Bioinformatics\u2010Driven Design of Fusion Recombinant Protein (EgFABP1\u2010EgTeg) for Enhanced Immunodiagnosis of Hydatid Cysts

Background/Objectives: Streptococcus suis is a zoonotic pathogen that causes infections in pigs and humans, leading to significant economic losses. S. suis can evade the immune system of hosts and induce persistent infections. Early detection and vaccination are crucial for controlling the disease in swine industries. This study aimed to investigate candidate recombinant protein for antibodies against S. suis detection and subunit vaccine development. Methods: The whole genome of S. suis BM407 was analyzed using bioinformatic tools to predict suitable proteins and genes for recombinant protein expression. Partial extracellular factor protein (epf) genes of S. suis serotype 2 DMST18783 were amplified. A 3301 bp amplicon was digested, and a specific 615 bp fragment was inserted into a pQE81L-KAN vector. Then, the constructed plasmid was cloned and expressed in Escherichia coli DH10β. Purified protein was analyzed using SDS-PAGE. In addition, translated amino acid sequences were analyzed for immune response properties, molecular docking, molecular dynamic simulation, and epitope prediction. Results: The amino acid sequence of recombinant extracellular factor protein (rEF) was revealed as a promising antigen containing putative protective regions as linear epitopes. Furthermore, the rEF was expressed as a histidine-tagged recombinant protein, and its properties were nearly similar to the predicted rEF using bioinformatic tools. Binding of the recombinant EF (rEF) protein was found to reduce fluctuations in the swine toll-like receptor 2. Furthermore, the rEF contained several regions that were predicted to be epitopes for both B-cells and T-cells. Conclusions: This study indicates that the recombinant EF fragment is a promising candidate for detecting antibodies against S. suis and as a component of a subunit vaccine.

The function of any protein depends directly on its secondary and tertiary structure. Proteins can fold into a three-dimensional shape, which is primarily depended on the arrangement of amino acids in the primary structure. In recent years, with the explosive sequencing of proteins, it is unfeasible to perform detailed experimental studies, as these methodologies are very expensive and time consuming. This leaves the structure of the majority of currently available protein sequences unknown. In this paper, a predictive model is therefore presented for the classification of protein sequence's secondary structures, namely alpha helix and beta sheet. The proteins used throughout this study were collected from the Structural Classification of Proteinsextended (SCOPe) database, which contains manually curated information from proteins with known structure. Two sets of proteins are used for all alpha and all beta protein sequences. The first set comprise of sequences with less than 40% identity, and the second set comprise of proteins with less than 95% identity. The analysis shows a strong connection between the amino acid indices used to convert protein sequences to numerical sequences and proteins' secondary structures. The total classification accuracy for the proposed classifier for the protein sequences with less than 40% identity for amino acid index BIOV880101 and BIOV880102 are 78.49% and 76.40%, respectively. The classification accuracy for sets of protein sequences with less than 95% identity for amino acid index BIOV880101 and BIOV880102 are 88.01% and 85.17%, respectively.

The major maize storage proteins (alpha zeins) are deposited as an insoluble mass in the protein bodies of the endosperm. Because they are insoluble in water, most structural studies are performed in alcohol solutions. To solve the question raised by several authors about denaturation of the alpha zein structure by alcohol, we analyze the secondary structure of alpha zeins prepared with and without solubilization in alcohol (corn gluten meal and protein bodies with high concentrations of alpha zeins and traces of beta zeins). The secondary structures of alpha zeins are analyzed in the solid state by Fourier transform IR spectroscopy (FTIR) in KBr pellets and solid-state 13C-NMR spectroscopy. The proportion of secondary structures obtained by FTIR of alpha zeins prepared with and without solubilization in alcohol yield almost identical proportions of alpha helices and beta sheets. The proportion of alpha helices (43%) agrees with that measured by circular dichroism in an alcohol solution. However, the proportion of beta sheets (28%) is higher than the one measured by the same technique. Gluten and protein body samples with high beta zein content showed higher beta sheet and lower alpha helix proportions than that obtained for alpha zein preparations. The solid-state 13C-NMR spectra show the carbonyl peak for the alpha zeins at delta 176 and for the sample rich in beta zeins at delta 172, which demonstrates the presence of a high content of alpha helices and beta sheets, respectively. These results indicate that alcohol solubilization does not affect the conformation of alpha zeins, validating the secondary structure measurements in solution.

