Comparisons of NMR spectral quality and success in crystallization demonstrate that NMR and X-ray crystallography are complementary methods for small protein structure determination

X-ray crystallography and NMR spectroscopy provide the only sources of experimental data from which protein structures can be analyzed at high or even atomic resolution. The degree to which these methods complement each other as sources of structural knowledge is a matter of debate; it is often proposed that small proteins yielding high quality, readily analyzed NMR spectra are a subset of those that readily yield strongly diffracting crystals. We have examined the correlation between NMR spectral quality and success in structure determination by X-ray crystallography for 159 prokaryotic and eukaryotic proteins, prescreened to avoid proteins providing polydisperse and/or aggregated samples. This study demonstrates that, across this protein sample set, the quality of a protein's [15N-1H]-heteronuclear correlation (HSQC) spectrum recorded under conditions generally suitable for 3D structure determination by NMR, a key predictor of the ability to determine a structure by NMR, is not correlated with successful crystallization and structure determination by X-ray crystallography. These results, together with similar results of an independent study presented in the accompanying paper (Yee, et al., J. Am. Chem. Soc., accompanying paper), demonstrate that X-ray crystallography and NMR often provide complementary sources of structural data and that both methods are required in order to optimize success for as many targets as possible in large-scale structural proteomics efforts.     

Sensitivity-enhanced sim-CT HMQC PFG-HBHA(CO)NH and PFG-CBCA(CO)NH triple-resonance experiments

Short transverse relaxation times of Calpha and Cbeta single-quantum coherences reduce the sensitivity of triple-resonance experiments involving transfers of Calpha/Cbeta or Halpha/Hbeta coherences. Multiple-quantum line-narrowing techniques improve the relaxation properties of 13C coherences, thereby increasing the sensitivity of the experiment. In the present work, we describe PFG-CBCA(CO)NH and PFG-HBHA(CO)NH experiments that utilize heteronuclear multiple-quantum coherences in a simultaneous constant-time period to obtain completely decoupled spectra with improved sensitivity. Results indicate that approximately 30% of cross peaks show an average enhancement of approximately 15% in the CBCA(CO)NH experiment. In the related HBHA(CO)NH experiment, approximately 97% of the cross peaks show an average enhancement of approximately 40%.     

Determination of the structures of symmetric protein oligomers from NMR chemical shifts and residual dipolar couplings

Symmetric protein dimers, trimers, and higher-order cyclic oligomers play key roles in many biological processes. However, structural studies of oligomeric systems by solution NMR can be difficult due to slow tumbling of the system and the difficulty in identifying NOE interactions across protein interfaces. Here, we present an automated method (RosettaOligomers) for determining the solution structures of oligomeric systems using only chemical shifts, sparse NOEs, and domain orientation restraints from residual dipolar couplings (RDCs) without a need for a previously determined structure of the monomeric subunit. The method integrates previously developed Rosetta protocols for solving the structures of monomeric proteins using sparse NMR data and for predicting the structures of both nonintertwined and intertwined symmetric oligomers. We illustrated the performance of the method using a benchmark set of nine protein dimers, one trimer, and one tetramer with available experimental data and various interface topologies. The final converged structures are found to be in good agreement with both experimental data and previously published high-resolution structures. The new approach is more readily applicable to large oligomeric systems than conventional structure-determination protocols, which often require a large number of NOEs, and will likely become increasingly relevant as more high-molecular weight systems are studied by NMR.     

A generalized approach to automated NMR peak list editing: application to reduced dimensionality triple resonance spectra

We present an algorithm and program called Pattern Picker that performs editing of raw peak lists derived from multidimensional NMR experiments with characteristic peak patterns. Pattern Picker detects groups of correlated peaks within peak lists from reduced dimensionality triple resonance (RD-TR) NMR spectra, with high fidelity and high yield. With typical quality RD-TR NMR data sets, Pattern Picker performs almost as well as human analysis, and is very robust in discriminating real peak sets from noise and other artifacts in unedited peak lists. The program uses a depth-first search algorithm with short-circuiting to efficiently explore a search tree representing every possible combination of peaks forming a group. The Pattern Picker program is particularly valuable for creating an automated peak picking/editing process. The Pattern Picker algorithm can be applied to a broad range of experiments with distinct peak patterns including RD, G-matrix Fourier transformation (GFT) NMR spectra, and experiments to measure scalar and residual dipolar coupling, thus promoting the use of experiments that are typically harder for a human to analyze. Since the complexity of peak patterns becomes a benefit rather than a drawback, Pattern Picker opens new opportunities in NMR experiment design.     

