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Molecular replacement by evolutionary search.

C R Kissinger1, D K Gehlhaar, B A Smith

  • 1Pfizer Inc., 10350 North Torrey Pines Road, San Diego, CA 92037, USA. chuck_kissinger@stromix.com

Acta Crystallographica. Section D, Biological Crystallography
|September 22, 2001
PubMed
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Stochastic search algorithms, like evolutionary algorithms, rapidly perform molecular replacement. Search model quality significantly impacts efficiency, with polyalanine models often outperforming all-atom models.

Area of Science:

  • Structural biology
  • Computational chemistry
  • Biophysics

Background:

  • Molecular replacement is crucial for determining protein structures.
  • Stochastic search algorithms offer potential for rapid and efficient structure determination.

Purpose of the Study:

  • To evaluate the performance of an evolutionary algorithm for six-dimensional molecular replacement.
  • To assess the impact of search model quality and target function on search efficiency.

Main Methods:

  • Development of a molecular replacement procedure using an evolutionary algorithm.
  • Simultaneous optimization of orientation and position of a search model.
  • Comparison of polyalanine and all-atom models.
  • Evaluation of different target functions (correlation coefficient vs. R factor).

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Main Results:

  • The evolutionary algorithm successfully identified solutions even with low-resolution search models.
  • Search efficiency was highly dependent on the quality of the search model.
  • Polyalanine models demonstrated superior search efficiency compared to all-atom models.
  • Correlation coefficient generally yielded better search efficiency than the R factor.

Conclusions:

  • Evolutionary algorithms are effective for rapid molecular replacement searches.
  • Search model quality is a critical factor for efficient molecular replacement.
  • Further development of evolutionary search algorithms is warranted.