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Title

Molecular Docking of Phytoligands to the viral protein receptor P. monodon Rab7

 

Authors

Jerrine Joseph1, Raj Bhaskaran2, Muthusamy Kaliraj1, Muthiyah Muthuswamy3, Arumugam Suresh1*

 

Affiliation

1Centre for Drug Discovery and Development, Sathyabama University, Jeppiaar Nagar, Rajiv Gandhi Salai, Chennai-600 119, Tamil Nadu, INDIA;

2Research and Development Centre, Sathyabama University, Jeppiaar Nagar, Rajiv Gandhi Salai, Chennai-600 119, Tamil Nadu, INDIA;

3Thiruvalluvar University Constituent College of Arts and Science, Kallakurichi-606204, Tamil Nadu, INDIA;

 

Email

kpm_suresh@yahoo.com

 

Article Type

Hypothesis

 

Date

Received March 5, 2017; Revised April 8, 2017; Accepted April 8, 2017; Published April 30, 2017

 

Abstract

The development of shrimp aquaculture has been severely affected by viral diseases resulting in a huge economic burden to the industry. White spot disease (WSD) has caused severe mortality in farmed shrimp in many countries. Globally aquaculture industries face huge economic losses due to rapid spread of White Spot Syndrome Virus (WSSV) disease that can cause 100% mortality in a short period of 3-10 days. In the present study in order to prevent the spread of WSSV disease in shrimps, the receptor, PmRab7 has been chosen as the drug target. Due to the absence of a precise 3D structure of the target, homology-modeling approach was employed to obtain the structure that was validated later. This structure was then used as a template to screen selective phytomolecules as potential antiviral agents and their docking results with the target are analyzed based on their energy scores. Identification of the drug-like molecule obtained from the docking analysis would be used to optimize to a candidate drug. This is expected to play a role of the inhibitor that blocks the binding of the viral protein to the receptor, duly preventing the WSSV disease.

 

Keywords

Drug target, WSSV, P. monodon Rab7, Homology modeling, Phytoligands

 

Citation

Joseph et al. Bioinformation 13(4): 116-121 (2017)

 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.