Journal of Structural and Functional Genomics

The NMR solution structures of the five constituent cold-shock domains (CSD) of the human UNR (upstream of N-ras) protein.

Publication Date: 2010 Mar 6 PMID: 20213426
Authors: Goroncy, A. K. - Koshiba, S. - Tochio, N. - Tomizawa, T. - Inoue, M. - Watanabe, S. - Harada, T. - Tanaka, A. - Ohara, O. - Kigawa, T. - Yokoyama, S.
Journal: J Struct Funct Genomics

Upon cold shock, the amounts of most proteins dramatically decrease from normal levels, but those of cold shock proteins (CSPs) and proteins containing cold-shock domains (CSDs) greatly increase. Although their biological function is still not completely clear, cold-shock proteins might control translation via RNA chaperoning. Many cold-shock proteins contain the motifs (Y/F)GFI and (V/F)(V/F)H, which are known as ribonucleoprotein (RNP)-1 and RNP-2 motifs implicated in RNA/DNA binding. We determined the solution NMR structures of all five constituent CSDs of the human UNR (upstream of N-ras) protein. The spatial arrangements of the sidechains in the RNP-1 and RNP-2 motifs are mostly conserved; however, the conformations of the following residues in the first CSD are different: F43 and H45 (the first phenylalanine residue and the histidine residue in the putative binding site RNP-2) and Y30 (the first residue in the putative binding site RNP-1). F43 and H45 affect each other, and H45 is further influenced by C46. The altered binding site of the first CSD, and its putatively enhanced intrinsic stability, may provide an explanation for the observation that the first CSD has 20-fold higher RNA-binding activity than the fifth CSD. It also lends support to the hypothesis that the UNR protein arose by repeated duplication of a protein that originally contained just one CSD, and that the proto-UNR protein acquired cysteine C46 by mutation during evolution.

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Cleavable C-terminal His-tag vectors for structure determination.

Publication Date: 2010 Mar 6 PMID: 20213425
Authors: Eschenfeldt, W. H. - Maltseva, N. - Stols, L. - Donnelly, M. I. - Gu, M. - Nocek, B. - Tan, K. - Kim, Y. - Joachimiak, A.
Journal: J Struct Funct Genomics

High-throughput structural genomics projects seek to delineate protein structure space by determining the structure of representatives of all major protein families. Generally this is accomplished by processing numerous proteins through standardized protocols, for the most part involving purification of N-terminally His-tagged proteins. Often proteins that fail this approach are abandoned, but in many cases further effort is warranted because of a protein's intrinsic value. In addition, failure often occurs relatively far into the path to structure determination, and many failed proteins passed the first critical step, expression as a soluble protein. Salvage pathways seek to recoup the investment in this subset of failed proteins through alternative cloning, nested truncations, chemical modification, mutagenesis, screening buffers, ligands and modifying processing steps. To this end we have developed a series of ligation-independent cloning expression vectors that append various cleavable C-terminal tags instead of the conventional N-terminal tags. In an initial set of 16 proteins that failed with an N-terminal appendage, structures were obtained for C-terminally tagged derivatives of five proteins, including an example for which several alternative salvaging steps had failed. The new vectors allow appending C-terminal His(6)-tag and His(6)- and MBP-tags, and are cleavable with TEV or with both TEV and TVMV proteases.

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Predicting protein crystallization propensity from protein sequence.

Publication Date: 2010 Feb 23 PMID: 20177794
Authors: Babnigg, G. - Joachimiak, A.
Journal: J Struct Funct Genomics

The high-throughput structure determination pipelines developed by structural genomics programs offer a unique opportunity for data mining. One important question is how protein properties derived from a primary sequence correlate with the protein's propensity to yield X-ray quality crystals (crystallizability) and 3D X-ray structures. A set of protein properties were computed for over 1,300 proteins that expressed well but were insoluble, and for ~720 unique proteins that resulted in X-ray structures. The correlation of the protein's iso-electric point and grand average hydropathy (GRAVY) with crystallizability was analyzed for full length and domain constructs of protein targets. In a second step, several additional properties that can be calculated from the protein sequence were added and evaluated. Using statistical analyses we have identified a set of the attributes correlating with a protein's propensity to crystallize and implemented a Support Vector Machine (SVM) classifier based on these. We have created applications to analyze and provide optimal boundary information for query sequences and to visualize the data. These tools are available via the web site http://bioinformatics.anl.gov/cgi-bin/tools/pdpredictor .

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