Analysis and prediction of the different types of beta-turn in proteins

beta-Turns have been extracted from 59 non-identical proteins (resolution 2 A) using the standard criterion that the distance between C alpha (i) and C alpha (i + 3) is less than 7 A (1 A = 0.1 nm). The beta-turns have been classified, using phi, psi angles, into seven conventional turn types (I, I', II, II', IV, VIa, VIb) and a new class of beta-turn, designated type VIII, in which the central residues (i + 1, i + 2) adopt an alpha R beta conformation. Most beta-turn types are found in various topological environments, with the exception of I' and II' beta-turns, where 83% and 50%, respectively, are found in beta-hairpins. Sufficient data have been gathered to enable, for the first time, the separate statistical analysis of type I and II beta-turns. The two turn types have been shown to be strikingly different in their sequence preferences. Type I turns favour Asp, Asn, Ser and Cys at i; Asp, Ser, Thr and Pro at i + 1; Asp, Ser, Asn and Arg at i + 2; Gly, Trp and Met at i + 3, whilst type II turns prefer Pro at i + 1; Gly and Asn at i + 2; Gln and Arg at i + 3. These preferences have been explained by the specific side-chain interactions observed within the X-ray structures. The positional trends for type I and II beta-turns have been incorporated into the simple empirical predictive algorithm originally developed by P.N. Lewis et al. The program has improved the positional prediction of beta-turns, and has enhanced and extended the method by predicting the type of beta-turn. Since the observed preferences reflect local interactions these predictions are applicable not only to proteins, but also to peptides, many of which are thought to contain beta-turns.     

PEPstr: a de novo method for tertiary structure prediction of small bioactive peptides

Among secondary structure elements, beta-turns are ubiquitous and major feature of bioactive peptides. We analyzed 77 biologically active peptides with length varying from 9 to 20 residues. Out of 77 peptides, 58 peptides were found to contain at least one beta-turn. Further, at the residue level, 34.9% of total peptide residues were found to be in beta-turns, higher than the number of helical (32.3%) and beta-sheet residues (6.9%). So, we utilized the predicted beta-turns information to develop an improved method for predicting the three-dimensional (3D) structure of small peptides. In principle, we built four different structural models for each peptide. The first 'model I' was built by assigning all the peptide residues an extended conformation (phi = Psi = 180 degrees ). Second 'model II' was built using the information of regular secondary structures (helices, beta-strands and coil) predicted from PSIPRED. In third 'model III', secondary structure information including beta-turn types predicted from BetaTurns method was used. The fourth 'model IV' had main-chain phi, Psi angles of model III and side chain angles assigned using standard Dunbrack backbone dependent rotamer library. These models were further refined using AMBER package and the resultant C(alpha) rmsd values were calculated. It was found that adding the beta-turns to the regular secondary structures greatly reduces the rmsd values both before and after the energy minimization. Hence, the results indicate that regular and irregular secondary structures, particularly beta-turns information can provide valuable and vital information in the tertiary structure prediction of small bioactive peptides. Based on the above study, a web server PEPstr (http://www.imtech.res.in/raghava/pepstr/) was developed for predicting the tertiary structure of small bioactive peptides.     

Structure characterization of the central repetitive domain of high molecular weight gluten proteins. II. Characterization in solution and in the dry state.

The structure of the central repetitive domain of high molecular weight HMW) wheat gluten proteins was characterized in solution and in the dry state using HMW proteins Bx6 and Bx7 and a subcloned, bacterially expressed part of the repetitive domain of HMW Dx5. Model studies of the HMW consensus peptides PGQGQQ and GYYPTSPQQ formed the basis for the data analysis (van Dijk AA et al., 1997, Protein Sci 6:637-648). In solution, the repetitive domain contained a continuous nonoverlapping series of both type I and type II II beta-turns at positions predicted from the model studies; type II beta-turns occurred at QPGQ and QQGY sequences and type I beta-turns at YPTS and SPQQ. The subcloned part of the HMW Dx5 repetitive domain sometimes migrated as two bands on SDS-PAGE; we present evidence that this may be caused by a single amino acid insertion that disturbs the regular structure of beta-turns. The type I beta-turns are lost when the protein is dried on a solid surface, probably by conversion to type II beta-turns. The homogeneous type II beta-turn distribution is compatible with the formation of a beta-spiral structure, which provides the protein with elastic properties. The beta-turns and thus the beta-spiral are stabilized by hydrogen bonds within and between turns. Reformation of this hydrogen bonding network after, e.g., mechanical disruption may be important for the elastic properties of gluten proteins.     

