An integrated platform for automated analysis of protein NMR structures

A topology-constrained distance network algorithm for protein structure determination from NOESY data

This article formulates the multidimensional nuclear Overhauser effect spectroscopy (NOESY) interpretation problem using graph theory and presents a novel, bottom-up, topology-constrained distance network analysis algorithm for NOESY cross peak interpretation using assigned resonances. AutoStructure is a software suite that implements this topology-constrained distance network analysis algorithm and iteratively generates structures using the three-dimensional (3D) protein structure calculation programs XPLOR/CNS or DYANA. The minimum input for AutoStructure includes the amino acid sequence, a list of resonance assignments, and lists of 2D, 3D, and/or 4D-NOESY cross peaks. AutoStructure can also analyze homodimeric proteins when X-filtered NOESY experiments are available. The quality of input data and final 3D structures is evaluated using recall, precision, and F-measure (RPF) scores, a statistical measure of goodness of fit with the input data. AutoStructure has been tested on three protein NMR data sets for which high-quality structures have previously been solved by an expert, and yields comparable high-quality distance constraint lists and 3D protein structures in hours. We also compare several protein structures determined using AutoStructure with corresponding homologous proteins determined with other independent methods. The program has been used in more than two dozen protein structure determinations, several of which have already been published.

SPINS: a laboratory information management system for organizing and archiving intermediate and final results from NMR protein structure determinations

Recent technological advances and experimental techniques have contributed to an increasing number and size of NMR datasets. In order to scale up productivity, laboratory information management systems for handling these extensive data need to be designed and implemented. The SPINS (Standardized ProteIn Nmr Storage) Laboratory Information Management System (LIMS) addresses these needs by providing an interface for archival of complete protein NMR structure determinations, together with functionality for depositing these data to the public BioMagResBank (BMRB). The software tracks intermediate files during each step of an NMR structure-determination process, including: data collection, data processing, resonance assignments, resonance assignment validation, structure calculation, and structure validation. The underlying SPINS data dictionary allows for the integration of various third party NMR data processing and analysis software, enabling users to launch programs they are accustomed to using for each step of the structure determination process directly out of the SPINS user interface.

Traditional biomolecular structure determination by NMR spectroscopy allows for major errors

One of the major goals of structural genomics projects is to determine the three-dimensional structure of representative members of as many different fold families as possible. Comparative modeling is expected to fill the remaining gaps by providing structural models of homologs of the experimentally determined proteins. However, for such an approach to be successful it is essential that the quality of the experimentally determined structures is adequate. In an attempt to build a homology model for the protein dynein light chain 2A (DLC2A) we found two potential templates, both experimentally determined nuclear magnetic resonance (NMR) structures originating from structural genomics efforts. Despite their high sequence identity (96%), the folds of the two structures are markedly different. This urged us to perform in-depth analyses of both structure ensembles and the deposited experimental data, the results of which clearly identify one of the two models as largely incorrect. Next, we analyzed the quality of a large set of recent NMR-derived structure ensembles originating from both structural genomics projects and individual structure determination groups. Unfortunately, a visual inspection of structures exhibiting lower quality scores than DLC2A reveals that the seriously flawed DLC2A structure is not an isolated incident. Overall, our results illustrate that the quality of NMR structures cannot be reliably evaluated using only traditional experimental input data and overall quality indicators as a reference and clearly demonstrate the urgent need for a tight integration of more sophisticated structure validation tools in NMR structure determination projects. In contrast to common methodologies where structures are typically evaluated as a whole, such tools should preferentially operate on a per-residue basis.

Three-dimensional biomolecular structures provide an invaluable source of biologically relevant information. To be able to learn the most of the wealth of information that these structures can provide us, it is of great importance that the quality and accuracy of the protein structure models deposited in the Protein Data Bank are as high as possible. In this work, the authors describe an analysis that illustrates that this is unfortunately not the case for many protein structures solved using nuclear magnetic resonance spectroscopy. They present an example in which two strikingly different models describing the same protein are analyzed using commonly available structure validation tools, and the results of this analysis show one of the two models to be incorrect. Subsequently, using a large set of recently determined structures, the authors demonstrate that unfortunately this example does not stand on its own. The analyses and examples clearly illustrate that relying solely on the experimental data to evaluate structural quality can provide a false sense of correctness and the combination of multiple sophisticated structure validation tools is required to detect the presence of errors in protein nuclear magnetic resonance structures.

Solution structure of Archaeglobus fulgidis peptidyl-tRNA hydrolase (Pth2) provides evidence for an extensive conserved family of Pth2 enzymes in archea, bacteria, and eukaryotes

The solution structure of protein AF2095 from the thermophilic archaea Archaeglobus fulgidis, a 123-residue (13.6-kDa) protein, has been determined by NMR methods. The structure of AF2095 is comprised of four alpha-helices and a mixed beta-sheet consisting of four parallel and anti-parallel beta-strands, where the alpha-helices sandwich the beta-sheet. Sequence and structural comparison of AF2095 with proteins from Homo sapiens, Methanocaldococcus jannaschii, and Sulfolobus solfataricus reveals that AF2095 is a peptidyl-tRNA hydrolase (Pth2). This structural comparison also identifies putative catalytic residues and a tRNA interaction region for AF2095. The structure of AF2095 is also similar to the structure of protein TA0108 from archaea Thermoplasma acidophilum, which is deposited in the Protein Data Bank but not functionally annotated. The NMR structure of AF2095 has been further leveraged to obtain good-quality structural models for 55 other proteins. Although earlier studies have proposed that the Pth2 protein family is restricted to archeal and eukaryotic organisms, the similarity of the AF2095 structure to human Pth2, the conservation of key active-site residues, and the good quality of the resulting homology models demonstrate a large family of homologous Pth2 proteins that are conserved in eukaryotic, archaeal, and bacterial organisms, providing novel insights in the evolution of the Pth and Pth2 enzyme families.

NMR data collection and analysis protocol for high-throughput protein structure determination

A standardized protocol enabling rapid NMR data collection for high-quality protein structure determination is presented that allows one to capitalize on high spectrometer sensitivity: a set of five G-matrix Fourier transform NMR experiments for resonance assignment based on highly resolved 4D and 5D spectral information is acquired in conjunction with a single simultaneous 3D 15N,13C(aliphatic),13C(aromatic)-resolved [1H,1H]-NOESY spectrum providing 1H-1H upper distance limit constraints. The protocol was integrated with methodology for semiautomated data analysis and used to solve eight NMR protein structures of the Northeast Structural Genomics Consortium pipeline. The molecular masses of the hypothetical target proteins ranged from 9 to 20 kDa with an average of approximately 14 kDa. Between 1 and 9 days of instrument time were invested per structure, which is less than approximately 10-25% of the measurement time routinely required to date with conventional approaches. The protocol presented here effectively removes data collection as a bottleneck for high-throughput solution structure determination of proteins up to at least approximately 20 kDa, while concurrently providing spectra that are highly amenable to fast and robust analysis.