Virtual screening of the inhibitors targeting at the viral protein 40 of Ebola virus
© Karthick et al. 2016
Received: 30 June 2015
Accepted: 28 January 2016
Published: 17 February 2016
The Ebola virus is highly pathogenic and destructive to humans and other primates. The Ebola virus encodes viral protein 40 (VP40), which is highly expressed and regulates the assembly and release of viral particles in the host cell. Because VP40 plays a prominent role in the life cycle of the Ebola virus, it is considered as a key target for antiviral treatment. However, there is currently no FDA-approved drug for treating Ebola virus infection, resulting in an urgent need to develop effective antiviral inhibitors that display good safety profiles in a short duration.
This study aimed to screen the effective lead candidate against Ebola infection. First, the lead molecules were filtered based on the docking score. Second, Lipinski rule of five and the other drug likeliness properties are predicted to assess the safety profile of the lead candidates. Finally, molecular dynamics simulations was performed to validate the lead compound.
Our results revealed that emodin-8-beta-D-glucoside from the Traditional Chinese Medicine Database (TCMD) represents an active lead candidate that targets the Ebola virus by inhibiting the activity of VP40, and displays good pharmacokinetic properties.
This report will considerably assist in the development of the competitive and robust antiviral agents against Ebola infection.
KeywordsEbola VP40 Traditional Chinese Medicine Database Molecular docking Molecular dynamics
Please see Additional file 1 for translations of the abstract into the six official working languages of the United Nations.
The Ebola virus is a virulent pathogen that causes haemorrhagic fever in humans and animals, and that leads to a fatality in nearly 90 % of cases within 7–11 days of infection . The Ebola virus has proven to be dangerous in many African countries, thereby contributing to its higher incidence of death . Ebola carries a negative-sense RNA genome containing seven genes that encode seven different structural proteins: VP24, VP30, VP35, VP40, a glycoprotein, a nucleoprotein and a polymerase (L) . In particular, the major matrix protein VP40 appears to be highly expressed in Ebola virus and plays a vital role in the budding of Ebola virus from the plasma membrane .
Additionally, VP40 participates in host cell RNA metabolism during the replication process [5, 6]. The crystallographic structure of VP40-RNA reveals that the R-134 and F-125 of VP40 mainly interact with RNA . These interactions play a crucial role in octamer formation and promote the replication of the Ebola virus. Mutational studies have shown that F-125 and R-134 mutations partially reduce RNA binding and completely abolish RNA binding and octamer formation, respectively . It is clearlyevident from the literature that the VP40-RNA binding mechanism is crucial in the process of viral transcription at early stages of infection . These studies strongly suggest that the binding of RNA to VP40 could be the critical factors for the successful life cycle of the Ebola virus. Because VP40 plays a vital role in the Ebola virus life cycle, it is considered as a potential target for the treatment of Ebola virus infection. However, the pharmacological inhibition of VP40 has yet to be studied in detail . Meanwhile, no FDA-licensed drug is currently available for the treatment of this lethal infection . Thus, the screening of small molecules against Ebola virus that target VP40 might shed light on the antiviral treatment of this disease.
To address this issue, the Traditional Chinese Medicine (TCM) Database (TCMD)  was used to identify novel, potent lead compounds to combat Ebola infection. At present, Computational approaches plays a vital role in biological research. Virtual screening is one of the most important promising techniques aids in dealing with a large number of lead molecules and ranks them using molecular docking. As of today, many drugs are optimized using computational approaches (Captopril, Dorzolamide, Saquinavir, Zanamivir, Oseltamivir, Aliskiren, Boceprevir, Nolatrexed, TMI-005, LY-517717, Rupintrivir and NVP-AUY922) .
Previous studies have showed that the combination of virtual screening with molecular docking and molecular dynamics approaches can successfully identify novel drug-like molecules for the treatment of infectious diseases [13–18]. In this study, we also predicted the oral toxicity (LD50) of the screened lead compounds to determine their side effects and bioavailability using computational methods.
The crystal structure of the matrix protein VP40 from the Ebola virus was obtained from RCSB . The corresponding PDB code is 1H2C . The three-dimensional structures of the lead compounds were retrieved from the TCMD. The three-dimensional structures of the target proteins were energy-minimized using the GROMACS package, version 4.6.3 [20, 21] adopting the GROMOS43a1 force field parameters before performing the docking analysis. Additional file 2: Figure S1 depicts the overall flow chart of the present study.
Virtual screening is an essential technique that is of immense importance to the field of drug discovery. This method is considered as an alternative approach to experimental screening and has produced an increased success rate in the drug discovery process [22, 23]. Because there is no FDA-approved drug available for treating Ebola virus infection [24–26], we used iScreen to apply a receptor-based virtual screening approach. iScreen is a compact web server for TCM docking and virtual screening . iScreen utilizes the PLANTS package, which is based on colony optimization, as a docking algorithm . This algorithm can efficiently rank the potential lead candidates. The three-dimensional structure of VP40 was used as the input for identifying the optimal lead compounds from TCMD. The RNA-VP40 binding site residues are used for virtual screening of lead compounds.
