In selecting a method to produce a recombinant protein, a researcher is faced with a bewildering array of choices as to where to start. To facilitate decision-making, we describe a consensus 'what to try first' strategy based on our collective analysis of the expression and purification of over 10,000 different proteins. This review presents methods that could be applied at the outset of any project, a prioritized list of alternate strategies and a list of pitfalls that trip many new investigators.
Assigning valid functions to proteins identified in genome projects is challenging, with over-prediction and database annotation errors major concerns1. We, and others2, are developing computation-guided strategies for functional discovery using “metabolite docking” to experimentally derived3 or homology-based4 three-dimensional structures. Bacterial metabolic pathways often are encoded by “genome neighborhoods” (gene clusters and/or operons), which can provide important clues for functional assignment. We recently demonstrated the synergy of docking and pathway context by “predicting” the intermediates in the glycolytic pathway in E. coli5. Metabolite docking to multiple binding proteins/enzymes in the same pathway increases the reliability of in silico predictions of substrate specificities because the pathway intermediates are structurally similar. We report that structure-guided approaches for predicting the substrate specificities of several enzymes encoded by a bacterial gene cluster allowed i) the correct prediction of the in vitro activity of a structurally characterized enzyme of unknown function (PDB 2PMQ), 2-epimerization of trans-4-hydroxy-L-proline betaine (tHyp-B) and cis-4-hydroxy-D-proline betaine (cHyp-B), and ii) the correct identification of the catabolic pathway in which Hyp-B 2-epimerase participates. The substrate-liganded pose predicted by virtual library screening (docking) was confirmed experimentally. The enzymatic activities in the predicted pathway were confirmed by in vitro assays and genetic analyses; the intermediates were identified by metabolomics; and repression of the genes encoding the pathway by high salt was established by transcriptomics, confirming the osmolyte role of tHyp-B. This study establishes the utility of structure-guide functional predictions to enable the discovery of new metabolic pathways.
The nuclear pore complex (NPC) is the sole passageway for the transport of macromolecules across the nuclear envelope. Nup133, a major component in the essential Y-shaped Nup84 complex, is a large scaffold protein of the NPC's outer ring structure. Here, we describe an integrative modeling approach that produces atomic models for multiple states of Saccharomyces cerevisiae (Sc) Nup133, based on the crystal structures of the sequence segments and their homologs, including the related Vanderwaltozyma polyspora (Vp) Nup133 residues 55 to 502 (VpNup133 55-502 ) determined in this study, small angle X-ray scattering profiles for 18 constructs of ScNup133 and one construct of VpNup133, and 23 negative-stain electron microscopy class averages of ScNup133 2-1157 . Using our integrative approach, we then computed a multi-state structural model of the full-length ScNup133 and validated it with mutational studies and 45 chemical cross-links determined via mass spectrometry. Finally, the model of ScNup133 allowed us to annotate a potential ArfGAP1 lipid packing sensor (ALPS) motif in Sc and VpNup133 and discuss its potential significance in the context of the whole NPC; we suggest that ALPS motifs are scattered throughout the NPC's scaffold in all eukaryotes and play a major role in the assembly and membrane anchoring of the NPC in the nuclear envelope. Our results are consistent with a common evolutionary origin of Nup133 with membrane coating complexes (the protocoatomer hypothesis); the presence of the ALPS motifs in coatomer-like nucleoporins suggests an ancestral mechanism for membrane recognition present in early membrane coating complexes. Molecular & Cellular Proteomics 13:
High-resolution structural information is important for improving our understanding of protein function in vitro and in vivo and providing information to enable drug discovery. The process leading to X-ray structure determination is often time consuming and labor intensive. It requires informed decisions in expression construct design, expression host selection, and strategies for protein purification, crystallization and structure determination. Previously published studies have demonstrated that compact globular domains defined by limited proteolysis represent good candidates for production of diffraction quality crystals [1-7]. Integration of mass spectrometry and proteolysis experiments can provide accurate definition of domain boundaries at unprecedented rates. We have conducted a critical evaluation of this approach with 400 target proteins produced by SGX (Structural GenomiX, Inc.) for the New York Structural GenomiX Research Consortium (NYSGXRC; http://www.nysgxrc.org) under the auspices of the National Institute of General Medical Sciences Protein Structure Initiative (http://www.nigms.nih.gov/psi). The objectives of this study were to develop parallel/automated protocols for proteolytic digestion and data acquisition for multiple proteins, and to carry out a systematic study to correlate domain definition via proteolysis with outcomes of crystallization and structure determination attempts. Initial results from this work demonstrate that proteins yielding diffraction quality crystals are typically resistant to proteolysis. Large-scale sub cloning and subsequent testing of expression, solubility, and crystallizability of proteolytically defined truncations is currently underway.
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