A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus

Identification of Prospective Ebola Virus VP35 and VP40 Protein Inhibitors from Myxobacterial Natural Products

The Ebola virus (EBOV) is a lethal pathogen causing hemorrhagic fever syndrome which remains a global health challenge. In the EBOV, two multifunctional proteins, VP35 and VP40, have significant roles in replication, virion assembly, and budding from the cell and have been identified as druggable targets. In this study, we employed in silico methods comprising molecular docking, molecular dynamic simulations, and pharmacological properties to identify prospective drugs for inhibiting VP35 and VP40 proteins from the myxobacterial bioactive natural product repertoire. Cystobactamid 934-2, Cystobactamid 919-1, and Cittilin A bound firmly to VP35. Meanwhile, 2-Hydroxysorangiadenosine, Enhypyrazinone B, and Sorangiadenosine showed strong binding to the matrix protein VP40. Molecular dynamic simulations revealed that, among these compounds, Cystobactamid 919-1 and 2-Hydroxysorangiadenosine had stable interactions with their respective targets. Similarly, molecular mechanics Poisson-Boltzmann surface area (MMPBSA) calculations indicated close-fitting receptor binding with VP35 or VP40. These two compounds also exhibited good pharmacological properties. In conclusion, we identified Cystobactamid 919-1 and 2-Hydroxysorangiadenosine as potential ligands for EBOV that target VP35 and VP40 proteins. These findings signify an essential step in vitro and in vivo to validate their potential for EBOV inhibition.

Association between oral antimalarial medication administration and mortality among patients with Ebola virus disease: a multisite cohort study

BACKGROUND

Empiric antimalarial treatment is a component of protocol-based management of Ebola virus disease (EVD), yet this approach has limited clinical evidence for patient-centered benefits.

METHODS

This retrospective cohort study evaluated the association between antimalarial treatment and mortality among patients with confirmed EVD. The data was collected from five International Medical Corps operated Ebola Treatment Units (ETUs) in Sierra Leone and Liberia from 2014 through 2015. The standardized protocol used for patient care included empiric oral treatment with combination artemether and lumefantrine, twice daily for three days; however, only a subset of patients received treatment due to resource variability. The outcome of interest was mortality, comparing patients treated with oral antimalarials within 48-h of admission to those not treated. Analysis was conducted with logistic regression to generate adjusted odds ratios (aORs). Multivariable analyses controlled for ETU country, malaria rapid diagnostic test result, age, EVD cycle threshold value, symptoms of bleeding, diarrhea, dysphagia and dyspnea, and additional standard clinical treatments.

RESULTS

Among the 424 cases analyzed, 376 (88.7%) received early oral antimalarials. Across all cases, mortality occurred in 57.5% (244). In comparing unadjusted mortality prevalence, early antimalarial treated cases yielded 55.1% mortality versus 77.1% mortality for those untreated (p = 0.005). Multivariable analysis demonstrated evidence of reduced aOR for mortality with early oral antimalarial treatment versus non-treatment (aOR = 0.34, 95% Confidence Interval: 0.12, 0.92, p = 0.039).

CONCLUSION

Early oral antimalarial treatment in an EVD outbreak was associated with reduced mortality. Further study is warranted to investigate this association between early oral antimalarial treatment and mortality in EVD patients.

Evaluating the performance of drug-repurposing technologies

Drug-repurposing technologies are growing in number and maturing. However, comparisons to each other and to reality are hindered because of a lack of consensus with respect to performance evaluation. Such comparability is necessary to determine scientific merit and to ensure that only meaningful predictions from repurposing technologies carry through to further validation and eventual patient use. Here, we review and compare performance evaluation measures for these technologies using version 2 of our shotgun repurposing Computational Analysis of Novel Drug Opportunities (CANDO) platform to illustrate their benefits, drawbacks, and limitations. Understanding and using different performance evaluation metrics ensures robust cross-platform comparability, enabling us to continue to strive toward optimal repurposing by decreasing the time and cost of drug discovery and development.

