Supersecondary Structure Research Articles

Intermediates in the folding equilibrium of repeat proteins from the TPR family.

In recent decades, advances in computational methods and experimental biophysical techniques have improved our understanding of protein folding. Although some of these advances have been remarkable, the structural variability of globular proteins usually encountered makes it difficult to extract general features of their folding processes. To overcome this difficulty, experimental and computational studies of the folding of repeat (or modular) proteins are of interest. Because their native structures can be described as linear arrays of the same, repeated, supersecondary structure unit, it is possible to seek a possibly independent behavior of the different modules without taking into account the intrinsic stability associated with different secondary structure motifs. In this work we have used a Monte Carlo-based simulation to study the folding equilibrium of four repeat proteins belonging to the tetratricopeptide repeat family. Our studies provide new insights into their energy profiles, enabling investigation about the existence of intermediate states and their relative stabilities. We have also performed structural analyses to describe the structure of these intermediates, going through the vast number of conformations obtained from the simulations. In this way, we have tried to identify the regions of each protein in which the modular structure yields a different behavior and, more specifically, regions of the proteins that can stay folded when the rest of the chain has been thermally denatured.

Role of Backbone Dipole Interactions in the Formation of Secondary and Supersecondary Structures of Proteins.

We present a generic solvated coarse-grained protein model that can be used to characterize the driving forces behind protein folding. Each amino acid is coarse-grained with two beads, a backbone, and a side chain. Although the backbone beads are modeled as polar entities, side chains are hydrophobic, polar, or charged, thus allowing the exploration of how sequence patterning determines a protein fold. The change in orientation of the atoms of the coarse-grained unit is captured by the addition of two oppositely charged dummy particles inside the backbone coarse-grained bead. These two dummy charges represent a dipole that can fluctuate, thus introducing structural polarization into the coarse-grained model. Realistic α/β content is achieved de novo without any biases in the force field toward a particular secondary structure. The dipoles created by the dummy particles interact with each other and drive the protein models to fold into unique structures depending on the amino acid patterning and presence of capping residues. We have also characterized the role of dipole–dipole and dipole–charge interactions in shaping the secondary and supersecondary structure of proteins. Formation of helix bundles and β-strands are also discussed.

Functional artificial luciferases as an optical readout for bioassays

This study elucidates functional artificial luciferases (ALucs) wholly synthesized for bioassays and molecular imaging. The ALucs bearing epitopes were newly created by amending the sequences of our previously reported ALucs in light of a multi-sequence alignment and hydrophobicity search. The synthesized ALucs are survived in live cells and stable in culture media for 25days after secretion. The epitopes in ALucs are exposed during the secretion process and indeed valid for column purification and immunological assays. The ALucs exerted a 9400-times stronger optical intensity with a coelenterazine derivative (CTZ i), when compared with Renilla reniformis luciferase 8.6–535. A supersecondary structure of ALuc30 was predicted with respect to the X-ray crystallographic information of the coelenterazine-binding protein (CBP). The structure revealed that ALuc30 has a room for accommodating the iodide of CTZ i. This study guides on how to create functional artificial luciferases and predicts the structural details with the current bioinformatics technologies.

Simultaneous Alignment and Folding of Protein Sequences

Accurate comparative analysis tools for low-homology proteins remains a difficult challenge in computational biology, especially sequence alignment and consensus folding problems. We present partiFold-Align, the first algorithm for simultaneous alignment and consensus folding of unaligned protein sequences; the algorithm's complexity is polynomial in time and space. Algorithmically, partiFold-Align exploits sparsity in the set of super-secondary structure pairings and alignment candidates to achieve an effectively cubic running time for simultaneous pairwise alignment and folding. We demonstrate the efficacy of these techniques on transmembrane β-barrel proteins, an important yet difficult class of proteins with few known three-dimensional structures. Testing against structurally derived sequence alignments, partiFold-Align significantly outperforms state-of-the-art pairwise and multiple sequence alignment tools in the most difficult low-sequence homology case. It also improves secondary structure prediction where current approaches fail. Importantly, partiFold-Align requires no prior training. These general techniques are widely applicable to many more protein families (partiFold-Align is available at http://partifold.csail.mit.edu/ ).

