J-UNIO protocol used for NMR structure determination of the 206-residue protein NP_346487.1 from <Emphasis Type="Italic">Streptococcus pneumoniae TIGR4</Emphasis>

The NMR structure of the 206-residue protein NP_346487.1 was determined with the J-UNIO protocol, which includes extensive automation of the structure determination. With input from three APSY-NMR experiments, UNIO-MATCH automatically yielded 77 % of the backbone assignments, which were interactively validated and extended to 97 %. With an input of the near-complete backbone assignments and three 3D heteronuclear-resolved [¹H,¹H]-NOESY spectra, automated side chain assignment with UNIO-ATNOS/ASCAN resulted in 77 % of the expected assignments, which was extended interactively to about 90 %. Automated NOE assignment and structure calculation with UNIO-ATNOS/CANDID in combination with CYANA was used for the structure determination of this two-domain protein. The individual domains in the NMR structure coincide closely with the crystal structure, and the NMR studies further imply that the two domains undergo restricted hinge motions relative to each other in solution. NP_346487.1 is so far the largest polypeptide chain to which the J-UNIO structure determination protocol has successfully been applied.     

Reliability of exclusively NOESY-based automated resonance assignment and structure determination of proteins

Protein structure determination by NMR can in principle be speeded up both by reducing the measurement time on the NMR spectrometer and by a more efficient analysis of the spectra. Here we study the reliability of protein structure determination based on a single type of spectra, namely nuclear Overhauser effect spectroscopy (NOESY), using a fully automated procedure for the sequence-specific resonance assignment with the recently introduced FLYA algorithm, followed by combined automated NOE distance restraint assignment and structure calculation with CYANA. This NOESY-FLYA method was applied to eight proteins with 63–160 residues for which resonance assignments and solution structures had previously been determined by the Northeast Structural Genomics Consortium (NESG), and unrefined and refined NOESY data sets have been made available for the Critical Assessment of Automated Structure Determination of Proteins by NMR project. Using only peak lists from three-dimensional ¹³C- or ¹⁵N-resolved NOESY spectra as input, the FLYA algorithm yielded for the eight proteins 91–98 % correct backbone and side-chain assignments if manually refined peak lists are used, and 64–96 % correct assignments based on raw peak lists. Subsequent structure calculations with CYANA then produced structures with root-mean-square deviation (RMSD) values to the manually determined reference structures of 0.8–2.0 Å if refined peak lists are used. With raw peak lists, calculations for 4 proteins converged resulting in RMSDs to the reference structure of 0.8–2.8 Å, whereas no convergence was obtained for the four other proteins (two of which did already not converge with the correct manual resonance assignments given as input). These results show that, given high-quality experimental NOESY peak lists, the chemical shift assignments can be uncovered, without any recourse to traditional through-bond type assignment experiments, to an extent that is sufficient for calculating accurate three-dimensional structures.     

Fully automated high-quality NMR structure determination of small <Superscript>2</Superscript>H-enriched proteins

Determination of high-quality small protein structures by nuclear magnetic resonance (NMR) methods generally requires acquisition and analysis of an extensive set of structural constraints. The process generally demands extensive backbone and sidechain resonance assignments, and weeks or even months of data collection and interpretation. Here we demonstrate rapid and high-quality protein NMR structure generation using CS-Rosetta with a perdeuterated protein sample made at a significantly reduced cost using new bacterial culture condensation methods. Our strategy provides the basis for a high-throughput approach for routine, rapid, high-quality structure determination of small proteins. As an example, we demonstrate the determination of a high-quality 3D structure of a small 8 kDa protein, E. coli cold shock protein A (CspA), using <4 days of data collection and fully automated data analysis methods together with CS-Rosetta. The resulting CspA structure is highly converged and in excellent agreement with the published crystal structure, with a backbone RMSD value of 0.5 Å, an all atom RMSD value of 1.2 Å to the crystal structure for well-defined regions, and RMSD value of 1.1 Å to crystal structure for core, non-solvent exposed sidechain atoms. Cross validation of the structure with ¹⁵N- and ¹³C-edited NOESY data obtained with a perdeuterated ¹⁵N, ¹³C-enriched ¹³CH₃ methyl protonated CspA sample confirms that essentially all of these independently-interpreted NOE-based constraints are already satisfied in each of the 10 CS-Rosetta structures. By these criteria, the CS-Rosetta structure generated by fully automated analysis of data for a perdeuterated sample provides an accurate structure of CspA. This represents a general approach for rapid, automated structure determination of small proteins by NMR.     

