Drug Repurposing: New Treatments for Zika Virus Infection?

In silico evidence of Remdesivir action in blood coagulation cascade modulation in COVID-19 treatment

BACKGROUND

Coronavirus disease 2019 (COVID-19) has demonstrated several clinical manifestations which include not only respiratory system issues but also liver, kidney, and other organ injuries. One of these abnormalities is coagulopathies, including thrombosis and disseminated intravascular coagulation. Because of this, the administration of low molecular weight heparin is required for patients that need to be hospitalized. In addition, Remdesivir is an antiviral that was used against Middle East Acute Respiratory Syndrome, Ebola, Acute Respiratory Syndrome, and other diseases, showing satisfactory results on recovery. Besides, there is evidence suggesting that this medication can provide a better prognosis for patients with COVID-19.

AIM

To investigate in silico the interaction between Remdesivir and clotting factors, pursuing a possibility of using it as medicine.

METHODS

In this in silico study, the 3D structures of angiotensin-converting enzyme 2 (ACE2), Factor I (fibrinogen), Factor II (prothrombin), Factor III (thromboplastin), Factor V (proaccelerin), Factor VII (proconvertin), Factor VIII (antihemophilic factor A), Factor IX (antihemophilic factor B), Factor X (Stuart-Prower factor), and Factor XI (precursor of thromboplastin (these structures are technically called receptors) were selected from the Protein Data Bank. The structures of the antivirals Remdesivir and Osetalmivir (these structures are called ligands) were selected from the PubChem database, while the structure of Atazanavir was selected from the ZINC database. The software AutoDock Tools (ADT) was used to prepare the receptors for molecular docking. Ions, peptides, water molecules, and other ones were removed from each ligand, and then, hydrogen atoms were added to the structures. The grid box was delimited and calculated using the same software ADT. A physiological environment with pH 7.4 is needed to make the ligands interact with the receptors, and still the software Marvin sketch^® (ChemAxon^®) was used to forecast the protonation state. To perform molecular docking, ADT and Vina software was connected. Using PyMol^® software and Discovery studio^® software from BIOVIA, it was possible to analyze the amino acid residues from receptors that were involved in the interactions with the ligands. Ligand tortions, atoms that participated in the interactions, and the type, strength, and duration of the interactions were also analyzed using those software.

RESULTS

Molecular docking analysis showed that Remdesivir and ACE2 had an affinity energy of -8.8 kcal/moL, forming a complex with eight hydrogen bonds involving seven atoms of Remdesivir and five amino acid residues of ACE2. Remdesivir and prothrombin had an interaction with six hydrogen bonds involving atoms of the drug and five amino acid residues of the clotting factor. Similar to that, Remdesivir and thromboplastin presented interactions via seven hydrogen bonds involving five atoms of the drug and four residues of the clotting factor. While Remdesivir and Factor V established a complex with seven hydrogen bonds between six antiviral atoms and six amino acid residues from the factor, and Factor VII connected with the drug by four hydrogen bonds, which involved three atoms of the drug and three residues of amino acids of the factor. The complex between Remdesivir and Factor IX formed an interaction via 11 hydrophilic bonds with seven atoms of the drug and seven residues of the clotting factor, plus one electrostatic bond and three hydrophobic interactions. Factor X and Remdesivir had an affinity energy of -9.6 kcal/moL, and the complex presented 10 hydrogen bonds and 14 different hydrophobic interactions which involved nine atoms of the drug and 16 amino acid residues of the clotting factor. The interaction between Remdesivir and Factor XI formed five hydrogen bonds involving five amino acid residues of the clotting factor and five of the antiviral atoms.

CONCLUSION

Because of the in silico significant affinity, Remdesivir possibly could act in the severe acute respiratory syndrome coronavirus 2 infection blockade by interacting with ACE2 and concomitantly act in the modulation of the coagulation cascade preventing the hypercoagulable state.

Recent advances in the development of methyltransferase (MTase) inhibitors against (re)emerging arboviruses diseases dengue and Zika

Emerging and/or re-emerging viral diseases such as dengue and Zika are a worldwide concern. Therefore, new antiviral therapeutics are necessary. In this sense, a non-structural protein with methyltransferase (MTase) activity is an attractive drug target because it plays a crucial role in dengue and Zika virus replication. Different drug strategies such as virtual screening, molecular docking, and molecular dynamics have identified new inhibitors that bind on the MTase active site. Therefore, in this review, we analyze MTase inhibitors, including S-adenosyl-L-methionine (SAM), S-adenosyl-l-homocysteine (SAH) and guanosine-5'-triphosphate (GTP) analogs, nitrogen-containing heterocycles (pyrimidine, adenosine, and pyridine), urea derivatives, and natural products. Advances in the design of MTase inhibitors could lead to the optimization of a possible single or broad-spectrum antiviral drug against dengue and Zika virus.

Virtual Screening of FDA-Approved Drugs for Enhanced Binding with Mitochondrial Aldehyde Dehydrogenase

Mitochondrial aldehyde dehydrogenase (ALDH2) is a potential target for the treatment of substance use disorders such as alcohol addiction. Here, we adopted computational methods of molecular dynamics (MD) simulation, docking, and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) analysis to perform a virtual screening of FDA-approved drugs, hitting potent inhibitors against ALDH2. Using MD-derived conformations as receptors, butenafine (net charge q = +1 e) and olaparib (q = 0) were selected as promising compounds with a low toxicity and a binding strength equal to or stronger than previously reported potent inhibitors of daidzin and CVT-10216. A few negatively charged compounds were also hit from the docking with the Autodock Vina software, while the MM-PBSA analysis yielded positive binding energies (unfavorable binding) for these compounds, mainly owing to electrostatic repulsion in association with a negatively charged receptor (q = -6 e for ALDH2 plus the cofactor NAD⁺). This revealed a deficiency of the Vina scoring in dealing with strong charge-charge interactions between binding partners, due to its built-in protocol of not using atomic charges for electrostatic interactions. These observations indicated a requirement of further verification using MD and/or MM-PBSA after docking prediction. The identification of key residues for the binding implied that the receptor residues at the bottom and entrance of the substrate-binding hydrophobic tunnel were able to offer additional interactions with different inhibitors such as π-π, π-alkyl, van der Waals contacts, and polar interactions, and that the rational use of these interactions is beneficial to the design of potent inhibitors against ALDH2.

Repurposing of potential antiviral drugs against RNA-dependent RNA polymerase of SARS-CoV-2 by computational approach

The high incidences of COVID-19 cases are believed to be associated with high transmissibility rates, which emphasizes the need for the discovery of evidence-based antiviral therapies for curing the disease. The rationale of repurposing existing classes of antiviral small molecule therapeutics against SARS-CoV-2 infection has been expected to accelerate the tedious and expensive drug development process. While Remdesivir has been recently approved to be the first treatment option for specific groups of COVID-19 patients, combinatory therapy with potential antiviral drugs may be necessary to enhance the efficacy in different populations. Hence, a comprehensive list of investigational antimicrobial drug compounds such as Favipiravir, Fidaxomicin, Galidesivir, GC376, Ribavirin, Rifabutin, and Umifenovir were computationally evaluated in this study. We performed in silico docking and molecular dynamics simulation on the selected small molecules against RNA-dependent RNA polymerase, which is one of the key target proteins of SARS-CoV-2, using AutoDock and GROMACS. Interestingly, our results revealed that the macrocyclic antibiotic, Fidaxomicin, possesses the highest binding affinity with the lowest energy value of -8.97 kcal/mol binding to the same active sites of RdRp. GC376, Rifabutin, Umifenovir and Remdesivir were identified as the next best compounds. Therefore, the above-mentioned compounds could be considered good leads for further preclinical and clinical experimentations as potentially efficient antiviral inhibitors for combination therapies against SARS-CoV-2.

