Protein structure determination by conformational space annealing using NMR geometric restraints

We have carried out numerical experiments to investigate the applicability of the global optimization method of conformational space annealing (CSA) to the enhanced NMR protein structure determination over existing PDB structures. The NMR protein structure determination is driven by the optimization of collective multiple restraints arising from experimental data and the basic stereochemical properties of a protein‐like molecule. By rigorous and straightforward application of CSA to the identical NMR experimental data used to generate existing PDB structures, we redetermined 56 recent PDB protein structures starting from fully randomized structures. The quality of CSA‐generated structures and existing PDB structures were assessed by multiobjective functions in terms of their consistencies with experimental data and the requirements of protein‐like stereochemistry. In 54 out of 56 cases, CSA‐generated structures were better than existing PDB structures in the Pareto‐dominant manner, while in the remaining two cases, it was a tie with mixed results. As a whole, all structural features tested improved in a statistically meaningful manner. The most improved feature was the Ramachandran favored portion of backbone torsion angles with about 8.6% improvement from 88.9% to 97.5% (P‐value <10^?17). We show that by straightforward application of CSA to the efficient global optimization of an energy function, NMR structures will be of better quality than existing PDB structures. Proteins 2015; 83:2251–2262. © 2015 Wiley Periodicals, Inc.     

Temperature and urea induced denaturation of the TRP‐cage mini protein TC5b: A simulation study consistent with experimental observations

The effects of temperature and urea denaturation (6M urea) on the dominant structures of the 20‐residue Trp‐cage mini‐protein TC5b are investigated by molecular dynamics simulations of the protein at different temperatures in aqueous and in 6M urea solution using explicit solvent degrees of freedom and the GROMOS force‐field parameter set 45A3. In aqueous solution at 278 K, TC5b is stable throughout the 20 ns of MD simulation and the trajectory structures largely agree with the NMR‐NOE atom–atom distance data available. Raising the temperature to 360 K and to 400 K, the protein denatures within 22 ns and 3 ns, showing that the denaturation temperature is well below 360 K using the GROMOS force field. This is 40–90 K lower than the denaturation temperatures observed in simulations using other much used protein force fields. As the experimental denaturation temperature is about 315 K, the GROMOS force field appears not to overstabilize TC5b, as other force fields and the use of continuum solvation models seem to do. This feature may directly stem from the GROMOS force‐field parameter calibration protocol, which primarily involves reproduction of condensed phase thermodynamic quantities such as energies, densities, and solvation free energies of small compounds representative for protein fragments. By adding 6M urea to the solution, the onset of denaturation is observed in the simulation, but is too slow to observe a particular side‐chain side‐chain contact (Trp6‐Ile4) that was experimentally observed to be characteristic for the denatured state. Interestingly, using temperature denaturation, the process is accelerated and the experimental data are reproduced.     

A computer-based protocol for semiautomated assignments and 3D structure determination of proteins

Summary A strategy is presented for the semiautomated assignment and 3D structure determination of proteins from heteronuclear multidimensional Nuclear Magnetic Resonance (NMR) data. This approach involves the computer-based assignment of the NMR signals, identification of distance restraints from nuclear Overhauser effects, and generation of 3D structures by using the NMR-derived restraints. The protocol is described in detail and illustrated on a resonance assignment and structure determination of the FK506 binding protein (FKBP, 107 amino acids) complexed to the immunosuppressant, ascomycin. The 3D structures produced from this automated protocol attained backbone and heavy atom rmsd of 1.17 and 1.69 Å, respectively. Although more highly resolved structures of the complex have been obtained by standard interpretation of NMR data (Meadows et al. (1993) Biochemistry, 32, 754–765), the structures generated with this automated protocol required minimal manual intervention during the spectral assignment and 3D structure calculations stages. Thus, the protocol may yield an approximate order of magnitude reduction in the time required for the generation of 3D structures of proteins from NMR data.     

