Effect of Stereochemistry (Z and E) and Position of α,β-Dehydrophenylalanine (ΔPhe) on β-turn Stability

Several model peptides containing α, β-dehydrophenylalanine (ΔPhe) in both Z and E configurations were studied for β-turn stability at the AM1 level of theory. Both configurations of ΔPhe are well able to stabilize β-turns in the backbone. However, the β-turns for peptides bearing Z-ΔPhe are energetically more stable than the E-counterparts. The difference in energies between the global minima of these peptides having the Z and E configuration of ΔPhe, is dictated by the size and stereochemistry of residues flanking ΔPhe. One distinct feature of E-ΔPhe is that it pushes peptides to adopt a Type II β-turn with the ΔPhe residue in the (i + 1) position of the turn. This unique feature may be exploited in peptide design.     

Beta-turns in proteins

The X-ray atomic co-ordinates from 29 proteins of known sequence and structure were utilized to elucidate 459 β-turns in regions of chain reversals. Tetrapeptides whose αC_iαC_{(i + 3)} distances were below 7 Å and not in a helical region were characterized as β-turns. In addition, β-turns were considered to have hydrogen bonding if their computed O_(i)N_{(i + 3)} distances were ≤3.5 Å. The torsion angles of 26 proteins containing 421 β-turns were examined and classified into 11 bend types based on the (φ, ψ) dihedral angles of the i + 1 and i + 2 bend residues. The average frequency of β-turns is 32% as compared to the 38% helices and 20% β-sheets in the 29 proteins. The most frequently occurring bend residues are Asn, Cys, Asp in the first position, Pro, Ser, Lys in the second position, Asn, Asp, Gly in the third position, and Trp, Gly, Tyr in the fourth position. Residues with the highest β-turn potential in all four positions are Pro, Gly, Asn, Asp, and Ser with the most hydrophobic residues (i.e. Val, IIe, and Leu) showing the lowest bend potential. However, in the region just beyond the β-turns, hydrophobic residues occur with greater frequency than do hydrophilic residues. An environmental analysis of β-turn neighboring residues shows that reverse chain folding is stabilized by anti-parallel β-sheets as well as helix-helix and α-β interactions. The β-turn potential at the 12 positions adjacent to and including the bend were plotted for the 20 amino acids and showed dramatic positional preferences, which may be classified according to the nature of the side-chains. An examination of the 27 β-turns in elastase showed that 21 were found in identical positions as those in α-chymotrypsin. However, only 37 of the 84 bend residues were conserved, indicating that structural similarity may persist despite differences in sequence homology. A survey of residues occupying bend types I′, II′ and III′ showed that Gly appeared most frequently in the third position in bend types I′ and III′ as well as in the second position in bend types II′ and III′. Fourteen hydrogenbonded type II bends were found without a Gly at the third position, contrary to the energy calculations. Eight type VI bends with a cis Pro at the third position were also elucidated.     

Characterization of β-turns in cyclic hexapeptides in solution by fourier transform IR spectroscopy

The β-turn represents a structural element frequently encountered in globular proteins. However, in spite of various theoretical and experimental studies the ir signature bands of pure β-turns are still not established beyond doubt. Although considerable information exists now on the ir spectra of β-helical and β-sheet structures, the lack of knowledge concerning turn structures in general, and that of β-turns in particular, presents a major uncertainty in the estimation of global protein secondary structures from ir spectroscopic data. To obtain more specific information about the characteristic amide bands in β-turns, we report herein an ir spectroscopic analysis of a series of five cyclic pseudo-hexapeptides known to form β-turns from previous CD and nmr studies [A. Perczel, M. Hollósi, B. M. Foxman, and G. D. Fasman (1991) Journal of the American Chemical Society, Volume 113, pp. 9772-9784 ]. We show here that in these cyclic peptides the amide groups involved in β-turns that comprise a ten-membered hydrogen-bonded ring (and represent the first H-bond pair in a β-sheet), give rise to characteristic amide I bands in the range 1638–1646 cm^?1, with the exact position depending on the solvent and the nature of the side-chain substituents. © 1993 John Wiley & Sons, Inc.     