Protein NMR structure determination with automated NOE-identification in the NOESY spectra using the new software ATNOS

Novel algorithms are presented for automated NOESY peak picking and NOE signal identification in homonuclear 2D and heteronuclear-resolved 3D [¹H,¹H]-NOESY spectra during de novoprotein structure determination by NMR, which have been implemented in the new software ATNOS (automated NOESY peak picking). The input for ATNOS consists of the amino acid sequence of the protein, chemical shift lists from the sequence-specific resonance assignment, and one or several 2D or 3D NOESY spectra. In the present implementation, ATNOS performs multiple cycles of NOE peak identification in concert with automated NOE assignment with the software CANDID and protein structure calculation with the program DYANA. In the second and subsequent cycles, the intermediate protein structures are used as an additional guide for the interpretation of the NOESY spectra. By incorporating the analysis of the raw NMR data into the process of automated de novoprotein NMR structure determination, ATNOS enables direct feedback between the protein structure, the NOE assignments and the experimental NOESY spectra. The main elements of the algorithms for NOESY spectral analysis are techniques for local baseline correction and evaluation of local noise level amplitudes, automated determination of spectrum-specific threshold parameters, the use of symmetry relations, and the inclusion of the chemical shift information and the intermediate protein structures in the process of distinguishing between NOE peaks and artifacts. The ATNOS procedure has been validated with experimental NMR data sets of three proteins, for which high-quality NMR structures had previously been obtained by interactive interpretation of the NOESY spectra. The ATNOS-based structures coincide closely with those obtained with interactive peak picking. Overall, we present the algorithms used in this paper as a further important step towards objective and efficient de novoprotein structure determination by NMR.     

Influence of the completeness of chemical shift assignments on NMR structures obtained with automated NOE assignment

Reliable automated NOE assignment and structure calculation on the basis of a largely complete, assigned input chemical shift list and a list of unassigned NOESY cross peaks has recently become feasible for routine NMR protein structure calculation and has been shown to yield results that are equivalent to those of the conventional, manual approach. However, these algorithms rely on the availability of a virtually complete list of the chemical shifts. This paper investigates the influence of incomplete chemical shift assignments on the reliability of NMR structures obtained with automated NOESY cross peak assignment. The program CYANA was used for combined automated NOESY assignment with the CANDID algorithm and structure calculations with torsion angle dynamics at various degrees of completeness of the chemical shift assignment which was simulated by random omission of entries in the experimental ¹H chemical shift lists that had been used for the earlier, conventional structure determinations of two proteins. Sets of structure calculations were performed choosing the omitted chemical shifts randomly among all assigned hydrogen atoms, or among aromatic hydrogen atoms. For comparison, automated NOESY assignment and structure calculations were performed with the complete experimental chemical shift but under random omission of NOESY cross peaks. When heteronuclear-resolved three-dimensional NOESY spectra are available the current CANDID algorithm yields in the absence of up to about 10% of the experimental ¹H chemical shifts reliable NOE assignments and three-dimensional structures that deviate by less than 2 Å from the reference structure obtained using all experimental chemical shift assignments. In contrast, the algorithm can accommodate the omission of up to 50% of the cross peaks in heteronuclear- resolved NOESY spectra without producing structures with a RMSD of more than 2 Å to the reference structure. When only homonuclear NOESY spectra are available, the algorithm is slightly more susceptible to missing data and can tolerate the absence of up to about 7% of the experimental ¹H chemical shifts or of up to 30% of the NOESY peaks.Abbreviations: BmPBP^A – Bombyx mori pheromone binding protein form A; CYANA – combined assignment and dynamics algorithm for NMR applications; NMR – nuclear magnetic resonance; NOE – nuclear Overhauser effect; NOESY – NOE spectroscopy; RMSD – root-mean-square deviation; WmKT – Williopsis mrakii killer toxin     

