PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Protein Structure, Secondary”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7Linked to original sources
PubMed2004

Protection of protein secondary structure by saccharides of different molecular weights during freeze-drying.

The protective effects of saccharides with various molecular weights (glucose, maltose, maltotriose, maltotetraose, maltopentaose, maltoheptaose, dextran 1060, dextran 4900, and dextran 10200) against lyophilization-induced structural perturbation of model proteins (BSA, ovalbumin) were studied. Fourier transform infrared (FT-IR) analysis of the proteins in initial solutions and freeze-dried solids indicated that maltose conferred the greatest protection against secondary structure change. The structure-stabilizing effect of maltooligosaccharides decreased in increasing the number of saccharide units. Larger molecules of dextran also showed a smaller structure-stabilizing effect. Increasing the effective saccharide molecular size by a borate-saccharide complexation reduced the protein structure-stabilizing effect of all of the saccharides except glucose. The results indicate that the larger saccharide molecules, and/or the complex formation with borate ion, reduce the free and accessible hydroxyl groups to interact with and stabilize the protein structure by a water-substitution mechanism.

Calorimetry, Differential Scanning↗
PubMed1994

Empirical studies of protein secondary structure by vibrational circular dichroism and related techniques. Alpha-lactalbumin and lysozyme as examples.

Vibrational circular dichroism (VCD) has been shown to be sensitive to secondary structure in proteins and peptides and has been used as the basis for quantitative secondary-structure-prediction algorithms. However, the accuracy of these algorithms is not matched by the apparent qualitative sensitivity of the VCD spectra. This report provides examples of the use of VCD to follow structural change spectrally and to clarify the qualitative nature of the structural changes underlying the spectral variation. The VCD spectra and the complementary UV electronic CD (ECD) and FTIR spectra of alpha-lactalbumin (LA) have been studied as a function of pH, denaturation, Ca2+ ion and solvent conditions for several species. Spectral data for lysozyme were compared with those of LA because of their very similar crystal structures. In fact, these proteins in D2O-based pH 7 solution have quite different spectra using these optical techniques. Even for the LA proteins, the human differs from the bovine and goat species. Furthermore, under low pH conditions, where the LAs are in a reversibly denatured, molten globule form, the spectra are more similar, species variation is minimal and the spectral differences from lysozyme are in fact smaller. Our data are consistent with native, pH 7, alpha-lactalbumin having a less well organized structure than lysozyme, possibly in a dynamic sense. Conversely, in the low-pH, molten globule form of LA, tertiary structure is lost which could relax constraints that might distort the helical segments in the native form. The differences between the interpretation of our results and those from X-ray and NMR data may be due to motional sampling of various geometries in LA which all contribute to the spectral signatures seen in optical spectra but whose contributions are washed out in NMR or frozen out in the crystal structure. Part of this flexibility may relate to the rather large 3(10)-helical content in the LA protein structure. Fluctionality may have specific functional effects, perhaps allowing LA to bind better to beta-galactosyl transferase and form the biologically active lactose synthetase complex.

Amino Acid Sequence↗
PubMed2001

Elucidating protein secondary structures using alpha-carbon recurrence quantifications.

Secondary structures of proteins were studied by recurrence quantification analysis (RQA). High-resolution, 3-dimensional coordinates of alpha-carbon atoms comprising a set of 68 proteins were downloaded from the Protein Data Bank. By fine-tuning four recurrence parameters (radius, line, residue, separation), it was possible to establish excellent agreement between percent contribution of alpha-helix and beta-sheet structures determined independently by RQA and that of the DSSP algorithm (Define Secondary Structure of Proteins). These results indicate that there is an equivalency between these two techniques, which are based upon totally different pattern recognition strategies. RQA enhances qualitative contact maps by quantifying the arrangements of recurrent points of alpha carbons close in 3-dimensional space. For example, the radius was systematically increased, moving the analysis beyond local alpha-carbon neighborhoods in order to capture super-secondary and tertiary structures. However, differences between proteins could only be detected within distances up to about 6-11 A, but not higher. This result underscores the complexity of alpha-carbon spacing when super-secondary structures appear at larger distances. Finally, RQA-defined secondary structures were found to be robust against random displacement of alpha carbons upwards of 1 A. This finding has potential import for the dynamic functions of proteins in motion.

Bacterial Proteins↗
PubMed2006

Efficient characterization of protein secondary structure in terms of screw motions.

A simple and efficient method is presented to describe the secondary structure of proteins in terms of orientational distances between consecutive peptide planes and local helix parameters. The method uses quaternion-based superposition fits of the protein peptide planes in conjunction with Chasles' theorem, which states that any rigid-body displacement can be described by a screw motion. The helix parameters are derived from the best superposition of consecutive peptide planes and the ;worst' fit is used to define the orientational distance. Applications are shown for standard secondary-structure motifs of peptide chains for several proteins belonging to different fold classes and for a description of structural changes in lysozyme under hydrostatic pressure. In the latter case, published reference data obtained by X-ray crystallography and by structural NMR measurements are used.