Molecular Cloning, Bioinformatics Analysis and Expression of Insulin-Like Growth Factor 2 from Tianzhu White Yak, Bos grunniens

The IGF family is essential for normal embryonic and postnatal development and plays important roles in the immune system, myogenesis, bone metabolism and other physiological functions, which makes the study of its structure and biological characteristics important. Tianzhu white yak (Bos grunniens) domesticated under alpine hypoxia environments, is well adapted to survive and grow against severe hypoxia and cold temperatures for extended periods. In this study, a full coding sequence of the IGF2 gene of Tianzhu white yak was amplified by reverse transcription PCR and rapid-amplification of cDNA ends (RACE) for the first time. The cDNA sequence revealed an open reading frame of 450 nucleotides, encoding a protein with 179 amino acids. Its expression in different tissues was also studied by Real time PCR. Phylogenetic tree analysis indicated that yak IGF2 was similar to Bos taurus, and 3D structure showed high similarity with the human IGF2. The putative full CDS of yak IGF2 was amplified by PCR in five tissues, and cDNA sequence analysis showed high homology to bovine IGF2. Moreover the super secondary structure prediction showed a similar 3D structure with human IGF2. Its conservation in sequence and structure has facilitated research on IGF2 and its physiological function in yak.

Prediction of four kinds of simple supersecondary structures in protein by using chemical shifts.

Knowledge of supersecondary structures can provide important information about its spatial structure of protein. Some approaches have been developed for the prediction of protein supersecondary structure. However, the feature used by these approaches is primarily based on amino acid sequences. In this study, a novel model is presented to predict protein supersecondary structure by use of chemical shifts (CSs) information derived from nuclear magnetic resonance (NMR) spectroscopy. Using these CSs as inputs of the method of quadratic discriminant analysis (QD), we achieve the overall prediction accuracy of 77.3%, which is competitive with the same method for predicting supersecondary structures from amino acid compositions in threefold cross-validation. Moreover, our finding suggests that the combined use of different chemical shifts will influence the accuracy of prediction.

基于支持向量机的整体分类器算法 预测酶蛋白质中四类简单超二级结构

酶是一种具有催化功能的蛋白质，研究酶蛋白质中的超二级结构对研究酶的结构及功能有重要作用。本文从酶蛋白质序列出发，首次对酶蛋白质中的四类简单超二级结构进行研究。以位点氨基酸及其紧邻关联为参数，选取五种序列片段截取方式，采用7-交叉检验，使用矩阵打分方法预测的结果不理想；将矩阵打分值作为特征参数输入支持向量机，并用整体分类器进行加权融合，得到了较好的预测结果，预测总精度达到72.64%，Matthew’s相关系数在0.57以上，因此，基于支持向量机的整体分类器方法是一种有效的预测酶蛋白质中超二级结构的方法。 Enzymes are a kind of protein that has catalytic function. The study of supersecondary structures in enzymes plays an important role in the structure and function of enzymes. Based on enzyme sequence information, four kinds of supersecondary structures in enzymes were researched for the first time. Amino acids of sites and dipeptide components of sites were selected as parameters, for five selections of the best fixed-length pattern, the predictive results in 7-fold cross-validation were not ideal by using scoring function method; scores were selected as input parameters of support vector machine (SVM); the results were fused with weighted factors by using ensemble classifier; the better performance was obtained; the overall prediction accuracy was 72.64% and the Matthews correlation coefficient was above 0.57. Therefore, ensemble classifier based on SVM is an effective method to predict four kinds of supersecondary structures in enzymes.

