Determination of protein secondary structure by Fourier transform infrared spectroscopy: a critical assessment.
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Amides↗
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Results for “Protein Structure, Secondary”
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ATR-FT/IR study on the interactions between gliadins and dextrin and their effects on protein secondary structure.
The effects of heat treatment and dextrin addition on the secondary structure of gliadins were investigated by means of attenuated total reflection Fourier transform infrared spectroscopy (ATR-FT/IR). Gliadins and gliadin/dextrin mixtures (before and after thermal treatment) were prepared as a dried protein film on the ATR-FT/IR zinc selenide cell plate and equilibrated at a water activity (a(w)) of 0.06. The results show that gliadins undergo conformational changes upon thermal treatment both in the absence and in the presence of dextrin. In particular, in the thermally treated gliadins, the decrease of the band at around 1651 cm(-)(1) and the increase of the bands at around 1628 and 1690 cm(-)(1) suggest a loss of alpha-helix structure and a higher content of protein aggregates. The same trend was observed in the presence of dextrin. Concerning the interactions between gliadins and dextrin, gliadin/dextrin mixtures show variations in the amide I region compared to native gliadins (e.g., an increase of the band at 1645 cm(-)(1) and the absence of the band at around 1668 cm(-)(1)) that might be due to hydrogen bond formation between gliadins and dextrin. It was also found that the spectrum of gliadin/dextrin mixtures was less affected by the hydration state than that of native gliadins, as observed from the differential spectra obtained by subtraction of the spectrum obtained at a(w) = 0.06 (driest condition tested) from the spectrum of the sample equilibrated at a(w) = 0.84. This could be due to the fact that C=O and N-H groups of gliadins are engaged to form hydrogen bonds with the hydroxyl groups of dextrin, and so they are not perturbed by the presence of water molecules. Finally, water activity effects on the secondary structure of gliadins are also discussed.
Dextrins↗
Robust multivariate statistics and the prediction of protein secondary structure content.
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Least-Squares Analysis↗
In unison: regularization of protein secondary structure predictions that makes use of multiple sequence alignments.
We present a method whose purpose is to post-process the fuzzy results of secondary structure prediction methods that use multiple sequence alignments, in order to obtain 'realistic' secondary structures, i.e., secondary structure elements whose length is greater than or equal to some predefined minimum length. This regularization helps with interpretation of the secondary structure prediction.
Algorithms↗
Effects of formaldehyde fixation on protein secondary structure: a calorimetric and infrared spectroscopic investigation.
We investigated the effects of formaldehyde fixation on the secondary structure of isolated proteins (bovine serum albumin, ribonuclease A, and hemoglobin) using high-sensitivity differential scanning calorimetry and Fourier transform infrared spectroscopy. Whereas thermograms obtained by scanning calorimetry on unfixed purified proteins demonstrated denaturation transitions in the 70-90 degrees C temperature range, the thermograms showed no denaturation transitions in this temperature range when the proteins had been placed in formaldehyde solutions. Thus, fixation destroyed the denaturation transition of bovine serum albumin, ribonuclease A, and hemoglobin. Infrared spectra obtained on the unfixed and fixed proteins were essentially identical. This demonstrates that the "fixed" proteins retain the secondary structure present before fixation. We therefore conclude that the cross-linking of proteins that occurs in the process of formaldehyde fixation "locks in" the secondary structure of these protein molecules.
Calorimetry, Differential Scanning↗
[Fourier transform infrared spectroscopy study on the protein secondary structure of photosystem II reaction center].
A successful study on the secondary structure of the isolated photosystem II (PSII) particles with the Fourier transform infrared spectroscopy is reported in this paper. The beta condensation effect is obviously characterized by infrared absorption spectra. The infrared spectra of both living protein and beta condensed protein samples are measured at room temperature. The amide I band in infrared spectrum is used to perform the quantitative analysis of the sample properties. The recorded spectra show the irreversible effect for the PSII particles after the 400 K heating. A rather strong change of the infrared spectra is observed due to the beta condensation of PSII protein. All the spectra are well fitted by 3-Lorentz-peak. The FTIR spectroscopy shows its effectiveness in studying the heating effect on the PSII particles.