Computational Study on Potential Novel Anti-Ebola Virus Protein VP35 Natural Compounds

Ebola virus (EBOV) is one of the most lethal pathogens that can infect humans. The Ebola viral protein VP35 (EBOV VP35) inhibits host IFN-α/β production by interfering with host immune responses to viral invasion and is thus considered as a plausible drug target. The aim of this study was to identify potential novel lead compounds against EBOV VP35 using computational techniques in drug discovery. The 3D structure of the EBOV VP35 with PDB ID: 3FKE was used for molecular docking studies. An integrated library of 7675 African natural product was pre-filtered using ADMET risk, with a threshold of 7 and, as a result, 1470 ligands were obtained for the downstream molecular docking using AutoDock Vina, after an energy minimization of the protein via GROMACS. Five known inhibitors, namely, amodiaquine, chloroquine, gossypetin, taxifolin and EGCG were used as standard control compounds for this study. The area under the curve (AUC) value, evaluating the docking protocol obtained from the receiver operating characteristic (ROC) curve, generated was 0.72, which was considered to be acceptable. The four identified potential lead compounds of NANPDB4048, NANPDB2412, ZINC000095486250 and NANPDB2476 had binding affinities of −8.2, −8.2, −8.1 and −8.0 kcal/mol, respectively, and were predicted to possess desirable antiviral activity including the inhibition of RNA synthesis and membrane permeability, with the probable activity (Pa) being greater than the probable inactivity (Pi) values. The predicted anti-EBOV inhibition efficiency values (IC₅₀), found using a random forest classifier, ranged from 3.35 to 11.99 μM, while the Ki values ranged from 0.97 to 1.37 μM. The compounds NANPDB4048 and NANPDB2412 had the lowest binding energy of −8.2 kcal/mol, implying a higher binding affinity to EBOV VP35 which was greater than those of the known inhibitors. The compounds were predicted to possess a low toxicity risk and to possess reasonably good pharmacological profiles. Molecular dynamics (MD) simulations of the protein–ligand complexes, lasting 50 ns, and molecular mechanisms Poisson-Boltzmann surface area (MM-PBSA) calculations corroborated the binding affinities of the identified compounds and identified novel critical interacting residues. The antiviral potential of the molecules could be confirmed experimentally, while the scaffolds could be optimized for the design of future novel anti-EBOV chemotherapeutics.

Attacking COVID-19 Progression Using Multi-Drug Therapy for Synergetic Target Engagement

COVID-19 is a devastating respiratory and inflammatory illness caused by a new coronavirus that is rapidly spreading throughout the human population. Over the past 12 months, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for COVID-19, has already infected over 160 million (>20% located in United States) and killed more than 3.3 million people around the world (>20% deaths in USA). As we face one of the most challenging times in our recent history, there is an urgent need to identify drug candidates that can attack SARS-CoV-2 on multiple fronts. We have therefore initiated a computational dynamics drug pipeline using molecular modeling, structure simulation, docking and machine learning models to predict the inhibitory activity of several million compounds against two essential SARS-CoV-2 viral proteins and their host protein interactors-S/Ace2, Tmprss2, Cathepsins L and K, and Mpro-to prevent binding, membrane fusion and replication of the virus, respectively. All together, we generated an ensemble of structural conformations that increase high-quality docking outcomes to screen over >6 million compounds including all FDA-approved drugs, drugs under clinical trial (>3000) and an additional >30 million selected chemotypes from fragment libraries. Our results yielded an initial set of 350 high-value compounds from both new and FDA-approved compounds that can now be tested experimentally in appropriate biological model systems. We anticipate that our results will initiate screening campaigns and accelerate the discovery of COVID-19 treatments.

Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review

BACKGROUND AND OBJECTIVE

During the recent global urgency, scientists, clinicians, and healthcare experts around the globe keep on searching for a new technology to support in tackling the Covid-19 pandemic. The evidence of Machine Learning (ML) and Artificial Intelligence (AI) application on the previous epidemic encourage researchers by giving a new angle to fight against the novel Coronavirus outbreak. This paper aims to comprehensively review the role of AI and ML as one significant method in the arena of screening, predicting, forecasting, contact tracing, and drug development for SARS-CoV-2 and its related epidemic.

