Docking studies of Benzisoxazole analogues in White Spot Syndrome Virus

 

T. Arunkumar1*, Ann Feba Ebby1, G. Narendrakumar2

1Department of Bioinformatics, School of Bio and Chemical Engineering,

Sathyabama University, Chennai 600119.

2Department of Biotechnology, School of Bio and Chemical Engineering,

Sathyabama University, Chennai 600119.

*Corresponding Author E-mail: ap_arunkumar@yahoo.com

 

ABSTRACT:

Objectives: The White Spot Syndrome Virus (WSSV) is the contagious and lethal disease that causes high mortality rates in shrimps. Effective tools and techniques exist to determine how serious of a problem it can be and to moderate its impact at this time.

Method: The Crystal Structure of Envelope Protein VP28 from WSSV was downloaded from the protein data bank (PDB) a database for the three-dimensional of proteins with PDB ID 2ED6 with the sequence length of 2040 amino acid residues. The DrugBank database is a unique bioinformatics and cheminformatics resource that combines detailed drug. The ligand for target protein zonisamide (1,2-benzoxazol-3-ylmethanesulfonamide) is a compound downloaded from the DrugBank database. binding site of the receptor molecule is predicted using Discovery studio, a software suite for simulating small and macromolecular systems developed  by Accelrys.

Results: Based on the target structure Crystal Structure of Envelope Protein VP28 and the ligand compound zonisamide the 64-binding site was identified using discovery studio and in that 10th site was reported as an active binding site which is having high scoring function. Active site is done for all the analogues in the 10th site. 293 analogs 72 ligand ADMT satisfy- pharmophore using hiphop hypothesis 10 using rank. Ligand fit identification docking 159 poses were obtained- rank 5 used as results – PLP value Jain score PMF Dock score rotation bond of the ligand internal energy.

 

KEYWORDS: White spot syndrome virus, Benzisoxazole, Docking – ligand fit.

 

 

 


INTRODUCTION:

White spot syndrome virus (WSSV) is a causative agent of contagious disease for penaeid viral disease in prawns called as White spot disease (WSD)1. The virus is an enveloped virus, rod-shaped containing double-stranded DNA genome that is classification under Whispoviridae. Earlier incidence of the disease was from 1990s, WSD has become the greatest threat in worldwide crustacean in aquaculture industries. WSSV was first reported from China in 19912,3.

 

And this disease is spread to major aquaculture regions of the world in Asia, USA, India, the Middle East and in Europe4. The worldwide generation of shrimp demonstrated a dilapidated pattern from 2000. The normal marine environment is likewise debilitated by WSSV as the infection has a wide host range, including salt and harsh water penaeids, crabs, sharp lobsters, freshwater shrimp and crawfish5. The episode of viral infections amid 1991 brought on a noteworthy set back in the shrimp business. WSSV spread quickly to shrimp cultivating regions all through Asia connected with an across the board pandemic by 1994. The WSSV causes genuine financial misfortunes due to 100% mortality prompting all out-product misfortunes inside of 3-10 days under some cultivating conditions. There are mainly four major envelope proteins for WSSV. VP28, VP19, VP24 and VP26. Of these proteins, VP28 is the most virulent one which covers the epidemics of the virus and is responsible for penetration into the shrimp cells inducing infection. In WSSV Viral protein 28 (VP28) is an objective protein atom because it is the entry way to shrimp cells6,7. The benzisoxazole functional group zonisamide (1,2-benzoxazol-3-ylmethanesulfonamide) is confirmed viable drug against WSSV. This atom has been accounted for to force intense antiviral action. Thus, benzisoxazole analogs or related medications can be utilized to treat this contamination in shrimps. work based on discovering a drug molecule that can help inhibit the virus infection. Protein-ligand docking studies using the discovery studio are employed to analyse and interpret the results. The target protein is VP28 on which a drug named zonisamide and its analogues are subjected to docking studies

 

MATERIALS AND METHODS:

The Crystal Structure of target Protein was downloaded from the protein data bank (PDB). The ligand for target protein was retrieved from Drug Bank database is a unique bioinformatics and cheminformatics resource. Binding site of the receptor molecule is predicted using Discovery studio, a software suite for simulating small and macromolecular systems developed by Accelrys. The docked molecules are viewed for hydrogen bond interactions between the ligand atoms and the amino acid residues of the receptor molecule with Biovia8. Different structural conformation of the protein -ligand complex was subjected to pose based dock score in Ligand fit module of Discovery Studio under CHARM force field and the energy function is based on pairwise structural analysis between the nonbonding interactions of protein-ligand complex. Finally, ADMET properties of ligands were studied through Discovery Studio 9,10.

