The Solution Conformational Features of Two Highly Homologous Antigenic Peptides of Foot-and-mouth Disease Virus Serotype A,Variants A and USA,Correlate with their Serological Properties

The solution structure of a peptide corresponding to the VP1 region 141–160 of foot-and-mouth disease virus (FMDV) serotype A variant USA has been studied by NMR and computer calculations and compared with the results from a study on a highly homologous peptide deriving from serotype A, variant A. The two peptides differ in their serological behaviour and contain the immunodominant epitope of the virus which partly overlaps with its receptor binding region. Distance constraints, derived both from 2D and 3D homonuclear NMR and 2D-heteronuclear NMR experiments, were combined with DG calculations to yield 50 structures. After refinement through EM and restrained molecular dynamics simulations the selected structures shared several general features. In particular the 151–158 region was a helix in all cases while a large loop similar to that found in peptide A but comprising less residues and stabilized by an H-bond between the side chains of D147 and S150 was found in the majority of structures. A further loop, common to all structures, was identified around the RGD sequence (145–147). This was different from that found in the corresponding region of peptide A as were the conformations of the individual residues within the RGDX sequence. The different structural features shown by the two peptides were rationalized in terms of the S148 (peptide A) to F148 (peptide USA) mutation. The second mutation, that at position 153 (L in A, P in USA) did not appear to affect the structure of the peptide significantly although the different dimensions of the loop in the central region and the type of H-bond stabilizing it could be potentially ascribed to this second mutation. All criteria used pointed to different structural features for the two peptides consistent with their serological behaviour.     

The use of side-chain packing methods in modeling bacteriophage repressor and cro proteins.

In recent years, it has been repeatedly demonstrated that the coordinates of the main-chain atoms alone are sufficient to determine the side-chain conformations of buried residues of compact proteins. Given a perfect backbone, the side-chain packing method can predict the side-chain conformations to an accuracy as high as 1.2 Å RMS deviation (RMSD) with greater than 80% of the χ angles correct. However, similarly rigorous studies have not been conducted to determine how well these apply, if at all, to the more important problem of homology modeling per se. Specifically, if the available backbone is imperfect, as expected for practical application of homology modeling, can packing constraints alone achieve sufficiently accurate predictions to be useful? Here, by systematically applying such methods to the pairwise modeling of two repressor and two cro proteins from the closely related bacteriophages 434 and P22, we find that when the backbone RMSD is 0.8 Å, the prediction on buried side chain is accurate with an RMS error of 1.8 Å and approximately 70% of the χ angles correctly predicted. When the backbone RMSD is larger, in the range of 1.6–1.8 Å, the prediction quality is still significantly better than random, with RMS error at 2.2 Å on the buried side chains and 60% accuracy on χ angles. Together these results suggest the following rules-of-thumb for homology modeling of buried side chains. When the sequence identity between the modeled sequence and the template sequence is >50% (or, equivalently, the expected backbone RMSD is <1 Å), side-chain packing methods work well. When sequence identity is between 30–50%, reflecting a backbone RMS error of 1–2 Å, it is still valid to use side-chain packing methods to predict the buried residues, albeit with care. When sequence identity is below 30% (or backbone RMS error greater than 2 Å), the backbone constraint alone is unlikely to produce useful models. Other methods, such as those involving the use of database fragments to reconstruct a template backbone, may be necessary as a complementary guide for modeling.     

A molecular dynamics approach for the generation of complete protein structures from limited coordinate data

Generation of full protein coordinates from limited information, e.g., the Cα coordinates, is an important step in protein homology modeling and structure determination, and molecular dynamics (MD) simulations may prove to be important in this task. We describe a new method, in which the protein backbone is built quickly in a rather crude way and then refined by minimization techniques. Subsequently, the side chains are positioned using extensive MD calculations. The method is tested on two proteins, and results compared to proteins constructed using two other MD-based methods. In the first method, we supplemented an existing backbone building method with a new procedure to add side chains. The second one largely consists of available methodology. The constructed proteins are compared to the corresponding X-ray structures, which became available during this study, and they are in good agreement (backbone RMS values of 0.5–0.7 Å, and all-atom RMS values of 1.5–1.9 Å). This comparative study indicates that extensive MD simulations are able, to some extent, to generate details of the native protein structure, and may contribute to the development of a standardized methodology to predict reliably (parts of) protein structures when only partial coordinate data are available. © 1994 John Wiley & Sons, Inc.     

