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    Journal of Computer-Aided Molecular Design, Volume 32

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    Volume 32, Number 1, January

    Special Issue: Drug Discovery Data Resource Grand Challenge 2 (D3RGC2)
    • Zied Gaieb, Shuai Liu, Symon Gathiaka, Michael Chiu, Huanwang Yang, Chenghua Shao, Victoria A. Feher, W. Patrick Walters, Bernd Kuhn, Markus G. Rudolph, Stephen K. Burley, Michael K. Gilson, Rommie E. Amaro:
      D3R Grand Challenge 2: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies
    • Christina Athanasiou, Sofia Vasilakaki, Dimitris Dellis, Zoe Cournia:
      Using physics-based pose predictions and free energy perturbation calculations to predict binding poses and relative binding affinities for FXR ligands in the D3R Grand Challenge
    • Matthew P. Baumgartner, David A. Evans:
      Lessons learned in induced fit docking and metadynamics in the Drug Design Data Resource Grand Challenge
    • Soumendranath Bhakat, Emil &#;berg, P&#;r S&#;derhjelm:
      Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling
    • Priscila da Silva Figueiredo Celestino Gomes, Franck Da Silva, Guillaume Bret, Didier Rognan:
      Ranking docking poses by graph matching of protein-ligand interaction

      Collaborative Database and Computational Models for Tuberculosis Drug Discovery

    • 1. Collaborative Database and Computational Models for Tuberculosis Drug Discovery Sean Ekins Collaborations in Chemistry, Fuquay Varina, NC. Collaborative Drug Discovery, Burlingame, CA. Department of Pharmacology, University of Medicine & Dentistry of New Jersey-Robert Wood Johnson Medical School, Piscataway, NJ. School of Pharmacy, Department of Pharmaceutical Sciences, University of Maryland, Baltimore, MD.
    • 2. In the long history of human kind (and animal kind, too) those who have learned to collaborate and improvise most effectively have prevailed. Charles Darwin
    • 3. Outline Introduction Collaborative Drug Discovery TB Collaborations and Drug Discovery Research Open ADME Models Repurposing FDA approved drugs The Future – Mobile Apps for Drug Discovery
    • 4. Open Innovation Open innovation is a paradigm that assumes that firms can and should use external ideas as well as internal ideas, and internal and external paths to market, as the firms look to advance their technology Chesbrough, H.W. (). Open Innovation: The new imperative for creating and profiting from technology. Boston: Harvard Business School Press, p. xxiv Collaborative Innovation A strategy in which groups partner to
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