 

RESULTS AND DISCUSSION:

Target Molecule (VP28):

The target molecule with the PDB ID 2ED6 retrieved from the PDB database is subjected to molecular docking with the selected drug compound.

 

http://www.rcsb.org/pdb/images/2ED6_bio_r_500.jpg?bioNum=1

Fig.1: Crystal Structure of Envelope Protein VP28 from White Spot Syndrome Virus (WSSV)

 

Retrieval of Ligand Molecule:

The ligand for target protein zonisamide (1,2-benzoxazol-3-ylmethanesulfonamide) with ID DB00909 (APRD00004) is a compound downloaded from the DrugBank database.

Smile Notation: NS(=O)(=O)CC1=NOC2=CC=CC=C12

 

Fig. 2: Two dimensional structure of 1,2-Benzisoxazole-3-methanesulfonamide

 

Receptor binding sites for ligand:

The binding site of the receptor molecule is analyzed from discovery studio .64 active sites was predicted and site 10, 23 and 50 are reported to be the active binding site for the ligand molecule. Among which the 10th site is chosen showed high scoring function. So the molecular docking is done for all the analogues at the 10th site 10.

 

ADMET Results and its 66Interpretation:

Out of 293 analogues of the zonisamide drug subjected to ADMET studies, it gave 72 ligands to satisfying the ADMET rules of drug. The point plots for the 293 compounds are displayed in the below figure.

 

Fig.3: ADMET point plot for 293 ligand molecules

 

The ADMET descriptors provided information regarding the BBB level, absorption level, solubility level, hepatotoxicity, CYP2D6, PPB level and PSA 2D values.

Pharmacophore Result Interpretation:

The common feature pharmacophore generation is studied for the ligands molecule obtained from the ADMET result. It generates common feature pharmacophore models from a set of ligands. It uses HipHop hypothesis to generate common feature pharmacophore among a set of active ligand. The elements need to coordinate distinctive concoction bunches with comparative properties so as to distinguish nove3l ligands. Ligand –receptor associates are regularly polar positive, polar negative and hydrophobic. 

 

Fig 4: shows the ten pharmacophore features generated that are common for all ligands.

 


Table 1: Pharmacophore generated results for ligand molecules

Sl. No

Hiphop Hypothesis

Pharmacophore features

Rank

Direct Hit

Partial Hit

Maximum Fit value

1

Hypo1

HAA

79.432

11111111111

000000000

3

2

Hypo2

HAA

76.805

11111111111

000000000

3

3

Hypo3

HAA

75.003

11111111111

000000000

3

4

Hypo4

HAA

74.262

11111111111

000000000

3

5

Hypo5

HAA

74.126

11111111111

000000000

3

6

Hypo6

HAA

68.799

11111111111

000000000

3

7

Hypo7

HAA

67.026

11111111111

000000000

3

8

Hypo8

HAA

65.398

11111111111

000000000

3

9

Hypo9

AA

45.561

11111111111

000000000

3

10

Hypo10

AA

22.459

11111111111

000000000

2

 


 

The above table shows us various pharmacophore models which were generated by the hiphop hypothesis. There are 10 hypothetical pharmacophore models generated for the input of analogs of zonisamide, these 10 models are named as “Hypo1” to “Hypo10” the ten pharmacophore models are generated based on a scoring function which ranks the generated models and the highest ranking model here is represented as model one.