METHOD

A selective assessment of information on the research article was executed on the databases related to the application of ML and AI technology on Covid-19. Rapid and critical analysis of the three crucial parameters, i.e., abstract, methodology, and the conclusion was done to relate to the model's possibilities for tackling the SARS-CoV-2 epidemic.

RESULT

This paper addresses on recent studies that apply ML and AI technology towards augmenting the researchers on multiple angles. It also addresses a few errors and challenges while using such algorithms in real-world problems. The paper also discusses suggestions conveying researchers on model design, medical experts, and policymakers in the current situation while tackling the Covid-19 pandemic and ahead.

CONCLUSION

The ongoing development in AI and ML has significantly improved treatment, medication, screening, prediction, forecasting, contact tracing, and drug/vaccine development process for the Covid-19 pandemic and reduce the human intervention in medical practice. However, most of the models are not deployed enough to show their real-world operation, but they are still up to the mark to tackle the SARS-CoV-2 epidemic.

Insights into Ebola Virus VP35 and VP24 Interferon Inhibitory Functions and their Initial Exploitation as Drug Targets

Upon viral infection, the interferon (IFN) system triggers potent antiviral mechanisms limiting viral growth and spread. Hence, to sustain their infection, viruses evolved efficient counteracting strategies to evade IFN control. Ebola virus (EBOV), member of the family Filoviridae, is one of the most virulent and deadly pathogen ever faced by humans. The etiological agent of the Ebola Virus Disease (EVD), EBOV can be undoubtedly considered the perfect example of a powerful inhibitor of the host organism immune response activation. Particularly, the efficacious suppression of the IFN cascade contributes to disease progression and severity. Among the EBOVencoded proteins, the Viral Proteins 35 (VP35) and 24 (VP24) are responsible for the EBOV extreme virulence, representing the core of such inhibitory function through which EBOV determines its very effective shield to the cellular immune defenses. VP35 inhibits the activation of the cascade leading to IFN production, while VP24 inhibits the activation of the IFN-stimulated genes. A number of studies demonstrated that both VP35 and VP24 is validated target for drug development. Insights into the structural characteristics of VP35 and VP24 domains revealed crucial pockets exploitable for drug development. Considered the lack of therapy for EVD, restoring the immune activation is a promising approach for drug development. In the present review, we summarize the importance of VP35 and VP24 proteins in counteracting the host IFN cellular response and discuss their potential as druggable viral targets as a promising approach toward attenuation of EBOV virulence.

Déjà vu: Stimulating open drug discovery for SARS-CoV-2

In the past decade we have seen two major Ebola virus outbreaks in Africa, the Zika virus in Brazil and the Americas and the current pandemic of coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). There is a strong sense of déjà vu because there are still no effective treatments. In the COVID-19 pandemic, despite being a new virus, there are already drugs suggested as active in in vitro assays that are being repurposed in clinical trials. Promising SARS-CoV-2 viral targets and computational approaches are described and discussed. Here, we propose, based on open antiviral drug discovery approaches for previous outbreaks, that there could still be gaps in our approach to drug discovery.

In Silico Studies against Viral Sexually Transmitted Diseases

Sexually Transmitted Diseases (STDs) refer to a variety of clinical syndromes and infections caused by pathogens that can be acquired and transmitted through sexual activity. Among STDs widely reported in the literature, viral sexual diseases have been increasing in a number of cases globally. This emphasizes the need for prevention and treatment. Among the methods widely used in drug planning are Computer-Aided Drug Design (CADD) studies and molecular docking which have the objective of investigating molecular interactions between two molecules to better understand the three -dimensional structural characteristics of the compounds. This review will discuss molecular docking studies applied to viral STDs, such as Ebola virus, Herpes virus and HIV, and reveal promising new drug candidates with high levels of specificity to their respective targets.

