Chemical shift based editing of CH<Subscript>3</Subscript> groups in fractionally <Superscript>13</Superscript>C-labelled proteins using GFT (3, 2)D CT-H<Emphasis Type="Underline">CC</Emphasis>H-COSY: stereospecific assignments of CH<Subscript>3</Subscript> groups of Val and Leu residues

We propose a (3, 2)D CT-HCCH-COSY experiment to rapidly collect the data and provide significant dispersion in the spectral region containing (13)C-(1)H cross peaks of CH(3) groups belonging to Ala, Ile, Leu, Met, Thr and Val residues. This enables one to carry out chemical shift based editing and grouping of all the (13)C-(1)H cross peaks of CH(3) groups belonging to Ala, Ile, Leu, Met, Thr and Val residues in fractionally (10%) (13)C-labelled proteins, which in turn aids in the sequence-specific resonance assignments in general and side-chain resonance assignments in particular, in any given protein. Further, we demonstrate the utility of this experiment for stereospecific assignments of the pro-R and pro-S methyl groups belonging to the Leu and Val residues in fractionally (10%) (13)C-labelled proteins. The proposed experiment opens up a wide range of applications in resonance assignment strategies and structure determination of proteins.     

NMR assignment of reduced form of copper, zinc superoxide dismutase from Salmonella enterica

Almost complete assignment (97%) of NMR resonances was obtained for the reduced, Cu(I), form of prokaryotic CuZnSOD from Salmonella enterica. ¹³C direct detection was used to complement the standard bouquet of ¹H detected triple resonance experiments and contributed to the identification of proline backbone resonances and to side chains assignments of Asx, Glx and aromatic rings. This is the only complete assignment available for monomer SOD from prokaryotic organisms.     

Probabilistic Identification of Spin Systems and their Assignments including Coil–Helix Inference as Output (PISTACHIO)

We present a novel automated strategy (PISTACHIO) for the probabilistic assignment of backbone and sidechain chemical shifts in proteins. The algorithm uses peak lists derived from various NMR experiments as input and provides as output ranked lists of assignments for all signals recognized in the input data as constituting spin systems. PISTACHIO was evaluate00000000d by comparing its performance with raw peak-picked data from 15 proteins ranging from 54 to 300 residues; the results were compared with those achieved by experts analyzing the same datasets by hand. As scored against the best available independent assignments for these proteins, the first-ranked PISTACHIO assignments were 80–100% correct for backbone signals and 75–95% correct for sidechain signals. The independent assignments benefited, in a number of cases, from structural data (e.g. from NOESY spectra) that were unavailable to PISTACHIO. Any number of datasets in any combination can serve as input. Thus PISTACHIO can be used as datasets are collected to ascertain the current extent of secure assignments, to identify residues with low assignment probability, and to suggest the types of additional data needed to remove ambiguities. The current implementation of PISTACHIO, which is available from a server on the Internet, supports input data from 15 standard double- and triple-resonance experiments. The software can readily accommodate additional types of experiments, including data from selectively labeled samples. The assignment probabilities can be carried forward and refined in subsequent steps leading to a structure. The performance of PISTACHIO showed no direct dependence on protein size, but correlated instead with data quality (completeness and signal-to-noise). PISTACHIO represents one component of a comprehensive probabilistic approach we are developing for the collection and analysis of protein NMR data.Electronic Supplementary Material Electronic Supplementary material is available for this article at and accessible for authorised users.     

Assignment validation software suite for the evaluation and presentation of protein resonance assignment data

We present a set of utilities and graphical user interface (GUI) tools for evaluating the quality of protein resonance assignments. The Assignment Validation Software (AVS) suite, together with new GUI features in the AutoAssign software package, provides a set of reports and graphs for validating protein resonance assignment data before its use in structure analysis and/or submission to the BioMagResBank (BMRB). Input includes a listing of resonance assignments and a summary of sequential connectivity data (i.e. triple resonance, NOE, or other data) used in deriving the assignments. These tools are useful for evaluating the accuracy of protein resonance assignments determined by either automated or manual methods.     