Drugs to limit Zika virus infection and implication for maternal-fetal health

Although the placenta has robust defense mechanisms that protect the fetus from a viral infection, some viruses can manipulate or evade these mechanisms and disrupt physiology or cross the placental barrier. It is well established that the Zika virus is capable of vertical transmission from mother to fetus and can cause malformation of the fetal central nervous system (i.e., microcephaly), as well as Guillain-Barre syndrome in adults. This review seeks to gather and assess the contributions of translational research associated with Zika virus infection, including maternal-fetal vertical transmission of the virus. Nearly 200 inhibitors that have been evaluated in vivo and/or in vitro for their therapeutic properties against the Zika virus are summarized in this review. We also review the status of current vaccine candidates. Our main objective is to provide clinically relevant information that can guide future research directions and strategies for optimized treatment and preventive care of infections caused by Zika virus or similar pathogens.

SperoPredictor: An Integrated Machine Learning and Molecular Docking-Based Drug Repurposing Framework With Use Case of COVID-19

The global spread of the SARS coronavirus 2 (SARS-CoV-2), its manifestation in human hosts as a contagious disease, and its variants have induced a pandemic resulting in the deaths of over 6,000,000 people. Extensive efforts have been devoted to drug research to cure and refrain the spread of COVID-19, but only one drug has received FDA approval yet. Traditional drug discovery is inefficient, costly, and unable to react to pandemic threats. Drug repurposing represents an effective strategy for drug discovery and reduces the time and cost compared to de novo drug discovery. In this study, a generic drug repurposing framework (SperoPredictor) has been developed which systematically integrates the various types of drugs and disease data and takes the advantage of machine learning (Random Forest, Tree Ensemble, and Gradient Boosted Trees) to repurpose potential drug candidates against any disease of interest. Drug and disease data for FDA-approved drugs (n = 2,865), containing four drug features and three disease features, were collected from chemical and biological databases and integrated with the form of drug-disease association tables. The resulting dataset was split into 70% for training, 15% for testing, and the remaining 15% for validation. The testing and validation accuracies of the models were 99.3% for Random Forest and 99.03% for Tree Ensemble. In practice, SperoPredictor identified 25 potential drug candidates against 6 human host-target proteomes identified from a systematic review of journals. Literature-based validation indicated 12 of 25 predicted drugs (48%) have been already used for COVID-19 followed by molecular docking and re-docking which indicated 4 of 13 drugs (30%) as potential candidates against COVID-19 to be pre-clinically and clinically validated. Finally, SperoPredictor results illustrated the ability of the platform to be rapidly deployed to repurpose the drugs as a rapid response to emergent situations (like COVID-19 and other pandemics).

A Network-Biology led Computational Drug repurposing Strategy to prioritize therapeutic options for COVID-19

The alarming pandemic situation of novel Severe Acute Respiratory Syndrome Coronavirus 2 (nSARS-CoV-2) infection, high drug development cost and slow process of drug discovery have made repositioning of existing drugs for therapeutics a popular alternative. It involves the repurposing of existing safe compounds which results in low overall development costs and shorter development timeline. In the present study, a computational network-biology approach has been used for comparing three candidate drugs i.e. quercetin, N-acetyl cysteine (NAC), and 2-deoxy-glucose (2-DG) to be effectively repurposed against COVID-19. For this, the associations between these drugs and genes of Severe Acute Respiratory Syndrome (SARS) and the Middle East Respiratory Syndrome (MERS) diseases were retrieved and a directed drug-gene-gene-disease interaction network was constructed. Further, to quantify the associations between a target gene and a disease gene, the shortest paths from the target gene to the disease genes were identified. A vector DV was calculated to represent the extent to which a disease gene was influenced by these drugs. Quercetin was quantified as the best among the three drugs, suited for repurposing with DV of -70.19, followed by NAC with DV of -39.99 and 2-DG with DV of -13.71. The drugs were also assessed for their safety and efficacy balance (in terms of therapeutic index) using network properties. It was found that quercetin was a forerunner than other two drugs.

Role of artificial intelligence in fast-track drug discovery and vaccine development for COVID-19

COVID-19 is a global pandemic spread across more than 200 countries and several measures are being taken to control it. Researchers in pharmaceutical academia/industry are incessantly targeting this disease through vaccine and drug development protocols. Artificial intelligence is being extensively explored for surveillance, diagnostics, contact tracing, and for clinical management of COVID-19. The most common application has been for repurposing of existing drugs through various AI tools. Successful training of artificial neural networks based on identification of specific patterns in binding of known antiviral drugs with protein sequences from diverse virus species have generated models giving good predictions for molecules against SARS-CoV-2 virus, in sync with clinical studies. ML tools have also been used to investigate immunogenic components of the virus to be exploited as vaccine candidates. In this chapter, the utilization of artificial intelligence to accelerate drug-design and vaccine design research for COVID-19 has been reviewed.

Antitussive noscapine and antiviral drug conjugates as arsenal against COVID-19: a comprehensive chemoinformatics analysis

Coronavirus pandemic has caused a vast number of deaths worldwide. Thus creating an urgent need to develop effective counteragents against novel coronavirus disease (COVID-19). Many antiviral drugs have been repurposed for treatment but implicated minimal recovery, which further advanced the need for clearer insights and innovation to derive effective therapeutics. Strategically, Noscapine, an approved antitussive drug with positive effects on lung linings may show favorable outcomes synergistically with antiviral drugs in trials. Hence, we have theoretically examined the combinatorial drug therapy by culminating the existing experimental results with in silico analyses. We employed the antitussive noscapine in conjugation with antiviral drugs (Chloroquine, Umifenovir, Hydroxychloroquine, Favlplravir and Galidesivir). We found that Noscapine-Hydroxychloroquine (Nos-Hcq) conjugate has strong binding affinity for the main protease (Mpro) of SARS-CoV-2, which performs key biological function in virus infection and progression. Nos-Hcq was analyzed through molecular dynamics simulation. The MD simulation for 100 ns affirmed the stable binding of conjugation unprecedentedly through RMSD and radius of gyration plots along with critical reaction coordinate binding free energy profile. Also, dynamical residue cross-correlation map with principal component analysis depicted the stable binding of Nos-Hcq conjugate to Mpro domains with optimal secondary structure statistics of complex dynamics. Also, we reveal the drugs with stable binding to major domains of Mpro can significantly improve the work profile of reaction coordinates, drug accession and inhibitory regulation of Mpro. The designed combinatorial therapy paves way for further prioritized in vitro and in vivo investigations for drug with robust binding against Mpro of SARS-CoV-2.

Determining reliable parameter estimates for within-host and within-vector models of Zika virus

In this paper, we introduce three within-host and one within-vector models of Zika virus. The within-host models are the target cell limited model, the target cell limited model with natural killer (NK) cells class, and a within-host-within-fetus model of a pregnant individual. The within-vector model includes the Zika virus dynamics in the midgut and salivary glands. The within-host models are not structurally identifiable with respect to data on viral load and NK cell counts. After rescaling, the scaled within-host models are locally structurally identifiable. The within-vector model is structurally identifiable with respect to viremia data in the midgut and salivary glands. Using Monte Carlo Simulations, we find that target cell limited model is practically identifiable from data on viremia; the target cell limited model with NK cell class is practically identifiable, except for the rescaled half saturation constant. The within-host-within-fetus model has all fetus-related parameters not practically identifiable without data on the fetus, as well as the rescaled half saturation constant is also not practically identifiable. The remaining parameters are practically identifiable. Finally we find that none of the parameters of the within-vector model is practically identifiable.