Structural comparison between retro-inverso and parent peptides: Molecular basis for the biological activity of a retro-inverso analogue of the immunodominant fragment of VP1 coat protein from foot-and-mouth disease virus

Antibodies induced against intact foot-and-mouth disease Virus (FMDV) particles bind to the retro-inverso analogue of fragment 141–159 of the viral coat protein VP1 of FMDV, variant A, equally well as to the parent peptide. A conformational investigation of this retro-inverso peptide was carried out by nmr spectroscopy and restrained molecular modeling in order to identify the structural basis for the antigenic mimicry between these retro-inverso and parent peptides. In 100% trifluoroethanol a well-defined left-handed α-helical region exists from residue 150 to residue 159, which is consistently present in all conformational families obtained from restrained modelling. A less-defined left-handed helical region is present in the tract 144–148, which is also consistent for all structures. Conformational flexibility exists about Gly149, which leads to two types of structures, either bent or linear. In the bent structures, a three-residue inverse tight turn is found, which can be classified as an inverse γ-turn centered at Gly149. The overall structural features of the retro-inverso peptide are shown to be similar to those of the parent L-peptide. The two molecules, however, are roughly mirror images because they share inherently chiral secondary structure elements. By comparing these conformational conclusions with the x-ray structure of the Fab complex of a corresponding VP1 antigenic fragment, a rationale is proposed to account for the topological requirements of specific recognition that are implied by the equivalent antigenic activity of the natural and retro-inverso compounds. © 1997 John Wiley & Sons, Inc. Biopoly 41: 569–590, 1997.     

RNA loop structure prediction via bond scaling and relaxation

We have developed a method for predicting the structure of small RNA loops that can be used to augment already existing RNA modeling techniques. The method requires no input constraints on loop configuration other than end-to-end distance. Initial loop structures are generated by randomizing the torsion angles, beginning at one end of the polynucleotide chain and correlating each successive angle with the previous. The bond lengths of these structures are then scaled to fit within the known end constraints and the equilibrium bond lengths of the potential energy function are scaled accordingly. Through a series of rescaling and minimization steps the structures are allowed to relax to lower energy configurations with standard bond lengths and reduced van der Waals clashes. This algorithm has been tested on the variable loops of yeast tRNA-Asp and yeast tRNA-Phe, as well as the sarcin-ricin tetraloop and the anticodon loop of yeast tRNA-Phe. The results indicate good correlation between potential energy and the loop structure predictions that are closest to the variable loop crystal structures, but poorer correlation for the more isolated stem loops. The number of stacking interactions has proven to be a good objective measure of the best loop predictions. Selecting on the basis of energy and stacking, we obtain two structures with 0.65 and 0.75 Å all-atom rms deviations (RMSD) from the crystal structure for the tRNA-Asp variable loop. The best structure prediction for the tRNA-Phe variable loop has an all-atom RMSD of 2.2 Å and a backbone RMSD of 1.6 Å, with a single base responsible for most of the deviation. For the sarcin-ricin loop from 28S ribosomal RNA, the predicted structure's all-atom RMSD from the nmr structure is 1.0 Å. We obtain a 1.8 Å RMSD structure for the tRNA-Phe anticodon loop. © 1996 John Wiley & Sons, Inc.     