Identification of Potential Dipeptidyl Peptidase (DPP)-IV Inhibitors among Moringa oleifera Phytochemicals by Virtual Screening, Molecular Docking Analysis, ADME/T-Based Prediction, and In Vitro Analyses

Moringa oleifera Lam. (MO) is called the “Miracle Tree” because of its extensive pharmacological activity. In addition to being an important food, it has also been used for a long time in traditional medicine in Asia for the treatment of chronic diseases such as diabetes and obesity. In this study, by constructing a library of MO phytochemical structures and using Discovery Studio software, compounds were subjected to virtual screening and molecular docking experiments related to their inhibition of dipeptidyl peptidase (DPP-IV), an important target for the treatment of type 2 diabetes. After the four-step screening process, involving screening for drug-like compounds, predicting the absorption, distribution, metabolism, excretion, and toxicity (ADME/T) of pharmacokinetic properties, LibDock heatmap matching analysis, and CDOCKER molecular docking analysis, three MO components that were candidate DPP-IV inhibitors were identified and their docking modes were analyzed. In vitro activity verification showed that all three MO components had certain DPP-IV inhibitory activities, of which O-Ethyl-4-[(α-l-rhamnosyloxy)-benzyl] carbamate (compound 1) had the highest activity (half-maximal inhibitory concentration [IC₅₀] = 798 nM). This study provides a reference for exploring the molecular mechanisms underlying the anti-diabetic activity of MO. The obtained DPP-IV inhibitors could be used for structural optimization and in-depth in vivo evaluation.

Perspectives towards antiviral drug discovery against Ebola virus

Ebola virus disease (EVD), caused by Ebola viruses, resulted in more than 11 500 deaths according to a recent 2018 WHO report. With mortality rates up to 90%, it is nowadays one of the most deadly infectious diseases. However, no Food and Drug Administration‐approved Ebola drugs or vaccines are available yet with the mainstay of therapy being supportive care. The high fatality rate and absence of effective treatment or vaccination make Ebola virus a category‐A biothreat pathogen. Fortunately, a series of investigational countermeasures have been developed to control and prevent this global threat. This review summarizes the recent therapeutic advances and ongoing research progress from research and development to clinical trials in the development of small‐molecule antiviral drugs, small‐interference RNA molecules, phosphorodiamidate morpholino oligomers, full‐length monoclonal antibodies, and vaccines. Moreover, difficulties are highlighted in the search for effective countermeasures against EVD with additional focus on the interplay between available in silico prediction methods and their evidenced potential in antiviral drug discovery.

Effect of Mass Artesunate-Amodiaquine Distribution on Mortality of Patients With Ebola Virus Disease During West African Outbreak

Background

Experiments in vitro have shown that the drug amodiaquine may inhibit Ebola virus activity. During the Ebola virus disease (EVD) epidemic in West Africa in 2014-2016, 2 mass drug administrations (MDAs) of artesunate-amodiaquine (ASAQ) were implemented to decrease the burden of malaria. The objective of this study was to assess the effect of the ASAQ MDAs on the mortality of patients with EVD.

Methods

A retrospective cohort design was used to analyze mortality data for patients with EVD admitted to 5 Ebola treatment units in Liberia and Sierra Leone. Patients admitted to the ETUs during the time period of ASAQ's therapeutic effect from areas where the MDA was implemented were matched to controls not exposed to ASAQ, using a range of covariates, including malaria co-infection status, and a logistic regression analysis was performed. The primary outcome was Ebola treatment unit mortality.

Results

A total of 424 patients with EVD had sufficient data for analysis. Overall, the mortality of EVD patients was 57.5%. A total of 22 EVD patients were exposed to ASAQ during the MDAs and were found to have decreased risk of death compared with those not exposed in a matched analysis, but this did not reach statistical significance (relative risk, 0.63; 95% confidence interval, 0.37-1.07; P = .086).

Conclusions

There was a non-statistically significantly decreased risk of mortality in EVD patients exposed to ASAQ during the 2 MDAs as compared with EVD patients not exposed to ASAQ. Further prospective trials are needed to determine the direct effect of ASAQ on EVD mortality.

