides pharmaceutical compositions comprising a compound listed in any one of Tables 1-8, or a derivative thereof, and a pharmaceutically acceptable carrier or diluent.

In some embodiments, the present disclosure provides pharmaceutical compositions comprising at least two compounds listed in any one of Tables 1-8 and a pharmaceutically acceptable carrier or diluent. In some embodiments, the present disclosure provides pharmaceutical compositions which comprises three or more, four or more, or five or more compounds listed in any one of Tables 1-8 and a pharmaceutically acceptable carrier or diluent.

In some embodiments, the present disclosure provides pharmaceutical compositions which comprises Conivaptan, Montelukast, Pazopanib, Ponatinib, Rilpivirine, Tirilazad, and/or a derivative thereof. In some embodiments, the pharmaceutical compositions comprise Conivaptan or a derivative thereof. In some embodiments, the pharmaceutical compositions comprise Montelukast or a derivative thereof. In some embodiments, the pharmaceutical compositions comprise Pazopanib or a derivative thereof. In some embodiments, the pharmaceutical compositions comprise Ponatinib or a derivative thereof. In some embodiments, the pharmaceutical compositions comprise Rilpivirine or a derivative thereof. In some embodiments, the pharmaceutical compositions comprise Tirilazad or a derivative thereof. In some embodiments, the pharmaceutical compositions comprise (i) Ponatinib and Rilpivirine; (ii) Ponatinib and Montelukast; (iii) Montelukast and Rilpivirine; (iv) Montelukast, Ponatinib, and Rilpivirine; (v) Montelukast and Tirilazad; (vi) Ponatinib and Tirilazad; (vii) Conivaptan, Montelukast, and Ponatinib; (viii) Tirilazad, Montelukast, and Ponatinib; or (ix) Pazopanib, Montelukast, and Ponatinib. In some embodiments, the pharmaceutical compositions comprises Ponatinib and Rilpivirine. In some embodiments, the pharmaceutical compositions comprises Ponatinib and Montelukast. In some embodiments, the pharmaceutical compositions comprises Montelukast and Rilpivirine. In some embodiments, the pharmaceutical compositions comprises Montelukast, Ponatinib, and Rilpivirine. In some embodiments, the pharmaceutical compositions comprises Montelukast and Tirilazad. In some embodiments, the pharmaceutical compositions comprises Ponatinib and Tirilazad. In some embodiments, the pharmaceutical compositions comprises Conivaptan, Montelukast, and Ponatinib. In some embodiments, the pharmaceutical compositions comprises Tirilazad, Montelukast, and Ponatinib. In some embodiments, the pharmaceutical compositions comprises Pazopanib, Montelukast, and Ponatinib.

In some embodiments, the present disclosure provides pharmaceutical compositions which can be effective to achieve an additive effect of inhibiting Nspl to achieve a greater therapeutic effect. In some embodiments, the present disclosure provides pharmaceutical compositions which can be effective to achieve a synergistic effect of inhibiting Nspl to achieve a greater therapeutic effect. In some embodiments, the present disclosure provides pharmaceutical compositions, further comprising an additional therapeutic agent.

In some embodiments, the present disclosure provides pharmaceutical compositions, wherein the compound specifically binds to a Nspl (Non-Structural Protein 1) molecule.

In some embodiments, the present disclosure provides pharmaceutical compositions, wherein the compound specifically binds to the N-terminal domain of an Nspl molecule. In some embodiments, the compound specifically binds within residues 1-120 of the Nspl molecule. In some embodiments, the compound specifically binds to an RNA groove in the N-terminal domain of the Nspl molecule. In some embodiments, the present disclosure provides pharmaceutical compositions, wherein the compound specifically binds to the C- terminal domain of an Nspl molecule. In some embodiments, the compound specifically binds within residues 121-180 of the Nspl molecule. In some embodiments, the compound specifically binds to a helix-loop-helix region in the C-terminal domain of the Nspl molecule.

In some embodiments, the present disclosure provides pharmaceutical compositions, wherein the at least two (e.g., at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10 or more) compounds specifically binds to non-competing epitopes on the same or different Nspl molecules. In some embodiments, pharmaceutical compositions comprise at least three compounds that specifically bind to non-competing epitopes on the same or different Nspl molecules.

In some embodiments, the present disclosure provides pharmaceutical compositions, wherein the at least two (e.g., at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10 or more) compounds independently bind to non-competing epitopes on the same or different Nspl molecules. In some embodiments, pharmaceutical compositions comprise at least three compounds that independently bind to non-competing epitopes on the same or different Nspl molecules.

In some embodiments, the present disclosure provides pharmaceutical compositions, wherein the at least two (e.g., at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10 or more) compounds independently bind to the N-terminal domain and the C-terminal domain on the same or different Nspl molecules. In some embodiments, pharmaceutical compositions comprise at least three compounds that independently bind to the N-terminal domain and the C-terminal domain on the same or different Nspl molecules. In some embodiments, the present disclosure provides pharmaceutical compositions, which may be effective to inhibit the activity of the N-terminal domain and the C-terminal domain on the same or different Nspl molecules to achieve a synergistic effect of inhibiting Nspl to achieve a greater therapeutic effect. In some embodiments, the present disclosure provides pharmaceutical compositions, wherein the Nspl molecule is derived from a virus.

In some embodiments, the present disclosure provides pharmaceutical compositions, wherein the virus is a coronavims, optionally, selected from a severe acute respiratory syndrome coronavims (SARS-CoV), a severe acute respiratory syndrome coronavims 2 (SARS-CoV-2), a Middle East respiratory syndrome coronavims (MERS-CoV), a human coronavims OC43 (HCoV-OC43), a human coronavims HKU1 (HCoV-HKUl), a human coronavims 229E (HCoV-229E), a human coronavims NL63 (HCoV-NL63), and variants thereof.

In some embodiments, the present disclosure provides pharmaceutical compositions, wherein the vims causes bronchitis and/or the common cold.

In some embodiments, the present disclosure provides pharmaceutical compositions, which may be effective (i) to diminish the activity of Nspl in vivo , in vitro , and/or ex vivo ,

(ii) to reduce the deleterious sequelae of COVID-19 infection by enhancing lung cell function and survival in a subject, (iii) to use in a subject with minimal toxicity, and/or (iv) when administered to a subject to achieve a therapeutic effect.

In some embodiments, the present disclosure provides pharmaceutical compositions, wherein: (i) the compound has an EC 100 of between about 0.01 mM and about 100 pM; and/or (ii) the compound has a Safety Index of greater than about 5.

In some embodiments, the compound may have an EC 100 of between about 0.01 pM and about 100 pM. For example, the compound may have an ECIOO of about 0.01 pM, about 0.02 pM, about 0.03 pM, about 0.04 pM, about 0.05 pM, about 0.06 pM, about 0.07 pM, about 0.08 pM, about 0.09 pM, about 0.1 pM, about 0.2 pM, about 0.3 pM, about 0.4 pM, about 0.5 pM, about 0.6 pM, about 0.7 pM, about 0.8 pM, about 0.9 pM, about 1 pM, about 5 pM, about 10 pM, about 15 pM, about 20 pM, about 25 pM, about 30 pM, about 35 pM, about 40 pM, about 45 pM, about 50 pM, about 55 pM, about 60 pM, about 65 pM, about 70 pM, about 75 pM, about 80 pM, about 85 pM, about 90 pM, about 95 pM, or about 100 pM.

In some embodiments, the compound may have a Safety Index of greater than about 5. In some embodiments, the compound may have a Safety Index of between about 5 and about 100. For example, the compound may have a Safety Index of about 5, about 10, about 15, about 20, about 25, about 30, about 35, about 40, about 45, about 50, about 55, about 60, about 65, about 70, about 75, about 80, about 85, about 90, about 95, about 100, about 150, about 200, about 250, about 300, about 350, about 400, about 450, about 500, about 550, about 600, about 650, about 700, about 750, about 800, about 850, about 900, about 950, about 1000, about 1500, about 2000, about 2500, about 3000, about 3500, about 4000, about 4500, or about 5000 or more.

In some embodiments, the present disclosure provides pharmaceutical compositions, which can reverse Nspl toxicity to substantially the same extent as a null mutation in the Nspl gene itself, as determined by a cytopathic assay, optionally wherein the null mutation comprises N128S/K129E and/or K164A.

Accordingly in one aspect, the present disclosure provides methods of treating or preventing a viral infection in a subject, the method comprising administering to the subject an effective amount of the pharmaceutical composition described herein.

In some embodiments, the present disclosure provides methods of treating or preventing a viral infection in a subject, the method comprising administering to the subject an effective amount of the pharmaceutical composition described herein, wherein the viral infection is a coronavirus infection.

In some embodiments, the present disclosure provides methods of treating or preventing a viral infection in a subject, the method comprising administering to the subject an effective amount of the pharmaceutical composition described herein, wherein the coronavirus infection is an infection by a SARS-CoV-2 virus.

In some embodiments, the present disclosure provides methods of treating or preventing a viral infection in a subject, the method comprising administering to the subject an effective amount of the pharmaceutical composition described herein, wherein the subject has, or is at risk of having, COVID-19.

In some embodiments, the present disclosure provides methods of treating or preventing a viral infection in a subject, the method comprising administering to the subject an effective amount of the pharmaceutical composition described herein, wherein the pharmaceutical composition is administered to the subject prior to onset of one or more manifestations of COVID-19.

In some embodiments, the present disclosure provides methods of treating or preventing a viral infection in a subject, the method comprising administering to the subject an effective amount of the pharmaceutical composition described herein, wherein the pharmaceutical composition is administered to the subject after the subject exhibits one or more manifestations of COVID-19.

In some embodiments, the present disclosure provides methods of treating or preventing a viral infection in a subject, the method comprising administering to the subject an effective amount of the pharmaceutical composition described herein, wherein the method results in the amelioration of one or more manifestations of COVID-19.

In some embodiments, the present disclosure provides methods of treating or preventing a viral infection in a subject, the method comprising administering to the subject an effective amount of the pharmaceutical composition described herein, wherein the pharmaceutical composition is administered by any suitable route, optionally, orally, intranasally, intravenously, intramuscularly, or subcutaneously.

In some embodiments, the present disclosure provides methods of treating or preventing a viral infection in a subject, the method comprising administering to the subject an effective amount of the pharmaceutical composition described herein, wherein the pharmaceutical composition is administered before and/or after viral shedding is first detected in a sample from the subject.

In some embodiments, the present disclosure provides methods of treating or preventing a viral infection in a subject, the method comprising administering to the subject an effective amount of the pharmaceutical composition described herein, wherein the pharmaceutical composition is administered in combination with an additional therapeutic agent.

In some embodiments, the present disclosure provides methods of treating or preventing a viral infection in a subject, the method comprising administering to the subject an effective amount of the pharmaceutical composition described herein, wherein the subject is human.

Accordingly in one aspect, the present disclosure provides assays, which may be effective to identify a compound or combination of compounds that specifically bind to an Nspl molecule. BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts the secondary structure of Nspl (Non- Structural Protein 1) from SARS-CoV-2. The N-terminal globular region consists of 7 beta-pleated sheets as shown. Juxtaposition of Beta- 1 with Beta-7 creates an RNA-binding groove that binds to the 5’ UTR of SARS-CoV-2 RNAs [9]. The N-globular region is connected via a disordered loop the C- domain, which is an alpha- loop-alpha (alpha-2 and alpha-3 helices as shown) [8]. The C- domain blocks the mRNA tunnel in human ribosomes to prevent host cell translation [2, 3, 12].

FIGS. 2A-2E depicts quantitation of the cytopathic effects of Nspl in H1299 cells. H1299 cells were transfected with Nspl mRNA in 96-well plates. FIG. 2A shows phase contrast images of non-transfected cells, and cells transfected with Tag-Red Fluorescent Protein (RFP) mRNA as a control or Nspl mRNA. Both RFP and Nspl mRNAs were flanked by viral UTRs, and cells were transfected under identical conditions on the same plate. FIG. 2B shows control (non-transfected) and Nspl -transfected cells that were stained with Hoescht 33342 dye as a measure of cell attachment. FIG. 2C shows Calcein-AM, as a measure of vitality or metabolic diversion. FIG. 2D shows TMRE, as a measure of mitochondrial membrane potential or activity. Fluorescent images and quantitation (n=6; p- value from a two-sided t-test compared to the control) are depicted. FIG. 2E shows the Viability Index is the normalized product of quantitation using the latter three dyes. The images in FIG. 2E were pseudocolored blue (Hoescht), green (Calcein-AM) and red (TMRE).

FIG. 3 shows a schematic diagram depicting the secondary structure of Nspl represented as an unfolded chain (from N- to C-terminal) with numbered alpha helices (a), numbered beta sheets (b), and 3 io helices. The beta sheets, b2 pairs with b6, b3 pairs with b4, and bΐ pairs with b7 to form an RNA groove. The C-terminal helix-loop-helix (oc2-oc3) is termed the ribosome gatekeeper [13] because of its role in blocking the RNA tunnel in the 40S ribosomal subunit. The sequential order and beta sheet pairings were adapted from Semper et al [18] and Almeida et al [65]. The mutations depicted are A (L21M), B (D33R), C (L123S/R124E), D (N128S/K129E), and E(K164A).

FIG. 4 shows measurement of efficacy and relationship to Nspl mutants. The

Viability Index was determined for H1299 cells treated under various control conditions: no transfection (Control), transfected with RNA containing only viral 5’ and 3 ’UTR and no coding sequence (Viral UTRs only), or transfected with no RNA (Lipo only). Nspl mRNA was also transfected into HI 299 cells in different contexts: wild-type Nspl flanked by the 5’UTR and 3’UTR corresponding to that of human alpha-globin mRNA (WT globin UTRs), or flanked by the viral UTRs corresponding to that of SARS-CoV-2 (WT Viral UTRs). All point mutations of Nspl (A through E, corresponding to the point mutations described in FIG. 3) were expressed as coding regions flanked by Viral UTRs. Efficacy is defined by a different scale as indicated, and represents the degree to which wild-type Nspl toxicity is reversed compared to HI 299 cells incubated under the same conditions of transfection. The statistical significance of context and mutations compared to WT Nspl -Viral UTRs are indicated (n>15 for each measure; p-value from a two-sided t-test, ns= not significant, ** p < 10-5).