Three-dimensional (3D) models are essential for visualization and conceptual understanding of complex architectures such as protein structure. Although there is a plethora of software platforms that allow digital depictions of protein structure at an atomic level in silico , physical models are needed to convey an intuitive understanding of biomolecular architecture. However, it is a challenge to represent all the relevant features of proteins in a single physical model due to their sheer structural complexity. Here, we describe a modular protein model that focuses only on representation of the secondary structure—the underlying structural skeleton. The simplified model consists of amino acid units, which can be linked together to reproduce the two most fundamental structural features of protein secondary structure: the relative positions of the amino acid alpha carbon atoms, and the intra-main chain hydrogen bonding pattern. We use 3D printing and magnets to create a set of three modular amino acid building blocks, which when linked together into a chain, can faithfully represent alpha helices, beta sheets, and turns. These simple to make models can be used to quickly assemble the alpha carbon trace of an entire protein domain, which conveys a tactile experience of the complexity of protein skeletal architecture. These models highlight the modularity of protein structure: where a single structural unit, the amino acid, can be linked together to form a larger, regular secondary structure. These models also have a propensity to spontaneously organize into alpha helices and beta sheets, as demonstrated by their ability to autonomously assemble when placed in a circulating water tank. These models provide a missing educational tool to expand knowledge of protein structure, foster deeper insight into protein folding, and inspire greater interest in biomacromolecular architecture.

Many studies revealed that different amino acids have different preferences for taking part in alpha helices and beta sheets conformations. Different substitution matrices have been prepared to compare the proteins' secondary and tertiary structures. Unfortunately, in many cases these matrices are unable to produce reliable results, due to the complexity of these conformations. In this work, following dissection of beta sheets with different size, the amino acids compositions of each position in each class of beta sheets were extracted and compared. The amino acid contents of the same position in different beta sheets were also compared. Our results indicate great differences in amino acid contents between beta sheets with different size. Individual substitution matrices might be required in order to do alignment and comparison studies for different types of beta sheets. These results might also imply alternative evolutionary route for beta sheets with different size; longer beta sheets could be a result of merging the smaller one together in different combinations, rather than simple expansion of the smaller sheets. Based on these findings hopefully we would be able to propose an improved substitution matrix (possibly more than one) that could be used for all secondary structures, regardless of their size.

Pneumococcal conjugate vaccines (PCVs) were constructed through chemical conjugation of pneumococcal capsules to immunogenic carrier proteins. The PCVs implementation in developing countries was prevented by their high manufacturing costs. This issue can be overcome by development of protein based vaccines against pneumococci. Antibody responses are necessary for protection against S. pneumoniae. Choline binding protein D (CBPD) was already identified as a pneumococcal surface protein able to elicit protection against S. pneumoniae and its most protective B-cell epitope region (MIBR) was determined. MIBR was highly conserved in common pneumococcal serotypes. Whole antigens are not as potent as epitope based vaccines and B-cell epitope based vaccines are more effective than whole antigen based vaccines in the prevention of infections. Bacterial flagellins are effective adjuvants that signal via Toll like receptor 5 (TLR5). The TLR5 binding site of flagellin located in the D1 domain and its proper conformation is critical for TLR5 recognition of flagellin. In the present study, therefore, we aim to design effective chimeric vaccines against pneumococci based on MIBR and flagellin of Salmonella Enteritidis (FliC) using bioinformatics tools. FliC was joined to MIBR at N-terminus (CFH), C-terminus (FCH) and the D3 domain (D3Gly202, D3Thr275). All of the constructs were immunoprotective regarding the VaxiJen score (0.8). The codon optimization for constructs was done using OPTIMIZER. Analysis of the mRNA secondary structures using Mfold tool revealed no stable hairpins at 5' ends of constructs and thus the antigens can be expressed appropriately. SCRATCH results indicated that the antigens can be expressed in the soluble form in Escherichia coli at more than 80% probability. The 3D models of antigens resulted from I-TASSER indicated the presence of alpha helix, beta sheet, turn, coil, and 310 helix as the protein structural elements. Superimposing 3D models of D1 domains of antigens with the D1 domain of FliC using FATCAT indicated no change in the D1 conformation. Therefore, FliC can exert its adjuvant effects in these constructs through TLR5 signaling. Inserting MIBR in Gly202 of FliC enhanced the protein beta sheet content remarkably, which can result in appropriate thermostability of the antigen. Our results, therefore, demonstrated that D3Gly202 is a suitable vaccine candidate, which can elicit protection against common S. pneumoniae serotypes causing invasive pneumococcal disease in children less than 5 years of age.

