Characterizing challenging microcrystalline solids with solid-state NMR shift tensor and synchrotron X-ray powder diffraction data: structural analysis of ambuic acid

Synchrotron X-ray powder diffraction and solid-state (13)C NMR shift tensor data are combined to provide a unique path to structure in microcrystalline organic solids. Analysis is demonstrated on ambuic acid powder, a widely occurring natural product, to provide the complete crystal structure. The NMR data verify phase purity, specify one molecule per asymmetric unit, and provide an initial structural model including relative stereochemistry and molecular conformation. A refinement of X-ray data from the initial model establishes that ambuic acid crystallizes in the P2(1) space group with unit cell parameters a = 15.5047(7), b = 4.3904(2), and c = 14.1933(4) A and beta = 110.3134(3) degrees . This combined analysis yields structural improvements at two dihedral angles over prior NMR predictions with differences of 103 degrees and 37 degrees found. Only minor differences of +/-5.5 degrees , on average, are observed at all remaining dihedral angles. Predicted hydroxyl hydrogen-bonding orientations also fit NMR predictions within +/-6.9 degrees . This refinement corrects chemical shift assignments at two carbons and reduces the NMR error by approximately 16%. This work demonstrates that the combination of long-range order information from synchrotron powder diffraction data together with the accurate shorter range structure given by solid-state NMR measurements is a powerful tool for studying challenging organic solids.     

24 IPR isomers of fullerene C84: Cage deformation as geometrical characteristic of local strains

The structures of 24 IPR‐isomers of C₈₄ fullerene with distributed single, double and delocalized bonds are presented. Obtained results are fully supported by DFT quantum‐chemical calculations of electronic and geometrical structures of these isomers. Two reasons of instability of fullerene molecules are their radical origin and/or high local strain. Distortion of pentagons as well as hexagons with alternating single and double bonds is the most significant geometrical parameter reflecting local strain of a molecule. These distortions are measured as maximal dihedral angles of those cycles and reach 20 degrees in mostly deformed hexagons and pentagons. In contrast high values of dihedral angles in hexagons with delocalized π‐bonds are typical for stable isomers. Other geometric parameters such as valence angles, sums of valence angles and dihedral angles between approximate planes of fused rings have no marked influence on stability. The development of strain‐related criteria for fullerene stability will be helpful in the prediction which isomers might potentially be observable in experiment. © 2011 Wiley Periodicals, Inc. Int J Quantum Chem, 2012     

Correlation between the magnetic g tensors and the local cysteine geometries for a series of reduced [2Fe-2S*] protein clusters. A quantum chemical density functional theory and structural analysis

We relied on the density functional theory (DFT) to study the electronic structure of the [2Fe-2S*](SH)4 model of the active site of 2Fe ferredoxins and other proteins containing reduced [2Fe-2S*] clusters. The two (Fe(3+)-Fe(2+)-S-H) dihedral angles Omega1 and Omega2 defined for the two ligands on the ferrous side were allowed to vary, while the two other (Fe(2+)-Fe(3+)-S-H) angles Omega3 and Omega4 on the ferric side were kept constant. The Landé (g), magnetic hyperfine, and quadrupole tensors for two geometries, C2 (Omega1 = Omega2) and Cs (Omega1 = -Omega2), were calculated. To apply our model to the actual proteins, we listed all of the crystallographic structures available for the [2Fe-2S*] systems. A classification of these proteins, based on the four dihedral angles [Omega(i)](i=1-4), separates them into three main classes. The main structural feature of the first class (Omega1 approximately Omega2), with an average dihedral angle Omega(av) = (Omega1 + Omega2)/2 comprised between 115 degrees and 150 degrees, corresponds to a local ferrous C2 geometry (rather than C2nu, as previously assumed by Bertrand and Gayda: Biochim. Biophys. Acta 1979, 579, 107). We then established a direct correlation between the three principal g values and Omega(av). It is the first time that such a link has been made between the spectroscopic and structural parameters, a link, moreover, fully rationalized by our DFT calculations. We finally point out the basic differences between our C2 results with those of the C2nu phenomenological model proposed in the late 1970s by Bertrand and Gayda.     