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

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

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.     

Resolving the ambiguity: Making sense of intrinsic disorder when PDB structures disagree

Missing regions in X‐ray crystal structures in the Protein Data Bank (PDB) have played a foundational role in the study of intrinsically disordered protein regions (IDPRs), especially in the development of in silico predictors of intrinsic disorder. However, a missing region is only a weak indication of intrinsic disorder, and this uncertainty is compounded by the presence of ambiguous regions, where more than one structure of the same protein sequence “disagrees” in terms of the presence or absence of missing residues. The question is this: are these ambiguous regions intrinsically disordered, or are they the result of static disorder that arises from experimental conditions, ensembles of structures, or domain wobbling? A novel way of looking at ambiguous regions in terms of the pattern between multiple PDB structures has been demonstrated. It was found that the propensity for intrinsic disorder increases as the level of ambiguity decreases. However, it is also shown that ambiguity is more likely to occur as the protein region is placed within different environmental conditions, and even the most ambiguous regions as a set display compositional bias that suggests flexibility. The results suggested that ambiguity is a natural result for many IDPRs crystallized under different conditions and that static disorder and wobbling domains are relatively rare. Instead, it is more likely that ambiguity arises because many of these regions were conditionally or partially disordered.     

Automated protein fold determination using a minimal NMR constraint strategy

Determination of precise and accurate protein structures by NMR generally requires weeks or even months to acquire and interpret all the necessary NMR data. However, even medium-accuracy fold information can often provide key clues about protein evolution and biochemical function(s). In this article we describe a largely automatic strategy for rapid determination of medium-accuracy protein backbone structures. Our strategy derives from ideas originally introduced by other groups for determining medium-accuracy NMR structures of large proteins using deuterated, (13)C-, (15)N-enriched protein samples with selective protonation of side-chain methyl groups ((13)CH(3)). Data collection includes acquiring NMR spectra for automatically determining assignments of backbone and side-chain (15)N, H(N) resonances, and side-chain (13)CH(3) methyl resonances. These assignments are determined automatically by the program AutoAssign using backbone triple resonance NMR data, together with Spin System Type Assignment Constraints (STACs) derived from side-chain triple-resonance experiments. The program AutoStructure then derives conformational constraints using these chemical shifts, amide (1)H/(2)H exchange, nuclear Overhauser effect spectroscopy (NOESY), and residual dipolar coupling data. The total time required for collecting such NMR data can potentially be as short as a few days. Here we demonstrate an integrated set of NMR software which can process these NMR spectra, carry out resonance assignments, interpret NOESY data, and generate medium-accuracy structures within a few days. The feasibility of this combined data collection and analysis strategy starting from raw NMR time domain data was illustrated by automatic analysis of a medium accuracy structure of the Z domain of Staphylococcal protein A.     

A calculation strategy for the structure determination of symmetric demers by 1H NMR

The structure determination of symmetric dimers by NMR is impeded by the ambiguity of inter- and intramonomer NOE crosspeaks. In this paper, a calculation strategy is presented that allows the calculation of dimer structures without resolving ther ambuguity by additional experiments (like asymmetric labeling). The strategy employs a molecular dynamic-based simulated annealing approach to minimize a traget function. The experimental part of the target function contains distance restraints that correctly describe the ambiguity of the NOE peaks, and a novel term that restrains the symmetry of the dimer without requiring the knowledge of the symmetry axis. The use of the method is illustrated by three examples, using experimentally obtained data and model data derived from a known structure. For the purpose of testing the method, it is assumed that every NOE crosspeak is ambiguous in all three cases. It is shown that the structure of a homologous protein is known and in ab intio structure determination. The method can be extended to higher order symmetric multimers. © 1993 Wiley-Liss, Inc.     

