Β-turn Type Research Articles

Total Synthesis of Cyclosenegalin A.

A Pro-Gly-typed cyclopeptide, cyclosenegalin A, was firstly isolated from Annona senegalensis and Annona scleroderma. In this study, we reported synthesis the cycloheptapeptide with a combination of solid- and solution-phase synthetic methods. This study also compared the effectiveness of β-turn inducer type I and II in cyclosenegalin A to facilitate the cyclization process. The synthesis of cyclosenegalin A were prepared using two different sequences of linear peptides for cyclization. First sequence employed β-turn type I inducer (Ser-Ala-Val-Thr) as turning point and second sequence employed β-turn type II inducer (Thr-Pro-Gly-Leu). The successful cyclization was obtained using the linear sequence of NH2-Ala-Val-Thr-Pro-Gly-Leu-Ser-OH with β-turn type II. The final product was obtained in 8.2 % yield with PyBOP/DIEA act as coupling agent. The synthetic cyclosenegalin A were characterized with HR-ToFMS, 1H NMR, 13C NMR, HSQC, HMBC, TOCSY, and ROESY. The synthetic product was also evaluated for its antimicrobial activity.

Self-assembly of FRV3FR peptide into supramolecular nanofibrils

Small peptides are commonly used monomers for the self-assembly of biologically relevant supramolecular nanomaterials. In this study, the heptameric sequence FRV3FR was found to self-assemble into nanofibrils in solution, as confirmed by transmission electron microscopy (TEM), leading to the subsequent formation of hydrogels. Circular dichroism (CD) analysis showed that the FRV3FR peptide adopts a secondary structure that closely resembles a β-turn type conformation. An alanine-based peptide termed FRA3FR was also studied to highlight the impact of the middle amino acid triad has in self-assembly. Even though the FRA3FR showed a similar CD signal, it failed to provide any significant nanostructure or hydrogel formation, demonstrating the ability valine residues over alanine in promoting self-assembly. This work presents preliminary studies on a novel peptide sequence, laying the groundwork for its potential development into a functional peptide-based nanomaterial.

Conformational aspects in the formation of structures of the backbone of polypeptide chains in proteins. Relationship between conformational stability/lability and β-turns

To assess the nature of the relationship between the integral conformational stability of tetrapeptides and the main types of β-turns (which are also tetrapeptides), calculations were performed using spectrum diagrams and asymmetry in the distribution of conformationally stable and unstable tetrapeptides. It was shown that type I', II, and II' β-turns are comprised of predominantly conformationally labile peptides, that is consistent with the predetermined nature of their structure as described earlier. As previously shown in our study, in this case the conformation is imposed by external conditions (namely the cycle closuring) and the prevalence of conformationally labile peptides facilitates the formation of the structure by virtue of external factors. Type I β-turn is an exception: peptides with different conformational lability are fairly evenly distributed. Most likely, this indicates that the formation of the type I β-turn is not predetermined.

A Perspective on the (Rise and Fall of) Protein β-Turns.

The β-turn is the third defined secondary structure after the α-helix and the β-sheet. The β-turns were described more than 50 years ago and account for more than 20% of protein residues. Nonetheless, they are often overlooked or even misunderstood. This poor knowledge of these local protein conformations is due to various factors, causes that I discuss here. For example, confusion still exists about the assignment of these local protein structures, their overlaps with other structures, the potential absence of a stabilizing hydrogen bond, the numerous types of β-turns and the software’s difficulty in assigning or visualizing them. I also propose some ideas to potentially/partially remedy this and present why β-turns can still be helpful, even in the AlphaFold 2 era.

Single-conformation spectroscopy of cold, protonated DPG-containing peptides: switching β-turn types and formation of a sequential type II/II′ double β-turn

Protonated DP and LP diastereomers of the pentapeptide YAPGA were examined with IR–UV spectroscopy for their ability to form β-turns.

Unusual Pseudopeptides: Syntheses and Structural Analyses of Ethylenediprolyl Peptides and Their Metal Complexes with Cu(II) Ion.

