pi-Turns: types,systematics and the context of their occurrence in protein structures

Background  

For a proper understanding of protein structure and folding it is important to know if a polypeptide segment adopts a conformation inherent in the sequence or it depends on the context of its flanking secondary structures. Turns of various lengths have been studied and characterized starting from three-residue γ-turn to six-residue π-turn. The Schellman motif occurring at the C-terminal end of α-helices is a classical example of hydrogen bonded π-turn involving residues at (i) and (i+5) positions. Hydrogen bonded and non-hydrogen bonded β- and α-turns have been identified previously; likewise, a systematic characterization of π-turns would provide valuable insight into turn structures.     

Predicting <Emphasis Type="Italic">β</Emphasis>-turns and their types using predicted backbone dihedral angles and secondary structures

Background  

β-turns are secondary structure elements usually classified as coil. Their prediction is important, because of their role in protein folding and their frequent occurrence in protein chains.     

Structure and denaturation of 4-chlorobenzoyl coenzyme A dehalogenase from <Emphasis Type="Italic">Arthrobacter</Emphasis> sp. strain TM-1

The secondary structure of the trimeric protein 4-chlorobenzoyl coenzyme A dehalogenase from Arthrobacter sp. strain TM-1, the second of three enzymes involved in the dechlorination of 4-chlorobenzoate to form 4-hydroxybenzoate, has been examined. E_mM for the enzyme was 12.59. Analysis by circular dichroism spectrometry in the far uv indicated that 4-chlorobenzoyl coenzyme A dehalogenase was composed mostly of α-helix (56%) with lesser amounts of random coil (21%), β-turn (13%) and β-sheet (9%). These data are in close agreement with a computational prediction of secondary structure from the primary amino acid sequence, which indicated 55.8% α-helix, 33.7% random coil and 10.5% β-sheet; the enzyme is, therefore, similar to the 4-chlorobenzoyl coenzyme A dehalogenase from Pseudomonas sp. CBS-3. The three-dimensional structure, including that of the presumed active site, predicted by computational analysis, is also closely similar to that of the Pseudomonas dehalogenase. Study of the stability and physicochemical properties revealed that at room temperature, the enzyme was stable for 24 h but was completely inactivated by heating to 60°C for 5 min; thereafter by cooling at 1°C min⁻¹ to 45°C, 20.6% of the activity could be recovered. Mildly acidic (pH 5.2) or alkaline (pH 10.1) conditions caused complete inactivation, but activity was fully recovered on returning the enzyme to pH 7.4. Circular dichroism studies also indicated that secondary structure was little altered by heating to 60°C, or by changing the pH from 7.4 to 6.0 or 9.2. Complete, irreversible destruction of, and maximal decrease in the fluorescence yield of the protein at 330–350 nm were brought about by 4.5 M urea or 1.1 M guanidinium chloride. Evidence was obtained to support the hypothetical three-dimensional model, that residues W140 and W167 are buried in a non-polar environment, whereas W182 appears at or close to the surface of the protein. At least one of the enzymes of the dehalogenase system (the combined 4-chlorobenzoate:CoA ligase, the dehalogenase and 4-hydroxybenzoyl coenzyme A thioesterase) appears to be capable of association with the cell membrane.

Better prediction of protein contact number using a support vector regression analysis of amino acid sequence

Background  

Protein tertiary structure can be partly characterized via each amino acid's contact number measuring how residues are spatially arranged. The contact number of a residue in a folded protein is a measure of its exposure to the local environment, and is defined as the number of C _β atoms in other residues within a sphere around the C _β atom of the residue of interest. Contact number is partly conserved between protein folds and thus is useful for protein fold and structure prediction. In turn, each residue's contact number can be partially predicted from primary amino acid sequence, assisting tertiary fold analysis from sequence data. In this study, we provide a more accurate contact number prediction method from protein primary sequence.     