Hydrogen-bonded turns in proteins: the case for a recount

Beta-turns are sites at which proteins change their overall chain direction, and they occur with high frequency in globular proteins. The Protein Data Bank has many instances of conformations that resemble beta-turns but lack the characteristic N-H(i) --> O=C(i - 3) hydrogen bond of an authentic beta-turn. Here, we identify potential hydrogen-bonded beta-turns in the coil library, a Web-accessible database utility comprised of all residues not in repetitive secondary structure, neither alpha-helix nor beta-sheet (http://www.roselab.jhu.edu/coil). In particular, candidate turns were identified as four-residue segments satisfying highly relaxed geometric criteria but lacking a strictly defined hydrogen bond. Such candidates were then subjected to a minimization protocol to determine whether slight changes in torsion angles are sufficient to shift the conformation into reference-quality geometry without deviating significantly from the original structure. This approach of applying constrained minimization to known structures reveals a substantial population of previously unidentified, stringently defined, hydrogen-bonded beta-turns. In particular, 33% of coil library residues were classified as beta-turns prior to minimization. After minimization, 45% of such residues could be classified as beta-turns, with another 8% in 3(10) helixes (which closely resemble type III beta-turns). Of the remaining coil library residues, 37% have backbone dihedral angles in left-handed polyproline II structure.     

gβ- and gγ-turns in proteins revisited: A new set of amino acid turn-type dependent positional preferences and potentials

The number of beta-turns in a representative set of 426 protein three-dimensional crystal structures selected from the recent Protein Data Bank has nearly doubled and the number of gamma-turns in a representative set of 320 proteins has increased over seven times since the previous analysis. Beta-turns (7153) and gamma-turns (911) extracted from these proteins were used to derive a revised set of type-dependent amino acid positional preferences and potentials. Compared with previous results, the preference for proline, methionine and tryptophan has increased and the preference for glutamine, valine, glutamic acid and alanine has decreased for beta-turns. Certain new amino acid preferences were observed for both turn types and individual amino acids showed turn-type dependent positional preferences. The rationale for new amino acid preferences are discussed in the light of hydrogen bonds and other interactions involving the turns. Where main-chain hydrogen bonds of the type NH(i + 3) --> CO(i) were not observed for some beta-turns, other main-chain hydrogen bonds or solvent interactions were observed that possibly stabilize such beta-turns. A number of unexpected isolated beta-turns with proline at i + 2 position were also observed. The NH(i + 2) --> CO(i) hydrogen bond was observed for almost all gamma-turns. Nearly 20% classic gamma-turns and 43% inverse gamma-turns are isolated turns.     

Optical spectroscopic elucidation of beta-turns in disulfide bridged cyclic tetrapeptides

Vibrational circular dichroism (VCD) spectroscopic features of type II beta-turns were characterized previously, but, criteria for differentiation between beta-turn types had not been established yet. Model tetrapeptides, cyclized through a disulfide bridge, were designed on the basis of previous experimental results and the observed incidence of amino acid residues in the i + 1 and i + 2 positions in beta-turns, to determine the features of VCD spectra of type I and II beta-turns. The results were correlated with electronic circular dichroism (ECD) spectra and VCD spectra calculated from conformational data obtained by molecular dynamics (MD) simulations. All cyclic tetrapeptides yielded VCD signals with a higher frequency negative and a lower frequency positive couplet with negative lobes overlapping. MD simulations confirmed the conformational homogeneity of these peptides in solution. Comparison with ECD spectroscopy, MD, and quantum chemical calculation results suggested that the low frequency component of VCD spectra originating from the tertiary amide vibrations could be used to distinguish between types of beta-turn structures. On the basis of this observation, VCD spectroscopic features of type II and VIII beta-turns and ECD spectroscopic properties of a type VIII beta-turn were suggested. The need for independent experimental as well as theoretical investigations to obtain decisive conformational information was recognized.     

