Virtual screen for repurposing approved and experimental drugs for candidate inhibitors of EBOLA virus infection

The Role of AI in Drug Discovery

The emergence of Artificial Intelligence (AI) in drug discovery marks a pivotal shift in pharmaceutical research, blending sophisticated computational techniques with conventional scientific exploration to break through enduring obstacles. This review paper elucidates the multifaceted applications of AI across various stages of drug development, highlighting significant advancements and methodologies. It delves into AI's instrumental role in drug design, polypharmacology, chemical synthesis, drug repurposing, and the prediction of drug properties such as toxicity, bioactivity, and physicochemical characteristics. Despite AI's promising advancements, the paper also addresses the challenges and limitations encountered in the field, including data quality, generalizability, computational demands, and ethical considerations. By offering a comprehensive overview of AI's role in drug discovery, this paper underscores the technology's potential to significantly enhance drug development, while also acknowledging the hurdles that must be overcome to fully realize its benefits.

DeepBindBC: a practical deep learning method for identifying native-like protein-ligand complexes in virtual screening

Identifying native-like protein-ligand complexes (PLCs) from an abundance of docking decoys is critical for large-scale virtual drug screening in early-stage drug discovery lead searching efforts. Providing reliable prediction is still a challenge for most current affinity predicting models because of a lack of non-binding data during model training, lost critical physical-chemical features, and difficulties in learning abstract information with limited neural layers. In this work, we proposed a deep learning model, DeepBindBC, for classifying putative ligands as binding or non-binding. Our model incorporates information on non-binding interactions, making it more suitable for real applications. ResNet model architecture and more detailed atom type representation guarantee implicit features can be learned more accurately. Here, we show that DeepBindBC outperforms Autodock Vina, Pafnucy, and DLSCORE for three DUD.E testing sets. Moreover, DeepBindBC identified a novel human pancreatic α-amylase binder validated by a fluorescence spectral experiment (K_a= 1.0×10⁵ M). Furthermore, DeepBindBC can be used as a core component of a hybrid virtual screening pipeline that incorporating many other complementary methods, such as DFCNN, Autodock Vina docking, and pocket molecular dynamics simulation. Additionally, an online web server based on the model is available at http://cbblab.siat.ac.cn/DeepBindBC/index.php for the user's convenience. Our model and the web server provide alternative tools in the early steps of drug discovery by providing accurate identification of native-like PLCs.

The Potential of 2-Substituted Quinolines as Antileishmanial Drug Candidates

There is a need for new, cost-effective drugs to treat leishmaniasis. A strategy based on traditional medicine practiced in Bolivia led to the discovery of the 2-substituted quinoline series as a source of molecules with antileishmanial activity and low toxicity. This review documents the development of the series from the first isolated natural compounds through several hundred synthetized molecules to an optimized compound exhibiting an in vitro IC₅₀ value of 0.2 µM against Leishmania donovani, and a selectivity index value of 187, together with in vivo activity on the L. donovani/hamster model. Attempts to establish structure–activity relationships are described, as well as studies that have attempted to determine the mechanism of action. For the latter, it appears that molecules of this series act on multiple targets, possibly including the immune system, which could explain the observed lack of drug resistance after in vitro drug pressure. We also show how nanotechnology strategies could valorize these drugs through adapted formulations and how a mechanistic targeting approach could generate new compounds with increased activity.

Advances in antibiotic drug discovery: reducing the barriers for antibiotic development

Antibiotic drug discovery has been an essential field of research since the early 1900s, but the threat from infectious bacteria has only increased over the decades because of the emergence of widespread multidrug resistance. In this review, we discuss the recent advances in natural product, computational and medicinal chemistry that have reinvigorated the field of antibiotic drug discovery while giving perspective on how easily, both in cost and in expertise, these methods can be implemented by other researchers with the goal of increasing the number of scientists contributing to this public health crisis.