Observation of glycine zipper and unanticipated occurrence of ambidextrous helices in the crystal structure of a chiral undecapeptide

Background  

The de novo design of peptides and proteins has recently surfaced as an approach for investigating protein structure and function. This approach vitally tests our knowledge of protein folding and function, while also laying the groundwork for the fabrication of proteins with properties not precedented in nature. The success of these studies relies heavily on the ability to design relatively short peptides that can espouse stable secondary structures. To this end, substitution with α, β-dehydroamino acids, especially α, β-dehydrophenylalanine (ΔPhe) comes in use for spawning well-defined structural motifs. Introduction of ΔPhe induces β-bends in small and 3₁₀-helices in longer peptide sequences.     

Using predicted shape string to enhance the accuracy of <Emphasis Type="Bold">γ</Emphasis>-turn prediction

Numerous methods for predicting γ-turns in proteins have been developed. However, the results they generally provided are not very good, with a Matthews correlation coefficient (MCC) ≤0.18. Here, an attempt has been made to develop a method to improve the accuracy of γ-turn prediction. First, we employ the geometric mean metric as optimal criterion to evaluate the performance of support vector machine for the highly imbalanced γ-turn dataset. This metric tries to maximize both the sensitivity and the specificity while keeping them balanced. Second, a predictor to generate protein shape string by structure alignment against the protein structure database has been designed and the predicted shape string is introduced as new variable for γ-turn prediction. Based on this perception, we have developed a new method for γ-turn prediction. After training and testing the benchmark dataset of 320 non-homologous protein chains using a fivefold cross-validation technique, the present method achieves excellent performance. The overall prediction accuracy Q _total can achieve 92.2% and the MCC is 0.38, which outperform the existing γ-turn prediction methods. Our results indicate that the protein shape string is useful for predicting protein tight turns and it is reasonable to use the dihedral angle information as a variable for machine learning to predict protein folding. The dataset used in this work and the software to generate predicted shape string from structure database can be obtained from anonymous ftp site freely.     

Mapping of the Mouse Actin Capping Protein Beta Subunit Gene

Background  

Capping protein (CP), a heterodimer of α and β subunits, is found in all eukaryotes. CP binds to the barbed ends of actin filaments in vitro and controls actin assembly and cell motility in vivo. Vertebrates have three isoforms of CPβ produced by alternatively splicing from one gene; lower organisms have one gene and one isoform.     

Secondary structure estimation of recombinant <Emphasis Type="Italic">psbH</Emphasis>, encoding a photosynthetic membrane protein of cyanobacterium <Emphasis Type="Italic">Synechocystis</Emphasis> sp. PCC 6803

The PsbH protein of cyanobacterium Synechocystis sp. PCC 6803 was expressed as a fusion protein with glutathione-S transferase (GST) in E. coli grown on a mineral medium enriched in ¹⁵N isotope. After enzymatic cleavage of the fusion protein, the ¹H-¹⁵N-HSQC spectrum of PsbH protein in presence of the detergent β-D-octyl-glucopyranoside (OG) was recorded on a Bruker DRX 500 MHz NMR spectrometer equipped with a 5 mm TXI cryoprobe to enhance the sensitivity and resolution. Non-labelled protein was used for secondary structure estimation by deconvolution from circular dichroism (CD) spectra. Experimental results were compared with our results from a structural model of PsbH using a restraint-based comparative modelling approach combined with molecular dynamics and energetic modelling. We found that PsbH shows 34–38% α-helical structure (Thr36-Ser60), a maximum of around 15% of β-sheet, and 12–19% of β-turn.     

dbOGAP - An Integrated Bioinformatics Resource for Protein O-GlcNAcylation

Background  

Protein O-GlcNAcylation (or O-GlcNAc-ylation) is an O-linked glycosylation involving the transfer of β-N-acetylglucosamine to the hydroxyl group of serine or threonine residues of proteins. Growing evidences suggest that protein O-GlcNAcylation is common and is analogous to phosphorylation in modulating broad ranges of biological processes. However, compared to phosphorylation, the amount of protein O-GlcNAcylation data is relatively limited and its annotation in databases is scarce. Furthermore, a bioinformatics resource for O-GlcNAcylation is lacking, and an O-GlcNAcylation site prediction tool is much needed.     

