Computational Design and Analysis of a Poly-Epitope Fusion Protein: A New Vaccine Candidate for Hepatitis and Poliovirus

Artificial intelligence in fusion protein three-dimensional structure prediction: Review and perspective

Recent advancements in artificial intelligence (AI) have accelerated the prediction of unknown protein structures. However, accurately predicting the three-dimensional (3D) structures of fusion proteins remains a difficult task because the current AI-based protein structure predictions are focused on the WT proteins rather than on the newly fused proteins in nature. Following the central dogma of biology, fusion proteins are translated from fusion transcripts, which are made by transcribing the fusion genes between two different loci through the chromosomal rearrangements in cancer. Accurately predicting the 3D structures of fusion proteins is important for understanding the functional roles and mechanisms of action of new chimeric proteins. However, predicting their 3D structure using a template-based model is challenging because known template structures are often unavailable in databases. Deep learning (DL) models that utilize multi-level protein information have revolutionized the prediction of protein 3D structures. In this review paper, we highlighted the latest advancements and ongoing challenges in predicting the 3D structure of fusion proteins using DL models. We aim to explore both the advantages and challenges of employing AlphaFold2, RoseTTAFold, tr-Rosetta and D-I-TASSER for modelling the 3D structures. HIGHLIGHTS: This review provides the overall pipeline and landscape of the prediction of the 3D structure of fusion protein. This review provides the factors that should be considered in predicting the 3D structures of fusion proteins using AI approaches in each step. This review highlights the latest advancements and ongoing challenges in predicting the 3D structure of fusion proteins using deep learning models. This review explores the advantages and challenges of employing AlphaFold2, RoseTTAFold, tr-Rosetta, and D-I-TASSER to model 3D structures.

Mapping Potential Vaccine Candidates Predicted by VaxiJen for Different Viral Pathogens between 2017-2021-A Scoping Review

Reverse vaccinology (RV) is a promising alternative to traditional vaccinology. RV focuses on in silico methods to identify antigens or potential vaccine candidates (PVCs) from a pathogen's proteome. Researchers use VaxiJen, the most well-known RV tool, to predict PVCs for various pathogens. The purpose of this scoping review is to provide an overview of PVCs predicted by VaxiJen for different viruses between 2017 and 2021 using Arksey and O'Malley's framework and the Preferred Reporting Items for Systematic Reviews extension for Scoping Reviews (PRISMA-ScR) guidelines. We used the term 'vaxijen' to search PubMed, Scopus, Web of Science, EBSCOhost, and ProQuest One Academic. The protocol was registered at the Open Science Framework (OSF). We identified articles on this topic, charted them, and discussed the key findings. The database searches yielded 1033 articles, of which 275 were eligible. Most studies focused on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), published between 2020 and 2021. Only a few articles (8/275; 2.9%) conducted experimental validations to confirm the predictions as vaccine candidates, with 2.2% (6/275) articles mentioning recombinant protein expression. Researchers commonly targeted parts of the SARS-CoV-2 spike (S) protein, with the frequently predicted epitopes as PVCs being major histocompatibility complex (MHC) class I T cell epitopes WTAGAAAYY, RQIAPGQTG, IAIVMVTIM, and B cell epitope IAPGQTGKIADY, among others. The findings of this review are promising for the development of novel vaccines. We recommend that vaccinologists use these findings as a guide to performing experimental validation for various viruses, with SARS-CoV-2 as a priority, because better vaccines are needed, especially to stay ahead of the emergence of new variants. If successful, these vaccines could provide broader protection than traditional vaccines.

Ofatumumab and Granzyme B as immunotoxin against CD20 antigen

Anti-CD20 antibodies such as ofatumumab has demonstrated efficacy in relapsed/refractory chronic lymphocytic leukemia, are among the most successful therapies to date. In this study, we have designed an immunotoxin composed of Granzyme B and the high affinity variant of Ofatumumab. Different simulation software applied to explore the structure of Granzyme B, a serine protease in cytotoxic lymphocytes granules as an apoptosis mediator was attached to its specific antibody structure (Ofatumumab) via an adaptor sequence. The accuracy, energy minimization and characterization of biological properties of the final structure were evaluated. Our computational outcomes indicated that the employed method for structure prediction has been successfully managed to design the immunotoxin structure. The precise and accurate design of the immune-therapeutic agents against cancer cells can be confirmed by employment of in-silico approaches. Consequently, based on this approach we could introduce a capable immunotoxin which specifically targeting CD20 in an accurate orientation and initiates cancer cell destruction by its toxin domain.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-022-00120-6.

