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From Structure to Recognition Principles: Mining in Crystal Data as a Prerequisite for Drug Design

  • Conference paper
Small Molecule — Protein Interactions

Part of the book series: Ernst Schering Research Foundation Workshop ((SCHERING FOUND,volume 42))

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Abstract

The discovery of novel leads and their subsequent optimization into development compounds is the key element in any drug discovery process. During the last several years, substantial efforts have been dedicated to the establishment of high-throughput screening technologies (HTS) (Houston and Banks 1997). Computer tools have been developed to drive robotic systems to fully automate and speed up the experimental testing along with a sophisticated selection of compounds used in the various screening assays. Testing entire libraries within weeks or even days is now feasible. However, initial euphoria that was pronouncing the end of any rational or knowledge-based approach to lead discovery has been superseded by a more realistic view, mainly as a result of the considerable costs involved and disappointingly low hit rates (Lahana 1999).

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Authors
  1. G. Klebe
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Editors and Affiliations

  1. Max-Planck-Institut für Molekulare Physiologie, Otto-Hahn-Straße 11, 44221, Dortmund, Germany

    H. Waldmann

  2. Universität Dortmund, Fachbereich 3, Organische Chemie, 44221, Dortmund, Germany

    H. Waldmann

  3. Medicinal Chemistry, Schering AG, 13342, Berlin, Germany

    M. Koppitz

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© 2003 Springer-Verlag Berlin Heidelberg

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Klebe, G. (2003). From Structure to Recognition Principles: Mining in Crystal Data as a Prerequisite for Drug Design. In: Waldmann, H., Koppitz, M. (eds) Small Molecule — Protein Interactions. Ernst Schering Research Foundation Workshop, vol 42. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-05314-0_8

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  • DOI: https://doi.org/10.1007/978-3-662-05314-0_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-05316-4

  • Online ISBN: 978-3-662-05314-0

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