Realistic sampling of amino acid geometries for a multipolar polarizable force field

The Quantum Chemical Topological Force Field (QCTFF) uses the machine learning method kriging to map atomic multipole moments to the coordinates of all atoms in the molecular system. It is important that kriging operates on relevant and realistic training sets of molecular geometries. Therefore, we sampled single amino acid geometries directly from protein crystal structures stored in the Protein Databank (PDB). This sampling enhances the conformational realism (in terms of dihedral angles) of the training geometries. However, these geometries can be fraught with inaccurate bond lengths and valence angles due to artefacts of the refinement process of the X‐ray diffraction patterns, combined with experimentally invisible hydrogen atoms. This is why we developed a hybrid PDB/nonstationary normal modes (NM) sampling approach called PDB/NM. This method is superior over standard NM sampling, which captures only geometries optimized from the stationary points of single amino acids in the gas phase. Indeed, PDB/NM combines the sampling of relevant dihedral angles with chemically correct local geometries. Geometries sampled using PDB/NM were used to build kriging models for alanine and lysine, and their prediction accuracy was compared to models built from geometries sampled from three other sampling approaches. Bond length variation, as opposed to variation in dihedral angles, puts pressure on prediction accuracy, potentially lowering it. Hence, the larger coverage of dihedral angles of the PDB/NM method does not deteriorate the predictive accuracy of kriging models, compared to the NM sampling around local energetic minima used so far in the development of QCTFF. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.     

PreSSAPro: a software for the prediction of secondary structure by amino acid properties

PreSSAPro is a software, available to the scientific community as a free web service designed to provide predictions of secondary structures starting from the amino acid sequence of a given protein. Predictions are based on our recently published work on the amino acid propensities for secondary structures in either large but not homogeneous protein data sets, as well as in smaller but homogeneous data sets corresponding to protein structural classes, i.e. all-alpha, all-beta, or alpha–beta proteins. Predictions result improved by the use of propensities evaluated for the right protein class. PreSSAPro predicts the secondary structure according to the right protein class, if known, or gives a multiple prediction with reference to the different structural classes. The comparison of these predictions represents a novel tool to evaluate what sequence regions can assume different secondary structures depending on the structural class assignment, in the perspective of identifying proteins able to fold in different conformations. The service is available at the URL http://bioinformatica.isa.cnr.it/PRESSAPRO/.     

Importance of RNA secondary structure information for yeast donor and acceptor splice site predictions by neural networks

Previously, Patterson et al. showed that mRNA structure information aids splice site prediction in human genes [Patterson, D.J., Yasuhara, K., Ruzzo, W.L., 2002. Pre-mRNA secondary structure prediction aids splice site prediction. Pac. Symp. Biocomput. 7, 223-234]. Here, we have attempted to predict splice sites in selected genes of Saccharomyces cerevisiae using the information obtained from the secondary structures of corresponding mRNAs. From Ares database, 154 genes were selected and their structures were predicted by Mfold. We selected a 20-nucleotide window around each site, each containing 4 nucleotides in the exon region. Based on whether the nucleotide is in a stem or not, the conventional four-letter nucleotide alphabet was translated into an eight-letter alphabet. Two different three-layer-based perceptron neural networks were devised to predict the 5' and 3' splice sites. In case of 5' site determination, a network with 3 neurons at the hidden layer was chosen, while in case of 3' site 20 neurons acted more efficiently. Both neural nets were trained applying Levenberg-Marquardt backpropagation method, using half of the available genes as training inputs and the other half for testing and cross-validations. Sequences with GUs and AGs non-sites were used as negative controls. The correlation coefficients in the predictions of 5' and 3' splice sites using eight-letter alphabet were 98.0% and 69.6%, respectively, while these values were 89.3% and 57.1% when four-letter alphabet is applied. Our results suggest that considering the secondary structure of mRNA molecules positively affects both donor and acceptor site predictions by increasing the capacity of neural networks in learning the patterns.     

Determining dihedral angles and local structure in silk peptide by 13C-2H REDOR

13C-2H REDOR NMR experiments were performed on 30-residue (AlaGly)15 silk I mimics of Bombyx mori silk fibroin to gain structural details about the elusive structure of the silk I conformation. 13C,2H-labeling strategies are illustrated for measuring individual dihedral angles in peptides and for determining local structure by REDOR. A major turn of type II character is found in the region Gly(14)-Ala(17).     

