Molecular docking and Simulation study to identify Antiviral agent by targeting MX protein against Betanodavirus causing viral nervous necrosis in Barramundi

 

Ruby Singh¹, K. Pani Prasad², Anshul Tiwari^3,4, Ajey Pathak⁵, Prachi Srivastava¹*

¹Amity Institute of Biotechnology, Amity University, Uttar Pradesh, Lucknow-227105, India.

²ICAR- Central Institute of Fisheries Education, Versova, Mumbai, Maharashtra-400061, India.

³Channing Division of Network Medicine, Brigham and Women Hospital, Harvard Medical School,

Boston, MA-02115, USA.

⁴Department of Ophthalmology, King George, Medical University, Uttar Pradesh, Lucknow-226020, India.

⁵National Bureau of Fish Genetic Resources (Indian Council of Agricultural Research), Canal Ring Road, P.O. Dilkusha, Lucknow-226002, Uttar Pradesh, India.

 

ABSTRACT:

Among many relevant issues dealing with fish farming, microbial infections are a major problem. There are different viral infections, which are continuously creating problems in fish farming and among these viral infections Betanoda viral infection is a foremost problem. The Betanodavirus is an important, emerging group of viruses known to infect around 40 species worldwide. The major target of this virus is the central nervous system and retina of fishes especially in Barramundi species. Viral Nervous Necrosis (VNN) is now a serious problem for different fish species which is yet to be resolved through strong antiviral compounds. The In- silico screening of potential phytochemicals as a drug molecule with low or no side effects against viral nervous necrosis in barramundi is the major objective of the study. The present study discusses the molecular interaction studies carried out between virtually screened phytochemicals and MX protein of barramundi fish. Findings based on virtual screening, calculation of molecular properties and bioactivity score showed that among 101 compounds, the hypogallic acid, cineole, eugenol, linalool, camphene, oligonol, azulene, caravacrol, pistol and squalene are the active phytochemicals against the selected MX protein. Further intense screening showed that Camphene is the best screened phytochemical with the lowest binding energy in complex with MX protein of Barramundi. Further molecular dynamic simulation study at 100ns (Nano seconds) proved the importance, stability and establishment of camphene as better natural prophylactic and therapeutic approaches to overcome or reduce the problem of viral nervous necrosis in barramundi.

 

 

 

INTRODUCTION:

Viral nervous necrosis is caused by Betanodavirus in variety of cultured fishes especially in marine fishes^1,2. This disease was first explained in hatchery-reared Japanese parrotfish in the year 1990 in Japan³ and in barramundi in Australia⁴.

This disease is highly infectious disease and causes high mortality in both marine and fresh water as well as hatchery and cultured facilities and negatively impacted the aquaculture industry². The Mortality rate of fish stock is very high that it may reach up to 100% within 2-3 days of onset of betanoda infection⁵. Betanodavirus mainly effect the retina, the central nervous system and peripheral nervous system and thus this infection results in cellular vacuolation, degrades neurons and causes abnormal swimming behaviour. The Younger fish have more severe lesions as compared to older fishes as they can show a predilection of the retina⁶. There are many progresses have been made against this disease in Lates Calcarifer through molecular biology approaches such as development of a Barramundi brain (BB) cell line from the Barramundi brain tissue as well as it has seen that there is existence of Betanodavirus in BB (Barramundi brain) cell lines which induces the expression of MX protein against this disease⁷. Antimicrobial peptides acts an antiviral agent against fish nodavirus and among three antimicrobial peptides two AMPs such as tilapia hepcidin^1-5 and grouper epinecidin-1 was found to be active⁸. Betanodavirus causes an increase in the expression of MX protein in fish brain. MX protein in Lates calcarifer plays a major role in understanding about the detailed mechanism of this Betanoda virus disease as this MX protein in fish (BB cell line) helps in clearance of Betanoda virus RdRp protein⁹. The first cell line which was reported to be infected with Betanodavirus was BB cell line and also it helped a lot in understanding the the mechanism of infection of betanodavirus in fishes and its perseverance¹⁰. It is very important to understand interaction of Betanodavirus with the host for the proper treatment¹¹, since Betanodavirus is a RNA virus so it’s transmission is horizontally as well as vertically both. There are no commercial vaccines are available because this disease has caused outbreaks in larval and juvenile stages¹¹. Among different approaches and remedies no doubt herbal remedies proves to be the most promising one in curing many viral and bacterial infection as herbs are safer for human as well as for environment as compared to the synthetic one so far coming in more practice of medicinal uses. It is noticeable that several researches have been done to use plant derived drugs as an antiviral agent against fish viral diseases.

