| 作者介绍：Thierry Langer Thierry Langer (b. 1962) is heading the Computer Aided Molecular Design Group at the University of Innsbruck (Tyrol, Austria). After his pharmacy M.S. degree (1987) he obtained a Ph.D. degree in organic chemistry at the University of Vienna (Austria) in 1991. He then spent one year as a post-doc fellow at the Universiteacute; Louis Pasteur (Strasbourg, France) with C. G. Wermuth. In 1992 he moved to the University of Innsbruck, where he established the molecular modeling group. Since 1997 he is associate professor for pharmaceutical chemistry. In addition to his academic appointments, he is also the founder and CEO of the Inteligand, a company specialized in providing computational services for the pharmaceutical industry. Professor Langer's main research interests are focused on theoretical pharmaceutical chemistry, drug design, and pharmacophore modeling using molecular modeling techniques as well as QSAR and 3D-QSAR. |
| A Personal Foreword. List of Contributors. Part I Introduction. 1 Pharmacophores: Historical Perspective and Viewpoint from a Medicinal Chemist (Camille G. Wermuth). 1.1 Definitions. 1.2 Historical Perspective. 1.3 Pharmacophores: the Viewpoint of a Medicinal Chemist. 1.4 Conclusion. References. Part II Pharmacophore Approaches. 2 Pharmacophore Model Generation Software Tools (Konstantin Poptodorov, Tien Luu, and Rémy D. Hoffmann). 2.1 Introduction. 2.2 Molecular Alignments. 2.3 Pharmacophore Modeling. 2.4 Automated Pharmacophore Generation Methods. 2.5 Other Methods. 2.6 Conclusions. References. 3 Alignment–free Pharmacophore Patterns – A Correlation–vector Approach (Steffen Renner, Uli Fechner, and Gisbert Schneider). 3.1 Introduction. 3.2 The Correlation–vector Approach. 3.3 Applications. 3.4 New Methods Influenced by the Correlation–vector Approach. 3.5 Conclusions. Acknowledgments. Abbreviations. References. 4 Feature Trees: Theory and Applications from Large–scale Virtual Screening to Data Analysis (Matthias Rarey, Patrick Fricker, Sally Hindle, Günther Metz, Christian Rummey, and Marc Zimmermann). 4.1 Introduction: from Linear to Non–linear Molecular Descriptors. 4.2 Creating Feature Trees from Molecules. 4.3 Algorithms for Pairwise Comparison of Feature Trees. 4.4 Feature Trees in Similarity Searching and Virtual Screening. 4.5 Searching Combinatorial Fragment Spaces with Feature Trees. 4.6 Multiple Feature Tree Models: Applications in HTS Data Analysis. 4.7 Drawing Similar Compounds in 2D Using Feature TreeMappings. 4.8 Conclusion. Acknowledgments. References. 5 Concept and Applications of Pseudoreceptors (Klaus–Jürgen Schleifer). 6 Pharmacophores from Macromolecular Complexes with LigandScout (Gerhard Wolber and Robert Kosara). 7 GRID–based Pharmacophore Models: Concept and Application Examples (Francesco Ortuso, Stefano Alcaro, and Thierry Langer). 8 “Hot Spot” Analysis of Protein–binding Sites as a Prerequisite for Structure–based Virtual Screening and Lead Optimization (Ruth Brenk and Gerhard Klebe). 9 Application of Pharmacophore Fingerprints to Structure–based Design and Data Mining (Prabha Karnachi and Amit Kulkarni). 10 SIFt: Analysis, Organization and Database Mining for Protein–Inhibitor Complexes. Application to Protein Kinase Inhibitors (Juswinder Singh, Zhan Deng, and Claudio Chuaqui). 11 Application of Structure–based Alignment Methods for 3D QSAR Analyses (Wolfgang Sippl). Part III Pharmacophores for Hit Identification and Lead Profiling: Applications and Validation. 12 Application of Pharmacophore Models in Medicinal Chemistry (Fabrizio Manetti, Maurizio Botta, and Andrea Tafi). 13 GPCR Anti–target Modeling: Pharmacophore Models to Avoid GPCR–mediated Side–effects (Thomas Klabunde). 14 Pharmacophores for Human ADME/Tox–related Proteins (Cheng Chang and Sean Ekins). 15 Are You Sure You Have a Good Model? (Nicolas Triballeau, Hugues–Olivier Bertrand, and Francine Acher). Acknowledgments. References. Subject Index. |
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