Drug Design

Objectives

Drug design is a very large scale and expensive process. A series of programs and methods have been developed to assist with a variety of problems to be faced in drug design. A major focus lies on lead structure finding and optimization. For this purpose new structure and physicochemical descriptors have been developed. In addition the conformational flexibility of chemical structures is considered. Pharmacophore evaluation is performed by determination of the Maximum Common Substructure (MCSS) of a set of biologically active molecules.
Another important topic is the design of combinatorial libraries and the evaluation of similarity and diversity of large datasets of molecules. Combinatorial libraries are designed using the synthesis planning program WODCA. Datasets of chemical compounds are classified by using Kohonen neural networks according to their biological activity. Based on these classification the biological activity of unknown substrates may be predicted.

Methods

3D Structure Generation

  1. J. Sadowski, J. Gasteiger
    From Atoms and Bonds to Three-dimensional Atomic Coordinates: Automatic Model Builders.
    Chem. Reviews, 1993, 93, 2567-2581.
  2. J. Sadowski, J. Gasteiger, G. Klebe
    Comparison of Automatic Three-dimensional Model Builders Using 639 X- Ray Structures.
    J. Chem. Inf. Comput. Sci. 1994, 34 , 1000-1008.

Empirical Estimation of Atomic, Bond, and Molecule Physicochemical Properties

  1. J. Gasteiger, M. Marsili
    Iterative Partial Equalization of Orbital - Electronegativity - A Rapid Access to Atomic Charges.
    Tetrahedron, 1980, 36, 3219-3228.
  2. J. Gasteiger, H. Saller
    Berechnung der Ladungsverteilung in konjugierten Systemen durch eine Quantifizierung des Mesomeriekonzeptes.
    Angew. Chem., 1985, 97, 699-701.
    Calculation of the Charge Distribution in Conjugated Systems by a Quantification of the Resonance Concept.
    Angew. Chem. Int. Ed. Engl., 1985, 24, 687-689.
  3. J. Gasteiger
    Empirical Methods for the Calculation of Physicochemical Data of Organic Compounds.
    In: Physical Property Prediction in Organic Compounds, Jochum, C.; Hicks, M.G.; Sunkel, J., Eds.;
    Springer Verlag, Heidelberg: 1988, 119-138.

Structure Descriptors

  • Encoding of Constitution
    • topological autocorrelation
  • 3D Structure
    • 3D autocorrelation
    • RDF Code
  • Molecular Surface
    • surface autocorrelation
    • 2D maps of surface properties
  1. J. H. Schuur, P. Selzer, J. Gasteiger,
    The Coding of the Three-dimensional Structure of Molecules by Molecular Transforms and Its Application to Structure - Spectra Correlations and Studies of Biological Activity.
    J. Chem. Inf. Comput. Sci., 1996, 36, 334-344.
  2. M. Wagener, J. Sadowski, J. Gasteiger,
    Autocorrelation of Molecular Surface Properties for Modeling Corticosteroid Binding Globulin and Cytosolic Ah Receptor Activity by Neural Networks.
    J. Am. Chem. Soc., 1995, 117, 7769-7775.
  3. H. Bauknecht, A. Zell, H. Bayer, P. Levi, M. Wagener, J. Sadowski, J. Gasteiger,
    Locating Biologically Active Compounds in Medium-Sized Heterogeneous Datasets by Topological Autocorrelation Vectors: Dopamine and Benzodiazepine Agonists.
    J. Chem. Inf. Comput. Sci., 1996, 36, 1205-1213.
  4. S. Anzali, G. Barnickel, M. Krug, J. Sadowski, M. Wagener, J. Gasteiger, J. Polanski,
    The Comparison of Geometric and Electronic Properties of Molecular Surfaces by Neural Networks: Application to the Analysis of Corticosteroid Binding Globulin Activity of Steroids.
    J. Comput.-Aided Mol. Design, 1996, 10, 521-534.

Similarity Perception

  1. M. Wagener, J. Gasteiger,
    Die Bestimmung größter deckungsgleicher Teilstrukturen mit einem genetischen Algorithmus: Anwendung in der Syntheseplanung und zur strukturellen Analyse biologischer Aktivität.
    Angew. Chem., 1994, 106, 1245-1248.
    The Determination of Maximum Common Substructures by a Genetic Algorithm: Application in Synthesis Design and for the Structural Analysis of Biological Activity.
    Angew. Chem. Int. Ed. Engl., 1994, 33, 1189-1192 (1994).
  2. S. Handschuh, M. Wagener, J. Gasteiger,
    Superposition of Three-Dimensional Structures Allowing for Conformational Flexibility by a Hybrid Method.
    J. Chem. Inf. Sci., 1998, 38, 220-232.
  3. J. Polanski, J. Gasteiger, M. Wagener, J. Sadowski,
    The Comparison of Molecular Surfaces by Neural Networks and Its Application to Quantitative Structure Activity Studies.
    Quant. Struct.-Act. Relat., 1998, 17, 27-36.
  4. S. Anzali, J. Gasteiger, U. Holzgrabe, J. Polanski, J. Sadowski, A. Teckentrup, M. Wagener,
    The Use of Self-Organizing Neural Networks in Drug Design,
    in "3D QSAR in Drug Design", Volume 2, p. 273-299
    H. Kubinyi, G. Folkers, Y. C. Martin, Eds., Kluwer/ESCOM, Dordrecht, NL: 1998.

Conformational Flexibility

  1. C.H. Schwab; J. Gasteiger,
    Addressing Conformational Flexibility,
    Oral Presentation; 5th International Conference on Chemical Structures,
    Noordwijkerhout, The Netherlands: Noordwijkerhout 1999.

Combinatorial Chemistry

Software

CORINA - a fast 3D structure generator
PETRA - prediction of physicochemical properties
KMAP - Kohonen neural network generator
GAMMA - Genetic Algorithm for Multiple Molecule Alignemt
SURFACE - generation of three dimensional surface coordinates
AUTOCORR - encoding of chemical structures

All programs are available through Molecular Networks GmbH. For further information please contact info@mol-net.de.

Contact

Prof.Dr. Johann Gasteiger
Dr. Lothar Terfloth
Dr. Christof H. Schwab
Dr. Thomas Kleinöder
Alexander von Homeyer