Using a Hydrophobic Contact Potential to Evaluate Native and Near-native Folds Generated by Molecular Dynamics Simulations

There are several knowledge-based energy functions that can distinguish the native fold from a pool of grossly misfolded decoys for a given sequence of amino acids. These decoys, which are typically generated by mounting, or “threading”, the sequence onto the backbones of unrelated protein structures, tend to be non-compact and quite different from the native structure: the root-mean-squared (RMS) deviations from the native are commonly in the range of 15 to 20 Å. Effective energy functions should also demonstrate a similar recognition capability when presented with compact decoys that depart only slightly in conformation from the correct structure (i.e. those with RMS deviations of ∼5 Å or less). Recently, we developed a simple yet powerful method for native fold recognition based on the tendency for native folds to form hydrophobic cores. Our energy measure, which we call the hydrophobic fitness score, is challenged to recognize the native fold from 2000 near-native structures generated for each of five small monomeric proteins. First, 1000 conformations for each protein were generated by molecular dynamics simulation at room temperature. The average RMS deviation of this set of 5000 was 1.5 Å. A total of 323 decoys had energies lower than native; however, none of these had RMS deviations greater than 2 Å. Another 1000 structures were generated for each at high temperature, in which a greater range of conformational space was explored (4.3 Å average RMS deviation). Out of this set, only seven decoys were misrecognized. The hydrophobic fitness energy of a conformation is strongly dependent upon the RMS deviation. On average our potential yields energy values which are lowest for the population of structures generated at room temperature, intermediate for those produced at high temperature and highest for those constructed by threading methods. In general, the lowest energy decoy conformations have backbones very close to native structure. The possible utility of our method for screening backbone candidates for the purpose of modelling by side-chain packing optimization is discussed.     

TANGLE: two-level support vector regression approach for protein backbone torsion angle prediction from primary sequences

Protein backbone torsion angles (Phi) and (Psi) involve two rotation angles rotating around the C(α)-N bond (Phi) and the C(α)-C bond (Psi). Due to the planarity of the linked rigid peptide bonds, these two angles can essentially determine the backbone geometry of proteins. Accordingly, the accurate prediction of protein backbone torsion angle from sequence information can assist the prediction of protein structures. In this study, we develop a new approach called TANGLE (Torsion ANGLE predictor) to predict the protein backbone torsion angles from amino acid sequences. TANGLE uses a two-level support vector regression approach to perform real-value torsion angle prediction using a variety of features derived from amino acid sequences, including the evolutionary profiles in the form of position-specific scoring matrices, predicted secondary structure, solvent accessibility and natively disordered region as well as other global sequence features. When evaluated based on a large benchmark dataset of 1,526 non-homologous proteins, the mean absolute errors (MAEs) of the Phi and Psi angle prediction are 27.8° and 44.6°, respectively, which are 1% and 3% respectively lower than that using one of the state-of-the-art prediction tools ANGLOR. Moreover, the prediction of TANGLE is significantly better than a random predictor that was built on the amino acid-specific basis, with the p-value<1.46e-147 and 7.97e-150, respectively by the Wilcoxon signed rank test. As a complementary approach to the current torsion angle prediction algorithms, TANGLE should prove useful in predicting protein structural properties and assisting protein fold recognition by applying the predicted torsion angles as useful restraints. TANGLE is freely accessible at http://sunflower.kuicr.kyoto-u.ac.jp/~sjn/TANGLE/.     

Structure and internal mobility of proteins: a molecular dynamics study of hen egg white lysozyme

The structure and internal motions of the protein hen egg white lysozyme are studied by analysis of simulation and experimental data. A molecular dynamics simulation and an energy minimization of the protein in vacuum have been made and the results compared with high-resolution structures and temperature factors of hen egg white lysozyme in two different crystal forms and of the homologous protein human lysozyme. The structures obtained from molecular dynamics and energy minimization have root-mean-square deviations for backbone atoms of 2.3 Å and 1.1–1.3 Å, respectively, relative to the crystal structures; the different crystal structures have root-mean-square deviations of 0.73–0.81 Å for the backbone atoms. In comparing the backbone dihedral angles, the difference between the dynamics and the crystal structure on which it is based is the same as that between any two crystal structures. The internal fluctuations of atomic positions calculated from the molecular dynamics trajectory agree well with the temperature factors from the three structures. Simulation and crystal results both show that there are large motions for residues involved in exposed turns of the backbone chain, relatively smaller motions for residues involved in the middle of helices or β-sheet structures, and relatively small motions of residues near disulfide bridges. Also, both the simulation and crystal data show that side-chain atoms have larger fluctuations than main-chain atoms. Moreover, the regions that have large deviations among the x-ray crystal structures, which indicates flexibility, are found to have large fluctuations in the simulation.     