FIGS. 5A-5B depicts the synergistic interactions among Ponatinib, Rilpivirine, and Montelukast. Combinations of drugs were applied to Nspl -transfected H1299 cells, and Efficacies were determined. The Efficacy at the indicated concentrations of each drug were used to visualize synergy using an online tool [35]. Areas demarcated in red represent synergistic combinations as shown in the scale quantitated by the ZIP method [35, 36]. FIG. 5A shows data pooled from triplicate experiments to generate the Efficacy table and Synergy plot of Ponatinib and Rilpivirine. FIG. 5B shows Efficacy table and Synergy plot between a combination of Ponatinib+Rilpivirine at a molar ratio of 2.5 to 1, and Montelukast. The concentration for the Ponatinib+Rilpivirine combination reflects that of Ponatinib only.

FIG. 6 depicts comparative Efficacies of drug combinations using Montelukast, Ponatinib, Rilpivirine. Efficacies were determined using compounds alone or in various combinations in Nspl -transfected HI 299 cells at the indicated concentrations. Measurements were conducted with N replicates and error bars represent + SEM. One combination (M2+P+R) displayed greater Efficacy than other combinations shown in this graph. A one way ANOVA analyses indicates that there is significant difference between the means of at least two drug combinations (F14, 243=1.985, p=0.02). Eliminating M2+P+R from the analyses rendered the one-way ANOVA not significant (F13, 233=1.274, p=0.23).

FIGS. 7A-7B depicts dose-response of a Montelukast-Ponatinib-Rilpivirine (MPR) combination. The ratio of Montelukast, Ponatinib, and Rilpivirine (MPR) were fixed such that a IX concentration = 1.25 mM Montelukast + 0.1 pM Ponatinib + 0.05 pM Rilpivirine. FIG. 7A shows varying concentrations of MPR were added to Nspl -transfected H1299 cells and Efficacy determined and depicted. Cytotoxicity using the Viability Index in non- transfected H1299 were determined at various concentrations of MPR and depicted on the same graph. FIG. 7B shows lx MPR was applied to H1299 cells transfected with wild-type (WT) Nspl or the indicated Nspl mutations (Mut A-C). Error bars represent ± SEM. Statistical significance of treatment with lxMPR is indicated (n>5; p-value from a two-sided t-test). Also shown for comparison are the Efficacy of 0.5xMPR on WT-Nspl -transfected H1299 cells (n=16, p-value from a two-sided t-test), and the effect of established mutations in the Nspl gene (Mut D and E, which do not differ significantly from 0.5xMPR-treated WT- Nspl -transfected H1299 cells).

FIGS. 8A-8C depicts synergistic interactions of potentially promising drug pairs. Serial dilutions of the indicated drugs were applied to Nspl -transfected HI 299 cells in 96- well plates, in a 2x2 matrix, and Efficacies were determined. The Efficacy at the indicated concentrations of each drug were inputted into SynergyFinder 2.0, an online tool for visualizing synergy [35]. Synergy is quantitated by the ZIP method [35, 36] and visualized on a red-green scale as indicated. Efficacy tables and Synergy plots are shown for each of the following drug pairs: (FIG. 8A) Montelukast versus Ponatinib (data were averaged or consolidated from 10 replicates); (FIG. 8B) Montelukast versus Tirilazad (data were averaged or consolidated from 3 replicates); and (FIG. 8C) Tirilazad versus Ponatinib (data were averaged or consolidated from 3 replicates).

FIGS. 9A-9C depicts synergistic interactions between selected drugs and Montelulast+Ponatinib (fixed molar ratio). Serial dilutions of the indicated drugs and Montelukast+Ponatinib or MP (molar ratios fixed at 10:1) were applied to Nspl -transfected H1299 cells in 96-well plates, in a 2x2 matrix, and Efficacies was determined. The concentration indicated for MP reflects that of Montelukast. Efficacy at the indicated concentrations of each drug were inputted into SynergyFinder 2.0, and synergy was quantitated and visualized as in FIGS. 8A-8C. Efficacy tables and Synergy plots are shown for each of the following drug combinations: (FIG. 9A) Conivaptan versus MP; (FIG. 9B) Tirilazad versus MP; (FIG. 9C) Pazopanib versus MP.

DETAILED DESCRIPTION

The present invention provides compounds that specifically bind to a Nspl (Non- Stmctural Protein 1) molecule and methods of use to treat subjects having or at risk of having a viral, e.g., a coronavims, infection. In particular, the present invention provides pharmaceutical compositions comprising compound(s) that specifically bind to a Nspl molecule derived from a severe acute respiratory syndrome coronavims 2 (SARS-CoV-2) and methods of use thereof to treat subjects having or at risk of having a SARS-CoV-2 infection ( i.e ., COVID-19).

In one aspect, the present invention provides a rapid multiplexed assay for detecting the action of Nspl in vitro (e.g., in cultured lung cells) and for identifying compounds that act as inhibitors of Nspl.

Accordingly, the present invention provides compounds that can be used to treat COVID-19. In particular, the present invention provides compositions comprising synergistic combinations of compounds that significantly inhibit Nspl action. More specifically, the present invention provides compositions comprising Ponatinib, Rilpivirine, and/or Montelukast, which together, may reverse the toxic effects of Nspl, for example, to the same extent as null mutations in the Nspl gene.

The following detailed description discloses pharmaceutical compositions comprising inhibitors of Nspl (Non- Structural Protein 1) as well as methods for treating or preventing a viral infection in subjects, e.g., subjects susceptible to or diagnosed with a coronavims, e.g., SARS-CoV, e.g., SARS-CoV-2 infection (i.e., COVID-19).

Additional embodiments contemplated by the invention include, without limitation, include:

1. Some of the dmgs listed in Tables 1-8 diminish the activity of Nspl and can thereby reduce the deleterious sequelae of COVID-19 infection by enhancing lung cell function and survival.

2. A combination of a drug that inhibits the N-domain plus a drug that inhibits the C- domain has a synergistic effect by furthering the inhibition of Nspl, providing greater therapeutic benefit. 3. The assay described herein provides a useful index of the potential therapeutic effectiveness of a drug or drug combination.

4. Some of the drugs have previously been used in humans for other therapeutic indications, and their effectiveness in COVID-19 is in the same therapeutic range as used previously. This would indicate that the drugs can be used in humans with minimal toxicity.

5. Related compounds to the drugs indicated in Tables 1-8 have therapeutic benefit in patients stricken with COVID-19.

6. In addition to just treating COVID-19, the drugs in Tables 1-8 and related compounds could potentially be used to prevent COVID-19 in an endemic geographic region, or to prevent deleterious symptoms in individuals exposed to the virus.

7. The drugs indicated in Tables 1-8 have potential benefits in related human coronaviral diseases, such as MERS, bronchitis, and the common cold.

8. Since the drugs listed in Tables 1-8 are targeted towards Nspl, they may be particularly valuable in treating individuals infected by certain variants of SARS-CoV-2. Variants are worrisome as they possess the potential to evade the protection afforded by vaccines. Currently, the dominant variants in circulation display mutations in the Spike protein but do not contain mutations in Nspl.

9. The drugs listed in Tables 1-8 may possess synergistic actions to drugs in development whose intended purpose is to treat COVID-19. For example, the drugs listed in Tables 1-8 could enhance the therapeutic effectiveness of protease inhibitors, polymerase inhibitors, or anti-helicase compounds that are in development as antiviral treatments for COVID-19. Accordingly, such drugs may constitute part of a cocktail for aggressive treatment of COVID-19.

I. Definitions

In order that the present invention may be more readily understood, certain terms are first defined. In addition, it should be noted that whenever a value or range of values of a parameter are recited, it is intended that values and ranges intermediate to the recited values are also intended to be part of this invention.

The articles “a” and “an” are used herein to refer to one or to more than one (i.e., to at least one) of the grammatical object of the article. By way of example, “an element” means one element or more than one element, e.g., a plurality of elements.

The term “including” is used herein to mean, and is used interchangeably with, the phrase “including but not limited to”.

The term “or” is used herein to mean, and is used interchangeably with, the term “and/or,” unless context clearly indicates otherwise.

The term “about” is used herein to mean within the typical ranges of tolerances in the art. For example, “about” can be understood as about 2 standard deviations from the mean. In certain embodiments, about means +10%. In certain embodiments, about means +5%. When about is present before a series of numbers or a range, it is understood that “about” can modify each of the numbers in the series or range.

The term “at least” prior to a number or series of numbers is understood to include the number adjacent to the term “at least”, and all subsequent numbers or integers that could logically be included, as clear from context. When at least is present before a series of numbers or a range, it is understood that “at least” can modify each of the numbers in the series or range.

As used herein, “no more than” or “less than” is understood as the value adjacent to the phrase and logical lower values or integers, as logical from context, to zero. When “no more than” is present before a series of numbers or a range, it is understood that “no more than” can modify each of the numbers in the series or range. As used herein, ranges include both the upper and lower limit.

As used herein, the term “coronavirus,”(“CoV”; subfamily Coronavirinae, family Coronaviridae, order Nidovirales), refers to a group of highly diverse, enveloped, positive-sense, single- stranded RNA viruses that cause respiratory, enteric, hepatic and neurological diseases of varying severity in a broad range of animal species, including humans. Coronaviruses are subdivided into four genera: Alphacoronavirus, Betacoronavirus (13CoV), Gammacoronavirus and Deltacoronavirus .

As use herein, the term “severe acute respiratory syndrome coronavirus” or “SARS- CoV”, refers to a coronavirus that was first discovered in 2003, which causes severe acute respiratory syndrome (SARS). SARS-CoV represents the prototype of a new lineage of coronaviruses capable of causing outbreaks of clinically significant and frequently fatal human disease. The complete genome of SARS-CoV has been identified, as well as common variants thereof. The genome of SARS-CoV is a 29,727-nucleotide polyadenylated RNA, has 11 open reading frames, and 41% of the residues are G or C. The genomic organization is typical of coronaviruses, with the characteristic gene order (5'-replicase (rep), spike (S), envelope (E), membrane (M), nucleocapsid (N)-3' and short untranslated regions at both termini. The SARS-CoV rep gene, which comprises about two-thirds of the genome, is predicted to encode two polyproteins that undergo co-translational proteolytic processing. There are four open reading frames (ORFs) downstream of rep that are predicted to encode the structural proteins, S, E, M and N. The hemagglutinin-esterase gene, which is present between ORFlb and S in group 2 and some group 3 coronaviruses was not found.

As use herein, the terms “severe acute respiratory syndrome coronavirus 2,” “SARS- CoV-2,” “2019-nCoV,” refer to the novel coronavirus that caused a pneumonia outbreak first reported in Wuhan, China in December 2019 (“COVID-19”). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that SARS-CoV-2 was most closely related (89.1% nucleotide similarity similarity) to SARS-CoV.

By the phrase “therapeutically effective amount” is meant an amount that produces the desired effect for which it is administered. The exact amount will depend on the purpose of the treatment, and will be ascertainable by one skilled in the art using known techniques (see, for example, Lloyd (1999) The Art, Science and Technology of Pharmaceutical Compounding).

By “treatment”, “prevention” or “amelioration” of a disease or disorder, e.g., a coronavirus, e.g., SARS-CoV, e.g., SARS-CoV-2, infection is meant delaying or preventing the onset of such a disease or disorder, reversing, alleviating, ameliorating, inhibiting, slowing or stopping the progression, aggravation or deterioration, the progression or severity of a condition associated with such a disease or disorder. In one embodiment, the symptoms of a disease or disorder, or pain and distress associated with an infection, are alleviated by at least 5%, at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or at least 95%. In one embodiment, the transmission of a coronavirus infection, is reduced by at least 5%, at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or at least 95%.

As used herein, a “subject” means a human or an animal. The animal may be a vertebrate such as a primate, rodent, domestic animal or game animal. Primates include chimpanzees, cynomologous monkeys, spider monkeys, and macaques, e.g., Rhesus. Rodents include mice, rats, woodchucks, ferrets, rabbits and hamsters. Domestic and game animals include cows, sheep, pigs, goats, birds, horses, pigs, deer, bison, buffalo, amphibians, reptiles, feline species, e.g., domestic cat, canine species, e.g., dog, fox, wolf, avian species, e.g., chicken, emu, ostrich, and fish, e.g., trout, catfish and salmon. In certain embodiments, the subject is an embryo or a fetus, where a life-long protection is elicited after vaccination with the present invention.

In certain embodiments, the subject is a mammal, e.g., a primate, e.g., a human. The terms, “patient” and “subject” are used interchangeably herein. Preferably, the subject is a mammal. The mammal can be a human, non-human primate, mouse, rat, dog, cat, horse, pig, sheep, goat, bird, reptile, amphibian, fish or cow. Mammals other than humans can be advantageously used as subjects that represent animal models of infectious diseases, or other related pathologies. A subject can be male or female. The subject can be an adult, an adolescent or a child. A subject can be one who has been previously diagnosed with or identified as suffering from or having a risk for developing a coronavirus, e.g., SARS-CoV, e.g., SARS-CoV-2, infection. In a preferred embodiment, the subject is a human, such as a human being treated or assessed for a coronavirus, e.g., SARS-CoV, e.g., SARS-CoV-2, infection; a human at risk for a coronavirus, e.g., SARS-CoV, e.g., SARS-CoV-2, infection; a human having a coronavirus, e.g., SARS-CoV, e.g., SARS-CoV-2, infection. In some embodiments, the subject is a female human. In other embodiments, the subject is a male human. In one embodiment, the subject is an adult subject. In another embodiment, the subject is a pediatric subject.