Computational Design and Analysis of a Multi-epitope Against Influenza A virus

Influenza A viruses are among the most studied viruses, however no effective prevention against influenza infection has been developed. So, designing an effective vaccine against Influenza A virus is a critical issue in the field of medical biotechnology. For this reason, to combat this disease, we have designed a novel multi-epitope vaccine candidate based on the several conserved and potential linear B-cell and T-cell binding epitopes by using the in silico approach. This vaccine consists of an ER signal conserved sequence, the PADRE conserved epitope and two conserved epitopes of Influenza matrix protein 2. T-cell binding epitopes from Matrix protein 2 were predicted by in silico tools of epitope prediction. The selected epitopes were joined by flexible linkers and physicochemical properties, toxicity, and allergenecity were investigated. The designed vaccine was antigenic, immunogenic, and non-allergenic with suitable physicochemical properties and has higher solubility. The final multi-epitope construct was modeled, confirmed by different programs and the molecular interactions with immune receptors were considered. The molecular docking assay indicated the interactions with immune-stimulatory toll-like receptor 3 (TLR3) and major histocompatibility complex class I (MHCI). The HADDOCK and H DOCK servers were used to make docking analysis, respectively. The docking analysis indicated a strong and stable binding interaction between the vaccine construct with major histocompatibility complex (MHC) class I and toll-like receptor 3. Overall, the findings suggest that the current vaccine may be a promising vaccine to prevent Influenza infection.

In Silico Prediction of Human Leukocytes Antigen (HLA) Class II Binding Hepatitis B Virus (HBV) Peptides in Botswana

Hepatitis B virus (HBV) is the primary cause of liver-related malignancies worldwide, and there is no effective cure for chronic HBV infection (CHB) currently. Strong immunological responses induced by T cells are associated with HBV clearance during acute infection; however, the repertoire of epitopes (epi) presented by major histocompatibility complexes (MHCs) to elicit these responses in various African populations is not well understood. In silico approaches were used to map and investigate 15-mers HBV peptides restricted to 9 HLA class II alleles with high population coverage in Botswana. Sequences from 44 HBV genotype A and 48 genotype D surface genes (PreS/S) from Botswana were used. Of the 1819 epi bindings predicted, 20.2% were strong binders (SB), and none of the putative epi bind to all the 9 alleles suggesting that multi-epitope, genotype-based, population-based vaccines will be more effective against HBV infections as opposed to previously proposed broad potency epitope-vaccines which were assumed to work for all alleles. In total, there were 297 unique epi predicted from the 3 proteins and amongst, S regions had the highest number of epi (n = 186). Epitope-densities (Depi) between genotypes A and D were similar. A number of mutations that hindered HLA-peptide binding were observed. We also identified antigenic and genotype-specific peptides with characteristics that are well suited for the development of sensitive diagnostic kits. This study identified candidate peptides that can be used for developing multi-epitope vaccines and highly sensitive diagnostic kits against HBV infection in an African population. Our results suggest that viral variability may hinder HBV peptide-MHC binding, required to initiate a cascade of immunological responses against infection.

cis-9-Hexadecenal, a Natural Compound Targeting Cell Wall Organization, Critical Growth Factor, and Virulence of Aspergillus fumigatus

Aspergillus fumigatus causes several nosocomial pulmonary infections and accounts for high morbidity and mortality rate globally. Among various virulence factors, 1,8-dihydroxynaphthalene-melanin plays an important role in the survival during unfavorable conditions both in vivo and in vitro, masks various molecular patterns associated with A. fumigatus, and protects it from the host immune system. In the present study, we aim to understand the potential of cis-9-hexadecenal as an antimelanogenic compound and its role in modulating other associated virulence factors in A. fumigatus. cis-9-Hexadecenal is a bioactive compound that belongs to C₁₆ mono-unsaturated fatty-aldehyde groups. Minimum effective concentration of cis-9-hexadecenal affecting A. fumigatus melanin biosynthesis was determined using broth microdilution method. The spectrophotometric analysis revealed reduced melanin content (91%) and hydrophobicity (59%) at 0.293 mM of cis-9-hexadecenal. Cell surface organizational changes using electron microscopy showed altered demelanized smooth A. fumigatus conidial surface without any protrusions after cis-9-hexadecenal treatment. The transcript analysis of polyketide synthase (PKS) pksP/alb1 gene was quantified through qRT-PCR which revealed an upregulated expression. Total proteome profiling conducted through LC-MS-MS showed upregulated PKS enzyme but other downstream proteins involved in the 1,8-dihydroxynaphthalene-melanin biosynthesis pathway were absent. The homology modeling of PKS using Expasy's web server predicted that PKS is stable at varied conditions and is hydrophilic in nature. The Ramachandran plot by PROCHECK confirmed the 3-D structure of PKS to be reliable. Docking analysis using AutoDock-4.2.6 predicted the binding of cis-9-hexadecenal and PKS at Thr-264 and Ser-171 residue via hydrogen bonding at a low binding energy of -4.95 kcal/mol.