Robust structure-based resonance assignment for functional protein studies by NMR

High-throughput functional protein NMR studies, like protein interactions or dynamics, require an automated approach for the assignment of the protein backbone. With the availability of a growing number of protein 3D structures, a new class of automated approaches, called structure-based assignment, has been developed quite recently. Structure-based approaches use primarily NMR input data that are not based on J-coupling and for which connections between residues are not limited by through bonds magnetization transfer efficiency. We present here a robust structure-based assignment approach using mainly H ^N –H ^N NOEs networks, as well as ¹ H–¹⁵ N residual dipolar couplings and chemical shifts. The NOEnet complete search algorithm is robust against assignment errors, even for sparse input data. Instead of a unique and partly erroneous assignment solution, an optimal assignment ensemble with an accuracy equal or near to 100% is given by NOEnet. We show that even low precision assignment ensembles give enough information for functional studies, like modeling of protein-complexes. Finally, the combination of NOEnet with a low number of ambiguous J-coupling sequential connectivities yields a high precision assignment ensemble. NOEnet will be available under: .     

Simultaneous determination of disulphide bridge topology and three-dimensional structure using ambiguous intersulphur distance restraints: Possibilities and limitations

Knowledge of the native disulphide bridge topology allows the introduction of conformational restraints between remote parts of the peptide chain. This information is therefore of great importance for the successful determination of the three-dimensional structure of cysteine-rich proteins by NMR spectroscopy. In this paper we investigate the limitations of using ambiguous intersulphur restraints [Nilges, M. (1995) J. Mol. Biol., 245, 645–660] associated with NMR experimental information to determine the native disulphide bridge pattern. Using these restraints in a simulated annealing protocol we have determined the correct topology of numerous examples, including a protein with seven disulphide bridges (phospholipase A₂) and a protein in which 25% of the total number of residues are cysteines (-conotoxin GIIIB). We have also characterised the behaviour of the method when only limited experimental data is available, and find that the proposed protocol permits disulphide bridge determination even with a small number of restraints (around 5 NOEs – including a long-range restraint – per residue). In addition, we have shown that under these conditions the use of a reduced penalty function allows the identification of misassigned NOE restraints. These results indicate that the use of ambiguous intersulphur distances with the proposed simulated annealing protocol is a general method for the determination of disulphide bridge topology, particularly interesting in the first steps of NMR study of cysteine-rich proteins. Comparison with previously proposed protocols indicates that the presented method is more reliable and the interpretation of results is straightforward.     

Systematic evaluation of CS‐Rosetta for membrane protein structure prediction with sparse NOE restraints

We critically test and validate the CS‐Rosetta methodology for de novo structure prediction of ‐helical membrane proteins (MPs) from NMR data, such as chemical shifts and NOE distance restraints. By systematically reducing the number and types of NOE restraints, we focus on determining the regime in which MP structures can be reliably predicted and pinpoint the boundaries of the approach. Five MPs of known structure were used as test systems, phototaxis sensory rhodopsin II (pSRII), a subdomain of pSRII, disulfide binding protein B (DsbB), microsomal prostaglandin E2 synthase‐1 (mPGES‐1), and translocator protein (TSPO). For pSRII and DsbB, where NMR and X‐ray structures are available, resolution‐adapted structural recombination (RASREC) CS‐Rosetta yields structures that are as close to the X‐ray structure as the published NMR structures if all available NMR data are used to guide structure prediction. For mPGES‐1 and Bacillus cereus TSPO, where only X‐ray crystal structures are available, highly accurate structures are obtained using simulated NMR data. One main advantage of RASREC CS‐Rosetta is its robustness with respect to even a drastic reduction of the number of NOEs. Close‐to‐native structures were obtained with one randomly picked long‐range NOEs for every 14, 31, 38, and 8 residues for full‐length pSRII, the pSRII subdomain, TSPO, and DsbB, respectively, in addition to using chemical shifts. For mPGES‐1, atomically accurate structures could be predicted even from chemical shifts alone. Our results show that atomic level accuracy for helical membrane proteins is achievable with CS‐Rosetta using very sparse NOE restraint sets to guide structure prediction. Proteins 2017; 85:812–826. © 2016 Wiley Periodicals, Inc.     

