Conservation of chain reversal regions in proteins.

Using the bend frequencies based on 29 proteins in the previous paper (Chou and Fasman, 1979), beta-turn probability profiles were calculated for the C-peptides of 10 mammalian proinsulins, for 7 proteinase inhibitors, and for 12 species of pancreatic ribonucleases. Beta-turn correlation coefficient matrix tables were also computed to obtain the statistical mean between 45 pairs of proinsulin C-peptides, less than Ct greater than = 0.57 +/- 0.31; 21 pairs of proteinase inhibitors, less than Ct greater than = 0.73 +/- 0.13; and 66 pairs of ribonucleases, less than Ct greater than = 0.83 +/- 0.08. Despite relatively low sequence conservation in these three sets of proteins, beta-turns were predicted to be highly conserved: 33% sequence vs. 78% bend for the proinsulins, 20% sequence vs. 85% bend for the proteinase inhibitors, and 65% sequence vs. 92% bend for the ribonucleases. These results suggest that chain reversal regions play an essential role in keeping the active structural domains in hormones and enzymes intact for their specific biological function.     

Computer prediction of potential immunogenic determinants from protein amino acid sequence

In proteins, immunogenic determinants that can induce protein-reactive antipeptide antibodies reside mostly in those parts of the molecule that have a high tendency to form beta-turns. A program for an IBM personal computer which predicts protein immunogenic determinants is described. The program predicts potential immunogenic determinants from protein amino acid sequences according to a Chou-Fasman-based probability of a beta-turn occurrence, p greater than 1.5 X 10(-4)(P. Y. Chou and G. D. Fasman, 1978, Adv. Enzymol. 47, 46-148). Oncopeptides (whose efficacy in generating protein-reactive antipeptide antibodies has been described) with a beta-turn probability of p greater than 1.5 X 10(-4) elicited antipeptide antibodies that reacted with the parent oncoprotein at a rate of 96%, thus showing a surprisingly good correlation between the tendency to form a beta-turn and the protein reactivity of antipeptide antibodies. Potential immunogenic determinants were predicted on myohemerythrin and myoglobin.     

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.     

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.     

Critical amino acids of p21 protein are located within beta-turns: further evaluation

It has been shown that malignant activation of ras proto-oncogenes was mediated by point mutations which resulted in the single amino acid conversions at positions 12, 13 or 61 of the ras gene products (p21 proteins). By analyzing randomly mutated ras genes, it has been demonstrated that amino acid substitutions at residues 12, 13, 59 and 63 activated p21. Furthermore, it has been shown that residues 16, 116 and 119 in p21 played critical roles in the guanine nucleotide binding and, consequently, the ability of the protein to induce changes characteristic of cellular transformation. By using the protein conformational prediction method of Chou and Fasman, the present work predicts that these critical amino acids, except glutamic acid at position 63, are located within beta-turns. The major "hot spots" for ras activation are codons 12 and 61. The author has predicted in an earlier paper that the single amino acid conversions at positions 12 and 61 would occur at beta-turn conformation consisting of residues 10-13 and 58-61, respectively. In the present study, probabilities of beta-turn occurrence at residues 10-13 or 58-61 of the p21 proteins encoded by various ras genes are compared. The probability for the normal p21 containing glycine as residue 12 is greatest, and the cancer-associated variants show less probabilities. The single amino acid substitutions at position 61 do not cause so decreased probabilities of beta-turn potential at residues 58-61, except the replacement by histidine. Histidine at position 61 is not predicted as occurring within a beta-turn.(ABSTRACT TRUNCATED AT 250 WORDS)     

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.     

Effect of temperature on the circular dichroism spectra of beta 2-microglobulins

When the temperature was lowered from 25 to 5 degrees C dramatic changes were observed in the near-ultraviolet circular dichroism spectra of bovine and caprine but not human beta 2-microglobulin. Comparison of the protein sequences suggests that the conformational change occurs in the amino-terminal 24 residues and that a tyrosine residue located on a potential beta-turn acts as a reporter group. Because delta H degrees is small (-22 kcal X mol-1), such conformational changes, possibly not readily observed, may occur at low temperatures in other proteins having potential beta-turns in otherwise aperiodic regions of sequence.     

