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Multidimensional NMR spectra are the basis for studying proteins by NMR spectroscopy and crucial for the development and evaluation of methods for biomolecular NMR data analysis. Nevertheless, in contrast to derived data such as chemical shift assignments in the BMRB and protein structures in the PDB databases, this primary data is in general not publicly archived. To change this unsatisfactory situation, we present a standardized set of solution NMR data comprising 1329 2–4-dimensional NMR spectra and associated reference (chemical shift assignments, structures) and derived (peak lists, restraints for structure calculation, etc.) annotations. With the 100-protein NMR spectra dataset that was originally compiled for the development of the ARTINA deep learning-based spectra analysis method, 100 protein structures can be reproduced from their original experimental data. The 100-protein NMR spectra dataset is expected to help the development of computational methods for NMR spectroscopy, in particular machine learning approaches, and enable consistent and objective comparisons of these methods. [ABSTRACT FROM AUTHOR]

Many proteins can adopt multiple conformations which are important for their function. This is also true for proteins and domains that are covalently linked to each other. One important example is ubiquitin, which can form chains of different conformations depending on which of its lysine side chains is used to form an isopeptide bond with the C-terminus of another ubiquitin molecule. Similarly, ubiquitin gets covalently attached to active-site residues of E2 ubiquitin-conjugating enzymes. Due to weak interactions between ubiquitin and its interaction partners, these covalent complexes adopt multiple conformations. Understanding the function of these complexes requires the characterization of the entire accessible conformation space and its modulation by interaction partners. Long-range (1.8–10 nm) distance restraints obtained by EPR spectroscopy in the form of probability distributions are ideally suited for this task as not only the mean distance but also information about the conformation dynamics is encoded in the experimental data. Here we describe a computational method that we have developed based on well-established structure determination software using NMR restraints to calculate the accessible conformation space using PELDOR/DEER data. [ABSTRACT FROM AUTHOR]

Most experimental methods for structural biology proceed in vitro and therefore the contribution of the intracellular environment on protein structure and dynamics is absent. Studying proteins at atomic resolution in living mammalian cells has been elusive due to the lack of methodologies. In-cell nuclear magnetic resonance spectroscopy (in-cell NMR) is an emerging technique with the power to do so. Here, we improved current methods of in-cell NMR by the development of a reporter system that allows monitoring the delivery of exogenous proteins into mammalian cells, a process that we called here "transexpression". The reporter system was used to develop an efficient protocol for in-cell NMR which enables spectral acquisition with higher quality for both disordered and folded proteins. With this method, the 3D atomic resolution structure of the model protein GB1 in human cells was determined with a backbone root-mean-square deviation (RMSD) of 1.1 Å. An improved method for in-cell NMR is developed using a reporter to evaluate protein delivery and delivery parameters to different cell lines and applied to IDPs and folded proteins including structure determination of GB1 at 1.1 Å resolution. [ABSTRACT FROM AUTHOR]

Recent methodological advances in solution NMR allow the determination of multi-state protein structures and provide insights into structurally and dynamically correlated protein sites at atomic resolution. This is demonstrated in the present work for the well-studied PDZ2 domain of protein human tyrosine phosphatase 1E for which protein allostery had been predicted. Two-state protein structures were calculated for both the free form and in complex with the RA-GEF2 peptide using the exact nuclear Overhauser effect (eNOE) method. In the apo protein, an allosteric conformational selection step comprising almost 60% of the domain was detected with an "open" ligand welcoming state and a "closed" state that obstructs the binding site by changing the distance between the β-sheet 2, α-helix 2, and sidechains of residues Lys38 and Lys72. The observed induced fit-type apo-holo structural rearrangements are in line with the previously published evolution-based analysis covering ~25% of the domain with only a partial overlap with the protein allostery of the open form. These presented structural studies highlight the presence of a dedicated highly optimized and complex dynamic interplay of the PDZ2 domain owed by the structure-dynamics landscape. In this manuscript the authors report accurate multi-state protein structures of the PDZ domain using biological NMR. By looking into protein structural states, the authors report an allosteric pathway at atomic resolution that validates previously reported low resolution findings and uncovered a structural hallmark of the allosteric ligand binding to the PDZ domain. [ABSTRACT FROM AUTHOR]

Nuclear Magnetic Resonance (NMR) spectroscopy is a major technique in structural biology with over 11,800 protein structures deposited in the Protein Data Bank. NMR can elucidate structures and dynamics of small and medium size proteins in solution, living cells, and solids, but has been limited by the tedious data analysis process. It typically requires weeks or months of manual work of a trained expert to turn NMR measurements into a protein structure. Automation of this process is an open problem, formulated in the field over 30 years ago. We present a solution to this challenge that enables the completely automated analysis of protein NMR data within hours after completing the measurements. Using only NMR spectra and the protein sequence as input, our machine learning-based method, ARTINA, delivers signal positions, resonance assignments, and structures strictly without human intervention. Tested on a 100-protein benchmark comprising 1329 multidimensional NMR spectra, ARTINA demonstrated its ability to solve structures with 1.44 Å median RMSD to the PDB reference and to identify 91.36% correct NMR resonance assignments. ARTINA can be used by non-experts, reducing the effort for a protein assignment or structure determination by NMR essentially to the preparation of the sample and the spectra measurements. The analysis of protein NMR spectra is time-consuming and can occupy a human expert for weeks or months. The researchers in this work present a deep learning-based method that delivers signal positions, chemical shift assignments, and structures of proteins within hours after completion of the NMR measurements. [ABSTRACT FROM AUTHOR]