Synthesis and structural characterization of poly(LGGVG), an elastin-like polypeptide

Poly(LGGVG) a potential elastin-like biomaterial has been synthesized and studied both in solution (by circular dicroism and nuclear magnetic resonance) and in the aggregated state (by transmission electron microscopy). For sake of comparison, also the conformation of the protected (Boc-LGGVG-OEt) and free (H(2)(+)-LGGVG-OH) 'monomers' has been investigated. While in the latter ones the presence has been evidenced of more or less stable type II beta-turns, the polymer showed a conformational ensemble, possibly comprising type II beta-turns, type I beta-turns and open (unordered) structures. At supramolecular level, twisted-rope aggregates were observed by transmission electron microscopy for the polymer. Thus, the title compound has shown to possess, at both molecular and supramolecular level, physico-chemical properties very similar to those of elastin, so to give some confidence that it could really constitute the precursor of an artificial substitute of elastin itself.     

Support vector machines for prediction and analysis of beta and gamma-turns in proteins

Tight turns have long been recognized as one of the three important features of proteins, together with alpha-helix and beta-sheet. Tight turns play an important role in globular proteins from both the structural and functional points of view. More than 90% tight turns are beta-turns and most of the rest are gamma-turns. Analysis and prediction of beta-turns and gamma-turns is very useful for design of new molecules such as drugs, pesticides, and antigens. In this paper we investigated two aspects of applying support vector machine (SVM), a promising machine learning method for bioinformatics, to prediction and analysis of beta-turns and gamma-turns. First, we developed two SVM-based methods, called BTSVM and GTSVM, which predict beta-turns and gamma-turns in a protein from its sequence. When compared with other methods, BTSVM has a superior performance and GTSVM is competitive. Second, we used SVMs with a linear kernel to estimate the support of amino acids for the formation of beta-turns and gamma-turns depending on their position in a protein. Our analysis results are more comprehensive and easier to use than the previous results in designing turns in proteins.     

Prediction of beta-turns.

An automated computer prediction of the chain reversal regions of globular proteins is described herein using bend frequencies and beta-turn conformational parameters (Pt) determined from 408 beta-turns in 29 proteins calculated from x-ray atomic coordinates. The probability of bend occurrence at residue i is pt = fi X fi+1 X fi+2 X fi+3 with the average bend probability less than Pt greater than = 0.55 X 10(-4). Tetrapeptides with pt greater than 0.75 X 10(-4) ( approximately to 1.5 X less than pt greater than) as well as less than Pt greater than 1.00 and less than Pa greater than less than less than Pt greater than greater than less than P beta greater than are selected by the computer as probable bends. Adjacent probable bends (i.e., 11-14, 12-15, 13-16) are compared pairwise by the computer, and the tetrapeptide with the higher pt value is predicted as a beta-turn. The percentage of bend and nonbend residues predicted correctly for 29 proteins by this computer algorithm is %t+nt = 70%, whereas 78% of the beta-turns were localized correctly within +/- 2 residues. The average beta-turn content in the 29 proteins is 32%, with helical proteins having fewer bends (17%) than beta-sheet proteins (41%). Three proteins having iron-sulfur clusters were found with the highest percentages of beta-turns: Chromatium high potential iron protein (65%), ferredoxin (57%), and rubredoxin (65%). Finally, the bend frequencies at all 12 positions from 457 beta-turns in 29 proteins (Chou and Fasman, 1977) were used to test the effectiveness of predicting bends using 2, 4, 8, and 12 residues as well as different cut-off pt values. The computer analysis showed that 1.25 less than pt greater than to be the best cut-off yielding 70% accuracy in %t+nt for 4 residues and %t+nt = 73% for 12 residues in predicting the bend and nonbend regions of proteins.     