1H, 13C and 15N resonance assignments of wild-type Bacillus subtilis Lipase A and its mutant evolved towards thermostability

Previously, we evolved Lipase A from Bacillus subtilis towards increased thermostability. The resulting mutant retains significant catalytic activity upon heating above 60 °C (and up to 100 °C) and cooling down, whereas wild-type lipase precipitates irreversibly and does not show significant activity in these conditions. Kinetic thermostability of proteins has not been characterized well on the molecular structure level so far, therefore our aim is to study it using NMR spectroscopy. Here, nearly complete ¹H, ¹³C and ¹⁵N resonance assignments are reported for wild-type and mutant Lipase A. Chemical shifts were used to predict secondary structure elements of both Lipase A variants.     

The J-UNIO protocol for automated protein structure determination by NMR in solution

The J-UNIO (JCSG protocol using the software UNIO) procedure for automated protein structure determination by NMR in solution is introduced. In the present implementation, J-UNIO makes use of APSY-NMR spectroscopy, 3D heteronuclear-resolved [(1)H,(1)H]-NOESY experiments, and the software UNIO. Applications with proteins from the JCSG target list with sizes up to 150 residues showed that the procedure is highly robust and efficient. In all instances the correct polypeptide fold was obtained in the first round of automated data analysis and structure calculation. After interactive validation of the data obtained from the automated routine, the quality of the final structures was comparable to results from interactive structure determination. Special advantages are that the NMR data have been recorded with 6-10 days of instrument time per protein, that there is only a single step of chemical shift adjustments to relate the backbone signals in the APSY-NMR spectra with the corresponding backbone signals in the NOESY spectra, and that the NOE-based amino acid side chain chemical shift assignments are automatically focused on those residues that are heavily weighted in the structure calculation. The individual working steps of J-UNIO are illustrated with the structure determination of the protein YP_926445.1 from Shewanella amazonensis, and the results obtained with 17 JCSG targets are critically evaluated.     

Construct optimization for protein NMR structure analysis using amide hydrogen/deuterium exchange mass spectrometry

Disordered or unstructured regions of proteins, while often very important biologically, can pose significant challenges for resonance assignment and three‐dimensional structure determination of the ordered regions of proteins by NMR methods. In this article, we demonstrate the application of ¹H/²H exchange mass spectrometry (DXMS) for the rapid identification of disordered segments of proteins and design of protein constructs that are more suitable for structural analysis by NMR. In this benchmark study, DXMS is applied to five NMR protein targets chosen from the Northeast Structural Genomics project. These data were then used to design optimized constructs for three partially disordered proteins. Truncated proteins obtained by deletion of disordered N‐ and C‐terminal tails were evaluated using ¹H‐¹⁵N HSQC and ¹H‐¹⁵N heteronuclear NOE NMR experiments to assess their structural integrity. These constructs provide significantly improved NMR spectra, with minimal structural perturbations to the ordered regions of the protein structure. As a representative example, we compare the solution structures of the full length and DXMS‐based truncated construct for a 77‐residue partially disordered DUF896 family protein YnzC from Bacillus subtilis, where deletion of the disordered residues (ca. 40% of the protein) does not affect the native structure. In addition, we demonstrate that throughput of the DXMS process can be increased by analyzing mixtures of up to four proteins without reducing the sequence coverage for each protein. Our results demonstrate that DXMS can serve as a central component of a process for optimizing protein constructs for NMR structure determination. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Practical use of chemical shift databases for protein solid-state NMR: 2D chemical shift maps and amino-acid assignment with secondary-structure information