Polynucleotide folding in yeast tRNAPhe: elucidation of short-, medium-, and long-range interactions of sugar-phosphate-sugar backbone and base using a "blocked" nucleotide probe

It has recently been proposed that the repeating backbone nucleotide may be regarded as consisting of two blocks of equal magnitude representable by two virtual bonds. Implicit consideration of the nucleotide (ψ,ψ) and internucleotide (ω′,ω) geometry that generate variety in polynucleotide conformations, and of the constancy of the repeating structural moieties (P-C4′ and C4′-P) independent of the above rotations, has enabled us to utilize this scheme in the study of ordered structures such as di-, oligonucleotides and, most significantly, tRNA. The polynucleotide folding dictated by short-, intermediate-, and long-range interactions in the monoclinic and orthorhombic forms is described and compared through circular plots depicting the virtual bond torsions and distance plots constructed independently for backbone as well as bases. The torsions and the bond angles associated with the virtual bonds afford a clear distinction between ordered helical segments from loops and bends of tRNA. Lower virtual bond torsions (?60° to 60°) concomitant with higher values of virtual bond angles characterize various bend regions, while torsions around 160°–210° typify ordered helical strands. The distance plot elucidates the type of interaction associated with various sub-structures (helix–helix, helix–loop, and loop–loop) that form the constituents of different structural domains. Several other features such as the manifestation of the P₁₀ loop and the approximate twofold symmetry in the tRNA molecule are conspicuous on the distance plot.     

Accuracy and reliability of the scaling-relaxation method for loop closure: An evaluation based on extensive and multiple copy conformational samplings

The accuracy and reliability of the recently proposed scaling-relaxation method for loop closure were examined by using extensive conformational sampling. For each of the eight heptapeptides chosen to represent a variety of protein conformations, 1,000–2,000 conformations were sampled. Each segment contained 14 rotatable backbone dihedral angles. The average root mean square deviations (RMSDs) between the predicted and the native conformations were 0.7 Å for the backbone and 1.2 Å for the side chain atoms. These predictions were substantially more accurate than the previous predictions (1.1 Å for the backbone and 2.2 Å for the side chain atoms) of the same eight protein segments based on limited conformational sampling (100 conformations for each segment). Large prediction errors mostly occurred at polar and surface side chains that are unlikely to have any meaningful conformation. Moreover, the reliability of seven of the eight predictions was demonstrated with their energy-RMSD and stability-RMSD correlations of the low-energy conformations, where the conformational stability was estimated by using the multiple copy simultaneous sampling method.     

Evidence of the coevolution of antigenicity and host cell tropism of foot-and-mouth disease virus in vivo

In this work we analyze the antigenic properties and the stability in cell culture of virus mutants recovered upon challenge of peptide-vaccinated cattle with foot-and-mouth disease virus (FMDV) C3 Arg85. Previously, we showed that a significant proportion of 29 lesions analyzed (41%) contained viruses with single amino acid replacements (R141G, L144P, or L147P) within a major antigenic site located at the G-H loop of VP1, known to participate also in interactions with integrin receptors. Here we document that no replacements at this site were found in viruses from 12 lesions developed in six control animals upon challenge with FMDV C3 Arg85. Sera from unprotected, vaccinated animals exhibited poor neutralization titers against mutants recovered from them. Sequence analyses of the viruses recovered upon 10 serial passages in BHK-21 and FBK-2 cells in the presence of preimmune (nonneutralizing) sera revealed that mutants reverted to the parental sequence, suggesting an effect of the amino acid replacements in the interaction of the viruses with cells. Parallel passages in the presence of subneutralizing concentrations of immune homologous sera resulted in the maintenance of mutations R141G and L147P, while mutation L144P reverted to the C3 Arg85 sequence. Reactivity with a panel of FMDV type C-specific monoclonal antibodies indicated that mutant viruses showed altered antigenicity. These results suggest that the selective pressure exerted by host humoral immune response can play a role in both the selection and stability of antigenic FMDV variants and that such variants can manifest alterations in cell tropism.     

