Repurposing Pyramax®, quinacrine and tilorone as treatments for Ebola virus disease

Artesunate-multiple pharmacological effects beyond treating malaria

Artesunate, a semisynthetic derivative of artemisinin, is not only recommended as the first-line drug for treating severe malaria but is also a significant member of Artemisinin-based Combination Therapies (ACTs), used in combination with other artemisinin derivatives for treating uncomplicated malaria. Beyond its potent anti-malarial activity, artesunate has garnered considerable attention for its pharmacological effects, which encompass broad-spectrum anti-tumor, anti-viral, and anti-inflammatory properties. It has collectively demonstrated superior drug tolerance, low toxicity, and mild side effects in cell line experiments in vitro, experimental animal models, and clinical drug researches, as a monotherapy or in combination with other agents. Investigating the pharmacological effects of artesunate will facilitate the exploration of novel drug applications and enhance the comprehensive clinical applications.

Exploring the druggability of the UEV domain of human TSG101 in search for broad-spectrum antivirals

The ubiquitin E2 variant domain of TSG101 (TSG101-UEV) plays a pivotal role in protein sorting and virus budding by recognizing PTAP motifs within ubiquitinated proteins. Disruption of TSG101-UEV/PTAP interactions has emerged as a promising strategy for the development of host-oriented broad-spectrum antivirals with low susceptibility to resistance. TSG101 is a challenging target characterized by an extended and flat binding interface, low affinity for PTAP ligands, and complex binding energetics. Here, we assess the druggability of the TSG101-UEV/PTAP binding interface by searching for drug-like inhibitors and evaluating their ability to block PTAP recognition, impair budding, and inhibit viral proliferation. A discovery workflow was established by combining in vitro miniaturized HTS assays and a set of cell-based activity assays including high-content bimolecular complementation, virus-like particle release measurement, and antiviral testing in live virus infection. This approach has allowed us to identify a set of chemically diverse molecules that block TSG101-UEV/PTAP binding with IC50s in the low μM range and are able to disrupt the interaction between full-length TSG101 and viral proteins in human cells and inhibit viral replication. State-of-the-art molecular docking studies reveal that the active compounds exploit binding hotspots at the PTAP binding site, unlocking the full binding potential of the TSG101-UEV binding pockets. These inhibitors represent promising hits for the development of novel broad-spectrum antivirals through targeted optimization and are also valuable tools for investigating the involvement of ESCRT in the proliferation of different virus families and study the secondary effects induced by the disruption of ESCRT/virus interactions.

Repurposing Drugs and Synergistic Combinations as Potential Therapies for Inhibiting SARS-CoV-2 and Coronavirus Replication

Drug repurposing can serve an important role in rapidly discovering medicament options for emerging microbial pandemics. In this study, a pragmatic approach is demonstrated for screening and testing drug combinations as potential broad-spectrum therapies against SARS-CoV-2 and other betacoronaviruses. Rapid cell-based phenotypic small molecule screens were executed using related common-cold-causing HCoV-OC43 betacoronavirus to identify replication inhibitors from a library of drugs approved by regulatory agencies for other indications. Given the best inhibitors, an expedient checkerboard strategy then served to identify synergistic drug combinations. These combinations were then validated using more challenging assays involving SARS-CoV-2 and variants. Promising drug combinations against multiple viral variants were discovered and involved Tilorone with Nelfinavir or Molnupiravir.

Inter-Species Pharmacokinetic Modeling and Scaling for Drug Repurposing of Pyronaridine and Artesunate

Even though several new targets (mostly viral infection) for drug repurposing of pyronaridine and artesunate have recently emerged in vitro and in vivo, inter-species pharmacokinetic (PK) data that can extend nonclinical efficacy to humans has not been reported over 30 years of usage. Since extrapolation of animal PK data to those of humans is essential to predict clinical outcomes for drug repurposing, this study aimed to investigate inter-species PK differences in three animal species (hamster, rat, and dog) and to support clinical translation of a fixed-dose combination of pyronaridine and artesunate. PK parameters (e.g., steady-state volume of distribution (Vss), clearance (CL), area under the concentration-time curve (AUC), mean residence time (MRT), etc.) of pyronaridine, artesunate, and dihydroartemisinin (an active metabolite of artesunate) were determined by non-compartmental analysis. In addition, one- or two-compartment PK modeling was performed to support inter-species scaling. The PK models appropriately described the blood concentrations of pyronaridine, artesunate, and dihydroartemisinin in all animal species, and the estimated PK parameters in three species were integrated for inter-species allometric scaling to predict human PKs. The simple allometric equation (Y = a × Wb) well explained the relationship between PK parameters and the actual body weight of animal species. The results from the study could be used as a basis for drug repurposing and support determining the effective dosage regimen for new indications based on in vitro/in vivo efficacy data and predicted human PKs in initial clinical trials.