Drug targets for COVID-19 therapeutics: Ongoing global efforts

The current global pandemic COVID-19 caused by the SARS-CoV-2 virus has already inflicted insurmountable damage both to the human lives and global economy. There is an immediate need for identification of effective drugs to contain the disastrous virus outbreak. Global efforts are already underway at a war footing to identify the best drug combination to address the disease. In this review, an attempt has been made to understand the SARS-CoV-2 life cycle, and based on this information potential druggable targets against SARS-CoV-2 are summarized. Also, the strategies for ongoing and future drug discovery against the SARS-CoV-2 virus are outlined. Given the urgency to find a definitive cure, ongoing drug repurposing efforts being carried out by various organizations are also described. The unprecedented crisis requires extraordinary efforts from the scientific community to effectively address the issue and prevent further loss of human lives and health.

Inhibition of in vitro Ebola infection by anti-parasitic quinoline derivatives

There continues to be no approved drugs for the treatment of Ebola virus disease (EVD). Despite a number of candidate drugs showing limited efficacy in vitro and/or in non-human primate studies, EVD continues to plaque certain areas of Africa without any efficacious treatments yet available. Recently, we have been exploring the potential for anti-malarial drugs to inhibit an in vitro model of Ebola Zaire replication using a transcription-competent virus-like particle (trVLP) assay. We examined the efficacy of chloroquine, amodiaquine and 36 novel anti-parasite quinoline derivatives at inhibiting Ebola virus replication. Drug efficacy was tested by trVLP assay and toxicity by MTT assay. Both chloroquine and amodiaquine were effective for inhibition of Ebola virus replication without significant toxicity. The half-maximal inhibitory concentration (IC ₅₀) of chloroquine and amodiaquine to inhibit Ebola virus replication were IC _{50, Chl} = 3.95 µM and IC _{50, Amo} = 1.45 µM, respectively. Additionally, three novel quinoline derivatives were identified as having inhibitory activity and low toxicity for Ebola trVLP replication, with 2NH2Q being the most promising derivative, with an IC ₅₀ of 4.66 µM. Quinoline compounds offer many advantages for disease treatment in tropical climates as they are cheap to produce, easy to synthesize and chemically stable. In this report, we have demonstrated the potential of anti-parasite quinolines for further investigation for use in EVD.

A computational approach yields selective inhibitors of human excitatory amino acid transporter 2 (EAAT2)

Excitatory amino acid transporters (EAATs) represent a protein family that is an emerging drug target with great therapeutic potential for managing central nervous system disorders characterized by dysregulation of glutamatergic neurotransmission. As such, it is of significant interest to discover selective modulators of EAAT2 function. Here, we applied computational methods to identify specific EAAT2 inhibitors. Utilizing a homology model of human EAAT2, we identified a binding pocket at the interface of the transport and trimerization domain. We next conducted a high-throughput virtual screen against this site and identified a selective class of EAAT2 inhibitors that were tested in glutamate uptake and whole-cell electrophysiology assays. These compounds represent potentially useful pharmacological tools suitable for further exploration of the therapeutic potential of EAAT2 and may provide molecular insights into mechanisms of allosteric modulation for glutamate transporters.

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.

Virtual Screen for Repurposing of Drugs for Candidate Influenza a M2 Ion-Channel Inhibitors

Influenza A virus (IAV) matrix protein 2 (M2), an ion channel, is crucial for virus infection, and therefore, an important anti-influenza drug target. Adamantanes, also known as M2 channel blockers, are one of the two classes of Food and Drug Administration-approved anti-influenza drugs, although their use was discontinued due to prevalent drug resistance. Fast emergence of resistance to current anti-influenza drugs have raised an urgent need for developing new anti-influenza drugs against resistant forms of circulating viruses. Here we propose a simple theoretical criterion for fast virtual screening of molecular libraries for candidate anti-influenza ion channel inhibitors both for wild type and adamantane-resistant influenza A viruses. After in silico screening of drug space using the EIIP/AQVN filter and further filtering of drugs by ligand based virtual screening and molecular docking we propose the best candidate drugs as potential dual inhibitors of wild type and adamantane-resistant influenza A viruses. Finally, guanethidine, the best ranked drug selected from ligand-based virtual screening, was experimentally tested. The experimental results show measurable anti-influenza activity of guanethidine in cell culture.

