Crowd sourcing a new paradigm for interactome driven drug target identification in Mycobacterium tuberculosis

Rohit Vashisht, Anupam Kumar Mondal, Akanksha Jain, Anup Shah, Priti Vishnoi, Priyanka Priyadarshini, Kausik Bhattacharyya, Harsha Rohira, Ashwini G. Bhat, Anurag Passi, Keya Mukherjee, Kumari Sonal Choudhary, Vikas Kumar, Anshula Arora, Prabhakaran Munusamy, Ahalyaa Subramanian, Aparna Venkatachalam, Gayathri S, Sweety Raj, Vijaya ChitraKaveri Verma, Salman Zaheer, Balaganesh J, Malarvizhi Gurusamy, Mohammed Razeeth, Ilamathi Raja, Madhumohan Thandapani, Vishal Mevada, Raviraj Soni, Shruti Rana, Girish Muthagadhalli Ramanna, Swetha Raghavan, Sunil N. Subramanya, Trupti Kholia, Rajesh Patel, Varsha Bhavnani, Lakavath Chiranjeevi, Soumi Sengupta, Pankaj Kumar Singh, Naresh Atray, Swati Gandhi, Tiruvayipati Suma Avasthi, Shefin Nisthar, Meenakshi Anurag, Pratibha Sharma, Yasha Hasija, Debasis Dash, Arun Sharma, Vinod Scaria, Zakir Thomas, Nagasuma Chandra, Samir K. Brahmachari, Anshu Bhardwaj

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23 Citations (Scopus)


A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative 'Connect to Decode' (C2D) to generate the first and largest manually curated interactome of Mtb termed 'interactome pathway' (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.

Original languageEnglish
Article numbere39808
Number of pages11
JournalPLoS ONE
Issue number7
Publication statusPublished - 11 Jul 2012
Externally publishedYes

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