Ebola Virus Bayesian Machine Learning Models Enable New in Vitro Leads

We have previously described the first Bayesian machine learning models from FDA-approved drug screens, for identifying compounds active against the Ebola virus (EBOV). These models led to the identification of three active molecules in vitro: tilorone, pyronaridine, and quinacrine. A follow-up study demonstrated that one of these compounds, tilorone, has 100% in vivo efficacy in mice infected with mouse-adapted EBOV at 30 mg/kg/day intraperitoneal. This suggested that we can learn from the published data on EBOV inhibition and use it to select new compounds for testing that are active in vivo. We used these previously built Bayesian machine learning EBOV models alongside our chemical insights for the selection of 12 molecules, absent from the training set, to test for in vitro EBOV inhibition. Nine molecules were directly selected using the model, and eight of these molecules possessed a promising in vitro activity (EC50 < 15 μM). Three further compounds were selected for an in vitro evaluation because they were antimalarials, and compounds of this class like pyronaridine and quinacrine have previously been shown to inhibit EBOV. We identified the antimalarial drug arterolane (IC50 = 4.53 μM) and the anticancer clinical candidate lucanthone (IC50 = 3.27 μM) as novel compounds that have EBOV inhibitory activity in HeLa cells and generally lack cytotoxicity. This work provides further validation for using machine learning and medicinal chemistry expertize to prioritize compounds for testing in vitro prior to more costly in vivo tests. These studies provide further corroboration of this strategy and suggest that it can likely be applied to other pathogens in the future.

Virtual screening of natural inhibitors targeting ornithine decarboxylase with pharmacophore scaffolding of DFMO and validation by molecular dynamics simulation studies

Ornithine decarboxylase (ODC) is an enzyme that initiates polyamine synthesis in human. Polyamines play key roles in cell-cell adhesion, cell motility and cell cycle regulation. Higher synthesis of polyamines also occurs in rapidly proliferating cancer cells are mediated by ODC. As per earlier studies, di-flouro-methyl-orninthine (DFMO) is a proven efficient inhibitor ODC targeting the catalytic activity, however, its usage is limited due to side effects. Targeting ODC is considered as a potential therapeutic modality in the treatment of cancer. In this study, it is attempted to use DFMO scaffold to build a ligand-based pharmocophore query using MOE to screen similar active compounds from Universal Natural Products Database with better ADMET properties. The identified compounds were virtually screened against the active cavity of ODC using Glide. Further, potential natural hits targeting ODC were shortlisted based on Molecular Mechanics/Generalized-Born/Surface Area (MM-GBSA) score. Finally, molecular dynamics simulations were performed for the natural molecule hit and DFMO in complex with ODC using Desmond. Among the hits shortlisted, 2-amino-5, 9, 13, 17-tetramethyloctadeca-8, 16-diene-1, 3, 14-triol (UNPD208110) was found to be highly potential, as it showed a higher binding affinity in terms of interactions with key active cavity residues, and also showed better ADMET property, HUMO-LUMO gap energy and more stable complex formation with ODC compared to DFMO. Hence, the proposed molecule (UNPD208110) shall be favourably considered as a potential natural inhibitor targeting ODC-mediated disease conditions.

A Systematic Review of Computational Drug Discovery, Development, and Repurposing for Ebola Virus Disease Treatment

Ebola virus disease (EVD) is a deadly global public health threat, with no currently approved treatments. Traditional drug discovery and development is too expensive and inefficient to react quickly to the threat. We review published research studies that utilize computational approaches to find or develop drugs that target the Ebola virus and synthesize its results. A variety of hypothesized and/or novel treatments are reported to have potential anti-Ebola activity. Approaches that utilize multi-targeting/polypharmacology have the most promise in treating EVD.

The Ebola virus VP35 protein binds viral immunostimulatory and host RNAs identified through deep sequencing

Ebola virus and Marburg virus are members of the Filovirdae family and causative agents of hemorrhagic fever with high fatality rates in humans. Filovirus virulence is partially attributed to the VP35 protein, a well-characterized inhibitor of the RIG-I-like receptor pathway that triggers the antiviral interferon (IFN) response. Prior work demonstrates the ability of VP35 to block potent RIG-I activators, such as Sendai virus (SeV), and this IFN-antagonist activity is directly correlated with its ability to bind RNA. Several structural studies demonstrate that VP35 binds short synthetic dsRNAs; yet, there are no data that identify viral immunostimulatory RNAs (isRNA) or host RNAs bound to VP35 in cells. Utilizing a SeV infection model, we demonstrate that both viral isRNA and host RNAs are bound to Ebola and Marburg VP35s in cells. By deep sequencing the purified VP35-bound RNA, we identified the SeV copy-back defective interfering (DI) RNA, previously identified as a robust RIG-I activator, as the isRNA bound by multiple filovirus VP35 proteins, including the VP35 protein from the West African outbreak strain (Makona EBOV). Moreover, RNAs isolated from a VP35 RNA-binding mutant were not immunostimulatory and did not include the SeV DI RNA. Strikingly, an analysis of host RNAs bound by wild-type, but not mutant, VP35 revealed that select host RNAs are preferentially bound by VP35 in cell culture. Taken together, these data support a model in which VP35 sequesters isRNA in virus-infected cells to avert RIG-I like receptor (RLR) activation.