Extended secondary structures in proteins

Supersecondary structures of proteins have been systematically searched and classified, but not enough attention has been devoted to such large edifices beyond the basic identification of secondary structures. The objective of the present study is to show that the association of secondary structures that share some of their backbone residues is a commonplace in globular proteins, and that such deeper fusion of secondary structures, namely extended secondary structures (ESSs), helps stabilize the original secondary structures and the resulting tertiary structures. For statistical purposes, a set of 163 proteins from the protein databank was randomly selected and a few specific cases are structurally analyzed and characterized in more detail. The results point that about 30% of the residues from each protein, on average, participate in ESS. Alternatively, for the specific cases considered, our results were based on the secondary structures produced after extensive Molecular Dynamics simulation of a protein–aqueous solvent system. Based on the very small width of the time distribution of the root mean squared deviations, between the ESS taken along the simulation and the ESS from the mean structure of the protein, for each ESS, we conclude that the ESSs significantly increase the conformational stability by forming very stable aggregates. The ubiquity and specificity of the ESS suggest that the role they play in the structure of proteins, including the domains formation, deserves to be thoroughly investigated.

On permuted super-secondary structures of transmembrane β-barrel proteins

Transmembrane β-barrel (TMB) proteins constitute a special class of proteins, which are located in outer membranes of Gram-negative bacteria, mitochondria, and chloroplasts. These proteins play diverse important roles in biological organisms. However, only a small number of TMB protein structures are currently known due to difficulties with experimental techniques. Hence, computational structure prediction methods based on learning are poorly tractable for these proteins. We introduce here a graph-theoretic ab initio model for predicting structures of TMB proteins by free energy minimization. TMB super-secondary structures with permuted arrangements are taken into consideration in this model. We show that finding a permuted structure is an NP-hard problem and then analyze the complexity of a tree decomposition-based algorithm to search for the optimal structure of a TMB protein corresponding to a given permutation. The robust performance of the model has been proven in our previously published results.

Super-secondary structure peptidomimetics: design and synthesis of an α–α hairpin analogue

The α–α helix motif presents key recognition domains in protein–protein and protein–oligonucleotide binding, and is one of the most common super-secondary structures. Herein, we describe the design, synthesis and structural characterisation of an α–α hairpin analogue based on a tetra-coordinated Pd(II) bis-(iminoisoquinoline) complex as a template for the display of two α-helix mimics. This approach is exemplified by the attachment of two biphenyl peptidomimetics to reproduce the side chains of the i and i+4 residues of two helices.

Circular dichroism and the secondary structure of the ROF2 protein from Arabidopsis thaliana

The protein ROF2 from the plant Arabidopsis thaliana acts as a heat stress modulator, being involved in the long-term acquired thermotolerance of the plant. Here we investigate the relationship between the biological function and the structure of ROF2, inferred by circular dichroism (CD) spectroscopy. The far-UV CD spectra, analyzed with the CDPro and DICHROWEB program packages, yield the percentages of α-helices, β-sheets, unordered regions, turns and poly(Pro)II-helices in the secondary structure of ROF2. According to the analysis, the percentages of the structural elements of ROF2 are about 40% for β-sheets, 30% for unordered regions, 17% for turns, 10% for poly(Pro)II-helices and 3% for α-helices. The near-UV CD spectra suggest that ROF2 proteins can associate, forming super-secondary structures. Our CD experiments performed at temperatures between 5°C and 97°C indicate that the thermal denaturation of ROF2 caused by a raise in temperature up to 55°C is followed by a thermal refolding of the protein as the temperature is raised further. The new secondary structure, acquired around 65°C, remains stable up to 97°C. The structural stability of ROF2 at high temperatures might play an important role in the experimentally observed thermotolerance of Arabidopsis thaliana.