Identifying protein antigenic epitopes that are recognizable by antibodies is a key step in immunologic research. This type of research has broad medical applications, such as new immunodiagnostic reagent discovery, vaccine design, and antibody design. However, due to the countless possibilities of potential epitopes, the experimental search through trial and error would be too costly and time-consuming to be practical. To facilitate this process and improve its efficiency, computational methods were developed to predict both linear epitopes and discontinuous antigenic epitopes. For linear B-cell epitope prediction, many methods were developed, including PREDITOP, PEOPLE, BEPITOPE, BepiPred, COBEpro, ABCpred, AAP, BCPred, BayesB, BEOracle/BROracle, BEST, LBEEP, DRREP, iBCE-EL, SVMTriP, etc. For the more challenging yet important task of discontinuous epitope prediction, methods were also developed, including CEP, DiscoTope, PEPITO, ElliPro, SEPPA, EPITOPIA, PEASE, EpiPred, SEPIa, EPCES, EPSVR, etc. In this chapter, we will discuss computational methods for B-cell epitope predictions of both linear and discontinuous epitopes. SVMTriP and EPCES/EPCSVR, the most successful among the methods for each type of the predictions, will be used as model methods to detail the standard protocols. For linear epitope prediction, SVMTriP was reported to achieve a sensitivity of 80.1% and a precision of 55.2% with a fivefold cross-validation based on a large dataset, yielding an AUC of 0.702. For discontinuous or conformational B-cell epitope prediction, EPCES and EPCSVR were both benchmarked by a curated independent test dataset in which all antigens had no complex structures with the antibody. The identified epitopes by these methods were later independently validated by various biochemical experiments. For these three model methods, webservers and all datasets are publicly available at http://sysbio.unl.edu/SVMTriP , http://sysbio.unl.edu/EPCES/ , and http://sysbio.unl.edu/EPSVR/ .

Guy's 13 is a mouse monoclonal antibody that specifically recognizes the major cell-surface adhesion protein SA I/II of Streptococcus mutans, one of the major causative agents of dental caries. Passive immunization with Guy's 13 prevents bacterial colonization in humans. To help elucidate the mechanism of prevention of colonization conferred by this antibody, the SA I/II epitope recognized by Guy's 13 was investigated. It was previously established that the epitope is conformational, being assembled from two non-contiguous regions of SA I/II. In the current study, using recombinant fragments of SA I/II and, ultimately, synthetic peptides, the discontinuous epitope was localized to residues 170-218 and 956-969. This work describes the mapping of a novel discontinuous epitope that requires an interaction between each determinant in order for epitope assembly and recognition by antibody to take place. Guy's 13 binds to the assembled epitope but not to these individual epitope fragments. The assembled epitope results from the interaction between the individual antigenic determinants and can be formed by mixing together determinants present on separate polypeptide chains. The data are consistent with one of the epitope fragments adopting a polyproline II-like helical conformation.

The interdisciplinary nature of biochemistry courses requires students to use both chemistry and biology knowledge to understand biochemical concepts. Research that has focused on external representations in biochemistry has uncovered student difficulties in comprehending and interpreting external representations in addition to a fragmented understanding of fundamental biochemistry concepts. This project focuses on students' understanding of primary and secondary protein structure and drawings (representations) of hydrogen-bonding in alpha helices and beta sheets. Analysis demonstrated that students can recognize and identify primary protein structure concepts when given a polypeptide. However, when asked to draw alpha helices and beta sheets and explain the role of hydrogen bonding their drawings students exhibited a fragmented understanding that lacked coherence. Faculty are encouraged to have students draw molecular level representations to make their mental models more explicit, complete, and coherent. This is in contrast to recognition and identification tasks, which do not adequately probe mental models and molecular level understanding.

