Restraint validation of biomolecular structures determined by NMR in the Protein Data Bank

Biomolecular structure analysis from experimental NMR studies generally relies on restraints derived from a combination of experimental and knowledge-based data. A challenge for the structural biology community has been a lack of standards for representing these restraints, preventing the establishment of uniform methods of model-vs-data structure validation against restraints and limiting interoperability between restraint-based structure modeling programs. The NEF and NMR-STAR formats provide a standardized approach for representing commonly used NMR restraints. Using these restraint formats, a standardized validation system for assessing structural models of biopolymers against restraints has been developed and implemented in the wwPDB OneDep data deposition-validation-biocuration system. The resulting wwPDB restraint violation report provides a model vs. data assessment of biomolecule structures determined using distance and dihedral restraints, with extensions to other restraint types currently being implemented. These tools are useful for assessing NMR models, as well as for assessing biomolecular structure predictions based on distance restraints.

Restraint Validation of Biomolecular Structures Determined by NMR in the Protein Data Bank

Biomolecular structure analysis from experimental NMR studies generally relies on restraints derived from a combination of experimental and knowledge-based data. A challenge for the structural biology community has been a lack of standards for representing these restraints, preventing the establishment of uniform methods of model-vs-data structure validation against restraints and limiting interoperability between restraint-based structure modeling programs. The NMR exchange (NEF) and NMR-STAR formats provide a standardized approach for representing commonly used NMR restraints. Using these restraint formats, a standardized validation system for assessing structural models of biopolymers against restraints has been developed and implemented in the wwPDB OneDep data deposition-validation-biocuration system. The resulting wwPDB Restraint Violation Report provides a model vs. data assessment of biomolecule structures determined using distance and dihedral restraints, with extensions to other restraint types currently being implemented. These tools are useful for assessing NMR models, as well as for assessing biomolecular structure predictions based on distance restraints.

Representing structures of the multiple conformational states of proteins

Biomolecules exhibit dynamic behavior that single-state models of their structures cannot fully capture. We review some recent advances for investigating multiple conformations of biomolecules, including experimental methods, molecular dynamics simulations, and machine learning. We also address the challenges associated with representing single- and multiple-state models in data archives, with a particular focus on NMR structures. Establishing standardized representations and annotations will facilitate effective communication and understanding of these complex models to the broader scientific community.

Blind assessment of monomeric AlphaFold2 protein structure models with experimental NMR data

Recent advances in molecular modeling of protein structures are changing the field of structural biology. AlphaFold-2 (AF2), an AI system developed by DeepMind, Inc., utilizes attention-based deep learning to predict models of protein structures with high accuracy relative to structures determined by X-ray crystallography and cryo-electron microscopy (cryoEM). Comparing AF2 models to structures determined using solution NMR data, both high similarities and distinct differences have been observed. Since AF2 was trained on X-ray crystal and cryoEM structures, we assessed how accurately AF2 can model small, monomeric, solution protein NMR structures which (i) were not used in the AF2 training data set, and (ii) did not have homologous structures in the Protein Data Bank at the time of AF2 training. We identified nine open-source protein NMR data sets for such "blind" targets, including chemical shift, raw NMR FID data, NOESY peak lists, and (for 1 case) 15N-1H residual dipolar coupling data. For these nine small (70-108 residues) monomeric proteins, we generated AF2 prediction models and assessed how well these models fit to these experimental NMR data, using several well-established NMR structure validation tools. In most of these cases, the AF2 models fit the NMR data nearly as well, or sometimes better than, the corresponding NMR structure models previously deposited in the Protein Data Bank. These results provide benchmark NMR data for assessing new NMR data analysis and protein structure prediction methods. They also document the potential for using AF2 as a guiding tool in protein NMR data analysis, and more generally for hypothesis generation in structural biology research.

Blind Assessment of Monomeric AlphaFold2 Protein Structure Models with Experimental NMR Data

Recent advances in molecular modeling of protein structures are changing the field of structural biology. AlphaFold-2 (AF2), an AI system developed by DeepMind, Inc., utilizes attention-based deep learning to predict models of protein structures with high accuracy relative to structures determined by X-ray crystallography and cryo-electron microscopy (cryoEM). Comparing AF2 models to structures determined using solution NMR data, both high similarities and distinct differences have been observed. Since AF2 was trained on X-ray crystal and cryoEM structures, we assessed how accurately AF2 can model small, monomeric, solution protein NMR structures which (i) were not used in the AF2 training data set, and (ii) did not have homologous structures in the Protein Data Bank at the time of AF2 training. We identified nine open source protein NMR data sets for such "blind" targets, including chemical shift, raw NMR FID data, NOESY peak lists, and (for 1 case) 15 N- 1 H residual dipolar coupling data. For these nine small (70 - 108 residues) monomeric proteins, we generated AF2 prediction models and assessed how well these models fit to these experimental NMR data, using several well-established NMR structure validation tools. In most of these cases, the AF2 models fit the NMR data nearly as well, or sometimes better than, the corresponding NMR structure models previously deposited in the Protein Data Bank. These results provide benchmark NMR data for assessing new NMR data analysis and protein structure prediction methods. They also document the potential for using AF2 as a guiding tool in protein NMR data analysis, and more generally for hypothesis generation in structural biology research.