BetaTPred: prediction of beta-TURNS in a protein using statistical algorithms

MOTIVATION: beta-turns play an important role from a structural and functional point of view. beta-turns are the most common type of non-repetitive structures in proteins and comprise on average, 25% of the residues. In the past numerous methods have been developed to predict beta-turns in a protein. Most of these prediction methods are based on statistical approaches. In order to utilize the full potential of these methods, there is a need to develop a web server. RESULTS: This paper describes a web server called BetaTPred, developed for predicting beta-TURNS in a protein from its amino acid sequence. BetaTPred allows the user to predict turns in a protein using existing statistical algorithms. It also allows to predict different types of beta-TURNS e.g. type I, I', II, II', VI, VIII and non-specific. This server assists the users in predicting the consensus beta-TURNS in a protein. AVAILABILITY: The server is accessible from http://imtech.res.in/raghava/betatpred/     

Circular dichroism studies on repeating polypeptide sequences of abductin

The secondary structure of abductin was investigated by CD and NMR studies of several synthetic peptides. Results obtained with these peptides showed the dominant conformations to be the polyproline II (PPII) structure in aqueous solution and different types of beta-turns in the less polar solvent trifluoroethanol. Accordingly, a preliminary structure-elasticity relationship for abductin, not unlike that currently accepted for elastin, is proposed.     

Mimicry by asx- and ST-turns of the four main types of beta-turn in proteins

Hydrogen-bonded beta-turns in proteins occur in four categories: type I (the most common), type II, type II', and type I'. Asx-turns resemble beta-turns, in that both have an NH. . .OC hydrogen bond forming a ring of 10 atoms. Serine and threonine side chains also commonly form hydrogen-bonded turns, here called ST-turns. Asx-turns and ST-turns can be categorized into four classes, based on side chain rotamers and the conformation of the central turn residue, which are geometrically equivalent to the four types of beta-turns. We propose asx- and ST-turns be named using the type I, II, I', and II' beta-turn nomenclature. Using this, the frequency of occurrence of both asx- and ST-turns is: type II' > type I > type II > type I', whereas for beta-turns it is type I > type II > type I' > type II'. Almost all type II asx-turns occur as a recently described three residue feature named an asx-nest.     

Structural motifs in the maturation process of peptide hormones. The somatostatin precursor. I. A CD conformational study.

Synthetic peptides reproducing both the native domain around the dibasic cleavage site of prosomatostatin, and mutated sequences there of, previously assayed in site-directed mutagenesis experiments, have been studied by CD in different solvent systems, such as water, TFE/H2O, MeCN/H2O and aqueous SDS, in order to ascertain the ability of each solvent to stabilize secondary structural motifs. A combination of deconvolution methods and empirical calculations, that allow subtraction of the contributions due to unordered structures from the spectra, suggests that mainly two distinct families of ordered conformers containing alpha-helix and/or structurally different beta-turns are present in solution, the relative stability of the different conformers depending on the nature of the solvent. The presence of beta-turns is in line with a previous NMR study in DMSO and DMSO/H2O. Comparison of the CD spectra in aqueous SDS of peptides undergoing processing with a sequence not processed in vivo shows that only the latter possesses a stable and detectable alpha-helix population. This observation suggests that the structuration involving beta-turns but no alpha-helix, which was observed by CD both in SDS and organic solvent/H2O mixtures at high water contents, might be of biological significance. The similarity of this structuration to molecular models obtained from NMR data in DMSO and DMSO/H2O is discussed.     

Amino acid periodicities and their structural implications for the evolutionarily conservative central domain of some silkmoth chorion proteins

The central domain is an evolutionarily conservative region that is invariant in length in the A and Hc-A families of silkmoth chorion proteins. This domain shows strong sixfold periodicities for various amino acid residues, such as glycine and large non-polar residues. The periodicities and their phase relationships, together with the documented prevalence of beta-sheets and beta-turns in the chorion, strongly support a secondary structure model in which short (4-residue) beta-sheet strands alternate with beta-turns, forming a compact antiparallel, probably twisted beta-sheet. This structure should be important for the establishment of higher order structure in the chorion.     