Amides↗
Variable selection method improves the prediction of protein secondary structure from circular dichroism spectra.
A new procedure based on the statistical method of "variable selection" is used to predict the secondary structure of proteins from circular dichroism spectra. Variable selection adds the flexibility found in the Provencher and Glöckner method (S. W. Provencher and J. Glöckner, 1981, Biochemistry 20, 33-37) to the method of Hennessey and Johnson (J. P. Hennessey and W. C. Johnson, 1981, Biochemistry 20, 1085-1094). Two analytical methods are presented for choosing a solution from the series generated by the Provencher and Glöckner method, and this improves the technique. All three methods are compared and it is shown that both the variable selection method and the improved Provencher and Glöckner methods have equivalent reliability superior to the original Hennessey and Johnson method. For the new variable selection method, correlation coefficients calculated between X-ray structure and predicted secondary structures for data measured to 178 nm are: 0.97 for alpha-helix, 0.75 for beta-sheet, 0.50 for beta-turn, and 0.89 for other structures. Although the variable selection method improves the analysis of circular dichroism data truncated at 190 nm, data measured to 178 nm gives superior results. It is shown that improving the fit to the measured CD beyond the accuracy of the data can result in poorer analyses.
Circular Dichroism↗
Prediction of protein secondary structure at 80% accuracy.
Secondary structure prediction involving up to 800 neural network predictions has been developed, by use of novel methods such as output expansion and a unique balloting procedure. An overall performance of 77.2%-80.2% (77.9%-80.6% mean per-chain) for three-state (helix, strand, coil) prediction was obtained when evaluated on a commonly used set of 126 protein chains. The method uses profiles made by position-specific scoring matrices as input, while at the output level it predicts on three consecutive residues simultaneously. The predictions arise from tenfold, cross validated training and testing of 1032 protein sequences, using a scheme with primary structure neural networks followed by structure filtering neural networks. With respect to blind prediction, this work is preliminary and awaits evaluation by CASP4.
Neural Networks, Computer↗
A modified definition of Sov, a segment-based measure for protein secondary structure prediction assessment.
We present a measure for the evaluation of secondary structure prediction methods that is based on secondary structure segments rather than individual residues. The algorithm is an extension of the segment overlap measure Sov, originally defined by Rost et al. (J Mol Biol 1994;235:13-26). The new definition of Sov corrects the normalization procedure and improves Sov's ability to discriminate between similar and dissimilar segment distributions. The method has been comprehensively tested during the second Critical Assessment of Techniques for Protein Structure Prediction (CASP2). Here, we describe the underlying concepts, modifications to the original definition, and their significance.
Algorithms↗
DICHROWEB, an online server for protein secondary structure analyses from circular dichroism spectroscopic data.
The DICHROWEB web server enables on-line analyses of circular dichroism (CD) spectroscopic data, providing calculated secondary structure content and graphical analyses comparing calculated structures and experimental data. The server is located at http://www.cryst.bbk.ac.uk/cdweb and may be accessed via a password-limited user ID, available upon completion of a registration form. The server facilitates analyses using five popular algorithms and (currently) seven different reference databases by accepting data in a user-friendly manner in a wide range of formats, including those output by both commercial CD instruments and synchrotron radiation-based circular dichroism beamlines, as well as those produced by spectral processing software packages. It produces as output calculated secondary structures, a goodness-of-fit parameter for the analyses, and tabular and graphical displays of experimental, calculated and difference spectra. The web pages associated with the server provide information on CD spectroscopic methods and terms, literature references and aids for interpreting the analysis results.
Algorithms↗
Environmental features are important in determining protein secondary structure.
We have investigated amino acid features that determine secondary structure: (1) the solvent accessibility of each side chain, and (2) the interaction of each side chain with others one to four residues apart. Solvent accessibility is a simple model that distinguishes residue environment. The pairwise interactions represent a simple model of local side chain to side chain interactions. To test the importance of these features we developed an algorithm to separate alpha-helices, beta-strands, and "other" structure. Single residue and pairwise probabilities were determined for 25,141 samples from proteins with <30% homology. Combining the features of solvent accessibility with pairwise probabilities allows us to distinguish the three structures after cross validation at the 82.0% level. We gain 1.4% to 2.0% accuracy by optimizing the propensities, demonstrating that probabilities do not necessarily reflect propensities. Optimization of residue exposures, weights of all probabilities, and propensities increased accuracy to 84.0%.
