Literature DB >> 23085175

Teach-Discover-Treat (TDT): collaborative computational drug discovery for neglected diseases.

Johanna M Jansen1, Wendy Cornell, Y Jane Tseng, Rommie E Amaro.   

Abstract

Teach-Discover-Treat (TDT) is an initiative to promote the development and sharing of computational tools solicited through a competition with the aim to impact education and collaborative drug discovery for neglected diseases. Collaboration, multidisciplinary integration, and innovation are essential for successful drug discovery. This requires a workforce that is trained in state-of-the-art workflows and equipped with the ability to collaborate on platforms that are accessible and free. The TDT competition solicits high quality computational workflows for neglected disease targets, using freely available, open access tools.
Copyright © 2012 Elsevier Inc. All rights reserved.

Entities:  

Mesh：

Year:  2012        PMID： 23085175      PMCID： PMC3508335          DOI： 10.1016/j.jmgm.2012.07.007

Source DB:  PubMed          Journal:  J Mol Graph Model        ISSN： 1093-3263            Impact factor:   2.518


  2 in total

1.  An audience with...Francis Collins. Interviewed by Asher Mullard.

Authors:  Francis Collins
Journal:  Nat Rev Drug Discov       Date:  2010-12-10       Impact factor: 84.694

2.  Reengineering translational science: the time is right.

Authors:  Francis S Collins
Journal:  Sci Transl Med       Date:  2011-07-06       Impact factor: 17.956
  2 in total
  5 in total

1.  Continuous Evaluation of Ligand Protein Predictions: A Weekly Community Challenge for Drug Docking.

Authors:  Jeffrey R Wagner; Christopher P Churas; Shuai Liu; Robert V Swift; Michael Chiu; Chenghua Shao; Victoria A Feher; Stephen K Burley; Michael K Gilson; Rommie E Amaro
Journal:  Structure       Date:  2019-06-27       Impact factor: 5.006

2.  CACHE (Critical Assessment of Computational Hit-finding Experiments): A public-private partnership benchmarking initiative to enable the development of computational methods for hit-finding.

Authors:  Suzanne Ackloo; Rima Al-Awar; Rommie E Amaro; Cheryl H Arrowsmith; Hatylas Azevedo; Robert A Batey; Yoshua Bengio; Ulrich A K Betz; Cristian G Bologa; John D Chodera; Wendy D Cornell; Ian Dunham; Gerhard F Ecker; Kristina Edfeldt; Aled M Edwards; Michael K Gilson; Claudia R Gordijo; Gerhard Hessler; Alexander Hillisch; Anders Hogner; John J Irwin; Johanna M Jansen; Daniel Kuhn; Andrew R Leach; Alpha A Lee; Uta Lessel; Maxwell R Morgan; John Moult; Ingo Muegge; Tudor I Oprea; Benjamin G Perry; Patrick Riley; Sophie A L Rousseaux; Kumar Singh Saikatendu; Vijayaratnam Santhakumar; Matthieu Schapira; Cora Scholten; Matthew H Todd; Masoud Vedadi; Andrea Volkamer; Timothy M Willson
Journal:  Nat Rev Chem       Date:  2022-02-15       Impact factor: 34.571

3.  Virtual-screening workflow tutorials and prospective results from the Teach-Discover-Treat competition 2014 against malaria.

Authors:  Sereina Riniker; Gregory A Landrum; Floriane Montanari; Santiago D Villalba; Julie Maier; Johanna M Jansen; W Patrick Walters; Anang A Shelat
Journal:  F1000Res       Date:  2017-07-17

4.  TeachOpenCADD: a teaching platform for computer-aided drug design using open source packages and data.

Authors:  Dominique Sydow; Andrea Morger; Maximilian Driller; Andrea Volkamer
Journal:  J Cheminform       Date:  2019-04-08       Impact factor: 5.514

Review 5.  Towards reproducible computational drug discovery.

Authors:  Nalini Schaduangrat; Samuel Lampa; Saw Simeon; Matthew Paul Gleeson; Ola Spjuth; Chanin Nantasenamat
Journal:  J Cheminform       Date:  2020-01-28       Impact factor: 5.514
  5 in total

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