Understanding the physical properties that control protein crystallization by analysis of large-scale experimental data.

TitleUnderstanding the physical properties that control protein crystallization by analysis of large-scale experimental data.
Publication TypeJournal Article
Year of Publication2009
AuthorsW Price, N, Chen, Y, Handelman, SK, Neely, H, Manor, P, Karlin, R, Nair, R, Liu, J, Baran, M, Everett, J, Tong, SN, Forouhar, F, Swaminathan, SS, Acton, T, Xiao, R, Luft, JR, Lauricella, A, DeTitta, GT, Rost, B, Montelione, GT, Hunt, JF
JournalNat Biotechnol
Volume27
Issue1
Pagination51-7
Date Published2009 Jan
ISSN1546-1696
KeywordsAlgorithms, Animals, Biophysics, Computational Biology, Crystallization, Entropy, Epitopes, Humans, Models, Statistical, Protein Folding, Proteins, Surface Properties, Thermodynamics
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.

DOI10.1038/nbt.1514
Alternate JournalNat. Biotechnol.
PubMed ID19079241
PubMed Central IDPMC2746436
Grant ListT32 GM008798-05 / GM / NIGMS NIH HHS / United States
U54 GM074899-01 / GM / NIGMS NIH HHS / United States
U54 GM074958 / GM / NIGMS NIH HHS / United States
U54 GM074958-01 / GM / NIGMS NIH HHS / United States