GalaxyRefine: Protein structure refinement driven by side-chain repacking

Immunoinformatic-guided novel mRNA vaccine designing to elicit immunogenic responses against the endemic Monkeypox virus

Monkeypox virus (MPXV) is an orthopoxvirus, causing zoonotic infections in humans with smallpox-like symptoms. The WHO reported MPXV cases in May 2022 and the outbreak caused significant morbidity threats to immunocompromised individuals and children. Currently, no clinically validated therapies are available against MPXV infections. The present study is based on immunoinformatics approaches to design mRNA-based novel vaccine models against MPXV. Three proteins were prioritized based on high antigenicity, low allergenicity, and toxicity values to predict T- and B-cell epitopes. Lead T- and B-cell epitopes were used to design vaccine constructs, linked with epitope-specific linkers and adjuvant to enhance immune responses. Additional sequences, including Kozak sequence, MITD sequence, tPA sequence, Goblin 5', 3' UTRs, and a poly(A) tail were added to design stable and highly immunogenic mRNA vaccine construct. High-quality structures were predicted by molecular modeling and 3D-structural validation of the vaccine construct. Population coverage and epitope-conservancy speculated broader protection of designed vaccine model against multiple MPXV infectious strains. MPXV-V4 was eventually prioritized based on its physicochemical and immunological parameters and docking scores. Molecular dynamics and immune simulations analyses predicted significant structural stability and binding affinity of the top-ranked vaccine model with immune receptors to elicit cellular and humoral immunogenic responses against the MPXV. The pursuance of experimental and clinical follow-up of these prioritized constructs may lay the groundwork to develop safe and effective vaccine against MPXV.Communicated by Ramaswamy H. Sarma.

Novel salty peptides derived from bovine bone: Identification, taste characteristic, and salt-enhancing mechanism

Excessive sodium intake is a major contributor to the incidence of cardiovascular diseases. The objective of this study was to prepare, isolate, and characterize peptides from bovine bone protein and investigate the salty/salt-enhancing mechanism of peptides. 1032 peptides were identified in the enzymatic hydrolysates of bovine bone protein and were further screened by the composition of amino acid residues and molecular docking analysis. 5 peptides were finally selected for solid-phase synthesis, and KER showed a better salty taste by sensory verification. Moreover, the synergistic effect of KER in NaCl and MSG solution could enhance the salty intensity by 65.26 %. The binding of KER to the salty receptor (TMC4) was driven by hydrogen bonding and electrostatic interactions with a binding energy of -88.0734 kcal/mol. This work may provide a new approach to efficiently screen salty peptides from natural food materials, which were expected as a taste enhancer used in salt-reducing foods.

Comprehensive bioinformatics-based annotation and functional characterization of bovine chymosin protein revealed novel biological insights

Chymosin, an aspartic protease present in the stomachs of young ruminants like cows (bovine), causes milk coagulation and cheese production through the breakdown of κ-casein peptide bonds at the Met105-Phe106 site. Bovine chymosin is first synthesized as a pre-prochymosin that is cleaved to produce the mature chymosin protein. Despite significant strides in research, our understanding of this crucial enzyme remains incomplete. The purpose of this work was to perform in silico evolutionary and functional analysis and to gain unique insights into the structure of this protein. For this, the sequence of Bos taurus chymosin from UniProt database was subjected to various bioinformatics analyses. We found that bovine chymosin is a low molecular weight and hydrophilic protein that has homologs in other Bovidae species. Two active sites of aspartic peptidases, along with a functional domain, were identified. Gene Ontology analysis further confirmed chymosin's involvement in proteolysis and aspartic endopeptidase activity. Potential disordered residues and post-translational modification sites were also uncovered. It was revealed that the secondary structure of bovine chymosin is comprised of beta strands (44.27%), coils (43.65%), and alpha helices (12.07%). A highly optimized 3D structure was also obtained. Moreover, crucial protein-protein interactions were unveiled. Altogether, these findings provide valuable insights that could guide future research on bovine chymosin and its biological roles.

Design of a novel multiepitope vaccine with CTLA-4 extracellular domain against Mycoplasma pneumoniae: A vaccine-immunoinformatics approach

BACKGROUND

Community-acquired pneumonia often stems from the macrolide-resistant strain of Mycoplasma pneumoniae, yet no effective vaccine exists against it.