A versatile method for systematic conformational searches: application to CheY

A novel molecular structure prediction method, the Z Method, is described. It provides a versatile platform for the development and use of systematic, grid‐based conformational search protocols, in which statistical information (i.e., rotamers) can also be included. The Z Method generates trial structures by applying many changes of the same type to a single starting structure, thereby sampling the conformation space in an unbiased way. The method, implemented in the CHARMM program as the Z Module, is applied here to an illustrative model problem in which rigid, systematic searches are performed in a 36‐dimensional conformational space that describes the relative positions of the 10 secondary structural elements of the protein CheY. A polar hydrogen representation with an implicit solvation term (EEF1) is used to evaluate successively larger fragments of the protein generated in a hierarchical build‐up procedure. After a final refinement stage, and a total computational time of about two‐and‐a‐half CPU days on AMD Opteron processors, the prediction is within 1.56 Å of the native structure. The errors in the predicted backbone dihedral angles are found to approximately cancel. Monte Carlo and simulated annealing trials on the same or smaller versions of the problem, using the same atomic model and energy terms, are shown to result in less accurate predictions. Although the problem solved here is a limited one, the findings illustrate the utility of systematic searches with atom‐based models for macromolecular structure prediction and the importance of unbiased sampling in structure prediction methods. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011     

Genetic engineering combined with deep UV resonance Raman spectroscopy for structural characterization of amyloid-like fibrils

Elucidating the structure of the cross-beta core in large amyloid fibrils is a challenging problem in modern structural biology. For the first time, a set of de novo polypeptides was genetically engineered to form amyloid-like fibrils with similar morphology and yet different strand length. Differential ultraviolet Raman spectroscopy allowed for separation of the spectroscopic signatures of the highly ordered beta-sheet strands and turns of the fibril core. The relationship between Raman frequencies and Ramachandran dihedral angles of the polypeptide backbone indicates the nature of the beta-sheet and turn structural elements.     

Protein Folding with a Reduced Model and Inaccurate Short‐Range Restraints

Summary: A reduced high‐coordination lattice protein model and the Replica Exchange Monte Carlo sampling were employed in de novo folding simulations of a set of representative small proteins. Three distinct situations were analyzed. In the first series of simulations, the folding was controlled purely by the generic force field of the model. In the second, a bias was introduced towards the theoretically predicted secondary structure. Finally, we superimposed soft restraints towards the native‐like local conformation of the backbone. The short‐range restraints used in these simulations are based on approximate values of ϕ and ψ dihedral angles, which may simulate restraints derived from inaccurate experimental measurements. Incorporating such data into the reduced model required developing a procedure, which transforms the ϕ and ψ coordinates into coordinates of the protein alpha carbon trace. It has been shown that such limited data are sufficient for de novo determination of three‐dimensional structures of small and topologically not too complex proteins.

Protein folding based on secondary structure prediction and simulated torsion angles data.     

Toward direct determination of conformations of protein building units from multidimensional NMR experiments VI: chemical shift analysis of his to gain 3D structure and protonation state information

NMR--chemical shift structure correlations were investigated by using GIAO-RB3LYP/6-311++G(2d,2p) formalism. Geometries and chemical shifts (CSI values) of 103 different conformers of N'-formyl-L-histidinamide were determined including both neutral and charged protonation forms. Correlations between amino acid torsional angle values and chemical shifts were investigated for the first time for an aromatic and polar amino acid residue whose side chain may carry different charges. Linear correlation coefficients of a significant level were determined between chemical shifts and dihedral angles for CSI[(1)H(alpha)]/phi, CSI[(13)C(alpha)]/phi, and CSI[(13)C(alpha)]/psi. Protonation of the imidazole ring induces the upfield shift of CSI[(13)C(alpha)] for positively charged histidines and an opposite effect for the negative residue. We investigated the correspondence of theoretical and experimental (13)C(alpha), (13)C(beta), and (1)H(alpha) chemical shifts and the nine basic conformational building units characteristic for proteins. These three chemical shift values allow the identification of conformational building units at 80% accuracy. These results enable the prediction of additional regular secondary structural elements (e.g., polyProlineII, inverse gamma-turns) and loops beyond the assignment of chemical shifts to alpha-helices and beta-pleated sheets. Moreover, the location of the His residue can be further specified in a beta-sheet. It is possible to determine whether the appropriate residue is located at the middle or in a first/last beta-strand within a beta-sheet based on calculated CSI values. Thus, the attractive idea of establishing local residue specific backbone folding parameters in peptides and proteins by employing chemical shift information (e.g., (1)H(alpha) and (13)C(alpha)) obtained from selected heteronuclear correlation NMR experiments (e.g., 2D-HSQC) is reinforced.     