The term “vaccine,” as used herein, includes any composition containing an immunogenic determinant which stimulates the immune system such that it can better respond to subsequent infections. A vaccine usually contains an immunogenic determinant, e.g., an antigen, and an adjuvant, the adjuvant serving to non- specifically enhance the immune response to that immunogenic determinant. Currently produced vaccines predominantly activate the humoral immune system, i.e., the antibody dependent immune response. Other vaccines focus on activating the cell-mediated immune system including cytotoxic T lymphocytes which are capable of killing targeted pathogens.

The term “adjuvant”, as used herein, refers to compounds that can be added to vaccines to stimulate immune responses against antigens. Adjuvants may enhance the immunogenicity of highly purified or recombinant antigens. Adjuvants may reduce the amount of antigen or the number of immunizations needed to protective immunity. For example, adjuvants may activate antibody- secreting B cells to produce a higher amount of antibodies. Alternatively, adjuvants can act as a depot for an antigen, present the antigen over a longer period of time, which could help maximize the immune response and provide a longer-lasting protection. Adjuvants may also be used to enhance the efficacy of a vaccine by helping to modify the immune response to particular types of immune system cells, for example, by activating T cells instead of antibody- secreting B cells depending on the purpose of the vaccine.

As used herein, the term “additive effect” means that the activity of the combination of compounds is about equal to the sum of the individual activities of the compound in the combination when the activity of each compound is determined individually.

As used herein, the term “synergy” or “synergistic” encompasses a more than additive effect of a combination of two or more agents compared to their individual effects. In certain embodiments, synergy or synergistic effect refers to an advantageous effect of using two or more agents in combination, e.g., in a pharmaceutical composition, or in a method of treatment. In certain embodiments, one or more advantageous effects is achieved by using one or more compounds that specifically binds to a Nspl (Non-Structural Protein 1) molecule in combination with a second therapeutic agent as described herein.

II. Compositions of the Invention

A. Nspl (Non-Structural Protein 1)

Nspl (Non-Structural Protein 1) is the first protein generated from the SARS-CoV-2 genome upon infection of human cells and is a major pathogenicity factor [7-9]. This protein plays a pivotal role in subverting the host cell’s translation machinery, by shutting down all host cell translation while allowing viral translation to occur [2-4]. Nspl has the distinction of being the only protein out of 30 proteins expressed from SARS-CoV-2 that is lethal to cells [5]. Previous studies in other beta-coronaviruses indicate that deletion of Nspl renders the virus nonpathogenic to the host [6], highlighting the importance of this protein in the life cycle of the virus.

Nspl is fundamentally an RNA binding protein that targets the 40S ribosomal subunit and the first stem-loop of the 5‘UTR of viral RNAs [8, 9]. Nspl also possesses significant protein-protein interactions that recruit translation factors and inhibit the export of mRNA from the nucleus [10]. Collectively, the outcome of these actions is the global inhibition of host cell mRNA translation while viral mRNA translation remains intact [7-13].

Accordingly, cellular innate defenses such as the induction of interferon is inhibited, while viral replication and assembly proceeds unhindered.

In addition to the key role played by Nspl during the initial stages of the viral life cycle, Nspl is the only protein expressed from the SARS-CoV-2 genome that leads to significant cell death [7]. The mechanism of cell death is apoptosis and occurs over the course of days after the expression of Nspl [7]. The inhibition of cell protein synthesis likely contributes to apoptosis as well as the severe respiratory symptoms associated with COVID- 19. Thus, therapeutics targeting Nspl could mitigate the symptoms of severe COVID-19 as well as slow the progression of the viral life cycle.

Another advantage to targeting Nspl is that the sequence of this protein has remained unaltered in all current SARS-CoV-2 variants of concern, including the alpha, beta, delta, epsilon, mu, and omicron variants. Therapeutics targeting Nspl may therefore target all such variants. Accordingly, targeting Nspl may have therapeutic benefits for patients stricken with COVID-19.

The 3-dimensional structure of Nspl has been solved using X-Ray crystallography and cryo-electron microscopy [2, 3, 7, 8]. The structure-function relation has also been deduced by comparison to SARS-CoV and by experimental methods. The protein is 180 amino acids long and folds into an N-terminal globular domain, connected by a disordered loop to an alpha-loop-alpha region at the C-terminal domain (FIG. 1, FIG. 3). The N-domain binds to the 5’UTR of viral RNAs via a groove created by juxtaposition of the first and last beta sheet of this region [9]. Mutations affecting the groove almost invariably diminish or abolish the action of Nspl [10], strongly suggesting that the RNA-binding groove in the N- domain is a functional site. The C-terminal alpha-loop-helix domain fits into the RNA tunnel of ribosomes, thereby blocking host cell translation [3]. Again, mutations affecting this domain diminish or abolish the activity of Nspl [11]. Thus, there are at least two independent functional domains contained within Nspl (FIG. 1, FIG. 3). B. Compounds targeting Nspl

The present disclosure provides compositions and therapeutic formulations comprising any of the exemplary compounds described herein, for example, as listed in any one of Tables 1-8, in combination with one or more additional therapeutic agents, and methods of treatment comprising administering such combinations to subjects in need thereof.

Accordingly in one aspect, the present disclosure provides pharmaceutical compositions comprising a compound listed in any one of Tables 1-8, or a derivative thereof, and a pharmaceutically acceptable carrier or diluent. In some embodiments, the present disclosure provides pharmaceutical compositions comprising at least two compounds (e.g., at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10 or more) listed in any one of Tables 1-8 and a pharmaceutically acceptable carrier or diluent. In some embodiments, the present disclosure provides pharmaceutical compositions which comprises three or more, four or more, or five or more (e.g., at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10 or more) compounds listed in any one of Tables 1-8 and a pharmaceutically acceptable carrier or diluent.

Exemplary Combinations

In some embodiments, the present disclosure provides pharmaceutical compositions which comprises Conivaptan, Montelukast, Pazopanib, Ponatinib, Rilpivirine, Tirilazad, and/or a derivative thereof. In some embodiments, the pharmaceutical compositions comprise Conivaptan or a derivative thereof. In some embodiments, the pharmaceutical compositions comprise Montelukast or a derivative thereof. In some embodiments, the pharmaceutical compositions comprise Pazopanib or a derivative thereof. In some embodiments, the pharmaceutical compositions comprise Ponatinib or a derivative thereof. In some embodiments, the pharmaceutical compositions comprise Rilpivirine or a derivative thereof. In some embodiments, the pharmaceutical compositions comprise Tirilazad or a derivative thereof. In some embodiments, the pharmaceutical compositions comprise (i) Ponatinib and Rilpivirine; (ii) Ponatinib and Montelukast; (iii) Montelukast and Rilpivirine; (iv) Montelukast, Ponatinib, and Rilpivirine; (v) Montelukast and Tirilazad; (vi) Ponatinib and Tirilazad; (vii) Conivaptan, Montelukast, and Ponatinib; (viii) Tirilazad, Montelukast, and Ponatinib; or (ix) Pazopanib, Montelukast, and Ponatinib. In some embodiments, the pharmaceutical compositions comprises Ponatinib and Rilpivirine. In some embodiments, the pharmaceutical compositions comprises Ponatinib and Montelukast. In some embodiments, the pharmaceutical compositions comprises Montelukast and Rilpivirine. In some embodiments, the pharmaceutical compositions comprises Montelukast, Ponatinib, and Rilpivirine. In some embodiments, the pharmaceutical compositions comprises Montelukast and Tirilazad. In some embodiments, the pharmaceutical compositions comprises Ponatinib and Tirilazad. In some embodiments, the pharmaceutical compositions comprises Conivaptan, Montelukast, and Ponatinib. In some embodiments, the pharmaceutical compositions comprises Tirilazad, Montelukast, and Ponatinib. In some embodiments, the pharmaceutical compositions comprises Pazopanib, Montelukast, and Ponatinib.

Exemplary additional therapeutic agents include any therapeutic agents that may be used for the treatment of any disorders described herein. In some embodiments, the additional therapeutic agents may be used for the treatment of a coronavirus, e.g., SARS-CoV-2, infection in a subject. In some embodiments, the additional therapeutic agents may be used for the treatment of COVID-19. The additional therapeutic agent(s) may be administered prior to, concurrent with, or after the administration of a composition of the present invention.

III. Therapeutic Uses and Kits

The present invention includes methods comprising administering to a subject in need thereof a therapeutic composition comprising a one or more of the compounds and/or compositions described herein. The therapeutic composition can comprise any of the compounds as disclosed herein and a pharmaceutically acceptable carrier or diluent. As used herein, the expression “a subject in need thereof’ means a human or non-human animal that exhibits one or more symptoms or indicia of a Nspl associated disorder or disease, and/or who otherwise would benefit from a decrease in Nspl activity. The compounds of the invention (and therapeutic compositions comprising the same) are useful, inter alia, for treating any disease or disorder in which inhibition of Nspl is beneficial.

In some embodiments, the present invention provides methods for treat various Nspl associated diseases. As used herein, the term “Nspl associated disease,” is a disease or disorder that is caused by, or associated with, Nspl protein production or Nspl protein activity. The term “Nspl associated disease” includes a disease, disorder or condition that would benefit from a decrease in Nspl protein activity. Non-limiting examples of Nspl associated disease include, for example, a viral infection. Further details regarding signs and symptoms of the various diseases or conditions are provided herein and are well known in the art.

Accordingly in one aspect, the present disclosure provides methods of treating or preventing a viral infection in a subject, the method comprising administering to the subject an effective amount of the pharmaceutical composition described herein. In some embodiments, the viral infection may be a coronavirus infection. More particularly, the coronavirus infection may be an infection by a SARS-CoV-2 virus or variant thereof. Such method may result in the amelioration of one or more manifestations of COVID-19.

In some embodiments, a pharmaceutical composition may be administered to the subject prior to onset of one or more manifestations of COVID-19. In some embodiments, a pharmaceutical composition may be administered to the subject after the subject exhibits one or more manifestations of COVID-19. In some embodiments, a pharmaceutical composition may be administered to the subject before and/or after viral shedding is first detected in a sample from the subject. The pharmaceutical composition may be administered by any suitable route, including, for example, orally, intranasally, intravenously, intramuscularly, or subcutaneously.

Administration of the compositions according to the methods of the invention may result in a reduction of the severity, signs, symptoms, or markers of a Nspl associated disease or disorder in a subject with a Nspl associated disease or disorder. By “reduction” in this context is meant a statistically significant decrease in such level. The reduction (absolute reduction or reduction of the difference between the elevated level in the subject and a normal level) can be, for example, at least about 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, or 95%, or to below the level of detection of the assay used.

Any of the compounds and/or compositions described herein may be comprised in a kit. The kit may further include reagents or instructions for using the compounds and/or compositions in a subject. It may also include one or more buffers.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention be-longs. Although methods and materials similar or equivalent to those described herein can be used, suitable methods and materials are described below. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, the present specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and not intended to be limiting.

The present invention is further illustrated by the following examples, which are not intended to be limiting in any way. The entire contents of all references, patents and published patent applications cited throughout this application, as well as the Figures, are hereby incorporated herein by reference.

EXAMPLES

Example 1. Virtual Screening

In silico screening was conducted to identify compounds that bind and potentially inhibit the function of Nspl. Two programs were used: ICM [13] and AutoDock Vina [14]. The crystal structure for the N-domain used was 7k7p [7], and binding was verified using 7k3n [8]. Virtual compound libraries utilized in this screen include DrugBank [15], ZINC 15 [16], and eDrug3D [17]. ICM was used to virtually screen for compounds that bind to the RNA-binding groove depicted in FIG. 1. The list of top hits is shown in Table 1. ICM was not used to identify compounds for the C-domain because the structure was too small. AutoDock Vina was used to screen potential compounds that bind to the N-domain using the ZINC 15 database (Tables 2-3), and the eDmg3D compendium (Table 4). AutoDock Vina was also used to screen potential compounds that bind to the C-domain using 3 available structures, 6zlw [3], 6zok [2], 7k5i [12]. The list of C-domain binding candidates is shown in Table 5. Other compounds of theoretical interest (derived from literature searches) is shown in Table 6.

Example 2. Rapid Cellular Screen for Nspl (Non-Structural Protein 1) Activity

Only about 12% of compounds selected from an in silico screen may show activity against a chosen target [18]. Therefore, further enrichment of candidate drugs is essential using the appropriate experimental assay.

Previous assays for Nspl (Non-Structural Protein 1) activity (in SARS-CoV) relied on the ability of Nspl to activate interferon activity in various cell types [10]. Other assays depended on the ability of Nspl to inhibit translation in a cell-free system [2, 3]. These assays are cumbersome and not readily amenable for screening potential drugs that have an inhibitory effect on Nspl function.

This study developed a rapid assay in H1299 cells, a lung cell line that has been used in SARS-CoV-2 research. Expression of Nspl in this cell line results in gradual cell death by progressive apoptosis. The assay was optimized in the following ways:

1. mRNA encoding Nspl was transfected into H1299 at 75%-80% confluence in 96- well plates. Under these conditions, almost 100% of the cells are transfected, and expression of the protein occurs in 4-6 hours. This is contrast to the typical DNA transfection protocol used by most laboratories, which is generally inefficient in lung cells.

2. The mRNA contains the 5’UTR and 3’UTR elements of the SARS-Cov-2 genomic RNA. Inclusion of these elements in the mRNA significantly enhanced the toxicity of Nspl.

3. A compound, polyTC, which is double-stranded RNA, is included in the cell culture experiment. PolyTC binds to the TL3 receptor, which potently induces interferon production [19]. PolyTC mimics infection by an RNA virus, and prompts cells to launch a robust innate cellular defense [19, 20]. Nspl blocks this defense from actually occurring by shutting down host cell translation. When this occurs, cells respond by committing suicide, that is, programmed cell death or apoptosis. It is thought that this curious response evolved to prevent the dissemination of virus [21], but it is also deleterious as observed during the clinical course of the disease. This assay essentially magnifies the lethality of Nspl induction by simulating an infection with high viral load in cell culture.