Highlights

AF2 models assessed against NMR data for 9 monomeric proteins not used in training.AF2 models fit NMR data almost as well as the experimentally-determined structures. RPF-DP, PSVS , and PDBStat software provide structure quality and RDC assessment. RPF-DP analysis using AF2 models suggests multiple conformational states.

Accurate de novo design of membrane-traversing macrocycles

We use computational design coupled with experimental characterization to systematically investigate the design principles for macrocycle membrane permeability and oral bioavailability. We designed 184 6-12 residue macrocycles with a wide range of predicted structures containing noncanonical backbone modifications and experimentally determined structures of 35; 29 are very close to the computational models. With such control, we show that membrane permeability can be systematically achieved by ensuring all amide (NH) groups are engaged in internal hydrogen bonding interactions. 84 designs over the 6-12 residue size range cross membranes with an apparent permeability greater than 1 × 10^-6 cm/s. Designs with exposed NH groups can be made membrane permeable through the design of an alternative isoenergetic fully hydrogen-bonded state favored in the lipid membrane. The ability to robustly design membrane-permeable and orally bioavailable peptides with high structural accuracy should contribute to the next generation of designed macrocycle therapeutics.

AlphaFold Models of Small Proteins Rival the Accuracy of Solution NMR Structures

Recent advances in molecular modeling using deep learning have the potential to revolutionize the field of structural biology. In particular, AlphaFold has been observed to provide models of protein structures with accuracies rivaling medium-resolution X-ray crystal structures, and with excellent atomic coordinate matches to experimental protein NMR and cryo-electron microscopy structures. Here we assess the hypothesis that AlphaFold models of small, relatively rigid proteins have accuracies (based on comparison against experimental data) similar to experimental solution NMR structures. We selected six representative small proteins with structures determined by both NMR and X-ray crystallography, and modeled each of them using AlphaFold. Using several structure validation tools integrated under the Protein Structure Validation Software suite (PSVS), we then assessed how well these models fit to experimental NMR data, including NOESY peak lists (RPF-DP scores), comparisons between predicted rigidity and chemical shift data (ANSURR scores), and ¹⁵N-¹H residual dipolar coupling data (RDC Q factors) analyzed by software tools integrated in the PSVS suite. Remarkably, the fits to NMR data for the protein structure models predicted with AlphaFold are generally similar, or better, than for the corresponding experimental NMR or X-ray crystal structures. Similar conclusions were reached in comparing AlphaFold2 predictions and NMR structures for three targets from the Critical Assessment of Protein Structure Prediction (CASP). These results contradict the widely held misperception that AlphaFold cannot accurately model solution NMR structures. They also document the value of PSVS for model vs. data assessment of protein NMR structures, and the potential for using AlphaFold models for guiding analysis of experimental NMR data and more generally in structural biology.

Development of Polyamine-Substituted Triphenylamine Ligands with High Affinity and Selectivity for G-Quadruplex DNA

Currently, significant efforts are devoted to designing small molecules able to bind selectively to guanine quadruplexes (G4s). These noncanonical DNA structures are implicated in various important biological processes and have been identified as potential targets for drug development. Previously, a series of triphenylamine (TPA)-based compounds, including macrocyclic polyamines, that displayed high affinity towards G4 DNA were reported. Following this initial work, herein a series of second-generation compounds, in which the central TPA has been functionalised with flexible and adaptive linear polyamines, are presented with the aim of maximising the selectivity towards G4 DNA. The acid-base properties of the new derivatives have been studied by means of potentiometric titrations, UV/Vis and fluorescence emission spectroscopy. The interaction with G4s and duplex DNA has been explored by using FRET melting assays, fluorescence spectroscopy and circular dichroism. Compared with previous TPA derivatives with macrocyclic substituents, the new ligands reported herein retain the G4 affinity, but display two orders of magnitude higher selectivity for G4 versus duplex DNA; this is most likely due to the ability of the linear substituents to embrace the G4 structure.

Protein structure prediction assisted with sparse NMR data in CASP13

CASP13 has investigated the impact of sparse NMR data on the accuracy of protein structure prediction. NOESY and ¹⁵ N-¹ H residual dipolar coupling data, typical of that obtained for ¹⁵ N,¹³ C-enriched, perdeuterated proteins up to about 40 kDa, were simulated for 11 CASP13 targets ranging in size from 80 to 326 residues. For several targets, two prediction groups generated models that are more accurate than those produced using baseline methods. Real NMR data collected for a de novo designed protein were also provided to predictors, including one data set in which only backbone resonance assignments were available. Some NMR-assisted prediction groups also did very well with these data. CASP13 also assessed whether incorporation of sparse NMR data improves the accuracy of protein structure prediction relative to nonassisted regular methods. In most cases, incorporation of sparse, noisy NMR data results in models with higher accuracy. The best NMR-assisted models were also compared with the best regular predictions of any CASP13 group for the same target. For six of 13 targets, the most accurate model provided by any NMR-assisted prediction group was more accurate than the most accurate model provided by any regular prediction group; however, for the remaining seven targets, one or more regular prediction method provided a more accurate model than even the best NMR-assisted model. These results suggest a novel approach for protein structure determination, in which advanced prediction methods are first used to generate structural models, and sparse NMR data is then used to validate and/or refine these models.

