Journal of Computer-Aided Molecular Design

, Volume 8, Issue 4, pp 421–432 | Cite as

Quantitative structure-activity relationships by neural networks and inductive logic programming. II. The inhibition of dihydrofolate reductase by triazines

  • Jonathan D. Hirst
  • Ross D. King
  • Michael J. E. Sternberg
Research Papers

Summary

One of the largest available data sets for developing a quantitative structure-activity relationship (QSAR) — the inhibition of dihydrofolate reductase (DHFR) by 2,4-diamino-6,6-dimethyl-5-phenyl-dihydrotriazine derivatives — has been used for a sixfold cross-validation trial of neural networks, inductive logic programming (ILP) and linear regression. No statistically significant difference was found between the predictive capabilities of the methods. However, the representation of molecules by attributes, which is integral to the ILP approach, provides understandable rules about drug-receptor interactions.

Key words

QSAR Artificial intelligence Neural networks DHFR inhibitors 

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Copyright information

© ESCOM Science Publishers B.V 1994

Authors and Affiliations

  • Jonathan D. Hirst
    • 1
  • Ross D. King
    • 1
  • Michael J. E. Sternberg
    • 1
  1. 1.Biomolecular Modelling LaboratoryImperial Cancer Research FundLondonU.K.

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