Abstract
Crystallization is the most serious bottleneck in high-throughput protein-structure determination by diffraction methods. We have used data mining of the large-scale experimental results of the Northeast Structural Genomics Consortium and experimental folding studies to characterize the biophysical properties that control protein crystallization. This analysis leads to the conclusion that crystallization propensity depends primarily on the prevalence of well-ordered surface epitopes capable of mediating interprotein interactions and is not strongly influenced by overall thermodynamic stability. We identify specific sequence features that correlate with crystallization propensity and that can be used to estimate the crystallization probability of a given construct. Analyses of entire predicted proteomes demonstrate substantial differences in the amino acid–sequence properties of human versus eubacterial proteins, which likely reflect differences in biophysical properties, including crystallization propensity. Our thermodynamic measurements do not generally support previous claims regarding correlations between sequence properties and protein stability.
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Acknowledgements
This work was supported by Protein Structure Initiative grants from the National Institutes of Health (NIH) to the Northeast Structural Genomics Consortium and the Center for High-Throughput Structural Biology. The full staffs of these consortia contributed to the experimental data analyzed in this paper. W.N.P. II was supported in part by an NIH training grant to the Department of Biological Sciences at Columbia, and S.K.H. was supported in part by a National Science Foundation grant to J.F.H. The authors thank Wayne Hendrickson and Liang Tong for support and advice and John Schwanoff and the New York Structural Biology Center for maintenance of the X4 beamlines at Brookhaven National Laboratory.
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Price II, W., Chen, Y., Handelman, S. et al. Understanding the physical properties that control protein crystallization by analysis of large-scale experimental data. Nat Biotechnol 27, 51–57 (2009). https://doi.org/10.1038/nbt.1514
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DOI: https://doi.org/10.1038/nbt.1514
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