Computational determination of toxicity risks associated with a selection of approved drugs having demonstrated activity against COVID-19

BACKGROUND

The emergence and rapid spread of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) in thelate 2019 has caused a devastating global pandemic of the severe pneumonia-like disease coronavirus disease 2019 (COVID-19). Although vaccines have been and are being developed, they are not accessible to everyone and not everyone can receive these vaccines. Also, it typically takes more than 10 years until a new therapeutic agent is approved for usage. Therefore, repurposing of known drugs can lend itself well as a key approach for significantly expediting the development of new therapies for COVID-19.

METHODS

We have incorporated machine learning-based computational tools and in silico models into the drug discovery process to predict Adsorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) profiles of 90 potential drugs for COVID-19 treatment identified from two independent studies mainly with the purpose of mitigating late-phase failures because of inferior pharmacokinetics and toxicity.

RESULTS

Here, we summarize the cardiotoxicity and general toxicity profiles of 90 potential drugs for COVID-19 treatment and outline the risks of repurposing and propose a stratification of patients accordingly. We shortlist a total of five compounds based on their non-toxic properties.

CONCLUSION

In summary, this manuscript aims to provide a potentially useful source of essential knowledge on toxicity assessment of 90 compounds for healthcare practitioners and researchers to find off-label alternatives for the treatment for COVID-19. The majority of the molecules discussed in this manuscript have already moved into clinical trials and thus their known pharmacological and human safety profiles are expected to facilitate a fast track preclinical and clinical assessment for treating COVID-19.

Topological network based drug repurposing for coronavirus 2019

The COVID-19 pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has become the current health concern and threat to the entire world. Thus, the world needs the fast recognition of appropriate drugs to restrict the spread of this disease. The global effort started to identify the best drug compounds to treat COVID-19, but going through a series of clinical trials and our lack of information about the details of the virus's performance has slowed down the time to reach this goal. In this work, we try to select the subset of human proteins as candidate sets that can bind to approved drugs. Our method is based on the information on human-virus protein interaction and their effect on the biological processes of the host cells. We also define some informative topological and statistical features for proteins in the protein-protein interaction network. We evaluate our selected sets with two groups of drugs. The first group contains the experimental unapproved treatments for COVID-19, and we show that from 17 drugs in this group, 15 drugs are approved by our selected sets. The second group contains the external clinical trials for COVID-19, and we show that 85% of drugs in this group, target at least one protein of our selected sets. We also study COVID-19 associated protein sets and identify proteins that are essential to disease pathology. For this analysis, we use DAVID tools to show and compare disease-associated genes that are contributed between the COVID-19 comorbidities. Our results for shared genes show significant enrichment for cardiovascular-related, hypertension, diabetes type 2, kidney-related and lung-related diseases. In the last part of this work, we recommend 56 potential effective drugs for further research and investigation for COVID-19 treatment. Materials and implementations are available at: https://github.com/MahnazHabibi/Drug-repurposing.

Potential drugs against COVID-19 revealed by gene expression profile, molecular docking and molecular dynamic simulation

Aim: SARS-CoV-2, an emerging betacoronavirus, is the causative agent of COVID-19. Currently, there are few specific and selective antiviral drugs for the treatment and vaccines to prevent contagion. However, their long-term effects can be revealed after several years, and new drugs for COVID-19 should continue to be investigated. Materials & methods: In the first step of our study we identified, through a gene expression analysis, several drugs that could act on the biological pathways altered in COVID-19. In the second step, we performed a docking simulation to test the properties of the identified drugs to target SARS-CoV-2. Results: The drugs that showed a higher binding affinity are bardoxolone (-8.78 kcal/mol), irinotecan (-8.40 kcal/mol) and pyrotinib (-8.40 kcal/mol). Conclusion: We suggested some drugs that could be efficient in treating COVID-19.

Mapping the intellectual structure of the coronavirus field (2000-2020): a co-word analysis

Over the two last decades, coronaviruses have affected human life in different ways, especially in terms of health and economy. Due to the profound effects of novel coronaviruses, growing tides of research are emerging in various research fields. This paper employs a co-word analysis approach to map the intellectual structure of the coronavirus literature for a better understanding of how coronavirus research and the disease itself have developed during the target timeframe. A strategic diagram has been drawn to depict the coronavirus domain's structure and development. A detailed picture of coronavirus literature has been extracted from a huge number of papers to provide a quick overview of the coronavirus literature. The main themes of past coronavirus-related publications are (a) "Antibody-Virus Interactions," (b) "Emerging Infectious Diseases," (c) "Protein Structure-based Drug Design and Antiviral Drug Discovery," (d) "Coronavirus Detection Methods," (e) "Viral Pathogenesis and Immunity," and (f) "Animal Coronaviruses." The emerging infectious diseases are mostly related to fatal diseases (such as Middle East respiratory syndrome, severe acute respiratory syndrome, and COVID-19) and animal coronaviruses (including porcine, turkey, feline, canine, equine, and bovine coronaviruses and infectious bronchitis virus), which are capable of placing animal-dependent industries such as the swine and poultry industries under strong economic pressure. Although considerable research into coronavirus has been done, this unique field has not yet matured sufficiently. Therefore, "Antibody-virus Interactions," "Emerging Infectious Diseases," and "Coronavirus Detection Methods" hold interesting, promising research gaps to be both explored and filled in the future.

Molecular docking, binding mode analysis, molecular dynamics, and prediction of ADMET/toxicity properties of selective potential antiviral agents against SARS-CoV-2 main protease: an effort toward drug repurposing to combat COVID-19

The importance of the main protease (M^pro) enzyme of SARS-CoV-2 in the digestion of viral polyproteins introduces M^pro as an attractive drug target for antiviral drug design. This study aims to carry out the molecular docking, molecular dynamics studies, and prediction of ADMET properties of selected potential antiviral molecules. The study provides an insight into biomolecular interactions to understand the inhibitory mechanism and the spatial orientation of the tested ligands and further, identification of key amino acid residues within the substrate-binding pocket that can be applied for structure-based drug design. In this regard, we carried out molecular docking studies of chloroquine (CQ), hydroxychloroquine (HCQ), remdesivir (RDV), GS441524, arbidol (ARB), and natural product glycyrrhizin (GA) using AutoDock 4.2 tool. To study the drug-receptor complex's stability, selected docking possesses were further subjected to molecular dynamics studies with Schrodinger software. The prediction of ADMET/toxicity properties was carried out on ADMET Prediction™. The docking studies suggested a potential role played by CYS145, HIS163, and GLU166 in the interaction of molecules within the active site of COVID-19 M^pro. In the docking studies, RDV and GA exhibited superiority in binding with the crystal structure of M^pro over the other selected molecules in this study. Spatial orientations of the molecules at the active site of M^pro exposed the significance of S1–S4 subsites and surrounding amino acid residues. Among GA and RDV, RDV showed better and stable interactions with the protein, which is the reason for the lesser RMSD values for RDV. Overall, the present in silico study indicated the direction to combat COVID-19 using FDA-approved drugs as promising agents, which do not need much toxicity studies and could also serve as starting points for lead optimization in drug discovery.