A theoretical study of conformational properties of N-methyl azapeptide derivatives

The conformational properties of azapeptide derivatives, Ac-azaGly-NHMe (1), Ac-azaAla-NHMe (2), Ac-NMe-azaGly-NHMe (3), Ac-NMe-azaAla-NHMe (4), Ac-azaGly-NMe(2) (5), Ac-azaAla-NMe(2) (6), Ac-NMe-azaGly-NMe(2) (7), and Ac-NMe-azaAla-NMe(2) (8), were systematically examined by using ab initio MO and DFT methods. Structural perturbations in azapeptides resulting from cyclic substitution of a methyl group at three N-positions of an azaamino acid were studied on the basis of the structure of the simplest model azapeptide, 1. Potential energy surfaces were generated at the HF/6-31G level for 1-4 and at the HF/6-31G//HF/3-21G level for 5-8 by rotating two key dihedral angles (phi, psi) in increments of 30 degrees. The backbone (phi, psi) angles of the minima for 1-4 are observed at the i + 2 position to form the betaI(I')-, betaII(II')-, betaVI-turns or the polyproline II structure according to the orientation of the acetyl group and the positions of the N-methyl groups. Compounds 5-8 coupled to a secondary amine were found to preferentially adopt polyproline II, betaI(III)-turn, or alpha-helical structure or even extended conformations depending on the orientation of the acetyl group and the positions of the N-methyl groups. Furthermore, N-methyl groups, depending on their positions, were found to affect the orientation of the amide group in the lowest energy conformations, the pyramidality of the N2 atom, and the bond length in azapeptide derivatives. These unique theoretical conformations of N-methyl azapeptide derivatives could be utilized in the definite design of secondary structure for peptides and proteins, and in the development of new drugs and molecular machines.     

From secondary structure to three-dimensional structure: Improved dihedral angle probability distribution function for use with energy searches for native structures of polypeptides and proteins

An improved scheme to help in the prediction of protein structure is presented. This procedure generates improved starting conformations of a protein suitable for energy minimization. Trivariate gaussian distribution functions for the π, ψ, and χ¹ dihedral angles have been derived, using conformational data from high resolution protein structures selected from the Protein Data Bank (PDB). These trivariate probability functions generate initial values for the π, ψ, and χ¹ dihedral angles which reflect the experimental values found in the PDB. These starting structures speed the search of the conformational space by focusing the search mainly in the regions of native proteins. The efficiency of the new trivariate probability distributions is demonstrated by comparing the results for the α-class polypeptide fragment, the mutant Antennapedia (C39 → S) homeodomain (2HOA), with those from two reference probability functions. The first reference probability function is a uniform or flat probability function and the second is a bivariate probability function for π and ψ. The trivariate gaussian probability functions are shown to search the conformational space more efficiently than the other two probability functions. The trivariate gaussian probability functions are also tested on the binding domain of Streptococcal protein G (2GB1), an α/β class protein. Since presently available energy functions are not accurate enough to identify the most native-like energy-minimized structures, three selection criteria were used to identify a native-like structure with a 1.90-Å rmsd from the NMR structure as the best structure for the Antennapedia fragment. Each individual selection criterion (ECEPP/3 energy, ECEPP/3 energy-plus-free energy of hydration, or a knowledge-based mean field method) was unable to identify a native-like structure, but simultaneous application of more than one selection criterion resulted in a successful identification of a native-like structure for the Antennapedia fragment. In addition to these tests, structure predictions are made for the Antennapedia polypeptide, using a Pattern Recognition-based Importance-Sampling Minimization (PRISM) procedure to predict the backbone conformational state of the mutant Antennapedia homeodomain. The ten most probable backbone conformational state predictions were used with the trivariate and bivariate gaussian dihedral angle probability distributions to generate starting structures (i.e., dihedral angles) suitable for energy minimization. The final energy-minimized structures show that neither the trivariate nor the bivariate gaussian probability distributions are able to overcome the inaccuracies in the backbone conformational state predictions to produce a native-like structure. Until highly accurate predictions of the backbone conformational states become available, application of these dihedral angle probability distributions must be limited to problems, such as homology modeling, in which only a limited portion of the backbone (e.g., surface loops) must be explored. © 1996 John Wiley & Sons, Inc.     

Magic angle spinning solid-state NMR spectroscopy for structural studies of protein interfaces. resonance assignments of differentially enriched Escherichia coli thioredoxin reassembled by fragment complementation

De novo site-specific backbone and side-chain resonance assignments are presented for U-15N(1-73)/U-13C,15N(74-108) reassembly of Escherichia coli thioredoxin by fragment complementation, determined using solid-state magic angle spinning NMR spectroscopy at 17.6 T. Backbone dihedral angles and secondary structure predicted from the statistical analysis of 13C and 15N chemical shifts are in general agreement with solution values for the intact full-length thioredoxin, confirming that the secondary structure is retained in the reassembled complex prepared as a poly(ethylene glycol) precipitate. The differential labeling of complementary thioredoxin fragments introduced in this work is expected to be beneficial for high-resolution structural studies of protein interfaces formed by protein assemblies by solid-state NMR spectroscopy.     