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.

Advances in Designing and Developing Vaccines, Drugs, and Therapies to Counter Ebola Virus

Ebola virus (EBOV), a member of the family Filoviridae, is responsible for causing Ebola virus disease (EVD) (formerly named Ebola hemorrhagic fever). This is a severe, often fatal illness with mortality rates varying from 50 to 90% in humans. Although the virus and associated disease has been recognized since 1976, it was only when the recent outbreak of EBOV in 2014-2016 highlighted the danger and global impact of this virus, necessitating the need for coming up with the effective vaccines and drugs to counter its pandemic threat. Albeit no commercial vaccine is available so far against EBOV, a few vaccine candidates are under evaluation and clinical trials to assess their prophylactic efficacy. These include recombinant viral vector (recombinant vesicular stomatitis virus vector, chimpanzee adenovirus type 3-vector, and modified vaccinia Ankara virus), Ebola virus-like particles, virus-like replicon particles, DNA, and plant-based vaccines. Due to improvement in the field of genomics and proteomics, epitope-targeted vaccines have gained top priority. Correspondingly, several therapies have also been developed, including immunoglobulins against specific viral structures small cell-penetrating antibody fragments that target intracellular EBOV proteins. Small interfering RNAs and oligomer-mediated inhibition have also been verified for EVD treatment. Other treatment options include viral entry inhibitors, transfusion of convalescent blood/serum, neutralizing antibodies, and gene expression inhibitors. Repurposed drugs, which have proven safety profiles, can be adapted after high-throughput screening for efficacy and potency for EVD treatment. Herbal and other natural products are also being explored for EVD treatment. Further studies to better understand the pathogenesis and antigenic structures of the virus can help in developing an effective vaccine and identifying appropriate antiviral targets. This review presents the recent advances in designing and developing vaccines, drugs, and therapies to counter the EBOV threat.

Susceptibility of paramyxoviruses and filoviruses to inhibition by 2'-monofluoro- and 2'-difluoro-4'-azidocytidine analogs

Ebolaviruses, marburgviruses, and henipaviruses are zoonotic pathogens belonging to the Filoviridae and Paramyxoviridae families. They exemplify viruses that continue to spill over into the human population, causing outbreaks characterized by high mortality and significant clinical sequelae in survivors of infection. There are currently no approved small molecule therapeutics for use in humans against these viruses. In this study, we evaluated the antiviral activity of the nucleoside analog 4'-azidocytidine (4'N₃-C, R1479) and its 2'-monofluoro- and 2'-difluoro-modified analogs (2'F-4'N₃-C and 2'diF-4'N₃-C) against representative paramyxoviruses (Nipah virus, Hendra virus, measles virus, and human parainfluenza virus 3) and filoviruses (Ebola virus, Sudan virus, and Ravn virus). We observed enhanced antiviral activity against paramyxoviruses with both 2'diF-4'N₃-C and 2'F-4'N₃-C compared to R1479. On the other hand, while R1479 and 2'diF-4'N₃-C inhibited filoviruses similarly to paramyxoviruses, we observed 10-fold lower filovirus inhibition by 2'F-4'N₃-C. To our knowledge, this is the first study to compare the susceptibility of paramyxoviruses and filoviruses to R1479 and its 2'-fluoro-modified analogs. The activity of these compounds against negative-strand RNA viruses endorses the development of 4'-modified nucleoside analogs as broad-spectrum therapeutics against zoonotic viruses of public health importance.

