Poster Session: Analogy and Intelligence in Model Building (AIMB)

  • Mathew A Hahn
  • W Todd Wipke

Abstract

The AIMB program is a symbolic, non-numerical approach to molecular model building and conformational analysis. The purpose of this project is to develop a rapid, accurate and automatic model builder that can be applied to a wide range of chemical structures. A further aim is to create a program that will facilitate the exploration of the conformational space of molecules and molecular fragments. The program utilises knowledge about the shape and structure of known molecules (taken from crystallographic data) for model construction and conformational search. Results are presented on the ability of AIMB to model a cyclooctane ring compound and its utility in exploring low energy conformations of the compound.

Keywords

Brittleness Cyclohexane Metaphor Tetrahydropyran 

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References

  1. 1.
    Molecular Mechanics; Burkert, U., Allinger, N. L., Eds; ACS Monograph 177; American Chemical Society: Washington, 1982.Google Scholar
  2. 2.
    Lenat, D. ‘Software for Intelligent Systems’. Sci. Am. 1984, 251, 204.CrossRefGoogle Scholar
  3. 3.
    Lenat, D., Mayank, P., Shepherd, M. ‘CYC: Using Common Sense Knowledge to Overcome Brittleness and Knowledge Acquisition Bottlenecks’. AI Mag. 1986, 6 (4), 65–85.Google Scholar
  4. 4.
    Winston, P. ‘Learning and Reasoning By Analogy’. Commun. ACM 1986, 23 (12), 689–703.CrossRefGoogle Scholar
  5. 5.
    Carbonell, J., Minton, S. ‘Metaphor and Common-Sense Reasoning’. Technical report CMU-CS-83-110, Computer Science Department, Carnegie-Mellon University, 1983.Google Scholar
  6. 6.
    Corey, E. J., Wipke, W. T. ‘Computer-Assisted Design of Complex Molecular Synthesis’. Science 1969, 166, 178–192.CrossRefGoogle Scholar
  7. 7.
    Wilson, S., Huffman, J. ‘Cambridge Data File in Organic Chemistry. Applications to Transition-State Structure, Conformational Analysis, and Structure/Activity Studies’. J. Org. Chem. 1980, 45, 560–566.CrossRefGoogle Scholar
  8. 8.
    Allen, F., Brice, M., Cartwright, B., Doubleday, A., Hummelink, T., Hummelink, B., Kennard, O., Motherwell, W., Rodgers, J., Watson, D. The Cambridge Crystallographic Data Centre: Computer-based Search, Retrieval, Analysis and Display of Information. Acta Crystallogr., Sect. B 1979, 35, 2331–2339.CrossRefGoogle Scholar
  9. 9.
    Kennard, O., Allen, F., Brice, M., Hummelink, T., Motherwell, W., Rodgers, J., Watson, D. ‘Computer-based Systems for the Retrieval of Data: Crystallography’. Pure Appl. Chem. 1977, 49, 1807–1816.CrossRefGoogle Scholar
  10. 10.
    Murray-Rust, P., Motherwell, W. ‘Computer Retrieval and Analysis of Molecular Geometry. I. General Principles and Methods’. Acta Crystallogr., Sect. B 1978, 34, 2518–2526.CrossRefGoogle Scholar
  11. 11.
    Murray-Rust, P., Bland, R. ‘Computer Retrieval and Analysis of Molecular Geometry. II. Variance and Its Interpretation’. Acta Crystallogr., Sect. B 1978, 34, 2527–2533.CrossRefGoogle Scholar
  12. 12.
    Taylor, R., Kennard, O. ‘The Estimation of Average Molecular Dimensions for Crystallographic Data’. Acta Crystallogr., Sect. B 1983, 39, 517–525.CrossRefGoogle Scholar
  13. 13.
    Wipke, W. T., Dyott, T.M. ‘Use of Ring Assemblies in a Ring Perception Algorithm’. J. Chem. Inf. Comput. Sci. 1975, 25, 140–147.Google Scholar
  14. 14.
    Wipke, W.T., Dyott, T.M. ‘Simulation and Evaluation of Chemical Synthesis. Computer Representation of Stereochemistry’. J. Am. Chem. Soc. 1974, 96, 4825–4834.CrossRefGoogle Scholar
  15. 15.
    A Handbook of Computational Chemistry: A Practical Guide to Chemical Structure and Energy Calculations; Clark, T. Ed.; John Wiley and Sons: New York, 1985.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1988

Authors and Affiliations

  • Mathew A Hahn
    • 1
  • W Todd Wipke
    • 1
  1. 1.Department of ChemistryUniversity of CaliforniaSanta CruzUSA

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