Identification of New Modulators and Inhibitors of Palmitoyl-Protein Thioesterase 1 for CLN1 Batten Disease and Cancer

Palmitoyl-protein thioesterase 1 (PPT1) is an understudied enzyme that is gaining attention due to its role in the depalmitoylation of several proteins involved in neurodegenerative diseases and cancer. PPT1 is overexpressed in several cancers, specifically cholangiocarcinoma and esophageal cancers. Inhibitors of PPT1 lead to cell death and have been shown to enhance the killing of tumor cells alongside known chemotherapeutics. PPT1 is hence a viable target for anticancer drug development. Furthermore, mutations in PPT1 cause a lysosomal storage disorder called infantile neuronal ceroid lipofuscinosis (CLN1 disease). Molecules that can inhibit, stabilize, or modulate the activity of this target are needed to address these diseases. We used PPT1 enzymatic assays to identify molecules that were subsequently tested by using differential scanning fluorimetry and microscale thermophoresis. Selected compounds were also tested in neuroblastoma cell lines. The resulting PPT1 screening data was used for building machine learning models to help select additional compounds for testing. We discovered two of the most potent PPT1 inhibitors reported to date, orlistat (IC50 178.8 nM) and palmostatin B (IC50 11.8 nM). When tested in HepG2 cells, it was found that these molecules had decreased activity, indicating that they were likely not penetrating the cells. The combination of in vitro enzymatic and biophysical assays enabled the identification of several molecules that can bind or inhibit PPT1 and may aid in the discovery of modulators or chaperones. The molecules identified could be used as a starting point for further optimization as treatments for other potential therapeutic applications outside CLN1 disease, such as cancer and neurological diseases.

Learning from COVID-19: How drug hunters can prepare for the next pandemic

Over 3 years, the SARS-CoV-2 pandemic killed nearly 7 million people and infected more than 767 million globally. During this time, our very small company was able to contribute to antiviral drug discovery efforts through global collaborations with other researchers, which enabled the identification and repurposing of multiple molecules with activity against SARS-CoV-2 including pyronaridine tetraphosphate, tilorone, quinacrine, vandetanib, lumefantrine, cetylpyridinium chloride, raloxifene, carvedilol, olmutinib, dacomitinib, crizotinib, and bosutinib. We highlight some of the key findings from this experience of using different computational and experimental strategies, and detail some of the challenges and strategies for how we might better prepare for the next pandemic so that potential antiviral treatments are available for future outbreaks.

Therapeutical Utilization and Repurposing of Artemisinin and Its Derivatives: A Narrative Review

Artemisinin (ART) and its derivatives have great therapeutical utility as antimalarials and can be repurposed for other indications, such as viral infections, autoimmune diseases, and cancer. This review presents a comprehensive overview of the therapeutic effects of ART-based drugs, beyond their antimalarial effects. This review also summarizes the information on their repurposing in other pathologies, with the hope that it will guide the future optimization of the use of ART-based drugs and of the treatment strategies for the listed diseases. By reviewing related literature, ART extraction and structure as well as the synthesis and structure of its derivatives are presented. Subsequently, the traditional roles of ART and its derivatives against malaria are reviewed, including antimalarial mechanism and occurrence of antimalarial resistance. Finally, the potential of ART and its derivatives to be repurposed for the treatment of other diseases are summarized. The great repurposing potential of ART and its derivatives may be useful for the control of emerging diseases with corresponding pathologies, and future research should be directed toward the synthesis of more effective derivatives or better combinations.

Transporter Inhibition Profile for the Antivirals Tilorone, Quinacrine and Pyronaridine

Pyronaridine, tilorone and quinacrine are cationic molecules that have in vitro activity against Ebola, SARS-CoV-2 and other viruses. All three molecules have also demonstrated in vivo activity against Ebola in mice, while pyronaridine showed in vivo efficacy against SARS-CoV-2 in mice. We have recently tested these molecules and other antivirals against human organic cation transporters (OCTs) and apical multidrug and toxin extruders (MATEs). Quinacrine was found to be an inhibitor of OCT2, while tilorone and pyronaridine were less potent, and these displayed variability depending on the substrate used. To assess whether any of these three molecules have other potential interactions with additional transporters, we have now screened them at 10 μM against various human efflux and uptake transporters including P-gp, OATP1B3, OAT1, OAT3, MRP1, MRP2, MRP3, BCRP, as well as confirmational testing against OCT1, OCT2, MATE1 and MATE2K. Interestingly, in this study tilorone appears to be a more potent inhibitor of OCT1 and OCT2 than pyronaridine or quinacrine. However, both pyronaridine and quinacrine appear to be more potent inhibitors of MATE1 and MATE2K. None of the three compounds inhibited MRP1, MRP2, MRP3, OAT1, OAT3, P-gp or OATP1B3. Similarly, we previously showed that tilorone and pyronaridine do not inhibit OATP1B1 and have confirmed that quinacrine behaves similarly. In total, these observations suggest that the three compounds only appear to interact with OCTs and MATEs to differing extents, suggesting they may be involved in fewer clinically relevant drug-transporter interactions involving pharmaceutical substrates of the other major transporters tested.

