Date: June 25th 2012

Dear Colleagues,

This message is an update on the teach-discover-treat (“TDT”)
initiative, which was launched at the ACS meeting in San Diego (see
www.teach-discover-treat.org). TDT aims to address outstanding gaps in
drug discovery education and treatments for neglected diseases. A
competition was launched that solicits submissions of computational
models and tutorials for drug discovery for neglected diseases in four
categories. This message announces the availability of a final data
file neeeded to complete a submisison for Challenge 3.

TDT Challenge 3 includes a task to perform prioritization of medicinal
chemistry efforts. From the readme file: "Prioritize compounds from
the virtual library with a multi-objective prioritization tool, taking
into account predicted binding affinity as well as additional measures
to rank attractiveness of drug candidates".

The virtual library file has been created by Michael Pollastri and
colleagues from Northeastern University and is now ready for download
from the TDT download page,
http://www.teach-discover-treat.org/downloads

The file is in csv format and contains information for 1,789,468
compounds (identifier, smiles, AlogP, molecular weight, number of
hydrogen-bond acceptors and donors, heavy atom count).

Please use this file for your submission for challenge 3 and provide a
rank-ordered list of your top-50 preferred candidates for synthesis.
If your submission is selected as the winner, at least 20 of these
compounds will be synthesized and tested for inhibition of TbrPDEB1.

Good luck!

The TDT Steering Committee
Hanneke Jansen, Rommie Amaro, Jane Tseng and Wendy Cornell