Vibrational analysis of peptides,polypeptides, and proteins. V. Normal vibrations of β-turns

The normal modes have been calculated for β-turns of types I, II, III, I′, II′, and III′. The complete set of frequencies is given for the first three structures; only the amide I, II, and III modes are given for the latter three structures. Calculations have been done for structures with standard dihedral angles, as well as for structures whose dihedral angles differ from these by amounts found in protein structures. The force field was that refined in our previous work on polypeptides. Transition dipole coupling was included, and is crucial to predicting frequency splittings in the amide I and amide II modes. The results show that in the amide I region, β-turn frequencies can overlap with those of the α-helix and β-sheet structures, and therefore caution must be exercised in the interpretation of protein bands in this region. The amide III modes of β-turns are predicted at significantly higher frequencies than those of α-helix and β-sheet structures, and this region therefore provides the best possibility of identifying β-turn structures. Amide V frequencies of β-turns may also be distinctive for such structures.     

Type I and II β-turns prediction using NMR chemical shifts

A method for predicting type I and II β-turns using nuclear magnetic resonance (NMR) chemical shifts is proposed. Isolated β-turn chemical-shift data were collected from 1,798 protein chains. One-dimensional statistical analyses on chemical-shift data of three classes β-turn (type I, II, and VIII) showed different distributions at four positions, (i) to (i + 3). Considering the central two residues of type I β-turns, the mean values of C_ο, C_α, H_N, and N_H chemical shifts were generally (i + 1) > (i + 2). The mean values of C_β and H_α chemical shifts were (i + 1) < (i + 2). The distributions of the central two residues in type II and VIII β-turns were also distinguishable by trends of chemical shift values. Two-dimensional cluster analyses on chemical-shift data show positional distributions more clearly. Based on these propensities of chemical shift classified as a function of position, rules were derived using scoring matrices for four consecutive residues to predict type I and II β-turns. The proposed method achieves an overall prediction accuracy of 83.2 and 84.2 % with the Matthews correlation coefficient values of 0.317 and 0.632 for type I and II β-turns, indicating that its higher accuracy for type II turn prediction. The results show that it is feasible to use NMR chemical shifts to predict the β-turn types in proteins. The proposed method can be incorporated into other chemical-shift based protein secondary structure prediction methods.     

How many hydrogen-bonded α-turns are possible?

The formation of α-turns is a possibility to reverse the direction of peptide sequences via five amino acids. In this paper, a systematic conformational analysis was performed to find the possible isolated α-turns with a hydrogen bond between the first and fifth amino acid employing the methods of ab initio MO theory in vacuum (HF/6-31G*, B3LYP/6-311?+?G*) and in solution (CPCM/HF/6-31G*). Only few α-turn structures with glycine and alanine backbones fulfill the geometry criteria for the i←(i?+?4) hydrogen bond satisfactorily. The most stable representatives agree with structures found in the Protein Data Bank. There is a general tendency to form additional hydrogen bonds for smaller pseudocycles corresponding to β- and γ-turns with better hydrogen bond geometries. Sometimes, this competition weakens or even destroys the i←(i?+?4) hydrogen bond leading to very stable double β-turn structures. This is also the reason why an “ideal” α-turn with three central amino acids having the perfect backbone angle values of an α-helix could not be localized. There are numerous hints for stable α-turns with a distance between the \( {{\hbox{C}}_\alpha } \)-atoms of the first and fifth amino acid smaller than 6-7 Å, but without an i←(i?+?4) hydrogen bond.     

On the location of β-turns

β-Turns are a common feature of cyclic peptides, but judging from recent x-ray and solution studies of cyclic hexapeptides it is not always possible to predict in advance the type of turn and the position of the turns in the sequence. Two or more backbone conformations containing β-turns may be of comparable energy and in rapid solvent- and temperature-dependent equilibrium in solution. The use of differential relaxation effects produced by a nitroxyl radical to locate β-turns with only minor perturbation of such equilibria is noted. Examination of the effect of a nitroxyl on the N-H resonances of the decapeptide hormone luteinizing hormone releasing hormone supports a dominant conformation with a β-turn at Gly⁶-Leu⁷. Although this turn is probably part of the biologically active conformation, it is not obvious in the more active [D -Ala⁶] analog.     