4. A multiplexed fluorescent assay to determine cell viability using the dye, calcein- AM [22], as well as early apoptosis, using the mitochondrial marker, TMRE [23], was used.

Under these conditions, the effect of the drug can be ascertained at different concentrations in about 1-2 days. Reproducible measurements of viability, cell death, and mitochondrial activity are obtained at different concentrations of the drug. Table 1. Compounds from DrugBank that are predicted to bind to the N-Domain using ICM.

Table 2. Candidates from the ZINC 15 database (with available common name) that are predicted to bind to the N-domain using AutoDock Vina.

Table 3. Candidates from the ZINC15 database (Ligand ID only) that ae predicted to bind to the N-domain using AutoDock Vina.

Table 4. Candidates from the eDrug database that ae predicted to bind to the N-domain using AutoDock Vina.

Table 5. Candidates from the eDrug database that ae predicted to bind to the C-domain using AutoDock Vina.

Table 6. Other Compounds of Interest, derived from Literature Searches.

Example 3. Synergistic Interactions of Repurposed Drugs that Inhibit Nspl, a Major Virulence Factor for COVID-19

To rapidly identify compounds that act as inhibitors of Nspl, a cell-based cytopathic assay was developed that takes advantage of Nspl’s ability to induce cell death. The theoretical binding affinity of compounds targeting active regions of Nspl were stratified using in silico screening. Drugs that can be repurposed were prioritized for further investigation. No single drug in this group possessed the ability to completely reverse Nspl action using the rapid cellular screen. Therefore, strategic combinations of compounds were systematically investigated using the rapid cellular screen. In this manner, specific combinations of drugs were identified that act synergistically and were capable of significantly reducing Nspl -mediated cell death. Moreover, the effective concentration of these drugs resides in the nanomolar range, which is clinically attainable in humans. Since the drugs have been previously used in humans, much is known about their side effects. Therefore, the testing of these drug combinations in clinical trials offers the possibility of alternative effective treatments for COVID-19.

Development of a Rapid Assay for Nspl Action. Nspl is the only viral gene product that significantly promotes apoptosis in lung cells during COVID-19 infection [7]. This experiment exploited this property to design a cytopathic assay to quantitate the deleterious effects of Nspl.

A synthetic gene encoding Nspl was constructed using sequences obtained from the original SARS-CoV-2 strain [14]. Capped mRNA was transcribed from the Nspl synthetic gene for expression in cultured cells. mRNA transfection was used to transiently express Nspl in cultured adherent cells, in order to simulate the conditions of viral infection and to ensure rapid expression of Nspl in the majority of cells. The assay was conducted in H1299, a lung-derived adenocarcinoma cell line previously used in COVID-19 research [7, 15].

Using GFP as a marker, >95% of H1299 cells are routinely transfected using the mRNA lipofection method.

Cell death is readily apparent in phase contrast images of HI 299 cells 1 day after transfection with Nspl mRNA (FIG. 2A). 60-70% of the cells remain adhered to the surface of the plate (FIG. 2B), indicating that 30-40% of cells die within a day after Nspl expression. Determination of metabolic viability using the stain, calcein-AM [16], which is a measure of intracellular esterase, revealed that overall metabolism declined to 60-70% with Nspl expression (FIG. 2C). Nspl -transfected cells also displayed a significant decline in mitochondrial membrane integrity, an early marker for apoptosis, to about 50-60% (FIG.

2D). Thus, three independent measures of cell viability are negatively affected by the expression of Nspl.

To develop a quantitative measure of Nspl action, we sought to consolidate the independent measurements of cell viability mentioned above. While each independent measurement (cell adherence, metabolism, and mitochondrial membrane integrity) was significantly reduced in Nspl -transfected cells (Fig. lb-d), the magnitude of the reduction in each case was too variable to permit confident identification of Nspl inhibitors using a single measurement. It is likely that cell death is gradual and proceeds through stages once the cell’s translational apparatus is subverted. Indeed, Nspl expression led to greater cell death when allowed to proceed for 48 or 72 hours [7]; however, a longer time in cell culture would increase the assay time and introduce confounding variables (i.e. cell growth) into the procedure.

The three measurements of cell health are quantitated by fluorescent dyes with distinct excitation/emission spectra, permitting the simultaneous capture of multiplexed data (Fig. lb-e). Images of transfected cultured cells reveal that the 3 independent measures of cell health are not uniform throughout the population (FIGS. 2B-2E). Thus, combining the quantities should reduce the variability. Accordingly, this experiment defined a measure that incorporates all three quantities, which was termed the “Viability Index”. The Viability Index is the product of all three measurements, normalized to 100 for healthy, non- transfected cells. As shown in FIG. 2E, the Viability Index shows a robust difference between Nspl -transfected cells and healthy non-transfected cells, with minimal quantitative variability.

Functional Sites within Nspl. The 2D secondary structure (FIG. 3) and 3D crystal structure [17, 18] of Nspl from SARS-CoV-2 have been determined. Nspl is 180 amino acids long and folds into an N-terminal globular domain that contains 7 beta sheets (residues 1-120), connected by an unstructured linker to a helix-loop-helix region in the C-terminal domain (residues 121-180).

The globular N-domain contains an RNA groove that accommodates the 5’UTR of viral RNAs [9]. The RNA groove is created by juxtaposition of the first and last beta sheet of this region [9] (Fig. 2), and mutations within the groove almost always diminish the action of Nspl [19], strongly suggesting that the RNA-binding groove in the N-domain is a functional site.

The C-terminal helix-loop-helix domain fits into the RNA tunnel of ribosomes, thereby blocking host cell translation [8]. Mutations affecting this domain also attenuate the activity of Nspl [19, 20]. This region has been termed the “ribosome gatekeeper” because it binds to ribosomes and promotes translation of viral mRNA [13].

Thus, at least two functional sites are defined by mutational analysis within Nspl: the RNA groove in the N-domain and the C-terminal helix-loop-helix. Both sites are potential targets for drug development. The Viability Index Enables Quantitative Evaluation of Nspl Context and Mutations. To validate the utility of the Viability Index as a quantitative measure of Nspl activity, this experiment measured the Viability Index of Nspl mRNA flanked by different untranslated regions, and Nspl mRNA containing different point mutations.

The context of the Nspl coding sequence impacts its toxicity. During infection, Nspl is transcribed from mRNA consisting of the coding region flanked by the 5’UTR (untranslated region) and 3’UTR of the SARS-CoV-2 genomic RNA [21]. These UTRs are present in all viral mRNAs [21]. Nspl mRNA flanked by viral UTRs had greater toxicity compared to Nspl in which the UTRs are replaced with those corresponding to the human alpha- globin gene (Fig. 2a). This is consistent with the finding that Nspl binds to viral 5’UTRs and enhances the translation of the coding sequence [9]. Through another mechanism that is not well understood, Nspl also causes the degradation of host cell mRNAs through non-recognition of the 5’UTR [22, 23]. This likely explains why Nspl flanked by globin UTRs is less toxic that Nspl flanked by viral UTRs.

Point mutations within the Nspl coding region had either no effect, loss-of- function, or gain-of- function. The relevant mutations are mapped to the 2D structure of Nspl (FIG. 3).

Mutation A (L21M) is an inadvertent mutation created outside of the RNA groove and had no apparent effect on Nspl activity as measured by the Viability Index (FIG. 4). Mutation B (D33R) is an established gain-of-function mutation that was previously shown to potently block host cell mRNA translation, consequently inhibiting interferon production by the SARS-CoV Nspl [19]. The 3D model of Nspl indicates that D33 lies in close proximity to the RNA groove and may increase the binding affinity of the viral 5’UTR for this pocket. This mutation also led to a significant reduction of the Viability Index compared to wild-type Nspl.

C (L123A/R124E) and D (N128S/K129E) are neighboring mutations located within the RNA groove (FIG. 3). D (N128S/K129E) is a well-characterized null mutation that blocks Nspl’s ability to suppress interferon activity in several studies [7, 8, 19]. By contrast, the neighboring mutation had the opposite effect: a gain-of-function that increases Nspl toxicity. The results suggest that the RNA groove is a functional site, in which mutations can lead to potent and sometimes diametrically opposite effects on the action of Nspl.

Mutation E (K164A) is located in the C-terminal domain (FIG. 3) and was previously reported to abolish the ability of Nspl to suppress host cell defenses [20]. The function of the C-domain is to block the RNA tunnel of ribosomes [8, 11, 13]. K164A also led to a significant reduction of the Viability Index compared to wild-type Nspl (FIG. 4). Thus, mutations define an essential role for this domain despite its small size (80 residues).

Further controls indicate that the conditions for introducing RNA into HI 299 cells had effects on the Viability Index. Lipofectamine and UTR sequences both reduced the Viability Index. We therefore define Efficacy as the ability of a compound to reverse the effects of Nspl to the level observed in the absence of Nspl under the same conditions (FIG. 4). Using this as a scale, a compound simulating the well-characterized null mutations D (N128S/K129E) and E (K164A) would have Efficacies of 60% and 54% respectively.

The assay for Nspl activity was designed to simulate the early phase of COVID-19 infection in lung cells. Previous cell culture experiments utilize an MOI of 0-3, that is, up to 3 virions per adherent cell [24, 25]. It is estimated that during infection, about 10³ infectious virions are eventually generated per cell [26]. By comparison, we calculate the number of Nspl mRNA molecules introduced into each cell is about 5 x 10⁶ copies, which is several orders of magnitude greater than the number of Nspl transcripts introduced per cell in live viral studies. This excessive Nspl expression accelerates H1299 cell death in this assay, but also ensures a stringent screen for potential Nspl inhibitors.

Virtual Screening for Inhibitors of Nspl. To experimentally evaluate a manageable number of candidate inhibitors using the Viability Index, candidates were stratified by virtual screening of compound libraries using previously determined 3-dimensional structures of Nspl. The two functional sites within Nspl (described above) were the focus of this in silico screen: the RNA groove in the N-domain and the C-terminal alpha- loop-helix. Two crystal structures for the N-domain, 7k7p [17] and 7k7n [18], as well as three structures for the C- domain: 6zlw [8], 6zok [11], and 7k5i [12].

Two established algorithms were used to stratify compound libraries: Internal Coordinate Mechanics (ICM) [27] and AutoDock Vina [28]. ICM stratifies compounds using parameters that assume both the ligand and protein receptor are flexible. AutoDock Vina determines the theoretical binding affinity of compounds but assumes the 3D structure of the protein receptor is fixed [28]. Data from both types of calculations differ, but results from both were used to guide subsequent experimental assays.

ICM was used to screen the DrugBank database [29], focusing on the RNA groove region represented in the crystal structure, 7k7p [17]. Due to the small size of the C-domain, it was not possible to use ICM to screen DrugBank for potential inhibitors. Autodock Vina was used to virtually screen publicly available compound databases: FDA-approved and World- approved drugs in the ZINC15 database [30], eDrug-3D [31], and selected compounds from PubChem [32]. Almost all the compounds screened are also contained within DrugBank. Autodock Vina was applied to compound interactions with both the RNA groove in the N-domain and the helix-loop-helix region in the C-domain to stratify potential inhibitors.

Due to the urgent need to identify potential therapeutics rapidly, only compounds that are readily available with documented human data, and with a theoretical binding affinity exceeding a specified threshold, were used in subsequent Nspl assays (Table 7). About 12,000 compounds in the DrugBank database were screened by ICM and stratified by ICM score. Readily available compounds with an ICM score <-22 (bolded) were selected for experimental testing. About 6,500 compounds were screened by AutoDock Vina as described in Methods. Readily available compounds with a binding score <-7.2 (bolded) were selected for experimental testing. Compounds identified from previously reported screens [9, 33, 34] are listed with both published scores and scores derived from this study (Table 7). Commonly used compounds listed in the "other" category have ICM or Vina scores in a range suggesting that they do not interact with Nspl, and were used as negative controls (Table 7). Footnotes indicate compounds with issues that may preclude their development as a drug (Table 7).

Table 7. Compounds Selected by Virtual Screening for Evaluation in Nspl Assays

Selected Using ICM

High Affinity for the C-domain predominantly

Previously Investigated [9, 33, 34, 55]

Other

¹ Cyclo(L-His-L-Pro) is a natural compound already produced in the body, which may preclude its use as a drug. 2 Flufenoxuron is an insecticide and toxic, which may preclude its use as a drug.

³ Beta-Carotene is a food product, which creates obstacles to accurate dosing. ⁴ Milbemycin oxime is a veterinary antiparasitic and toxic, which may preclude its use as a drug.

⁵ Tirilazad is an investigational drug for strokes that failed Phase 3 trials and is not readily available for clinical use.

⁶ Golvatinib is an investigational drug that is not readily available for clinical use.

⁷ Glycyrrhizic acid is used in flavorings and found in licorice; as a food product there will be obstacles to dosing.

Individual Compounds Partially Reverse Nspl Toxicity. Compounds were serially diluted and applied to Nspl -transfected H1299 cells, and the Viability Index and Efficacy calculated. In all cases, the maximum Efficacy of the drug (Emax) rarely exceeded 20% and multiple measurements were obtained over a range of concentrations. Due to the low value of Emax, the EC50 could not be reliably calculated, so the EC 100 (concentration at which the maximum efficacy was observed) was used instead. The half-maximal cytotoxic concentration (CC50) was also determined using the Viability Index over a higher range of drug concentrations. The Safety Index was then calculated as the ratio of CC50/EC100. These data are shown in Table 8.

None of the compounds tested displayed a robust ability to reverse the toxic effects of Nspl. Due to the generally low Efficacy shown by most compounds, high variability was observed in calculations of Efficacy as shown by %CVmean values. However, selected compounds may have synergistic inhibitory effects on Nspl. Thus, compounds with a high Emax, low %CVmean, low EC 100, and a high Safety Index were considered for further investigation (Table 8). Compounds were serially diluted in DMEM-N2 and applied to Nspl - transfected HI 299 cells in 96-well plates as described in Methods. The maximum Efficacy (Emax) and concentration at which Emax was observed (EC 100) were determined over replicate experiments (N) as indicated (Table 8). The half-maximal cytotoxic concentration (CC50) of each compound was also determined using the Viability Index (Table 8). The Safety Index is defined as the ratio of CC50 over EC 100. Bolded values were determined under serum-free conditions (i.e. DMEM-N2), while all other measurements were determined in cells incubated with fetal calf serum (Table 8).