Three-dimensional structure of the weakly associated protein homodimer SeR13 using RDCs and paramagnetic surface mapping

The traditional NMR‐based method for determining oligomeric protein structure usually involves distinguishing and assigning intra‐ and intersubunit NOEs. This task becomes challenging when determining symmetric homo‐dimer structures because NOE cross‐peaks from a given pair of protons occur at the same position whether intra‐ or intersubunit in origin. While there are isotope‐filtering strategies for distinguishing intra from intermolecular NOE interactions in these cases, they are laborious and often prove ineffectual in cases of weak dimers, where observation of intermolecular NOEs is rare. Here, we present an efficient procedure for weak dimer structure determination based on residual dipolar couplings (RDCs), chemical shift changes upon dilution, and paramagnetic surface perturbations. This procedure is applied to the Northeast Structural Genomics Consortium protein target, SeR13, a negatively charged Staphylococcus epidermidis dimeric protein (K_d 3.4 ± 1.4 mM) composed of 86 amino acids. A structure determination for the monomeric form using traditional NMR methods is presented, followed by a dimer structure determination using docking under orientation constraints from RDCs data, and scoring under residue pair potentials and shape‐based predictions of RDCs. Validation using paramagnetic surface perturbation and chemical shift perturbation data acquired on sample dilution is also presented. The general utility of the dimer structure determination procedure and the possible relevance of SeR13 dimer formation are discussed.     

NMR structure of cysteinyl-phosphorylated enzyme IIB of the N,N'-diacetylchitobiose-specific phosphoenolpyruvate-dependent phosphotransferase system of Escherichia coli

The determination by NMR of the solution structure of the phosphorylated enzyme IIB (P-IIB(Chb)) of the N,N'-diacetylchitobiose-specific phosphoenolpyruvate-dependent phosphotransferase system of Escherichia coli is presented. Most of the backbone and side-chain resonances were assigned using a variety of mostly heteronuclear NMR experiments. The remaining resonances were assigned with the help of the structure calculations.NOE-derived distance restraints were used in distance geometry calculations followed by molecular dynamics and simulated annealing protocols. In addition, combinations of ambiguous restraints were used to resolve ambiguities in the NOE assignments. By combining sets of ambiguous and unambiguous restraints into new ambiguous restraints, an error function was constructed that was less sensitive to information loss caused by assignment uncertainties. The final set of structures had a pairwise rmsd of 0.59 A and 1.16 A for the heavy atoms of the backbone and side-chains, respectively.Comparing the P-IIB(Chb) solution structure with the previously determined NMR and X-ray structures of the wild-type and the Cys10Ser mutant shows that significant differences between the structures are limited to the active-site region. The phosphoryl group at the active-site cysteine residue is surrounded by a loop formed by residues 10 through 16. NOE and chemical shift data suggest that the phosphoryl group makes hydrogen bonds with the backbone amide protons of residues 12 and 15. The binding mode of the phosphoryl group is very similar to that of the protein tyrosine phosphatases. The differences observed are in accordance with the presumption that IIB(Chb) has to be more resistant to hydrolysis than the protein tyrosine phosphatases. We propose a proton relay network by which a transfer occurs between the cysteine SH proton and the solvent via the hydroxyl group of Thr16.     