Algorithms↗
The effect of vesical outlet obstruction on the protein secondary structure of the mucosa and serosa in rabbit bladder wall.
The biochemical composition of physiologically moist mucosa and serosa of rabbit bladder before and after bladder outlet obstruction was determined by means of FT-IR spectroscopy with the ATR method and second-derivative analysis. A predominantly beta-sheet structure was found in the amide I band for mucosa and serosa before and after obstruction, but the random coil structure increased in both obstructed bladder samples. However, the major beta-sheet structure associated with some alpha-helical structure in the amide II band of mucosa and serosa for non-obstructed bladder changed into a predominantly alpha-helical structure after bladder obstruction. The obstructed bladder serosa was more pronounced. The amount of glycoproteins doubled in the obstructed bladder serosa, but did not change in the bladder mucosa.
Animals↗
Predicting protein secondary structure using neural net and statistical methods.
A comparison of neural network methods and Bayesian statistical methods is presented for prediction of the secondary structure of proteins given their primary sequence. The Bayesian method makes the unphysical assumption that the probability of an amino acid occurring in each position in the protein is independent of the amino acids occurring elsewhere. However, we find the predictive accuracy of the Bayesian method to be only minimally less than the accuracy of the most sophisticated methods used to date. We present the relationship of neural network methods to Bayesian statistical methods and show that, in principle, neural methods offer considerable power, although apparently they are not particularly useful for this problem. In the process, we derive a neural formalism in which the output neurons directly represent the conditional probabilities of structure class. The probabilistic formalism allows introduction of a new objective function, the mutual information, which translates the notion of correlation as a measure of predictive accuracy into a useful training measure. Although a similar accuracy to other approaches (utilizing a mean-square error) is achieved using this new measure, the accuracy on the training set is significantly and tantalizingly higher, even though the number of adjustable parameters remains the same. The mutual information measure predicts a greater fraction of helix and sheet structures correctly than the mean-square error measure, at the expense of coil accuracy, precisely as it was designed to do. By combining the two objective functions, we obtain a marginally improved accuracy of 64.4%, with Matthews coefficients C alpha, C beta and Ccoil of 0.40, 0.32 and 0.42, respectively. However, since all methods to date perform only slightly better than the Bayes algorithm, which entails the drastic assumption of independence of amino acids, one is forced to conclude that little progress has been made on this problem, despite the application of a variety of sophisticated algorithms such as neural networks, and that further advances will require a better understanding of the relevant biophysics.
Bayes Theorem↗
A simple and fast approach to prediction of protein secondary structure from multiply aligned sequences with accuracy above 70%.
To improve secondary structure predictions in protein sequences, the information residing in multiple sequence alignments of substituted but structurally related proteins is exploited. A database comprised of 70 protein families and a total of 2,500 sequences, some of which were aligned by tertiary structural superpositions, was used to calculate residue exchange weight matrices within alpha-helical, beta-strand, and coil substructures, respectively. Secondary structure predictions were made based on the observed residue substitutions in local regions of the multiple alignments and the largest possible associated exchange weights in each of the three matrix types. Comparison of the observed and predicted secondary structure on a per-residue basis yielded a mean accuracy of 72.2%. Individual alpha-helix, beta-strand, and coil states were respectively predicted at 66.7, and 75.8% correctness, representing a well-balanced three-state prediction. The accuracy level, verified by cross-validation through jack-knife tests on all protein families, dropped, on average, to only 70.9%, indicating the rigor of the prediction procedure. On the basis of robustness, conceptual clarity, accuracy, and executable efficiency, the method has considerable advantage, especially with its sole reliance on amino acid substitutions within structurally related proteins.
Algorithms↗
Relationship between nuclear magnetic resonance chemical shift and protein secondary structure.