Acid–base behaviour and binding to double stranded DNA/RNA of benzo[g]phthalazine-based ligands

Benzo[g]phthalazine derivatives show different binding modes and base selectivity towards canonical DNA/RNA depending on the substitution of the aromatic moiety.

Mapping molecular binding by means of conformational dynamics measurements

Protein–protein interactions are key in virtually all biological processes. The study of these interactions and the interfaces that mediate them play a key role in the understanding of biological function. In particular, the observation of protein–protein interactions in their dynamic environment is technically difficult. Here two surface analysis techniques, dual polarization interferometry and quartz crystal microbalance with dissipation monitoring, were paired for real-time mapping of the conformational dynamics of protein–protein interactions. Our approach monitors this dynamics in real time and in situ, which is a great advancement within technological platforms for drug discovery. Results agree with the experimental observations of the interaction between the TRIM21α protein and circulating autoantibodies via a bridging bipolar mechanism. This work provides a new chip-based method to monitor conformational dynamics of protein–protein interactions, which is amenable to miniaturized high-throughput determination.

Protein–protein interactions are key in virtually all biological processes.

Enhancement of SOD activity in boehmite supported nanoreceptors

Binuclear Cu²⁺ complexes of a pyridinophane polyamine ligand grafted to boehmite nanoparticles display a remarkable SOD activity enhancement.

Synthesis, Characterization, and Cu(2+) Coordination Studies of a 3-Hydroxy-4-pyridinone Aza Scorpiand Derivative

The synthesis, acid-base behavior, and Cu(2+) coordination chemistry of a new ligand (L1) consisting of an azamacrocyclic core appended with a lateral chain containing a 3-hydroxy-2-methyl-4(1H)-pyridinone group have been studied by potentiometry, cyclic voltammetry, and NMR and UV-vis spectroscopy. UV-vis and NMR studies showed that phenolate group was protonated at the highest pH values [log K = 9.72(1)]. Potentiometric studies point out the formation of Cu(2+) complexes of 1:2, 2:2, 4:3, 1:1, and 2:1 Cu(2+)/L1 stoichiometries. UV-vis analysis and electrochemical studies evidence the implication of the pyridinone moieties in the metal coordination of the 1:2 Cu(2+)/L1 complexes. L1 shows a stronger chelating ability than the reference chelating ligand deferiprone. While L1 shows no cytotoxicity in HeLa and ARPE-19 human cell lines (3.1-25.0 μg/mL), it has significant antioxidant activity, as denoted by TEAC assays at physiological pH. The addition of Cu(2+) diminishes the antioxidant activity because of its coordination to the pyridinone moiety phenolic group.

A water molecule in the interior of a 1H-pyrazole Cu2+ metallocage

A pyrazole aza-macrocyclic Cu²⁺ metallocage shows the inclusion of a water molecule not hydrogen bonded with any acceptor or donor groups of the cage.

A community resource of experimental data for NMR / X-ray crystal structure pairs

We have developed an online NMR / X-ray Structure Pair Data Repository. The NIGMS Protein Structure Initiative (PSI) has provided many valuable reagents, 3D structures, and technologies for structural biology. The Northeast Structural Genomics Consortium was one of several PSI centers. NESG used both X-ray crystallography and NMR spectroscopy for protein structure determination. A key goal of the PSI was to provide experimental structures for at least one representative of each of hundreds of targeted protein domain families. In some cases, structures for identical (or nearly identical) constructs were determined by both NMR and X-ray crystallography. NMR spectroscopy and X-ray diffraction data for 41 of these "NMR / X-ray" structure pairs determined using conventional triple-resonance NMR methods with extensive sidechain resonance assignments have been organized in an online NMR / X-ray Structure Pair Data Repository. In addition, several NMR data sets for perdeuterated, methyl-protonated protein samples are included in this repository. As an example of the utility of this repository, these data were used to revisit questions about the precision and accuracy of protein NMR structures first outlined by Levy and coworkers several years ago (Andrec et al., Proteins 2007;69:449-465). These results demonstrate that the agreement between NMR and X-ray crystal structures is improved using modern methods of protein NMR spectroscopy. The NMR / X-ray Structure Pair Data Repository will provide a valuable resource for new computational NMR methods development.