Structural properties of the truncated and wild types of Taka-amylase: A molecular dynamics simulation and docking study

• Structures of the native and truncated Taka amylase were compared. • C-terminal domain is essential for the stability of the structure. • The barrel region and the large cleft remained native in truncated enzymes. • Binding affinity of maltoheptaose toward enzymes is more than those of maltotriose. In this work, structures of the native (Amyl-C) and truncated Taka amylase were compared by molecular modeling methods. Using in silico enzyme engineering approach, 50 (Amyl-S1) and 100 (Amyl-S2) amino acids were eliminated from Amyl-C to produce the truncated forms. Analysis of the tertiary structures showed that three essential domains of the enzyme including super secondary structure (αβ) 8 , the barrel region, and the large cleft remained native in Amyl-S1 and Amyl-S2. Secondary structures of Met112-Val118, Gly202-His211, Gln230-Asp233, Phe292-Asp297 residues in Amyl-C, Amyl-S1, and Amyl-S2 remained unchanged. These domains are necessary for catalytic function of alpha-amylase superfamily. Flexibility analysis of the three forms was examined and it is obtained that by truncation, the flexibility of the C-terminal domain was increased. This shows that C-terminal domain is essential for the stability of the structure which is in agreement with experimental observations. However, Glu156, Gln 162, Gly234, Val 245, Asn260, Ser264, Asp 297 of Amyl-C had higher flexibility than those in truncated enzymes. Maltotriose, maltotetraose, maltopentaose, maltohexaose and maltoheptaose as five substrates were docked to the three enzyme forms. Binding affinity of maltoheptaose was higher in Amyl-C and Amyl-S1and lower in Amyl-S2 than that of maltotriose. In all forms the substrates were associated with three residues of the catalytic triad.

Modeling Proteins Using a Super-Secondary Structure Library and NMR Chemical Shift Information

A remaining challenge in protein modeling is to predict structures for sequences with no sequence similarity to any experimentally solved structure. Based on earlier observations, the library of protein backbone supersecondary structure motifs (Smotifs) saturated about a decade ago. Therefore, it should be possible to build any structure from a combination of existing Smotifs with the help of limited experimental data that are sufficient to relate the backbone conformations of Smotifs between target proteins and known structures. Here, we present a hybrid modeling algorithm that relies on an exhaustive Smotif library and on nuclear magnetic resonance chemical shift patterns without any input of primary sequence information. In a test of 102 proteins, the algorithm delivered 90 homology-model-quality models, among them 24 high-quality ones, and a topologically correct solution for almost all cases. The current approach opens a venue to address the modeling of larger protein structures for which chemical shifts are available.

Data Mining of Supersecondary Structure Homology between Light Chains of Immunogloblins and MHC Molecules: Absence of the Common Conformational Fragment in the Human IgM Rheumatoid Factor

It is shown that fuzzy search and data mining techniques of supersecondary structure homology for subunits of proteins using conformational code patterns of α-helix-type (3β5α4β) and β-sheet-type (6α4β4β) fragments can be used to extract correlations between fragments of MHC class I molecules and the light chain of immunoglobulins. The new method of conformational pattern analysis with fuzzy search of structural code homology reflects well the shape of main chain rather than secondary structure in comparison with the DSSP method. Further, the data mining technique using the combination of h- and s-fragment patterns can quantify the supersecondary structure homology between any subunits of proteins with different amino acid sequences. Characteristic fragment patterns (string "shhshss"), which were sandwiched between two identical amino acid sequences His and Pro, were found in light chains of various types of immunogloblins, α-chain and β-2 microglobulin of MHC class I and α-chain and β-chain of MHC class II, but not in heavy chains of Fab immunoglobulin fragments and T cell receptors (TCR). Leukocyte immunoglobulin-like receptors (LILR) are related by the conformational fragment (string "shhshss") to β-2 microglobulins as a type of pair forms (string "sohsss"). Further, human IgM rheumatoid factor, one of the immunogloblins, did not strongly exhibit the conformational fragment pattern. Nonclassic MHC class I molecules CD1D, MIC-A, and MIC-B, which have functions to activate NKT, NK, and T cells, did not also clearly show the patterns. These code-driven mining techniques can be utilized as a metadata-generating tool for systems biology to elucidate the biological function of such conformational fragments of MHC I and II molecules, which come in contact with various signal ligands on the surface of T cells and natural killer cells.