Accuracy of side-chain prediction upon near-native protein backbones generated by ab initio folding methods

The ab initio folding problem can be divided into two sequential tasks of approximately equal computational complexity: the generation of native-like backbone folds and the positioning of side chains upon these backbones. The prediction of side-chain conformation in this context is challenging, because at best only the near-native global fold of the protein is known. To test the effect of displacements in the protein backbones on side-chain prediction for folds generated ab initio, sets of near-native backbones (≤ 4 Å Cα RMS error) for four small proteins were generated by two methods. The steric environment surrounding each residue was probed by placing the side chains in the native conformation on each of these decoys, followed by torsion-space optimization to remove steric clashes on a rigid backbone. We observe that on average 40% of the χ1 angles were displaced by 40° or more, effectively setting the limits in accuracy for side-chain modeling under these conditions. Three different algorithms were subsequently used for prediction of side-chain conformation. The average prediction accuracy for the three methods was remarkably similar: 49% to 51% of the χ1 angles were predicted correctly overall (33% to 36% of the χ1+2 angles). Interestingly, when the inter-side-chain interactions were disregarded, the mean accuracy increased. A consensus approach is described, in which side-chain conformations are defined based on the most frequently predicted χ angles for a given method upon each set of near-native backbones. We find that consensus modeling, which de facto includes backbone flexibility, improves side-chain prediction: χ1 accuracy improved to 51–54% (36–42% of χ1+2). Implications of a consensus method for ab initio protein structure prediction are discussed. Proteins 33:204–217, 1998. © 1998 Wiley-Liss, Inc.     

High‐accuracy modeling of antibody structures by a search for minimum‐energy recombination of backbone fragments

Current methods for antibody structure prediction rely on sequence homology to known structures. Although this strategy often yields accurate predictions, models can be stereo‐chemically strained. Here, we present a fully automated algorithm, called AbPredict, that disregards sequence homology, and instead uses a Monte Carlo search for low‐energy conformations built from backbone segments and rigid‐body orientations that appear in antibody molecular structures. We find cases where AbPredict selects accurate loop templates with sequence identity as low as 10%, whereas the template of highest sequence identity diverges substantially from the query's conformation. Accordingly, in several cases reported in the recent Antibody Modeling Assessment benchmark, AbPredict models were more accurate than those from any participant, and the models' stereo‐chemical quality was consistently high. Furthermore, in two blind cases provided to us by crystallographers prior to structure determination, the method achieved <1.5 Ångstrom overall backbone accuracy. Accurate modeling of unstrained antibody structures will enable design and engineering of improved binders for biomedical research directly from sequence. Proteins 2016; 85:30–38. © 2016 Wiley Periodicals, Inc.     

Efficient search on energy minima for structure prediction of nucleic acid motifs

Structure prediction of non-canonical motifs such as mismatches, extra unmatched nucleotides or internal and hairpin loop structures in nucleic acids is of great importance for understanding the function and design of nucleic acid structures. Systematic conformational analysis of such motifs typically involves the generation of many possible combinations of backbone dihedral torsion angles for a given motif and subsequent energy minimization (EM) and evaluation. Such approach is limited due to the number of dihedral angle combinations that grows very rapidly with the size of the motif. Two conformational search approaches have been developed that allow both an effective crossing of barriers during conformational searches and the computational demand grows much less with system size then search methods that explore all combinations of backbone dihedral torsion angles. In the first search protocol single torsion angles are flipped into favorable states using constraint EM and subsequent relaxation without constraints. The approach is repeated in an iterative manner along the backbone of the structural motif until no further energy improvement is obtained. In case of two test systems, a DNA-trinucleotide loop (sequence: GCA) and a RNA tetraloop (sequence: UUCG), the approach successfully identified low energy states close to experiment for two out of five start structures. In the second method randomly selected combinations of up to six backbone torsion angles are simultaneously flipped into preset ranges by a short constraint EM followed by unconstraint EM and acceptance according to a Metropolis acceptance criterion. This combined stochastic/EM search was even more effective than the single torsion flip approach and selected low energy states for the two test cases in between two and four cases out of five start structures.     