Introduction of a new scheme for classifying β-turns in protein structures

Protein β-turn classification remains an area of ongoing development in structural biology research. While the commonly used nomenclature defining type I, type II and type IV β-turns was introduced in the 1970s and 1980s, refinements of β-turn type definitions have been introduced as recently as 2019 by Dunbrack, Jr and co-workers who expanded the number of β-turn types to 18 (Shapovalov et al, PLOS Computat. Biol., 15, e1006844, 2019). Based on their analysis of 13 030 turns from 1074 ultrahigh resolution (≤1.2 Å) protein structures, they used a new clustering algorithm to expand the definitions used to classify protein β-turns and introduced a new nomenclature system. We recently encountered a specific problem when classifying β-turns in crystal structures of pentapeptide repeat proteins (PRPs) determined in our lab that are largely composed of β-turns that often lie close to, but just outside of, canonical β-turn regions. To address this problem, we devised a new scheme that merges the Klyne-Prelog stereochemistry nomenclature and definitions with the Ramachandran plot. The resulting Klyne-Prelog-modified Ramachandran plot scheme defines 1296 distinct potential β-turn classifications that cover all possible protein β-turn space with a nomenclature that indicates the stereochemistry of i + 1 and i + 2 backbone dihedral angles. The utility of the new classification scheme was illustrated by re-classification of the β-turns in all known protein structures in the PRP superfamily and further assessed using a database of 16 657 high-resolution protein structures (≤1.5 Å) from which 522 776 β-turns were identified and classified.     

Critical amino acids responsible for converting specificities of proteins and for enhancing enzyme evolution are located around β-turn potentials: Data-based prediction

Various reports have described that amino acid substitutions can alter substrate, positional, inhibitory, and target gene specificities of proteins. By using the method of Chou and Fasman, the present work predicts that critical amino acids for converting these specificities are located around β-turns. Residues responsible for the alterations of substrate specificities of trypsin,l-lactate dehydrogenase, aspartate aminotransferase, β-lactamase, and cytochrome P-450 are found to exist within regions predicted as β-turns. The ratios of hydroxylation and oxygenation positions of substrates by cytochrome P-450 and lipoxygenase, respectively, are varied by changes of the protein structures, probably around turn conformations. Inhibitory specificities of bovine pancreatic trypsin inhibitor and α₁-antitrypsin and target gene specificity of glucocorticoid receptor are converted by changing turn structures. Occurrence of β-turn probabilities can be predicted around the amino acid alteration positions of an evolutionally antecedent protein of a nylon degradation enzyme. These findings will have relevance to work on protein engineering and enzyme evolution.     

Structural features determining the site specificity of a rat liver cAMP-independent protein kinase.

The Seryl and Threonyl residues affected in α_s1 and in β-caseins by rat liver “casein kinase TS” (a cytosolic cAMP-independent protein kinase) have been identified. All of them, as well as the residues affected by the same enzyme in α_s2-casein are characterized by an acidic group two residues to their C terminus and by being located within predicted β-turns. Several other potential sites of phosphorylation, according to their primary structure, but located outside predicted β-turns, are not significantly labeled by the protein kinase. It seems conceivable therefore that both a definite aminoacid sequence including a critical acidic residue, and the existence of a β-turn are required for the activity of this protein kinase.     

Prediction of β-Turns

Kohonen's self-organization model, a neural network model, is applied to predict the β-turns in proteins. There are 455 β-turn tetrapeptides and 3807 non-β-turn tetrapeptides in the training database. The rates of correct prediction for the 110 β-turn tetrapeptides and 30,229 non-β-turn tetrapeptides in the testing database are 81.8% and 90.7%, respectively. The high quality of prediction of neural network model implies that the residue-coupled effect along a polypeptide chain is important for the formation of reversal turns, such as β-turns, during the process of protein folding.     

Insulin analogues with modifications in the β-turn of the B-chain

The β-turn formed by the amino acid residues 20–23 of the B-chain of insulin has been implicated as an important structural feature of the molecule. In other biologically active peptides, stabilization of β-turns has resulted in increases in activity. We have synthesized three insulin analogues containing modifications which would be expected to increase the stability of the β-turn. In two analogues, we have substituted α-aminoisobutyric acid (Aib) for the Glu residue normally present in position B21 or for the Arg residue normally present in position B22; in a third compound, we have replaced the Glu residue with its D-isomer. Biological evaluation of these compounds showed that [B21 Aib]insulin displays a potencyca. one-fourth that of natural insulin, while [B22 Aib]insulin is less than 10% as potent. In contrast, [B21 D-Glu]insulin is equipotent with natural insulin. We conclude that the β-turn region of the insulin molecule normally possesses considerable flexibility, which may be necessary for it to assume a conformation commensurate with high biological activity. If this is the case, [B21 D-Glu]insulin may exhibit a stabilized geometry similar to that of natural insulin when bound to the insulin receptor.     

