Pharmacophore Mapping of Dengue Virus Inhibitors of Natural Origin Using Phase and Self Organizing Neural Networks

Authors

  • Afroz Alam Professor, Department of Bioinformatics, Karunya University, Karunya Nagar-Coimbatore, Tamil Nadu, Coimbatore, India
  • Chinnu Sunny Department of Bioinformatics, Karunya University, Karunya Nagar, Coimbatore, Tamil Nadu, India

DOI:

https://doi.org/10.37591/(rrjobi).v1i2.360

Abstract

Dengue virus (DENV) infection is an important arthropod-born viral infection infecting about 2.5 billion people worldwide. To date there are no effective vaccine or antiviral treatment for dengue. Dengue patients are usually supportively treated until they recover without any specific treatment measures. Plants and plant’s derived compounds remain an important source for the discovery and the development of new antiviral drugs because of their expected low side effects and their high accessibility in the nature. Thirty one compounds have been identified from literatures which are known to inhibit the virus. But the action or orientation of these compounds on the receptor are unknown. So docking studies and pharmacophore model generation were carried out using these compounds and a known receptor NS2B-NS3 pro of dengue virus. Most of the compound exhibited good docking results among which Rutin showed the best docking score and energy. Some other compounds which exhibited good properties were methyl gallate, 4 Hydroxypandruitin A and Hespertin.  Pharmacophores were also generated which exhibited the features of the receptor, with which these compounds interact.

 

Keywords: dengue virus, docking, pharmacophore, SOM

 

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Published

2019-03-26

Issue

Vol. 1 No. 2 (2014)

Section

Research Article

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