Automated assignment and 3D structure calculations using combinations of 2D homonuclear and 3D heteronuclear NOESY spectra

The NOAH/DIAMOD suite uses feedback filtering and self-correcting distance geometry to generate 3D structures from unassigned NOESY spectra. In this study we determined the minimum set of experiments needed to generate a high quality structure bundle. Different combinations of 3D ¹⁵N-edited, ¹³C-edited HSQC-NOESY and 2D homonuclear ¹H-¹H NOESY spectra of the 77 amino acid protein, myeloid progenitor inhibitory factor-1 (MPIF-1) were used as input for NOAH/DIAMOD calculations. The quality of the assignments of NOESY cross peaks and the accuracy of the automatically generated 3D structures were compared to those obtained with a conventional manual procedure. Combining data from two types of experiments synergistically increased the number of peaks assigned unambiguously in both individual spectra. As a general trend for the accuracy of the structures we observed structural variations in the backbone fold of the final structures of about 2 Å for single spectral data, of 1 Å to 1.5 Å for double spectral data, and of 0.6 Å for triple spectral data sets. The quality of the assignments and 3D structures from the optimal data using all three spectra were similar to those obtained from traditional assignment methods with structural variations within the bundle of 0.6 Å and 1.3 Å for backbone and heavy atoms, respectively. Almost all constraints (97%) of the automatic NOESY cross peak assignments were cross compatible with the structures from the conventional manual assignment procedure, and an even larger proportion (99%) of the manually derived constraints were compatible with the automatically determined 3D structures. The two mean structures determined by both methods differed only by 1.3 Å rmsd for the backbone atoms in the well-defined regions of the protein. Thus NOAD/DIAMOD analysis of spectra from labeled proteins provides a reliable method for high throughput analysis of genomic targets.     

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     

Application of automated NOE assignment to three-dimensional structure refinement of a 28 kDa single-chain T cell receptor

An automated procedure for NOE assignment and three-dimensional structure refinement is presented. The input to the procedure consists of (1) an ensemble of preliminary protein NMR structures, (2) partial sequence-specific assignments for the protein and (3) the positions and volumes of unassigned NOESY cross peaks. Chemical shifts for unassigned side chain protons are predicted from the preliminary structures. The chemical shifts and unassigned NOESY cross peaks are input to an automated procedure for NOE assignment and structure calculation (ARIA) [Nilges et al. (1997) J. Mol. Biol., 269, 408–422]. ARIA is optimized for the task of structure refinement of larger proteins. Errors are filtered to ensure that sequence-specific assignments are reliable. The procedure is applied to the 27.8 kDa single-chain T cell receptor (scTCR). Preliminary NMR structures, nearly complete backbone assignments, partial assignments of side chain protons and more than 1300 unassigned NOESY cross peaks are input. Using the procedure, the resonant frequencies of more than 40 additional side chain protons are assigned. Over 400 new NOE cross peaks are assigned unambiguously. Distances derived from the automatically assigned NOEs improve the precision and quality of calculated scTCR structures. In the refined structures, a hydrophobic cluster of side chains on the scTCR surface that binds major histocompatibility complex (MHC)/antigen is revealed. It is composed of the side chains of residues from three loops and stabilizes the conformation of residues that interact with MHC.     

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.     

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.     

SANE (Structure Assisted NOE Evaluation): An automated model-based approach for NOE assignment

A reliable automated approach for assignment of NOESY spectra would allow more rapid determination of protein structures by NMR. In this paper we describe a semi-automated procedure for complete NOESY assignment (SANE, Structure Assisted NOE Evaluation), coupled to an iterative procedure for NMR structure determination where the user is directly involved. Our method is similar to ARIA [Nilges et al. (1997) J. Mol. Biol., 269, 408–422], but is compatible with the molecular dynamics suites AMBER and DYANA. The method is ideal for systems where an initial model or crystal structure is available, but has also been used successfully for ab initio structure determination. Use of this semi-automated iterative approach assists in the identification of errors in the NOE assignments to short-cut the path to an NMR solution structure.     