Alpha-diaminobutyric acid-linked hairpin polyamides

A hairpin polyamide-chlorambucil conjugate linked by alpha-diaminobutyric acid (alpha-DABA) has been shown to have interesting biological properties in cellular and small animal models. Remarkably, this new class of hairpin polyamides has not been previously characterized with regard to energetics and sequence specificity. Herein we present a series of pyrrole-imidazole hairpin polyamides linked by alpha-DABA and compare them to polyamides containing the standard gamma-DABA turn unit. The alpha-DABA hairpins have overall decreased binding affinities. However, alpha-DABA polyamide-chlorambucil conjugates are sequence-specific DNA alkylators with increased specificities. Affinity cleavage studies of alpha-DABA polyamide-EDTA conjugates confirmed their preference for binding DNA in a forward hairpin conformation. In contrast, an unsubstituted glycine-linked polyamide prefers to bind in an extended binding mode. Thus, substitution on the turn unit locks the alpha-DABA polyamide into the forward hairpin binding motif.     

NetTurnP--neural network prediction of beta-turns by use of evolutionary information and predicted protein sequence features

β-turns are the most common type of non-repetitive structures, and constitute on average 25% of the amino acids in proteins. The formation of β-turns plays an important role in protein folding, protein stability and molecular recognition processes. In this work we present the neural network method NetTurnP, for prediction of two-class β-turns and prediction of the individual β-turn types, by use of evolutionary information and predicted protein sequence features. It has been evaluated against a commonly used dataset BT426, and achieves a Matthews correlation coefficient of 0.50, which is the highest reported performance on a two-class prediction of β-turn and not-β-turn. Furthermore NetTurnP shows improved performance on some of the specific β-turn types. In the present work, neural network methods have been trained to predict β-turn or not and individual β-turn types from the primary amino acid sequence. The individual β-turn types I, I', II, II', VIII, VIa1, VIa2, VIba and IV have been predicted based on classifications by PROMOTIF, and the two-class prediction of β-turn or not is a superset comprised of all β-turn types. The performance is evaluated using a golden set of non-homologous sequences known as BT426. Our two-class prediction method achieves a performance of: MCC=0.50, Qtotal=82.1%, sensitivity=75.6%, PPV=68.8% and AUC=0.864. We have compared our performance to eleven other prediction methods that obtain Matthews correlation coefficients in the range of 0.17-0.47. For the type specific β-turn predictions, only type I and II can be predicted with reasonable Matthews correlation coefficients, where we obtain performance values of 0.36 and 0.31, respectively. CONCLUSION: The NetTurnP method has been implemented as a webserver, which is freely available at http://www.cbs.dtu.dk/services/NetTurnP/. NetTurnP is the only available webserver that allows submission of multiple sequences.     

The structure of the ends of α-helices in globular proteins: effect of additional hydrogen bonds and implications for helix formation

We prepared a set of about 2000 α-helices from a relational database of high-resolution three-dimensional structures of globular proteins, and identified additional main chain i ← i+3 hydrogen bonds at the ends of the helices (i.e., where the hydrogen bonding potential is not fulfilled by canonical i ← i+4 hydrogen bonds). About one-third of α-helices have such additional hydrogen bonds at the N-terminus, and more than half do so at the C-terminus. Although many of these additional hydrogen bonds at the C-terminus are associated with Schellman loops, the majority are not. We compared the dihedral angles at the termini of α-helices having or lacking the additional hydrogen bonds. Significant differences were found, especially at the C-terminus, where the dihedral angles at positions C2 and C1 in the absence of additional hydrogen bonds deviate substantially from those occurring within the α-helix. Using a novel approach we show how the structure of the C-terminus of the α-helix can emerge from that of constituent overlapping α-turns and β-turns, which individually show a variation in dihedral angles at different positions. We have also considered the direction of propagation of the α-helix using this approach. If one assumes that helices start as a single α-turn and grow by successive addition of further α-turns, the paths for growth in the N → C and C → N directions differ in a way that suggests that extension in the C → N direction is favored.     

2-Alkyl-2-carboxyazetidines as γ-turn inducers: incorporation into neurotrophin fragments

Conveniently substituted 2-alkyl-2-carboxyazetidine amino acids have been incorporated into NGF and NT3 tetrapeptide sequences to investigate their utility as reverse turn inducers (γ- vs. β-turns). Despite the presence of an Asp residue at i position, highly preferred in β-turns, molecular modeling and NMR studies indicated that the azetidine-containing peptides mainly stabilized γ-turn conformations.     

