Ebola virus: A gap in drug design and discovery - experimental and computational perspective

A Benchmark Dataset for Evaluating Practical Performance of Model Quality Assessment of Homology Models

Protein structure prediction is an important issue in structural bioinformatics. In this process, model quality assessment (MQA), which estimates the accuracy of the predicted structure, is also practically important. Currently, the most commonly used dataset to evaluate the performance of MQA is the critical assessment of the protein structure prediction (CASP) dataset. However, the CASP dataset does not contain enough targets with high-quality models, and thus cannot sufficiently evaluate the MQA performance in practical use. Additionally, most application studies employ homology modeling because of its reliability. However, the CASP dataset includes models generated by de novo methods, which may lead to the mis-estimation of MQA performance. In this study, we created new benchmark datasets, named a homology models dataset for model quality assessment (HMDM), that contain targets with high-quality models derived using homology modeling. We then benchmarked the performance of the MQA methods using the new datasets and compared their performance to that of the classical selection based on the sequence identity of the template proteins. The results showed that model selection by the latest MQA methods using deep learning is better than selection by template sequence identity and classical statistical potentials. Using HMDM, it is possible to verify the MQA performance for high-accuracy homology models.

Antiviral Drug Targets of Single-Stranded RNA Viruses Causing Chronic Human Diseases

Ribonucleic acid (RNA) viruses associated with chronic diseases in humans are major threats to public health causing high mortality globally. The high mutation rate of RNA viruses helps them to escape the immune response and also is responsible for the development of drug resistance. Chronic infections caused by human immunodeficiency virus (HIV) and hepatitis viruses (HBV and HCV) lead to acquired immunodeficiency syndrome (AIDS) and hepatocellular carcinoma respectively, which are one of the major causes of human deaths. Effective preventative measures to limit chronic and re-emerging viral infections are absolutely necessary. Each class of antiviral agents targets a specific stage in the viral life cycle and inhibits them from its development and proliferation. Most often, antiviral drugs target a specific viral protein, therefore only a few broad-spectrum drugs are available. This review will be focused on the selected viral target proteins of pathogenic viruses containing single-stranded (ss) RNA genome that causes chronic infections in humans (e.g. HIV, HCV, Flaviviruses). In the recent past, an exponential increase in the number of available three-dimensional protein structures (>150000 in Protein Data Bank), allowed us to better understand the molecular mechanism of action of protein targets and antivirals. Advancements in the in silico approaches paved the way to design and develop several novels, highly specific small-molecule inhibitors targeting the viral proteins.

Molecular docking enabled updated screening of the matrix protein VP40 from Ebola virus with millions of compounds in the MCULE database for potential inhibitors

Ebola virus is known for several outbreaks of hemorrhagic fever in West Africa. This RNA virus is linked to high fatality and easy transmission. Recently, an effective vaccine and a monoclonal antibody cocktail have been introduced to combat Ebola virus infection. The matrix protein VP40 of Ebola virus is a known drug target and it is essential for viral life cycle through participation in RNA transcription as well as for the budding of the mature virus. It is known that residues phenylalanine 125 and arginine 134 of VP40 are involved in the interaction with RNA. Therefore, it is of interest to screen VP40 with millions of compounds at the mcule.com database for potential inhibitors. The output hits were ranked according to their minimum binding energy to matrix protein VP40. We further calculated the pharmacokinetics and toxicology properties for the best five hits using several predictive ADME analysis web tools. We report a candidate lead (compound #5: ((10R)-10-(4-hydroxyphenyl)-11,12,14,16-tetraazatetracyclo[7.7.0.02,7.011,15] hexadeca-1(16), 2(7),3,5,8,12,14-heptaen-8-ol)) with high drug-likeness score, promising lead-likeness behaviour and high median lethal dose. The candidate lead compound #5 engages in hydrogen bonding and hydrophobic interactions with VP40 active site residues. Thus, the lead compound #5 is recommended for further in vitro and in vivo validations for further consideration.

Pharmacoinformatics-based identification of potential bioactive compounds against Ebola virus protein VP24

BACKGROUND

The impact of Ebola virus disease (EVD) is devastating with concomitant high fatalities. Currently, various drugs and vaccines are at different stages of development, corroborating the need to identify new therapeutic molecules. The VP24 protein of the Ebola virus (EBOV) plays a key role in the pathology and replication of the EVD. The VP24 protein interferes with the host immune response to viral infections and promotes nucleocapsid formation, thus making it a viable drug target. This study sought to identify putative lead compounds from the African flora with potential to inhibit the activity of the EBOV VP24 protein using pharmacoinformatics and molecular docking.