We introduce a Python-based program that utilizes the large database of ¹³C and ¹⁵N chemical shifts in the Biological Magnetic Resonance Bank to rapidly predict the amino acid type and secondary structure from correlated chemical shifts. The program, called PACSYlite Unified Query (PLUQ), is designed to help assign peaks obtained from 2D ¹³C–¹³C, ¹⁵N–¹³C, or 3D ¹⁵N–¹³C–¹³C magic-angle-spinning correlation spectra. We show secondary-structure specific 2D ¹³C–¹³C correlation maps of all twenty amino acids, constructed from a chemical shift database of 262,209 residues. The maps reveal interesting conformation-dependent chemical shift distributions and facilitate searching of correlation peaks during amino-acid type assignment. Based on these correlations, PLUQ outputs the most likely amino acid types and the associated secondary structures from inputs of experimental chemical shifts. We test the assignment accuracy using four high-quality protein structures. Based on only the Cα and Cβ chemical shifts, the highest-ranked PLUQ assignments were 40–60 % correct in both the amino-acid type and the secondary structure. For three input chemical shifts (CO–Cα–Cβ or N–Cα–Cβ), the first-ranked assignments were correct for 60 % of the residues, while within the top three predictions, the correct assignments were found for 80 % of the residues. PLUQ and the chemical shift maps are expected to be useful at the first stage of sequential assignment, for combination with automated sequential assignment programs, and for highly disordered proteins for which secondary structure analysis is the main goal of structure determination.     

CSSI-PRO: a method for secondary structure type editing,assignment and estimation in proteins using linear combination of backbone chemical shifts

Estimation of secondary structure in polypeptides is important for studying their structure, folding and dynamics. In NMR spectroscopy, such information is generally obtained after sequence specific resonance assignments are completed. We present here a new methodology for assignment of secondary structure type to spin systems in proteins directly from NMR spectra, without prior knowledge of resonance assignments. The methodology, named Combination of Shifts for Secondary Structure Identification in Proteins (CSSI-PRO), involves detection of specific linear combination of backbone ¹H^α and ¹³C′ chemical shifts in a two-dimensional (2D) NMR experiment based on G-matrix Fourier transform (GFT) NMR spectroscopy. Such linear combinations of shifts facilitate editing of residues belonging to α-helical/β-strand regions into distinct spectral regions nearly independent of the amino acid type, thereby allowing the estimation of overall secondary structure content of the protein. Comparison of the predicted secondary structure content with those estimated based on their respective 3D structures and/or the method of Chemical Shift Index for 237 proteins gives a correlation of more than 90% and an overall rmsd of 7.0%, which is comparable to other biophysical techniques used for structural characterization of proteins. Taken together, this methodology has a wide range of applications in NMR spectroscopy such as rapid protein structure determination, monitoring conformational changes in protein-folding/ligand-binding studies and automated resonance assignment. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

High resolution solid-state NMR spectroscopy of the <Emphasis Type="Italic">Yersinia pestis</Emphasis> outer membrane protein Ail in lipid membranes

The outer membrane protein Ail (Adhesion invasion locus) is one of the most abundant proteins on the cell surface of Yersinia pestis during human infection. Its functions are expressed through interactions with a variety of human host proteins, and are essential for microbial virulence. Structures of Ail have been determined by X-ray diffraction and solution NMR spectroscopy, but those samples contained detergents that interfere with functionality, thus, precluding analysis of the structural basis for Ail’s biological activity. Here, we demonstrate that high-resolution solid-state NMR spectra can be obtained from samples of Ail in detergent-free phospholipid liposomes, prepared with a lipid to protein molar ratio of 100. The spectra, obtained with ¹³C or ¹H detection, have very narrow line widths (0.40–0.60 ppm for ¹³C, 0.11–0.15 ppm for ¹H, and 0.46–0.64 ppm for ¹⁵N) that are consistent with a high level of sample homogeneity. The spectra enable resonance assignments to be obtained for N, CO, CA and CB atomic sites from 75 out of 156 residues in the sequence of Ail, including 80% of the transmembrane region. The ¹H-detected solid-state NMR ¹H/¹⁵N correlation spectra obtained for Ail in liposomes compare very favorably with the solution NMR ¹H/¹⁵N TROSY spectra obtained for Ail in nanodiscs prepared with a similar lipid to protein molar ratio. These results set the stage for studies of the molecular basis of the functional interactions of Ail with its protein partners from human host cells, as well as the development of drugs targeting Ail.     