Conformational energy calculations on glycosylated turns in glycoproteins

Analysis of the amino acid sequence of glycoproteins has suggested the β-turn as a likely site of glycosylation in glycoproteins. According to this model, the peptide chain traverses the interior of a globular protein, reversing its direction at the protein surface, a likely point for the attachment of hydrophilic carbohydrate residues. In order to search for plausible conformations of glycosylated β-turns in asparagine-linked glycoproteins, we have adapted the conformational energy calculation method of Scheraga and coworkers for use in carbohydrates. The parameters for nonbonded and hydrogen-bonded interactions have been published, and electrostatic parameters are derived from a CNDO calculation on a model glycopeptide. Our results indicate that the orientation of the glycosyl amide bond having the amide proton nearly trans to the anomeric proton of the sugar has the lowest energy. Although CD and nmr experiments in our laboratory have consistently found this conformation, our calculations show the conformation having these two protons in a cis relationship to lie very close in energy. Calculations on the glycopeptide linkage model, α-N-acetyl, δ-N(2-acetamido-1,2-dideoxy-β-D -glucopyranosyl)-N′-methyl-L -asparaginyl amide show that several distinct geometries are allowed for glycosylated β-turns. For a type I β-turn, three conformations of the glycosylated side chain are found within 4 kcal of the minimum, while two conformations of the glycosylated side chain are allowed for a type II turn. The hydrogen-bonded C7 conformation is also allowed. Stereoviews of the low-energy conformations reveal no major hydrogen-bonding interaction between the peptide and sugar.     

Conformational difference between diastereomers of Dnp-Val-Aib-Gly-Leu-pNA studied by x-ray crystal analyses

In order to investigate the Conformational change of the α-aminoisobutyric acid (Aib) containing peptide by the D /L replacement of an amino acid residue, single crystals of two diastereomers, Dnp-L -Val-Aib-Gly-L -Leu-pNA (L -L isomer) and Dnp-D -Val-Aib-Gly-L -Leu-pNA (D -L isomer), were prepared from aqueous methanol solutions as CH₃OH and CH₃OH · H₂O solvates, respectively, and were analyzed by the x-ray diffraction method. Molecular conformation of L -L isomer adopts consecutive two different types of β-turns, a type II′ β-turn bent at Aib-Gly, and a type III β-turn bent at Gly-Leu, stabilized by two intramolecular (Leu) NH …? O?C (Val) and (pNA) NH …? O?C(Aib) hydrogen bonds. In contrast, these two intramolecular hydrogen bonds lead the D -L isomer to a distorted 3₁₀-helix conformation consisting of consecutive two type-III β-turn of Aib-Gly-Leu sequence. The most significant structural difference between these diastereomers is the mutual orientation between the Dnp and pNA chromophores. While the extensive stacking of both the chromophores is intramolecularly formed for the folded conformation of L -L isomer, they are oriented toward an opposite direction in the open conformation of D -L isomer and are intermolecularly stacked with each other. The large separation between these diastereomers observed in the chromatography is discussed in the relation with their Conformational differences. © 1993 John Wiley & Sons, Inc.     

Highly constrained dipeptoid analogues containing a type II′ β-turn mimic as novel and selective CCK-A receptor ligands

Conformationally constrained dipeptoid analogues containing the type II′ β-turn mimic (2S,5S,11bR)-2-amino-3-oxohexahydroindolizino[8,7-b]indole-5-carboxylate framework in place of the α-MeTrp residue, show high binding affinity and selectivity for CCK-A receptors, suggesting that a turn-like conformation could contribute to the bioactive conformation at this CCK receptor subtype.     

Classification and Prediction of β-Turn Types

Although a β-turn consists of only four amino acids, it assumes many different types in proteins. Is this basically dependent on the tetrapeptide sequence alone or is it due to a variety of interactions with the other part of a protein? To answer this question, a residue-coupled model is proposed that can reflect the sequence-coupling effect for a tetrapeptide in not only a β-turn or non-β-turn, but also different types of a β-turn. The predicted results by the model for 6022 tetrapeptides indicate that the rates of correct prediction for β-turn types I, I′, II, II′, VI, and VIII and non-β-turns are 68.54%, 93.60%, 85.19%, 97.75%, 100%, 88.75%, and 61.02%, respectively. Each of these seven rates is significantly higher than $\frac{1}{7}$ = 14.29%, the completely randomized rate, implying that the formation of different β-turn types or non-β-turns is considerably correlated with the sequences of a tetrapeptide.