Energetically unfavorable amide conformations for N6‐acetyllysine side chains in refined protein structures

The reversible acetylation of lysine to form N6‐acetyllysine in the regulation of protein function is a hallmark of epigenetics. Acetylation of the positively charged amino group of the lysine side chain generates a neutral N‐alkylacetamide moiety that serves as a molecular “switch” for the modulation of protein function and protein–protein interactions. We now report the analysis of 381 N6‐acetyllysine side chain amide conformations as found in 79 protein crystal structures and 11 protein NMR structures deposited in the Protein Data Bank (PDB) of the Research Collaboratory for Structural Bioinformatics. We find that only 74.3% of N6‐acetyllysine residues in protein crystal structures and 46.5% in protein NMR structures contain amide groups with energetically preferred trans or generously trans conformations. Surprisingly, 17.6% of N6‐acetyllysine residues in protein crystal structures and 5.3% in protein NMR structures contain amide groups with energetically unfavorable cis or generously cis conformations. Even more surprisingly, 8.1% of N6‐acetyllysine residues in protein crystal structures and 48.2% in NMR structures contain amide groups with energetically prohibitive twisted conformations that approach the transition state structure for cis‐trans isomerization. In contrast, 109 unique N‐alkylacetamide groups contained in 84 highly accurate small molecule crystal structures retrieved from the Cambridge Structural Database exclusively adopt energetically preferred trans conformations. Therefore, we conclude that cis and twisted N6‐acetyllysine amides in protein structures deposited in the PDB are erroneously modeled due to their energetically unfavorable or prohibitive conformations. Proteins 2013; © 2012 Wiley Periodicals, Inc.     

Relationship between chemical shift value and accessible surface area for all amino acid atoms

Background  

Chemical shifts obtained from NMR experiments are an important tool in determining secondary, even tertiary, protein structure. The main repository for chemical shift data is the BioMagResBank, which provides NMR-STAR files with this type of information. However, it is not trivial to link this information to available coordinate data from the PDB for non-backbone atoms due to atom and chain naming differences, as well as sequence numbering changes.     

A graphical method for analyzing distance restraints using residual dipolar couplings for structure determination of symmetric protein homo-oligomers

High-resolution structure determination of homo-oligomeric protein complexes remains a daunting task for NMR spectroscopists. Although isotope-filtered experiments allow separation of intermolecular NOEs from intramolecular NOEs and determination of the structure of each subunit within the oligomeric state, degenerate chemical shifts of equivalent nuclei from different subunits make it difficult to assign intermolecular NOEs to nuclei from specific pairs of subunits with certainty, hindering structural analysis of the oligomeric state. Here, we introduce a graphical method, DISCO, for the analysis of intermolecular distance restraints and structure determination of symmetric homo-oligomers using residual dipolar couplings. Based on knowledge that the symmetry axis of an oligomeric complex must be parallel to an eigenvector of the alignment tensor of residual dipolar couplings, we can represent distance restraints as annuli in a plane encoding the parameters of the symmetry axis. Oligomeric protein structures with the best restraint satisfaction correspond to regions of this plane with the greatest number of overlapping annuli. This graphical analysis yields a technique to characterize the complete set of oligomeric structures satisfying the distance restraints and to quantitatively evaluate the contribution of each distance restraint. We demonstrate our method for the trimeric E. coli diacylglycerol kinase, addressing the challenges in obtaining subunit assignments for distance restraints. We also demonstrate our method on a dimeric mutant of the immunoglobulin-binding domain B1 of streptococcal protein G to show the resilience of our method to ambiguous atom assignments. In both studies, DISCO computed oligomer structures with high accuracy despite using ambiguously assigned distance restraints.     

Building native protein conformation from NMR backbone chemical shifts using Monte Carlo fragment assembly

We have been analyzing the extent to which protein secondary structure determines protein tertiary structure in simple protein folds. An earlier paper demonstrated that three-dimensional structure can be obtained successfully using only highly approximate backbone torsion angles for every residue. Here, the initial information is further diluted by introducing a realistic degree of experimental uncertainty into this process. In particular, we tackle the practical problem of determining three-dimensional structure solely from backbone chemical shifts, which can be measured directly by NMR and are known to be correlated with a protein's backbone torsion angles. Extending our previous algorithm to incorporate these experimentally determined data, clusters of structures compatible with the experimentally determined chemical shifts were generated by fragment assembly Monte Carlo. The cluster that corresponds to the native conformation was then identified based on four energy terms: steric clash, solvent-squeezing, hydrogen-bonding, and hydrophobic contact. Currently, the method has been applied successfully to five small proteins with simple topology. Although still under development, this approach offers promise for high-throughput NMR structure determination.     