Recent advances in the field of protein structure determination using liquid-state NMR enable the elucidation of multi-state protein conformations that can provide insight into correlated and non-correlated protein dynamics at atomic resolution. So far, NMR-derived multi-state structures were typically evaluated by means of visual inspection of structure superpositions, target function values that quantify the violation of experimented restraints and root-mean-square deviations that quantify similarity between conformers. As an alternative or complementary approach, we present here the use of a recently introduced structural correlation measure, PDBcor, that quantifies the clustering of protein states as an additional measure for multi-state protein structure analysis. It can be used for various assays including the validation of experimental distance restraints, optimization of the number of protein states, estimation of protein state populations, identification of key distance restraints, NOE network analysis and semiquantitative analysis of the protein correlation network. We present applications for the final quality analysis stages of typical multi-state protein structure calculations. [ABSTRACT FROM AUTHOR]

NMR structure calculation using NOE-derived distance restraints requires a considerable number of assignments of both backbone and sidechains resonances, often difficult or impossible to get for large or complex proteins. Pseudocontact shifts (PCSs) also play a well-established role in NMR protein structure calculation, usually to augment existing structural, mostly NOE-derived, information. Existing refinement protocols using PCSs usually either require a sizeable number of sidechain assignments or are complemented by other experimental restraints. Here, we present an automated iterative procedure to perform backbone protein structure refinements requiring only a limited amount of backbone amide PCSs. Already known structural features from a starting homology model, in this case modules of repeat proteins, are framed into a scaffold that is subsequently refined by experimental PCSs. The method produces reliable indicators that can be monitored to judge about the performance. We applied it to a system in which sidechain assignments are hardly possible, designed Armadillo repeat proteins (dArmRPs), and we calculated the solution NMR structure of YM4A, a dArmRP containing four sequence-identical internal modules, obtaining high convergence to a single structure. We suggest that this approach is particularly useful when approximate folds are known from other techniques, such as X-ray crystallography, while avoiding inherent artefacts due to, for instance, crystal packing. [ABSTRACT FROM AUTHOR]

Resonance assignments are challenging for membrane proteins due to the size of the lipid/detergent-protein complex and the presence of line-broadening from conformational exchange. As a consequence, many correlations are missing in the triple-resonance NMR experiments typically used for assignments. Herein, we present an approach in which correlations from these solution-state NMR experiments are supplemented by data from 13C unlabeling, single-amino acid type labeling, 4D NOESY data and proximity of moieties to lipids or water in combination with a structure of the protein. These additional data are used to edit the expected peaklists for the automated assignment protocol FLYA, a module of the program package CYANA. We demonstrate application of the protocol to the 262-residue proton pump from archaeal bacteriorhodopsin (bR) in lipid nanodiscs. The lipid-protein assembly is characterized by an overall correlation time of 44 ns. The protocol yielded assignments for 62% of all backbone (H, N, Cα, Cβ, C′) resonances of bR, corresponding to 74% of all observed backbone spin systems, and 60% of the Ala, Met, Ile (δ1), Leu and Val methyl groups, thus enabling to assign a large fraction of the protein without mutagenesis data. Most missing resonances stem from the extracellular half, likely due intermediate exchange line-broadening. Further analysis revealed that missing information of the amino acid type of the preceding residue is the largest problem, and that 4D NOESY experiments are particularly helpful to compensate for that information loss. [ABSTRACT FROM AUTHOR]

Yos9 is an essential component of the endoplasmic reticulum associated protein degradation (ERAD) system that is responsible for removing terminally misfolded proteins from the ER lumen and mediating proteasomal degradation in the cytosol. Glycoproteins that fail to attain their native conformation in the ER expose a distinct oligosaccharide structure, a terminal α1,6-linked mannose residue, that is specifically recognized by the mannose 6-phoshate receptor homology (MRH) domain of Yos9. We have determined the structure of the MRH domain of Yos9 in its free form and complexed with 3α, 6α-mannopentaose. We show that binding is achieved by loops between β-strands performing an inward movement and that this movement also affects the entire β-barrel leading to a twist. These rearrangements may facilitate the processing of client proteins by downstream acting factors. In contrast, other oligosaccharides such as 2α-mannobiose bind weakly with only locally occurring chemical shift changes underscoring the specificity of this substrate selection process within ERAD. [ABSTRACT FROM AUTHOR]

The automated identification of signals in multidimensional NMR spectra is a challenging task, complicated by signal overlap, noise, and spectral artifacts, for which no universally accepted method is available. Here, we present a new peak picking algorithm, CYPICK, that follows, as far as possible, the manual approach taken by a spectroscopist who analyzes peak patterns in contour plots of the spectrum, but is fully automated. Human visual inspection is replaced by the evaluation of geometric criteria applied to contour lines, such as local extremality, approximate circularity (after appropriate scaling of the spectrum axes), and convexity. The performance of CYPICK was evaluated for a variety of spectra from different proteins by systematic comparison with peak lists obtained by other, manual or automated, peak picking methods, as well as by analyzing the results of automated chemical shift assignment and structure calculation based on input peak lists from CYPICK. The results show that CYPICK yielded peak lists that compare in most cases favorably to those obtained by other automated peak pickers with respect to the criteria of finding a maximal number of real signals, a minimal number of artifact peaks, and maximal correctness of the chemical shift assignments and the three-dimensional structure obtained by fully automated assignment and structure calculation. [ABSTRACT FROM AUTHOR]