Amino acid selective unlabeling for sequence specific resonance assignments in proteins

Sequence specific resonance assignment constitutes an important step towards high-resolution structure determination of proteins by NMR and is aided by selective identification and assignment of amino acid types. The traditional approach to selective labeling yields only the chemical shifts of the particular amino acid being selected and does not help in establishing a link between adjacent residues along the polypeptide chain, which is important for sequential assignments. An alternative approach is the method of amino acid selective ‘unlabeling’ or reverse labeling, which involves selective unlabeling of specific amino acid types against a uniformly ¹³C/¹⁵N labeled background. Based on this method, we present a novel approach for sequential assignments in proteins. The method involves a new NMR experiment named, {¹²CO _i –¹⁵N _i+1}-filtered HSQC, which aids in linking the ¹H^N/¹⁵N resonances of the selectively unlabeled residue, i, and its C-terminal neighbor, i + 1, in HN-detected double and triple resonance spectra. This leads to the assignment of a tri-peptide segment from the knowledge of the amino acid types of residues: i − 1, i and i + 1, thereby speeding up the sequential assignment process. The method has the advantage of being relatively inexpensive, applicable to ²H labeled protein and can be coupled with cell-free synthesis and/or automated assignment approaches. A detailed survey involving unlabeling of different amino acid types individually or in pairs reveals that the proposed approach is also robust to misincorporation of ¹⁴N at undesired sites. Taken together, this study represents the first application of selective unlabeling for sequence specific resonance assignments and opens up new avenues to using this methodology in protein structural studies.     

Automated combined assignment of NOESY spectra and three-dimensional protein structure determination

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.     

Proton nuclear magnetic resonance studies on huwentoxin-I from the venom of the spiderSelenocosmia huwena: 1. Sequence-specific1H-NMR assignments

The complete sequence-specific assignments of resonances in the¹H-NMR spectrum of huwentoxin-I from the Chinese bird spider,Selenocosmia huwena, is described. A combination of two-dimensional NMR experiments including 2D-COSY, 2D-NOESY, and 2D-TOCSY has been employed on samples of the toxin dissolved in D₂O and in H₂O for assignment purposes. Protons belonging to spin systems for each of the 33 amino acids were identified. The sequence-specific assignments were facilitated by the identification ofd _N connectivities on the fingerprint regions of the COSY and NOESY spectra and were supported by the identification ofd _NN andd _N connectivities in the TOCSY and NOESY spectra. These studies provide a basis for the determination of the solution-phase conformation of this toxin.Abbreviations HWTX-I huwentoxin-I - 2D two-dimensional - COSY 2D homonuclear correlation spectroscopy - NOE nuclear Overhauser enhancement - NOESY 2D nuclear Overhauser enhancement spectroscopy - TOCSY 2D total correlation spectroscopy - TPPI time-proportional phase incrementation - TSP sodium 3-(trimethyl-silyl)propionate-d4 - EDTA ethylenediaminetetraacetic acid     

Optimization of amino acid type-specific <Superscript>13</Superscript>C and <Superscript>15</Superscript>N labeling for the backbone assignment of membrane proteins by solution- and solid-state NMR with the UPLABEL algorithm

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 ¹³C or/and ¹⁵N such that cross peaks between ¹³CO(i – 1) and ¹⁵NH(i) result only for pairs of sequentially adjacent amino acids of which the first is labeled with ¹³C and the second with ¹⁵N. 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 (B₂R) and applied as a starting point for the backbone assignment of the membrane protein proteorhodopsin.     