Efficient Search on Energy Minima for Structure Prediction of Nucleic Acid Motifs

Abstract

Structure prediction of non-canonical motifs such as mismatches, extra unmatched nucleotides or internal and hairpin loop structures in nucleic acids is of great importance for understanding the function and design of nucleic acid structures. Systematic conformational analysis of such motifs typically involves the generation of many possible combinations of backbone dihedral torsion angles for a given motif and subsequent energy minimization (EM) and evaluation. Such approach is limited due to the number of dihedral angle combinations that grows very rapidly with the size of the motif. Two conformational search approaches have been developed that allow both an effective crossing of barriers during con-formational searches and the computational demand grows much less with system size then search methods that explore all combinations of backbone dihedral torsion angles. In the first search protocol single torsion angles are flipped into favorable states using constraint EM and subsequent relaxation without constraints. The approach is repeated in an iterative manner along the backbone of the structural motif until no further energy improvement is obtained. In case of two test systems, a DNA-trinucleotide loop (sequence: GCA) and a RNA tetraloop (sequence: UUCG), the approach successfully identified low energy states close to experiment for two out of five start structures. In the second method randomly selected combinations of up to six backbone torsion angles are simultaneously flipped into preset ranges by a short constraint EM followed by unconstraint EM and acceptance according to a Metropolis acceptance criterion. This combined stochastic/EM search was even more effective than the single torsion flip approach and selected low energy states for the two test cases in between two and four cases out of five start structures.     

A complete relaxation matrix refinement of the solution structure of a paramagnetic metalloprotein: Reduced HiPIP I from Ectothiorhodospira halophila

We have accounted for the effect of paramagnetism on the intensities of NOEs in a 73-residue paramagnetic metalloprotein, the reduced high-potential iron sulfur protein ISO I from Ectothiorhodospira halophila, whose solution structure had been recently solved by us. The paramagnetic effects were dealt with through a suitably modified complete relaxation matrix approach. We have then recalculated the structure through a distance geometry program by minimizing the difference between the sixth roots of the calculated and experimental NOEs. The average RMSD, calculated on residues 4–71, within the structures constituting the two families decreased from 0.67 to 0.46 Å for backbone atoms and from 1.23 to 1.06 Å for all heavy atoms. The structures in the new family are for the most part within the indetermination of the previous, less resolved, family. A few specific differences are detected and related to the presence of non-negligible paramagnetic effects, which are now properly evaluated.     

Two proposed general configurations for bacterial cell wall peptidoglycans shown by space-filling molecular models

Bacterial cell wall peptidoglycans are built from unbranched β-(1 → 4)-linked glycan chains composed of alternately repeating units of N-acetylglucosamine and N-acetylmuramic acid residues, with peptide side chains attached to the muramic acid residues. The glycan chains are interconnected by peptide bonds formed between the peptide side chains. Through the use of three-dimensional molecular models, two configurations of the glycan strands and the peptide side chains are described, which by their constancy of form reflect the fundamental constancies of the covalent structures. Each of these two models will accommodate any chemical modification that has been observed in bacteria without change in the configuration of the peptide backbone. Some alterations in the chemical structure, which have been sought in bacteria, but not found, would not be tolerated by the models. In these models, glycan strands are parallel, with their lengths and widths predominantly in the plane of the cell wall. The cross-bridging portions of the peptide side chains are at right angles to the glycan strand, in a separate, parallel plane. A compact model is presented in which the peptide side chain is closely appressed to the glycan strand and is stabilized by three hydrogen bonds per disaccharide–peptide subunit. In a second model, the peptide side chain is raised away from the glycan strand in an entirely extended configuration. The compact and extended forms are interconvertible. The thickness of a sheet of peptidoglycan would be from 10.6 to 11.1 Å for the compact model, and 19.1 Å for the extended model.     