Characterisation of the tryptophan synthase alpha subunit in maize

Background  

In bacteria, such as Salmonella typhimurium, tryptophan is synthesized from indole-3-glycerole phosphate (IGP) by a tryptophan synthase αββα heterotetramer. Plants have evolved multiple α (TSA) and β (TSB) homologs, which have probably diverged in biological function and their ability of subunit interaction. There is some evidence for a tryptophan synthase (TS) complex in Arabidopsis. On the other hand maize (Zea mays) expresses the TSA-homologs BX1 and IGL that efficiently cleave IGP, independent of interaction with TSB.     

PALSSE: A program to delineate linear secondary structural elements from protein structures

Background  

The majority of residues in protein structures are involved in the formation of α-helices and β-strands. These distinctive secondary structure patterns can be used to represent a protein for visual inspection and in vector-based protein structure comparison. Success of such structural comparison methods depends crucially on the accurate identification and delineation of secondary structure elements.     

Structural and functional importance of theβ-turn in proteins. Studies on proline-containing peptides

We report here two sets of results on proline-containing linear peptides, one of which brings out the role of theβ-turn conformation in the structure of nascent collagen while the other points to the functional importance of the β-turn in calcium-binding proteins. Based on the data on peptides containing the -Pro-Gly-sequence, we had proposed and experimentally verified that theβ-turn conformation in these peptides is a structural requirement for the enzymic hydroxylation of the proline residues in the nascent (unhydroxylated) procollagen molecule. Our recent data, presented here, on the conformation of peptides containing both the -Pro-Gly- and -Gly-Pro-sequences reveal that while theβ-turn in the substrate molecule is required at the catalytic site of prolyl hydroxylase, the polyproline-II structure is necessary for effective binding at the active site of the enzyme. Thus, peptides containing either theβ-turn or the polyproline-II structure alone are found to act only as inhibitors while those with the polyproline-II followed byβ-turn serve as substrates of the enzyme. In another study, we have synthesized the two linear peptides: Boc-Pro-D-Ala-Ala-NHCH₃ and Boc-Pro-Gly-Ala-NHCH₃ each of which adopts, in solution, a structure with two consecutiveβ-turns, as judged from circular dichroism, infrared and nuclear magnetic resonance data. Drastic spectral changes are seen in these peptides on binding to Ca²⁺. Both the peptides show a distinct specificity to Ca²⁺ over Mg²⁺, Na⁺ and Li₊. A conformational change in the peptides occurs on Ca²⁺ binding which brings together the carbonyl groups to coordinate with the metal ion. These results imply a functional role for theβ-turn in Ca²⁺ — binding proteins.     

PCI-SS: MISO dynamic nonlinear protein secondary structure prediction

Background  

Since the function of a protein is largely dictated by its three dimensional configuration, determining a protein's structure is of fundamental importance to biology. Here we report on a novel approach to determining the one dimensional secondary structure of proteins (distinguishing α-helices, β-strands, and non-regular structures) from primary sequence data which makes use of Parallel Cascade Identification (PCI), a powerful technique from the field of nonlinear system identification.     

Distill: a suite of web servers for the prediction of one-, two- and three-dimensional structural features of proteins

Background  

We describe Distill, a suite of servers for the prediction of protein structural features: secondary structure; relative solvent accessibility; contact density; backbone structural motifs; residue contact maps at 6, 8 and 12 Angstrom; coarse protein topology. The servers are based on large-scale ensembles of recursive neural networks and trained on large, up-to-date, non-redundant subsets of the Protein Data Bank. Together with structural feature predictions, Distill includes a server for prediction of C _α traces for short proteins (up to 200 amino acids).     