Algorithms↗
PubMed1993

Effects of relative band intensity on prediction of protein secondary structure from CD.

Increasing the magnitude of a protein CD spectrum obviously increases the magnitude of each predicted secondary structure by the same amount. However, increasing the magnitude of the negative, long-wave-length portion of a protein CD spectrum usually has the opposite effect from increasing the positive, short-wave-length portion. Thus small distortions in the CD spectra of proteins at short wavelength can have a significant effect on the analysis for secondary structure. This measurement error and its effect on the analysis are systematically investigated for 16 proteins of known structure. The results demonstrate that a two-point calibration of a CD instrument is mandatory to avoid serious errors when estimating secondary structure from protein CD spectra.

Calibration↗
PubMedDate not supplied

Bayesian segmentation of protein secondary structure.

We present a novel method for predicting the secondary structure of a protein from its amino acid sequence. Most existing methods predict each position in turn based on a local window of residues, sliding this window along the length of the sequence. In contrast, we develop a probabilistic model of protein sequence/structure relationships in terms of structural segments, and formulate secondary structure prediction as a general Bayesian inference problem. A distinctive feature of our approach is the ability to develop explicit probabilistic models for alpha-helices, beta-strands, and other classes of secondary structure, incorporating experimentally and empirically observed aspects of protein structure such as helical capping signals, side chain correlations, and segment length distributions. Our model is Markovian in the segments, permitting efficient exact calculation of the posterior probability distribution over all possible segmentations of the sequence using dynamic programming. The optimal segmentation is computed and compared to a predictor based on marginal posterior modes, and the latter is shown to provide significant improvement in predictive accuracy. The marginalization procedure provides exact secondary structure probabilities at each sequence position, which are shown to be reliable estimates of prediction uncertainty. We apply this model to a database of 452 nonhomologous structures, achieving accuracies as high as the best currently available methods. We conclude by discussing an extension of this framework to model nonlocal interactions in protein structures, providing a possible direction for future improvements in secondary structure prediction accuracy.

Algorithms↗
PubMed2000

S curve, a graphic representation of protein secondary structure sequence and its applications.

A secondary structure sequence is a symbolic string composed of three kinds of letters, indicating the helix, strand, and coil (including turns), respectively. A graphic representation for this abstract symbolic sequence is proposed here, called the S curve. The S curve is the unique representation for a given secondary structure sequence in the sense that the sequence and the S curve can be uniquely determined from the other. Therefore, the S curve contains all the information that the secondary structure sequence contains. Different geometrical properties of the S curve are studied in details, which reflect the basic characteristics of the secondary structure sequences. The S curves are used to display, analyze, and compare the secondary structure sequences. Detailed application examples are presented. One advantage of the S curve methodology is that the main patterns of a given secondary structure sequence can be grasped quickly in a perceivable form. This is particularly useful in the cases in which longer sequences are involved and structures of proteins are unknown.

Amino Acid Sequence↗
PubMedDate not supplied

Changes in protein secondary structure during gluten deformation studied by dynamic fourier transform infrared spectroscopy.

Fourier transform infrared (FT-IR) spectroscopy was used to monitor changes in the secondary structure of wheat prolamins, the main components of gluten, during mechanical deformation in a series of cycles of extension and relaxation. A sample derived from protein bodies isolated from developing grain showed a buildup of persistent beta-sheet structure. In gluten, the ratio of beta-sheet to random and beta-turn structures changed on extension. After the applied force was released, the sample recovered some of its original shape and structure, but the material became stiffer in consecutive extension cycles. The relationship between gluten structure and mechanical properties is discussed in terms of a model in which conversion of beta-turn to beta-sheet structure is a response to extension and a means by which elastic energy is stored in the system.

Glutens↗
PubMed1997

Seventy-five percent accuracy in protein secondary structure prediction.

In this study we present an accurate secondary structure prediction procedure by using an query and related sequences. The most novel aspect of our approach is its reliance on local pairwise alignment of the sequence to be predicted with each related sequence rather than utilization of a multiple alignment. The residue-by-residue accuracy of the method is 75% in three structural states after jack-knife tests. The gain in prediction accuracy compared with the existing techniques, which are at best 72%, is achieved by secondary structure propensities based on both local and long-range effects, utilization of similar sequence information in the form of carefully selected pairwise alignment fragments, and reliance on a large collection of known protein primary structures. The method is especially appropriate for large-scale sequence analysis of efforts such as genome characterization, where precise and significant multiple sequence alignments are not available or achievable.

Algorithms↗
PubMed2004

The optimization of protein secondary structure determination with infrared and circular dichroism spectra.

