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Differential evolution for protein crystallographic optimizations.

Duncan E McRee
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Abstract

Genetic algorithms are powerful optimizers that have been underutilized in protein crystallography, given that many crystallographic problems have characteristics that would benefit from these algorithms: non-linearity, interdependent parameters and a complex function landscape. These functions have been implemented for real-space optimizations in a new fitting program, MIfit, for real-space refinement of protein models and heavy-atom searches. Some programming tips and examples will be presented here to aid others who might want to use genetic algorithms in their own work.

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AlgorithmsCrystallography, X-RayModels, MolecularProtein ConformationProteinsJournal Article

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Duncan E McRee. 2004-11-26. Differential evolution for protein crystallographic optimizations.. https://doi.org/10.1107/s0907444904025491

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PubMed2026

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