Comparison of parameters estimated from A/Ci and A/Cc curve analysis

The parameters estimated from traditional A/C _i curve analysis are dependent upon some underlying assumptions that substomatal CO₂ concentration (C _i) equals the chloroplast CO₂ concentration (C _c) and the C _i value at which the A/C _i curve switches between Rubisco- and electron transport-limited portions of the curve (C _i-t) is set to a constant. However, the assumptions reduced the accuracy of parameter estimation significantly without taking the influence of C _i-t value and mesophyll conductance (g _m) on parameters into account. Based on the analysis of Larix gmelinii’s A/C _i curves, it showed the C _i-t value varied significantly, ranging from 24 Pa to 72 Pa and averaging 38 Pa. t-test demonstrated there were significant differences in parameters respectively estimated from A/C _i and A/C _c curve analysis (p<0.01). Compared with the maximum ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) carboxylation rate (V_cmax), the maximum electron transport rate (J_max) and J_max/V_cmax estimated from A/C _c curve analysis which considers the effects of g _m limit and simultaneously fits parameters with the whole A/C _c curve, mean V_cmax estimated from A/C _i curve analysis (V_cmax-C _i) was underestimated by 37.49%; mean Jmax estimated from A/C _i curve analysis (J_max-C _i) was overestimated by 17.8% and (J_max-C _i)/(V_cmax-C _i) was overestimated by 24.2%. However, there was a significant linear relationship between V_cmax estimated from A/C _i curve analysis and V_cmax estimated from A/C _c curve analysis, so was it J_max (p<0.05).     

Hierarchical Classification I: Single-Linkage Method

This is the first part of a survey of hierarchical clustering algorithms using joining methods: the Single-Linkage algorithm. Complete-Linkage and general algorithms defined by d(A_i, B) = = α,d(A_i, A_r)±α_sd(A_i, A_s)±βd(A_r, A_s) will be discussed in two subsequent papers.     

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.     

Proton nuclear magnetic resonance studies on huwentoxin-I from the venom of the spiderSelenocosmia huwena: 1. Sequence-specific1H-NMR assignments

The complete sequence-specific assignments of resonances in the¹H-NMR spectrum of huwentoxin-I from the Chinese bird spider,Selenocosmia huwena, is described. A combination of two-dimensional NMR experiments including 2D-COSY, 2D-NOESY, and 2D-TOCSY has been employed on samples of the toxin dissolved in D₂O and in H₂O for assignment purposes. Protons belonging to spin systems for each of the 33 amino acids were identified. The sequence-specific assignments were facilitated by the identification ofd _αN connectivities on the fingerprint regions of the COSY and NOESY spectra and were supported by the identification ofd _NN andd _αN connectivities in the TOCSY and NOESY spectra. These studies provide a basis for the determination of the solution-phase conformation of this toxin.     

Additive and testcross genetic variances in crosses among recombinant inbreds

 Breeders desire populations with a high mean performance and a large genetic variance. Theory and methods are lacking for predicting additive variance (V _A ) and testcross variance (V _T ) in biparental populations. Breeders have unsuccessfully attempted to predict V _A based on the coefficient of coancestry ( f ) or molecular-marker similarity between parents. In this paper, we derive the expected values of V _A and V _T in biparental populations, examine the variability of V _A among biparental crosses, and discuss how V _A and V _T may be predicted in applied breeding programs. Suppose i is a recombinant inbred derived from the cross between inbreds P ₁ and P ₂, and inbred j is not a direct descendant of i. Let V _A(i,j) be the additive variance in the F₂ of the (i×j) biparental cross. Let V _T(i, j) be the variance among testcrosses of F₂ individuals with a specific unrelated inbred or population. Assuming linkage equilibrium and the absence of epistasis, V _A(i, j) =λV _A(P1, j) +(1−λ) V _A(P2, j) , where λ= parental contribution of P ₁ to i. Similarly, V _T(i, j) = λV _T(P1, j) +(1−λ) V _T(P2, j) . Additive variance in crosses between recombinant inbreds cannot be modelled as a function of  f if, as indicated in the literature, V _A differs among crosses of founder inbreds. If molecular-marker similarity between parents is used as an estimate of f, then a strong linear relationship is likewise not expected between V _A and marker similarity. Differences between the actual and expected λ led to variation in V _A . In applied breeding programs, modelling V _A or V _T in biparental crosses may be feasible with estimates of V _A or V _T in prior crosses and information on λ obtained from molecular-marker data. Received: 23 September 1997 / Accepted: 30 December 1997     