We have used the circular dichroism and infrared spectra of a specially designed 50 protein database [Oberg, K.A., Ruysschaert, J.M. & Goormaghtigh, E. (2003) Protein Sci. 12, 2015-2031] in order to optimize the accuracy of spectroscopic protein secondary structure determination using multivariate statistical analysis methods. The results demonstrate that when the proteins are carefully selected for the diversity in their structure, no smaller subset of the database contains the necessary information to describe the entire set. One conclusion of the paper is therefore that large protein databases, observing stringent selection criteria, are necessary for the prediction of unknown proteins. A second important conclusion is that only the comparison of analyses run on circular dichroism and infrared spectra independently is able to identify failed solutions in the absence of known structure. Interestingly, it was also found in the course of this study that the amide II band has high information content and could be used alone for secondary structure prediction in place of amide I.

Algorithms↗
PubMed1993

The limits of protein secondary structure prediction accuracy from multiple sequence alignment.

The expected best residue-by-residue accuracies for secondary structure prediction from multiple protein sequence alignment have been determined by an analysis of known protein structural families. The results show substantial variation is possible among homologous protein structures, and that 100% agreement is unlikely between a consensus prediction and one member of a protein structural family. The study provides the range of agreement to be expected between a perfect secondary structure prediction from a multiple alignment and each protein within the alignment. The results of this study overcome the difficulties inherent in the use of residue-by-residue accuracy for assessing the quality of consensus secondary structure predictions. The accuracies of recent consensus predictions for the annexins, SH2 domains and SH3 domains fall within the expected range for a perfect prediction.

Amino Acid Sequence↗
PubMed1994

Destabilization of the complete protein secondary structure on binding to the chaperone GroEL.

Protein folding in vivo is mediated by helper proteins, the molecular chaperones, of which Hsp60 and its Escherichia coli variant GroEL are some of the best characterized. GroEL is an oligomeric protein with 14 subunits each of M(r) 60K, which possesses weak, co-operative ATPase activity and high plasticity. GroEL seems to interact with non-native proteins, binding one or two molecules per 14-mer in a 'central cavity', but little is known about the conformational state of the bound polypeptides. Here we use nuclear magnetic resonance techniques to show that the interaction of the small protein cyclophilin with GroEL is reversible by temperature changes, and all amide protons in GroEL-bound cyclophilin are exchanged with the solvent, although this exchange does not occur in free cyclophilin. The complete secondary structure of cyclophilin must be disrupted when bound to GroEL.

Amino Acid Isomerases↗
PubMed2004

Protein secondary structure assignment through Voronoï tessellation.

We present a new automatic algorithm, named VoTAP (Voronoï Tessellation Assignment Procedure), which assigns secondary structures of a polypeptide chain using the list of alpha-carbon coordinates. This program uses three-dimensional Voronoï tessellation. This geometrical tool associates with each amino acid a Voronoï polyhedron, the faces of which unambiguously define contacts between residues. Thanks to the face area, for the contacts close together along the primary structure (low-order contacts) a distinction is made between strong and normal ones. This new definition yields new contact matrices, which are analyzed and used to assign secondary structures. This assignment is performed in two stages. The first one uses contacts between residues close together along the primary structure and is based on data collected on a bank of 282 well-refined nonredundant structures. In this bank, associations were made between the prints defined by these low-order contacts and the assignments performed by different automatic methods. The second step focuses on the strand assignment and uses contacts between distant residues. Comparison with several other automatic assignment methods are presented, and the influence of resolution on the assignment is investigated.

Algorithms↗
PubMed2002

Thermal folding and mechanical unfolding pathways of protein secondary structures.

Mechanical stretching of secondary structures is studied through molecular dynamics simulations of a Go-like model. Force versus displacement curves are studied as a function of the stiffness and velocity of the pulling device. The succession of stretching events, as measured by the order in which contacts are ruptured, is compared to the sequencing of events during thermal folding and unfolding. Opposite cross-correlations are found for an alpha-helix and a beta-hairpin structure. In a tandem of two alpha-helices, the two constituent helices unravel nearly simultaneously. A simple condition for simultaneous versus sequential unraveling of repeat units is presented.

Computer Simulation↗
PubMed2006

Water penetration into protein secondary structure revealed by hydrogen-deuterium exchange two-dimensional infrared spectroscopy.

Two-dimensional infrared spectroscopy in conjunction with hydrogen-deuterium exchange experiments provides detailed information about solvent penetration into protein structure. Correlating the secondary-structure sensitivity of the amide I vibration and the solvent-exposure sensitivity of amide II provides a direct probe of solvent-inaccessible residues of proteins embedded in the hydrophobic core or those involved in strong hydrogen bonds in secondary structures. Distinct spectral signatures of the cross-peak region arising from the coupling of the amide I and II modes imply a significant degree of structural stability of hydrogen-bonded contacts in alpha-helices and beta-sheets in a series of proteins. Ubiquitin, an alpha/beta-protein, exhibits strong alpha-helical signatures and lacks those of the beta-sheet in the cross-peak region, demonstrating that ubiquitin's beta-sheet exchanges protons with the surrounding solvent and is conformationally unstable.

Amides↗