METHODS

This study proposes a vaccine-immunoinformatics strategy for Mycoplasma pneumoniae and other pathogenic microbes. Specifically, dominant B and T cell epitopes of the Mycoplasma pneumoniae P30 adhesion protein were identified through immunoinformatics method. The vaccine sequence was then constructed by coupling with CTLA-4 extracellular region, a novel molecular adjuvant for antigen-presenting cells. Subsequently, the vaccine's physicochemical properties, antigenicity, and allergenicity were verified. Molecular dynamics modeling was employed to confirm interaction with TLR-2, TLR-4, B7-1, and B7-2. Finally, the vaccine underwent in silico cloning for expression.

RESULTS

The vaccine exhibited both antigenicity and non-allergenicity. Molecular dynamics simulation, post-docking with TLR-2, TLR-4, B7-1, and B7-2, demonstrated stable interaction between the vaccine and these molecules. In silico cloning confirmed effective expression of the vaccine gene in insect baculovirus vectors.

CONCLUSION

This vaccine-immunoinformatics approach holds promise for the development of vaccines against Mycoplasma pneumoniae and other pathogenic non-viral and non-bacterial microbes.

Identification of novel T-cell epitopes on monkeypox virus and development of multi-epitopes vaccine using immunoinformatics approaches

Monkeypox virus (MPV) is closely related to the smallpox virus, and previous data from Africa suggest that the smallpox vaccine (VARV) is at least 85% effective in preventing MPV. No multi-epitope vaccine has yet been developed to prevent MPV infection. In this work, we used in silico structural biology and advanced immunoinformatic strategies to design a multi-epitope subunit vaccine against MPV infection. The designed vaccine sequence is adjuvanted with CpG-ODN and includes HTL/CTL epitopes for similar proteins between vaccinia virus (VACV) that induced T-cell production in vaccinated volunteers and the first draft sequence of the MPV genome associated with the suspected outbreak in several countries, May 2022. In addition, the specific binding of the modified vaccine and the immune Toll-like receptor 9 (TLR9) was estimated by molecular interaction studies. Strong interaction in the binding groove as well as good docking scores confirmed the stringency of the modified vaccine. The stability of the interaction was confirmed by a classical molecular dynamics simulation and normal mode analysis. Then, the immune simulation also indicated the ability of this vaccine to induce an effective immune response against MPV. Codon optimization and in silico cloning of the vaccine into the pET-28a (+) vector also showed its expression potential in the E. coli K12 system. The promising data obtained from the various in silico studies indicate that this vaccine is effective against MPV. However, additional in vitro and in vivo studies are still needed to confirm its efficacy.Communicated by Ramaswamy H. Sarma.

Formulation of next-generation polyvalent vaccine candidates against three important poxviruses by targeting DNA-dependent RNA polymerase using an integrated immunoinformatics and molecular modeling approach

BACKGROUND

Poxviruses comprise a group of large double-stranded DNA viruses and are known to cause diseases in humans, livestock animals, and other animal species. The Mpox virus (MPXV; formerly Monkeypox), variola virus (VARV), and volepox virus (VPXV) are among the prevalent poxviruses of the Orthopoxviridae genera. The ongoing Mpox infectious disease pandemic caused by the Mpox virus has had a major impact on public health across the globe. To date, only limited repurposed antivirals and vaccines are available for the effective treatment of Mpox and other poxviruses that cause contagious diseases.

METHODS

The present study was conducted with the primary goal of formulating multi-epitope vaccines against three evolutionary closed poxviruses i.e., MPXV, VARV, and VPXV using an integrated immunoinformatics and molecular modeling approach. DNA-dependent RNA polymerase (DdRp), a potential vaccine target of poxviruses, has been used to determine immunodominant B and T-cell epitopes followed by interactions analysis with Toll-like receptor 2 at the atomic level.

RESULTS

Three multi-epitope vaccine constructs, namely DdRp_MPXV (V1), DdRp_VARV (V2), and DdRp_VPXV (V3) were designed. These vaccine constructs were found to be antigenic, non-allergenic, non-toxic, and soluble with desired physicochemical properties. Protein-protein docking and interaction profiling analysis depicts a strong binding pattern between the targeted immune receptor TLR2 and the structural models of the designed vaccine constructs, and manifested a number of biochemical bonds (hydrogen bonds, salt bridges, and non-bonded contacts). State-of-the-art all-atoms molecular dynamics simulations revealed highly stable interactions of vaccine constructs with TLR2 at the atomic level throughout the simulations on 300 nanoseconds. Additionally, the outcome of the immune simulation analysis suggested that designed vaccines have the potential to induce protective immunity against targeted poxviruses.