It is noteworthy that some of the candidates selected for this analysis were identified in previous in silico work, and have reported affinities that were much greater than those calculated here (Table 7). Previously investigated candidates [9, 33, 34] were docked to a simulated 3D structure of SARS-CoV-2 Nspl before the experimentally derived 3D structure was available, which may explain why the reported theoretical binding affinities were high. Despite the appeal of high theoretical binding affinities to Nspl, none of the most promising candidates identified by others or by our studies could reverse the toxic effects of Nspl in a meaningful fashion.

Table 8. Viability Indices of Selected Compounds

High Affinity for the N-domain

High Affinity for the C-domain predominantly

Previously Investigated

Other

Synergistic Nspl-inhibitory Interactions among Compounds. Two potentially functional sites within Nspl were used to screen for potential inhibitors of Nspl: the N- terminal RNA groove and the helix-loop-helix C-terminal region. Most of the compounds that are thought to bind to the N-terminal RNA groove also have high binding affinities for the C-terminal region (Table 7). However, synergy may exist between compounds that bind to either site preferentially . In addition, the RNA groove can accommodate several compounds, raising the possibility of synergistic binding to this region.

Compounds from the original list (Table 7) were selected for synergistic studies (Table 8). Preferred compounds had an Emax with a low %CVmean, an EC 100 in the low micromolar or sub-micromolar range, and a Safety Index >5. Drug combinations containing serial dilutions of each compound were applied to Nspl -transfected cells in a 2D matrix on 96-well plates. The efficacy of each combination was determined and data visualized using the online tool, SynergyFinder [35]. To quantify synergistic interactions, the ZIP scoring method was used [36].

Due to the need to progressively acquire greater numbers of data points to determine synergy as the number of compounds increases, only the first significant synergistic interactions that are of clinical significance are reported at this time. The determination of synergy among N compounds requires at least (NxN)/2 dual combinations. The analysis of each combination requires the acquisition of M² data points, where M is the number of serial dilutions. Initially, this experiment examined potential interactions among compounds that are thought to bind with high affinity to the N-terminal RNA groove. Cursory analyses of combinations that involved Olsalazine, Eravacycline, Dihydroergotamine, Montelukast, Ponatinib, Imatinib, Venetoclax, Nilotinib, and Golvatinib revealed weak or non-existent synergistic or additive interactions, though the analyses were not exhaustive. One compound, Montelukast, showed a broad tendency to enhance Efficacy in multiple cases (FIGS. 8A-8C, FIGS. 9A-9C). Montelukast+Ponatinib was among the first drug combinations identified that consistently displayed higher Efficacy than either drug alone, although the effect was primarily additive (FIG. 8A). Another compound that consistently raised Efficacy in a synergistic pattern was Tirilazad, which was reported to bind tightly to the RNA groove in previous screens [9, 33]. Tirilazad combined with either Montelukast (FIG. 8B) or Ponatinib (FIG. 8C) substantially raised Efficacy, but the concentration of Tirilazad (1 to 5 mM), its limited oral bioavailability, and its status as an investigational drug are obstacles to its further clinical development.

The low Efficacies observed using pairs of compounds prompted us to consider adding a third drug to Montelukast+Ponatinib (fixed at a molar ratio of 10:1). Indeed, adding Conivaptan (FIG. 9A) or Tirilazad (FIG. 9B) substantially raised Efficacy. In the latter case, the highest Efficacies ranged from 45-71%, suggesting it is possible to find a drug combination that reverses Nspl toxicity to the same extent as a null mutation in the gene itself.

This experiment next asked if synergy exists between compounds predominantly targeting the C-terminal domain and compounds targeting the N-terminal RNA groove (Table 7, Table 8), many of which also target the C-domain. This experiment first tested combinations with Pazopanib, which had the highest theoretical affinity for the helix-loop- helix region (Table 7). Significant synergy was observed between Pazopanib and the Montelukast+Ponatinib combination (fixed at a molar ratio of 10:1) (FIG. 9C). However, the concentration of Pazopanib required to attain Efficacies mimicking the effect of a null mutation was about 80 mM, precluding clinical use (FIG. 9C).

This experiment next tested combinations with Rilpivirine, which had the next highest theoretical binding affinity for the C-terminal helix-loop-helix region (Table 7). Significant synergy was observed between Ponatinib and Rilpivirine, well within concentrations that would be used clinically and over a broad concentration of each compound (FIG. 5A). Since the addition of Montelukast improved Efficacy in several experiments involving drug combinations (FIGS. 8A-8C, FIGS. 9A-9C), this drug was added to the Ponatinib+Rilpivirine combination (fixed at a molar ratio of 2.5:1). Substantial synergy was observed over a broad concentration of each drug (FIG. 5B), with further enhancement of Efficacy. Under optimal conditions, the Efficacy of the Montelukast+Ponatinib+Rilpivirine combination ranged from 47 to 64% (FIG. 5B), which is similar to the effects of a null mutation in the Nspl gene (FIG. 4). These data suggest that a Montelukast+Ponatinib+Rilpivirine drug combination reverses the toxic effects of Nspl at concentrations that are attainable clinically.

Defining the Montelukast+Ponatinib+Rilpivirine Interaction. The Efficacies of individual compounds, pairs of compounds, and triple combinations were examined systematically in Nspl -transfected H1299 cells over several replicate experiments using concentrations that are attainable clinically (FIG. 6). Under these conditions, individual compounds displayed Efficacies <20%, and various pairs showed marginal improvement. A one-way ANOVA was used to compare the Efficacies of the 15 drug combinations depicted in FIG. 6. The analyses revealed a statistically significant difference between the means of at least two drug combinations (Fu_{, 243}=1.985, p=0.02). It is obvious that only the last drug combination (M2+P+R) displayed substantial Efficacy compared to the others (FIG. 6). Eliminating M2+P+R from the analyses rendered the one-way ANOVA not significant ( B_{, 233}=1.274, p= 0.23). These analyses suggest that single drugs or pairs of drugs are unlikely to possess meaningful Efficacy. Moreover, among the combinations that utilized three drugs, only one combination showed effect.

The data from FIG. 6 suggests that an optimal proportion of Montelukast+Ponatinib+Rilpivirine (abbreviated MPR) is 1.25: 0.10: 0.05. This triple combination was applied to Nsp-1 transfected H1299 cells over a range of concentrations (FIG. 7A). A typical dose-response curve is produced with serial dilutions of MPR, and the effective concentrations are well separated from toxic concentrations (FIG. 7A). The optimal concentration of MPR is actually 0.5x (0.625 mM Montelukast, 0.05 pM Ponatinib, and 0.025 pM Rilpivirine), resulting in a mean Efficacy of 59%. The %CVmean of this combination is 12.5%, which is a lower number than the %CVmean of Efficacy from single drugs. The low %CVmean indicates a reliable number.

The CC50 of MPR was 8X, providing a safety index of 16 (FIG. 7A).

To further understand the mechanism by which the MPR drug combination may be acting, lxMPR was applied to HI 299 cells transfected with the Nspl point mutations, Mut A, B and C (FIG. 7B). In all cases, MPR treatment of H1299 cells transfected with these Nspl mutations failed to rescue these cells from toxicity. However, it is notable that lxMPR raised Efficacy in the gain- of -function point mutant B (D33R), which lies outside of the RNA groove. By contrast, lxMPRdid not raise Efficacy to a statistically significant level with mutations A and C, which are located adjacent to or within the RNA groove. These data suggest that the potential mechanism of MPR is to bind to the RNA groove of Nspl. Lastly, the Efficacy of 0.5xMPR in treating WT-Nspl -transfected H1299 cells is similar to the effect of the established null mutations, Mut D and E, in Nspl (FIG. 7B). Given the importance of Nspl in the early pathogenesis of COVID-19, these data support the investigation of this repurposed drug combination in clinical trials for the treatment of this disease.

Discussion

Nspl is a promising molecular target because of its critical role during early SARS- CoV-2 pathogenesis. In SARS-CoV-2 [8, 11, 13], SARS-CoV [37], and MERS [38], Nspl shuts down host protein synthesis but ribosomes remain permissive for viral protein synthesis. Experimental deletion of Nspl in a highly virulent beta-coronavirus, murine hepatitis virus, converts the virus from a lethal pathogen to a nonlethal one [39]. Moreover, naturally occurring variants of SARS-CoV-2 containing deletions in the helix-loop-helix region of the C-domain of Nspl have been identified in China [40]. This variant renders the virus less severe clinically, with lower viral loads and smaller plaque size [40]. These observations suggest that targeting Nspl of SARS-CoV-2 could mitigate the severe clinical sequelae of COVID-19 infection.

The mechanism by which SARS-CoV-2 induces apoptosis in lung cells has not been fully elucidated, but targeting this process can attenuate disease severity [41]. Among the most prominent host protein changes in SARS-CoV-2 infected alveolar epithelial cells are those affecting eukaryotic translation elongation and viral mRNA translation [42], consistent with Nspl’s primary action of subverting host protein synthesis [8, 11, 13]. Accordingly, Nspl blocks the production of interferon I [43-45] and interferon III [22], key players in the innate defense against viral infection. Mutations affecting the RNA groove or the helix-loop- helix region of Nspl reverse the interferon-blocking actions of Nspl [19]. Thus, Nspl contributes to the apoptotic process by inhibiting host protein translation and interferon action. The Nspl assay described here is essentially a cytopathic assay that simulates the expression of Nspl mRNA during infection.

Since Nspl functions only when introduced inside cells, its actions are not dependent on viral tropism. Indeed, we observed similar actions of Nspl on HeLa cells (data not shown), a cell line that does not support SARS-CoV-2 replication [46]. SARS-CoV-2 infection can lead to multi-organ damage, and Nspl is a likely contender in this pathogenesis. The design of the assay described herein can be adapted to investigate the role of Nspl in other tissues.

Virtual screening of compound libraries is useful for ranking the likelihood that a chemical interacts with a specified target, saving time and expense in drug screening. An estimated 5-12% of compounds from a “hit” list eventually turn out to have activity [47, 48]. However, Nspl is not homologous to known mammalian proteins [49], and algorithms may not be optimized for identifying potential “hits”. To increase our chances of finding “hits”, we used two different, well-regarded algorithms to compile an initial list of prospective Nspl inhibitors, focusing on readily available compounds that could be repurposed. In addition, compounds identified by other investigators [9, 33, 34] were examined. However, experimentally, none of the compounds alone were capable of substantially inhibiting Nspl (i.e. Efficacy >20%).

It was reasoned that synergistic interactions among compounds could promote their ability to inhibit Nspl. For instance, compounds that preferentially target different functional domains - such as the N-terminal RNA groove and C-terminal helix-loop-helix - may work synergistically together. However, identifying the relevant synergistic interactions is labor- intensive because the number of potential drug pairs multiplies as more drugs are tested, and synergy can only be determined after testing serial dilutions of each drug together in a 2x2 matrix.

Here, significant synergy with Montelukast, Ponatinib, and Rilpivirine, which together, abolishes Nspl toxicity in our cell-based assay is reported. The combination is clinically meaningful for the following reasons. All three drugs are FDA-approved and can be administered orally once a day. For synergistic inhibition, the effective concentration ranges of Montelukast, Ponatinib, and Rilpivirine are 625-1,250 nM, 50-125 nM, and 30-60 nM, respectively. After a standard dose of 10 mg of Montelukast, peak plasma concentrations ranged from 495 ng/mF (810 nM) to 603 ng/mF (990 nM) [50]. The steady state plasma concentration of Ponatinib in patients taking the standard oral dose of 15 mg was 43.6 ng/mF or 80 nM [51]. The standard oral dose of Rilpivirine is 25 mg daily, resulting in plasma levels of 30-70 nM [52]. There are no known adverse interactions among the three drugs, though the doses may require reduction due to common paths of elimination according to information on DrugBank [29]. Thus, all three drugs can be given orally and are expected to attain plasma concentrations that in our preclinical study, inhibits Nspl to the same extent as a null mutation. In addition, Montelukast, Ponatinib, and Rilpivirine have been suggested as treatments for COVID-19 in other studies. In silico docking studies suggest that Montelukast binds to the SARS-CoV-2 proteins Mpro [53], RdRp [53], and 3CL [54]. In Vero6 cells, Montelukast inhibited SARS-CoV-2 replication, albeit at a high IC50 of 18.82 mM [55]. In addition, Montelukast inhibits the action of inflammatory cytokines, suggesting it could tame cytokine storms during severe COVID-19 infection [56]. No prospective trials of Montelukast have been performed, but a retrospective study suggests that COVID- 19- positive patients taking this drug (10 mg daily) had fewer deleterious symptoms compared to patients not taking the drug [57]. Recent in silico docking studies also suggest that Ponatinib binds to host factors that influence infection [58, 59], and that Rilpivirine can bind to Mpro, PLpro, Spro, ACE2, and RdRp [60].

This initial study suggests that detection of a single repurposed compound to inhibit Nspl to a clinically meaningful degree may be challenging. When the search strategy was expanded to include 2-3 drugs co-administered together, a number of potential combinations were identified. Specifically, a mixture of Montelukast, Ponatinib, and Rilpivirine was shown to inhibit Nspl toxicity in cultured lung cells at concentrations that are clinically attainable with oral administration. Further studies will explore the utility of this finding by prospective clinical trials, as well as to identify other meaningful drug combinations.