An evaluation of beta-turn prediction methods

MOTIVATION: beta-turn is an important element of protein structure. In the past three decades, numerous beta-turn prediction methods have been developed based on various strategies. For a detailed discussion about the importance of beta-turns and a systematic introduction of the existing prediction algorithms for beta-turns and their types, please see a recent review (Chou, Analytical Biochemistry, 286, 1-16, 2000). However at present, it is still difficult to say which method is better than the other. This is because of the fact that these methods were developed on different sets of data. Thus, it is important to evaluate the performance of beta-turn prediction methods. RESULTS: We have evaluated the performance of six methods of beta-turn prediction. All the methods have been tested on a set of 426 non-homologous protein chains. It has been observed that the performance of the neural network based method, BTPRED, is significantly better than the statistical methods. One of the reasons for its better performance is that it utilizes the predicted secondary structure information. We have also trained, tested and evaluated the performance of all methods except BTPRED and GORBTURN, on new data set using a 7-fold cross-validation technique. There is a significant improvement in performance of all the methods when secondary structure information is incorporated. Moreover, after incorporating secondary structure information, the Sequence Coupled Model has yielded better results in predicting beta-turns as compared with other methods. In this study, both threshold dependent and independent (ROC) measures have been used for evaluation.     

Prediction of beta-turns in proteins using neural networks

The use of neural networks to improve empirical secondary structure prediction is explored with regard to the identification of the position and conformational class of beta-turns, a four-residue chain reversal. Recently an algorithm was developed for beta-turn predictions based on the empirical approach of Chou and Fasman using different parameters for three classes (I, II and non-specific) of beta-turns. In this paper, using the same data, an alternative approach to derive an empirical prediction method is used based on neural networks which is a general learning algorithm extensively used in artificial intelligence. Thus the results of the two approaches can be compared. The most severe test of prediction accuracy is the percentage of turn predictions that are correct and the neural network gives an overall improvement from 20.6% to 26.0%. The proportion of correctly predicted residues is 71%, compared to a chance level of about 58%. Thus neural networks provide a method of obtaining more accurate predictions from empirical data than a simpler method of deriving propensities.     

Quantitative analysis of cyclic beta-turn models.

The beta-turn is a frequently found structural unit in the conformation of globular proteins. Although the circular dichroism (CD) spectra of the alpha-helix and beta-pleated sheet are well defined, there remains some ambiguity concerning the pure component CD spectra of the different types of beta-turns. Recently, it has been reported (Hollósi, M., Kövér, K.E., Holly, S., Radics, L., & Fasman, G.D., 1987, Biopolymers 26, 1527-1572; Perczel, A., Hollósi, M., Foxman, B.M., & Fasman, G.D., 1991a, J. Am. Chem. Soc. 113, 9772-9784) that some pseudohexapeptides (e.g., the cyclo[(delta)Ava-Gly-Pro-Aaa-Gly] where Aaa = Ser, Ser(OtBu), or Gly) in many solvents adopt a conformational mixture of type I and the type II beta-turns, although the X-ray-determined conformation was an ideal type I beta-turn. In addition to these pseudohexapeptides, conformational analysis was also carried out on three pseudotetrapeptides and three pseudooctapeptides. The target of the conformation analysis reported herein was to determine whether the ring stress of the above beta-turn models has an influence on their conformational properties. Quantitative nuclear Overhauser effect (NOE) measurements yielded interproton distances. The conformational average distances so obtained were interpreted utilizing molecular dynamics (MD) simulations to yield the conformational percentages. These conformational ratios were correlated with the conformational weights obtained by quantitative CD analysis of the same compounds. The pure component CD curves of type I and type II beta-turns were also obtained, using a recently developed algorithm (Perczel, A., Tusnády, G., Hollósi, M., & Fasman, G.D., 1991b, Protein Eng. 4(6), 669-679). For the first time the results of a CD deconvolution, based on the CD spectra of 14 beta-turn models, were assigned by quantitative NOE results. The NOE experiments confirmed the ratios of the component curves found for the two major beta-turns by CD analysis. These results can now be used to enhance the conformational determination of globular proteins on the basis of their CD spectra.     

