A bioinformatics approach for identifying the probable cause of the cross-interaction of antibodies to the antigenic protein HPV16 L1 with the HPV6 L1 protein

This paper describes an attempt to analyze, with the aid of bioinformatics resources (programs and databases), the probable cause of the cross-interaction of antibodies against HPV16 L1 with antigenic protein HPV6 L1, which has been revealed in the investigation of the candidate vaccine obtained on the base of a plant expression system (tomato plants). In our opinion, the most likely reason for the cross-interaction of antibodies with antigens of different pathogenic HPV types is the similarity of their antigenic determinants. In this work, the amino acid sequences of HPV16 L1 and HPV6 L1 used for the development of a binary vaccine against cervical cancer and anogenital papillomatosis have been analyzed. For the analysis of antigenic determinants, the programs BepiPred-2.0: Sequential B-Cell Epitope Predictor, DiscoTope 2.0 Server and SYFPEITHI have been used. As a result of the analysis of probable B-cell linear determinants (epitopes), it has been found that in both types of HPV the proteins have approximately the same location and size of linear antigenic determinants; the difference is observed only in the form of small shifts in the size of several amino acid residues. However, there are some differences in the amino acid composition of epitopes; therefore, the possibility for cross-interaction of the antibodies with the antigens due to the similarity of linear antigenic determinants for B-cells is very small. The analysis of potential threedimensional epitopes for B-cells has shown that due to little difference between them the HPV16 L1 and HPV6 L1 proteins have no prerequisites for cross-interaction of the antibodies with the antigens belonging to the two different pathogenic HPV types. The analysis of probable linear epitopes for T-cells has revealed a common antigenic determinant in the two protein sequences. According to the rank made with the SYFPEITHI program, the amino acid sequence AQL(I)FNKPYWL is the second most likely antigenic determinant for T-cells. Meanwhile, the amino acid sequences of this determinant in HPV16 L1 and HPV6 L1 are virtually identical. There is a difference in only one position, but it is not critical due to the similarity of the physicochemical properties of amino acids, for which there is a replacement in the amino acid sequence of antigenic determinants. Consequently, some moderate cross-interaction of the antibodies to HPV16 L1 with the antigens of HPV6 L1 may be expected.

Peptides derived from gp43, the most antigenic protein from Paracoccidioides brasiliensis, form amyloid fibrils in vitro: implications for vaccine development

Fungal infection is an important health problem in Latin America, and in Brazil in particular. Paracoccidioides (mainly P. brasiliensis and P. lutzii) is responsible for paracoccidioidomycosis, a disease that affects mainly the lungs. The glycoprotein gp43 is involved in fungi adhesion to epithelial cells, which makes this protein an interesting target of study. A specific stretch of 15 amino acids that spans the region 181–195 (named P10) of gp43 is an important epitope of gp43 that is being envisioned as a vaccine candidate. Here we show that synthetic P10 forms typical amyloid aggregates in solution in very short times, a property that could hamper vaccine development. Seeds obtained by fragmentation of P10 fibrils were able to induce the aggregation of P4, but not P23, two other peptides derived from gp43. In silico analysis revealed several regions within the P10 sequence that can form amyloid with steric zipper architecture. Besides, in-silico proteolysis studies with gp43 revealed that aggregation-prone, P10-like peptides could be generated by several proteases, which suggests that P10 could be formed under physiological conditions. Considering our data in the context of a potential vaccine development, we redesigned the sequence of P10, maintaining the antigenic region (HTLAIR), but drastically reducing its aggregation propensity.

Advances in the Application of Nanomaterials as Treatments for Bacterial Infectious Diseases

Bacteria-targeting nanomaterials have been widely used in the diagnosis and treatment of bacterial infectious diseases. These nanomaterials show great potential as antimicrobial agents due to their broad-spectrum antibacterial capacity and relatively low toxicity. Recently, nanomaterials have improved the accurate detection of pathogens, provided therapeutic strategies against nosocomial infections and facilitated the delivery of antigenic protein vaccines that induce humoral and cellular immunity. Biomaterial implants, which have traditionally been hindered by bacterial colonization, benefit from their ability to prevent bacteria from forming biofilms and spreading into adjacent tissues. Wound repair is improving in terms of both the function and prevention of bacterial infection, as we tailor nanomaterials to their needs, select encapsulation methods and materials, incorporate activation systems and add immune-activating adjuvants. Recent years have produced numerous advances in their antibacterial applications, but even further expansion in the diagnosis and treatment of infectious diseases is expected in the future.

ArVirInd - a database of arboviral antigenic proteins from the Indian subcontinent

Studies on antigenic proteins for arboviruses are important for providing diagnostics and vaccine development. India and its neighbouring countries have huge burden of arboviral diseases. Data mining for country-specific sequences from existing databases is cumbersome and time-consuming. This necessitated the development of a database of antigenic proteins from arbo-viruses isolated from the countries of the Indian subcontinent. Arboviral antigenic protein sequences were obtained from the NCBI and other databases. In silico antigenic characterization was performed (Epitope predictions) and data incorporated in the database. The front end is designed and developed using HTML, CSS and PHP. For the backend of the database, we have used MySQL. A database, named ArVirInd, is created as a repository of information on antigenic proteins. This enlists sequences by country and year of outbreak or origin of the viral strain. For each entry antigenic information is provided along with functional sites, etc. Researchers can search this database by virus/protein name, country and year of collection (or in combination). It is available publicly via Internet at http://www.arvirind.co.in. ArVirInd will be useful in the study of immuno-informatics, diagnostics and vaccinology for arboviruses.

Peptides derived from gp43, the most antigenic protein from Paracoccidioides brasiliensis, form amyloid fibrils in vitro: implications for vaccine development

Fungal infection is an important health problem in Latin America, and in Brazil in particular. Paracoccidioides (P. brasiliensis and P. lutzii) is responsible for paracoccidioidomycosis, a disease that affects mainly the lungs. The glycoprotein gp43 is involved in fungi adhesion to epithelial cells, which makes this protein an interesting target of study. A specific stretch of 15 amino acids that spans the region 181-195 (named P10) of gp43 is an important epitope of gp43 that is being envisioned as a vaccine candidate. Here we show that synthetic P10 forms typical amyloid aggregates in solution in very short times, a property that could hamper vaccine development. Seeds obtained by fragmentation of P10 fibrils were able to induce the aggregation of P4, but not P23, two other peptides derived from gp43. In silico analysis revealed several regions within the P10 sequence that are capable of forming amyloid with steric zipper architecture. Besides, in-silico proteolysis studies with gp43 revealed that aggregation-prone, P10-like peptides could be generated by several proteases, which suggests that P10 could be formed under physiological conditions. Considering our data in the context of a potential vaccine development, we redesigned the sequence of P10, maintaining the antigenic region (HTLAIR), but drastically reducing its aggregation propensity.