VP40 of the Ebola Virus as a Target for EboV Therapy: Comprehensive Conformational and Inhibitor Binding Landscape from Accelerated Molecular Dynamics

The first account of the dynamic features of the loop region of VP40 of the Ebola virus was studied using accelerated molecular dynamics simulations and reported herein. Among the proteins of the Ebola virus, the matrix protein (VP40) plays a significant role in the virus lifecycle thereby making it a promising therapeutic target. Of interest is the newly elucidated N-terminal domain loop region of VP40 comprising residues K127, T129, and N130 which when mutated to alanine have demonstrated an unrecognized role for N-terminal domain-plasma membrane interaction for efficient VP40-plasma membrane localization, oligomerization, matrix assembly, and egress. The molecular understanding of the conformational features of VP40 in complex with a known inhibitor still remains elusive. Using accelerated molecular dynamics approaches, we conducted a comparative study on VP40 apo and bound systems to understand the conformational features of VP40 at the molecular level and to determine the effect of inhibitor binding with the aid of a number of post-dynamic analytical tools. Significant features were seen in the presence of an inhibitor as per molecular mechanics/generalized born surface area binding free energy calculations. Results revealed that inhibitor binding to VP40 reduces the flexibility and mobility of the protein as supported by root mean square fluctuation and root mean square deviation calculations. The study revealed a characteristic "twisting" motion and coiling of the loop region of VP40 accompanied by conformational changes in the dimer interface upon inhibitor binding. We believe that results presented in this study will ultimately provide useful insight into the binding landscape of VP40 which could assist researchers in the discovery of potent Ebola virus inhibitors for anti-Ebola therapies.

Targeting endosomal acidification by chloroquine analogs as a promising strategy for the treatment of emerging viral diseases

Emerging viruses such as HIV, dengue, influenza A, SARS coronavirus, Ebola, and other viruses pose a significant threat to human health. Majority of these viruses are responsible for the outbreaks of pathogenic lethal infections. To date, there are no effective therapeutic strategies available for the prophylaxis and treatment of these infections. Chloroquine analogs have been used for decades as the primary and most successful drugs against malaria. Concomitant with the emergence of chloroquine‐resistant Plasmodium strains and a subsequent decrease in the use as antimalarial drugs, other applications of the analogs have been investigated. Since the analogs have interesting biochemical properties, these drugs are found to be effective against a wide variety of viral infections. As antiviral action, the analogs have been shown to inhibit acidification of endosome during the events of replication and infection. Moreover, immunomodulatory effects of analogs have been beneficial to patients with severe inflammatory complications of several viral diseases. Interestingly, one of the successful targeting strategies is the inhibition of HIV replication by the analogs in vitro which are being tested in several clinical trials. This review focuses on the potentialities of chloroquine analogs for the treatment of endosomal low pH dependent emerging viral diseases.

Integrated Computational Approach for Virtual Hit Identification against Ebola Viral Proteins VP35 and VP40

