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Molecular Modeling and Prediction of Bioactivity

  • Klaus Gundertofte
  • Flemming Steen Jørgensen

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Overview

    1. Front Matter
      Pages 1-1
    2. James P. Snyder, Forrest D. Snyder
      Pages 3-23
  3. New Developments and Applications of Multivariate QSAR

    1. Front Matter
      Pages 25-25
    2. Svante Wold, Michael Sjöström, Per M. Andersson, Anna Linusson, Maria Edman, Torbjörn Lundstedt et al.
      Pages 27-45
    3. William C. Herndon, Hung-Ta Chen, Yumei Zhang, Gabrielle Rum
      Pages 47-52
    4. Wolfgang Sippl, Jean-Marie Contreras, Yveline Rival, Camille G. Wermuth
      Pages 53-58
    5. Marjana Novič, Matevž Pompe, Jure Zupan
      Pages 59-64
    6. Lennart Eriksson, Patrik Andersson, Erik Johansson, Mats Tysklind, Maria Sandberg, Svante Wold
      Pages 65-70
  4. The Future of 3D-QSAR

    1. Front Matter
      Pages 71-71
    2. Gabriele Cruciani, Manuel Pastor, Sergio Clementi
      Pages 73-81
    3. Jordi Mestres, Douglas C. Rohrer, Gerald M. Maggiora
      Pages 83-88
    4. Robert D. Clark, Michael Brusati, Robert Jilek, Trevor Heritage, Richard D. Cramer
      Pages 95-100
  5. Prediction of Ligand-Protein Binding

    1. Front Matter
      Pages 101-101
    2. Gerhard Klebe, Markus Böhm, Frank Dullweber, Ulrich Grädler, Holger Gohlke, Manfred Hendlich
      Pages 103-110
    3. Abdelaziz Yasri, Michel Kaczorek, Roger Lahana, Gérard Grassy, Roland Buelow
      Pages 111-121
    4. Modesto Orozco, Carles Colominas, Xavier Barril, F. Javier Luque
      Pages 129-134
    5. Elena López-de-Briñas, Juan J. Lozano, Nuría B. Centeno, Jordi Segura, Marisa González, Rafael de la Torre et al.
      Pages 141-146
  6. Computational Aspects of Molecular Diversity and Combinatorial Libraries

    1. Front Matter
      Pages 147-147
    2. Johann Gasteiger, Sandra Handschuh, Markus C. Hemmer, Thomas Kleinöder, Christof H. Schwab, Andreas Teckentrup et al.
      Pages 157-168
    3. Christian Lemmen, Thomas Lengauer
      Pages 169-174
    4. Frank R. Burden, David A. Winkler
      Pages 175-180
  7. Affinity and Efficacy Models fo G-Protein Coupled Receptors

    1. Front Matter
      Pages 181-181
    2. Maria Santagati, Arthur Doweyko, Andrea Santagati, Maria Modica, Salvatore Guccione, Hongming Chen et al.
      Pages 183-194
    3. Slavomir Filipek, Danuta Pawlak
      Pages 195-200
    4. Joong-Youn Shim, Elizabeth R. Collantes, William J. Welsh, Allyn C. Howlett
      Pages 201-206
    5. Monica Clementi, Sara Clementi, Sergio Clementi, Gabriele Cruciani, Manuel Pastor, Jonas E. Nilsson
      Pages 207-212
  8. New Methods in Drug Discovery

    1. Front Matter
      Pages 213-213
    2. Oleg A. Raevsky, Klaus J. Schaper, Han van de Waterbeemd, James W. McFarland
      Pages 221-227
  9. Modeling of Membrane Penetration

    1. Front Matter
      Pages 229-229
    2. Lene H. Krarup, Anders Berglund, Maria Sandberg, Inge Thøger Christensen, Lars Hovgaard, Sven Frokjaer
      Pages 231-236
    3. Manfred Kansy, Krystyna Kratzat, Isabelle Parrilla, Frank Senner, Björn Wagner
      Pages 237-243
    4. Wouter H. J. Vaes, Eñaut Urrestarazu Ramos, Henk J. M. Verhaar, Christopher J. Cramer, Joop L. M. Hermens
      Pages 245-248
    5. M. D. Wessel, P. C. Jurs, J. W. Tolan, S. M. Muskal
      Pages 249-255
  10. Poster Presentations

    1. Front Matter
      Pages 257-257
    2. New Developments and Applications of Multivariate QSAR

      1. Miki Akamatsu, Yoshihisa Ozoe, Taizo Higata, Izumi Ikeda, Kazuo Mochida, Kazuo Koike et al.
        Pages 263-264
      2. Raimund Mannhold, Gabriele Cruciani
        Pages 265-266
      3. Sanja Tomić, Lennart Nilsson, Rebecca C. Wade
        Pages 269-270
      4. Erik Johansson, Lennart Eriksson, Maria Sandberg, Svante Wold
        Pages 271-272
      5. John C. Dearden, Shazia A. Ahmed, Mark T. D. Cronin, Janeth A. Sharra
        Pages 273-274
      6. G. Gallo, M. Mabilia, M. Santaniello, M. O. Tinti, P. Chiodi
        Pages 275-276
      7. James W. McFarland, Oleg A. Raevsky, Wendell W. Wilkerson
        Pages 280-281

About this book

Introduction

Much of chemistry, molecular biology, and drug design, are centered around the relationships between chemical structure and measured properties of compounds and polymers, such as viscosity, acidity, solubility, toxicity, enzyme binding, and membrane penetration. For any set of compounds, these relationships are by necessity complicated, particularly when the properties are of biological nature. To investigate and utilize such complicated relationships, henceforth abbreviated SAR for structure-activity relationships, and QSAR for quantitative SAR, we need a description of the variation in chemical structure of relevant compounds and biological targets, good measures of the biological properties, and, of course, an ability to synthesize compounds of interest. In addition, we need reasonable ways to construct and express the relationships, i. e. , mathematical or other models, as well as ways to select the compounds to be investigated so that the resulting QSAR indeed is informative and useful for the stated purposes. In the present context, these purposes typically are the conceptual understanding of the SAR, and the ability to propose new compounds with improved property profiles. Here we discuss the two latter parts of the SARlQSAR problem, i. e. , reasonable ways to model the relationships, and how to select compounds to make the models as "good" as possible. The second is often called the problem of statistical experimental design, which in the present context we call statistical molecular design, SMD. 1.

Keywords

chemistry chemometrics development drug discovery future protein receptor

Editors and affiliations

  • Klaus Gundertofte
    • 1
  • Flemming Steen Jørgensen
    • 2
  1. 1.H. Lundbeck A/SValbyDenmark
  2. 2.Royal Danish School of PharmacyCopenhagenDenmark

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-4141-7
  • Copyright Information Kluwer Academic / Plenum Publishers, New York 2000
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-6857-1
  • Online ISBN 978-1-4615-4141-7
  • Buy this book on publisher's site
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