METHODS

An integrated library of 7675 natural products originating from Africa obtained from the AfroDB and NANPDB databases, as well as known inhibitors were screened against VP24 (PDB ID: 4M0Q) utilising AutoDock Vina after energy minimization using GROMACS. The top 19 compounds were physicochemically and pharmacologically profiled using ADMET Predictor™, SwissADME and DataWarrior. The mechanisms of binding between the molecules and EBOV VP24 were characterised using LigPlot+. The performance of the molecular docking was evaluated by generating a receiver operating characteristic (ROC) by screening known inhibitors and decoys against EBOV VP24. The prediction of activity spectra for substances (PASS) and machine learning-based Open Bayesian models were used to predict the anti-viral and anti-Ebola activity of the molecules, respectively.

RESULTS

Four natural products, namely, ZINC000095486070, ZINC000003594643, ZINC000095486008 and sarcophine were found to be potential EBOV VP24-inhibitiory molecules. The molecular docking results showed that ZINC000095486070 had high binding affinity of -9.7 kcal/mol with EBOV VP24, which was greater than those of the known VP24-inhibitors used as standards in the study including Ouabain, Nilotinib, Clomiphene, Torimefene, Miglustat and BCX4430. The area under the curve of the generated ROC for evaluating the performance of the molecular docking was 0.77, which was considered acceptable. The predicted promising molecules were also validated using induced-fit docking with the receptor using Schrödinger and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. The molecules had better binding mechanisms and were pharmacologically profiled to have plausible efficacies, negligible toxicity as well as suitable for designing anti-Ebola scaffolds. ZINC000095486008 and sarcophine (NANPDB135) were predicted to possess anti-viral activity, while ZINC000095486070 and ZINC000003594643 to be anti-Ebola compounds.

CONCLUSION

The identified compounds are potential inhibitors worthy of further development as EBOV biotherapeutic agents. The scaffolds of the compounds could also serve as building blocks for designing novel Ebola inhibitors.

Constraints of Viral RNA Synthesis on Codon Usage of Negative-Strand RNA Virus

Negative-strand RNA viruses (NSVs) include some of the most pathogenic human viruses known. NSVs completely rely on the host cell for protein translation, but their codon usage bias is often different from that of the host. This discrepancy may have originated from the unique mechanism of NSV RNA synthesis in that the genomic RNA sequestered in the nucleocapsid serves as the template. The stability of the genomic RNA in the nucleocapsid appears to regulate its accessibility to the viral RNA polymerase, thus placing constraints on codon usage to balance viral RNA synthesis. By in situ analyses of vesicular stomatitis virus RNA synthesis, specific activities of viral RNA synthesis were correlated with the genomic RNA sequence. It was found that by simply altering the sequence and not the amino acid that it encoded, a significant reduction, up to an ∼750-fold reduction, in viral RNA transcripts occurred. Through subsequent sequence analysis and thermal shift assays, it was found that the purine/pyrimidine content modulates the overall stability of the polymerase complex, resulting in alteration of the activity of viral RNA synthesis. The codon usage is therefore constrained by the obligation of the NSV genome for viral RNA synthesis.IMPORTANCE Negative-strand RNA viruses (NSVs) include the most pathogenic viruses known. New methods to monitor their evolutionary trends are urgently needed for the development of antivirals and vaccines. The protein translation machinery of the host cell is currently recognized as a main genomic regulator of RNA virus evolution, which works especially well for positive-strand RNA viruses. However, this approach fails for NSVs because it does not consider the unique mechanism of their viral RNA synthesis. For NSVs, the viral RNA-dependent RNA polymerase (vRdRp) must gain access to the genome sequestered in the nucleocapsid. Our work suggests a paradigm shift that the interactions between the RNA genome and the nucleocapsid protein regulate the activity of vRdRp, which selects codon usage.

Molecular modelling studies on adamantane-based Ebola virus GP-1 inhibitors using docking, pharmacophore and 3D-QSAR

The pathogenic Ebola virus (EBOV) causes a potential health risk and global spread. To date, few drugs are available for the treatment of Ebola virus disease (EVD) that allow researchers to use computational methods for designing potential drugs. The developed PHASE-based common six-point pharmacophore hypothesis (AADHPR_1) showed the necessity of two hydrogen bond acceptor features, one hydrogen bond donor feature, one hydrophobic group feature, one positively ionizable and one aromatic ring feature for further designing. We developed best 3D-QSAR models with high regression coefficients for the training (r²>0.82) and test (Q²>0.5) sets for both atoms-based and field-based 3D-QSAR models. The molecule 1A-4 (docking score = -4.711 kcal/mol) was obtained as best docked (SP mode) on Ebola virus envelope glycoprotein (PDB ID-3CSY) as compared with the standards oseltamivir (docking score = -4.39 kcal/mol) and zanamivir (docking score = -3.392 kcal/mol). The obtained ZINC hit ZINC58935541 showed a good docking score of -4.892 kcal/mol. The ZINC58935541 molecule also showed a strong binding affinity towards the receptor cavity of Ebola virus envelope glycoprotein when simulated for 1.2 ns. The good QikProp parameters reflect the fact that this molecule, upon optimization into a lead, might become a good candidate for the treatment of EVD.

