Teach – Discover – Treat: A COMP initiative to provide high quality computational chemistry tutorials that impact education and drug discovery for neglected diseases http://www.TDTproject.org
Challenge 4 :: Open Innovation
Share an innovative computational chemistry workflow that can impact drug discovery for neglected diseases. Examples can include, but are not limited to, workflows for target identification, scaffold-hopping, property predictions, target selection (various flavors of druggability assessment).
Workflow components: The submissions must contain a clear tutorial for a computational chemistry workflow that is relevant to drug discovery. If the example dataset used in the tutorial is not a neglected disease dataset, the workflow has to be adaptable for use in a neglected disease setting.
Input data-package
TDT case studies provided on this website or other relevant data sets, including proprietary data as long as the computational tools and models are freely available.
Submission package
Submit your tutorial and data here: http://file.teach-discover-treat.org/submit/index.php
NOTE #1: models built on proprietary data are allowed in this category as long as the model and software needed to run the model are freely available to all. The proprietary data does not have to be released but the tutorial should include example data files to run through the workflow and showcase how the model supports drug discovery.
NOTE #2: If your workflow is exemplified with a neglected disease target, consider making predictions from the virtual catalogues provided through IUPUI’s Distributed Drug Discovery (D3) initiative (www.chem.iupui.edu/people/william-l-scott). For access to the IUPUI-Distributed Drug Discovery (D3) database, register for a free read-download account with Collaborative Drug Discovery (CDD) at https://www.collaborativedrug.com/register/iupui-d3. Your predictions may well inspire the next round of synthesis in this project, and compounds could be made through the D3 program at no-cost for experimental testing.
The Judging Criteria can be found here.
NOTE: the submissions must contain a clear tutorial for a computational chemistry workflow that is relevant to drug discovery. If the example dataset is not a neglected disease dataset, the workflow has to be adaptable for use in a neglected disease setting.
Challenge 4 :: Open Innovation
Share an innovative computational chemistry workflow that can impact drug discovery for neglected diseases. Examples can include, but are not limited to, workflows for target identification, scaffold-hopping, property predictions, target selection (various flavors of druggability assessment).
Workflow components: The submissions must contain a clear tutorial for a computational chemistry workflow that is relevant to drug discovery. If the example dataset used in the tutorial is not a neglected disease dataset, the workflow has to be adaptable for use in a neglected disease setting.
Input data-package
TDT case studies provided on this website or other relevant data sets, including proprietary data as long as the computational tools and models are freely available.
Submission package
Submit your tutorial and data here: http://file.teach-discover-treat.org/submit/index.php
NOTE #1: models built on proprietary data are allowed in this category as long as the model and software needed to run the model are freely available to all. The proprietary data does not have to be released but the tutorial should include example data files to run through the workflow and showcase how the model supports drug discovery.
NOTE #2: If your workflow is exemplified with a neglected disease target, consider making predictions from the virtual catalogues provided through IUPUI’s Distributed Drug Discovery (D3) initiative (www.chem.iupui.edu/people/william-l-scott). For access to the IUPUI-Distributed Drug Discovery (D3) database, register for a free read-download account with Collaborative Drug Discovery (CDD) at https://www.collaborativedrug.com/register/iupui-d3. Your predictions may well inspire the next round of synthesis in this project, and compounds could be made through the D3 program at no-cost for experimental testing.
The Judging Criteria can be found here.
NOTE: the submissions must contain a clear tutorial for a computational chemistry workflow that is relevant to drug discovery. If the example dataset is not a neglected disease dataset, the workflow has to be adaptable for use in a neglected disease setting.