Dissecting the structural determinants for the difference in mechanical stability of silk and amyloid beta-sheet stacks

Stacking of β-sheets results in a protein super secondary structure with remarkable mechanical properties. β-Stacks are the determinants of a silk fiber's resilience and are also the building blocks of amyloid fibrils. While both silk and amyloid-type crystals are known to feature a high resistance against rupture, their structural and mechanical similarities and particularities are yet to be fully understood. Here, we systematically compare the rupture force and stiffness of amyloid and spider silk poly-alanine β-stacks of comparable sizes using Molecular Dynamics simulations. We identify the direction of force application as the primary determinant of the rupture strength; β-sheets in silk are orientated along the fiber axis, i.e. the pulling direction, and consequently require high forces in the several nanoNewton range for shearing β-strands apart, while β-sheets in amyloid are oriented vertically to the fiber, allowing a zipper-like rupture at sub-nanoNewton forces. A secondary factor rendering amyloid β-stacks softer and weaker than their spider silk counterparts is the sub-optimal side-chain packing between β-sheets due to the sequence variations of amyloid-forming proteins as opposed to the perfectly packed poly-alanine β-sheets of silk. Taken together, amyloid fibers can reach the stiffness of silk fibers in spite of their softer and weaker β-sheet arrangement as they are missing a softening amorphous matrix.

Probing the protein space for extending the detection of weak homology folds

Redundancy of prediction methods has been used to explore the occurrence of weak homology protein motifs. A hybrid template-based algorithm has been implemented to predict different layers of protein structure by detecting domain building sub-structures, which share low sequence identity. Physicochemical determinants, secondary structure profiles, and multiple alignments have been analyzed to generate a broad set of structural sub-domains. Then, intensive computing procedures generated all the various tridimensional folds on the basis of secondary structure predictions, fragment assembly and detection of structural homologs. The proposed algorithm not only identifies common protein sub-structures, but also detects higher order architectures such as domain superfamilies/superfolds by linking backbone trajectories of supersecondary structures. Applying rigid transformation protocols, population of the detected domain building models with an average root mean square deviation from native structures of 2.3Å and an average template modeling score from native structures of 0.43 has been obtained. The fold detection algorithm here proposed yields more accurate results than previously proposed methods, predicting structural homology also for proteins sharing less than 20% sequence identity. Our tools are freely available at http://www.acbrc.org/tools.html.

Detection of secondary and supersecondary structures of proteins from cryo-electron microscopy

Recent advances in three-dimensional electron microscopy (3D EM) have enabled the quantitative visualization of the structural building blocks of proteins at improved resolutions. We provide algorithms to detect the secondary structures (α-helices and β-sheets) from proteins for which the volumetric maps are reconstructed at 6-10Å resolution. Additionally, we show that when the resolution is coarser than 10Å, some of the supersecondary structures can be detected from 3D EM maps. For both these algorithms, we employ tools from computational geometry and differential topology, specifically the computation of stable/unstable manifolds of certain critical points of the distance function induced by the molecular surface. Our results connect mathematically well-defined constructions with bio-chemically induced structures observed in proteins.

Unusual thermodynamic properties of a compact state of IgG3 Kuc and Sur pFh fragments (Hinge region)

The pFh fragments from the hinge region of human IgG3 Kuc and Sur are able to fold into a compact structure, thereby giving proteins with secondary (supersecondary) structure, mainly represented by the left-handed polyproline II helix. It has been shown that thermal denaturation of a compact pFh from the hinge region of IgG3 Kuc and Sur comprises two stages. At the first stage, the compact protein structure unfolds according to the all-or-none model with retention of the secondary structure. At the second stage, the left-handed polyproline II helix, composed of four separate cooperative blocks formed of strands with a high content of proline residues, melts itself. A polyproline conformation of the secondary structure and a large number of disulfide bonds between the chains determine a high specific enthalpy of denaturation and a high thermal stability, respectively.