Multiple approaches to repurposing drugs for neuroblastoma

Neuroblastoma (NB) is the second leading extracranial solid tumor of early childhood with about two-thirds of cases presenting before the age of 5, and accounts for roughly 15 percent of all pediatric cancer fatalities in the United States. Treatments against NB are lacking, resulting in a low survival rate in high-risk patients. A repurposing approach using already approved or clinical stage compounds can be used for diseases for which the patient population is small, and the commercial market limited. We have used Bayesian machine learning, in vitro cell assays, and combination analysis to identify molecules with potential use for NB. We demonstrated that pyronaridine (SH-SY5Y IC50 1.70 µM, SK-N-AS IC50 3.45 µM), BAY 11-7082 (SH-SY5Y IC50 0.85 µM, SK-N-AS IC50 1.23 µM), niclosamide (SH-SY5Y IC50 0.87 µM, SK-N-AS IC50 2.33 µM) and fingolimod (SH-SY5Y IC50 4.71 µM, SK-N-AS IC50 6.11 µM) showed cytotoxicity against NB. As several of the molecules are approved drugs in the US or elsewhere, they may be repurposed more readily for NB treatment. Pyronaridine was also tested in combinations in SH-SY5Y cells and demonstrated an antagonistic effect with either etoposide or crizotinib. Whereas when crizotinib and etoposide were combined with each other they had a synergistic effect in these cells. We have also described several analogs of pyronaridine to explore the structure-activity relationship against cell lines. We describe multiple molecules demonstrating cytotoxicity against NB and the further evaluation of these molecules and combinations using other NB cells lines and in vivo models will be important in the future to assess translational potential.

Tilorone-Dihydrochloride Protects against Rift Valley Fever Virus Infection and Disease in the Mouse Model

Rift Valley fever (RVF) is a mosquito-borne zoonotic disease endemic to Africa and the Middle East that can affect humans and ruminant livestock. Currently, there are no approved vaccines or therapeutics for the treatment of severe RVF disease in humans. Tilorone-dihydrochloride (Tilorone) is a broad-spectrum antiviral candidate that has previously shown efficacy against a wide range of DNA and RNA viruses, and which is clinically utilized for the treatment of respiratory infections in Russia and other Eastern European countries. Here, we evaluated the antiviral activity of Tilorone against Rift Valley fever virus (RVFV). In vitro, Tilorone inhibited both vaccine (MP-12) and virulent (ZH501) strains of RVFV at low micromolar concentrations. In the mouse model, treatment with Tilorone significantly improved survival outcomes in BALB/c mice challenged with a lethal dose of RVFV ZH501. Treatment with 30 mg/kg/day resulted in 80% survival when administered immediately after infection. In post-exposure prophylaxis, Tilorone resulted in 30% survival at one day after infection when administered at 45 mg/kg/day. These findings demonstrate that Tilorone has potent antiviral efficacy against RVFV infection in vitro and in vivo and supports further development of Tilorone as a potential antiviral therapeutic for treatment of RVFV infection.

Defending Antiviral Cationic Amphiphilic Drugs That May Cause Drug-Induced Phospholipidosis

A recent publication in Science has proposed that cationic amphiphilic drugs repurposed for COVID-19 typically use phosholipidosis as their antiviral mechanism of action in cells but will have no in vivo efficacy. On the contrary, our viewpoint, supported by additional experimental data for similar cationic amphiphilic drugs, indicates that many of these molecules have both in vitro and in vivo efficacy with no reported phospholipidosis, and therefore, this class of compounds should not be avoided but further explored, as we continue the search for broad spectrum antivirals.