Current–voltage–time records of ion translocating enzymes

Membrane currents, as non-linear functions of membrane voltage, V, and time, t, can be recorded quickly by triangular V protocols. From the differences, dI(V,t), of these relationships upon addition of a putative substrate of a charge-translocating membrane protein, the I(V,t) relationships of the transporter itself can be determined. These relationships likely comprise a steady-state component, I_a(V), of the active transporter, and a dynamic component, p_a(V,t), of its V- and time-dependent activity, p_a. Here, the steady-state component is modeled by a central reaction cycle, which senses a fraction _tr of the total V, whereas 1–_tr can be assigned to an inner and outer pore section with _i and _o, respectively (_i+_tr+_o = 1). For the enzymatic cycle, fast binding/debinding is assumed, plus V-sensitive and -insensitive reaction steps which may become rate limiting for charge translocation. At given substrate concentrations, I_a(V) is defined by eight independent system parameters, including a coefficient for the barrier shape of charge translocation. In ordinary cases, the behavior of p_a(V,t) can be described by two rate constants (for activation and inactivation) and their respective V-sensitivity coefficients. Here, the effects of the individual system parameters on I(V,t) from triangular V-clamp experiments are investigated systematically. The results are illustrated by panels of typical curve shapes for non-gated and gated transporters to enable a first classification of mechanisms. We demonstrate that all system parameters can be determined fairly well by fitting the model to experimental data of known origin. Applicability of the model to channels, pumps and cotransporters is discussed.     

A CD and an nmr study of multiple bradykinin conformations in aqueous trifluoroethanol solutions

CD and nmr studies have been carried out on aqueous trifluoroethanol (TFE) solutions of bradykinin (BK) and a bradykinin antagonist. The CD results exhibit a striking effect of TFE on the spectra of BK, with sequence Arg-Pro-Pro-Gly-Phe-Ser-Pro-Phe-Arg, and the BK antagonist, with sequence D -Arg-Arg-Pro-Hyp-Gly-Thi-D -Ser-D -Cpg-Cpg-Arg [where Hyp is 4-hydroxy-L -proline; Thi refers to β-(2-thienyl)-L -alanine and Cpg refers to α-cyclopentylglycine]. The effect of increasing concentration of TFE in water on the difference ellipticity at 222 nm was examined and showed that BK may be a mixture of at least two different conformers, one of which largely forms when the TFE concentration is increased beyond 80%. The linear extrapolation of 100% of the difference ellipticity of BK at low TFE concentrations yields a value in agreement with that shown by the BK antagonist, indicating that the conformation of BK at the lower TFE concentrations is similar to that of the BK antagonist. The conformational analysis was carried out using both one-dimensional and two-dimensional ¹H-nmr techniques. The total correlation spectroscopy (TOCSY) spectrum of BK in a 60/40% (v/v) TFE/H₂O solution at 10°C and a nuclear Overhauser effect spectroscopy (NOESY) spectrum that shows only sequential H_α(i) – NH(i + 1) or the H_α(i) – H_δδ′(i + 1) NOEs indicate that the majority of the molecules adopt an all-trans extended conformation. The TOCSY for BK in the 95/5% (v/v) TFE/H₂O solution shows that there are two major conformations in the solution with about equal population. The NOESY experiment shows two new important cross peaks for one conformation, namely Pro²(α)-Pro³ (α) and the Pro²(α)-Gly⁴(NH), indicating a cis Pro²-Pro³ bond and a type VI β-turn between residues Arg¹ and Gly⁴ involving cis proline at position 3, respectively. The low temperature coefficient of Gly⁴ for this conformation suggests the presence of an intramolecular hydrogen bond, therefore a type VIa β-turn is present. The other conformation is all trans and extended. The BK antafonist shows difference CD spectra in TFE solutions referred to H₂O that are superficially indicative of a β-bend. However, nmr speaks against this possibility, as only one set of peaks were observed in the TOCSY and NOESY experiments, indicating an all-trans extended confirmation over the range of TFE concentrations. The BK-antagonist CD data suggest that solvent perturbation of the CD of an extended confirmation perturbation of the optical activity of the thienyl moiety of the peptide since the CD spectrum of N-acetyl-β-thienyl-L -alanine N-methylamide is strongly perturbed by TFE. The present results again demonstrate the complementary relationship between CD and nmr. © 1994 John Wiley & Sons, Inc.     