Structure based virtual screening of the Ebola virus trimeric glycoprotein using consensus scoring

Ebola virus (EBOV) causes zoonotic viral infection with a potential risk of global spread and a highly fatal effect on humans. Till date, no drug has gotten market approval for the treatment of Ebola virus disease (EVD), and this perhaps allows the use of both experimental and computational approaches in the antiviral drug discovery process. The main target of potential vaccines that are recently undergoing clinical trials is trimeric glycoprotein (GP) of the EBOV and its exact crystal structure was used in this structure based virtual screening study, with the aid of consensus scoring to select three possible hit compounds from about 36 million compounds in MCULE's database. Amongst these three compounds, (5R)-5-[[5-(4-chlorophenyl)-1,2,4-oxadiazol-3-yl]methyl]-N-[(4-methoxyphenyl)methyl]-4,5-dihydroisoxazole-3-carboxamide (SC-2, C₂₁H₁₉ClN₄O₄) showed good features with respect to drug likeness, ligand efficiency metrics, solubility, absorption and distribution properties and non-carcinogenicity to emerge as the most promising compound that can be optimized to lead compound against the GP EBOV. The binding mode showed that SC-2 is well embedded within the trimeric chains of the GP EBOV with molecular interactions with some amino acids. The SC-2 hit compound, upon its optimization to lead, might be a good potential candidate with efficacy against the EBOV pathogen and subsequently receive necessary approval to be used as antiviral drug for the treatment of EVD.

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.

A simple method for calculation of basic molecular properties of nutrients and their use as a criterion for a healthy diet

Background: Healthy nutrition is vital for good health and well-being. Despite the important role of a healthy nutritional diet, recommendations for healthy eating remain elusive and are mainly based on general properties of nutrients. The present study proposes an improved characterization of the molecular characteristics of nutrients, which are important for biological functions and can be useful in describing a healthy diet. Methods: We investigated the electronic properties of some known nutrient ingredients. In this analysis, we used the average quasi valence number (AQVN) and the electron-ion interaction potential (EIIP), which are molecular descriptors that represent the basic electronic properties of organic molecules.   Results: Our results show that most nutrients can be represented by specific groups of organic compounds according to their basic electronic properties, and these differ from the vast majority of known chemicals. Based on this finding, we have proposed a simple criterion for the selection of food components for healthy nutrition. Discussion: Further studies on the electronic properties of nutrients could serve as a basis for better understanding of their biological functions.

Repurposed Therapeutic Agents Targeting the Ebola Virus: A Systematic Review

BACKGROUND

The Ebola virus has been responsible for numerous outbreaks since the 1970s, with the most recent outbreak taking place between 2014 and 2016 and causing an international public health emergency. Ebola virus disease (EVD) has a high mortality rate and no approved targeted treatment exists to date. A number of established drugs are being considered as potential therapeutic agents for the treatment of EVD.

OBJECTIVE

We aimed to identify potential drug repositioning candidates and to assess the scientific evidence available on their efficacy.

METHODS

We conducted a systematic literature search in MEDLINE, Embase, and other relevant trial registry platforms for studies published between January 1976 and January 2017. We included drug screening, preclinical studies, and clinical studies on repurposed drugs for the treatment of EVD. The risk of bias for animal studies and nonrandomized clinical studies was assessed. The quality of reporting for case series and case reports was evaluated. Finally, we selected drugs approved by established regulatory authorities, which have positive in vitro study outcomes and at least one additional animal or clinical trial.

RESULTS

We identified 3301 publications, of which 37 studies fulfilled our inclusion criteria. Studies were highly heterogeneous in terms of study type, methodology, and intervention. The risk of bias was high for 13 out of 14 animal studies. We selected 11 drugs with potential anti-EVD therapeutic effects and summarized their evidence.

CONCLUSIONS

Several established drugs may have therapeutic effects on EVD, but the quality and quantity of current scientific evidence is lacking. This review highlights the need for well-designed and conducted preclinical and clinical research to establish the efficacy of potential repurposed drugs against EVD.