Materials and Methods

Cell Lines, Cell Culture, and Transfection. Unless otherwise specified, all reagents were purchased from ThermoFisher Scientific. H1299 cells were obtained from the American Type Culture Collection (ATCC) and maintained in DMEM supplemented with 10% fetal calf serum (FCS) and 100 U/mF penicillin- streptomycin. Cells were grown in an incubator that maintained the temperature at 37°C, air humidity at 95%, and CO2 concentration at 5%, and passaged every 3-4 days with PBS and 0.05% Trypsin-EDTA. To prepare cells for transfection, they were plated at a density that would be predicted to reach 50% the next day in a volume of 70 pF per well on 96-well plates.

RNA transfections were carried out in 96-well plates with H1299 cells plated at 50% density. The equivalent of 0.05-0.2 pF of Fipofectamine™ MessengerMax™ was first diluted in Opti-MEM™ in a volume of 5 pF for 5 min, and then added to 50-200 ng RNA (diluted in Opti-MEM to a volume of 5 pF) in a total volume of 10 pF, and incubated for an additional 10 minutes at room temperature. The mixture was then diluted to a volume of 50 pL with Opti-MEM and added to H1299 cells growing in a single well. This would be scaled depending on the number of wells to be transfected per plate.

Nspl Assay. H1299 cells growing on 96-well plates were transfected with Nspl mRNA as described above and incubated with the lipofectamine-RNA mix for 3 hours. Little difference in gene expression was observed between 2 to 4 hours of incubation with the lipofectamine-RNA mix. Media was then replaced by addition of 80 pL DMEM-10% FCS- lOOU/mL Pen-Strep or 80 pL serum- free DMEM-1% N2 supplement- lOOU/mL Pen-Strep.

HI 299 cells were then returned in the CO2 incubator overnight.

Approximately 20 hours after replacement of the lipofectamine-RNA mix from H1299 cells, the media was again replaced with 100 pL of a mixture containing compatible fluorophores diluted in FluoroBrite™: 1 mM Hoechst 33342, 1 mM Calcein-AM (Cayman Chemical Company), and 20 nM Tetramethylrhodamine, ethyl ester (TMRE, Cayman Chemical Company). Cells were placed in the CO2 incubator for 1 hour and the media was changed to 50 pL of Fluorobrite or PBS alone.

Fluorescence from 96-well plates was measured using a Spectramax Microplate Gemini XPS reader with the following parameters: Hoechst 33342 staining — excitation-355 nm; emission-460 nm; calcein-AM — excitation-485 nm; emission-520 nm; TMRE — excitation- 544 nm; emission-590 nm. After normalizing values for each fluorescence reading to non-transfected controls, the product of all three readings represents the “Viability Index”.

Efficacy, ECIOO, CC50. Efficacy is quantified as the degree to which a drug or drug combination reverses all toxic effects of Nspl as determined by the Viability Index. The quantity is value between 0 and 100, where 0 represents no effect and 100 is complete reversal. The ECIOO is the concentration of drug where maximum Efficacy is observed. The CC50 is the half-maximal concentration of drug that produces death in H1299 cells. The half-maximal concentration was determined from dose response data fitted to a sigmoidal curve (www.aatbio.com/tools).

Ligand Docking and Screening. The ICM Pocket Finder method [61] in ICM-Pro v3.9-lc (Molsoft, LLC) was used to define a dmggable pocket within the Nspl crystal structure, 7k7p [17]. The pocket is essentially identical to the RNA groove that accommodates the 5’UTR of viral mRNAs [9]. The ICM-VLS method [62, 63] (MolSoft LLC) was used to dock, score and rank chemicals from the Drugbank database [29] that are predicted bind to this pocket.

PyRx [64] is a user interface that assimilates Autodock Vina [28] with other programs, and was used to screen the compound libraries ZINC 15 [30] and eDrug-3D [31]. The molecular targets were the RNA groove pocket within the structures, 7k7p [17] and 7k7n [18], and the loop-helix-loop regions of the C-domain (structures 6zlw [8], 6zok [11], and 7k5i [12]).

Compounds. All compounds were obtained from the Cayman Chemical Company with some exceptions. Eravacycline was obtained from MedChemExpress. Flufenoxuron, kanamycin, tetracycline, ampicillin, haloperidol, and risperidone were purchased from the Sigma-Aldrich.

All compounds were dissolved in the recommended solvent (DMSO, DMF, alcohol, or water). Compounds were diluted in serum-free DMEM-N2 to the desired concentrations before addition to media.

Identification of Synergistic Interactions. H1299 cells were plates on 96-well plates and transfected with Nspl mRNA as described above. Lipofectamine-RNA mixtures were replaced with 80 pL serum-free DMEM-1% N2 supplement- lOOU/mL Pen-Strep. 20 pL of serial dilutions of each drug (diluted in DMEM-1% N2 supplement- lOOU/mL Pen- Strep) were added in a matrix configuration, and the cells were incubated for another 20 hours in the tissue culture incubator. Plates were then subjected to the multiplexed fluorescent assay described above, and the Variability Index and Efficacy over a range of drug concentrations were determined.

Efficacy measurements from a matrix of drug concentrations were evaluated using Synergy Finder 2.0 [35], an online visualization tool to identify synergistic interactions. The ZIP scoring method was used to calculate synergies [36].

References

1. Zhou, P., X.L. Yang, X.G. Wang, B. Hu, L. Zhang, W. Zhang, H.R. Si, Y. Zhu, B. Li, C.L. Huang, H.D. Chen, J. Chen, Y. Luo, H. Guo, R.D. Jiang, M.Q. Liu, Y. Chen, X.R. Shen, X. Wang, X.S. Zheng, K. Zhao, Q.J. Chen, F. Deng, L.L. Liu, B. Yan, F.X. Zhan, Y.Y. Wang, G.F. Xiao, and Z.L. Shi, A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature, 2020. 579(7798): p. 270-273.

2. Schubert, K., E.D. Karousis, A. Jomaa, A. Scaiola, B. Echeverria, L.A. Gurzeler, M.

Leibundgut, V. Thiel, O. Muhlemann, and N. Ban, SARS-CoV-2 Nspl binds the ribosomal mRNA channel to inhibit translation. Nat Struct Mol Biol, 2020. 27(10): p. 959-966.

3. Thoms, M., R. Buschauer, M. Ameismeier, L. Koepke, T. Denk, M. Hirschenberger, H.

Kratzat, M. Hayn, T. Mackens-Kiani, J. Cheng, J.H. Straub, C.M. Sturzel, T. Frohlich,

O. Berninghausen, T. Becker, F. Kirchhoff, K.M.J. Sparrer, and R. Beckmann, Structural basis for translational shutdown and immune evasion by the Nspl protein of SARS-CoV- 2. Science, 2020. 369(6508): p. 1249-1255.

4. Tidu, A., A. Janvier, L. Schaeffer, P. Sosnowski, L. Kuhn, P. Hammann, E. Westhof, G.

Eriani, and F. Martin, The viral protein NSP1 acts as a ribosome gatekeeper for shutting down host translation and fostering SARS-CoV-2 translation. RNA, 2020.

5. Yuan, S., L. Peng, J.J. Park, Y. Hu, S.C. Devarkar, M.B. Dong, Q. Shen, S. Wu, S. Chen,

I.B. Lomakin, and Y. Xiong, Nonstructural Protein 1 of SARS-CoV-2 Is a Potent Pathogenicity Factor Redirecting Host Protein Synthesis Machinery toward Viral RNA. Mol Cell, 2020.

6. Zust, R., L. Cervantes-Barragan, T. Kuri, G. Blakqori, F. Weber, B. Ludewig, and V.

Thiel, Coronavirus nonstructural protein 1 is a major pathogenicity factor: implications for the rational design of coronavirus vaccines. PLoS Pathog, 2007. 3(8): p. el09.

7. Clark, L.K., T.J. Green, and C.M. Petit, Structure of Nonstructural Protein 1 from SARS-

CoV-2. J Virol, 2021. 95(4).

8. Semper, C., N. Watanabe, and A. Savchenko, Structural characterization of nonstructural protein 1 from SARS-CoV-2. iScience, 2021. 24(1): p. 101903.

9. Vankadari, N., N.N. Jeyasankar, and W.J. Lopes, Structure of the SARS-CoV-2 Nspl/5'-

Untranslated Region Complex and Implications for Potential Therapeutic Targets, a Vaccine, and Virulence. J Phys Chem Lett, 2020. 11(22): p. 9659-9668.

10. Jauregui, A.R., D. Savalia, V.K. Lowry, C.M. Farrell, and M.G. Wathelet, Identification of residues of SARS-CoV nspl that differentially affect inhibition of gene expression and antiviral signaling. PLoS One, 2013. 8(4): p. e62416.

11. Shen, Z., G. Zhang, Y. Yang, M. Li, S. Yang, and G. Peng, Lysine 164 is critical for SARS-CoV-2 Nspl inhibition of host gene expression. J Gen Virol, 2020. 12. Shi, M., L. Wang, P. Fontana, S. Vora, Y. Zhang, T.M. Fu, J. Lieberman, and H. Wu, SARS-CoV-2 Nspl suppresses host but not viral translation through a bipartite mechanism. bioRxiv, 2020.

13. Abagyan, R., M. Totrov, and D. Kuznetsov, ICM — A new method for protein modeling and design: Applications to docking and structure prediction from the distorted native conformation. Journal of Computational Chemistry, 1994. 15: p. 488-506.

14. Trott, O. and A.J. Olson, AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem, 2010. 31(2): p. 455-61.

15. Wishart, D.S., Y.D. Feunang, A.C. Guo, E.J. Lo, A. Marcu, J.R. Grant, T. Sajed, D. Johnson, C. Li, Z. Sayeeda, N. Assempour, I. Iynkkaran, Y. Liu, A. Maciejewski, N. Gale, A. Wilson, L. Chin, R. Cummings, D. Le, A. Pon, C. Knox, and M. Wilson, DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res, 2018. 46(D1): p. D1074-D1082.

16. Sterling, T. and J.J. Irwin, ZINC 15— Ligand Discovery for Everyone. J Chem Inf Model, 2015. 55(11): p. 2324-37.

17. Pihan, E., L. Colliandre, J.F. Guichou, and D. Douguet, e-Drug3D: 3D structure collections dedicated to drug repurposing and fragment-based drug design. Bioinformatics, 2012. 28(11): p. 1540-1.

18. Adeshina, Y.O., E.J. Deeds, and J. Karanicolas, Machine learning classification can reduce false positives in structure-based virtual screening. Proc Natl Acad Sci U S A, 2020. 117(31): p. 18477-18488.

19. Jiang, Q., H. Wei, and Z. Tian, Poly I:C enhances cycloheximide-induced apoptosis of tumor cells through TLR3 pathway. BMC Cancer, 2008. 8: p. 12.

20. Dufour, F., L. Bertrand, A. Pearson, N. Grandvaux, and Y. Langelier, The ribonucleotide reductase R1 subunits of herpes simplex virus 1 and 2 protect cells against poly(I . C)- induced apoptosis. J Virol, 2011. 85(17): p. 8689-701.

21. Barber, G.N., Host defense, viruses and apoptosis. Cell Death Differ, 2001. 8(2): p. 113- 26.

22. Uggeri, J., R. Gatti, S. Belletti, R. Scandroglio, R. Corradini, B.M. Rotoli, and G. Orlandini, Calcein-AM is a detector of intracellular oxidative activity. Histochem Cell Biol, 2004. 122(5): p. 499-505. 23. Scaduto, R.C., Jr. and L.W. Grotyohann, Measurement of mitochondrial membrane potential using fluorescent rhodamine derivatives. Biophys J, 1999. 76(1 Pt 1): p. 469- 77.

Additional References

1. Wibmer, C.K., F. Ayres, T. Hermanus, M. Madzivhandila, P. Kgagudi, B. Oosthuysen, B.E. Lambson, T. de Oliveira, M. Vermeulen, K. van der Berg, T. Rossouw, M. Boswell, V. Ueckermann, S. Meiring, A. von Gottberg, C. Cohen, L. Morris, J.N. Bhiman, and P.L. Moore, SARS-CoV-2501Y.V2 escapes neutralization by South African COVID-19 donor plasma. Nat Med, 2021. 27(4): p. 622-625.

2. Tada, T., B.M. Dcosta, H. Zhou, A. Vaill, W. Kazmierski, and N.R. Landau, Decreased neutralization of SARS-CoV-2 global variants by therapeutic anti-spike protein monoclonal antibodies. bioRxiv, 2021.

3. McCallum, M., J. Bassi, A. De Marco, A. Chen, A.C. Walls, J. Di Iulio, M.A. Tortorici, M.J. Navarro, C. Silacci-Fregni, C. Saliba, K.R. Sprouse, M. Agostini, D. Pinto, K. Culap, S. Bianchi, S. Jaconi, E. Cameroni, J.E. Bowen, S.W. Tilles, M.S. Pizzuto, S.B. Guastalla,

G. Bona, A.F. Pellanda, C. Garzoni, W.C. Van Voorhis, L.E. Rosen, G. Snell, A. Telenti,

H.W. Virgin, L. Piccoli, D. Corti, and D. Veesler, SARS-CoV-2 immune evasion by the

B.1.427 /B.1.429 variant of concern. Science, 2021.

4. Wang, R., J. Chen, K. Gao, and G.W. Wei, Vaccine-escape and fast- growing mutations in the United Kingdom, the United States, Singapore, Spain, India, and other COVID-19- devastated countries. Genomics, 2021. 113(4): p. 2158-2170.

5. Weisblum, Y., F. Schmidt, F. Zhang, J. DaSilva, D. Poston, J.C. Lorenzi, F. Muecksch,

M. Rutkowska, H.H. Hoffmann, E. Michailidis, C. Gaebler, M. Agudelo, A. Cho, Z. Wang, A. Gazumyan, M. Cipolla, L. Luchsinger, C.D. Hillyer, M. Caskey, D.F. Robbiani,

C.M. Rice, M.C. Nussenzweig, T. Hatziioannou, and P.D. Bieniasz, Escape from neutralizing antibodies by SARS-CoV-2 spike protein variants. Elife, 2020. 9.