STITCHER: Dynamic assembly of likely amyloid and prion β‐structures from secondary structure predictions

The supersecondary structure of amyloids and prions, proteins of intense clinical and biological interest, are difficult to determine by standard experimental or computational means. In addition, significant conformational heterogeneity is known or suspected to exist in many amyloid fibrils. Previous work has demonstrated that probability-based prediction of discrete β-strand pairs can offer insight into these structures. Here, we devise a system of energetic rules that can be used to dynamically assemble these discrete β-strand pairs into complete amyloid β-structures. The STITCHER algorithm progressively ‘stitches’ strand-pairs into full β-sheets based on a novel free-energy model, incorporating experimentally observed amino-acid side-chain stacking contributions, entropic estimates, and steric restrictions for amyloidal parallel β-sheet construction. A dynamic program computes the top 50 structures and returns both the highest scoring structure and a consensus structure taken by polling this list for common discrete elements. Putative structural heterogeneity can be inferred from sequence regions that compose poorly. Predictions show agreement with experimental models of Alzheimer’s amyloid beta peptide and the Podospora anserina Het-s prion. Predictions of the HET-s homolog HET-S also reflect experimental observations of poor amyloid formation. We put forward predicted structures for the yeast prion Sup35, suggesting N-terminal structural stability enabled by tyrosine ladders, and C-terminal heterogeneity. Predictions for the Rnq1 prion and alpha-synuclein are also given, identifying a similar mix of homogenous and heterogeneous secondary structure elements. STITCHER provides novel insight into the energetic basis of amyloid structure, provides accurate structure predictions, and can help guide future experimental studies.Proteins 2012. © 2011 Wiley Periodicals, Inc.

Exosite Interactions Impact Matrix Metalloproteinase Collagen Specificities

Members of the matrix metalloproteinase (MMP) family selectively cleave collagens in vivo. However, the substrate structural determinants that facilitate interaction with specific MMPs are not well defined. We hypothesized that type I-III collagen sequences located N- or C-terminal to the physiological cleavage site mediate substrate selectivity among MMP-1, MMP-2, MMP-8, MMP-13, and MMP-14/membrane-type 1 (MT1)-MMP. The enzyme kinetics for hydrolysis of three fluorogenic triple-helical peptides (fTHPs) was evaluated herein. The first fTHP contained consensus residues 769-783 from type I-III collagens, the second inserted α1(II) collagen residues 763-768 N-terminal to the consensus sequence, and the third inserted α1(II) collagen residues 784-792 C-terminal to the consensus sequence. Our analyses showed that insertion of the C-terminal residues significantly increased k(cat)/K(m) and k(cat) for MMP-1. MMP-13 showed the opposite behavior with a decreased k(cat)/K(m) and k(cat) and a greatly improved K(m) in response to the C-terminal residues. Insertion of the N-terminal residues enhanced k(cat)/K(m) and k(cat) for MMP-8 and MT1-MMP. For MMP-2, the C-terminal residues enhanced K(m) and dramatically decreased k(cat), resulting in a decrease in the overall activity. These changes in activities and kinetic parameters represented the collagen preferences of MMP-8, MMP-13, and MT1-MMP well. Thus, interactions with secondary binding sites (exosites) helped direct the specificity of these enzymes. However, MMP-1 collagen preferences were not recapitulated by the fTHP studies. The preference of MMP-1 for type III collagen appears to be primarily based on the flexibility of the hydrolysis site of type III collagen compared with types I and II. Further characterization of exosite determinants that govern interactions of MMPs with collagenous substrates should aid the development of pharmacotherapeutics that target individual MMPs.