Identification of Potential Therapeutics to Conquer Drug Resistance in Salmonella typhimurium: Drug Repurposing Strategy

BACKGROUND

Salmonella typhimurium is the main cause of gastrointestinal illness in humans, and treatment options are decreasing because drug-resistant strains have emerged.

OBJECTIVE

The objective of this study was to use computational drug repurposing to identify a novel candidate with an effective mechanism of action to circumvent the drug resistance.

METHODS

We used the Mantra 2.0 database to initially screen drug candidates that share similar gene expression profiles to those of quinolones. Data were further reduced using pharmacophore mapping theory. Finally, we employed molecular-simulation studies to calculate the binding affinity of the screened candidates with DNA gyrase, alongside an analysis of side effects.

RESULTS

A total of 16 drug candidates from the Mantra 2.0 database were screened. The pharmacophoric features of the screened candidates were examined and nalidixic acid features compared using the PharamGist program. A total of 11 compounds with the highest pharmacophore score were considered for binding energy calculation. Finally, we analysed the side effects of the eight drug candidates that showed significant binding affinity in the simulation study.

CONCLUSION

Overall, flufenamic acid and sulconazole may be potential drug candidates that could be studied in vitro to assess their resistance profile against Salmonella enterica Typhimurium.

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.

Arginase Flavonoid Anti-Leishmanial in Silico Inhibitors Flagged against Anti-Targets

Arginase, a drug target for the treatment of leishmaniasis, is involved in the biosynthesis of polyamines. Flavonoids are interesting natural compounds found in many foods and some of them may inhibit this enzyme. The MetIDB database containing 5667 compounds was screened using an EIIP/AQVN filter and 3D QSAR to find the most promising candidate compounds. In addition, these top hits were screened in silico versus human arginase and an anti-target battery consisting of cytochromes P450 2a6, 2c9, 3a4, sulfotransferase, and the pregnane-X-receptor in order to flag their possible interactions with these proteins involved in the metabolism of substances. The resulting compounds may have promise to be further developed for the treatment of leishmaniasis.

Machine learning models identify molecules active against the Ebola virus in vitro

The search for small molecule inhibitors of Ebola virus (EBOV) has led to several high throughput screens over the past 3 years. These have identified a range of FDA-approved active pharmaceutical ingredients (APIs) with anti-EBOV activity in vitro and several of which are also active in a mouse infection model. There are millions of additional commercially-available molecules that could be screened for potential activities as anti-EBOV compounds. One way to prioritize compounds for testing is to generate computational models based on the high throughput screening data and then virtually screen compound libraries. In the current study, we have generated Bayesian machine learning models with viral pseudotype entry assay and the EBOV replication assay data. We have validated the models internally and externally. We have also used these models to computationally score the MicroSource library of drugs to select those likely to be potential inhibitors. Three of the highest scoring molecules that were not in the model training sets, quinacrine, pyronaridine and tilorone, were tested in vitro and had EC50 values of 350, 420 and 230 nM, respectively. Pyronaridine is a component of a combination therapy for malaria that was recently approved by the European Medicines Agency, which may make it more readily accessible for clinical testing. Like other known antimalarial drugs active against EBOV, it shares the 4-aminoquinoline scaffold. Tilorone, is an investigational antiviral agent that has shown a broad array of biological activities including cell growth inhibition in cancer cells, antifibrotic properties, α7 nicotinic receptor agonist activity, radioprotective activity and activation of hypoxia inducible factor-1. Quinacrine is an antimalarial but also has use as an anthelmintic. Our results suggest data sets with less than 1,000 molecules can produce validated machine learning models that can in turn be utilized to identify novel EBOV inhibitors in vitro.

Discovery of anti-Ebola drugs: a computational drug repositioning case study

Computational drug repositioning has complemented and guided the experimental drug repositioning assignments in the recent past.