Molecular docking analysis
The top ranked lead compounds were further evaluated via molecular docking analysis using AutoDock 4.2.6 . We have used different docking algorithms and repeated docking to increase the accuracy and reliability of the docking result and to reduce the false positive outcome. The AutoDock tools were used for the addition of charges and polar hydrogens and the adjustment of other parameters. Additionally, Autogrid was used to generate grid maps and spacing . Furthermore, the Lamarckian genetic algorithm (LGA) was employed to perform molecular docking. Each docking experiment consisted of 10 different docking runs, which were set to terminate after 250,000 energy evaluations. The docking calculation included a population size of 150 and a translational step of 0.2 Å, and the docking results were ranked according to the binding free energy and the frequency of the most probable binding site. Also, the energetic contribution of screened lead compounds and VP40 was analysed using PEARLS . Furthermore, the intermolecular interactions of the complexes were analysed.
Intermolecular interaction analysis
In addition to the binding affinity of the molecules, their inhibitory effect can be determined by analysing their interactions with receptor molecules. In particular, hydrogen bond interactions ensure the stability of drug-receptor complexes. Thus, we use PDBsum  and Chimera  to analyse the intermolecular interactions.
Molecular dynamics simulation
The structures of the docked complexes of VP40 with the screened lead compounds were used as the starting point for MD simulations using the GROMACS package, version 4.6.4 [20, 21] adopting the GROMOS43a1 force field parameters. The structures were solvated in a cubic box with a size of 0.9 nm using periodic boundary conditions and the SPC water model . The topology of the lead compounds was generated using the PRODRG server . Subsequently, energy minimization was performed for both complex structures using the steepest descent energy protocol. Furthermore, the systems were equilibrated by performing a position-restrained dynamics simulation (NVT and NPT) at 300 K for 300 ps. Then, the equilibrated structures were subjected to molecular dynamics simulations for 50,000psata constant temperature of 300 K and pressure of 1 atm, and the integration time step was set to 2 fs. The non-bonded list was generated using an Atom-based threshold of 8 Å. Long-range electrostatic interactions were managed using the particle-mesh Ewald algorithm . A 0.9 nm threshold was employed Lennard-Jones interaction. During the simulations, the lengths of all bonds containing hydrogen atoms were constrained utilizing the Lincs algorithm ; the trajectory snapshots were stored for structural analysis every picosecond. The RMSD and the hydrogen bonds were analysed using the Gromacs utilities g_rms and g_hbond. Furthermore, the MM-PBSA  was calculated to determine the binding free energy between VP40 and the lead compounds.
ADME analysis and Drug likeliness analysis
Lipinski’s rule of five was used to testthe bioavailability characteristics, such as the absorption, distribution, metabolism and elimination (ADME), of the lead compounds. In the present study, these molecular properties and the drug-likeness of the lead compounds were estimated using the Molsoft program (http://molsoft.com/mprop/).
Prediction of toxicity risk and oral toxicity (LD50)
We predicted the preclinical oral toxicity (LD50) of the lead compounds using the Osiris Property Explorer (http://www.organic-chemistry.org/prog/peo/) and the ProTox web server , respectively. The ProTox web server prediction method is based on the analysis of two-dimensional (2D) similarity to compounds displaying known LD50 values and on the identification of over-represented fragments in toxic compounds. The ProTox server integrates toxicity class prediction using similarity- and fragment-based methods with alerts for possible toxicity targets, thus providing insight into the mechanisms involved in the development of toxicity.
Virtual screening and docking analysis
Molecular dynamics simulation
ADME and drug-likeness analysis
Based on the analysis described above, it was predicted that compounds 1 and 2 are stable and display a high binding affinity to the drug target. Molecular properties such as the partition coefficient (logP), molecular weight (MW), and the number of hydrogen bond acceptors and donors in a molecule are always considered when predicting the bioavailability of the molecule . These molecular properties were used to formulate the “rule of five”21. This rule states that most molecules displaying good membrane permeability exhibit a molecular weight ≤500, a calculated octanol–water partition coefficient, logP ≤5, hydrogen bond donor’s ≤5 and hydrogen bond acceptors ≤10 . Therefore, the molecular properties and bioactivity of these lead compounds were predicted using the Molsoft program (http://molsoft.com/mprop/) based on the Lipinski rule of five, which states that an orally active compound should have no more than one violation. The results showed that both compounds 1 and 2 displayed one violation, which is acceptable according to the Lipinski rule of five (Additional file 2: Table S6) [42, 43]. Furthermore, drug-likeness is a key factor that determines the efficacy of the drug in terms of favourable absorption, distribution, metabolism, excretion and toxicological (ADMET) parameters. The drug-likeness values of compounds 1 and 2 were 0.88 and 0.36, respectively, which indicated that 1 displays higher druggability than compound 2.
