Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10883648 | Progress in Biophysics and Molecular Biology | 2005 | 25 Pages |
Abstract
This paper discusses a novel approach that may improve the efficiency and success rate for protein crystallization. An automated nanodispensing system is used to rapidly prepare crystallization conditions using minimal sample. Proteins are subjected to an incomplete factorial screen (balanced parameter screen), thereby efficiently searching the entire “crystallization space” for suitable conditions. The screen conditions and scored experimental results are subsequently analyzed using a neural network algorithm to predict new conditions likely to yield improved crystals. Results based on a small number of proteins suggest that the combination of a balanced incomplete factorial screen and neural network analysis may provide an efficient method for producing diffraction-quality protein crystals.
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Authors
Lawrence J. DeLucas, David Hamrick, Larry Cosenza, Lisa Nagy, Debbie McCombs, Terry Bray, Arnon Chait, Brad Stoops, Alexander Belgovskiy, W. William Wilson, Marc Parham, Nikolai Chernov,