The original article can be found online at https://doi.org/10.1007/s10858-021-00376-8. Results are shown for calculating 2000 structures with a UPL:PCS weight of 1:0.1. b precision (top) and accuracy (bottom) versus the number of calculated structures computed with 25000 MD steps and a UPL:PCS weight of 1:0.1. c accuracy versus the UPL and PCS weights when computed with 2000 structures in 25000 MD steps The original article has been corrected. [Extracted from the article]

An algorithm, CYLIB, is presented for converting molecular topology descriptions from the PDB Chemical Component Dictionary into CYANA residue library entries. The CYANA structure calculation algorithm uses torsion angle molecular dynamics for the efficient computation of three-dimensional structures from NMR-derived restraints. For this, the molecules have to be represented in torsion angle space with rotations around covalent single bonds as the only degrees of freedom. The molecule must be given a tree structure of torsion angles connecting rigid units composed of one or several atoms with fixed relative positions. Setting up CYANA residue library entries therefore involves, besides straightforward format conversion, the non-trivial step of defining a suitable tree structure of torsion angles, and to re-order the atoms in a way that is compatible with this tree structure. This can be done manually for small numbers of ligands but the process is time-consuming and error-prone. An automated method is necessary in order to handle the large number of different potential ligand molecules to be studied in drug design projects. Here, we present an algorithm for this purpose, and show that CYANA structure calculations can be performed with almost all small molecule ligands and non-standard amino acid residues in the PDB Chemical Component Dictionary. [ABSTRACT FROM AUTHOR]

The automated assignment of NOESY cross peaks has become a fundamental technique for NMR protein structure analysis. A widely used algorithm for this purpose is implemented in the program CYANA. It has been used for a large number of structure determinations of proteins in solution but was so far not described in full detail. In this paper we present a complete description of the CYANA implementation of automated NOESY assignment, which differs extensively from its predecessor CANDID by the use of a consistent probabilistic treatment, and we discuss its performance in the second round of the critical assessment of structure determination by NMR. [ABSTRACT FROM AUTHOR]

The automated assignment of NOESY cross peaks has become a fundamental technique for NMR protein structure analysis. A widely used algorithm for this purpose is implemented in the program CYANA. It has been used for a large number of structure determinations of proteins in solution but a systematic evaluation of its performance has not yet been reported. In this paper we systematically analyze the reliability of combined automated NOESY assignment and structure calculation with CYANA under a variety of conditions on the basis of the experimental NMR data sets of ten proteins. To evaluate the robustness of the algorithm, the original high-quality experimental data sets were modified in different ways to simulate the effect of data imperfections, i.e. incomplete or erroneous chemical shift assignments, missing NOESY cross peaks, inaccurate peak positions, inaccurate peak intensities, lower dimensionality NOESY spectra, and higher tolerances for the matching of chemical shifts and peak positions. The results show that the algorithm is remarkably robust with regard to imperfections of the NOESY peak lists and the chemical shift tolerances but susceptible to lacking or erroneous resonance assignments, in particular for nuclei that are involved in many NOESY cross peaks. [ABSTRACT FROM AUTHOR]

Tissue-specific alternative pre-mRNA splicing is often cooperatively regulated by multiple splicing factors, but the structural basis of cooperative RNA recognition is poorly understood. In Caenorhabditis elegans, ligand binding specificity of fibroblast growth factor receptors (FGFRs) is determined by mutually exclusive alternative splicing of the sole FGFR gene, egl-15. Here we determined the solution structure of a ternary complex of the RNA-recognition motif (RRM) domains from the RBFOX protein ASD-1, SUP-12 and their target RNA from egl-15. The two RRM domains cooperatively interact with the RNA by sandwiching a G base to form the stable complex. Multichromatic fluorescence splicing reporters confirmed the requirement of the G and the juxtaposition of the respective cis elements for effective splicing regulation in vivo. Moreover, we identified a new target for the heterologous complex through an element search, confirming the functional significance of the intermolecular coordination. [ABSTRACT FROM AUTHOR]

A fast, robust and reliable strategy for automated sequential resonance assignment for uniformly [C, N]-labeled RNA via its phosphodiester backbone is presented. It is based on a series of high-dimensional through-bond APSY experiments: a 5D HCP-CCH COSY, a 4D H1′C1′CH TOCSY for ribose resonances, a 5D HCNCH for ribose-to-base connection, a 4D H6C6C5H5 TOCSY for pyrimidine resonances, and a 4D H8C8(C)C2H2 TOCSY for adenine resonances. The utilized pulse sequences are partially novel, and optimized to enable long evolution times in all dimensions. The highly precise APSY peak lists derived with these experiments could be used directly for reliable automated resonance assignment with the FLYA algorithm. This approach resulted in 98 % assignment completeness for all C-H, N1/9 and P resonances of a stem-loop with 14 nucleotides. [ABSTRACT FROM AUTHOR]

