A hybrid genetic algorithm with pattern search for finding heavy atoms in protein crystals

  • Authors:

  • Joshua L. Payne;Margaret J. Eppstein

  • Affiliations:

  • University of Vermont, Burlington, VT;University of Vermont, Burlington, VT

  • Venue:
  • GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
  • Year:
  • 2005

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Abstract

One approach for determining the molecular structure of proteins is a technique called iso-morphous replacement, in which crystallographers dope protein crystals with heavy atoms, such as mercury or platinum. By comparing measured amplitudes of diffracted x-rays through protein crystals with and without the heavy atoms, the locations of the heavy atoms can be estimated. Once the locations of the heavy atoms are known, the phases of the diffracted x-rays through the protein crystal can be estimated, which in turn enables the structure of the protein to be estimated. Unfortunately, the key step in this process is the estimation of the locations of the heavy atoms, and this is a multi-modal, non-linear inverse problem. We report results of a pilot study that show that a 2-stage hybrid algorithm, using a stochastic genetic algorithm for stage 1 followed by a deterministic pattern search algorithm for stage 2, can successfully locate up to 5 heavy atoms in computer simulated crystals using noise free data. We conclude that the method may be a viable approach for finding heavy atoms in protein crystals, and suggest ways in which the approach can be scaled up to larger problems.