The second round of Critical Assessment of Automated Structure Determination of Proteins by NMR: CASD-NMR-2013

The second round of the community-wide initiative Critical Assessment of automated Structure Determination of Proteins by NMR (CASD-NMR-2013) comprised ten blind target datasets, consisting of unprocessed spectral data, assigned chemical shift lists and unassigned NOESY peak and RDC lists, that were made available in both curated (i.e. manually refined) or un-curated (i.e. automatically generated) form. Ten structure calculation programs, using fully automated protocols only, generated a total of 164 three-dimensional structures (entries) for the ten targets, sometimes using both curated and un-curated lists to generate multiple entries for a single target. The accuracy of the entries could be established by comparing them to the corresponding manually solved structure of each target, which was not available at the time the data were provided. Across the entire data set, 71 % of all entries submitted achieved an accuracy relative to the reference NMR structure better than 1.5 Å. Methods based on NOESY peak lists achieved even better results with up to 100% of the entries within the 1.5 Å threshold for some programs. However, some methods did not converge for some targets using un-curated NOESY peak lists. Over 90% of the entries achieved an accuracy better than the more relaxed threshold of 2.5 Å that was used in the previous CASD-NMR-2010 round. Comparisons between entries generated with un-curated versus curated peaks show only marginal improvements for the latter in those cases where both calculations converged.

Analysis of the structural quality of the CASD-NMR 2013 entries

We performed a comprehensive structure validation of both automated and manually generated structures of the 10 targets of the CASD-NMR-2013 effort. We established that automated structure determination protocols are capable of reliably producing structures of comparable accuracy and quality to those generated by a skilled researcher, at least for small, single domain proteins such as the ten targets tested. The most robust results appear to be obtained when NOESY peak lists are used either as the primary input data or to augment chemical shift data without the need to manually filter such lists. A detailed analysis of the long-range NOE restraints generated by the different programs from the same data showed a surprisingly low degree of overlap. Additionally, we found that there was no significant correlation between the extent of the NOE restraint overlap and the accuracy of the structure. This result was surprising given the importance of NOE data in producing good quality structures. We suggest that this could be explained by the information redundancy present in NOEs between atoms contained within a fixed covalent network.

Equilibrium, kinetic, and computational studies on the formation of Cu2+ and Zn2+ complexes with an indazole-containing azamacrocyclic scorpiand: evidence for metal-induced tautomerism

Cu(2+) and Zn(2+) coordination chemistry of a new member of the family of scorpiand-like macrocyclic ligands derived from tris(2-aminoethyl)amine (tren) is reported. The new ligand (L1) contains in its pendant arm not only the amine group derived from tren but also a 6-indazole ring. Potentiometric studies allow the determination of four protonation constants. UV-vis and fluorescence data support that the last protonation step occurs on the indazole group. Equilibrium measurements in the presence of Cu(2+) and Zn(2+) reveal the formation of stable [ML1](2+), [MHL1](3+), and [ML1(OH)](+) complexes. Kinetic studies on the acid-promoted decomposition of the metal complexes were carried out using both absorbance and fluorescence detection. For Zn(2+), both types of detection led to the same results. The experiments suggest that [ZnL1](2+) protonates upon addition of an acid excess to form [ZnHL1](3+) within the mixing time of the stopped-flow instrument, which then decomposes with a first-order dependence on the acid concentration. The kinetic behavior is more complex in the case of Cu(2+). Both [CuL1](2+) and [CuHL1](3+) show similar absorption spectra and convert within the mixing time to a new intermediate species with a band at 750 nm, the process being reverted by addition of base. The intermediate then decomposes with a second-order dependence on the acid concentration. However, kinetic experiments with fluorescence detection showed the existence of an additional faster step. With the help of DFT calculations, an interpretation is proposed in which protonation of [CuL1](2+) to form [CuHL1](3+) would involve dissociation of the tren-based NH group in the pendant arm and coordination of a 2H-indazole group. Further protonation would lead to dissociation of coordinated indazole, which then will convert to the more stable 1H tautomer in a process signaled by fluorescence changes that would not be affecting to the d-d spectrum of the complex.

The expanded FindCore method for identification of a core atom set for assessment of protein structure prediction

Maximizing the scientific impact of NMR-based structure determination requires robust and statistically sound methods for assessing the precision of NMR-derived structures. In particular, a method to define a core atom set for calculating superimpositions and validating structure predictions is critical to the use of NMR-derived structures as targets in the CASP competition. FindCore (Snyder and Montelione, Proteins 2005;59:673-686) is a superimposition independent method for identifying a core atom set and partitioning that set into domains. However, as FindCore optimizes superimposition by sensitively excluding not-well-defined atoms, the FindCore core may not comprise all atoms suitable for use in certain applications of NMR structures, including the CASP assessment process. Adapting the FindCore approach to assess predicted models against experimental NMR structures in CASP10 required modification of the FindCore method. This paper describes conventions and a standard protocol to calculate an "Expanded FindCore" atom set suitable for validation and application in biological and biophysical contexts. A key application of the Expanded FindCore method is to identify a core set of atoms in the experimental NMR structure for which it makes sense to validate predicted protein structure models. We demonstrate the application of this Expanded FindCore method in characterizing well-defined regions of 18 NMR-derived CASP10 target structures. The Expanded FindCore protocol defines "expanded core atom sets" that match an expert's intuition of which parts of the structure are sufficiently well defined to use in assessing CASP model predictions. We also illustrate the impact of this analysis on the CASP GDT assessment scores.