An analysis of the 1H nuclear magnetic resonance chemical shift assignments and secondary structure designations for over 70 proteins has revealed some very strong and unexpected relationships. Similar studies, performed on smaller databases, for 13C and 15N chemical shifts reveal equally strong correlations to protein secondary structure. Among the more interesting results to emerge from this work is the finding that all 20 naturally occurring amino acids experience a mean alpha-1H upfield shift of 0.39 parts per million (from the random coil value) when placed in a helical configuration. In a like manner, the alpha-1H chemical shift is found to move downfield by an average of 0.37 parts per million when the residue is placed in a beta-strand or extended configuration. Similar changes are also found for amide 1H, carbonyl 13C, alpha-13C and amide 15N chemical shifts. Other relationships between chemical shift and protein conformation are also uncovered; in particular, a correlation between helix dipole effects and amide proton chemical shifts as well as a relationship between alpha-proton chemical shifts and main-chain flexibility. Additionally, useful relationships between alpha-proton chemical shifts and backbone dihedral angles as well as correlations between amide proton chemical shifts and hydrogen bond effects are demonstrated.
Hydrogen Bonding↗
A note on circular-dichroic-constrained prediction of protein secondary structure.
Circular dichroic (CD) spectra of bovine immunosuppressant binding proteins FKBP12 and FKBP25, and cyclophilins (peptidylprolyl isomerases) A (bCyP-18) and B(bCyP-20), the immunophilins which selectively bind the clinically useful immunosuppressants FK506, rapamycin and cyclosporin A, respectively, were analysed using the singular-value-decomposition algorithm augmented by a simplified variable selection method. The differences between the CD-estimated values of alpha-helix, beta-structure and beta-turn and those predicted by the Chou-Fasman algorithm were minimized using the CD data as constraints of an algorithm which utilizes the method of hierarchical updating of quasi-equipotential peptide segments of the Chou-Fasman prediction. The method allows one to correct the Chou-Fasman prediction of secondary structures in globular proteins.
Amino Acid Isomerases↗
[Determination of protein secondary structure from circular dichroism spectra. III. Protein-derived base spectra of circular dichroism for antiparallel and parallel beta-structures].
Protein-derived basic CD spectra for alpha-helix, antiparallel and parallel beta-structures, beta-bends and irregular form of proteins have been determined from the experimental CD spectra of six (myoglobin, lysozyme, ribonuclease A, papain, lactate dehydrogenase, subtilisin BPN') or seven (glyceraldehyde-3-phosphate dehydrogenase added) reference proteins and the analysis of the X-ray data. The secondary structures of thirteen proteins (seven reference and six additional ones) have been analysed using the basic CD spectra thus obtained. The data obtained have been compared with the results of the X-ray data analysis. It is shown that the accuracy of determination of the beta-structure and beta-bends contents using our basic CD spectra is about 2-3 times better than using the basic spectra reported by Chang et al. (Analyt. Biochem. 91, 13-31, 1978).
Circular Dichroism↗
Novel matrix descriptor for secondary structure segments in proteins: demonstration of predictability from circular dichroism spectra.
An extension to standard protein secondary structure predictions using optical spectra that encompasses the number and average lengths of segments of uniform secondary structure in the sequence is demonstrated. The connectivity and numbers of segments can be described by a matrix descriptor [sij] (i, j representing segment types such as helix and beta-sheet strands). Independent knowledge of the fractional concentration of each secondary structure type and of the total number of residues in the protein then with [sij] yields the average segment length of each type. The physical background for prediction of this extended structural descriptor from spectral data is summarized, rules for its generation from reference X-ray structures are defined, and formal variants of its form are discussed. Using a novel neural network approach to analyze a training set of electronic circular dichroism (ECD) and vibrational circular dichroism (VCD) spectra for 23 proteins, matrix descriptors encompassing helix, sheet, and other forms are predicted. The results show that the matrix descriptor can be predicted to an accuracy comparable to that of conventionally predicted average fractional secondary structures. In this respect the ECD predictions of [sij] were significantly more accurate than the VCD ones, which may result from the longer range length dependence of the ECD bandshape and intensity. Summary results for a parallel analysis using Fourier transform infrared spectra indicate somewhat lower reliability than those for VCD.
Circular Dichroism↗