 

In screening of such potential herbal compounds in silico-based bioinformatics approaches are playing a very important step^12-15. Bioinformatics is the major and advanced field of science which uses computational technology for solving problems in biology. Due to advancement of this field there we can easily access and manage various types of biological information such as genomic, proteomic and metabolomic thus we can get detailed information about disease mechanisms and in identifying new molecular targets for drug discovery¹⁶. Virtual screening is In-silico based methods for the discovery of list of molecules which can act as a drug to inhibit the effect of the viral/fungal/bacterial protein. The major goal of this approach is to reduce the maximum essential chemical spaces of molecules and to screen against the specific targeted protein¹⁷. On the basis of computational point of view, molecular docking is more demanding in comparison to pharmacophore modeling and also it can actually predict the binding affinities of active site between ligands and protein¹⁸. As we know, Protein is adjustable and flexible in nature¹⁹, it keeps on changing its conformation²⁰ and whereas docking is a rigid methodology so in order to get the best conformation, induced flexible docking and Molecular dynamics was performed²¹. The major highlights of this study was to understand the stability and binding mode between MX and the best possible ligand using virtual screening, molecular docking and molecular dynamics simulations²² and then after docking the compound having the least binding energy is selected as the best then it’s dynamic simulation as well as Induced flexible docking was performed to get the best conformation and the stability of compound against the Betanodavirus. The results obtained from MD of the complex provided an insight into the interacting amino acids between MX of Lates Calcarifer and rdrp protein⁹ of Betanodavirus. The amino acid residues were further targeted to search a potential inhibitor that could bind to them and inhibit Mx-rdrp assembly and or increases the expression of MX⁷ which in turn reduce the chances of entry of Betanodavirus into Barramundi. This screened out potential antiviral agent may either can enhance the immunological aspects or can be used as prophylactic measures against the protection of such dreadful virus reason of great economic loss in fisheries. The main aim of the study is In- silico screening of potential phytochemicals as a drug molecule with low or no side effects against viral nervous necrosis in Barramundi.

 

METHODOLOGY:

Virtual screening:

Virtual screening is most important In- silico technology in the pharmaceutical industry¹⁷. Through extensive literature survey and Pub-Chem search, 101 molecules were screened on the basis of their antibacterial and antiviral activity against fish viral and bacterial diseases based on the published data. The virtual library of compounds was prepared along with their Pub-Chem Id. The details of commercially available molecule or already published antiviral against NNV is also prepared along with their chemical formula, molecular weight and Pub-Chem id. Smart screening was done with the help of Molinspiration tool that followed the Lipinski’s rule of five and then the selected compounds were ready for the molecular docking studies^23,24.

 

Molecular docking studies:

Docking is a computational methodology and an important In- silico technique in which we can predict the most preferred orientation of one molecule binding to a second molecule to form a stable complex model for potential inhibitors²⁵ as in this case MX protein binding with the best possible ligand (with which it can form most stable complex) in order to inhibit the Betanodavirus and Docking is one of the best methods used to identify the best complex between a protein and a potential ligand²⁶. The natural ligands along with already available molecule selected through literature search for this study were docked into the modeled 3D structure of MX²⁷ by using AutoDock4.2²⁶. All steps were performed according to the Auto dock protocol and with the help of Auto grid (in the same protocol parameter of Autodock) the grid box was set at X=3.42, Y= 25.778, Z= 2.496 and dimension at X= 64, Y= 52, Z=50. Through PyMol molecular viewer (www.pymol.org), UCSF chimera (www.cgl.ucsf.edu)²⁸ and ligplot (www.ebi.ac.uk/thornton-srv/software/ ligplot)²⁹ was used to analyze the obtained docked structures by Auto Dock²⁶.