FAST-NMR: functional annotation screening technology using NMR spectroscopy

An abundance of protein structures emerging from structural genomics and the Protein Structure Initiative (PSI) are not amenable to ready functional assignment because of a lack of sequence and structural homology to proteins of known function. We describe a high-throughput NMR methodology (FAST-NMR) to annotate the biological function of novel proteins through the structural and sequence analysis of protein-ligand interactions. This is based on basic tenets of biochemistry where proteins with similar functions will have similar active sites and exhibit similar ligand binding interactions, despite global differences in sequence and structure. Protein-ligand interactions are determined through a tiered NMR screen using a library composed of compounds with known biological activity. A rapid co-structure is determined by combining the experimental identification of the ligand binding site from NMR chemical shift perturbations with the protein-ligand docking program AutoDock. Our CPASS (Comparison of Protein Active Site Structures) software and database are then used to compare this active site with proteins of known function. The methodology is demonstrated using unannotated protein SAV1430 from Staphylococcus aureus.     

Novel anti-Prelog stereospecific carbonyl reductases from Candida parapsilosis for asymmetric reduction of prochiral ketones

The application of biocatalysis to the synthesis of chiral molecules is one of the greenest technologies for the replacement of chemical routes due to its environmentally benign reaction conditions and unparalleled chemo-, regio- and stereoselectivities. We have been interested in searching for carbonyl reductase enzymes and assessing their substrate specificity and stereoselectivity. We now report a gene cluster identified in Candida parapsilosis that consists of four open reading frames including three putative stereospecific carbonyl reductases (scr1, scr2, and scr3) and an alcohol dehydrogenase (cpadh). These newly identified three stereospecific carbonyl reductases (SCRs) showed high catalytic activities for producing (S)-1-phenyl-1,2-ethanediol from 2-hydroxyacetophenone with NADPH as the coenzyme. Together with CPADH, all four enzymes from this cluster are carbonyl reductases with novel anti-Prelog stereoselectivity. SCR1 and SCR3 exhibited distinct specificities to acetophenone derivatives and chloro-substituted 2-hydroxyacetophenones, and especially very high activities towards ethyl 4-chloro-3-oxobutyrate, a β-ketoester with important pharmaceutical potential. Our study also showed that genomic mining is a powerful tool for the discovery of new enzymes.     

Evidence for the quantum birth of our universe

We present evidence for a nonsingular origin of the Universe with intial conditions determined by quantum physics and relativistic gravity. In particular, we establish that the present temperature of the microwave background and the present density of the Universe agree well with our predictions from these intial conditions, after evolution to the present age using the Einstein-Friedmann equation. Remarkably, the quantum origin for the Universe naturally allows its evolution at exactly the critical density. We also discuss the consequences of these results to some fundamental aspects of quantum physics in the early Universe.     

Protein NMR recall, precision, and F-measure scores (RPF scores): structure quality assessment measures based on information retrieval statistics

One of the most important challenges in modern protein NMR is the development of fast and sensitive structure quality assessment measures that can be used to evaluate the "goodness-of-fit" of the 3D structure with NOESY data, to indicate the correctness of the fold and accuracy of the resulting structure. Quality assessment is especially critical for automated NOESY interpretation and structure determination approaches. This paper describes new NMR quality assessment scores, including Recall, Precision, and F-measure scores (referred to here are "NMR RPF" scores), which quickly provide global measures of the goodness-of-fit of the 3D structures with NOESY peak lists using methods from information retrieval statistics. The sensitivity of the F-measure is improved using a scaled Fold Discriminating Power (DP) score. These statistical RPF scores are quite rapid to compute since NOE assignments and complete relaxation matrix calculations are not required. A graphical method for site-specific assessment of structure quality based on the Precision statistic is also described. These statistical measures are demonstrated to be valuable for assessing protein NMR structure accuracy. Their relationships to other proposed NMR "R-factors" and structure quality assessment scores are also discussed.