Recently developed methods to measure distances in proteins with high accuracy by “exact” nuclear Overhauser effects (eNOEs) make it possible to determine stereospecific assignments, which are particularly important to fully exploit the accuracy of the eNOE distance measurements. Stereospecific assignments are determined by comparing the eNOE-derived distances to protein structure bundles calculated without stereospecific assignments, or an independently determined crystal structure. The absolute and relative CYANA target function difference upon swapping the stereospecific assignment of a diastereotopic group yields the respective stereospecific assignment. We applied the method to the eNOE data set that has recently been obtained for the third immunoglobulin-binding domain of protein G (GB3). The 884 eNOEs provide relevant data for 47 of the total of 75 diastereotopic groups. Stereospecific assignments could be established for 45 diastereotopic groups (96 %) using the X-ray structure, or for 27 diastereotopic groups (57 %) using structures calculated with the eNOE data set without stereospecific assignments, all of which are in agreement with those determined previously. The latter case is relevant for structure determinations based on eNOEs. The accuracy of the eNOE distance measurements is crucial for making stereospecific assignments because applying the same method to the traditional NOE data set for GB3 with imprecise upper distance bounds yields only 13 correct stereospecific assignments using the X-ray structure or 2 correct stereospecific assignments using NMR structures calculated without stereospecific assignments. [ABSTRACT FROM AUTHOR]

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 C- or N-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. [ABSTRACT FROM AUTHOR]

Solid-state NMR is an emerging structure determination technique for crystalline and non-crystalline protein assemblies, e.g., amyloids. Resonance assignment constitutes the first and often very time-consuming step to a structure. We present ssFLYA, a generally applicable algorithm for automatic assignment of protein solid-state NMR spectra. Application to microcrystals of ubiquitin and the Ure2 prion C-terminal domain, as well as amyloids of HET-s(218-289) and α-synuclein yielded 88-97 % correctness for the backbone and side-chain assignments that are classified as self-consistent by the algorithm, and 77-90 % correctness if also assignments classified as tentative by the algorithm are included. [ABSTRACT FROM AUTHOR]

Peak overlap is one of the major factors complicating the analysis of biomolecular NMR spectra. We present a general method for predicting the extent of peak overlap in multidimensional NMR spectra and its validation using both, experimental data sets and Monte Carlo simulation. The method is based on knowledge of the magnetization transfer pathways of the NMR experiments and chemical shift statistics from the Biological Magnetic Resonance Data Bank. Assuming a normal distribution with characteristic mean value and standard deviation for the chemical shift of each observable atom, an analytic expression was derived for the expected overlap probability of the cross peaks. The analytical approach was verified to agree with the average peak overlap in a large number of individual peak lists simulated using the same chemical shift statistics. The method was applied to eight proteins, including an intrinsically disordered one, for which the prediction results could be compared with the actual overlap based on the experimentally measured chemical shifts. The extent of overlap predicted using only statistical chemical shift information was in good agreement with the overlap that was observed when the measured shifts were used in the virtual spectrum, except for the intrinsically disordered protein. Since the spectral complexity of a protein NMR spectrum is a crucial factor for protein structure determination, analytical overlap prediction can be used to identify potentially difficult proteins before conducting NMR experiments. Overlap predictions can be tailored to particular classes of proteins by preparing statistics from corresponding protein databases. The method is also suitable for optimizing recording parameters and labeling schemes for NMR experiments and improving the reliability of automated spectra analysis and protein structure determination. [ABSTRACT FROM AUTHOR]

Peak lists are commonly used in NMR as input data for various software tools such as automatic assignment and structure calculation programs. Inconsistencies of chemical shift referencing among different peak lists or between peak and chemical shift lists can cause severe problems during peak assignment. Here we present a simple and robust tool to achieve self-consistency of the chemical shift referencing among a set of peak lists. The Peakmatch algorithm matches a set of peak lists to a specified reference peak list, neither of which have to be assigned. The chemical shift referencing offset between two peak lists is determined by optimizing an assignment-free match score function using either a complete grid search or downhill simplex optimization. It is shown that peak lists from many different types of spectra can be matched reliably as long as they contain at least two corresponding dimensions. Using a simulated peak list, the Peakmatch algorithm can also be used to obtain the optimal agreement between a chemical shift list and experimental peak lists. Combining these features makes Peakmatch a useful tool that can be applied routinely before automatic assignment or structure calculation in order to obtain an optimized input data set. [ABSTRACT FROM AUTHOR]

The WeNMR () project is a European Union funded international effort to streamline and automate analysis of Nuclear Magnetic Resonance (NMR) and Small Angle X-Ray scattering (SAXS) imaging data for atomic and near-atomic resolution molecular structures. Conventional calculation of structure requires the use of various software packages, considerable user expertise and ample computational resources. To facilitate the use of NMR spectroscopy and SAXS in life sciences the WeNMR consortium has established standard computational workflows and services through easy-to-use web interfaces, while still retaining sufficient flexibility to handle more specific requests. Thus far, a number of programs often used in structural biology have been made available through application portals. The implementation of these services, in particular the distribution of calculations to a Grid computing infrastructure, involves a novel mechanism for submission and handling of jobs that is independent of the type of job being run. With over 450 registered users (September 2012), WeNMR is currently the largest Virtual Organization (VO) in life sciences. With its large and worldwide user community, WeNMR has become the first Virtual Research Community officially recognized by the European Grid Infrastructure (EGI). [ABSTRACT FROM AUTHOR]