Repositioning Drugs on Human Influenza A Viruses Based on a Novel Nuclear Norm Minimization Method

Influenza A viruses, especially H3N2 and H1N1 subtypes, are viruses that often spread among humans and cause influenza pandemic. There have been several big influenza pandemics that have caused millions of human deaths in history, and the threat of influenza viruses to public health is still serious nowadays due to the frequent antigenic drift and antigenic shift events. However, only few effective anti-flu drugs have been developed to date. The high development cost, long research and development time, and drug side effects are the major bottlenecks, which could be relieved by drug repositioning. In this study, we proposed a novel antiviral Drug Repositioning method based on minimizing Matrix Nuclear Norm (DRMNN). Specifically, a virus-drug correlation database consisting of 34 viruses and 205 antiviral drugs was first curated from public databases and published literature. Together with drug similarity on chemical structure and virus sequence similarity, we formulated the drug repositioning problem as a low-rank matrix completion problem, which was solved by minimizing the nuclear norm of a matrix with a few regularization terms. DRMNN was compared with three recent association prediction algorithms. The AUC of DRMNN in the global fivefold cross-validation (fivefold CV) is 0.8661, and the AUC in the local leave-one-out cross-validation (LOOCV) is 0.6929. Experiments have shown that DRMNN is better than other algorithms in predicting which drugs are effective against influenza A virus. With H3N2 as an example, 10 drugs most likely to be effective against H3N2 viruses were listed, among which six drugs were reported, in other literature, to have some effect on the viruses. The protein docking experiments between the chemical structure of the prioritized drugs and viral hemagglutinin protein also provided evidence for the potential of the predicted drugs for the treatment of influenza.

Repurposing Approved Drugs for Guiding COVID-19 Prophylaxis: A Systematic Review

The SARS-CoV-2 outbreak originally appeared in China in December 2019 and became a global pandemic in March 2020. This infectious disease has directly affected public health and the world economy. Several palliative therapeutic treatments and prophylaxis strategies have been used to control the progress of this viral infection, including pre-(PrEP) and post-exposure prophylaxis. On the other hand, research groups around the world are still studying novel drug prophylaxis and treatment using repurposing approaches, as well as vaccination options, which are in different pre-clinical and clinical testing phases. This systematic review evaluated 1,228 articles from the PubMed and Scopus indexing databases, following the Kitchenham bibliographic searching protocol, with the aim to list drug candidates, potentially approved to be used as new options for SARS-CoV-2 prophylaxis clinical trials and medical protocols. In searching protocol, we used the following keywords: "Covid-19 or SARS-CoV-2" or "Coronavirus or 2019 nCoV," "prophylaxis," "prophylactic," "pre-exposure," "COVID-19 or SARS-CoV-2 Chemoprophylaxis," "repurposed," "strategies," "clinical," "trials," "anti-SARS-CoV-2," "anti-covid-19," "Antiviral," "Therapy prevention in vitro," in cells "and" human testing. After all protocol steps, we selected 60 articles that included: 15 studies with clinical data, 22 studies that used in vitro experiments, seven studies using animal models, and 18 studies performed with in silico experiments. Additionally, we included more 22 compounds between FDA approved drugs and drug-like like molecules, which were tested in large-scale screenings, as well as those repurposed approved drugs with new mechanism of actions. The drugs selected in this review can assist clinical studies and medical guidelines on the rational repurposing of known antiviral drugs for COVID-19 prophylaxis.

Repurposing anticancer drugs for the management of COVID-19

Since its outbreak in the last December, coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 has rapidly spread worldwide at a pandemic proportion and thus is regarded as a global public health emergency. The existing therapeutic options for COVID-19 beyond the intensive supportive care are limited, with an undefined or modest efficacy reported so far. Drug repurposing represents an enthusiastic mechanism to use approved drugs outside the scope of their original indication and accelerate the discovery of new therapeutic options. With the emergence of COVID-19, drug repurposing has been largely applied for early clinical testing. In this review, we discuss some repurposed anticancer drugs for the treatment of COVID-19, which are under investigation in clinical trials or proposed for the clinical testing.

Emerging strategies on in silico drug development against COVID-19: challenges and opportunities

The importance of coronaviruses as human pathogen has been highlighted by the recent outbreak of SARS-CoV-2 leading to the search of suitable drugs to overcome respiratory infections caused by the virus. Due to the lack of specific drugs against coronavirus, the existing antiviral and antimalarial drugs are currently being administered to the patients infected with SARS-CoV-2. The scientists are also considering repurposing of some of the existing drugs as a suitable option in search of effective drugs against coronavirus till the establishment of a potent drug and/or vaccine. Computer-aided drug discovery provides a promising attempt to enable scientists to develop new and target specific drugs to combat any disease. The discovery of novel targets for COVID-19 using computer-aided drug discovery tools requires knowledge of the structure of coronavirus and various target proteins present in the virus. Targeting viral proteins will make the drug specific against the virus, thereby, increasing the chances of viral mortality. Hence, this review provides the structure of SARS-CoV-2 virus along with the important viral components involved in causing infection. It also focuses on the role of various target proteins in disease, the mechanism by which currently administered drugs act against the virus and the repurposing of few drugs. The gap arising from the absence of specific drugs is addressed by proposing potential antiviral drug targets which might provide insights into structure-based drug development against SARS-CoV-2.

Repurposing of FDA-Approved Toremifene to Treat COVID-19 by Blocking the Spike Glycoprotein and NSP14 of SARS-CoV-2

The global pandemic of Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to the death of more than 675,000 worldwide and over 150,000 in the United States alone. However, there are currently no approved effective pharmacotherapies for COVID-19. Here, we combine homology modeling, molecular docking, molecular dynamics simulation, and binding affinity calculations to determine potential targets for toremifene, a selective estrogen receptor modulator which we have previously identified as a SARS-CoV-2 inhibitor. Our results indicate the possibility of inhibition of the spike glycoprotein by toremifene, responsible for aiding in fusion of the viral membrane with the cell membrane, via a perturbation to the fusion core. An interaction between the dimethylamine end of toremifene and residues Q954 and N955 in heptad repeat 1 (HR1) perturbs the structure, causing a shift from what is normally a long, helical region to short helices connected by unstructured regions. Additionally, we found a strong interaction between toremifene and the methyltransferase nonstructural protein (NSP) 14, which could be inhibitory to viral replication via its active site. These results suggest potential structural mechanisms for toremifene by blocking the spike protein and NSP14 of SARS-CoV-2, offering a drug candidate for COVID-19.

In silico molecular docking analysis for repurposing therapeutics against multiple proteins from SARS-CoV-2

SARS-CoV-2 has devastated the world with its rapid spread and fatality. The researchers across the globe are struggling hard to search a drug to treat this infection. Understanding the time constraint, the best approach is to study clinically approved drugs for control of this deadly pandemic of COVID 19. The repurposing of such drugs can be supported with the study of molecular interactions to enhance the possibility of application. The present work is a molecular docking study of proteins responsible for viral propagation namely 3Clpro, Nsp10/16, Spike protein, SARS protein receptor binding domain, Nsp 9 viral single strand binding protein and viral helicase. The protein through virus enters the host cell-human angiotensin-converting enzyme 2 (ACE2) receptor, is also used as a target for molecular docking. The docking was done with most discussed drugs for SARS-CoV-2 like Ritonavir, Lopinavir, Remdesivir, Chloroquine, Hydroxychloroquine (HCQ), routine antiviral drugs like Oseltamivir and Ribavirin. In addition, small molecules with anti-inflammatory actions like Mycophenolic acid (MPA), Pemirolast, Isoniazid and Eriodictyol were also tested. The generated data confirms the potential of Ritonavir, Lopinavir and Remdesivir as a therapeutic candidate against SARS-CoV-2. It is observed that Eriodictyol binds to almost all selected target proteins with good binding energy, suggesting its importance in treatment of COVID 19. Molecular interactions of Ritonavir, Lopinavir and Remdesivir against SARS-CoV-2 proteins enhanced their potential as a candidate drug for treatment of COVID-19. Eriodictyol had emerged as a new repurposing drug that can be used in COVID-19.

Repositioning and investigational drugs for Zika virus infection treatment: a patent review

INTRODUCTION

Zika virus (ZIKV) is transmitted to humans throughout bites of Aedes mosquitoes. ZIKV infection may be asymptomatic in most cases, but it may cause fever, headache, muscle pain, and rash. Guillain-Barré syndrome also may be associated with the infection. Furthermore, the Pan American Health Organization informed 3,715 cases of the congenital ZIKV syndrome (CZS) in the Americas from 2015 - 2017, which may include microcephaly and other craniofacial deformities.