 

Induced Flexible docking:

Ligands after binding with the protein or with another ligand used to induce conformational changes in the binding active sites so in order to get the most stable complex, we used the induced flexible protocol which allows specifications of whole loop to move so that to get the best conformation and most stable. We investigated the atomic level interaction using flexible docking (IFD) and molecular dynamics^21,30.

 

MD Simulation Analysis:

Stability of docked complex and interaction of MX with Camphene was simulated till 100 ns using Scrodinger Desmond³⁰. The complex of MX and Camphene was immersed in cubic box with sufficient distance of 2.8 A° spacing containing 36736 water molecules and then solvated with the help of three-point water model i.e, extended simple point charge with the periodic boundary conditions at 300 K. The total charge of the solvent system was neutralized by adding Sodium (NA) i.e., 18 Na of 8.909mM molar concentration of ions was added to the MX. The system was enumerated at 300k for 100 ns. Cut off for Vander walls interactions and short-range electrostatics interactions was kept at 1.4A°. After stability, both the systems were subjected to 100 ns MD simulation at 300 K temperature along with I bar pressure without any restrictions or moderations. After the equilibration of the system, the most stable conformation trajectories were captured for docking validation. Camphene compound from docking calculation which was based upon its binding energy was docked in obtained stable conformation from the trajectory for MX to explore the interaction stability.

 

RESULTS AND DISCUSSION:

Virtual screening:

Virtual library of 101 compounds prepared through extensive literature survey compounds^32-41 which is kept as a supplementary table.

 

Screening by molinspiration:

The chemical names of 73 compounds are tabulated in a table which is kept as supplementary table shows the calculated property of compounds through molinspiration server and the 73 compounds were screened on the basis of lipinski’s rule of five. All the selected compounds obey the rule of lipinski’s rule of five and have drug likeness property⁴². These parameters play a vital role in determination of bioactivity of chemical compound⁴³. Lipinski’s rule of five describes the general rule of an orally active drug must have⁴⁴. In table 1 details of already published compounds against NNV are listed.

 

Molecular Docking studies:

Auto Dock 4.2 was used for the docking studies. The docked complex having the lowest binding energy was selected as the most possible antiviral agent²⁵. The total screened 73 compounds were docked into the active site of MX protein.

 

Table 1: List of already available molecules against NNV

Sr. No.	Name of synthetic molecule	PubChem ID	Chemical formula	Molecular weight(g/mol)
1	Oligonol	11230	C10H18O	154.249
2	Gymnemagenol	21592406	C30H50O4	474.715
3	Dasyscyphin C	25058111, (D and B) 11515996	C23H34O3, C22H32O2	358.514

 

Table 2: Binding energy of screened phytochemicals

Table 3: Binding energy of available molecule with Mx

 

The best 15 compounds are tabulated in Table 2 on the basis of their binding energy and binding affinity with MX protein of Lates calcarifer. The compounds which was having the least binding energy was Camphene (-4.05) and it was selected as the potential antiviral against Betanodavirus. Binding energy of already validated compounds against NNV by in vitro studies is also given in table 3. Thus, it can give a clear finding of all effective antivirals against NNV and we can get a comparative data on the basis of current findings and already published data. Thus, camphene is best than oligonol and gymnemagenol against NNV but have less binding affinity than dasyscyphin C which in vitro work is already published but D and B form of this compound information is not published yet.

 

The interaction of all the best 13 compounds Azulene, Camphene, carvacrol, cineole, fucoidan, Linalool, n-tricontanol, octadecanoic acid, oligonol, phytol, squalene, Tetradecanoic acid, Zingeronewith MX protein are graphically represented in the figure1(a, b, c, d, e, f, g, h, I, j, k, l, m) by UCSF chimera analyzer²⁹ as well as by LIG Plot analysis³⁰ in figure 2

Figure 1: Molecular interaction between MX protein and Screened Phytochemicals through UCSF chimera (a)Azulene (b)Camphene (c)carvacrol (d) cineole (e)fucoidan(f) Linalool(g) n-tricontanol(h) octadecanoic acid (i)oligonol (j)phytol (k)squalene (l) Tetradecanoic acid(m) Zingerone.