Solution NMR characterization of apical membrane antigen 1 and small molecule interactions as a basis for designing new antimalarials

Plasmodium falciparum apical membrane antigen 1 (PfAMA1) plays an important role in the invasion by merozoites of human red blood cells during a malaria infection. A key region of PfAMA1 is a conserved hydrophobic cleft formed by 12 hydrophobic residues. As anti‐apical membrane antigen 1 antibodies and other inhibitory molecules that target this hydrophobic cleft are able to block the invasion process, PfAMA1 is an attractive target for the development of strain‐transcending antimalarial agents. As solution nuclear magnetic resonance spectroscopy is a valuable technique for the rapid characterization of protein–ligand interactions, we have determined the sequence‐specific backbone assignments for PfAMA1 from two P. falciparum strains, FVO and 3D7. Both selective labelling and unlabelling strategies were used to complement triple‐resonance experiments in order to facilitate the assignment process. We have then used these assignments for mapping the binding sites for small molecules, including benzimidazoles, pyrazoles and 2‐aminothiazoles, which were selected on the basis of their affinities measured from surface plasmon resonance binding experiments. Among the compounds tested, benzimidazoles showed binding to a similar region on both FVO and 3D7 PfAMA1, suggesting that these compounds are promising scaffolds for the development of novel PfAMA1 inhibitors. Copyright © 2016 John Wiley & Sons, Ltd.     

SAGA: rapid automatic mainchain NMR assignment for large proteins

Here we describe a new algorithm for automatically determining the mainchain sequential assignment of NMR spectra for proteins. Using only the customary triple resonance experiments, assignments can be quickly found for not only small proteins having rather complete data, but also for large proteins, even when only half the residues can be assigned. The result of the calculation is not the single best assignment according to some criterion, but rather a large number of satisfactory assignments that are summarized in such a way as to help the user identify portions of the sequence that are assigned with confidence, vs. other portions where the assignment has some correlated alternatives. Thus very imperfect initial data can be used to suggest future experiments.     

Complete backbone assignment of a Ca2+-binding protein of the βγ-crystallin superfamily from Methanosarcina acetivorans, at two denaturant concentrations

We report here almost complete backbone assignment of a Ca²⁺-binding protein of the βγ-crystallin superfamily from Methanosarcina acetivorans, at two denaturant (GdmCl) concentrations, using double and triple resonance experiments. These NMR assignments will be useful to understand the unfolding path of this protein. Ravi P. Barnwal and Geetika Agarwal have contributed equally.     

High-resolution aliphatic side-chain assignments in 3D HCcoNH experiments with joint H–C evolution and non-uniform sampling

We describe an efficient NMR triple resonance approach that correlates, at high resolution, protein side-chain and backbone resonances. It relies on the combination of two strategies: joint evolution of aliphatic side-chain proton/carbon coherences using a backbone N–H based HCcoNH reduced dimensionality (RD) experiment and non-uniform sampling (NUS) in two indirect dimensions. A typical data set containing such correlation information can be acquired in 2 days, at very high resolution unfeasible for conventional 4D HCcoNH-TOCSY experiments. The resonances of the aliphatic side-chain protons are unambiguously assigned to their attached carbons through the analysis of the ‘sum’ and ‘difference’ spectra. This approach circumvents the tedious process of manual resonance assignments using HCcH-TOCSY data, while providing additional resolving power of backbone N–H signals. A simple peak-list based algorithm has been implemented in the IBIS software for rapid automated backbone and side-chain assignments.     

The program XEASY for computer-supported NMR spectral analysis of biological macromolecules

Summary A new program package, XEASY, was written for interactive computer support of the analysis of NMR spectra for three-dimensional structure determination of biological macromolecules. XEASY was developed for work with 2D, 3D and 4D NMR data sets. It includes all the functions performed by the precursor program EASY, which was designed for the analysis of 2D NMR spectra, i.e., peak picking and support of sequence-specific resonance assignments, cross-peak assignments, cross-peak integration and rate constant determination for dynamic processes. Since the program utilizes the X-window system and the Motif widget set, it is portable on a wide range of UNIX workstations. The design objective was to provide maximal computer support for the analysis of spectra, while providing the user with complete control over the final resonance assignments. Technically important features of XEASY are the use and flexible visual display of strips, i.e., two-dimensional spectral regions that contain the relevant parts of 3D or 4D NMR spectra, automated sorting routines to narrow down the selection of strips that need to be interactively considered in a particular assignment step, a protocol of resonance assignments that can be used for reliable bookkeeping, independent of the assignment strategy used, and capabilities for proper treatment of spectral folding and efficient transfer of resonance assignments between spectra of different types and different dimensionality, including projected, reduced-dimensionality triple-resonance experiments.Abbreviations 1D, 2D, 3D, 4D one-, two-, three-, four-dimensional - NOE nuclear Overhauser enhancement - NOESY nuclear Overhauser enhancement spectroscopy - TOCSY total correlation spectroscopy - COSY correlation spectroscopy - TPPI time-proportional phase incrementation     

Graphical interpretation of Boolean operators for protein NMR assignments

We have developed a graphics based algorithm for semi-automated protein NMR assignments. Using the basic sequential triple resonance assignment strategy, the method is inspired by the Boolean operators as it applies "AND"-, "OR"- and "NOT"-like operations on planes pulled out of the classical three-dimensional spectra to obtain its functionality. The method's strength lies in the continuous graphical presentation of the spectra, allowing both a semi-automatic peaklist construction and sequential assignment. We demonstrate here its general use for the case of a folded protein with a well-dispersed spectrum, but equally for a natively unfolded protein where spectral resolution is minimal.     