Remdesivir and EIDD-1931 Interact with Human Equilibrative Nucleoside Transporters 1 and 2: Implications for Reaching SARS-CoV-2 Viral Sanctuary Sites

Equilibrative nucleoside transporters (ENTs) are present at the blood-testis barrier (BTB), where they can facilitate antiviral drug disposition to eliminate a sanctuary site for viruses detectable in semen. The purpose of this study was to investigate ENT-drug interactions with three nucleoside analogs, remdesivir, molnupiravir, and molnupiravir's active metabolite, β-d-N⁴-hydroxycytidine (EIDD-1931), and four non-nucleoside molecules repurposed as antivirals for coronavirus disease 2019 (COVID-19). The study used three-dimensional pharmacophores for ENT1 and ENT2 substrates and inhibitors and Bayesian machine learning models to identify potential interactions with these transporters. In vitro transport experiments demonstrated that remdesivir was the most potent inhibitor of ENT-mediated [³H]uridine uptake (ENT1 IC₅₀: 39 μM; ENT2 IC₅₀: 77 μM), followed by EIDD-1931 (ENT1 IC₅₀: 259 μM; ENT2 IC₅₀: 467 μM), whereas molnupiravir was a modest inhibitor (ENT1 IC₅₀: 701 μM; ENT2 IC₅₀: 851 μM). Other proposed antivirals failed to inhibit ENT-mediated [³H]uridine uptake below 1 mM. Remdesivir accumulation decreased in the presence of 6-S-[(4-nitrophenyl)methyl]-6-thioinosine (NBMPR) by 30% in ENT1 cells (P = 0.0248) and 27% in ENT2 cells (P = 0.0054). EIDD-1931 accumulation decreased in the presence of NBMPR by 77% in ENT1 cells (P = 0.0463) and by 64% in ENT2 cells (P = 0.0132), which supported computational predictions that both are ENT substrates that may be important for efficacy against COVID-19. NBMPR failed to decrease molnupiravir uptake, suggesting that ENT interaction is likely inhibitory. Our combined computational and in vitro data can be used to identify additional ENT-drug interactions to improve our understanding of drugs that can circumvent the BTB. SIGNIFICANCE STATEMENT: This study identified remdesivir and EIDD-1931 as substrates of equilibrative nucleoside transporters 1 and 2. This provides a potential mechanism for uptake of these drugs into cells and may be important for antiviral potential in the testes and other tissues expressing these transporters.

Machine Learning Models Identify Inhibitors of SARS-CoV-2

With the rapidly evolving SARS-CoV-2 variants of concern, there is an urgent need for the discovery of further treatments for the coronavirus disease (COVID-19). Drug repurposing is one of the most rapid strategies for addressing this need, and numerous compounds have already been selected for in vitro testing by several groups. These have led to a growing database of molecules with in vitro activity against the virus. Machine learning models can assist drug discovery through prediction of the best compounds based on previously published data. Herein, we have implemented several machine learning methods to develop predictive models from recent SARS-CoV-2 in vitro inhibition data and used them to prioritize additional FDA-approved compounds for in vitro testing selected from our in-house compound library. From the compounds predicted with a Bayesian machine learning model, lumefantrine, an antimalarial was selected for testing and showed limited antiviral activity in cell-based assays while demonstrating binding (K_d 259 nM) to the spike protein using microscale thermophoresis. Several other compounds which we prioritized have since been tested by others and were also found to be active in vitro. This combined machine learning and in vitro testing approach can be expanded to virtually screen available molecules with predicted activity against SARS-CoV-2 reference WIV04 strain and circulating variants of concern. In the process of this work, we have created multiple iterations of machine learning models that can be used as a prioritization tool for SARS-CoV-2 antiviral drug discovery programs. The very latest model for SARS-CoV-2 with over 500 compounds is now freely available at www.assaycentral.org.

Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade

Introduction: Drug design and discovery of new antivirals will always be extremely important in medicinal chemistry, taking into account known and new viral diseases that are yet to come. Although machine learning (ML) have shown to improve predictions on the biological potential of chemicals and accelerate the discovery of drugs over the past decade, new methods and their combinations have improved their performance and established promising perspectives regarding ML in the search for new antivirals.Areas covered: The authors consider some interesting areas that deal with different ML techniques applied to antivirals. Recent innovative studies on ML and antivirals were selected and analyzed in detail. Also, the authors provide a brief look at the past to the present to detect advances and bottlenecks in the area.Expert opinion: From classical ML techniques, it was possible to boost the searches for antivirals. However, from the emergence of new algorithms and the improvement in old approaches, promising results will be achieved every day, as we have observed in the case of SARS-CoV-2. Recent experience has shown that it is possible to use ML to discover new antiviral candidates from virtual screening and drug repurposing.