A neural network method for prediction of beta-turn types in proteins using evolutionary information

MOTIVATION: The prediction of beta-turns is an important element of protein secondary structure prediction. Recently, a highly accurate neural network based method Betatpred2 has been developed for predicting beta-turns in proteins using position-specific scoring matrices (PSSM) generated by PSI-BLAST and secondary structure information predicted by PSIPRED. However, the major limitation of Betatpred2 is that it predicts only beta-turn and non-beta-turn residues and does not provide any information of different beta-turn types. Thus, there is a need to predict beta-turn types using an approach based on multiple sequence alignment, which will be useful in overall tertiary structure prediction. RESULTS: In the present work, a method has been developed for the prediction of beta-turn types I, II, IV and VIII. For each turn type, two consecutive feed-forward back-propagation networks with a single hidden layer have been used where the first sequence-to-structure network has been trained on single sequences as well as on PSI-BLAST PSSM. The output from the first network along with PSIPRED predicted secondary structure has been used as input for the second-level structure-to-structure network. The networks have been trained and tested on a non-homologous dataset of 426 proteins chains by 7-fold cross-validation. It has been observed that the prediction performance for each turn type is improved significantly by using multiple sequence alignment. The performance has been further improved by using a second level structure-to-structure network and PSIPRED predicted secondary structure information. It has been observed that Type I and II beta-turns have better prediction performance than Type IV and VIII beta-turns. The final network yields an overall accuracy of 74.5, 93.5, 67.9 and 96.5% with MCC values of 0.29, 0.29, 0.23 and 0.02 for Type I, II, IV and VIII beta-turns, respectively, and is better than random prediction. AVAILABILITY: A web server for prediction of beta-turn types I, II, IV and VIII based on above approach is available at http://www.imtech.res.in/raghava/betaturns/ and http://bioinformatics.uams.edu/mirror/betaturns/ (mirror site).     

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.     

Increasing protein conformational stability by optimizing beta-turn sequence

Protein conformational stability is an important concern in many fields. Here, we describe a strategy for significantly increasing conformational stability by optimizing beta-turn sequence. Proline and glycine residues are statistically preferred at several beta-turn positions, presumably because their unique side-chains contribute favorably to conformational stability in certain beta-turn positions. However, beta-turn sequences often deviate from preferred proline or preferred glycine. Therefore, our strategy involves replacing non-proline and non-glycine beta-turn residues with preferred proline or preferred glycine residues. Here, we develop guidelines for selecting appropriate mutations, and present results for five mutations (S31P, S42G, S48P, T76P, and Q77G) that significantly increase the conformational stability of RNase Sa. The increases in stability ranged from 0.7 kcal/mol to 1.3 kcal/mol. The strategy was successful in overlapping or isolated beta-turns, at buried (up to 50%) or completely exposed sites, and at relatively flexible or inflexible sites. Considering the significant number of beta-turn residues in every globular protein and the frequent deviation of beta-turn sequences from preferred proline and preferred glycine residues, this simple, efficient strategy will be useful for increasing the conformational stability of proteins.     

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.     

Tandemly repeating peptide motifs and their secondary structure in Ceratitis capitata eggshell proteins Ccs36 and Ccs38.

Evidence from amino acid composition, Fourier transform analysis of primary structure and secondary structure prediction suggests a tripartite structure for Ceratitis capitata eggshell proteins Ccs36 and Ccs38, which consists of a central domain and two flanking 'arms'. The proteins, apparently, contain tandemly repeating peptide motifs specific for each domain of the tripartite structure. The central domain of both proteins, which exhibits extensive sequence homology with the corresponding domains of Drosophila melanogaster proteins s36 and s38, is formed by tandem repeats of an octapeptide-X-X-X-Z-Z-Z-Z-Z- (where X = large hydrophobic residue and Z = beta-turn former residue) and its variants. It is predicted to adopt a compact, most probably twisted, antiparallel beta-pleated sheet structure of beta-sheet strands regularly alternating with beta-turns or loops. The central domains of Ccs36 and Ccs38 share structural similarities, but they are recognizably different. The 'arms' of the proteins presumably serving for protein and species-specific functions differ substantially from those of Drosophila melanogaster. In Ccs36, the C-terminal 'arm' is formed by, almost precise, tandem repeats of an octapeptide-Y-X-A-A-P-A-A-S- (X = G or S), whereas the N-terminal 'arm' contains repeats of the octapeptide -Z-Z-Z-A-X-A-A-Z- (X = Q, N or E and Z a beta-turn former). In both 'arms' alpha-helices are predicted, alternating with beta-turns.(ABSTRACT TRUNCATED AT 250 WORDS)     

