The antigenic index: a novel algorithm for predicting antigenic determinants

In this paper, we introduce a computer algorithm which can be used to predict the topological features of a protein directly from its primary amino acid sequence. The computer program generates values for surface accessibility parameters and combines these values with those obtained for regional backbone flexibility and predicted secondary structure. The output of this algorithm, the antigenic index, is used to create a linear surface contour profile of the protein. Because most, if not all, antigenic sites are located within surface exposed regions of a protein, the program offers a reliable means of predicting potential antigenic determinants. We have tested the ability of this program to generate accurate surface contour profiles and predict antigenic sites from the linear amino acid sequences of well-characterized proteins and found a strong correlation between the predictions of the antigenic index and known structural and biological data

AB INITIO PROTEIN STRUCTURE PREDICTION ALGORITHMS

Genes that encode novel proteins are constantly being discovered and added to databases, but the speed with which their structures are being determined is not keeping up with this rate of discovery. Currently, homology and threading methods perform the best for protein structure prediction, but they are not appropriate to use for all proteins. Still, the best way to determine a protein\u27s structure is through biological experimentation. This research looks into possible methods and relations that pertain to ab initio protein structure prediction. The study includes the use of positional and transitional probabilities of amino acids obtained from a non-redundant set of proteins created by Jpred for training computational methods. The methods this study focuses on are Hidden Markov Models and incorporating neighboring amino acids in the primary structure of proteins with the above-mentioned probabilities. The methods are presented to predict the secondary structure of amino acids without relying on the existence of a homolog. The main goal of this research is to be able to obtain information from an amino acid sequence that could be used for all future predictions of protein structures. Further, analysis of the performance of the methods is presented for explanation of how they could be incorporated in current and future work

Characterization of Desmoglein-3 Epitope Region Peptides as Synthetic Antigens: Analysis of their in vitro T-cell Stimulating Efficacy, Cytotoxicity, Stability and their Conformational Features

Desmoglein-3 (Dsg3) adhesion protein is the main target of autoantibodies and autoreactive T cells in Pemphigus vulgaris (PV) autoimmune skin disorder. Several mapping studies of Dsg3 T cell epitope regions were performed, and based on those data, we designed and synthesized four peptide series corresponding to Dsg3 T cell epitope regions. Each peptide series consists of a 17mer full-length peptide (Dsg3/189–205, Dsg3/206–222, Dsg3/342–358, and Dsg3/761–777) and its N-terminally truncated derivatives, resulting in 15 peptides altogether. The peptides were prepared on solid phase and were chemically characterized. In order to establish a structure–activity relationship, the solution conformation of the synthetic peptides has been investigated using electronic circular dichroism spectroscopy. The in vitro T cell stimulating efficacy of the peptides has been determined on peripheral blood mononuclear cells isolated from whole blood of PV patients and also from healthy donors. After 20h of stimulation, the interferon (IFN)-γ content of the supernatants was measured by enzyme-linked immunosorbent assay. In the in vitro conditions, peptides were stable and non-cytotoxic. The in vitro IFN-γ production profile of healthy donors and PV patients, induced by peptides as synthetic antigens, was markedly different. The most unambiguous differences were observed after stimulation with 17mer peptide Dsg3/342–358, and three truncated derivatives from two other peptide series, namely, peptides Dsg3/192–205, Dsg3/763–777, and Dsg3/764–777. Comparative analysis of in vitro activity and the capability of oligopeptides to form ordered or unordered secondary structure showed that peptides bearing high solvent sensibility and backbone flexibility were themost capable to distinguish between healthy and PV donors

Folding and Binding Properties of Human Complement Receptor Type 1 Extracellular Domain

Complement receptor type 1 (CR1 or CD35) is a peripheral glycosylated membrane protein that regulates the complement activation in the control of immune responses. The author would like to overview the folding and binding properties of the soluble form of CR1, so-called as sCR1, introducing our development of the high-yield overexpression and purification methods as well as the investigation to its molecular structure. Although sCR1 prepared through our method showed the highest binding affinity against C3b, it is quite difficult to be crystallized for X-ray structure analysis. In spite of many attempts, only microcrystals have been obtained so far. Considering the usefulness to understand factors within the difficulty, the primary sequence of sCR1 has been reexamined from the viewpoints both of secondary structure predictions and recent findings of intrinsically disordered proteins (IDPs) or natively unfolded proteins (NUPs). As an example, the theoretically predicted structure of a short consensus repeat (SCR) of a binding domain, SCR-15–17 in sCR1 is compared with the reported solution structure by NMR. The discussion is extended to protein structure studies with proteins containing ID regions, which are unfolded state without taking uniformly decided structures

In silico Vaccine Design against Dengue Virus Type 2 Envelope Glycoprotein

Dengue fever is caused by the mosquito-borne virus termed (DENV). However, DENV-2 has been identified as the most prevalent amongst the Indonesian pediatric urban population, in contrast with the other four serotypes. Therefore, it is important to reduce severe infection risk by adopting preventive measures, including through vaccine development. The aim of this study, therefore is to use various in silico tools in the design of epitope-based peptide vaccines (T-cell and B-cell types), based on the DENV-2 envelope glycoprotein sequences available. Therefore, in silico methods were adopted in the analysis of the retrieved protein sequences. This technique was required to determine the most immunogenic protein, and is achieved through conservancy analysis, epitope identification, molecular simulation, and allergenicity assessment. Furthermore, B4XPM1, and KAWLVHRQW were identified from positions 204-212, while the 77 to 85 peptide region was considered the most potent T-cell and B-cell epitopes. The interaction between KAWLVHRQW and HLA-C*12:03 occurs with maximum population coverage, alongside high conservancy (96.98%) and binding affinity. These results indicated a potential for the designed epitopes to demonstrate high immunity against DENV-2

Mitigation of peri-implantitis by rational design of bifunctional peptides with antimicrobial properties

This document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Biomaterials Science and Engineering, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acsbiomaterials.9b01213.The integration of molecular and cell biology with materials science has led to strategies to improve the interface between dental implants with the surrounding soft and hard tissues in order to replace missing teeth and restore mastication. More than 3 million implants have been placed in the US alone and this number is rising by 500,000/year. Peri-implantitis, an inflammatory response to oral pathogens growing on the implant surface threatens to reduce service life leading to eventual implant failure, and such an outcome will have adverse impact on public health and create significant health care costs. Here we report a predictive approach to peptide design, which enabled us to engineer a bifunctional peptide to combat bacterial colonization and biofilm formation, reducing the adverse host inflammatory immune response that destroys the tissue surrounding implants and shortens their lifespans. This bifunctional peptide contains a titanium-binding domain that recognizes and binds with high affinity to titanium implant surfaces, fused through a rigid spacer domain with an antimicrobial domain. By varying the antimicrobial peptide domain, we were able to predict the properties of the resulting bifunctional peptides in their entirety by analyzing the sequence-structure-function relationship. These bifunctional peptides achieve: 1) nearly 100% surface coverage within minutes, a timeframe suitable for their clinical application to existing implants; 2) nearly 100% binding to a titanium surface even in the presence of contaminating serum protein; 3) durability to brushing with a commercially available electric toothbrush; and 4) retention of antimicrobial activity on the implant surface following bacterial challenge. A bifunctional peptide film can be applied to both new implants and/or repeatedly applied to previously placed implants to control bacterial colonization mitigating peri-implant disease that threatens dental implant longevity