Sequence-specific 1H, 13C, and 15N resonance assignments of GRP1 PH domain

The carboxy-terminal pleckstrin homology (PH) domain recruits GRP1 to the plasma membrane through the specific binding to phosphatidylinositol 3,4,5-trisphosphate [PtdIns(3,4,5)P₃]. Here, we describe backbone and side chain assignments of the GRP1 PH domain determined by triple resonance experiments. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

CASA: An Efficient Automated Assignment of Protein Mainchain NMR Data Using an Ordered Tree Search Algorithm

Rapid analysis of protein structure, interaction, and dynamics requires fast and automated assignments of 3D protein backbone triple-resonance NMR spectra. We introduce a new depth-first ordered tree search method of automated assignment, CASA, which uses hand-edited peak-pick lists of a flexible number of triple resonance experiments. The computer program was tested on 13 artificially simulated peak lists for proteins up to 723 residues, as well as on the experimental data for four proteins. Under reasonable tolerances, it generated assignments that correspond to the ones reported in the literature within a few minutes of CPU time. The program was also tested on the proteins analyzed by other methods, with both simulated and experimental peaklists, and it could generate good assignments in all relevant cases. The robustness was further tested under various situations.     

Towards structural genomics of RNA: rapid NMR resonance assignment and simultaneous RNA tertiary structure determination using residual dipolar couplings

We report a new residual dipolar couplings (RDCs) based NMR procedure for rapidly determining RNA tertiary structure demonstrated on a uniformly (15)N/(13)C-labeled 27 nt variant of the trans-activation response element (TAR) RNA from HIV-I. In this procedure, the time-consuming nuclear Overhauser enhancement (NOE)-based sequential assignment step is replaced by a fully automated RDC-based assignment strategy. This approach involves examination of all allowed sequence-specific resonance assignment permutations for best-fit agreement between measured RDCs and coordinates for sub-structures in a target RNA. Using idealized A-form geometries to model Watson-Crick helices and coordinates from a previous X-ray structure to model a hairpin loop in TAR, the best-fit RDC assignment solutions are determined very rapidly (相似文献   

Rapid analysis of protein backbone resonance assignments using cryogenic probes,a distributed Linux-based computing architecture,and an integrated set of spectral analysis tools

Rapid data collection, spectral referencing, processing by time domain deconvolution, peak picking and editing, and assignment of NMR spectra are necessary components of any efficient integrated system for protein NMR structure analysis. We have developed a set of software tools designated AutoProc, AutoPeak, and AutoAssign, which function together with the data processing and peak-picking programs NMRPipe and Sparky, to provide an integrated software system for rapid analysis of protein backbone resonance assignments. In this paper we demonstrate that these tools, together with high-sensitivity triple resonance NMR cryoprobes for data collection and a Linux-based computer cluster architecture, can be combined to provide nearly complete backbone resonance assignments and secondary structures (based on chemical shift data) for a 59-residue protein in less than 30 hours of data collection and processing time. In this optimum case of a small protein providing excellent spectra, extensive backbone resonance assignments could also be obtained using less than 6 hours of data collection and processing time. These results demonstrate the feasibility of high throughput triple resonance NMR for determining resonance assignments and secondary structures of small proteins, and the potential for applying NMR in large scale structural proteomics projects.Abbreviations: BPTI – bovine pancreatic trypsin inhibitor; LP – linear prediction; FT – Fourier transform; S/N – signal-to-noise ratio; FID – free induction decay     

Fully automated sequence-specific resonance assignments of hetero- nuclear protein spectra

Full automation of the analysis of spectra is a prerequisite for high-throughput NMR studies in structural or functional genomics. Sequence-specific assignments often form the major bottleneck. Here, we present a procedure that yields nearly complete backbone and side chain resonance assignments starting from a set of heteronuclear three-dimensional spectra. Neither manual intervention, e.g., to correct lists obtained from peak picking before feeding these to an assignment program, nor protein-specific information, e.g., structures of homologous proteins, were required. By combining two earlier published procedures, AUTOPSY [Koradi et al. (1998) J. Magn. Reson., 135, 288–297] and GARANT [Bartels et al. (1996) J. Biomol. NMR, 7, 207–213], with a new program, PICS, all necessary steps from spectra analyses to sequence-specific assignments were performed fully automatically. Characteristic features of the present approach are a flexible design allowing as input almost any combination of NMR spectra, applicability to side chains, robustness with respect to parameter choices (such as noise levels) and reproducibility. In this study, automated resonance assignments were obtained for the 14 kD blue copper protein azurin from P. aeruginosa using five spectra: HNCACB, HNHA, HCCH-TOCSY, ¹⁵N-NOESY-HSQC and ¹³C-NOESY-HSQC. Peaks from these three-dimensional spectra were filtered and calibrated with the help of two two-dimensional spectra: ¹⁵N-HSQC and ¹³C-HSQC. The rate of incorrect assignments is less than 1.5% for backbone nuclei and about 3.5% when side chain protons are also considered.     