Homology modeling in drug discovery: Overview, current applications, and future perspectives

Homology modeling is one of the computational structure prediction methods that are used to determine protein 3D structure from its amino acid sequence. It is considered to be the most accurate of the computational structure prediction methods. It consists of multiple steps that are straightforward and easy to apply. There are many tools and servers that are used for homology modeling. There is no single modeling program or server which is superior in every aspect to others. Since the functionality of the model depends on the quality of the generated protein 3D structure, maximizing the quality of homology modeling is crucial. Homology modeling has many applications in the drug discovery process. Since drugs interact with receptors that consist mainly of proteins, protein 3D structure determination, and thus homology modeling is important in drug discovery. Accordingly, there has been the clarification of protein interactions using 3D structures of proteins that are built with homology modeling. This contributes to the identification of novel drug candidates. Homology modeling plays an important role in making drug discovery faster, easier, cheaper, and more practical. As new modeling methods and combinations are introduced, the scope of its applications widens.

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.

A Polyamide Inhibits Replication of Vesicular Stomatitis Virus by Targeting RNA in the Nucleocapsid

Polyamides have been shown to bind double-stranded DNA by complementing the curvature of the minor groove and forming various hydrogen bonds with DNA. Several polyamide molecules have been found to have potent antiviral activities against papillomavirus, a double-stranded DNA virus. By analogy, we reason that polyamides may also interact with the structured RNA bound in the nucleocapsid of a negative-strand RNA virus. Vesicular stomatitis virus (VSV) was selected as a prototype virus to test this possibility since its genomic RNA encapsidated in the nucleocapsid forms a structure resembling one strand of an A-form RNA duplex. One polyamide molecule, UMSL1011, was found to inhibit infection of VSV. To confirm that the polyamide targeted the nucleocapsid, a nucleocapsid-like particle (NLP) was incubated with UMSL1011. The encapsidated RNA in the polyamide-treated NLP was protected from thermo-release and digestion by RNase A. UMSL1011 also inhibits viral RNA synthesis in the intracellular activity assay for the viral RNA-dependent RNA polymerase. The crystal structure revealed that UMSL1011 binds the structured RNA in the nucleocapsid. The conclusion of our studies is that the RNA in the nucleocapsid is a viable antiviral target of polyamides. Since the RNA structure in the nucleocapsid is similar in all negative-strand RNA viruses, polyamides may be optimized to target the specific RNA genome of a negative-strand RNA virus, such as respiratory syncytial virus and Ebola virus.IMPORTANCE Negative-strand RNA viruses (NSVs) include several life-threatening pathogens, such as rabies virus, respiratory syncytial virus, and Ebola virus. There are no effective antiviral drugs against these viruses. Polyamides offer an exceptional opportunity because they may be optimized to target each NSV. Our studies on vesicular stomatitis virus, an NSV, demonstrated that a polyamide molecule could specifically target the viral RNA in the nucleocapsid and inhibit viral growth. The target specificity of the polyamide molecule was proved by its inhibition of thermo-release and RNA nuclease digestion of the RNA bound in a model nucleocapsid, and a crystal structure of the polyamide inside the nucleocapsid. This encouraging observation provided the proof-of-concept rationale for designing polyamides as antiviral drugs against NSVs.

Ebola virus - epidemiology, diagnosis, and control: threat to humans, lessons learnt, and preparedness plans - an update on its 40 year's journey

Ebola virus (EBOV) is an extremely contagious pathogen and causes lethal hemorrhagic fever disease in man and animals. The recently occurred Ebola virus disease (EVD) outbreaks in the West African countries have categorized it as an international health concern. For the virus maintenance and transmission, the non-human primates and reservoir hosts like fruit bats have played a vital role. For curbing the disease timely, we need effective therapeutics/prophylactics, however, in the absence of any approved vaccine, timely diagnosis and monitoring of EBOV remains of utmost importance. The technologically advanced vaccines like a viral-vectored vaccine, DNA vaccine and virus-like particles are underway for testing against EBOV. In the absence of any effective control measure, the adaptation of high standards of biosecurity measures, strict sanitary and hygienic practices, strengthening of surveillance and monitoring systems, imposing appropriate quarantine checks and vigilance on trade, transport, and movement of visitors from EVD endemic countries remains the answer of choice for tackling the EBOV spread. Herein, we converse with the current scenario of EBOV giving due emphasis on animal and veterinary perspectives along with advances in diagnosis and control strategies to be adopted, lessons learned from the recent outbreaks and the global preparedness plans. To retrieve the evolutionary information, we have analyzed a total of 56 genome sequences of various EBOV species submitted between 1976 and 2016 in public databases.

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.