1H(C) and 1H(N) total NOE correlations in a single 3D NMR experiment. 15N and 13C time-sharing in t1 and t2 dimensions for simultaneous data acquisition

Simultaneous data acquisition in time-sharing (TS) multi-dimensional NMR experiments has been shown an effective means to reduce experimental time, and thus to accelerate structure determination of proteins. This has been accomplished by spin evolution time-sharing of the X and Y heteronuclei, such as ¹⁵N and ¹³C, in one of the time dimensions. In this work, we report a new 3D TS experiment, which allows simultaneous ¹³C and ¹⁵N spin labeling coherence in both t ₁ and t ₂ dimensions to give four NOESY spectra in a single 3D experiment. These spectra represent total NOE correlations between ¹H_N and ¹H_C resonances. This strategy of double time-sharing (2TS) results in an overall four-fold reduction in experimental time compared with its conventional counterpart. This 3D 2TS CN-CN-H HSQC-NOESY-HSQC pulse sequence also demonstrates improvements in water suppression, ¹⁵N spectral resolution and sensitivity, which were developed based on 2D TS CN-H HSQC and 3D TS H-CN-H NOESY-HSQC experiments. Combining the 3D TS and the 3D 2TS NOESY experiments, NOE assignment ambiguities and errors are considerably reduced. These results will be useful for rapid protein structure determination to complement the effort of discerning the functions of diverse genomic proteins.     

Pseudo-4D triple resonance experiments to resolve HN overlap in the backbone assignment of unfolded proteins

The solution NMR resonance assignment of the protein backbone is most commonly carried out using triple resonance experiments that involve ¹⁵N and ¹HN resonances. The assignment becomes problematic when there is resonance overlap of ¹⁵N–¹HN cross peaks. For such residues, one cannot unambiguously link the “left” side of the NH root to the “right” side, and the residues associated with such overlapping HN resonances remain often unassigned. Here we present a solution to this problem: a hybrid (4d,3d) reduced-dimensionality HN(CO)CA(CON)CA sequence. In this experiment, the Ca(i) resonance is modulated with the frequency of the Ca(i−1) resonance, which helps in resolving the ambiguity involved in connecting the Ca(i) and Ca(i−1) resonances for overlapping NH roots. The experiment has limited sensitivity, and is only suited for small or unfolded proteins. In a companion experiment, (4d,3d) reduced-dimensionality HNCO(N)CA, the Ca(i) resonance is modulated with the frequency of the CO(i−1) resonance, hence resolving the ambiguity existent in pairing up the Ca(i) and CO(i−1) resonances for overlapping NH roots.     

3D Triple-resonance NMR techniques for the sequential assignment of NH and 15N resonances in 15N- and 13C-labelled proteins

Summary Two new 3D ¹H-¹⁵N-¹³C triple-resonance experiments are presented which provide sequential cross peaks between the amide proton of one residue and the amide nitrogen of the preceding and succeeding residues or the amide proton of one residue and the amide proton of the preceding and succeeding residues, respectively. These experiments, which we term 3D-HN(CA)NNH and 3D-H(NCA)NNH, utilize an optimized magnetization transfer via the ²J_NC coupling to establish the sequential assignment of backbone NH and ¹⁵N resonances. In contrast to NH-NH connectivities observable in homonuclear NOESY spectra, the assignments from the 3D-H(NCA)NNH experiment are conformation independent to a first-order approximation. Thus the assignments obtained from these experiments can be used as either confirmation of assignments obtained from a conventional homonuclear approach or as an initial step in the analysis of backbone resonances according to Ikura et al. (1990) [Biochemistry, 29, 4659–4667]. Both techniques were applied to uniformly ¹⁵N- and ¹³C-labelled ribonuclease T1.