Analysis of gammabeta, betagamma, gammagamma, betabeta multiple turns in proteins.

The number of gamma-turns in a representative protein dataset selected from the current Protein Data Bank has increased almost seven times during the past decade. Eighty percent classic gamma-turns and 57% inverse gamma-turns are associated as multiple turns with either another y-turn or a beta-turn. We refer to these as multiple turns of the (gammabeta)1,2,3 or (betagamma)1,2,3 type, depending upon whether the gamma-turn is before or after the beta-turn along the protein chain, respectively. However, for multiple turns involving only gamma-turns, we follow the nomenclature analogous to that proposed earlier for the multiple (or double) beta-turns. Fifty-eight per cent beta-turns are associated as multiple turns with another beta-turn. We extracted multiple turns from the protein dataset and classified them on the basis of individual gamma- or beta-turn types and the number of overlapping residues. Furthermore, we evaluated the amino acid positional potentials and determined the statistically significant amino acid preferences, hydrogen bond/side-chain interaction preferences in the multiple turns and secondary structure preferences for residues immediately flanking these turns. The results of our analysis would be useful in the modeling, prediction or design of multiple turns in proteins. The amino acid sequence corresponding to the multiple turn, position in the protein chain, PDB Code/chain in which multiple turn is present and the individual turn types constituting the multiple turns are available from our website and this information would also be integrated in our Database of Structural Motifs in Proteins (http://www.cdfd.org.in/dsmp.html).     

The insulin receptor juxtamembrane region contains two independent tyrosine/beta-turn internalization signals

We have investigated the role of tyrosine residues in the insulin receptor cytoplasmic juxtamembrane region (Tyr953 and Tyr960) during endocytosis. Analysis of the secondary structure of the juxtamembrane region by the Chou-Fasman algorithms predicts that both the sequences GPLY953 and NPEY960 form tyrosine-containing beta-turns. Similarly, analysis of model peptides by 1-D and 2-D NMR show that these sequences form beta-turns in solution, whereas replacement of the tyrosine residues with alanine destabilizes the beta-turn. CHO cell lines were prepared expressing mutant receptors in which each tyrosine was mutated to phenylalanine or alanine, and an additional mutant contained alanine at both positions. These mutations had no effect on insulin binding or receptor autophosphorylation. Replacements with phenylalanine had no effect on the rate of [125I]insulin endocytosis, whereas single substitutions with alanine reduced [125I]insulin endocytosis by 40-50%. Replacement of both tyrosines with alanine reduced internalization by 70%. These data suggest that the insulin receptor contains two tyrosine/beta-turns which contribute independently and additively to insulin-stimulated endocytosis.     

Assessing computational amino acid beta-turn propensities with a phage-displayed combinatorial library and directed evolution

Structure propensities of amino acids are important determinants in guiding proteins' local and global structure formation. We constructed a phage display library--a hexa-HIS tag upstream of a CXXC (X stands for any of the 20 natural amino acids) motif appending N-terminal to the minor capsid protein pIII of M13KE filamentous phage--and developed a novel directed-evolution procedure to select for amino acid sequences forming increasingly stable beta-turns in the disulfide-bridged CXXC motif. The sequences that emerged from the directed-evolution cycles were in good agreement with type II beta-turn propensities derived from surveys of known protein structures, in particular, Pro-Gly forming a type II beta-turn. The agreement strongly supported the notion that beta-turn formation plays an active role in initiating local structure folding in proteins.     

