Cheminformatics Crowd Computing for Tuberculosis Drug Discovery


Cheminformatics Crowd Computing for Tuberculosis Drug Discovery (3C4TB) is an innovative crowd-computing initiative to involve individuals and computer algorithms to help prioritize potential leads to accelerate drug discovery for Tuberculosis.

Why Crowd Computing ?
Creation and implementation of methods for prioritization of leads require enormous human intellectual inputs and efforts to realize. Our effort is to provide the basic molecular Kernel or the molecular data-set of active anti-tubercular molecules in standard inter-operable formats and integrate prioritization methodologies to arrive at a small subset of molecules for early-stage trials.

Is the data Open Access / Open Source ?
Yes, all data coming out of this project would be Open Access under CC-BY-SA 2.0. We generally would require the methodologies of all methods used for prioritization be published before-hand in a peer-reviewed journal before inclusion in the data-set archive.

Joining the Initiative

The programme would be open from September 1st 2013.
Watchout this page for more information

Participating with your method
Participating in this programme with your method is straight forward. You need to download the compendium file in requisite format and use your prioritization method on the data-set. You would require to annotate the output and share the results on the shared repository.

Collaborating on this programme
We invite and are open to academic collaboration from individuals, institutes or organisations on this initiative. If you have an interesting methodology you would like to try on this data-set, or would like to suggest a methodology which is already not used on this data-set, please contact Dr. Vinod Scaria for more details.

Funding and Resources
We acknowledge the funding from the Open Source Drug Discovery Initiative/CSIR for the programme. We also acknowledge the availability of communication and compute resources from NKN and CDAC-Garuda for the project.



Data and Results
A compendium of data-sets for prioritization and the data-sets filtered through multiple prioritization approaches are available for download. 

  • Molecules with anti-tubercular activities   0k - May 17, 2013, 3:23 AM by Vinod Scaria (v1)
    ‎Compendium of small molecules with anti-tubercular activities. The molecules are categorised based on the source. Molecular information is available in SMILES, MOL2 and SDF formats‎
Showing 1 files from page Data Repository.

Data Statistics 
We continuously track and monitor progress of this Open Source programme. The data statistics of this programme is available online. [learn more]

You could also track the recent developments at 3C4TB on Social Media. We could be found on Facebook and Google+