Sulfur K-edge spectroscopic investigation of second coordination sphere effects in oxomolybdenum-thiolates: relationship to molybdenum-cysteine covalency and electron transfer in sulfite oxidase

Second-coordination sphere effects such as hydrogen bonding and steric constraints that provide for specific geometric configurations play a critical role in tuning the electronic structure of metalloenzyme active sites and thus have a significant effect on their catalytic efficiency. Crystallographic characterization of vertebrate and plant sulfite oxidase (SO) suggests that an average O(oxo)-Mo-S(Cys)-C dihedral angle of approximately 77 degrees exists at the active site of these enzymes. This angle is slightly more acute (approximately 72 degrees) in the bacterial sulfite dehydrogenase (SDH) from Starkeya novella. Here we report the synthesis, crystallographic, and electronic structural characterization of Tp*MoO(mba) (where Tp* = (3,5-dimethyltrispyrazol-1-yl)borate; mba = 2-mercaptobenzyl alcohol), the first oxomolybdenum monothiolate to possess an O(ax)-Mo-S(thiolate)-C dihedral angle of approximately 90 degrees . Sulfur X-ray absorption spectroscopy clearly shows that O(ax)-Mo-S(thiolate)-C dihedral angles near 90 degrees effectively eliminate covalency contributions to the Mo(xy) redox orbital from the thiolate sulfur. Sulfur K-pre-edge X-ray absorption spectroscopy intensity ratios for the spin-allowed S(1s) --> Sv(p) + Mo(xy) and S(1s) --> Sv(p) + Mo(xz,yz) transitions have been calibrated by a direct comparison of theory with experiment to yield thiolate Sv(p) orbital contributions, c(j)(2), to the Mo(xy) redox orbital and the Mo(xz,yz) orbital set. Furthermore, these intensity ratios are related to a second coordination sphere structural parameter, the O(oxo)-Mo-S(thiolate)-C dihedral angle. The relationship between Mo-S(thiolate) and Mo-S(dithiolene) covalency in oxomolydenum systems is discussed, particularly with respect to electron-transfer regeneration in SO.     

SPINE X: improving protein secondary structure prediction by multistep learning coupled with prediction of solvent accessible surface area and backbone torsion angles

Accurate prediction of protein secondary structure is essential for accurate sequence alignment, three-dimensional structure modeling, and function prediction. The accuracy of ab initio secondary structure prediction from sequence, however, has only increased from around 77 to 80% over the past decade. Here, we developed a multistep neural-network algorithm by coupling secondary structure prediction with prediction of solvent accessibility and backbone torsion angles in an iterative manner. Our method called SPINE X was applied to a dataset of 2640 proteins (25% sequence identity cutoff) previously built for the first version of SPINE and achieved a 82.0% accuracy based on 10-fold cross validation (Q(3)). Surpassing 81% accuracy by SPINE X is further confirmed by employing an independently built test dataset of 1833 protein chains, a recently built dataset of 1975 proteins and 117 CASP 9 targets (critical assessment of structure prediction techniques) with an accuracy of 81.3%, 82.3% and 81.8%, respectively. The prediction accuracy is further improved to 83.8% for the dataset of 2640 proteins if the DSSP assignment used above is replaced by a more consistent consensus secondary structure assignment method. Comparison to the popular PSIPRED and CASP-winning structure-prediction techniques is made. SPINE X predicts number of helices and sheets correctly for 21.0% of 1833 proteins, compared to 17.6% by PSIPRED. It further shows that SPINE X consistently makes more accurate prediction in helical residues (6%) without over prediction while PSIPRED makes more accurate prediction in coil residues (3-5%) and over predicts them by 7%. SPINE X Server and its training/test datasets are available at http://sparks.informatics.iupui.edu/     

Structural importance of secondary interactions in molecules: origin of unconventional conformations of phosphine-borane adducts

The series of phosphine-borane adducts, Ph2(H3C--C[triple chemical bond]C)P--B(C6F5)3 (8 c), Ph(H3C--C[triple chemical bond]C)2P--B(C6F5)3 (8 b) and (H3C--C[triple chemical bond]C)3P--B(C6F5)3 (8 a), was prepared. The X-ray crystal structure analyses revealed close to eclipsed conformations for all members of this series with average dihedral angles theta(C-P-B-C) of 8.1 degrees (8 c), 12.3 degrees (8 b) and 20.3 degrees (8 a). Quantum chemical analysis of these compounds revealed the importance of a subtle interplay between competing attractive and repulsive secondary interactions, causing the surprising eclipsed conformational preference for systems of this degree of complexity. Some cyclic phosphine-borane adducts were studied for comparison.