Proteins are inherently dynamic systems whose motions cover large ranges in both magnitude and timescale. Because of the omnipresence of motion, it is likely that dynamics have important roles in the function of biomolecules. For detailed understanding of a protein's function, the three-dimensional structure and description of its dynamics are therefore required. Structure determination methods are well established, and NMR-relaxation phenomena provide insights into local molecular dynamics; moreover, recently several attempts have been made to detect concerted motion. Here, we present an ensemble-based structure-determination protocol using ensemble-averaged distance restraints obtained from exact NOE rates. Application to the model protein GB3 establishes an ensemble of structures that reveals correlated motion across the ?-sheet, concerted motion between the backbone and side chains localized in the structure core, and a lack of concerted conformational exchange between the ?-sheet and the ?-helix. [ABSTRACT FROM AUTHOR]

A method is introduced to represent an ensemble of conformers of a protein by a single structure in torsion angle space that lies closest to the averaged Cartesian coordinates while maintaining perfect covalent geometry and on average equal steric quality and an equally good fit to the experimental (e.g. NMR) data as the individual conformers of the ensemble. The single representative 'regmean structure' is obtained by simulated annealing in torsion angle space with the program CYANA using as input data the experimental restraints, restraints for the atom positions relative to the average Cartesian coordinates, and restraints for the torsion angles relative to the corresponding principal cluster average values of the ensemble. The method was applied to 11 proteins for which NMR structure ensembles are available, and compared to alternative, commonly used simple approaches for selecting a single representative structure, e.g. the structure from the ensemble that best fulfills the experimental and steric restraints, or the structure from the ensemble that has the lowest RMSD value to the average Cartesian coordinates. In all cases our method found a structure in torsion angle space that is significantly closer to the mean coordinates than the alternatives while maintaining the same quality as individual conformers. The method is thus suitable to generate representative single structure representations of protein structure ensembles in torsion angle space. Since in the case of NMR structure calculations with CYANA the single structure is calculated in the same way as the individual conformers except that weak positional and torsion angle restraints are added, we propose to represent new NMR structures by a 'regmean bundle' consisting of the single representative structure as the first conformer and all but one original individual conformers (the original conformer with the highest target function value is discarded in order to keep the number of conformers in the bundle constant). In this way, analyses that require a single structure can be carried out in the most meaningful way using the first model, while at the same time the additional information contained in the ensemble remains available. [ABSTRACT FROM AUTHOR]

fully automated method is presented for determining NMR solution structures of proteins using exclusively NOESY spectra as input, obviating the need to measure any spectra only for obtaining resonance assignments but devoid of structural information. Applied to two small proteins, the approach yielded structures that coincided closely with conventionally determined structures. [ABSTRACT FROM AUTHOR]

n in silico fragment-based drug design approach was devised and applied towards the identification of small molecule inhibitors of the dengue virus (DENV) NS2B-NS3 protease. Currently, no DENV protease co-crystal structure with bound inhibitor and fully formed substrate binding site is available. Therefore a homology model of DENV NS2B-NS3 protease was generated employing a multiple template spatial restraints method and used for structure-based design. A library of molecular fragments was derived from the ZINC screening database with help of the retrosynthetic combinatorial analysis procedure (RECAP). 150,000 molecular fragments were docked to the DENV protease homology model and the docking poses were rescored using a target-specific scoring function. High scoring fragments were assembled to small molecule candidates by an implicit linking cascade. The cascade included substructure searching and structural filters focusing on interactions with the S1 and S2 pockets of the protease. The chemical space adjacent to the promising candidates was further explored by neighborhood searching. A total of 23 compounds were tested experimentally and two compounds were discovered to inhibit dengue protease (IC = 7.7 μM and 37.9 μM, respectively) and the related West Nile virus protease (IC = 6.3 μM and 39.0 μM, respectively). This study demonstrates the successful application of a structure-guided fragment-based in silico drug design approach for dengue protease inhibitors providing straightforward hit generation using a combination of homology modeling, fragment docking, chemical similarity and structural filters. [ABSTRACT FROM AUTHOR]

We present a computational method for finding optimal labeling patterns for the backbone assignment of membrane proteins and other large proteins that cannot be assigned by conventional strategies. Following the approach of Kainosho and Tsuji (Biochemistry 21:6273-6279 (1982)), types of amino acids are labeled with C or/and N such that cross peaks between CO( i - 1) and NH( i) result only for pairs of sequentially adjacent amino acids of which the first is labeled with C and the second with N. In this way, unambiguous sequence-specific assignments can be obtained for unique pairs of amino acids that occur exactly once in the sequence of the protein. To be practical, it is crucial to limit the number of differently labeled protein samples that have to be prepared while obtaining an optimal extent of labeled unique amino acid pairs. Our computer algorithm UPLABEL for optimal unique pair labeling, implemented in the program CYANA and in a standalone program, and also available through a web portal, uses combinatorial optimization to find for a given amino acid sequence labeling patterns that maximize the number of unique pair assignments with a minimal number of differently labeled protein samples. Various auxiliary conditions, including labeled amino acid availability and price, previously known partial assignments, and sequence regions of particular interest can be taken into account when determining optimal amino acid type-specific labeling patterns. The method is illustrated for the assignment of the human G-protein coupled receptor bradykinin B2 (BR) and applied as a starting point for the backbone assignment of the membrane protein proteorhodopsin. [ABSTRACT FROM AUTHOR]