AREAS COVERED

This review identifies patent documents on repositioning for ZIKV infection treatment of already approved drugs or phases II/III investigated drugs for other diseases. Thirty-six patents were found reporting compounds with anti-ZIKV activity with application dates ranging from 2015 to 2019.

EXPERT OPINION

The main drugs claimed in patents were ribavirin, sofosbuvir, and alpha interferons. Preventing CZS is one of the most significant challenges in ZIKV infection. Therefore, repositioning sofosbuvir and niclosamide, that pose no danger for pregnant women, is a particular issue to be considered for clinical tests involving ZIKV disease. Given the substantial costs and developing time of new a drug, repositioning of old drugs is becoming an attractive alternative for diseases with neglected treatments.

Credible Protein Targets and Curative Strategies for COVID-19: a Review

The pandemic of coronavirus infection 2019 (COVID-19) due to the serious respiratory condition created by the coronavirus 2 (SARS-CoV-2) presents a challenge to recognize effective strategies for management and treatment. In general, COVID-19 is an acute disease that can also be fatal, with an ongoing 10.2% case morbidity rate. Extreme illness may bring about death because of enormous alveolar damage and hemorrhage along with progressive respiratory failure. The rapidly expanding information with respect to SARS-CoV-2 research suggests a substantial number of potential drug targets. The most encouraging treatment to date is suggested to be with the help of remdesivir, hydroxychloroquine, and many such repurposed drugs. Remdesivir has a strong in vitro activity for SARS-CoV-2, yet it is not the drug of choice as affirmed by the US Food and Drug Administration and presently is being tried in progressing randomized preliminaries. The COVID-19 pandemic has been the worst worldwide general health emergency of this age and, possibly, since the pandemic influenza outbreak of 1918. The speed and volume of clinical preliminaries propelled to examine potential treatments for COVID-19 feature both the need and capacity to create abundant evidence even in the center of a pandemic. No treatments have been demonstrated as accurate and dependable to date. This review presents a concise precise of the targets and broad treatment strategies for the benefit of researchers.

Identification of therapeutic target in S2 domain of SARS nCov-2 Spike glycoprotein: Key to design and discover drug candidates for inhibition of viral entry into host cell

Humanity is facing a grieve danger of coronavirus disease-19 caused by severe acute respiratory syndrome novel coronavirus-2 (SARS nCov-2). There is an urgent need of therapeutics that can help in overcoming this global pandemic. Identifying novel therapeutic target and screening already approved drug is a faster approach in this situation. Spike glycoprotein (Sgp) of SARS nCoV-2 is potentials target where in researchers have targeted receptor binding domain (RBD) of S1 domain. The S2 domain of Sgp also plays a pivotal role in viral entry, but the mechanism is less understood. We analyzed the structure of Sgp S2 domain in pre-fusion state and Heptad repeat region in its post-fusion state available from protein data bank. Sgp shows three major regions in S2 domain, the fusion peptide (FP), heptad repeat 1 (HR1) and central helical (CH) region. The HR1 region undergoes structural changes by flipping approximately 180∘ and coil up to form a rod like structure during fusion process implying its role in viral entry into the host cell. This structural change in S2 domain helices is crucial step, if this process is hindered by targeting the HR1 and CH region then the progression of virus can be stopped. Possible binding cavity was identified near the HR1 and CH region in S2 domain and docking-based virtual screening of FDA approved drugs was performed. Promising candidates like Troxerutin, Thymopentin and Daclatasvir can be used as therapeutics provided an immediate in-vitro and clinical studies are carried out by research groups.

Investigation of Some Antiviral N-Heterocycles as COVID 19 Drug: Molecular Docking and DFT Calculations

The novel coronavirus, COVID-19, caused by SARS-CoV-2, is a global health pandemic that started in December 2019. The effective drug target among coronaviruses is the main protease M^pro, because of its essential role in processing the polyproteins that are translated from the viral RNA. In this study, the bioactivity of some selected heterocyclic drugs named Favipiravir (1), Amodiaquine (2), 2'-Fluoro-2'-deoxycytidine (3), and Ribavirin (4) was evaluated as inhibitors and nucleotide analogues for COVID-19 using computational modeling strategies. The density functional theory (DFT) calculations were performed to estimate the thermal parameters, dipole moment, polarizability, and molecular electrostatic potential of the present drugs; additionally, Mulliken atomic charges of the drugs as well as the chemical reactivity descriptors were investigated. The nominated drugs were docked on SARS-CoV-2 main protease (PDB: 6LU7) to evaluate the binding affinity of these drugs. Besides, the computations data of DFT the docking simulation studies was predicted that the Amodiaquine (2) has the least binding energy (-7.77 Kcal/mol) and might serve as a good inhibitor to SARS-CoV-2 comparable with the approved medicines, hydroxychloroquine, and remdesivir which have binding affinity -6.06 and -4.96 Kcal/mol, respectively. The high binding affinity of 2 was attributed to the presence of three hydrogen bonds along with different hydrophobic interactions between the drug and the critical amino acids residues of the receptor. Finally, the estimated molecular electrostatic potential results by DFT were used to illustrate the molecular docking findings. The DFT calculations showed that drug 2 has the highest of lying HOMO, electrophilicity index, basicity, and dipole moment. All these parameters could share with different extent to significantly affect the binding affinity of these drugs with the active protein sites.

Mechanistic Insights into Zika Virus NS3 Helicase Inhibition by Epigallocatechin-3-Gallate

Since 2007, repeated outbreaks of Zika virus (ZIKV) have affected millions of people worldwide and created a global health concern with major complications like microcephaly and Guillain Barre's syndrome. To date, there is not a single Zika-specific licensed drug present in the market. However, in recent months, several antiviral molecules have been screened against ZIKV. Among those, (-)-epigallocatechin-3-gallate (EGCG), a green tea polyphenol, has shown great virucidal potential against flaviviruses including ZIKV. The mechanistic understanding of EGCG-targeting viral proteins is not yet entirely deciphered except that little is known about its interaction with viral envelope protein and viral protease. We designed our current study to find inhibitory actions of EGCG against ZIKV NS3 helicase. NS3 helicase performs a significant role in viral replication by unwinding RNA after hydrolyzing NTP. We employed molecular docking and simulation approach and found significant interactions at the ATPase site and also at the RNA binding site. Further, the enzymatic assay has shown significant inhibition of NTPase activity with an IC₅₀ value of 295.7 nM and Ki of 0.387 ± 0.034 μM. Our study suggests the possibility that EGCG could be considered as a prime backbone molecule for further broad-spectrum inhibitor development against ZIKV and other flaviviruses.

Longitudinal [18F]FB-IL-2 PET Imaging to Assess the Immunopathogenicity of O'nyong-nyong Virus Infection

O'nyong-nyong virus (ONNV) is an arthritogenic alphavirus that caused two large epidemics in 1959 and 1996, affecting millions of people in Africa. More recently, sero-surveillance of healthy blood donors conducted in 2019 revealed high rates of unreported ONNV infection in Uganda. Due to similar clinical symptoms with other endemic mosquito-borne pathogens in the region, including chikungunya virus, dengue virus and malaria, ONNV infections are often un- or misdiagnosed. Elucidating the immunopathogenic factors of this re-emerging arbovirus is critical with the expanding geographic distribution of competent vectors. This study reports the establishment of an immune competent C57BL6/J mouse model to mechanistically characterize ONNV infection and assess potential treatment efficacy. This mouse model successfully recapitulated arthralgia and viremia profiles seen in ONNV patients. Furthermore, longitudinal in-vivo PET imaging with [¹⁸F]FB-IL-2 (CD25+CD4+ binding probe) and histopathological assessment in this model demonstrated the pathogenic role of CD4+ T cells in driving joint pathology. Concordantly, in vivo CD4+ T cell depletion, or suppression with fingolimod, an FDA-approved immunomodulating drug, abrogated CD4+ T cell-mediated disease. This study demonstrates the importance of this immune competent ONNV model for future studies on factors influencing disease pathogenesis, which could shape the discovery of novel therapeutic strategies for arthritogenic alphaviruses.

