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Title

 

 

 

 

 

Functional interpretation of APN receptor from M. sexta using a molecular model

 

Authors

 

Anamika Singh & C. V. S. Sivaprasad

 

Affiliation

 

 

Bioinformatics and Applied Division, Indian Institute of Information Technology, Deoghat, Jhalwa, Allahabad 211012, India

 

Email

 

shiva@iiita.ac.in

 

Article Type

 

Hypothesis

 

Date

 

received April 04, 2008; revised November 01, 2008; accepted January 02, 2009; published April 21, 2009

 

Abstract

Insect pests are the major cause of damage to commercially important agricultural crops. The continuous application of synthetic pesticides resulted in severe insect resistance by plants. This causes irreversible damage to the environment. Bacillus thuringiensis (Bt) emerged as a valuable biological alternative in pest control. However, insect resistance against Bt has been reported in many cases. Insects develop resistance to insecticides through mechanisms that reduce the binding of toxins to gut receptors. Nonetheless, the molecular mechanism of insect resistance is not fully understood. Therefore, it is important to study the mechanism of toxin resistance by analyzing amino-peptidase-N (APN) receptor of the insect M. sexta. A homology model of APN was constructed using Insight II molecular modeling software and the model was further evaluated using the PROCHECK program. Oligosaccharides participating in post translational modification were constructed and docked onto specific APN functional sites. Post analyses of the APN model provide insights on the functional properties of APN towards the understanding of receptor and toxin interactions. We also discuss the predicted binding sites for ligands, metals and Bt toxins in M. sexta APN receptor. These data help in the development of a roadmap for the design and synthesis of novel insect resistant Cry toxins.

 

Keywords

glycosylation, Manduca Sexta, post transnational modifications, aminopeptidase-N, Cry toxins

 

Citation

Singh & Sivaprasad, Bioinformation 3(8): 321-325 (2009)

 

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.