ABOUT   |   AIMS and SCOPE   |   AUTHOR INSTRUCTIONS   |   EDITORIAL BOARD   |   ARCHIVE   |   CURRENT ISSUE   |   SUBMIT MANUSCRIPT ONLINE  |
bioinfo issue

This Article

Copyright © 2015 | AIZEON publishers | All rights reserved

 Open Access
 Abstract
 Full Text PDF Free

 

Services

Articles by corresponding author in PubMed

Articles by corresponding author in Google Scholar

 

 

aizeon

 



 

International Journal of Computational Bioinformatics and In Silico Modeling
2015: Volume-4 Issue-3
ISSN: 2320-0634

>>Back to Issues

ABSTRACT   REFERENCES  
International Journal of Computational Bioinformatics and In Silico Modeling 4(3) 2015: 651-658

Exploring the binding pattern of predicted potent inhibitor to sirR_mtb; Modeling and structure-base virtual screening of sirR protein of Mycobacterium Tuberculosis (MTB)



Ashfaq Ur Rehman1,2, TK Muhammad1, Abdul Wadood2, K Qaiser1, Zahid Ullah2, A Ayaz3, BJ Syed2, M Naeem2,5, BS Syed2, JMA Bilal4 and R Hamid1*

1 Department of Bioinformatics, Muhammad Ali Jinnah University Islamabad, Pakistan-23200.
2 Department of Biochemistry, Computational Medicinal Laboratory Chemistry Lab, Abdul Wali Khan University Mardan, Pakistan.
3 Department of Biotechnology, Abdul Wali Khan University Mardan, Pakistan-23200.
4 Department of Chemistry, Education College for women, Anbar University, Iraq.
5 Department of Chemical and Biological engineering, Zhejiang University, China.

* Corresponding Author

ABSTRACT

Tuberculosis (TB) is considered as a fatal disease and globally its mortality rate is about 2 million per year, this disease is caused by Mycobacterium tuberculosis (MTB). According to the previous reports, latent infection is prevalent in one-third of population. In the current study an efforts was made to predict an effective drug, as there is still no drug that efficiently kills these resting bacilli. During this study, three MTB_sirR inhibitors were identified using computer-aided drug design approach. Molecular Operating Environment (MOE 2011-10) software was utilized to generate three dimensional structures of MTB_sirR protein, and the predicted model was verified using RAMPAGE and ERRAT programs. Structural-Base Virtual screening was performed by docking inhibitors obtained from the Chembridge Database to the active site of the MTB_sirR protein using MOE-Dock 2011-10 software. Based on dock-score, Hydrogen bonds and interaction energy calculated in our computational approach, three compounds (Chembridge ID: 10293776, 10279567 and 10294460) might be the potent inhibitor of the MTB_sirR protein.

 


Copyright © 2015 | AIZEON publishers | All rights reserved

..........................................................................................................................................................................................................

Citation: Ashfaq Ur Rehman et al. (2015). Exploring the binding pattern of predicted potent inhibitor to sirR_mtb; Modeling and structure-base virtual screening of sirR protein of Mycobacterium Tuberculosis (MTB). Int J Comput Bioinfo In Silico Model 4(3): 651-658

..........................................................................................................................................................................................................