6. Levin, E.G., Y. Lustig, C. Cohen, R. Fluss, V. Indenbaum, S. Amit, R. Doolman, K.

Asraf, E. Mendelson, A. Ziv, C. Rubin, L. Freedman, Y. Kreiss, and G. Regev-Yochay, Waning Immune Humoral Response to BNT162b2 Covid-19 Vaccine over 6 Months. N Engl J Med, 2021. 7. Yuan, S., L. Peng, J.J. Park, Y. Hu, S.C. Devarkar, M.B. Dong, Q. Shen, S. Wu, S. Chen, I.B. Lomakin, and Y. Xiong, Nonstructural Protein 1 of SARS-CoV-2 Is a Potent Pathogenicity Factor Redirecting Host Protein Synthesis Machinery toward Viral RNA. Mol Cell, 2020.

8. Thoms, M., R. Buschauer, M. Ameismeier, L. Koepke, T. Denk, M. Hirschenberger, H. Kratzat, M. Hayn, T. Mackens-Kiani, J. Cheng, J.H. Straub, C.M. Sturzel, T. Frohlich, O. Beminghausen, T. Becker, F. Kirchhoff, K.M.J. Sparrer, and R. Beckmann, Structural basis for translational shutdown and immune evasion by the Nspl protein of SARS-CoV-2. Science, 2020. 369(6508): p. 1249-1255.

9. Vankadari, N., N.N. Jeyasankar, and W.J. Lopes, Structure of the SARS-CoV-2 Nspl/5'- Untranslated Region Complex and Implications for Potential Therapeutic Targets, a Vaccine, and Virulence. J Phys Chem Lett, 2020. 11(22): p. 9659-9668.

10. Zhang, K., L. Miorin, T. Makio, I. Dehghan, S. Gao, Y. Xie, H. Zhong, M. Esparza, T. Kehrer, A. Kumar, T.C. Hobman, C. Ptak, B. Gao, J.D. Minna, Z. Chen, A. Garcia-Sastre, Y. Ren, R.W. Wozniak, and B.M.A. Fontoura, Nspl protein of SARS-CoV-2 disrupts the mRNA export machinery to inhibit host gene expression. Sci Adv, 2021. 7(6).

11. Schubert, K., E.D. Karousis, A. Jomaa, A. Scaiola, B. Echeverria, L.A. Gurzeler, M. Leibundgut, V. Thiel, O. Muhlemann, and N. Ban, SARS-CoV-2 Nspl binds the ribosomal mRNA channel to inhibit translation. Nat Struct Mol Biol, 2020. 27(10): p. 959-966.

12. Shi, M., L. Wang, P. Fontana, S. Vora, Y. Zhang, T.M. Fu, J. Lieberman, and H. Wu, SARS-CoV-2 Nspl suppresses host but not viral translation through a bipartite mechanism. bioRxiv, 2020.

13. Tidu, A., A. Janvier, L. Schaeffer, P. Sosnowski, L. Kuhn, P. Hammann, E. Westhof, G. Eriani, and F. Martin, The viral protein NSP1 acts as a ribosome gatekeeper for shutting down host translation and fostering SARS-CoV-2 translation. RNA, 2020.

14. Zhou, P., X.L. Yang, X.G. Wang, B. Hu, L. Zhang, W. Zhang, H.R. Si, Y. Zhu, B. Li, C.L. Huang, H.D. Chen, J. Chen, Y. Luo, H. Guo, R.D. Jiang, M.Q. Liu, Y. Chen, X.R. Shen, X. Wang, X.S. Zheng, K. Zhao, Q.J. Chen, F. Deng, L.L. Liu, B. Yan, F.X. Zhan, Y.Y. Wang, G.F. Xiao, and Z.L. Shi, A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature, 2020. 579(7798): p. 270-273. 15. Hoffmann, M., H. Kleine-Weber, S. Schroeder, N. Kruger, T. Herrler, S. Erichsen, T.S. Schiergens, G. Herrler, N.H. Wu, A. Nitsche, M.A. Muller, C. Drosten, and S. Pohlmann, SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor. Cell, 2020. 181(2): p. 271-280 e8. 16. Uggeri, J., R. Gatti, S. Belletti, R. Scandroglio, R. Corradini, B.M. Rotoli, and G.

Orlandini, Calcein-AM is a detector of intracellular oxidative activity. Histochem Cell Biol, 2004. 122(5): p. 499-505.

17. Clark, L.K., T.J. Green, and C.M. Petit, Structure of Nonstructural Protein 1 from SARS- CoV-2. J Virol, 2021. 95(4). 18. Semper, C., N. Watanabe, and A. Savchenko, Structural characterization of nonstructural protein 1 from SARS-CoV-2. iScience, 2021. 24(1): p. 101903.

19. Jauregui, A.R., D. Savalia, V.K. Lowry, C.M. Farrell, and M.G. Wathelet, Identification of residues of SARS-CoV nspl that differentially affect inhibition of gene expression and antiviral signaling. PLoS One, 2013. 8(4): p. e62416. 20. Shen, Z., G. Zhang, Y. Yang, M. Li, S. Yang, and G. Peng, Lysine 164 is critical for

SARS-CoV-2 Nspl inhibition of host gene expression. J Gen Virol, 2020.

21. Kim, D., J.Y. Lee, J.S. Yang, J.W. Kim, V.N. Kim, and H. Chang, The Architecture of SARS-CoV-2 Transcriptome. Cell, 2020. 181(4): p. 914-921 elO.

22. Burke, J.M., L.A. St Clair, R. Perera, and R. Parker, SARS-CoV-2 infection triggers widespread host mRNA decay leading to an mRNA export block. RNA, 2021.

23. Huang, C., K.G. Lokugamage, J.M. Rozovics, K. Narayanan, B.L. Semler, and S. Makino, SARS coronavirus nspl protein induces template-dependent endonucleolytic cleavage ofmRNAs: viral mRNAs are resistant to nspl -induced RNA cleavage. PLoS Pathog, 2011. 7(12): p. el002433. 24. Chu, H., J.F. Chan, T.T. Yuen, H. Shuai, S. Yuan, Y. Wang, B. Hu, C.C. Yip, J.O.

Tsang, X. Huang, Y. Chai, D. Yang, Y. Hou, K.K. Chik, X. Zhang, A.Y. Fung, H.W. Tsoi, J.P. Cai, W.M. Chan, J.D. Ip, A.W. Chu, J. Zhou, D.C. Lung, K.H. Kok, K.K. To, O.T. Tsang, K.H. Chan, and K.Y. Yuen, Comparative tropism, replication kinetics, and cell damage profiling of SARS-CoV-2 and SARS-CoV with implications for clinical manifestations, transmissibility, and laboratory studies of COVID-19: an observational study. Lancet Microbe, 2020. 1(1): p. el4-e23.

25. Ogando, N.S., T.J. Dalebout, J.C. Zevenhoven-Dobbe, R. Limpens, Y. van der Meer, L. Caly, J. Druce, J.J.C. de Vries, M. Kikkert, M. Barcena, I. Sidorov, and E.J. Snijder, SARS-coronavirus-2 replication in Vero E6 cells: replication kinetics, rapid adaptation and cytopathology. J Gen Virol, 2020. 101(9): p. 925-940.

26. Sender, R., Y.M. Bar-On, S. Gleizer, B. Bemshtein, A. Flamholz, R. Phillips, and R. Milo, The total number and mass of SARS-CoV-2 virions. Proc Natl Acad Sci U S A,

2021. 118(25).

27. Abagyan, R., M. Totrov, and D. Kuznetsov, ICM — A new method for protein modeling and design: Applications to docking and structure prediction from the distorted native conformation. Journal of Computational Chemistry, 1994. 15: p. 488-506.

28. Trott, O. and A.J. Olson, AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem, 2010. 31(2): p. 455-61.

29. Wishart, D.S., Y.D. Feunang, A.C. Guo, E.J. Fo, A. Marcu, J.R. Grant, T. Sajed, D. Johnson, C. Fi, Z. Sayeeda, N. Assempour, I. Iynkkaran, Y. Fiu, A. Maciejewski, N. Gale, A. Wilson, F. Chin, R. Cummings, D. Fe, A. Pon, C. Knox, and M. Wilson, DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res, 2018.

46(D1): p. D1074-D1082.

30. Sterling, T. and J.J. Irwin, ZINC 15— Ligand Discovery for Everyone. J Chem Inf Model, 2015. 55(11): p. 2324-37.

31. Pihan, E., F. Colliandre, J.F. Guichou, and D. Douguet, e-Drug3D: 3D structure collections dedicated to drug repurposing and fragment-based drug design. Bioinformatics, 2012. 28(11): p. 1540-1.

32. Kim, S., J. Chen, T. Cheng, A. Gindulyte, J. He, S. He, Q. Fi, B.A. Shoemaker, P.A. Thiessen, B. Yu, F. Zaslavsky, J. Zhang, and E.E. Bolton, PubChem in 2021: new data content and improved web interfaces. Nucleic Acids Res, 2021. 49(D1): p. D1388-D1395.

33. de Fima Menezes, G. and R.A. da Silva, Identification of potential drugs against SARS- CoV-2 non- structural protein 1 (nspl ). J Biomol Struct Dyn, 2021. 39(15): p. 5657-5667. 34. Sharma, A., V. Tiwari, and R. Sowdhamini, Computational search for potential COVID- 19 drugs from FDA approved drugs and small molecules of natural origin identifies several anti-virals and plant products. J Biosci, 2020. 45.

35. Ianevski, A., A.K. Giri, and T. Aittokallio, SynergyFinder 2.0: visual analytics of multi drug combination synergies. Nucleic Acids Res, 2020. 48(W1): p. W488-W493.

36. Yadav, B., K. Wennerberg, T. Aittokallio, and J. Tang, Searching for Drug Synergy in Complex Dose-Response Landscapes Using an Interaction Potency Model. Comput Struct Biotechnol J, 2015. 13: p. 504-13.

37. Tanaka, T., W. Kamitani, M.L. DeDiego, L. Enjuanes, and Y. Matsuura, Severe acute respiratory syndrome coronavirus nspl facilitates efficient propagation in cells through a specific translational shutoff of host mRN A. J Virol, 2012. 86(20): p. 11128-37.

38. Terada, Y., K. Kawachi, Y. Matsuura, and W. Kamitani, MERS coronavirus nspl participates in an efficient propagation through a specific interaction with viral RNA. Virology, 2017. 511: p. 95-105.

39. Zust, R., L. Cervantes-Barragan, T. Kuri, G. Blakqori, F. Weber, B. Ludewig, and V. Thiel, Coronavirus non-structural protein 1 is a major pathogenicity factor: implications for the rational design of coronavirus vaccines. PLoS Pathog, 2007. 3(8): p. el09.

40. Lin, J.W., C. Tang, H.C. Wei, B. Du, C. Chen, M. Wang, Y. Zhou, M.X. Yu, L. Cheng,

S. Kuivanen, N.S. Ogando, L. Levanov, Y. Zhao, C.L. Li, R. Zhou, Z. Li, Y. Zhang, K. Sun, C. Wang, L. Chen, X. Xiao, X. Zheng, S.S. Chen, Z. Zhou, R. Yang, D. Zhang, M. Xu, J. Song, D. Wang, Y. Li, S. Lei, W. Zeng, Q. Yang, P. He, Y. Zhang, L. Zhou, L. Cao, F. Luo, H. Liu, L. Wang, F. Ye, M. Zhang, M. Li, W. Fan, X. Li, K. Li, B. Ke, J. Xu, H. Yang, S. He, M. Pan, Y. Yan, Y. Zha, L. Jiang, C. Yu, Y. Liu, Z. Xu, Q. Li, Y. Jiang, J. Sun, W. Hong, H. Wei, G. Lu, O. Vapalahti, Y. Luo, Y. Wei, T. Connor, W. Tan, E.J. Snijder, T. Smura, W. Li, J. Geng, B. Ying, and L. Chen, Genomic monitoring ofSARS- CoV-2 uncovers an Nspl deletion variant that modulates type I interferon response. Cell Host Microbe, 2021. 29(3): p. 489-502 e8.

41. Chu, H., H. Shuai, Y. Hou, X. Zhang, L. Wen, X. Huang, B. Hu, D. Yang, Y. Wang, C. Yoon, B.H. Wong, C. Li, X. Zhao, V.K. Poon, J.P. Cai, K.K. Wong, M.L. Yeung, J. Zhou, R.K. Au-Yeung, S. Yuan, D.Y. Jin, K.H. Kok, S. Perlman, J.F. Chan, and K.Y. Yuen, Targeting highly pathogenic coronavirus-induced apoptosis reduces viral pathogenesis and disease severity. Sci Adv, 2021. 7(25). Hekman, R.M., A.J. Hume, R.K. Goel, K.M. Abo, J. Huang, B.C. Blum, R.B. Werder, E.L. Suder, I. Paul, S. Phanse, A. Youssef, K.D. Alysandratos, D. Padhorny, S. Ojha, A. Mora-Martin, D. Kretov, P.E.A. Ash, M. Verma, J. Zhao, J.J. Patten, C. Villacorta-Martin,

D. Bolzan, C. Perea-Resa, E. Bullitt, A. Hinds, A. Tilston-Lunel, X. Varelas, S. Farhangmehr, U. Braunschweig, J.H. Kwan, M. McComb, A. Basu, M. Saeed, V. Perissi,

E.J. Burks, M.D. Layne, J.H. Connor, R. Davey, J.X. Cheng, B.L. Wolozin, B.J.