Protein NMR structures refined with Rosetta have higher accuracy relative to corresponding X-ray crystal structures

We have found that refinement of protein NMR structures using Rosetta with experimental NMR restraints yields more accurate protein NMR structures than those that have been deposited in the PDB using standard refinement protocols. Using 40 pairs of NMR and X-ray crystal structures determined by the Northeast Structural Genomics Consortium, for proteins ranging in size from 5-22 kDa, restrained Rosetta refined structures fit better to the raw experimental data, are in better agreement with their X-ray counterparts, and have better phasing power compared to conventionally determined NMR structures. For 37 proteins for which NMR ensembles were available and which had similar structures in solution and in the crystal, all of the restrained Rosetta refined NMR structures were sufficiently accurate to be used for solving the corresponding X-ray crystal structures by molecular replacement. The protocol for restrained refinement of protein NMR structures was also compared with restrained CS-Rosetta calculations. For proteins smaller than 10 kDa, restrained CS-Rosetta, starting from extended conformations, provides slightly more accurate structures, while for proteins in the size range of 10-25 kDa the less CPU intensive restrained Rosetta refinement protocols provided equally or more accurate structures. The restrained Rosetta protocols described here can improve the accuracy of protein NMR structures and should find broad and general for studies of protein structure and function.

Synthetic single and double aza-scorpiand macrocycles acting as inhibitors of the antioxidant enzymes iron superoxide dismutase and trypanothione reductase in Trypanosoma cruzi with promising results in a murine model

Synthetic scorpiand-like azamacrocycles selectively inhibit SOD and TR enzymes of Trypanosoma cruzi in mice causing death of the parasites and increasing the mouse survival rate after infection and treatment.

Quality assessment of protein NMR structures

Biomolecular NMR structures are now routinely used in biology, chemistry, and bioinformatics. Methods and metrics for assessing the accuracy and precision of protein NMR structures are beginning to be standardized across the biological NMR community. These include both knowledge-based assessment metrics, parameterized from the database of protein structures, and model versus data assessment metrics. On line servers are available that provide comprehensive protein structure quality assessment reports, and efforts are in progress by the world-wide Protein Data Bank (wwPDB) to develop a biomolecular NMR structure quality assessment pipeline as part of the structure deposition process. These quality assessment metrics and standards will aid NMR spectroscopists in determining more accurate structures, and increase the value and utility of these structures for the broad scientific community.

PDBStat: a universal restraint converter and restraint analysis software package for protein NMR

The heterogeneous array of software tools used in the process of protein NMR structure determination presents organizational challenges in the structure determination and validation processes, and creates a learning curve that limits the broader use of protein NMR in biology. These challenges, including accurate use of data in different data formats required by software carrying out similar tasks, continue to confound the efforts of novices and experts alike. These important issues need to be addressed robustly in order to standardize protein NMR structure determination and validation. PDBStat is a C/C++ computer program originally developed as a universal coordinate and protein NMR restraint converter. Its primary function is to provide a user-friendly tool for interconverting between protein coordinate and protein NMR restraint data formats. It also provides an integrated set of computational methods for protein NMR restraint analysis and structure quality assessment, relabeling of prochiral atoms with correct IUPAC names, as well as multiple methods for analysis of the consistency of atomic positions indicated by their convergence across a protein NMR ensemble. In this paper we provide a detailed description of the PDBStat software, and highlight some of its valuable computational capabilities. As an example, we demonstrate the use of the PDBStat restraint converter for restrained CS-Rosetta structure generation calculations, and compare the resulting protein NMR structure models with those generated from the same NMR restraint data using more traditional structure determination methods. These results demonstrate the value of a universal restraint converter in allowing the use of multiple structure generation methods with the same restraint data for consensus analysis of protein NMR structures and the underlying restraint data.

[Evaluation of the variability in the susceptibility of Acinetobacter baumannii to tigecycline in the same medium with two methods of quantitative diffusion different commercial]

INTRODUCTION

Tigecycline may be a therapeutic alternative for the control of multidrug-resistant Acinetobacter baumannii, although there is no consensus on the cutoffs or susceptibility to the variability of the minimum inhibitory concentration (MIC) according to the culture medium and strips for the antibiogram against this microorganism by quantitative diffusion method. Therefore, the objective was to verify this variability and propose epsilometer test strip that more closely resemble to the standard method.

MATERIAL AND METHODS

38 strains of A. baumannii were selected and evaluated their susceptibility to tigecycline with two different commercial strips (E-TEST and Liofilchem). MICs were compared with those obtained by the standard technique of microdilution broth.

RESULTS

MICs obtained by the Liofilchem strip were more similar to standard method than those obtained by E-TEST strips.

CONCLUSION

In the two studied strips, higher MICs to those obtained by the standard method were observed leading to false-positive tigecicline resistance in many cases. However, the Liofilchem strip showed the results more closely resemble to the standard method.

