Crowd sourcing a new paradigm for interactome driven drug target identification in Mycobacterium tuberculosis
| Autor: | Swati Gandhi, Vishal Mevada, Varsha Bhavnani, Aparna Venkatachalam, Nagasuma Chandra, Anurag Passi, Gayathri S, Soumi Sengupta, Swetha Raghavan, Trupti Kholia, Anupam Kumar Mondal, Pankaj Kumar Singh, Samir K. Brahmachari, Debasis Dash, Tiruvayipati Suma Avasthi, Anup Shah, Girish Muthagadhalli Ramanna, Malarvizhi Gurusamy, Balaganesh J, Madhumohan Thandapani, Pratibha Sharma, Harsha Rohira, Arun Sharma, Anshula Arora, Prabhakaran Munusamy, Rohit Vashisht, Kumari Sonal Choudhary, Zakir Thomas, Keya Mukherjee, Ilamathi Raja, Raviraj Soni, Priti Vishnoi, Priyanka Priyadarshini, Shruti Rana, Ashwini G. Bhat, Vinod Scaria, Kaveri Verma, Rajesh Patel, Mohammed Razeeth, Ahalyaa Subramanian, Kausik Bhattacharyya, Salman Zaheer, Lakavath Chiranjeevi, Sweety Raj, Vijaya Chitra, Anshu Bhardwaj, Shefin Nisthar, Meenakshi Anurag, Vikas Kumar, Yasha Hasija, Naresh Atray, Akanksha Jain, Sunil N. Subramanya |
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| Přispěvatelé: | OSDD Consortium |
| Rok vydání: | 2011 |
| Předmět: |
Bacterial Diseases
Drugs and Devices Drug Research and Development Proteome Science Gene regulatory network Genomics Context (language use) Computational biology Biology Genome Interactome Biochemistry Mycobacterium Drug Delivery Systems Bacterial Proteins Genome Analysis Tools ddc:570 Protein Interaction Mapping Drug Discovery Genetics Humans Tuberculosis Gene Regulatory Networks Protein Interactions Whole genome sequencing Multidisciplinary Drug discovery Macrophages Systems Biology Proteins Computational Biology Mycobacterium tuberculosis Infectious Diseases Host-Pathogen Interactions Crowdsourcing Medicine Gene Function Genome Bacterial Signal Transduction Research Article |
| Zdroj: | PLoS ONE PLoS ONE, Vol 7, Iss 7, p e39808 (2012) |
| ISSN: | 1932-6203 |
| Popis: | 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 `3interactome 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. |
| Databáze: | OpenAIRE |
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