Blencowe, S. Wuchty, S.M. Lyons, D. Kozakov, D. Cifuentes, M. Blower, D.N. Kotton, A.A. Wilson, E. Muhlberger, and A. Emili, Actionable Cytopatho genic Host Responses of Human Alveolar Type 2 Cells to SARS-CoV-2. Mol Cell, 2020. 80(6): p. 1104-1122 e9. Kumar, A., R. Ishida, T. Strilets, J. Cole, J. Lopez-Orozco, N. Fayad, A. Felix-Lopez, M. Elaish, D. Evseev, K.E. Magor, L.K. Mahal, L.P. Nagata, D.H. Evans, and T.C. Hobman, SARS-CoV-2 Nonstructural Protein 1 Inhibits the Interferon Response by Causing Depletion of Key Host Signaling Factors. J Virol, 2021. 95(13): p. e0026621. Vazquez, C., S.E. Swanson, S.G. Negatu, M. Dittmar, J. Miller, H.R. Ramage, S. Cherry, and K.A. Jurado, SARS-CoV-2 viral proteins NSP1 and NSP13 inhibit interferon activation through distinct mechanisms. PLoS One, 2021. 16(6): p. e0253089. Xia, H., Z. Cao, X. Xie, X. Zhang, J.Y. Chen, H. Wang, V.D. Menachery, R. Rajsbaum, and P.Y. Shi, Evasion of Type I Interferon by SARS-CoV-2. Cell Rep, 2020. 33(1): p. 108234. Wang, L., X. Fan, G. Bonenfant, D. Cui, J. Hossain, N. Jiang, G. Larson, M. Currier, J. Liddell, M. Wilson, A. Tamin, J. Harcourt, J. Ciomperlik-Patton, H. Pang, N. Dybdahl- Sissoko, R. Campagnoli, P.Y. Shi, J. Barnes, N.J. Thornburg, D.E. Wentworth, and B. Zhou, Susceptibility to SARS-CoV-2 of Cell Lines and Substrates Commonly Used to Diagnose and Isolate Influenza and Other Viruses. Emerg Infect Dis, 202E 27(5): p. 1380-1392. Adeshina, Y.O., E.J. Deeds, and J. Karanicolas, Machine learning classification can reduce false positives in structure-based virtual screening. Proc Natl Acad Sci U S A, 2020. 117(31): p. 18477-18488. 48. Shoichet, B.K. and B.K. Kobilka, Structure -based drug screening for G-protein-coupled receptors. Trends Pharmacol Sci, 2012. 33(5): p. 268-72.

49. Narayanan, K., S.I. Ramirez, K.G. Lokugamage, and S. Makino, Coronavirus nonstructural protein 1: Common and distinct functions in the regulation of host and viral gene expression. Virus Res, 2015. 202: p. 89-100.

50. Zhao, J.J., J.D. Rogers, S.D. Holland, P. Larson, R.D. Amin, R. Haesen, A. Freeman, M. Seiberling, M. Merz, and H. Cheng, Pharmacokinetics and bioavailability of montelukast sodium (MK-0476) in healthy young and elderly volunteers. Biopharm Drug Dispos, 1997. 18(9): p. 769-77.

51. Yasu, T., K. Momo, S. Kobayashi, S. Kuroda, and A. Tojo, Simple Determination of Plasma Ponatinib Concentration Using HPLC. Biol Pharm Bull, 2018. 41(2): p. 254-258.

52. Aouri, M., C. Barcelo, M. Guidi, M. Rotger, M. Cavassini, C. Hizrel, T. Buclin, L.A. Decosterd, C. Csajka, and H.I.V.C.S. Swiss, Population Pharmacokinetics and Pharmacogenetics Analysis of Rilpivirine in HIV-1 -Infected Individuals. Antimicrob Agents Chemother, 2017. 61(1).

53. Copertino, D.C., R.R.R. Duarte, T.R. Powell, M. de Mulder Rougvie, and D.F. Nixon, Montelukast drug activity and potential against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). J Med Virol, 2021. 93(1): p. 187-189.

54. Sharma, T., M. Abohashrh, M.H. Baig, J.J. Dong, M.M. Alam, I. Ahmad, and S. Irfan, Screening of drug databank against WT and mutant main protease of SARS-CoV-2: Towards finding potential compound for repurposing against COVID-19. Saudi J Biol Sci, 2021. 28(5): p. 3152-3159.

55. Kumar, S., B. Singh, P. Kumari, P.V. Kumar, G. Agnihotri, S. Khan, T. Kant Beuria, G.H. Syed, and A. Dixit, Identification of multipotent drugs for COVID-19 therapeutics with the evaluation of their SARS-CoV2 inhibitory activity. Comput Struct Biotechnol J, 2021. 19: p. 1998-2017.

56. Funk, C.D. and A. Ardakani, A Novel Strategy to Mitigate the Hyperinflammatory Response to COVID-19 by Targeting Leukotrienes. Front Pharmacol, 2020. 11: p. 1214.

57. Khan, A.R., C. Misdary, N. Yegya-Raman, S. Kim, N. Narayanan, S. Siddiqui, P. Salgame, J. Radbel, F. Groote, C. Michel, J. Mehnert, C. Hernandez, T. Braciale, J. Malhotra, M.A. Gentile, and S.K. Jabbour, Montelukast in hospitalized patients diagnosed with COVID-19. J Asthma, 2021: p. 1-7.

58. Kumawat, A., S. Namsani, D. Pramanik, S. Roy, and J.K. Singh, Integrated docking and enhanced sampling-based selection of repurposing drugs for SARS-CoV-2 by targeting host dependent factors. J Biomol Struct Dyn, 2021: p. 1-12.

59. Sauvat, A., F. Ciccosanti, F. Colavita, M. Di Rienzo, C. Castilletti, M.R. Capobianchi, O. Kepp, L. Zitvogel, G.M. Fimia, M. Piacentini, and G. Kroemer, On-target versus off- target effects of drugs inhibiting the replication of SARS-CoV-2. Cell Death Dis, 2020. 11(8): p. 656. 60. Ameen, F., E. Mamidala, R. Davella, and S. Vallala, Rilpivirine inhibits SARS-CoV-2 protein targets: A potential multi-target drug. J Infect Public Health, 2021. 14(10): p. 1454-1460.

61. An, J., M. Totrov, and R. Abagyan, Pocketome via comprehensive identification and classification of ligand binding envelopes. Mol Cell Proteomics, 2005. 4(6): p. 752-61. 62. Lam, P.C., R. Abagyan, and M. Totrov, Ligand-biased ensemble receptor docking

(LigBEnD): a hybrid ligand/receptor structure-based approach. J Comput Aided Mol Des, 2018. 32(1): p. 187-198.

63. Neves, M.A., M. Totrov, and R. Abagyan, Docking and scoring with ICM: the benchmarking results and strategies for improvement. J Comput Aided Mol Des, 2012. 26(6): p. 675-86.

64. Dallakyan, S. and A.J. Olson, Small-molecule library screening by docking with PyRx. Methods Mol Biol, 2015. 1263: p. 243-50.

65. Almeida, M.S., M.A. Johnson, T. Herrmann, M. Geralt, and K. Wuthrich, Novel beta barrelfold in the nuclear magnetic resonance structure of the replicase nonstructural protein 1 from the severe acute respiratory syndrome coronavirus. J Virol, 2007. 81(7): p. 3151-61.

Claims

We claim:

1. A pharmaceutical composition comprising a compound listed in any one of Tables 1-8, or a derivative thereof, and a pharmaceutically acceptable carrier or diluent.

2. A pharmaceutical composition comprising at least two compounds listed in any one of Tables 1-8, or a derivative thereof, and a pharmaceutically acceptable carrier or diluent.

3. The pharmaceutical composition of claim 2, which comprises three or more, four or more, or five or more compounds listed in any one of Tables 1-8, or a derivative thereof, and a pharmaceutically acceptable carrier or diluent.

4. The pharmaceutical composition of any one of the preceding claims, which comprises Conivaptan, Montelukast, Pazopanib, Ponatinib, Rilpivirine, Tirilazad, and/or a derivative thereof.

5. The pharmaceutical composition of any one of the preceding claims, which comprises Conivaptan or a derivative thereof.

6. The pharmaceutical composition of any one of the preceding claims, which comprises Montelukast or a derivative thereof.

7. The pharmaceutical composition of any one of the preceding claims, which comprises Pazopanib or a derivative thereof.

8. The pharmaceutical composition of any one of the preceding claims, which comprises Ponatinib or a derivative thereof.

9. The pharmaceutical composition of any one of the preceding claims, which comprises Rilpivirine or a derivative thereof.

10. The pharmaceutical composition of any one of the preceding claims, which comprises Tirilazad or a derivative thereof.

11. The pharmaceutical composition of any one of the preceding claims, which comprises

(i) Ponatinib and Rilpivirine;

(ii) Ponatinib and Montelukast;

(iii) Montelukast and Rilpivirine;

(iv) Montelukast, Ponatinib, and Rilpivirine;

(v) Montelukast and Tirilazad;

(vi) Ponatinib and Tirilazad;

(vii) Conivaptan, Montelukast, and Ponatinib;

(viii) Tirilazad, Montelukast, and Ponatinib; or

(ix) Pazopanib, Montelukast, and Ponatinib.

12. The pharmaceutical composition of any one of the preceding claims, which is effective to achieve an additive effect of inhibiting Nspl to achieve a greater therapeutic effect.

13. The pharmaceutical composition of any one of the preceding claims, which is effective to achieve a synergistic effect of inhibiting Nspl to achieve a greater therapeutic effect.

14. The pharmaceutical composition of any one of the preceding claims, further comprising an additional therapeutic agent.

15. The pharmaceutical composition of any one of the preceding claims, wherein the compound specifically binds to a Nspl (Non- Structural Protein 1) molecule.

16. The pharmaceutical composition of any one of the preceding claims, wherein the compound specifically binds to the N-terminal domain of an Nspl molecule, optionally wherein the compound specifically binds within residues 1-120 of the Nspl molecule, optionally wherein the compound specifically binds to an RNA groove in the N- terminal domain of the Nspl molecule.

17. The pharmaceutical composition of any one of the preceding claims, wherein the compound specifically binds to the C-terminal domain of an Nspl molecule, optionally wherein the compound specifically binds within residues 121-180 of the Nspl molecule, optionally wherein the compound specifically binds to a helix-loop-helix region in the C-terminal domain of the Nspl molecule.

18. The pharmaceutical composition of any one of claims 2-17, wherein the at least two compounds specifically binds to non-competing epitopes on the same or different Nspl molecules.

19. The pharmaceutical composition of any one of claims 2-18, wherein the at least two compounds independently bind to non-competing epitopes on the same or different Nspl molecules.

20. The pharmaceutical composition of any one of claims 2-19, wherein the at least two compounds independently bind to the N-terminal domain and the C-terminal domain on the same or different Nspl molecules.

21. The pharmaceutical composition of any one of claims 3-20, wherein the at least three compounds specifically binds to non-competing epitopes on the same or different Nspl molecules.

22. The pharmaceutical composition of any one of claims 3-21, wherein the at least three compounds independently bind to non-competing epitopes on the same or different Nspl molecules.

23. The pharmaceutical composition of any one of claims 3-22, wherein the at least three compounds independently bind to the N-terminal domain and the C-terminal domain on the same or different Nspl molecules.

24. The pharmaceutical composition any one of the preceding claims, which is effective to inhibit the activity of the N-terminal domain and the C-terminal domain on the same or different Nspl molecules to achieve a synergistic effect of inhibiting Nspl to achieve a greater therapeutic effect.

25. The pharmaceutical composition of any one of the preceding claims, wherein the Nspl molecule is derived from a virus.

26. The pharmaceutical composition of claim 25, wherein the virus is a coronavirus, optionally, selected from a severe acute respiratory syndrome coronavirus (SARS-CoV), a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a Middle East respiratory syndrome coronavirus (MERS-CoV), a human coronavirus OC43 (HCoV- OC43), a human coronavirus HKU 1 (HCoV-HKU 1), a human coronavirus 229E (HCoV- 229E), a human coronavirus NL63 (HCoV-NL63), and variants thereof.

27. The pharmaceutical composition of claim 25 or 26, wherein the virus causes bronchitis and/or the common cold.

28. The pharmaceutical composition of any one of the preceding claims, which may be effective

(i) to diminish the activity of Nspl in vivo , in vitro , and/or ex vivo ,

(ii) to reduce the deleterious sequelae of COVID-19 infection by enhancing lung cell function and survival in a subject,

(iii) to use in a subject with minimal toxicity, and/or

(iv) when administered to a subject to achieve a therapeutic effect.

29. The pharmaceutical composition of any one of the preceding claims, wherein:

(i) the compound has an ECIOO of between about 0.01 mM and about 100 pM; and/or

(ii) the compound has a Safety Index of greater than about 5.

30. The pharmaceutical composition of any one of the preceding claims, which can reverse Nspl toxicity to substantially the same extent as a null mutation in the Nspl gene itself, as determined by a cytopathic assay, optionally wherein the null mutation comprises N128S/K129E and/or K164A.

31. A method of treating or preventing a viral infection in a subject, the method comprising administering to the subject an effective amount of the pharmaceutical composition of any one of claims 1-30.

32. The method of claim 31, wherein the viral infection is a coronavims infection.

33. The method of claim 32, wherein the coronavims infection is an infection by a SARS-CoV-2 virus.

34. The method of any one of claims 31-33, wherein the subject has, or is at risk of having, COVID-19.

35. The method of claim 34, wherein the pharmaceutical composition is administered to the subject prior to onset of one or more manifestations of COVID-19.

36. The method of claim 35, wherein the pharmaceutical composition is administered to the subject after the subject exhibits one or more manifestations of COVID- 19.

37. The method of any one of claims 31-36, wherein the method results in the amelioration of one or more manifestations of COVID-19.

38. The method of any one of claims 31-37, wherein the pharmaceutical composition is administered by any suitable route, optionally, orally, intranasally, intravenously, intramuscularly, or subcutaneously.

39. The method of any one of claims 31-38, wherein the pharmaceutical composition is administered before and/or after viral shedding is first detected in a sample from the subject.

40. The method of claim any one of claims 31-39, wherein the pharmaceutical composition is administered in combination with an additional therapeutic agent.

41. The method of claim any one of claims 31-40, wherein the subject is human.

42. An assay described herein, which may be effective to identify a compound or combination of compounds that specifically bind to an Nspl molecule.