Tritopic phenanthroline and pyridine tail-tied aza-scorpiands

The synthesis of two new tritopic double-scorpiand receptors in which two equivalent 5-(2-aminoethyl)-2,5,8-triaza[9]-(2,6)-pyridinophane moieties have been linked with 2,6-dimethylpyridine (L1) or 2,9-dimethylphenanthroline (L2) units is reported for the first time. Their acid-base behaviour and Zn(2+) coordination chemistry have been studied by pH-metric titrations, molecular dynamic calculations, NMR, UV-Vis and steady-state fluorescence techniques. L1 and L2 behave, respectively, as hexaprotic and heptaprotic bases in the experimental conditions used (298.1 +/- 0.1 K, 0.15 mol dm(-3) NaCl, pH range under study 2.0-11.0). These ligands are able to form mono-, bi- and trinuclear Zn(2+) complexes depending on the Zn(2+)-receptor molar ratio. Interaction of L1 and L2 with pyrophosphate (PPi), tripolyphosphate (TPP) and adenosine 5'-triphosphate (ATP) has been followed by pH-metric titrations, (1)H and (31)P NMR techniques and molecular dynamic analysis. Finally, formation of mixed complexes Zn(2+)-L-PPi, Zn(2+)-L-TPP and Zn(2+)-L-ATP has been studied for both receptors by potentiometric titrations.

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

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

Assessing model accuracy using the homology modeling automatically software

Homology modeling is a powerful technique that greatly increases the value of experimental structure determination by using the structural information of one protein to predict the structures of homologous proteins. We have previously described a method of homology modeling by satisfaction of spatial restraints (Li et al., Protein Sci 1997;6:956-970). The Homology Modeling Automatically (HOMA) web site, <http://www-nmr.cabm.rutgers.edu/HOMA>, is a new tool, using this method to predict 3D structure of a target protein based on the sequence alignment of the target protein to a template protein and the structure coordinates of the template. The user is presented with the resulting models, together with an extensive structure validation report providing critical assessments of the quality of the resulting homology models. The homology modeling method employed by HOMA was assessed and validated using twenty-four groups of homologous proteins. Using HOMA, homology models were generated for 510 proteins, including 264 proteins modeled with correct folds and 246 modeled with incorrect folds. Accuracies of these models were assessed by superimposition on the corresponding experimentally determined structures. A subset of these results was compared with parallel studies of modeling accuracy using several other automated homology modeling approaches. Overall, HOMA provides prediction accuracies similar to other state-of-the-art homology modeling methods. We also provide an evaluation of several structure quality validation tools in assessing the accuracy of homology models generated with HOMA. This study demonstrates that Verify3D (Luthy et al., Nature 1992;356:83-85) and ProsaII (Sippl, Proteins 1993;17:355-362) are most sensitive in distinguishing between homology models with correct or incorrect folds. For homology models that have the correct fold, the steric conformational energy (including primarily the Van der Waals energy), MolProbity clashscore (Word et al., Protein Sci 2000;9:2251-2259), and the PROCHECK G-factors (Laskowski et al., J Biomol NMR 1996;8:477-486) provide sensitive and consistent methods for assessing accuracy and can distinguish between homology models of higher and lower accuracy. As demonstrated in the accompanying paper (Bhattacharya et al., accompanying paper), combinations of these scores for models generated with HOMA provide a basis for distinguishing low from high accuracy models.

Evaluating protein structures determined by structural genomics consortia

Structural genomics projects are providing large quantities of new 3D structural data for proteins. To monitor the quality of these data, we have developed the protein structure validation software suite (PSVS), for assessment of protein structures generated by NMR or X-ray crystallographic methods. PSVS is broadly applicable for structure quality assessment in structural biology projects. The software integrates under a single interface analyses from several widely-used structure quality evaluation tools, including PROCHECK (Laskowski et al., J Appl Crystallog 1993;26:283-291), MolProbity (Lovell et al., Proteins 2003;50:437-450), Verify3D (Luthy et al., Nature 1992;356:83-85), ProsaII (Sippl, Proteins 1993;17: 355-362), the PDB validation software, and various structure-validation tools developed in our own laboratory. PSVS provides standard constraint analyses, statistics on goodness-of-fit between structures and experimental data, and knowledge-based structure quality scores in standardized format suitable for database integration. The analysis provides both global and site-specific measures of protein structure quality. Global quality measures are reported as Z scores, based on calibration with a set of high-resolution X-ray crystal structures. PSVS is particularly useful in assessing protein structures determined by NMR methods, but is also valuable for assessing X-ray crystal structures or homology models. Using these tools, we assessed protein structures generated by the Northeast Structural Genomics Consortium and other international structural genomics projects, over a 5-year period. Protein structures produced from structural genomics projects exhibit quality score distributions similar to those of structures produced in traditional structural biology projects during the same time period. However, while some NMR structures have structure quality scores similar to those seen in higher-resolution X-ray crystal structures, the majority of NMR structures have lower scores. Potential reasons for this "structure quality score gap" between NMR and X-ray crystal structures are discussed.