The synthetic unnatural amino acids and their peptides as peptidomimetics have shown remarkable structural and functional properties. In the repertoire of synthetic peptides, pseudopeptides have emerged as attractive small peptidomimetics that are capable of forming the characteristic secondary structures in the solid/solution phase, as in natural peptides. This report describes the synthesis and structural analyses of novel pseudopeptides as ethylenediprolyl (etpro) tetra/hexapeptides, comprising a chiral diaminedicarboxylate scaffold. Their NMR and CD spectral analyses strongly support the formation of the β-turn-type structures in organic solvents (ACN/MeOH). Further, the single-crystal X-ray studies of tetrapseudopeptide confirm the formation of a unique self-assembly structure as β-strand type in the solid state through hydrogen bonding. Importantly, their diamine moiety influences the formation of Cu-complexes with Cu(II) ions. A tetrapseudopeptide monocarboxylate-Cu(II) complex forms the single crystal that is studied by the single-crystal X-ray diffractometer. The crystal structure of the tetrapseudopeptide-Cu(II) complex confirms the formation of the distorted square planar geometry structure, almost like the amyloid β(Aβ)-peptide-Cu(II) complex structural geometry. Hence, these etpro-pseudopeptides are emerging peptidomimatics that form β-turn types of structures and metal complexes mainly with Cu(II) ions. These molecules could be considered for the development of peptide-based catalysts and peptide-based therapeutic drug candidates.

Insights into the composition, structure-function relationship, and molecular organization of surfactants from spent coffee grounds

Macromolecular/polymeric constituents of surfactants and their self-assembly in aqueous solutions play a key role in their technologically relevant application such as stabilization of foams and emulsions. However, such information on coffee-based surfactants is scarce. The present study is first-of-its-kind in elucidating the chemical and molecular fingerprints of surfactants derived from spent coffee grounds (SCG). Initial part of the study involved estimation of the total proteins and sugars, and monosaccharide composition of high (HMW) and low molecular weight (LMW) surfactants derived from dry and defatted SCG, which in turn is the residue obtained after hot water brewing of roasted Robusta and Arabica coffee granules. The HMW surfactants had higher protein and sugar contents that were directly related to their foamability and foam stability, respectively. Mannose and arabinose were the major sugars identified in HMW surfactants. LMW surfactants showed lower protein and sugar contents and absence of arabinose. Thus, only the HMW surfactants were subjected to MALDI-TOF mass spectrometry, LC-MS-MS based protein profiling, circular dichroism spectroscopy, and small-angle X-ray scattering. The presence of quercetin-sugar complexes, protease, transferase, and acylated proteins and a β-turn type protein secondary structure were detected in the SCG-surfactants. The transition from lamellar to rod-shaped micellar structures was observed when the surfactant concentration in aqueous solution was increased from a lower concentration to its critical micelle concentration (0.2%–0.8%, w/v).

Developability Assessment of an Isolated CH2 Immunoglobulin Domain.

The IgG CH2 domain continues to hold promise for the development of new therapeutic entities because of its bifunctional role as a biomarker and effector protein. The need for further understanding of molecular stability and aggregation in therapeutic proteins has led to the development of a breakthrough quantum cascade laser microscope to allow for real-time comparability assessment of an array of related proteins in solution upon thermal perturbation. Our objective was to perform a comprehensive developability assessment of three similar monoclonal antibody (mAb) fragments: CH2, CH2s, and m01s. The CH2 construct consists of residues Pro238 to Lys340 of the IgG1 heavy chain sequence. CH2s has a 7-residue deletion at the N-terminus and a 16-residue C-terminal extension containing a histidine tag. The m01s construct is identical to CH2s, except for two cysteines introduced at positions 242 and 334. A series of hyperspectral images was acquired during thermal perturbation from 28 to 60 °C for all three proteins in an array. Co-distribution and two-dimensional infrared correlation spectroscopies yielded the mechanism of aggregation and stability for these three proteins. The level of detail is unprecedented, identifying the regions within CH2 and CH2s that are prone to self-association and establishing the differences in stability. Furthermore, CH2 helical segments, β-sheets, β-turns, and random coil regions were less stable than in CH2s and m01s because of the presence of the N-terminal 310-helix and β-turn type III. The engineered disulfide bridge in m01s eliminated the self-association process and rendered this mAb fragment the most stable.

