Mining the Proteome of Haemophilus ducreyi for Identification of Potential Drug Targets

Aditya Narayan Sarangi*, 1, Stuti Gupta1, Nidhi Trivedi1, Bhawna Rathi1, Shailendra Kumar Gupta*, 2
1 Biomedical Informatics Centre, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India
2 ENVIS Centre, Indian Institute of Toxicology Research, Lucknow, India

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© 2010 Sarangi et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Biomedical Informatics Centre, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow-226014, India; Tel: +91 522 2668004 Extn: 8503; Fax: +91 522 2668017; E-mail: andCorrespondence: Indian Institute of Toxicology Research (CSIR), P.O. Box. 80, MG Marg, Lucknow -226001 India; Tel: +91 522 2284591; Fax: +91 522 2628227; E-mail:


Chancroid is an extremely infectious sexually transmitted disease (STD) caused by the bacterium Haemophilus ducreyi, prevalent in Africa, United States and in some parts of South Asia. Chancroid has been recognized as a cofactor for human immunodeficiency virus (HIV) transmission. So, there is a requirement to develop an efficient drug to combat chancroid, which can also diminish the HIV prevalence in those populations where chancroid is a prime source for HIV infection. The availability of the complete proteome information of H. ducreyi help enabled in silico analysis for identification of potential vaccine candidates and drug targets. Our study revealed 1226 proteins in H. ducreyi to be nonhomologous with human proteome. Screening these proteins using the Database of Essential Genes (DEG) resulted in the identification of 451 essential proteins. Analysis of the identified essential proteins, using the KEGG Automated Annotation Server (KAAS), revealed 40 proteins of H. ducreyi as potential drug targets as they are involved in pathogen specific metabolic pathways. Subcellular localization prediction of these 451 essential proteins revealed that 11 proteins lie on the outer membrane of the pathogen which could be potential vaccine candidates. Functional family prediction for the 50 putative uncharacterized essential proteins of H. ducreyi by SVM-Prot web server revealed that out of 50, 3 proteins as transmembrane proteins, which may be potential drug targets. Identification of potential inhibitors against these targets through virtual screening may consequence in detection of novel lead compounds effective against H. ducreyi to combat chancroid.

Keywords: Proteome mining, Drug target, Vaccine candidate, Chancroid, Haemophilus ducreyi, HIV, AIDS.