Stereo-array isotope labeling (SAIL) has been combined with the fully automated NMR structure determination algorithm FLYA to determine the three-dimensional structure of the protein ubiquitin from different sets of input NMR spectra. SAIL provides a complete stereo- and regio-specific pattern of stable isotopes that results in sharper resonance lines and reduced signal overlap, without information loss. Here we show that as a result of the superior quality of the SAIL NMR spectra, reliable, fully automated analyses of the NMR spectra and structure calculations are possible using fewer input spectra than with conventional uniformly 13C/15N-labeled proteins. FLYA calculations with SAIL ubiquitin, using a single three-dimensional “through-bond” spectrum (and 2D HSQC spectra) in addition to the 13C-edited and 15N-edited NOESY spectra for conformational restraints, yielded structures with an accuracy of 0.83–1.15 Å for the backbone RMSD to the conventionally determined solution structure of SAIL ubiquitin. NMR structures can thus be determined almost exclusively from the NOESY spectra that yield the conformational restraints, without the need to record many spectra only for determining intermediate, auxiliary data of the chemical shift assignments. The FLYA calculations for this report resulted in 252 ubiquitin structure bundles, obtained with different input data but identical structure calculation and refinement methods. These structures cover the entire range from highly accurate structures to seriously, but not trivially, wrong structures, and thus constitute a valuable database for the substantiation of structure validation methods. [ABSTRACT FROM AUTHOR]

Investigating proteins ‘at work’ in a living environment at atomic resolution is a major goal of molecular biology, which has not been achieved even though methods for the three-dimensional (3D) structure determination of purified proteins in single crystals or in solution are widely used. Recent developments in NMR hardware and methodology have enabled the measurement of high-resolution heteronuclear multi-dimensional NMR spectra of macromolecules in living cells (in-cell NMR). Various intracellular events such as conformational changes, dynamics and binding events have been investigated by this method. However, the low sensitivity and the short lifetime of the samples have so far prevented the acquisition of sufficient structural information to determine protein structures by in-cell NMR. Here we show the first, to our knowledge, 3D protein structure calculated exclusively on the basis of information obtained in living cells. The structure of the putative heavy-metal binding protein TTHA1718 from Thermus thermophilus HB8 overexpressed in Escherichia coli cells was solved by in-cell NMR. Rapid measurement of the 3D NMR spectra by nonlinear sampling of the indirectly acquired dimensions was used to overcome problems caused by the instability and low sensitivity of living E. coli samples. Almost all of the expected backbone NMR resonances and most of the side-chain NMR resonances were observed and assigned, enabling high quality (0.96 ångström backbone root mean squared deviation) structures to be calculated that are very similar to the in vitro structure of TTHA1718 determined independently. The in-cell NMR approach can thus provide accurate high-resolution structures of proteins in living environments. [ABSTRACT FROM AUTHOR]

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%. [ABSTRACT FROM AUTHOR]

Non-ribosomal peptide synthetases (NRPS) and polyketide synthases (PKS) found in bacteria, fungi and plants use two different types of thioesterases for the production of highly active biological compounds. Type I thioesterases (TEI) catalyse the release step from the assembly line of the final product where it is transported from one reaction centre to the next as a thioester linked to a 4′-phosphopantetheine (4′-PP) cofactor that is covalently attached to thiolation (T) domains. The second enzyme involved in the synthesis of these secondary metabolites, the type II thioesterase (TEII), is a crucial repair enzyme for the regeneration of functional 4′-PP cofactors of holo-T domains of NRPS and PKS systems. Mispriming of 4′-PP cofactors by acetyl- and short-chain acyl-residues interrupts the biosynthetic system. This repair reaction is very important, because roughly 80% of CoA, the precursor of the 4′-PP cofactor, is acetylated in bacteria. Here we report the three-dimensional structure of a type II thioesterase from Bacillus subtilis free and in complex with a T domain. Comparison with structures of TEI enzymes shows the basis for substrate selectivity and the different modes of interaction of TEII and TEI enzymes with T domains. Furthermore, we show that the TEII enzyme exists in several conformations of which only one is selected on interaction with its native substrate, a modified holo-T domain. [ABSTRACT FROM AUTHOR]

The recent expansion of structural genomics has increased the demands for quick and accurate protein structure determination by NMR spectroscopy. The conventional strategy without an automated protocol can no longer satisfy the needs of high-throughput application to a large number of proteins, with each data set including many NMR spectra, chemical shifts, NOE assignments, and calculated structures. We have developed the new software KUJIRA, a package of integrated modules for the systematic and interactive analysis of NMR data, which is designed to reduce the tediousness of organizing and manipulating a large number of NMR data sets. In combination with CYANA, the program for automated NOE assignment and structure determination, we have established a robust and highly optimized strategy for comprehensive protein structure analysis. An application of KUJIRA in accordance with our new strategy was carried out by a non-expert in NMR structure analysis, demonstrating that the accurate assignment of the chemical shifts and a high-quality structure of a small protein can be completed in a few weeks. The high completeness of the chemical shift assignment and the NOE assignment achieved by the systematic analysis using KUJIRA and CYANA led, in practice, to increased reliability of the determined structure. [ABSTRACT FROM AUTHOR]