Structural preferences of cysteine sulfinic acid: The sulfinate engages in multiple local interactions with the peptide backbone

Cysteine sulfinic acid (Cys-SO2–) is a non-enzymatic oxidative post-translational modification (PTM) that has been identified in hundreds of proteins. However, the effects of cysteine sulfination are in most cases poorly understood. Cys-SO2– is structurally distinctive, with long sulfur-carbon and sulfur-oxygen bonds, and with tetrahedral geometry around sulfur due to its lone pair. Cys-SO2– thus has a unique range of potential interactions with the protein backbone which could facilitate protein structural changes. Herein, the structural effects of cysteine oxidation to the sulfinic acid were investigated in model peptides and folded proteins using NMR spectroscopy, circular dichroism, bioinformatics, and computational studies. In the PDB, Cys-SO2– shows a greater preference for α-helix than Cys. In addition, Cys-SO2– is more commonly found in structures with φ > 0, including in multiple types of β-turn. Sulfinate oxygens engage in hydrogen bonds with adjacent (i or i + 1) amide hydrogens. Over half of sulfinates have at least one hydrogen bond with an adjacent amide, and several structures have hydrogen bonds with both adjacent amides. Alternately, sulfur or either oxygen can act as an electron donor for n→π* interactions with the backbone carbonyl of the same residue, as indicated by frequent S⋯CO or O⋯CO distances below the sums of their van der Waals radii in protein structures. In peptides, Cys-SO2– favored α-helical structure at the N-terminus, consistent with helix dipole effects and backbone hydrogen bonds with the sulfinate promoting α-helix. Cys-SO2– has only modestly greater polyproline II helix propensity than Cys-SH, likely due to competition from multiple side chain-backbone interactions. Cys-SO2– stabilizes the i+1 position of a β-turn relative to Cys-SH. Within proteins, the range of side chain-main chain interactions available to Cys-SO2– compared to Cys-SH provides a basis for potential changes in protein structure and function due to cysteine oxidation to the sulfinic acid.

Response of enhanced sludge methanogenesis by red mud to temperature: Spectroscopic and electrochemical elucidation of endogenous redox mediators

Adding conductive materials can promote methanogenesis via facilitating electron exchange between syntrophic bacteria and methanogenic archaea. However, little is known about how temperature would interact with such an addition and thus affect the compositions and characteristics of endogenous redox mediators (ERMs). In particular, it is of strong interest to understand how the temperature variation would affect the improvement on methanogenesis induced by ERMs with conductive materials. Herein, we have investigated the response of sludge methanogenesis to temperature variation (from 15 to 35 °C) and spectroscopically detected the ERMs induced by conductive red mud. It was demonstrated that the increasing temperature enhanced the stimulating effect of conductive red mud on methane accumulation, and the methane production potential showed a linear relationship with redox parameters such as areal capacitance (Ca), free charges (R2) and electron exchange capacity (EEC). 2DCOS spectra further indicated that ν(C-O) and δ(O-H) in humic acids, β-turn type III amide I νs(C=O) in Cytochrome c, and δ(C-H) in amines and lipids became the main redox groups in ERMs at 35 °C with the addition of red mud. The model revealed that the contribution of ERMs to the CO2 reduction to CH4 increased from 35.2 ± 1.4% to 58.6 ± 1.5% when the temperature increased from 15 to 35 °C. Our finding that conductive materials stimulated the formation and electroactivity of ERMs with the increasing temperature during anaerobic digestion can have important implications for the improvement of engineered methanogenic processes.

Specific β-Turns Precede PPIIL Structures Binding to Allele-Specific HLA-DRβ1* PBRs in Fully-Protective Malaria Vaccine Components.

The 3D structural analysis of 62 peptides derived from highly pathogenic Plasmodium falciparum malaria parasite proteins involved in host cell invasion led to finding a striking association between particular β-turn types located in the N-terminal peripheral flanking residue region (preceding the polyproline II left-handed structures fitting into the HLA-DRβ* allele family) and modified immune protection-inducing protein structure induced long-lasting protective immunity. This is the first time association between two different secondary structures associated with a specific immunological function has been described: full, long-lasting protective immunity.