Machine Learning in Discovery of New Antivirals and Optimization of Viral Infections Therapy

Nowadays, computational approaches play an important role in the design of new drug-like compounds and optimization of pharmacotherapeutic treatment of diseases. The emerging growth of viral infections, including those caused by the Human Immunodeficiency Virus (HIV), Ebola virus, recently detected coronavirus, and some others, leads to many newly infected people with a high risk of death or severe complications. A huge amount of chemical, biological, clinical data is at the disposal of the researchers. Therefore, there are many opportunities to find the relationships between the particular features of chemical data and the antiviral activity of biologically active compounds based on machine learning approaches. Biological and clinical data can also be used for building models to predict relationships between viral genotype and drug resistance, which might help determine the clinical outcome of treatment. In the current study, we consider machine-learning approaches in the antiviral research carried out during the past decade. We overview in detail the application of machine-learning methods for the design of new potential antiviral agents and vaccines, drug resistance prediction, and analysis of virus-host interactions. Our review also covers the perspectives of using the machine-learning approaches for antiviral research, including Dengue, Ebola viruses, Influenza A, Human Immunodeficiency Virus, coronaviruses, and some others.

Repurposing the Ebola and Marburg Virus Inhibitors Tilorone, Quinacrine, and Pyronaridine: In Vitro Activity against SARS-CoV-2 and Potential Mechanisms

Severe acute respiratory coronavirus 2 (SARS-CoV-2) is a newly identified virus that has resulted in over 2.5 million deaths globally and over 116 million cases globally in March, 2021. Small-molecule inhibitors that reverse disease severity have proven difficult to discover. One of the key approaches that has been widely applied in an effort to speed up the translation of drugs is drug repurposing. A few drugs have shown in vitro activity against Ebola viruses and demonstrated activity against SARS-CoV-2 in vivo. Most notably, the RNA polymerase targeting remdesivir demonstrated activity in vitro and efficacy in the early stage of the disease in humans. Testing other small-molecule drugs that are active against Ebola viruses (EBOVs) would appear a reasonable strategy to evaluate their potential for SARS-CoV-2. We have previously repurposed pyronaridine, tilorone, and quinacrine (from malaria, influenza, and antiprotozoal uses, respectively) as inhibitors of Ebola and Marburg viruses in vitro in HeLa cells and mouse-adapted EBOV in mice in vivo. We have now tested these three drugs in various cell lines (VeroE6, Vero76, Caco-2, Calu-3, A549-ACE2, HUH-7, and monocytes) infected with SARS-CoV-2 as well as other viruses (including MHV and HCoV 229E). The compilation of these results indicated considerable variability in antiviral activity observed across cell lines. We found that tilorone and pyronaridine inhibited the virus replication in A549-ACE2 cells with IC50 values of 180 nM and IC50 198 nM, respectively. We used microscale thermophoresis to test the binding of these molecules to the spike protein, and tilorone and pyronaridine bind to the spike receptor binding domain protein with K d values of 339 and 647 nM, respectively. Human Cmax for pyronaridine and quinacrine is greater than the IC50 observed in A549-ACE2 cells. We also provide novel insights into the mechanism of these compounds which is likely lysosomotropic.

The Antiviral Drug Tilorone Is a Potent and Selective Inhibitor of Acetylcholinesterase

Acetylcholinesterase (AChE) is an important drug target in neurological disorders like Alzheimer's disease, Lewy body dementia, and Parkinson's disease dementia as well as for other conditions like myasthenia gravis and anticholinergic poisoning. In this study, we have used a combination of high-throughput screening, machine learning, and docking to identify new inhibitors of this enzyme. Bayesian machine learning models were generated with literature data from ChEMBL for eel and human AChE inhibitors as well as butyrylcholinesterase inhibitors (BuChE) and compared with other machine learning methods. High-throughput screens for the eel AChE inhibitor model identified several molecules including tilorone, an antiviral drug that is well-established outside of the United States, as a newly identified nanomolar AChE inhibitor. We have described how tilorone inhibits both eel and human AChE with IC₅₀'s of 14.4 nM and 64.4 nM, respectively, but does not inhibit the closely related BuChE IC₅₀ > 50 μM. We have docked tilorone into the human AChE crystal structure and shown that this selectivity is likely due to the reliance on a specific interaction with a hydrophobic residue in the peripheral anionic site of AChE that is absent in BuChE. We also conducted a pharmacological safety profile (SafetyScreen44) and kinase selectivity screen (SelectScreen) that showed tilorone (1 μM) only inhibited AChE out of 44 toxicology target proteins evaluated and did not appreciably inhibit any of the 485 kinases tested. This study suggests there may be a potential role for repurposing tilorone or its derivatives in conditions that benefit from AChE inhibition.