Nuclear-magnetic-resonance spectroscopy can determine the three-dimensional structure of proteins in solution. However, its potential has been limited by the difficulty of interpreting NMR spectra in the presence of broadened and overlapping resonance lines and low signal-to-noise ratios. Here we present stereo-array isotope labelling (SAIL), a technique that can overcome many of these problems by applying a complete stereospecific and regiospecific pattern of stable isotopes that is optimal with regard to the quality and information content of the resulting NMR spectra. SAIL uses exclusively chemically and enzymatically synthesized amino acids for cell-free protein expression. We demonstrate for the 17-kDa protein calmodulin and the 41-kDa maltodextrin-binding protein that SAIL offers sharpened lines, spectral simplification without loss of information, and the ability to rapidly collect the structural restraints required to solve a high-quality solution structure for proteins twice as large as commonly solved by NMR. It thus makes a large class of proteins newly accessible to detailed solution structure determination. [ABSTRACT FROM AUTHOR]

Describes the solution structure of the mouse enhancer of rudimentary (ER) protein determined by using heteronuclear nuclear magnetic resonance spectroscopy. Role of the regulatory or enzymatic activity of ER in pyrimidine biosynthesis and the cell cycle; Dimer or trimer behavior of ER in solution.

Determines the nuclear magnetic resonance (NMR) structure of the monomeric form of the protein gpD. Structural basis of the trimerization during capsid assembly; Mechanism of capsid stabilization by gpD; Statistics for the NMR solution structure of the gpD protein.

Examines how the structures of both the human feline sarcoma oncogene (Fes) protein and Src SH2 domains operate differently in the context of the full length Fes protein. Approach in which the Fes SH2 domain acts in a negative regulatory way; Description on the structures of Fes and SrC SH2 domains; Involvement of Fes in the growth and differentiation of myeloid hematopoietic cells.

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: BmPBPA – 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 [ABSTRACT FROM AUTHOR]

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 novo protein 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 novo protein 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 novo protein structure determination by NMR. [ABSTRACT FROM AUTHOR]

Presents a letter to the editor commenting on the NMR structure of the class I human ubiquitin-conjugating enzyme 2b.

A new program, Mapper, for semiautomatic sequence-specific NMR assignment in proteins is introduced. The program uses an input of short fragments of sequentially neighboring residues, which have been assembled based on sequential NMR connectivities and for which either the 13Cα and 13Cβ chemical shifts or data on the amino acid type from other sources are known. Mapper then performs an exhaustive search for self-consistent simultaneous mappings of all these fragments onto the protein sequence. Compared to using only the individual mappings of the spectroscopically connected fragments, the global mapping adds a powerful new constraint, which results in resolving many otherwise intractable ambiguities. In an initial application, virtually complete sequence-specific assignments were obtained for a 110 kDa homooctameric protein, 7,8-dihydroneopterin aldolase from Staphylococcus aureus. [ABSTRACT FROM AUTHOR]

The program DYANA, for calculation of solution structures of biomolecules with an algorithm based on simulated annealing by torsion angle dynamics, has been supplemented with a new routine, PSEUDYANA, that enables efficient use of pseudocontact shifts as additional constraints in structure calculations of paramagnetic metalloproteins. PSEUDYANA can determine the location of the metal ion inside the protein frame and allows to define a single tensor of magnetic susceptibility from a family of conformers. As an illustration, a PSEUDYANA structure calculation is provided for a metal-undecapeptide complex, where simulated pseudocontact shifts but no NOE restraints are used as conformational constraints. [ABSTRACT FROM AUTHOR]

The new computer algorithm FOUND, which is implemented as an integrated module of the DYANA structure calculation program, is capable of performing systematic local conformation analyses by exhaustive grid searches for arbitrary contiguous fragments of proteins and nucleic acids. It uses torsion angles as the only degrees of freedom to identify all conformations that fulfill the steric and NMR-derived conformational restraints within a contiguous molecular fragment, as defined either by limits on the maximal restraint violations or by the fragment-based DYANA target function value. Sets of mutually dependent torsion angles, for example in ribose rings, are treated as a single degree of freedom. The results of the local conformation analysis include allowed torsion angle ranges and stereospecific assignments for diastereotopic substituents, which are then included in the input of a subsequent structure calculation. FOUND can be used for grid searches comprising up to 13 torsion angles, such as the backbone of a complete α-helical turn or dinucleotide fragments in nucleic acids, and yields a significantly higher number of stereospecific assignments than the precursor grid search algorithm HABAS. [ABSTRACT FROM AUTHOR]

A procedure for automated protein structure determination is presented that is based on an iterative procedure during which the NOESY peak list assignment and the structure calculation are performed simultaneously. The input consists of a list of NOESY peak positions and a list of chemical shifts as obtained from sequence-specific resonance assignment. For the present applications of this approach the previously introduced NOAH routine was implemented in the distance geometry program DIANA. As an illustration, experimental 2D and 3D NOESY cross-peak lists of six proteins have been analyzed, for which complete sequence-specific 1H assignments are available for the polypeptide backbone and the amino acid side chains. The automated method assigned 70–90% of all NOESY cross peaks, which is on average 10% less than with the interactive approach, and only between 0.8% and 2.4% of the automatically assigned peaks had a different assignment than in the corresponding manually assigned peak lists. The structures obtained with NOAH/DIANA are in close agreement with those from manually assigned peak lists, and with both approaches the residual constraint violations correspond to high-quality NMR structure determinations. Systematic comparisons of the bundles of conformers that represent corresponding automatically and interactively determined structures document the absence of significant bias in either approach, indicating that an important step has been made towards automation of structure determination from NMR spectra. [ABSTRACT FROM AUTHOR]