A topology-constrained distance network algorithm for protein structure determination from NOESY data

This article formulates the multidimensional nuclear Overhauser effect spectroscopy (NOESY) interpretation problem using graph theory and presents a novel, bottom-up, topology-constrained distance network analysis algorithm for NOESY cross peak interpretation using assigned resonances. AutoStructure is a software suite that implements this topology-constrained distance network analysis algorithm and iteratively generates structures using the three-dimensional (3D) protein structure calculation programs XPLOR/CNS or DYANA. The minimum input for AutoStructure includes the amino acid sequence, a list of resonance assignments, and lists of 2D, 3D, and/or 4D-NOESY cross peaks. AutoStructure can also analyze homodimeric proteins when X-filtered NOESY experiments are available. The quality of input data and final 3D structures is evaluated using recall, precision, and F-measure (RPF) scores, a statistical measure of goodness of fit with the input data. AutoStructure has been tested on three protein NMR data sets for which high-quality structures have previously been solved by an expert, and yields comparable high-quality distance constraint lists and 3D protein structures in hours. We also compare several protein structures determined using AutoStructure with corresponding homologous proteins determined with other independent methods. The program has been used in more than two dozen protein structure determinations, several of which have already been published.

Specific interaction of citrate with bis(fluorophoric) bibrachial lariat aza-crown in comparison with the other components of the Krebs cycle

Among the Krebs cycle components, just citrate enhances the fluorescence of a new bi(brachial) lariat aza-crown containing appended naphthalene fluorophores.

An integrated platform for automated analysis of protein NMR structures

Recent developments provide automated analysis of NMR assignments and three-dimensional (3D) structures of proteins. These approaches are generally applicable to proteins ranging from about 50 to 150 amino acids. In this chapter, we summarize progress by the Northeast Structural Genomics Consortium in standardizing the NMR data collection process for protein structure determination and in building an integrated platform for automated protein NMR structure analysis. Our integrated platform includes the following principal steps: (1) standardized NMR data collection, (2) standardized data processing (including spectral referencing and Fourier transformation), (3) automated peak picking and peak list editing, (4) automated analysis of resonance assignments, (5) automated analysis of NOESY data together with 3D structure determination, and (6) methods for protein structure validation. In particular, the software AutoStructure for automated NOESY data analysis is described in this chapter, together with a discussion of practical considerations for its use in high-throughput structure production efforts. The critical area of data quality assessment has evolved significantly over the past few years and involves evaluation of both intermediate and final peak lists, resonance assignments, and structural information derived from the NMR data. Methods for quality control of each of the major automated analysis steps in our platform are also discussed. Despite significant remaining challenges, when good quality data are available, automated analysis of protein NMR assignments and structures with this platform is both fast and reliable.

[Methicillin resistant Staphylococcus aureus from clinical samples in Cordoba (Spain)]

Increases in methicillin-resistant Staphylococcus aureus (MRSA) strains and in isolates with reduced susceptibility to glucopeptides have become an important problem in the epidemiology of Gram-positive microorganisms. All the consecutive S. aureus collected in our hospital from 1995 to 2001 were studied. Of the 4531 isolates 24.23% were methicillin resistant in this period. The highest number of methicillin-resistant strains were found in wound exudates. In recent years an almost 20% increase in MRSA has occurred in our hospital. As MRSA strains are an important problem in our area and their prevalence is on the rise, as is multiresistance, the monitoring and control of MRSA strains in our hospitals is necessary.

Solution NMR structure of aD,L-alternating oligonorleucine as a model of ?-helix

beta-Helix structures are of particular interest due to their capacity to form transmembrane channels with different transport properties. However, the relatively large number of beta-helices configurations does not allow a direct conformational analysis of beta-helical oligopeptides. A synthetic alternating D,L-oligopeptide with twelve norleucines (XIIMe) has been used as a model to get insight in the conformational features of beta-helix structures. The spatial configuration of XIIMe in solution has been determined by NMR. An extensive set of distances (nuclear Overhauser effect) and dihedral (J coupling constants) constraints have been included in molecular dynamics calculations. The NMR experimental data and theoretical calculations clearly indicate that the XIIMe adopts a single beta(4.4)-helix-type conformation in nonpolar solvents.

Novel, potent calmodulin antagonists derived from an all-D hexapeptide combinatorial library that inhibit in vivo cell proliferation: activity and structural characterization

Calmodulin is known to bind to various amphipathic helical peptide sequences, and the calmodulin-peptide binding surface has been shown to be remarkably tolerant sterically. D-Amino acid peptides, therefore, represent potential nonhydrolysable intracellular antagonists of calmodulin. In the present study, synthetic combinatorial libraries have been used to develop novel D-amino acid hexapeptide antagonists to calmodulin-regulated phosphodiesterase activity. Five hexapeptides were identified from a library containing over 52 million sequences. These peptides inhibited cell proliferation both in cell culture using normal rat kidney cells and by injection via the femoral vein following partial hepatectomy of rat liver cells. These hexapeptides showed no toxic effect on the cells. Despite their short length, the identified hexapeptides appear to adopt a partial helical conformation similar to other known calmodulin-binding peptides, as shown by CD spectroscopy in the presence of calmodulin and NMR spectroscopy in DMSO. The present peptides are the shortest peptide calmodulin antagonists reported to date showing potential in vivo activity.