Toxicity risks and oral toxicity (LD50) analysis
Drug discovery is a complicated procedure that requires compounds to be highly bioavailable and safe to enter the clinical phase. Toxicity and side effects are the major issues that lead to the failure of a drug during its development. Animal trials are currently the predominant method used to determine the possible toxic effects of drug candidates and cosmetics. In silico prediction serves as an alternative approach for simplifying and rationalizing drug development at the preclinical stage, thereby helping to minimize the cost, time, and animals involved . Therefore, we used the Osiris Property Explorer to assess the toxicity risk of the screened lead compounds. The analysis indicated that neither of these lead compounds exerts any mutagenic, tumorigenic or reproductive effects (Additional file 2: Table S7).
Furthermore, we used the Protoxweb server to calculate the LD50 value of the screened lead compounds. Higher the LD50 dose, lower the toxicity of the compound. The predicted oral toxicity of compound 1 was 5000 mg/kg, and the toxicity class is in the range of 5. These results indicate that compound 1 displays a better safety profile than compound 2 (Additional file 2: Table S7).
Ebola infection has become a significant challenge to human life, as Ebola has killed millions of people thus far (http://www.cdc.gov/vhf/ebola/outbreaks/history/distribution-map.html). Various efforts have been introduced to develop effective vaccines against this disease. However, no concrete report has demonstrated the pharmacological inhibition of the Ebola virus. Because the fatality rate of Ebola in humans is increasing each day, there is an urgent need to develop potential drugs at a faster pace. Thus, we adopted a computational approach to support experimental biologists in developing an effective drug in a shorter duration. Virtual screening is a modern technique that is used to prioritize active hits based on their binding affinity to a target. Many successful drug candidates have been developed against various diseases using this technique. In particular, molecular dynamics-based virtual screening is helpful for predicting the quality of screened lead compounds. As TCM, the most reliable source of medications, we employed the TCMD for virtual screening.
In this report, we have computationally identified 2 TCM-based lead candidates, emodin-8-beta-D-glucoside and tonkinochromane_G, as potential inhibitors of Ebola infection. VP40 is a core target for antiviral agents because of its essential role in the replication of the Ebola virus. VP40 binds to RNA, which forms an octameric ring structure to promote the replication of the virus. Interaction analysis showed that RNA forms a hydrogen bond with R-134 and close interactions with F-125 and T-123 (Fig. 2). R-134 and F-125 have previously been demonstrated to be the key residues involved in RNA binding . In the present study, we found that both lead compounds form a hydrogen bond interaction with R-134 and interact with other key residues (Figs. 3 and 4) that can negatively influence the binding of RNA to VP40, potentially inhibiting the Ebola virus replication process. In support of the docking analysis results, molecular dynamics simulations showed that these two lead compounds are more stable and exhibit stronger binding to VP40 due to forming a greater number of hydrogen bonds. The MM-PBSA analysis also showed that these lead compounds displayed a high binding affinity throughout the simulation.
Finally, the molecular properties, carcinogenicity and oral toxicity (LD50) parameters of these compounds indicated that emodin-8-beta-D-glucoside might be a more promising lead candidate than tonkinochromane_G for the future development of an effective antiviral agent against the Ebola virus. It is also to be noted that emodin-8-O-beta-D-glucoside is extracted from the herb Polygonum cuspidatum Sieb. etZucc, which is used for the treatment against hepatitis and emodin-8-O-beta-D-glucoside itself, demonstrated pharmacological importance in neuro-protective effects against cerebral ischemia-reperfused injury and glutamate-induced neuronal damage . While computations do not provide a complete replacement for experimental research, the relationship between computational and experimental approaches is very crucial process to guide the experimental biologist in screening and synthesize the compound in more rational and rapid way . Hence, we hope that our computational findings will be crucial for experimental biologists to develop antiviral agents very quickly against the Ebola virus.
Emodin-8-beta-D-glucoside and tonkinochromane_G are the lead candidates screened from the TCM database that is predicted to have potential antiviral activity against Ebola infection. Docking analysis revealed that these lead compounds interact with R-134 and F-125, which are the key residues for RNA binding. Further, molecular dynamics simulation results also validated the effective binding of these two compounds with the target. Finally, predicted oral toxicity and other physicochemical properties showed that emodin-8-beta-D-glucoside can be safer and efficient lead candidate for the development of antiviral therapeutics.
This work was supported by the Research Grants Council of Hong Kong  and Faculty Research Grant [FRG2/14-15/063]. The authors thank for the support of VIT and Galgotias University.
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