EZ-ASSIGN, a program for exhaustive NMR chemical shift assignments of large proteins from complete or incomplete triple-resonance data

For several of the proteins in the BioMagResBank larger than 200 residues, 60 % or fewer of the backbone resonances were assigned. But how reliable are those assignments? In contrast to complete assignments, where it is possible to check whether every triple-resonance Generalized Spin System (GSS) is assigned once and only once, with incomplete data one should compare all possible assignments and pick the best one. But that is not feasible: For example, for 200 residues and an incomplete set of 100 GSS, there are 1.6 × 10²⁶⁰ possible assignments. In “EZ-ASSIGN”, the protein sequence is divided in smaller unique fragments. Combined with intelligent search approaches, an exhaustive comparison of all possible assignments is now feasible using a laptop computer. The program was tested with experimental data of a 388-residue domain of the Hsp70 chaperone protein DnaK and for a 351-residue domain of a type III secretion ATPase. EZ-ASSIGN reproduced the hand assignments. It did slightly better than the computer program PINE (Bahrami et al. in PLoS Comput Biol 5(3):e1000307, 2009) and significantly outperformed SAGA (Crippen et al. in J Biomol NMR 46:281–298, 2010), AUTOASSIGN (Zimmerman et al. in J Mol Biol 269:592–610, 1997), and IBIS (Hyberts and Wagner in J Biomol NMR 26:335–344, 2003). Next, EZ-ASSIGN was used to investigate how well NMR data of decreasing completeness can be assigned. We found that the program could confidently assign fragments in very incomplete data. Here, EZ-ASSIGN dramatically outperformed all the other assignment programs tested.     

High resolution nmr and x-ray crystallography data of caudicifolin from Euphorbia acaulis

A diterpene lactone was isolated from the cold petrol (60−80°) extract of rhizomes of Euphorbia acaulis, a plant material used by a tribe of central India for curing various inflammatory disorder. The diterpene, which was observed to be identical to caudicifolin on the basis of its physical constants, was subjected to high resolution NMR spectroscopy and X-ray crystallography examination. This paper reports the salient features of the 2D ¹H NMR, ¹³C NMR and X-ray crystallography data of the compound. ¹³C NMR assignments were made by the use of proton noise decoupling, SFORD, APT and automatic spectral editing techniques. ¹H NMR assignments were made with the aid of a COSY experiment for long range couplings and NOE correlated 2D-experiments. The ¹H and ¹³C NMR spectral assignments have been further corroborated by H/C correlation experimental results.     

Automated assignment of NMR chemical shifts using peak-particle dynamics simulation with the DYNASSIGN algorithm

A new algorithm, DYNASSIGN, for the automated assignment of NMR chemical shift resonances was developed in which expected cross peaks in multidimensional NMR spectra are represented by peak-particles and assignment restraints are translated into a potential energy function. Molecular dynamics simulation techniques are used to calculate a trajectory of the system of peak-particles subjected to the potential function in order to find energetically optimal configurations that correspond to correct assignments. Peak-particle dynamics-based simulated annealing was combined with the Hungarian algorithm for local optimization, and a residue-based score was introduced to distinguish between reliable assignments and “unassigned” resonances for which no reliable assignment can be established. The DYNASSIGN algorithm was implemented in the program CYANA and tested with data sets obtained from the experimental NMR data of nine small proteins. With a set of 10 commonly used NMR spectra, on average 82.5% of all backbone and side-chain ¹H, ¹³C and ¹⁵N resonances could be assigned with an average error rate of 3.5%.     

A novel strategy for NMR resonance assignment and protein structure determination

The quality of protein structures determined by nuclear magnetic resonance (NMR) spectroscopy is contingent on the number and quality of experimentally-derived resonance assignments, distance and angular restraints. Two key features of protein NMR data have posed challenges for the routine and automated structure determination of small to medium sized proteins; (1) spectral resolution – especially of crowded nuclear Overhauser effect spectroscopy (NOESY) spectra, and (2) the reliance on a continuous network of weak scalar couplings as part of most common assignment protocols. In order to facilitate NMR structure determination, we developed a semi-automated strategy that utilizes non-uniform sampling (NUS) and multidimensional decomposition (MDD) for optimal data collection and processing of selected, high resolution multidimensional NMR experiments, combined it with an ABACUS protocol for sequential and side chain resonance assignments, and streamlined this procedure to execute structure and refinement calculations in CYANA and CNS, respectively. Two graphical user interfaces (GUIs) were developed to facilitate efficient analysis and compilation of the data and to guide automated structure determination. This integrated method was implemented and refined on over 30 high quality structures of proteins ranging from 5.5 to 16.5 kDa in size.     