Nuclear magnetic resonance and protein structure

NMR provides a wealth of structural information about proteins in solution, but does not, by itself, permit an unambiguous determination of a unique structure. A rigorous interpretation of NMR data to obtain the entire family of structures compatible with a given data set requires extensive, systematic and unbiased sampling of the conformational space of the polypeptide chain. Methods of sampling based on the exclusion paradigm--i. e. those that generate structures, check constraints and accept or reject members of the family on that basis, avoid the problem of generating erroneous structures by converging on local minima, which is a common pitfall of methods based on the optimization paradigm. Their much higher computational cost can be reduced by solving the structure in stages, using abstract representations of partial structures, and guiding the computation by control heuristics. The heuristic refinement method developed at Stanford and encoded in the expert system PROTEAN yields more or less extensive families of structures, depending on the size of the NMR data set, and defines the "allowed volume" in which each atom (or other substructure) may lie, with all experimental constraints satisfied. The allowed volume is a measure of the uncertainty of our knowledge of the structure, to which both the limitations of the data and the uncertainty of position resulting from molecular motion may contribute. Prediction of the experimental NMR spectra by solving the generalized Bloch equations (or the Redfield density matrix) for the protein, using atomic coordinates that lie within the allowed atomic volume, provides the final test for the correctness of the proposed structure.(ABSTRACT TRUNCATED AT 250 WORDS)     

Calculation of symmetric multimer structures from NMR data using a priori knowledge of the monomer structure, co-monomer restraints, and interface mapping: The case of leucine zippers

Summary NMR studies of symmetric multimers are problematic due to the difficulty in distinguishing between intra-, inter-, and co-monomer (mixed) NOE signals. Previously, one of us described a general calculation strategy called dynamic assignment by which this difficulty can be overcome [Nilges, M. (1993) Proteins, 17, 297–309]. Here we describe extensions to the method for handling many co-monomer NOEs and for taking advantege of prior knowledge of monomer structures. The new protocol was developed for the particularly difficult case of leucine zipper (LZ) homodimers, for which the previous protocol proved inefficient. In addition to the problem of dimer symmetry, LZs have a particularly high proportion of co-monomer NOE signals and a high degree of repetition in sequence and structure, leading to significant spectral overlap. Furthermore, the leucine zipper is a rather extended (as opposed to globular) protein domain; accurately determining such a structure based only on the very short distances obtainable by NMR is clearly a challenge to the NMR structure determination method. We have previously shown that, for LZ homodimers, many of the backbone-backbone NOESY cross peaks can be unambiguously assigned as intra-monomer, enabling approximate monomer structures to be calculated. Using model and experimental data sets, we verified that the new protocol converges to the correct dimer structure. The results show that short-range NMR distance data can be sufficient to define accurately the extended LZ. The protocol has been used to derive a novel solution structure of the c-Jun LZ domain. Based on these calculations, we propose the protocol as a prototype for the general case of symmetric multimers where the monomer structure is known.Abbreviations 3D three-dimensional - GCN4-c crystal structure of the GCN4 LZ homodimer - GCN4-s solution structures of GCN4 - GSYM global symmetry - Jun-m model structure of the Jun LZ homodimer - Jun-s solution structure of Jun - LZ leucine zipper - MFP mean force potential - MDSA molecular dynamical simulated annealing - NCS noncrystallographic symmetry - NOE nuclear Overhauser enhancement - rmsd root-mean-square deviation - vdW van der Waals