Deciphering the shape and deformation of secondary structures through local conformation analysis

Background  

Protein deformation has been extensively analysed through global methods based on RMSD, torsion angles and Principal Components Analysis calculations. Here we use a local approach, able to distinguish among the different backbone conformations within loops, α-helices and β-strands, to address the question of secondary structures' shape variation within proteins and deformation at interface upon complexation.     

The highly conserved serine threonine kinase StkP of Streptococcus pneumoniae contributes to penicillin susceptibility independently from genes encoding penicillin-binding proteins

Background  

The serine/threonine kinase StkP of Streptococcus pneumoniae is a major virulence factor in the mouse model of infection. StkP is a modular protein with a N-terminal kinase domain a C-terminal PASTA domain carrying the signature of penicillin-binding protein (PBP) and prokaryotic serine threonine kinase. In laboratory cultures, one target of StkP is the phosphoglucosamine mutase GlmM involved in the first steps of peptidoglycan biosynthesis. In order to further elucidate the importance of StkP in S. pneumoniae, its role in resistance to β-lactams has been assessed by mutational analysis in laboratory cultures and its genetic conservation has been investigated in isolates from infected sites (virulent), asymptomatic carriers, susceptible and non-susceptible to β-lactams.     

Protein secondary structure from circular dichroism spectra

Circular dichroism spectra of proteins are extremely sensitive to secondary structure. Nevertheless, circular dichroism spectra should not be analyzed for protein secondary structure unless they are measured to at least 184 nm. Even if all the various types ofβ-turns are lumped together, there are at least 5 different types of secondary structure in a protein (α-helix, antiparallelβ-sheet, parallelβ-sheet,β-turn, and other structures not included in the first 4 categories). It is not possible to solve for these 5 parameters unless there are 5 equations. Singular value decomposition can be used to show that circular dichroism spectra of proteins measured to 200 nm contain only 2 pieces of information, while spectra measured to 190 nm contain about 4. Adding the constraint that the sum of secondary structures must equal 1 provides another piece of information, but even with this constraint, spectra measured to 190 nm simply do not analyze well for the 5 unknowns in secondary structure. Spectra measured to 184 nm do contain 5 pieces of information and we have used such spectra successfully to analyze a variety of proteins for their component secondary structures.     

Predominant membrane localization is an essential feature of the bacterial signal recognition particle receptor

Background  

The signal recognition particle (SRP) receptor plays a vital role in co-translational protein targeting, because it connects the soluble SRP-ribosome-nascent chain complex (SRP-RNCs) to the membrane bound Sec translocon. The eukaryotic SRP receptor (SR) is a heterodimeric protein complex, consisting of two unrelated GTPases. The SRβ subunit is an integral membrane protein, which tethers the SRP-interacting SRα subunit permanently to the endoplasmic reticulum membrane. The prokaryotic SR lacks the SRβ subunit and consists of only the SRα homologue FtsY. Strikingly, although FtsY requires membrane contact for functionality, cell fractionation studies have localized FtsY predominantly to the cytosolic fraction of Escherichia coli. So far, the exact function of the soluble SR in E. coli is unknown, but it has been suggested that, in contrast to eukaryotes, the prokaryotic SR might bind SRP-RNCs already in the cytosol and only then initiates membrane targeting.     

Functional characterization of the trans-membrane domain interactions of the Sec61 protein translocation complex beta-subunit

Background  

In eukaryotic cells co- and post-translational protein translocation is mediated by the trimeric Sec61 complex. Currently, the role of the Sec61 complex β-subunit in protein translocation is poorly understood. We have shown previously that in Saccharomyces cerevisiae the trans-membrane domain alone is sufficient for the function of the β-subunit Sbh1p in co-translational protein translocation. In addition, Sbh1p co-purifies not only with the protein translocation channel subunits Sec61p and Sss1p, but also with the reticulon family protein Rtn1p.