NMR assignment of the nonstructural protein nsp3(1066–1181) from SARS-CoV

Sequence-specific NMR assignments of the globular core comprising the residues 1066–1181 within the non-structural protein nsp3e from the SARS coronavirus have been obtained using triple-resonance NMR experiments with the uniformly [¹³C, ¹⁵N]-labeled protein. The backbone and side chain assignments are nearly complete, providing the basis for the ongoing NMR structure determination. A preliminary identification of regular secondary structures has been derived from the ¹³C chemical shifts.     

Chemical shift assignments and secondary structure prediction for Q4DY78, a conserved kinetoplastid-specific protein from <Emphasis Type="Italic">Trypanosoma cruzi</Emphasis>

Trypanosoma cruzi, Trypanosma brucei and Leishmania spp. are kinetoplastid protozoa causative agents of Chagas disease, sleeping sickness and leishmaniasis, respectively, neglected tropical diseases estimated to infect millions of people worldwide. Their genome sequencing has revealed approximately 50 % of genes encoding hypothetical proteins of unknown function, opening possibilities for novel target identification and drug discovery. Q4DY78 is a putative essential protein from T. cruzi conserved in the related kinetoplastids and divergent from mammalian host proteins. Here we report the ¹H, ¹⁵N, and ¹³C chemical shift assignments and secondary structure analysis of the Q4DY78 protein as basis for NMR structure determination, functional analysis and drug screening.     

1H, 13C, and 15N NMR assignments of the Pyrococcus abyssi DNA polymerase II intein

Protein splicing is a precise post-translational process mediated by inteins. Inteins are intervening proteins that cleave themselves from a precursor protein while joining the flanking sequences. Here we report the ¹⁵N, ¹³C, and ¹H chemical shift assignments of the intein from DNA polymerase II of Pyrococcus abyssi (Pab PolII intein), which has been recombinantly overexpressed and isotopically labeled. The NMR assignments of Pab PolII intein are essential for solution structure determination and protein dynamics study.     

Protein side-chain resonance assignment and NOE assignment using RDC-defined backbones without TOCSY data

One bottleneck in NMR structure determination lies in the laborious and time-consuming process of side-chain resonance and NOE assignments. Compared to the well-studied backbone resonance assignment problem, automated side-chain resonance and NOE assignments are relatively less explored. Most NOE assignment algorithms require nearly complete side-chain resonance assignments from a series of through-bond experiments such as HCCH-TOCSY or HCCCONH. Unfortunately, these TOCSY experiments perform poorly on large proteins. To overcome this deficiency, we present a novel algorithm, called Nasca (NOE Assignment and Side-Chain Assignment), to automate both side-chain resonance and NOE assignments and to perform high-resolution protein structure determination in the absence of any explicit through-bond experiment to facilitate side-chain resonance assignment, such as HCCH-TOCSY. After casting the assignment problem into a Markov Random Field (MRF), Nasca extends and applies combinatorial protein design algorithms to compute optimal assignments that best interpret the NMR data. The MRF captures the contact map information of the protein derived from NOESY spectra, exploits the backbone structural information determined by RDCs, and considers all possible side-chain rotamers. The complexity of the combinatorial search is reduced by using a dead-end elimination (DEE) algorithm, which prunes side-chain resonance assignments that are provably not part of the optimal solution. Then an A* search algorithm is employed to find a set of optimal side-chain resonance assignments that best fit the NMR data. These side-chain resonance assignments are then used to resolve the NOE assignment ambiguity and compute high-resolution protein structures. Tests on five proteins show that Nasca assigns resonances for more than 90% of side-chain protons, and achieves about 80% correct assignments. The final structures computed using the NOE distance restraints assigned by Nasca have backbone RMSD 0.8–1.5 Å from the reference structures determined by traditional NMR approaches.