In Silico Discovery of Candidate Drugs against Covid-19

Previous studies reported that Angiotensin converting enzyme 2 (ACE2) is the main cell receptor of SARS-CoV and SARS-CoV-2. It plays a key role in the access of the virus into the cell to produce the final infection. In the present study we investigated in silico the basic mechanism of ACE2 in the lung and provided evidences for new potentially effective drugs for Covid-19. Specifically, we used the gene expression profiles from public datasets including The Cancer Genome Atlas, Gene Expression Omnibus and Genotype-Tissue Expression, Gene Ontology and pathway enrichment analysis to investigate the main functions of ACE2-correlated genes. We constructed a protein-protein interaction network containing the genes co-expressed with ACE2. Finally, we focused on the genes in the network that are already associated with known drugs and evaluated their role for a potential treatment of Covid-19. Our results demonstrate that the genes correlated with ACE2 are mainly enriched in the sterol biosynthetic process, Aryldialkylphosphatase activity, adenosylhomocysteinase activity, trialkylsulfonium hydrolase activity, acetate-CoA and CoA ligase activity. We identified a network of 193 genes, 222 interactions and 36 potential drugs that could have a crucial role. Among possible interesting drugs for Covid-19 treatment, we found Nimesulide, Fluticasone Propionate, Thiabendazole, Photofrin, Didanosine and Flutamide.

Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2

Human coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus (SARS-CoV) and 2019 novel coronavirus (2019-nCoV, also known as SARS-CoV-2), lead global epidemics with high morbidity and mortality. However, there are currently no effective drugs targeting 2019-nCoV/SARS-CoV-2. Drug repurposing, representing as an effective drug discovery strategy from existing drugs, could shorten the time and reduce the cost compared to de novo drug discovery. In this study, we present an integrative, antiviral drug repurposing methodology implementing a systems pharmacology-based network medicine platform, quantifying the interplay between the HCoV-host interactome and drug targets in the human protein-protein interaction network. Phylogenetic analyses of 15 HCoV whole genomes reveal that 2019-nCoV/SARS-CoV-2 shares the highest nucleotide sequence identity with SARS-CoV (79.7%). Specifically, the envelope and nucleocapsid proteins of 2019-nCoV/SARS-CoV-2 are two evolutionarily conserved regions, having the sequence identities of 96% and 89.6%, respectively, compared to SARS-CoV. Using network proximity analyses of drug targets and HCoV-host interactions in the human interactome, we prioritize 16 potential anti-HCoV repurposable drugs (e.g., melatonin, mercaptopurine, and sirolimus) that are further validated by enrichment analyses of drug-gene signatures and HCoV-induced transcriptomics data in human cell lines. We further identify three potential drug combinations (e.g., sirolimus plus dactinomycin, mercaptopurine plus melatonin, and toremifene plus emodin) captured by the "Complementary Exposure" pattern: the targets of the drugs both hit the HCoV-host subnetwork, but target separate neighborhoods in the human interactome network. In summary, this study offers powerful network-based methodologies for rapid identification of candidate repurposable drugs and potential drug combinations targeting 2019-nCoV/SARS-CoV-2.

Computer-Assisted and Data Driven Approaches for Surveillance, Drug Discovery, and Vaccine Design for the Zika Virus

Human life has been at the edge of catastrophe for millennia due diseases which emerge and reemerge at random. The recent outbreak of the Zika virus (ZIKV) is one such menace that shook the global public health community abruptly. Modern technologies, including computational tools as well as experimental approaches, need to be harnessed fast and effectively in a coordinated manner in order to properly address such challenges. In this paper, based on our earlier research, we have proposed a four-pronged approach to tackle the emerging pathogens like ZIKV: (a) Epidemiological modelling of spread mechanisms of ZIKV; (b) assessment of the public health risk of newly emerging strains of the pathogens by comparing them with existing strains/pathogens using fast computational sequence comparison methods; (c) implementation of vaccine design methods in order to produce a set of probable peptide vaccine candidates for quick synthesis/production and testing in the laboratory; and (d) designing of novel therapeutic molecules and their laboratory testing as well as validation of new drugs or repurposing of drugs for use against ZIKV. For each of these stages, we provide an extensive review of the technical challenges and current state-of-the-art. Further, we outline the future areas of research and discuss how they can work together to proactively combat ZIKV or future emerging pathogens.

Inhibitory Effects of Antiviral Drug Candidates on Canine Parvovirus in F81 cells

Canine parvovirus (CPV) is a common etiological agent of acute enteritis, which occurs globally in domestic and wild carnivores. Despite the widespread use of inactivated or live attenuated vaccines, the emergence of antigenic variants and the influence of maternal antibodies have raised some concerns regarding the efficacy of commercial vaccines. While no specific antiviral therapy for CPV infection exists, the only treatment option for the infection is supportive therapy based on symptoms. Thus, there is an urgent medical need to develop antiviral therapeutic options to reduce the burden of CPV-related disease. In this study, a cytopathic effect (CPE)-based high-throughput screening assay was used to screen CPV inhibitors from a Food and Drug Administration (FDA)-approved drug library. After two rounds of screening, seven out of 1430 screened drugs were found to have >50% CPE inhibition. Three drugs—Nitazoxanide, Closantel Sodium, and Closantel—with higher anti-CPV effects were further evaluated in F81 cells by absolute PCR quantification and indirect immunofluorescence assay (IFA). The inhibitory effects of all three drugs were dose-dependent. Time of addition assay indicated that the drugs inhibited the early processes of the CPV replication cycle, and the inhibition effects were relatively high within 2 h postinfection. Western blot assay also showed that the three drugs had broad-spectrum antiviral activity against different subspecies of three CPV variants. In addition, antiapoptotic effects were observed within 12 h in Nitazoxanide-treated F81 cells regardless of CPV infection, while Closantel Sodium- or Closantel-treated cells had no pro- or antiapoptotic effects. In conclusion, Nitazoxanide, Closantel Sodium, and Closantel can effectively inhibit different subspecies of CPV. Since the safety profiles of FDA-approved drugs have already been extensively studied, these three drugs can potentially become specific and effective anti-CPV drugs.

Identification of a clinical compound losmapimod that blocks Lassa virus entry

Lassa virus (LASV) causes Lassa hemorrhagic fever in humans and poses a significant threat to public health in West Africa. Current therapeutic treatments for Lassa fever are limited, making the development of novel countermeasures an urgent priority. In this study, we identified losmapimod, a p38 mitogen-activated protein kinase (MAPK) inhibitor, from 102 screened compounds as an inhibitor of LASV infection. Losmapimod exerted its inhibitory effect against LASV after p38 MAPK down-regulation, and, interestingly, had no effect on other arenaviruses capable of causing viral hemorrhagic fever. Mechanistic studies showed that losmapimod inhibited LASV entry by affecting the stable signal peptide (SSP)-GP2 subunit interface of the LASV glycoprotein, thereby blocking pH-dependent viral fusion. As an aryl heteroaryl bis-carboxyamide derivative, losmapimod represents a novel chemical scaffold with anti-LASV activity, and it provides a new lead structure for the future development of LASV fusion inhibitors.