 

Figure 2: Molecular interaction between MX protein and Screened Phytochemicals through LigPlot (a)Azulene (b)Camphene (c)carvacrol (d) cineole (e)fucoidan (f) Linalool(g) n-tricontanol(h) octadecanoic acid (i)oligonol (j)phytol (k)squalene (l) Tetradecanoic acid(m) Zingerone

 

 

Figure 3: Induced flexible docking Image of ligand camphene and MX protein showing the best conformation of binding site between camphene and MX.

 

Figure 4: Protein ligand RMSD:Root mean square deviation of Camphene and MX complex during 100ns of simulation. Camphene shown in the red colour and Mx in blue colour.

 

Induced flexible Docking:

This Figure 3 shows the atomic level interaction using Induced flexible docking which shows the best conformation as we know the protein is flexible in nature and docking is a rigid process so IFD is done to show the best conformation site of protein and ligand binding complex.

 

MD Simulation Analysis:

The dynamic simulation was performed for the Camphene only as it was selected as the best antiviral amongst all on the basis of minimum binding energy so in order to see the stability of the complex MX and camphene, molecular dynamic simulation was carried out^48-49. Over the course of 100 ns simulation period, the potential energy tends to decrease and which in turn indicates the stabilization of the system. Root mean square deviation (RMSD) was calculated for MX and camphene during the course of simulation trajectory of 100 nano seconds(ns) and it was calculated for all the frames in the trajectory. The RMSD plot for protein MX and ligand Camphene as shown in Figure 4. The Figure 4 shows the RMSD evolution of a protein (left Y-axis) which indicated its equilibration during the simulation and its fluctuations towards the end of the simulation period, which was around 23-24nm, a thermal average structure. In this the MX protein is undergoing a large conformational change during the course of simulation. Ligand RMSD (right Y-axis) indicated the stability of camphene with MX protein and with its binding pocket. In this plot 4 “Lig fit Prot” showed the RMSD of Camphene when the MX-Camphene complex was first aligned on the MX protein backbone of the reference and then the RMSD of the Camphene was measured.

 

CONCLUSION:

Through virtual screening and extensive literature search 101 compounds were selected and finally potential antiviral agent was screened on the basis of binding energy which was calculated by docking studies and the compound Camphene was found the best effective antiviral compound as it is having the least binding energy from all the selected compounds of our current findings. We got a comparative result from the current findings as well as the findings which. Through this in silico work we can get the clear findings of all the best antiviral against NNV and can be used as a drug against NNV which is causing major negative impact in aquatic industry. This finding can be a positive boost for aquatic industry and for the safe environment too. Molecular dynamic simulation was done after docking and induced flexible docking which suggested camphene as a best screened ligand and then it’s dynamic simulation result (23- 24nm RMSD) values showed the most dynamic stable configuration between MX of Lates Calcarifer and camphene. Thus, the present study makes a foundation for Camphene as a best antiviral against betanodavirus causing viral nervous necrosis in Lates Calcarifer by targeting MX protein.

 

ACKNOWLEDGEMENTS:

We heartily acknowledge to the Director, Dr. Kuldeep K Lal, National Bureau of Fish Genetic Resources, Lucknow and we are very grateful to senior scientist Dr. Vinod Kumar Devaraji, who helped a lot in dynamic Simulation Facilities and we also extend our sincere thanks to the Director and Vice-Chancellor Dr. Gopal Krishna, Central Institute of Fisheries Education, Mumbai. Finally, our gratitude towards Ms. Neha Srivastava, system network administrator from Biotech park, Lucknow, for her great help during this research.

 

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Accepted on 30.06.2020           © RJPT All right reserved

Research J. Pharm. and Tech 2021; 14(3):1405-1411.