TY  - JOUR
A1  - Vashisht, Rohit
A1  - Mondal, Anupam Kumar
A1  - Jain, Akanksha
A1  - Shah, Anup
A1  - Vishnoi, Priti
A1  - Priyadarshini, Priyanka
A1  - Bhattacharyya, Kausik
A1  - Rohira, Harsha
A1  - Bhat, Ashwini G.
A1  - Passi, Anurag
A1  - Mukherjee, Keya
A1  - Choudhary, Kumari Sonal
A1  - Kumar, Vikas
A1  - Arora, Anshula
A1  - Munusamy, Prabhakaran
A1  - Subramanian, Ahalyaa
A1  - Venkatachalam, Aparna
A1  - S., Gayathri
A1  - Raja, Sweety
A1  - Chitra, Vijaya
A1  - Verma, Kaveri
A1  - Zaheer, Salman
A1  - J., Balaganesh
A1  - Gurusamy, Malarvizhi
A1  - Razeeth, Mohammed
A1  - Raja, Ilamathi
A1  - Thandapani, Madhumohan
A1  - Mevada, Vishal
A1  - Soni, Raviraj
A1  - Rana, Shruti
A1  - Ramanna, Girish Muthagadhalli
A1  - Raghavan, Swetha
A1  - Subramanya, Sunil N.
A1  - Kholia, Trupti
A1  - Patel, Rajesh
A1  - Bhavnani, Varsha
A1  - Chiranjeevi, Lakavath
A1  - Sengupta, Soumi
A1  - Singh, Pankaj Kumar
A1  - Atray, Naresh
A1  - Gandhi, Swati
A1  - Avasthi, Tiruvayipati Suma
A1  - Nisthar, Shefin
A1  - Anurag, Meenakshi
A1  - Sharma, Pratibha
A1  - Hasija, Yasha
A1  - Dash, Debasis
A1  - Sharma, Arun
A1  - Scaria, Vinod
A1  - Thomas, Zakir
A1  - Chandra, Nagasuma
A1  - Brahmachari, Samir K.
A1  - Bhardwaj, Anshu
T1  - Crowd sourcing a new paradigm for interactome driven drug target identification in Mycobacterium tuberculosis
T2  - PLoS One
N2  - 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.
Y1  - 2012
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/25555
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-255553
SN  - 1932-6203
VL  - 7
IS  - (7):e39808
PB  - PLoS
CY  - Lawrence, Kan.
ER  -