CONCLUSIONS

Taken together, formulated next-generation polyvalent vaccines were found to have good efficacy against closely related poxviruses (MPXV, VARV, and VPXV) as demonstrated by our extensive immunoinformatics and molecular modeling evaluations; however, further experimental investigations are still needed.

Integrating pan-genome and reverse vaccinology to design multi-epitope vaccine against Herpes simplex virus type-1

Herpes simplex virus type-1 (HSV-1), the etiological agent of sporadic encephalitis and recurring oral (sometimes genital) infections in humans, affects millions each year. The evolving viral genome reduces susceptibility to existing antivirals and, thus, necessitates new therapeutic strategies. Immunoinformatics strategies have shown promise in designing novel vaccine candidates in the absence of a clinically licensed vaccine to prevent HSV-1. However, to encourage clinical translation, the HSV-1 pan-genome was integrated with the reverse-vaccinology pipeline for rigorous screening of universal vaccine candidates. Viral targets were screened from 104 available complete genomes. Among 364 proteins, envelope glycoprotein D being an outer membrane protein with a high antigenicity score (> 0.4) and solubility (> 0.6) was selected for epitope screening. A total of 17 T-cell and 4 B-cell epitopes with highly antigenic, immunogenic, non-toxic properties and high global population coverage were identified. Furthermore, 8 vaccine constructs were designed using different combinations of epitopes and suitable linkers. VC-8 was identified as the most potential vaccine candidate regarding chemical and structural stability. Molecular docking revealed high interactive affinity (low binding energy: - 56.25 kcal/mol) of VC-8 with the target elicited by firm intermolecular H-bonds, salt-bridges, and hydrophobic interactions, which was validated with simulations. Compatibility of the vaccine candidate to be expressed in pET-29(a) + plasmid was established by in silico cloning studies. Immune simulations confirmed the potential of VC-8 to trigger robust B-cell, T-cell, cytokine, and antibody-mediated responses, thereby suggesting a promising candidate for the future of HSV-1 prevention.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-04022-6.

Reverse Vaccinology-Based Multi-Epitope Vaccine Design Against Indian Group A Rotavirus Targeting VP7, VP4, and VP6 Proteins

Rotavirus, a primary contributor to severe cases of infantile gastroenteritis on a global scale, results in significant morbidity and mortality in the under-five population, particularly in middle to low-income countries, including India. WHO-approved live-attenuated vaccines are linked to a heightened susceptibility to intussusception and exhibit low efficacy, primarily attributed to the high genetic diversity of rotavirus, varying over time and across different geographic regions. Herein, molecular data on Indian rotavirus A (RVA) has been reviewed through phylogenetic analysis, revealing G1P[8] to be the prevalent strain of RVA in India. The conserved capsid protein sequences of VP7, VP4 and VP6 were used to examine helper T lymphocyte, cytotoxic T lymphocyte and linear B cell epitopes. Twenty epitopes were identified after evaluation of factors such as antigenicity, non-allergenicity, non-toxicity, and stability. These epitopes were then interconnected using suitable linkers and an N-terminal beta defensin adjuvant. The in silico designed vaccine exhibited structural stability and interactions with integrins (αvβ3 and αIIbβ3) and toll-like receptors (TLR2 and TLR4) indicated by docking and normal mode analyses. The immune simulation profile of the designed RVA multiepitope vaccine exhibited its potential to trigger humoral as well as cell-mediated immunity, indicating that it is a promising immunogen. These computational findings indicate potential efficacy of the designed vaccine against rotavirus infection.

Computational exploration of SLC14A1 genetic variants through structure modeling, protein-ligand docking, and molecular dynamics simulation