Isotopically labeled methyl groups provide NMR probes in large, otherwise deuterated proteins. However, the resonance assignment constitutes a bottleneck for broader applicability of methyl-based NMR. Here, we present the automated MethylFLYA method for the assignment of methyl groups that is based on methyl-methyl nuclear Overhauser effect spectroscopy (NOESY) peak lists. MethylFLYA is applied to five proteins (28–358 kDa) comprising a total of 708 isotope-labeled methyl groups, of which 612 contribute NOESY cross peaks. MethylFLYA confidently assigns 488 methyl groups, i.e. 80% of those with NOESY data. Of these, 459 agree with the reference, 6 were different, and 23 were without reference assignment. MethylFLYA assigns significantly more methyl groups than alternative algorithms, has an average error rate of 1%, modest runtimes of 0.4–1.2 h, and can handle arbitrary isotope labeling patterns and data from other types of NMR spectra. The structures and dynamics of large proteins can be studied with methyl-based NMR but peak assignment is still challenging. Here the authors present MethylFLYA that allows automated assignment of methyl groups and apply it to five proteins with molecular weights in the range from 28 to 358 kDa. [ABSTRACT FROM AUTHOR]

Atomic-resolution structure determination is crucial for understanding protein function. Cryo-EM and NMR spectroscopy both provide structural information, but currently cryo-EM does not routinely give access to atomic-level structural data, and, generally, NMR structure determination is restricted to small (<30 kDa) proteins. We introduce an integrated structure determination approach that simultaneously uses NMR and EM data to overcome the limits of each of these methods. The approach enables structure determination of the 468 kDa large dodecameric aminopeptidase TET2 to a precision and accuracy below 1 Å by combining secondary-structure information obtained from near-complete magic-angle-spinning NMR assignments of the 39 kDa-large subunits, distance restraints from backbone amides and ILV methyl groups, and a 4.1 Å resolution EM map. The resulting structure exceeds current standards of NMR and EM structure determination in terms of molecular weight and precision. Importantly, the approach is successful even in cases where only medium-resolution cryo-EM data are available. NMR structure determination is challenging for proteins with a molecular weight above 30 kDa and atomic-resolution structure determination from cryo-EM data is currently not the rule. Here the authors describe an integrated structure determination approach that simultaneously uses NMR and EM data and allows them to determine the structure of the 468 kDa dodecameric aminopeptidase TET2 complex. [ABSTRACT FROM AUTHOR]

Escherichia coli diacylglycerol kinase (DGK) is an integral membrane protein, which catalyses the ATP-dependent phosphorylation of diacylglycerol (DAG) to phosphatic acid (PA). It is a unique trimeric enzyme, which does not share sequence homology with typical kinases. It exhibits a notable complexity in structure and function despite of its small size. Here, chemical shift assignment of wild-type DGK within lipid bilayers was carried out based on 3D MAS NMR, utilizing manual and automatic analysis protocols. Upon nucleotide binding, extensive chemical shift perturbations could be observed. These data provide evidence for a symmetric DGK trimer with all of its three active sites concurrently occupied. Additionally, we could detect that the nucleotide substrate induces a substantial conformational change, most likely directing DGK into its catalytic active form. Furthermore, functionally relevant interprotomer interactions are identified by DNP-enhanced MAS NMR in combination with site-directed mutagenesis and functional assays. [ABSTRACT FROM AUTHOR]

RNA not only translates the genetic code into proteins, but also carries out important cellular functions. Understanding such functions requires knowledge of the structure and dynamics at atomic resolution. Almost half of the published RNA structures have been solved by nuclear magnetic resonance (NMR). However, as a result of severe resonance overlap and low proton density, high-resolution RNA structures are rarely obtained from nuclear Overhauser enhancement (NOE) data alone. Instead, additional semi-empirical restraints and labor-intensive techniques are required for structural averages, while there are only a few experimentally derived ensembles representing dynamics. Here we show that our exact NOE (eNOE) based structure determination protocol is able to define a 14-mer UUCG tetraloop structure at high resolution without other restraints. Additionally, we use eNOEs to calculate a two-state structure, which samples its conformational space. The protocol may open an avenue to obtain high-resolution structures of small RNA of unprecedented accuracy with moderate experimental efforts. Parker Nichols et al. present an exact nuclear Overhauser enhancement (eNOE) protocol for defining small RNA structures at high resolution using only NOE distance data. They apply eNOE to a 14-mer UUCG tetraloop structure, obtaining a decrease in root-mean-square deviation from 1.52 Å to 0.44 Å, compared to conventional NOE. [ABSTRACT FROM AUTHOR]

The article presents a unified, open-source nuclear magnetic resonance (NMR) exchange format (NEF) for NMR restraints and associated data. NMR restraint data are deposited in a variety of software-specific formats that have to be curated by the Biological Magnetic Resonance Bank (BMRB). Also discussed are the consultations and workshops organized by the Worldwide Protein Data Bank and the Collaborative Computing Project for NMR to attain a unified approach to represent NMR data.