Parameterization and Analysis of Peptide-Based Catalysts for the Atroposelective Bromination of 3-Arylquinazolin-4(3H)-ones.

We report the development of a method to parameterize and predict the performance of structurally flexible β-turn-containing peptide catalysts, using the atroposelective bromination of 3-arylquinazolin-4(3H)-ones as a case study. The multivariate correlations obtained for tetrapeptides of two β-turn types, type I' pre-helical and type II' β-hairpin, indicate that although one conformer may be associated with a more dominant contribution to the observed enantioselectivity, it is possible that multiple conformers contribute to a complex transition state ensemble.

Analyzing Structural Properties of Heterogeneous Cardiolipin-Bound Cytochrome C and Their Regulation by Surface-Enhanced Infrared Absorption Spectroscopy.

Apoptotic mechanisms are not fully understood due to limitations in present analytical methods. Such understanding may be advanced by unravelling the structural properties of heterogeneous cardiolipin (CL)-bound cytochrome c (cyt c) and the factors or events that regulate them. In this study, surface-enhanced infrared absorption spectroscopy (SEIRAS) was employed to probe the adsorption of cyt c on CL membranes in biomimetic conditions. The results clearly show that pure electrostatic interactions result in the unfolding of partial α-helices, while the synergy between hydrogen bonding and electrostatic interactions governs orientation homogeneity of adsorbed protein, and conformational transition between α-helices and β-sheet. Hydrogen bonding plays a dual role; along with hydrophobic interactions, it may disturb the microenvironment of some secondary structures such as the β-turn type III, while it also triggers structural changes in lipid molecules likely resulting from the extension of CL acyl chains to the hydrophobic channels of cyt c. These findings provide the details of protein transitions in early apoptosis at the molecular level.

Extension of the classical classification of β-turns.

The functional properties of a protein primarily depend on its three-dimensional (3D) structure. These properties have classically been assigned, visualized and analysed on the basis of protein secondary structures. The β-turn is the third most important secondary structure after helices and β-strands. β-turns have been classified according to the values of the dihedral angles φ and ψ of the central residue. Conventionally, eight different types of β-turns have been defined, whereas those that cannot be defined are classified as type IV β-turns. This classification remains the most widely used. Nonetheless, the miscellaneous type IV β-turns represent 1/3rd of β-turn residues. An unsupervised specific clustering approach was designed to search for recurrent new turns in the type IV category. The classical rules of β-turn type assignment were central to the approach. The four most frequently occurring clusters defined the new β-turn types. Unexpectedly, these types, designated IV1, IV2, IV3 and IV4, represent half of the type IV β-turns and occur more frequently than many of the previously established types. These types show convincing particularities, in terms of both structures and sequences that allow for the classical β-turn classification to be extended for the first time in 25 years.

Descriptive statistics of disallowed regions and various protein secondary structures in the context of studying twisted β-hairpins

A detailed analysis of polypeptide-chain backbone conformations was carried out for polypeptide-chain segments adjacent to β-turn regions, including the sites of disallowed conformations. A cross comparison of conformations was performed for disallowed regions of the Ramachandran plot and main types of β-turns and adjacent secondary structures. Based on the results, disallowed region 2 (II, II') in the Ramachandran plot was shown to coincide mainly with β-hairpins and, more exactly, twisted β-hairpins. The frequency of residues with angles ϕi, ψi that fall in region 2 (II, II') in the latter is 140 times higher than in common β-hairpins.

In silico platform for predicting and initiating β-turns in a protein at desired locations.

Numerous studies have been performed for analysis and prediction of β-turns in a protein. This study focuses on analyzing, predicting, and designing of β-turns to understand the preference of amino acids in β-turn formation. We analyzed around 20,000 PDB chains to understand the preference of residues or pair of residues at different positions in β-turns. Based on the results, a propensity-based method has been developed for predicting β-turns with an accuracy of 82%. We introduced a new approach entitled "Turn level prediction method," which predicts the complete β-turn rather than focusing on the residues in a β-turn. Finally, we developed BetaTPred3, a Random forest based method for predicting β-turns by utilizing various features of four residues present in β-turns. The BetaTPred3 achieved an accuracy of 79% with 0.51 MCC that is comparable or better than existing methods on BT426 dataset. Additionally, models were developed to predict β-turn types with better performance than other methods available in the literature. In order to improve the quality of prediction of turns, we developed prediction models on a large and latest dataset of 6376 nonredundant protein chains. Based on this study, a web server has been developed for prediction of β-turns and their types in proteins. This web server also predicts minimum number of mutations required to initiate or break a β-turn in a protein at specified location of a protein.

