A Genetic Algorithm for Conformational Search of Organic Molecules: Implications for Materials Chemistry

Milan Keser*, Samuel I. Stupp

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

A genetic algorithm was designed in order to predict the low-energy conformations of organic molecules, particularly those of interest in the study of self assembly. The molecules of interest typically have many degrees of freedom so that it is difficult to minimize their conformational energies by conventional means. This has been our motivation in developing a genetic algorithm tailored specifically for efficient conformational search. The algorithm incorporates binary coding, fitness proportional selection, full generational replacement, N-point crossover, fitness scaling and niching. The algorithm was able to predict the minimum energy conformation of tricosane (C23H48) after only several thousand energy evaluations. Furthermore, the algorithm found low-energy conformations of self assembling molecules synthesized in our laboratory which match predictions based on X-ray and electron diffraction data.

Original languageEnglish (US)
Pages (from-to)345-351
Number of pages7
JournalComputers and Chemistry
Volume22
Issue number4
StatePublished - Jun 20 1998

Funding

Acknowledgements*The authors are grateful to the National Science Foundation for support of this work through grant DMR!8201590[

Keywords

  • Genetic algorithm
  • Organic molecules
  • Self assembly

ASJC Scopus subject areas

  • Biotechnology
  • Applied Microbiology and Biotechnology
  • General Chemical Engineering

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