NMR studies of the structure and dynamics of peptide E, an endogenous opioid peptide that binds with high affinity to multiple opioid receptor subtypes

Structural and dynamic properties of opioid peptide E have been examined in an sodium dodecyl sulfate (SDS) micelle. Structural and dynamic studies both indicate that this peptide exhibits greater segmental mobility than typical structured proteins. An nmr structural analysis of adrenal peptide E in SDS micelles indicated the presence of two well-defined beta-turns, one at the N-terminus encompassing residues 3 to 6, and the second in the region between residues 15 and 18. Certain side chain dihedral angles were also remarkably well defined, such as the chi 1 angle of F4, which exhibited a trans configuration. These calculated structures were based on a set of 9.5 restraints per residue. The backbone dynamics of peptide E in SDS micelles were examined through an analysis of 15N-relaxation parameters. An extended model-free analysis was used to interpret the relaxation data. The overall rotational correlation time is 19.7 ns. the average order parameter S2 is 0.66 +/- 0.15. The N-terminal loop region residues including G3 to R6 have an average order parameter of 0.70 +/- 0.23. The average order parameter lies somewhere between that observed for a random coil (e.g., S2 = 0.3) and that of a well-defined tertiary fold (e.g., S2 = 0.86). This suggests that peptide E in SDS micelles adopts a restricted range of conformations rather than a random coil. Based on the helical structure recently obtained for the highly homologous kappa-agonist dynorphin-A(1-17) and the beta-turn in the same region of peptide E, it is reasonable to assume that these two elements of secondary structure reflect different receptor subtype binding geometries. The intermediate order parameters observed for peptide E in an SDS micelle suggest a degree of dynamic mobility that may enable facile interconversion between helical and beta-turn geometries in the N-terminal agonist domain.     

Solution structure of the RWD domain of the mouse GCN2 protein

GCN2 is the alpha-subunit of the only translation initiation factor (eIF2alpha) kinase that appears in all eukaryotes. Its function requires an interaction with GCN1 via the domain at its N-terminus, which is termed the RWD domain after three major RWD-containing proteins: RING finger-containing proteins, WD-repeat-containing proteins, and yeast DEAD (DEXD)-like helicases. In this study, we determined the solution structure of the mouse GCN2 RWD domain using NMR spectroscopy. The structure forms an alpha + beta sandwich fold consisting of two layers: a four-stranded antiparallel beta-sheet, and three side-by-side alpha-helices, with an alphabetabetabetabetaalphaalpha topology. A characteristic YPXXXP motif, which always occurs in RWD domains, forms a stable loop including three consecutive beta-turns that overlap with each other by two residues (triple beta-turn). As putative binding sites with GCN1, a structure-based alignment allowed the identification of several surface residues in alpha-helix 3 that are characteristic of the GCN2 RWD domains. Despite the apparent absence of sequence similarity, the RWD structure significantly resembles that of ubiquitin-conjugating enzymes (E2s), with most of the structural differences in the region connecting beta-strand 4 and alpha-helix 3. The structural architecture, including the triple beta-turn, is fundamentally common among various RWD domains and E2s, but most of the surface residues on the structure vary. Thus, it appears that the RWD domain is a novel structural domain for protein-binding that plays specific roles in individual RWD-containing proteins.     

A non-intuitive design of a cyclic decapeptide library with unique backbone structural features

An analysis of hydrogen bonding patterns of cyclic decapeptide (CDP) beta-sheet structures has resulted in a 'non-intuitive' design of cyclic decapeptides wherein their beta-turns and residue positions can be fixed by choosing 2 of the 10 residues, i.e. positions i and i+4, to be Prolines or N-substituted residues. This sequence relationship between the two Pro or N-substituted residues is shown to uniquely define the conformation of the CDP. Furthermore, this design of the 2 beta-turn, beta-sheet CDP structure is expected to be characterised by residues disposed in an exclusive fashion in which four residues are on one side of the ring, two on the other and the four corner residues in the beta-turn are in the plane of the ring. This opens up the possibility of fine-tuning the four residues facing one way and /or the two residues facing the other way such that a library containing a myriad of chemically diverse systems could be obtained. The design process along with the molecular modelling of specific CDP-s and the building of a CDP library are discussed in detail.