Characterization of the solution conformations of leuprolide acetate.

Leuprolide acetate (pGlu-His-Trp-Ser-Tyr-d-Leu-Leu-Arg-Pro-NHEt), a potent LHRH agonist in wide clinical use, was characterized conformationally by NMR and circular dichroism. It displayed quite different preferred conformations under different solution conditions: two low population beta-turns in water, a nascent helix in TFE/water at low pH, and a high population beta-turn in TFE/water at slightly acidic pH. The pH-related conformational change in TFE/water is attributed to the pK(a) of the acetate counterion, not to ionizable groups on the peptide. None of these conformations are in exact agreement with previous computational predictions.     

Conformational studies of alanine-rich peptide using CD and FTIR spectroscopy.

The circular dichroism (CD) and Fourier transform infrared (FTIR) methods were applied to the conformational studies of alanine-rich peptide Ac-K-[A]11-KGGY-NH2 (where K is lysine, A is alanine, G is glycine and Y is tyrozyne) in water, methanol (MeOH) and trifluoroethanol (TFE). The analysis of CD-spectra of the peptide in water at different concentrations revealed that the secondary structure content depends on the peptide concentration and pH of the solution. The increase of the peptide concentration causes a decrease of alpha-helix content and, simultaneously, an increase of beta-sheet structure, while the unordered structure is the predominant one. Additional elements are discovered in MeOH and TFE but alpha-helix and beta-turns predominate. Moreover, in these solutions the percentage content of the secondary structure does not depend on the temperature. FTIR measurements, carried out at higher peptide concentration (about one order of magnitude) than these CD measurements mentioned above, revealed that in water solution the solid state beta-sheet, and aggregated structures, dominate. However, in TFE the most abundant are alpha-helix and beta-turns structures. The thioflavine T assay showed the tendency of the studied peptide for aggregate.     

Mimicry of beta II'-turns of proteins in cyclic pentapeptides with one and without D-amino acids.

The solution structure of eight cyclic pentapeptides has been determined by two-dimensional 1H-NMR spectroscopy combined with spectra simulations and restrained molecular dynamic simulations. Six of the cyclic pentapeptides were derived from the C-terminal cholecystokinin fragment CCK-4 enlarged with Asp1 resulting in the sequence (Asp-Trp-Met-Asp-Phe), one L-amino acid after the other was substituted by its D-analog. In addition, two peptides, including an all-L-amino-acid-containing cyclic pentapeptide, cyclo(Asp-Phe-Lys-Ala-Thr) and cyclo(Asp-Phe-Lys-Ala-D-Thr) were investigated. All D-amino-acid-containing peptides show beta II'-turn conformations with the D-amino acid in the i + 1 position, excepting the D-aspartic-acid-containing peptides. These two peptides are characterized by the lack of beta-turns at pH values less than 4, suggesting that D-aspartic acid in the full-protonized state avoids the formation of beta-turns in these compounds. At pH values greater than 5, a conformational change into the beta II'-turn conformation was also observed for these peptides. Conformations without beta-turns are expected for cyclic all-L pentapeptides, but both cyclo(Asp-Phe-Lys-Ala-Thr) and the D-Thr analog cyclo(Asp-Phe-Lys-Ala-D-Thr) exhibit beta II'-turn conformations around Thr-Asp and D-Thr-Asp. Thus cyclic all-L pentapeptides and those with one D-amino acid are able to form similar structures preferably with a beta II'-turn. The beta-turn formation in cyclic pentapeptides containing a D-aspartic acid is dependent on the ionization state. The relevance of the work to the design of beta'-turn mimetics is discussed.