Repurposed therapeutic agents targeting the Ebola virus: a protocol for a systematic review

BACKGROUND

The recent Ebola epidemic in western Africa developed into an acute public health emergency of unprecedented level in modern times. The treatment provided in most cases has been limited to supportive care, as no approved therapies are available to date. Several established, licenced drugs have been suggested as potential repurposed therapeutic agents for Ebola. However, scientific data on their efficacy in treating Ebola is limited. The purpose of this review is to systematically assess scientific evidence on potential drugs targeting Ebola. In specific, we aim to (1) identify drug library screens involving therapeutic agents targeting the Ebola virus, (2) list potential approved drugs identified from drug screens and review their mechanism of action against the Ebola virus and (3) summarise the outcome of preclinical and clinical trials investigating approved drugs targeting the Ebola virus.

METHODS/DESIGN

We will develop comprehensive systematic search strategies and will perform a systematic literature search in MEDLINE, Embase and Cochrane Central Register of Controlled Trials (CENTRAL). Two authors will independently screen the titles, abstracts and the references of all selected articles on the basis of inclusion criteria. These include any available drug screening, preclinical studies and clinical studies examining the efficacy of approved therapeutic agents targeting the Ebola virus. There will be no restrictions on the type of participants, the type of comparator, time or setting. Data extraction and quality assessment will be undertaken by two review authors working independently.

DISCUSSION

This systematic review will provide systematic knowledge on potential repurposed therapeutic agents targeting Ebola. It aims to help guide future investigations on repurposed drugs and avoid repetitive studies.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42015024349.

Machine learning models identify molecules active against the Ebola virus in vitro

The search for small molecule inhibitors of Ebola virus (EBOV) has led to several high throughput screens over the past 3 years. These have identified a range of FDA-approved active pharmaceutical ingredients (APIs) with anti-EBOV activity in vitro and several of which are also active in a mouse infection model. There are millions of additional commercially-available molecules that could be screened for potential activities as anti-EBOV compounds. One way to prioritize compounds for testing is to generate computational models based on the high throughput screening data and then virtually screen compound libraries. In the current study, we have generated Bayesian machine learning models with viral pseudotype entry assay and the EBOV replication assay data. We have validated the models internally and externally. We have also used these models to computationally score the MicroSource library of drugs to select those likely to be potential inhibitors. Three of the highest scoring molecules that were not in the model training sets, quinacrine, pyronaridine and tilorone, were tested in vitro and had EC ₅₀ values of 350, 420 and 230 nM, respectively. Pyronaridine is a component of a combination therapy for malaria that was recently approved by the European Medicines Agency, which may make it more readily accessible for clinical testing. Like other known antimalarial drugs active against EBOV, it shares the 4-aminoquinoline scaffold. Tilorone, is an investigational antiviral agent that has shown a broad array of biological activities including cell growth inhibition in cancer cells, antifibrotic properties, α7 nicotinic receptor agonist activity, radioprotective activity and activation of hypoxia inducible factor-1. Quinacrine is an antimalarial but also has use as an anthelmintic. Our results suggest data sets with less than 1,000 molecules can produce validated machine learning models that can in turn be utilized to identify novel EBOV inhibitors in vitro.

Machine learning models identify molecules active against the Ebola virus in vitro