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 Cο, Cα, H(N), and N(H) chemical shifts were generally (i + 1) > (i + 2). The mean values of Cβ and Hα 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.

Predicting Βeta-Turns and Βeta-Turn Types Using a Novel Over-Sampling Approach

β-turn is one of the most important reverse turns because of its role in protein folding. Many computational methods have been studied for predicting β-turns and β-turn types. However, due to the imbalanced dataset, the performance is still inadequate. In this study, we proposed a novel over-sampling technique FOST to deal with the class-imbalance problem. Experimental results on three standard benchmark datasets showed that our method is comparable with state-of-the-art methods. In addition, we applied our algorithm to five benchmark datasets from UCI Machine Learning Repository and achieved significant improvement in G-mean and Sensitivity. It means that our method is also effective for various imbalanced data other than β-turns and β-turn types.

Toward engineering efficient peptidomimetics. Screening conformational landscape of two modified dehydroaminoacids

Effective peptidomimetics should posses structural rigidity and appropriate interaction pattern leading to potential spatial and electronic matching to the target receptor site. Rational design of such small bioactive molecules could push chemical synthesis and molecular modeling toward faster progress in medicinal chemistry. Conformational properties of N-t-butoxycarbonyl-glycine-(E/Z)-dehydrophenylalanine N',N'-dimethylamides (Boc-Gly-(E/Z)-ΔPhe-NMe2 ) in chloroform were studied by NMR and IR spectroscopy. The experimental findings were supported by extensive calculations at DFT(B3LYP, M06-2X) and MP2 levels of theory and the β-turn tendency for both isomers of the studied dipeptide were determined in vacuum and in solution. The theoretical data and experimental IR results were used as an additional information for the NMR-based determination of the detailed solution conformations of the peptides. The obtained results reveal that N-methylation of C-terminal amide group changes dramatically the conformational properties of studied dehydropeptides. Theoretical conformational analysis reveals that the tendency to adopt β-turn conformations is much weaker for the N-methylated Z isomer (Boc-Gly-(Z)-ΔPhe-NMe2 ), both in vacuum and in polar environment. On the contrary, N-methylated E isomer (Boc-Gly-(E)-ΔPhe-NMe2 ) can easily adopt β-turn conformation, but the backbone torsion angles (φ1, ψ1, φ2, ψ2) are off the limits for common β-turn types.

LVQ-SMOTE – Learning Vector Quantization based Synthetic Minority Over–sampling Technique for biomedical data

BackgroundOver-sampling methods based on Synthetic Minority Over-sampling Technique (SMOTE) have been proposed for classification problems of imbalanced biomedical data. However, the existing over-sampling methods achieve slightly better or sometimes worse result than the simplest SMOTE. In order to improve the effectiveness of SMOTE, this paper presents a novel over-sampling method using codebooks obtained by the learning vector quantization. In general, even when an existing SMOTE applied to a biomedical dataset, its empty feature space is still so huge that most classification algorithms would not perform well on estimating borderlines between classes. To tackle this problem, our over-sampling method generates synthetic samples which occupy more feature space than the other SMOTE algorithms. Briefly saying, our over-sampling method enables to generate useful synthetic samples by referring to actual samples taken from real-world datasets.ResultsExperiments on eight real-world imbalanced datasets demonstrate that our proposed over-sampling method performs better than the simplest SMOTE on four of five standard classification algorithms. Moreover, it is seen that the performance of our method increases if the latest SMOTE called MWMOTE is used in our algorithm. Experiments on datasets for β-turn types prediction show some important patterns that have not been seen in previous analyses.ConclusionsThe proposed over-sampling method generates useful synthetic samples for the classification of imbalanced biomedical data. Besides, the proposed over-sampling method is basically compatible with basic classification algorithms and the existing over-sampling methods.