The Ebola virus (EBOV) has been recognised for nearly 40 years, with the most recent EBOV outbreak being in West Africa, where it created a humanitarian crisis. Mortalities reported up to 30 March 2016 totalled 11,307. However, up until now, EBOV drugs have been far from achieving regulatory (FDA) approval. It is therefore essential to identify parent compounds that have the potential to be developed into effective drugs. Studies on Ebola viral proteins have shown that some can elicit an immunological response in mice, and these are now considered essential components of a vaccine designed to protect against Ebola haemorrhagic fever. The current study focuses on chemoinformatic approaches to identify virtual hits against Ebola viral proteins (VP35 and VP40), including protein binding site prediction, drug-likeness, pharmacokinetic and pharmacodynamic properties, metabolic site prediction, and molecular docking. Retrospective validation was performed using a database of non-active compounds, and early enrichment of EBOV actives at different false positive rates was calculated. Homology modelling and subsequent superimposition of binding site residues on other strains of EBOV were carried out to check residual conformations, and hence to confirm the efficacy of potential compounds. As a mechanism for artefactual inhibition of proteins through non-specific compounds, virtual hits were assessed for their aggregator potential compared with previously reported aggregators. These systematic studies have indicated that a few compounds may be effective inhibitors of EBOV replication and therefore might have the potential to be developed as anti-EBOV drugs after subsequent testing and validation in experiments in vivo.

Discriminating agonist and antagonist ligands of the nuclear receptors using 3D-pharmacophores

Nuclear receptors (NRs) constitute an important class of therapeutic targets. We evaluated the performance of 3D structure-based and ligand-based pharmacophore models in predicting the pharmacological profile of NRs ligands using the NRLiSt BDB database. We could generate selective pharmacophores for agonist and antagonist ligands and we found that the best performances were obtained by combining the structure-based and the ligand-based approaches. The combination of pharmacophores that were generated allowed to cover most of the chemical space of the NRLiSt BDB datasets. By screening the whole NRLiSt BDB on our 3D pharmacophores, we demonstrated their selectivity towards their dedicated NRs ligands. The 3D pharmacophores herein presented can thus be used as a predictor of the pharmacological activity of NRs ligands.Graphical AbstractUsing a combination of structure-based and ligand-based pharmacophores, agonist and antagonist ligands of the Nuclear Receptors included in the NRLiSt BDB database could be separated.

Chloroquine inhibited Ebola virus replication in vitro but failed to protect against infection and disease in the in vivo guinea pig model

Ebola virus (EBOV) is highly pathogenic, with a predisposition to cause outbreaks in human populations accompanied by significant mortality. Owing to the lack of approved therapies, screening programmes of potentially efficacious drugs have been undertaken. One of these studies has demonstrated the possible utility of chloroquine against EBOV using pseudotyped assays. In mouse models of EBOV disease there are conflicting reports of the therapeutic effects of chloroquine. There are currently no reports of its efficacy using the larger and more stringent guinea pig model of infection. In this study we have shown that replication of live EBOV is impaired by chloroquine in vitro. However, no protective effects were observed in vivo when EBOV-infected guinea pigs were treated with chloroquine. These results advocate that chloroquine should not be considered as a treatment strategy for EBOV.

Development of Small-Molecule Antivirals for Ebola

Ebola hemorrhagic fever is a deadly disease caused by infection with one of the Ebola virus species. Although a significant progress has recently been made in understanding of Ebola virus biology and pathogenesis, development of effective anti-Ebola treatments has not been very productive, compared to other areas of antiviral research (e.g., HIV and HCV infections). No approved vaccine or medicine is available for Ebola but several are currently under development. This review summarises attempts in identification, evaluation, and development of small-molecule candidates for treatment of Ebola viral disease, including the most promising experimental drugs brincidofovir (CMX001), BCX4430, and favipiravir (T-705).

Small molecules with antiviral activity against the Ebola virus

The recent outbreak of the Ebola virus in West Africa has highlighted the clear shortage of broad-spectrum antiviral drugs for emerging viruses. There are numerous FDA approved drugs and other small molecules described in the literature that could be further evaluated for their potential as antiviral compounds. These molecules are in addition to the few new antivirals that have been tested in Ebola patients but were not originally developed against the Ebola virus, and may play an important role as we await an effective vaccine. The balance between using FDA approved drugs versus novel antivirals with minimal safety and no efficacy data in humans should be considered. We have evaluated 55 molecules from the perspective of an experienced medicinal chemist as well as using simple molecular properties and have highlighted 16 compounds that have desirable qualities as well as those that may be less desirable. In addition we propose that a collaborative database for sharing such published and novel information on small molecules is needed for the research community studying the Ebola virus.