Repurposing of FDA-Approved NSAIDs for DPP-4 Inhibition as an Alternative for Diabetes Mellitus Treatment: Computational and in Vitro Study

A drug repurposing strategy could be a potential approach to overcoming the economic costs for diabetes mellitus (DM) treatment incurred by most countries. DM has emerged as a global epidemic, and an increase in the outbreak has led developing countries like Mexico, India, and China to recommend a prevention method as an alternative proposed by their respective healthcare sectors. Incretin-based therapy has been successful in treating diabetes mellitus, and inhibitors like sitagliptin, vildagliptin, saxagliptin, and alogliptin belong to this category. As of now, drug repurposing strategies have not been used to identify existing therapeutics that can become dipeptidyl peptidase-4 (DPP-4) inhibitors. Hence, this work presents the use of bioinformatics tools like the Activity Atlas model, flexible molecular docking simulations, and three-dimensional reference interaction site model (3D-RISM) calculations to assist in repurposing Food and Drug Administration (FDA)-approved drugs into specific nonsteroidal anti-inflammatory medications such as DPP-4 inhibitors. Initially, the Activity Atlas model was constructed based on the top scoring DPP-4 inhibitors, and then the model was used to understand features of nonsteroidal anti-inflammatory drugs (NSAIDs) as a function of electrostatic, hydrophobic, and active shape features of DPP-4 inhibition. The FlexX algorithm was used to infer protein-ligand interacting residues, and binding energy, to predict potential draggability towards the DPP-4 mechanism of action. 3D-RISM calculations on piroxicam-bound DPP-4 were used to understand the stability of water molecules at the active site. Finally, piroxicam was chosen as the repurposing drug to become a new DPP-4 inhibitor and validated experimentally using fluorescence spectroscopy assay. These findings are novel and provide new insights into the role of piroxicam as a new lead to inhibit DPP-4 and, taking into consideration the biological half-life of piroxicam, it can be proposed as a possible therapeutic strategy for treating diabetes mellitus.

Repositioning salicylanilide anthelmintic drugs to treat adenovirus infections

The repositioning of drugs already approved by regulatory agencies for other indications is an emerging alternative for the development of new antimicrobial therapies. The repositioning process involves lower risks and costs than the de novo development of novel antimicrobial drugs. Currently, infections by adenovirus show a steady increment with a high clinical impact in immunosuppressed and immunocompetent patients. The lack of a safe and efficacious drug to treat these infections supports the search for new antiviral drugs. Here we evaluated the anti-adenovirus activity of niclosanide, oxyclozanide, and rafoxanide, three salicylanilide anthelmintic drugs. Also, we carried out the cytotoxicity evaluation and partial characterization of the mechanism of action of these drugs. The salicylanilide anthelmintic drugs showed significant anti-adenovirus activity at low micromolar concentrations with little cytotoxicity. Moreover, our mechanistic assays suggest differences in the way the drugs exert anti-adenovirus activity. Niclosamide and rafoxanide target transport of the HAdV particle from the endosome to the nuclear envelope, whilst oxyclozanide specifically targets adenovirus immediately early gene E1A transcription. Data suggests that the studied salicylanilide anthelmintic drugs could be suitable for further clinical evaluation for the development of new antiviral drugs to treat infections by adenovirus in immunosuppressed patients and in immunocompetent individuals with community-acquired pneumonia.

In Silico Oncology Drug Repositioning and Polypharmacology

Network-aided in silico approaches have been widely used for prediction of drug-target interactions and evaluation of drug safety to increase the clinical efficiency and productivity during drug discovery and development. Here we review the advances and new progress in this field and summarize the translational applications of several new network-aided in silico approaches we developed recently. In addition, we describe the detailed protocols for a network-aided drug repositioning infrastructure for identification of new targets for old drugs, failed drugs in clinical trials, and new chemical entities. These state-of-the-art network-aided in silico approaches have been used for the discovery and development of broad-acting and targeted clinical therapies for various complex diseases, in particular for oncology drug repositioning. In this chapter, the described network-aided in silico protocols are appropriate for target-centric drug repositioning to various complex diseases, but expertise is still necessary to perform the specific oncology projects based on the cancer targets of interest.

Investigational drugs for the treatment of Zika virus infection: a preclinical and clinical update

INTRODUCTION

The Zika virus (ZIKV) infection results in severe neurological complications and has emerged as a threat to public health worldwide. No drugs or vaccines are available for use in the clinic and the need for novel and effective therapeutic agents is urgent.

AREAS COVERED

This review describes the latest progress of antiviral development for the treatment of ZIKV infection; it primarily focuses on the literature describing 20 potential anti-ZIKV drugs/agents currently being tested in vivo or in clinical trials. The paper also discusses the need for novel ZIKV inhibitors and the critical issues for successful antiviral drug development.

EXPERT OPINION

So far, 20 compounds have been tested in vivo and three in the clinical trials; progressing these compounds to the clinic is a challenge. Novel ZIKV inhibitors that target virus or host factors are urgently needed. Knowledge-driven drug repurposing, structure-based discovery, RNA interference, long noncoding RNAs, miRNAs, and peptide inhibitors may pave the way for the discovery of such novel agents.

Inhibition of adenovirus infection by mifepristone

The repurposing of drugs approved by the regulatory agencies for other indications is emerging as a valuable alternative for the development of new antimicrobial therapies, involving lower risks and costs than the de novo development of novel antimicrobial drugs. Adenovirus infections have showed a steady increment in recent years, with a high clinical impact in both immunosuppressed and immunocompetent patients. In this context, the lack of a specific drug to treat these infections supports the search for new therapeutic alternatives. In this study, we examined the anti-HAdV properties of mifepristone, a commercially available synthetic steroid drug. Mifepristone showed significant in vitro anti-HAdV activity at low micromolar concentrations with little cytotoxicity. Our mechanistic assays suggest that this drug could affect the microtubule transport, interfering with the entry of the virus into the nucleus and therefore inhibiting HAdV infection.

Emetine inhibits Zika and Ebola virus infections through two molecular mechanisms: inhibiting viral replication and decreasing viral entry

The re-emergence of Zika virus (ZIKV) and Ebola virus (EBOV) poses serious and continued threats to the global public health. Effective therapeutics for these maladies is an unmet need. Here, we show that emetine, an anti-protozoal agent, potently inhibits ZIKV and EBOV infection with a low nanomolar half maximal inhibitory concentration (IC₅₀) in vitro and potent activity in vivo. Two mechanisms of action for emetine are identified: the inhibition of ZIKV NS5 polymerase activity and disruption of lysosomal function. Emetine also inhibits EBOV entry. Cephaeline, a desmethyl analog of emetine, which may be better tolerated in patients than emetine, exhibits a similar efficacy against both ZIKV and EBOV infections. Hence, emetine and cephaeline offer pharmaceutical therapies against both ZIKV and EBOV infection.

Zika virus: from an obscurity to a priority

Despite being discovered approximately 70 years ago, Zika virus (ZIKV) has received little attention, until the occurrence of alarming epidemics in the Pacific Islands and Latin America between 2013 and 2016. These series of outbreaks resulted in crippling neurological complications in adults, and congenital deformities in new-borns. The dire outcomes marked ZIKV as a re-emerging pathogen of public health concern. Over a period of two years, extensive studies have been conducted to understand different aspects of ZIKV from pathogen biology to infection, including the immune response during virus-host interplay in established animal models, as well as potential therapeutics against ZIKV infection. The vast diversity of novel findings has added value to ZIKV research, and a strategic consolidation is crucial to encompass the latest advances and developments, as well as missing pieces of the puzzle. This review thus aims to provide a concise yet extensive update on current ZIKV studies.