 

Each of these generated models have different pharmacophore features these features are represented as single letter words such as “H” meaning hydrophobic groups, “A” meaning hydrogen bond acceptors and so on. The fitness value and rank gives us an idea about how selected molecules share some common chemical features with one and another. In the selected model, “HAAAA” meaning one hydrophobic groups and four hydrogen bond acceptors are present in this model. The structure of this model is given above with the various analogs in different orientations with respect to the pharmacophore.

 

Docking Using LIGANDFIT:

LigandFit algorithm in the discovery studio is implemented for docking the ligand with the target molecule.

 

 

From the results from docking performed, 10 poses for the receptor –ligand interactions as input. Output of 74 compounds selected for docking, 15 compounds generated successful results for receptor-ligand interactions with 159 poses. The ligscore, PMF, PLP, Jain, Dock score are the five values used to analyze the docking results. A high score in all the above values shows a highly stable molecular complex. Jain scoring function is the sum of five interaction terms: Lipophilic interactions, polar attractive interactions, polar repulsive interactions, salvation of the protein and ligand and an entropy term for the ligand. The highly stable complexes are analyzed through consensus scoring method.

 

Consensus Scoring:

Several poses are generated for each of the ligand given as input for docking. Consensus scoring is employed to obtain the high scoring docking molecule which helps in finding the best interacting molecule based on the PLP values, Jain score, PMF, dock score, rotational bonds of the ligand and the ligand internal energy. This scoring methods evaluates all the above values for the docked molecules and then retrieves the best receptor – ligand complex.

 

 


Table 2: Consensus Scoring Result

Name

Index

Lig

Score1

Lig

Score2

PLP1

PLP2

Jain

PMF

DOCK

SCORE

LF

Rotlbonds

LIG INTERNAL

ENERGY

Consensus

24867864

117

2.06

2.61

30.32

27.41

-0.58

44.22

69.98

2

-1.984

2

29942561

147

2.74

2.47

28.27

33.74

0.24

32.56

50.967

3

-1.164

3

12506981

21

2.66

3.6

44.5

43.64

0.89

51.02

43.097

4

-3.875

7

12506980

11

1.62

3.76

49.85

41.61

0.64

48.2

39.346

4

-1.19

7

12506979

1

1.97

2.15

39.81

40.7

0.32

45.31

39.226

4

-1.513

3


The above scoring method helped identify the stable interactions from among the 159 docked score.

 

Table 3: Hydrogen bond interaction studies for the docked complexes.

Sl No

Pubchen ID

Amino acid residue

Donor atoms

Accepted atoms

Distance (A)

1

24867864

ASP 191

H23

OD1

1.05549

2

29942561

ARG 53

LYS 142

HH12

HZ1,HZ3

O2,N7

O3,N6

1.86232

1.70238

3

12506981

LYS 142

HZ1,HZ3

O4

1.80228

4

12506980

ARG 53

LYS 142

HH12

HZ1

O4

O3,N7

1.77,1.86,2.48

5

12506979

LYS 142

LYS 147

HZ1,HZ3

HN

O3,O5,N8

O8

2.40,2.38,1.89,

2.27,1.82

 


Ligand-Receptor Interaction Studies:

The molecule obtained after consensus scoring is subjected to further analysis of hydrogen bond interaction studies that helps determine the stability of the complex.

 

Fig. 5: Ligand receptor interaction

 

SUMMARY AND CONCLUSION:

Based on the target structure Crystal Structure of Envelope Protein VP28 and the ligand compound zonisamide the 64 binding site was identified using discovery studio and in that 10th site was reported as an active binding site which is having high scoring function. Active site is done for all the analogues in the 10th site. 293 analogs 72 ligand ADMT satisfy- pharmophore using hiphop hypothesis 10 using rank. Ligand fit identification docking 159 poses were obtained- rank 5 used as results – PLP value Jain score

 

PMF Dock score rotation bond of the ligand internal energy.

 

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Received on 06.04.2017             Modified on 11.06.2017

Accepted on 05.07.2017           © RJPT All right reserved

Research J. Pharm. and Tech. 2017; 10(8): 2497-2500.

DOI: 10.5958/0974-360X.2017.00441.3