HYPER: a hierarchical algorithm for automatic determination of protein dihedral-angle constraints and stereospecific C beta H2 resonance assignments from NMR data

A new computer program, HYPER, has been developed for automated analysis of protein dihedral angle values and C beta H2 stereospecific assignments from NMR data. HYPER uses a hierarchical grid-search algorithm to determine allowed values of phi, psi, and chi 1 dihedral angles and C beta H2 stereospecific assignments based on a set of NMR-derived distance and/or scalar-coupling constraints. Dihedral-angle constraints are valuable for restricting conformational space and improving convergence in three-dimensional structure calculations. HYPER computes the set of phi, psi, and chi 1 dihedral angles and C beta H2 stereospecific assignments that are consistent with up to nine intraresidue and sequential distance bounds, two pairs of relative distance bounds, thirteen homo- and heteronuclear scalar coupling bounds, and two pairs of relative scalar coupling constant bounds. The program is designed to be very flexible, and provides for simple user modification of Karplus equations and standard polypeptide geometries, allowing it to accommodate recent and future improved calibrations of Karplus curves. The C code has been optimized to execute rapidly (0.3-1.5 CPU-sec residue-1 using a 5 degrees grid) on Silicon Graphics R8000, R10000 and Intel Pentium CPUs, making it useful for interactive evaluation of inconsistent experimental constraints. The HYPER program has been tested for internal consistency and reliability using both simulated and real protein NMR data sets.

Homology modeling of an RNP domain from a human RNA-binding protein: Homology-constrained energy optimization provides a criterion for distinguishing potential sequence alignments

We have recently described an automated approach for homology modeling using restrained molecular dynamics and simulated annealing procedures (Li et al, Protein Sci., 6:956-970,1997). We have employed this approach for constructing a homology model of the putative RNA-binding domain of the human RNA-binding protein with multiple splice sites (RBP-MS). The regions of RBP-MS which are homologous to the template protein snRNP U1A were constrained by "homology distance constraints," while the conformation of the non-homologous regions were defined only by a potential energy function. A full energy function without explicit solvent was employed to ensure that the calculated structures have good conformational energies and are physically reasonable. The effects of mis-alignment of the unknown and the template sequences were also explored in order to determine the feasibility of this homology modeling method for distinguishing possible sequence alignments based on considerations of the resulting conformational energies of modeled structures. Differences in the alignments of the unknown and the template sequences result in significant differences in the conformational energies of the calculated homology models. These results suggest that conformational energies and residual constraint violations in these homology-constrained simulated annealing calculations can be used as criteria to distinguish between correct and incorrect sequence alignments and chain folds.

Solution NMR structure and backbone dynamics of the major cold-shock protein (CspA) from Escherichia coli: evidence for conformational dynamics in the single-stranded RNA-binding site

The major cold-shock protein (CspA) from Escherichia coli is a single-stranded nucleic acid-binding protein that is produced in response to cold stress. We have previously reported its overall chain fold as determined by NMR spectroscopy [Newkirk, K., Feng, W., Jiang, W., Tejero, R., Emerson, S. D., Inouye, M., and Montelione, G. T. (1994) Proc. Natl. Acad. Sci. U.S.A. 91, 5114-5118]. Here we describe the complete analysis of 1H, 13C, and 15N resonance assignments for CspA, together with a refined solution NMR structure based on 699 conformational constraints and an analysis of backbone dynamics based on 15N relaxation rate measurements. An extensive set of triple-resonance NMR experiments for obtaining the backbone and side chain resonance assignments were carried out on uniformly 13C- and 15N-enriched CspA. Using a subset of these triple-resonance experiments, the computer program AUTOASSIGN provided automatic analysis of sequence-specific backbone N, Calpha, C', HN, Halpha, and side chain Cbeta resonance assignments. The remaining 1H, 13C, and 15N resonance assignments for CspA were then obtained by manual analysis of additional NMR spectra. Dihedral angle constraints and stereospecific methylene Hbeta resonance assignments were determined using a new conformational grid search program, HYPER, and used together with longer-range constraints as input for three-dimensional structure calculations. The resulting solution NMR structure of CspA is a well-defined five-stranded beta-barrel with surface-exposed aromatic groups that form a single-stranded nucleic acid-binding site. Backbone dynamics of CspA have also been characterized by 15N T1, T2, and heteronuclear 15N-1H NOE measurements and analyzed using the extended Lipari-Szabo formalism. These dynamic measurements indicate a molecular rotational correlation time taum of 4.88 +/- 0.04 ns and provide evidence for fast time scale (taue < 500 ps) dynamics in surface loops and motions on the microsecond to millisecond time scale within the proposed nucleic acid-binding epitope.

A novel RNA-binding motif in influenza A virus non-structural protein 1

The solution NMR structure of the RNA-binding domain from influenza virus non-structural protein 1 exhibits a novel dimeric six-helical protein fold. Distributions of basic residues and conserved salt bridges of dimeric NS1(1-73) suggest that the face containing antiparallel helices 2 and 2' forms a novel arginine-rich nucleic acid binding motif.