Antibodies as a model system for comparative model refinement

Predicting the conformations of loops is a critical aspect of protein comparative (homology) modeling. Despite considerable advances in developing loop prediction algorithms, refining loops in homology models remains challenging. In this work, we use antibodies as a model system to investigate strategies for more robustly predicting loop conformations when the protein model contains errors in the conformations of side chains and protein backbone surrounding the loop in question. Specifically, our test system consists of partial models of antibodies in which the “scaffold” (i.e., the portion other than the complementarity determining region, CDR, loops) retains native backbone conformation, whereas the CDR loops are predicted using a combination of knowledge‐based modeling (H1, H2, L1, L2, and L3) and ab initio loop prediction (H3). H3 is the most variable of the CDRs. Using a previously published method, a test set of 10 shorter H3 loops (5–7 residues) are predicted to an average backbone (N? Cα? C? O) RMSD of 2.7 Å while 11 longer loops (8–9 residues) are predicted to 5.1 Å, thus recapitulating the difficulties in refining loops in models. By contrast, in control calculations predicting the same loops in crystal structures, the same method reconstructs the loops to an average of 0.5 and 1.4 Å for the shorter and longer loops, respectively. We modify the loop prediction method to improve the ability to sample near‐native loop conformations in the models, primarily by reducing the sensitivity of the sampling to the loop surroundings, and allowing the other CDR loops to optimize with the H3 loop. The new method improves the average accuracy significantly to 1.3 Å RMSD and 3.1 Å RMSD for the shorter and longer loops, respectively. Finally, we present results predicting 8–10 residue loops within complete comparative models of five nonantibody proteins. While anecdotal, these mixed, full‐model results suggest our approach is a promising step toward more accurately predicting loops in homology models. Furthermore, while significant challenges remain, our method is a potentially useful tool for predicting antibody structures based on a known Fv scaffold. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

On the computation of the tertiary structure of globular proteins—IV. Use of secondary structure information

The distance geometry approach for computing the tertiary structure of globular proteins emphasized in this series of papers (Goelet al., J. theor. Biol. 99, 705–757, 1982) is developed further. This development includes incorporation of some secondary structure information—the location of alpha helices in the primary sequence—in the algorithm to compute the tertiary structure of alpha helical globular proteins. An algorithm is developed which estimates the interresidue distances between chain-proximate helices. These distances, in conjunction with the global statistical average distances obtainable from a database of real proteins and determined by the primary sequence of the protein under study, are used to determine the tertiary structure. Five proteins, parvalbumin, hemerythrin, human hemoglobin, lamprey hemoglobin, and sperm whale myoglobin, are investigated. The root mean square (RMS) errors between the calculated structures and those determined by X-ray diffraction range from 4.78 to 7.56 Å. These RMSs are 0.21–2.76 Å lower than those estimated without the secondary structure information. Contact maps and three-dimensional backbone representations also show considerable improvements with the introduction of secondary structure information.     

Chimeric polioviruses that include sequences derived from two independent antigenic sites of foot-and-mouth disease virus (FMDV) induce neutralizing antibodies against FMDV in guinea pigs.

Five poliovirus recombinants containing sequences corresponding to foot-and-mouth disease virus (FMDV) antigenic sites were constructed. Viable virus was recovered from four of these plasmids, in which the VP1 beta B-beta C loop (antigenic site 1) of poliovirus type 1 Sabin had been replaced with sequences derived from the VP1 beta G-beta H loop (antigenic site 1) of FMDV O1 Kaufbeuren (O1K), chimera O1.1 (residues 141 to 154), chimera O1.2 (residues 147 to 156), and chimera O1.3 (residues 140 to 160) or from the beta B-beta C loop of VP1 (antigenic site 3) in chimera O3.1 (residues 40 to 49). One chimera (O1.3) was neutralized by FMDV-specific polyclonal serum and monoclonal antibodies directed against antigenic site 1 of FMDV. Chimeras O1.3 and O3.1 induced site-specific FMDV-neutralizing antibodies in guinea pigs. Chimera O1.3 was capable of inducing a protective response against FMDV challenge in some guinea pigs.