Zika clinical updates: implications for pediatrics

PURPOSE OF REVIEW

Zika virus (ZIKV), a mosquito-borne flavivirus, has gained recognition over the past few years as an important new cause of congenital infection. As a result, it is critical that pediatricians understand its epidemiology, clinical presentation, clinical sequelae, and management.

RECENT FINDINGS

The recent ZIKV epidemiology, clinical presentation of acute infection in children and complications, perinatal infection, and congenital infection will be summarized in this ZIKV review. This will be followed by a brief summary on ZIKV diagnosis, management, treatment, and prevention.

SUMMARY

The field of clinical research in ZIKV has rapidly evolved over recent months. It is critical that pediatricians continue to stay up-to-date with the continuously evolving understanding of the clinical aspects of ZIKV to ensure optimal identification and management of affected infants and children. Given the recent changes in Centers for Disease Control and Prevention guidelines to limit screening of asymptomatic pregnant women in the United States with possible ZIKV exposure, comprehensive ZIKV clinical knowledge becomes even more crucial.

Comparative analysis of different cell systems for Zika virus (ZIKV) propagation and evaluation of anti-ZIKV compounds in vitro

A strong correlation between Zika virus (ZIKV) infection and severe neurological disease in newborns and occasionally adults has emerged in the Brazilian outbreak. Efficient human cell-based assays are required to test candidate inhibitors of ZIKV replication. The aim of this work was to investigate ZIKV propagation and quantification in different cell lines. The human (U87, A549, Huh7), mosquito (C6/36) and monkey (VERO E6) cell lines tested were all permissive to ZIKV infection. When assessed by plaque forming units (PFU) in three different target cell lines, the maximal production of ZIKV was achieved in Huh7 at day 3 post-infection (6.38±0.44 log₁₀PFU/ml). The C6/36 cell line showed a low and slow production of virus when compared with other cell lines. A549 readout cells generated a larger number of plaques compared to Huh7 but not to VERO E6 cells. ZIKV PFU and RNA titers showed the highest correlation when Huh7 and A549 were used as the producer and readout cells, respectively. Also, U87 cells produced ZIKV RNA titers which were highly correlated with PFU independently from the readout cell line. Using the best virus-cell system, sofosbuvir and ribavirin EC₅₀ were 1.2μM and 1.1μM when measured through plaque assay, and 4.2μM and 5.2μM when measured by quantitative real time PCR (qRT-PCR), respectively. In summary, ZIKV can efficiently infect different human cell lines and rapidly reach peak viral titers. Overall, A549 cells appear to be as efficient as the VERO E6 gold standard for plaque assay allowing the use of human, rather than simian, cells for evaluating candidate anti-ZIKV compounds by the reference assay. The possibility to replace the labor-intensive plaque assay with the more rapid and easy-to-perform qRT-PCR is appealing and warrants further investigation.

Zika in the Americas, year 2: What have we learned? What gaps remain? A report from the Global Virus Network

In response to the outbreak of Zika virus (ZIKV) infection in the Western Hemisphere and the recognition of a causal association with fetal malformations, the Global Virus Network (GVN) assembled an international taskforce of virologists to promote basic research, recommend public health measures and encourage the rapid development of vaccines, antiviral therapies and new diagnostic tests. In this article, taskforce members and other experts review what has been learned about ZIKV-induced disease in humans, its modes of transmission and the cause and nature of associated congenital manifestations. After describing the make-up of the taskforce, we summarize the emergence of ZIKV in the Americas, Africa and Asia, its spread by mosquitoes, and current control measures. We then review the spectrum of primary ZIKV-induced disease in adults and children, sites of persistent infection and sexual transmission, then examine what has been learned about maternal-fetal transmission and the congenital Zika syndrome, including knowledge obtained from studies in laboratory animals. Subsequent sections focus on vaccine development, antiviral therapeutics and new diagnostic tests. After reviewing current understanding of the mechanisms of emergence of Zika virus, we consider the likely future of the pandemic.

Suramin inhibits Zika virus replication by interfering with virus attachment and release of infectious particles

Zika virus (ZIKV) is a mosquito-borne flavivirus that mostly causes asymptomatic infections or mild disease characterized by low-grade fever, rash, conjunctivitis, and malaise. However, the recent massive ZIKV epidemics in the Americas have also linked ZIKV infection to fetal malformations like microcephaly and Guillain-Barré syndrome in adults, and have uncovered previously unrecognized routes of vertical and sexual transmission. Here we describe inhibition of ZIKV replication by suramin, originally an anti-parasitic drug, which was more recently shown to inhibit multiple viruses. In cell culture-based assays, using reduction of cytopathic effect as read-out, suramin had an EC₅₀ of ∼40 μM and a selectivity index of 48. In single replication cycle experiments, suramin treatment also caused a strong dose-dependent decrease in intracellular ZIKV RNA levels and a >3-log reduction in infectious progeny titers. Time-of-addition experiments revealed that suramin inhibits a very early step of the replication cycle as well as the release of infectious progeny. Only during the first 2 h of infection suramin treatment strongly reduced the fraction of cells that became infected with ZIKV, suggesting the drug affects virus binding/entry. Binding experiments at 4 °C using ³⁵S-labeled ZIKV demonstrated that suramin interferes with attachment to host cells. When suramin treatment was initiated post-entry, viral RNA synthesis was unaffected, while both the release of genomes and the infectivity of ZIKV were reduced. This suggests the compound also affects virion biogenesis, possibly by interfering with glycosylation and the maturation of ZIKV during its traffic through the secretory pathway. The inhibitory effect of suramin on ZIKV attachment and virion biogenesis and its broad-spectrum activity warrant further evaluation of this compound as a potential therapeutic.

Heparin prevents Zika virus induced-cytopathic effects in human neural progenitor cells

The recent Zika virus (ZIKV) outbreak, which mainly affected Brazil and neighbouring states, demonstrated the paucity of information concerning the epidemiology of several flaviruses, but also highlighted the lack of available agents with which to treat such emerging diseases. Here, we show that heparin, a widely used anticoagulant, while exerting a modest inhibitory effect on Zika Virus replication, fully prevents virus-induced cell death of human neural progenitor cells (NPCs).

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Recent outbreak of Zika virus in Brazil included widespread neurological effects.

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One approach to tackling emerging infection is to re-purpose existing pharmaceuticals.

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The anticoagulant, heparin, inhibits infection weakly, but completely prevents cell death.

Advances in Developing Therapies to Combat Zika Virus: Current Knowledge and Future Perspectives

Zika virus (ZIKV) remained largely quiescent for nearly six decades after its first appearance in 1947. ZIKV reappeared after 2007, resulting in a declaration of an international "public health emergency" in 2016 by the World Health Organization (WHO). Until this time, ZIKV was considered to induce only mild illness, but it has now been established as the cause of severe clinical manifestations, including fetal anomalies, neurological problems, and autoimmune disorders. Infection during pregnancy can cause congenital brain abnormalities, including microcephaly and neurological degeneration, and in other cases, Guillain-Barré syndrome, making infections with ZIKV a substantial public health concern. Genomic and molecular investigations are underway to investigate ZIKV pathology and its recent enhanced pathogenicity, as well as to design safe and potent vaccines, drugs, and therapeutics. This review describes progress in the design and development of various anti-ZIKV therapeutics, including drugs targeting virus entry into cells and the helicase protein, nucleosides, inhibitors of NS3 protein, small molecules, methyltransferase inhibitors, interferons, repurposed drugs, drugs designed with the aid of computers, neutralizing antibodies, convalescent serum, antibodies that limit antibody-dependent enhancement, and herbal medicines. Additionally, covalent inhibitors of viral protein expression and anti-Toll-like receptor molecules are discussed. To counter ZIKV-associated disease, we need to make rapid progress in developing novel therapies that work effectually to inhibit ZIKV.