The search for small molecule inhibitors of Ebola virus (EBOV) has led to several high throughput screens over the past 3 years. These have identified a range of FDA-approved active pharmaceutical ingredients (APIs) with anti-EBOV activity in vitro and several of which are also active in a mouse infection model. There are millions of additional commercially-available molecules that could be screened for potential activities as anti-EBOV compounds. One way to prioritize compounds for testing is to generate computational models based on the high throughput screening data and then virtually screen compound libraries. In the current study, we have generated Bayesian machine learning models with viral pseudotype entry assay and the EBOV replication assay data. We have validated the models internally and externally. We have also used these models to computationally score the MicroSource library of drugs to select those likely to be potential inhibitors. Three of the highest scoring molecules that were not in the model training sets, quinacrine, pyronaridine and tilorone, were tested in vitro and had EC ₅₀ values of 350, 420 and 230 nM, respectively. Pyronaridine is a component of a combination therapy for malaria that was recently approved by the European Medicines Agency, which may make it more readily accessible for clinical testing. Like other known antimalarial drugs active against EBOV, it shares the 4-aminoquinoline scaffold. Tilorone, is an investigational antiviral agent that has shown a broad array of biological activities including cell growth inhibition in cancer cells, antifibrotic properties, α7 nicotinic receptor agonist activity, radioprotective activity and activation of hypoxia inducible factor-1. Quinacrine is an antimalarial but also has use as an anthelmintic. Our results suggest data sets with less than 1,000 molecules can produce validated machine learning models that can in turn be utilized to identify novel EBOV inhibitors in vitro.

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).

In silico analysis suggests repurposing of ibuprofen for prevention and treatment of EBOLA virus disease

The large 2014/2015 Ebola virus outbreak in West Africa points out the urgent need to develop new preventive and therapeutic approaches that are effective against Ebola viruses and  can be rapidly utilized. Recently, a simple theoretical criterion for the virtual screening of molecular libraries for candidate inhibitors of Ebola virus infection was proposed. Using this method the ‘drug space’ was screened and 267 approved and 382 experimental drugs as candidates for treatment of the Ebola virus disease (EVD) have been selected. Detailed analysis of these drugs revealed the non-steroidal anti-inflammatory drug ibuprofen as an inexpensive, widely accessible and minimally toxic candidate for prevention and treatment of EVD. Furthermore, the molecular mechanism underlying this possible protective effect of ibuprofen against EVD is suggested in this article.

Preclinical discovery and development of maraviroc for the treatment of HIV

INTRODUCTION

Maraviroc is a first-in-class antiretroviral (ARV) drug acting on a host cell target (CCR5), which blocks the entry of the HIV virus into the cell. Maraviroc is currently indicated for combination ARV treatment in adults infected only with CCR5-tropic HIV-1.

AREAS COVERED

This drug discovery case history focuses on the key studies that led to the discovery and approval of maraviroc, as well as on post-launch clinical reports. The article is based on the data reported in published preclinical and clinical studies, conference posters and on drug package data.

EXPERT OPINION

The profound understanding of HIV's entry mechanisms has provided a strong biological rationale for targeting the chemokine receptor CCR5. The CCR5-antagonist mariviroc, with its unique mode of action and excellent safety profile, is an important therapeutic option for HIV patients. In general, the authors believe that targeting host factors is a useful approach for combating new and re-emerging transmissible diseases, as well as pathogens that easily become resistant to common antiviral drugs. Maraviroc, offering a potent and safe cellular receptor-mediated pharmacological response to HIV, has paved the way for the development of a new generation of host-targeting antivirals.

FDA approved drugs as potential Ebola treatments

In the search for treatments for the Ebola Virus, multiple screens of FDA drugs have led to the identification of several with promising in vitro activity. These compounds were not originally developed as antivirals and some have been further tested in mouse in vivo models. We put forward the opinion that some of these drugs could be evaluated further and move into the clinic as they are already FDA approved and in many cases readily available. This may be important if there is a further outbreak in future and no other therapeutic is available.

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.

Virtual screen for repurposing approved and experimental drugs for candidate inhibitors of EBOLA virus infection

The ongoing Ebola virus epidemic has presented numerous challenges with respect to control and treatment because there are no approved drugs or vaccines for the Ebola virus disease (EVD). Herein is proposed simple theoretical criterion for fast virtual screening of molecular libraries for candidate inhibitors of Ebola virus infection. We performed a repurposing screen of 6438 drugs from DrugBank using this criterion and selected 267 approved and 382 experimental drugs as candidates for treatment of EVD including 15 anti-malarial drugs and 32 antibiotics. An open source Web server allowing screening of molecular libraries for candidate drugs for treatment of EVD was also established.