Applications of genetic algorithms on the structure - Activity relationship analysis of some cinnamamides

T. J. Hou, J. M. Wang, N. Liao, X. J. Xu

Research output: Contribution to journalArticle

67 Citations (Scopus)

Abstract

Quantitative structure-activity relationships (QSARs) for 35 cinnamamides were studied. By using a genetic algorithm (GA), a group of multiple regression models with high fitness scores was generated. From the statistical analyses of the descriptors used in the evolution procedure, the principal features affecting the anticonvulsant activity were found. The significant descriptors include the partition coefficient, the molar refraction, the Hammet σ constant of the substituents on the benzene ring, and the formation energy of the molecules. It could be found that the steric complementarity and the hydrophobic interaction between the inhibitors and the receptor were very important to the biological activity, while the contribution of the electronic effect was not so obvious. Moreover, by construction of the spline models for these four principal descriptors, the effective range for each descriptor was identified.

Original languageEnglish (US)
Pages (from-to)775-781
Number of pages7
JournalJournal of Chemical Information and Computer Sciences
Volume39
Issue number5
StatePublished - 1999

Fingerprint

activity structure
Genetic algorithms
Bioactivity
Benzene
Refraction
fitness
Splines
Anticonvulsants
electronics
energy
regression
Molecules
interaction
Group
cinnamamide

ASJC Scopus subject areas

  • Chemistry(all)
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems

Cite this

Applications of genetic algorithms on the structure - Activity relationship analysis of some cinnamamides. / Hou, T. J.; Wang, J. M.; Liao, N.; Xu, X. J.

In: Journal of Chemical Information and Computer Sciences, Vol. 39, No. 5, 1999, p. 775-781.

Research output: Contribution to journalArticle

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