Discovery of discontinuous B-cell epitopes is a major challenge in vaccine design. Previous epitope prediction methods have mostly been based on protein sequences and are not very effective. Here, we present DiscoTope, a novel method for discontinuous epitope prediction that uses protein three-dimensional structural data. The method is based on amino acid statistics, spatial information, and surface accessibility in a compiled data set of discontinuous epitopes determined by X-ray crystallography of antibody/antigen protein complexes. DiscoTope is the first method to focus explicitly on discontinuous epitopes. We show that the new structure-based method has a better performance for predicting residues of discontinuous epitopes than methods based solely on sequence information, and that it can successfully predict epitope residues that have been identified by different techniques. DiscoTope detects 15.5% of residues located in discontinuous epitopes with a specificity of 95%. At this level of specificity, the conventional Parker hydrophilicity scale for predicting linear B-cell epitopes identifies only 11.0% of residues located in discontinuous epitopes. Predictions by the DiscoTope method can guide experimental epitope mapping in both rational vaccine design and development of diagnostic tools, and may lead to more efficient epitope identification.

Exploring peptide mimics for the production of antibodies against discontinuous protein epitopes

Acinetobacter baumannii is one of the main causes of nosocomial infections. No vaccine has yet been licensed for use in humans, and efforts are still ongoing. In the present study, we have predicted the B-cell epitopes of A. baumannii's outer membrane protein K (OMPK) by using epitope prediction algorithms as possible vaccine candidates for future studies. The linear B-cell epitopes were predicted by seven different prediction tools. The 3D structure of OMPK was modeled and used for discontinuous epitope prediction by ElliPro and DiscoTope 2.0 tools. The final linear epitopes and the discontinuous epitope segments were checked for potential allergenicity, toxicity, human similarity, and experimental records. The structure and physicochemical features of the final epitopic peptide were assessed by numerous bioinformatics tools. Many B-cell epitopes were detected that could be assessed for possible antigenicity and immunogenicity. Also, an epitopic 22-mer region (peptide) of OMPK was found that contained both linear and discontinuous B-cell epitopes. This epitopic peptide has been found to possess appropriate physicochemical and structural properties to be an A. baumannii vaccine candidate. Altogether, here, the high immunogenic B-cell epitopes of OMPK have been identified, and a high immunogenic 22-mer peptide as an A. baumannii vaccine candidate has been introduced. The in vitro/in vivo studies of this peptide are recommended to decide its real efficacy and efficiency.

Peptide Folding on Peptide Amphiphile Micelles Determines Micelle Structure and Assembly

Anti-liver cytosol type 1 (LC1) autoantibody is detected in 30% of sera from patients with type 2 autoimmune hepatitis (AIH), and is the only circulating autoantibody in 10% of cases. Human formiminotransferase cyclodeaminase (FTCD) has been shown to be the specific liver antigen recognized by anti-LC1 autoantibodies. The aim of this study was to identify the dominant epitope on human FTCD and to analyze antigenic-site sequences for clues on the development of AIH. Recombinant proteins and peptides covering the entire cDNA of human FTCD were tested against anti-LC1 autoantibodies. Conformational epitopes were found throughout the protein but linear epitopes were found exclusively in the C-terminal 146 amino acids. Two groups of sera with different reactivities were found: 69%of the sera recognized two specific linear epitopes at positions 428-434 (NTPEEKD) and 440-447 (LQEGLRRA) of human FTCD; others reacted only with a discontinuous epitope between the amino acids at position 395 and 528. FTCD autoantibody production is thus a polyclonal-antigen-driven B cell response. Autoantibodies against conformational or discontinuous epitopes were found in all patients and two-thirds also recognized linear epitopes on human FTCD.

Structural and Dynamical Study of Bovine Carbonic Anhydrase II in the Presence of Substrate: An Essential Dynamics and Molecular Dynamics Simulation Study