Resonance assignment strategies for the analysis of nmr spectra of proteins

Determination of the high resolution solution structure of a protein using nuclear magnetic resonance (NMR) spectroscopy requires that resonances observed in the NMR spectra be unequivocally assigned to individual nuclei of the protein. With the advent of modern, two-dimensional NMR techniques arose methodologies for assigning the¹H resonances based on 2D, homonuclear¹H NMR experiments. These include the sequential assignment strategy and the main chain directed strategy. These basic strategies have been extended to include newer 3D homonuclear experiments and 2D and 3D heteronuclear resolved and edited methods. Most recently a novel, conceptually new approach to the problem has been introduced that relies on heteronuclear, multidimensional so-called triple resonance experiments for both backbone and sidechain resonance assignments in proteins. This article reviews the evolution of strategies for the assignment of resonances of proteins.     

Backbone and side-chain heteronuclear resonance assignments and hyperfine NMR shifts in horse cytochrome c

The [H26N, H33N] mutant of horse heart cytochrome c was expressed in E. coli during growth on isotopically enriched minimal media. Complete resonance assignments of both the diamagnetic reduced (spin zero) and paramagnetic oxidized (spin (1/2)) states of the protein were obtained using standard triple resonance and total correlation spectroscopy using the previously determined (1)H chemical shifts of the wild-type protein as a guide. The correspondence of chemical shifts between the wild type and the mutant protein is excellent, indicating that they have nearly identical structures. The expanded library of chemical shifts for both redox states in both proteins allowed the refinement of the electron spin g-tensor of the oxidized states. The g-tensors of the oxidized states of the wild-type and [H26N, H33N] mutant proteins are closely similar, indicating that the subtle details of the ligand fields are nearly identical. The refined g-tensors were then used to probe for redox-dependent structure change in the two proteins.     

Fast Assignment of <Superscript>15</Superscript>N-HSQC Peaks using High-Resolution 3D HNcocaNH Experiments with Non-Uniform Sampling

We describe an efficient NMR triple resonance approach for fast assignment of backbone amide resonance peaks in the ¹⁵N-HSQC spectrum. The exceptionally high resolutions achieved in the 3D HncocaNH and hNcocaNH experiments together with non-uniform sampling facilitate error-free sequential connection of backbone amides. Data required for the complete backbone amide assignment of the 56-residue protein GB1 domain were obtained in 14 h. Data analysis was vastly streamlined using a ‘backbone NH walk’ method to determine sequential connectivities without the need for ¹³C chemical shifts comparison. Amino acid residues in the sequentially connected NH chains are classified into two groups by a simple variation of the NMR pulse sequence, and the resulting ‘ZeBra’ stripe patterns are useful for mapping these chains to the protein sequence. In addition to resolving ambiguous assignments derived from conventional backbone experiments, this approach can be employed to rapidly assign small proteins or flexible regions in larger proteins, and to transfer assignments to mutant proteins or proteins in different ligand-binding states.     

Assigning backbone NMR resonances for full length tau isoforms: efficient compromise between manual assignments and reduced dimensionality

Tau protein is the longest disordered protein for which nearly complete backbone NMR resonance assignments have been reported. Full-length tau protein was initially assigned using a laborious combination of bootstrapping assignments from shorter tau fragments and conventional triple resonance NMR experiments. Subsequently it was reported that assignments of comparable quality could be obtained in a fully automated fashion from data obtained using reduced dimensionality NMR (RDNMR) experiments employing a large number of indirect dimensions. Although the latter strategy offers many advantages, it presents some difficulties if manual intervention, confirmation, or correction of the assignments is desirable, as may often be the case for long disordered and degenerate polypeptide sequences. Here we demonstrate that nearly complete backbone resonance assignments for full-length tau isoforms can be obtained without resorting either to bootstrapping from smaller fragments or to very high dimensionality experiments and automation. Instead, a set of RDNMR triple resonance experiments of modest dimensionality lend themselves readily to efficient and unambiguous manual assignments. An analysis of the backbone chemical shifts obtained in this fashion indicates several regions in full length tau with a notable propensity for helical or strand-like structure that are in good agreement with previous observations.     

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.