The urea transporter UT-B1, encoded by the SLC14A1 gene, has been hypothesized to be a significant protein whose deficiency and dysfunction contribute to the pathogenesis of bladder cancer and many other diseases. Several studies reported the association of genetic alterations in the SLC14A1 (UT-B1) gene with bladder carcinogenesis, suggesting a need for thorough characterization of the UT-B1 protein's coding and non-coding variants. This study used various computational techniques to investigate the commonly occurring germ-line missense and non-coding SNPs (ncSNPs) of the SLC14A1 gene (UT-B1) for their structural, functional, and molecular implications for disease susceptibility and dysfunctionality. SLC14A1 missense variants, primarily identified from the ENSEMBL genome browser, were screened through twelve functionality prediction tools leading to two variants D280Y (predicted detrimental by maximum tools) and D280N (high global MAF) for rs1058396. Subsequently, the ConSurf and NetSurf tools revealed the D280 residue to be in a variable site and exposed on the protein surface. According to I-Mutant2.0 and MUpro, both variants are predicted to cause a significant effect on protein stability. Analysis of molecular docking anticipated these two variants to decrease the binding affinity of UT-B1 protein for the examined ligands to a significant extent. Molecular dynamics also disclosed the possible destabilization of the UT-B1 protein due to single nucleotide polymorphism compared to wild-type protein which may result in impaired protein function. Furthermore, several non-coding SNPs were estimated to affect transcription factor binding and regulation of SLC14A1 gene expression. Additionally, two ncSNPs were found to affect miRNA-based post-transcriptional regulation by creating new seed regions for miRNA binding. This comprehensive in-silico study of SLC14A1 gene variants may serve as a springboard for future large-scale investigations examining SLC14A1 polymorphisms.

Novel HER2-based multi-epitope vaccine (HER2-MEV) against HER2-positive breast cancer: In silico design and validation

Breast cancer (BC) continues to be the malignancy with the highest diagnosis rate worldwide. Between 15 % and 30 % of BC patients show overexpressed human epidermal growth factor receptor 2 (HER2), which is linked to poor clinical results in terms of invasiveness and recurrence risk. Passive immunity-based therapeutic approaches for treating HER2-enriched BC, are not effective and significant problems need to be tackled. Constructing multi-epitope vaccines is favored over single-epitope vaccines due to its ability to induce immunity against a variety of antigenic targets which will improve the efficacy of the vaccine. The current study describes a multi-epitope vaccine from HER2 protein against HER2-positive BC using several immunoinformatic techniques to achieve a potent and durable immune response. Nine Cytotoxic T lymphocytes (CTL) and five Helper T lymphocytes (HTL) epitopes were predicted and validated from HER2 protein using in silico tools. The expressed protein of the designed vaccine is predicted to be highly thermostable with better solubility. The predicted vaccine 3D structure was validated by ProSA servers and by the ERRAT server. Molecular docking analysis revealed a high binding affinity and stability of the designed vaccine with MHCI and TLR-2, 4, 7, and 9 receptors. The analysis of the C-ImmSim server revealed that the novel vaccine construct had the ability to elicit robust anti-cancerous innate, humoral, and cell-mediated immune responses. The vaccine can be a suitable option for HER2-positive BC patients and other patients with HER2-positive cancers to evoke immune responses. However, in vitro and in vivo experiments are needed to assess its effectiveness and safety.

Computational design of novel chimeric multiepitope vaccine against bacterial and viral disease in tilapia (Oreochromis sp.)

Regarding several infectious diseases in fish, multiple vaccinations are not favorable. The chimeric multiepitope vaccine (CMEV) harboring several antigens for multi-disease prevention would enhance vaccine efficiency in terms of multiple disease prevention. Herein, the immunogens of tilapia's seven pathogens including E. tarda, F. columnare, F. noatunensis, S. iniae, S. agalactiae, A. hydrophila, and TiLV were used for CMEV design. After shuffling and annotating the B-cell epitopes, 5,040 CMEV primary protein structures were obtained. Secondary and tertiary protein structures were predicted by AlphaFold2 creating 25,200 CMEV. Proper amino acid alignment in the secondary structures was achieved by the Ramachandran plot. In silico determination of physiochemical and other properties including allergenicity, antigenicity, glycosylation, and conformational B-cell epitopes were determined. The selected CMEV (OSLM0467, OSLM2629, and OSLM4294) showed a predicted molecular weight (MW) of 70 kDa, with feasible sites of N- and O-glycosylation, and a number of potentially conformational B-cell epitope residues. Molecular docking, codon optimization, and in-silico cloning were tested to evaluate the possibility of protein expression. Those CMEVs will further elucidate in vitro and in vivo to evaluate the efficacy and specific immune response. This research will highlight the new era of vaccines designed based on in silico structural vaccine design.

Drug to genome to drug: a computational large-scale chemogenomics screening for novel drug candidates against sporotrichosis

Sporotrichosis is recognized as the predominant subcutaneous mycosis in South America, attributed to pathogenic species within the Sporothrix genus. Notably, in Brazil, Sporothrix brasiliensis emerges as the principal species, exhibiting significant sapronotic, zoonotic and enzootic epidemic potential. Consequently, the discovery of novel therapeutic agents for the treatment of sporotrichosis is imperative. The present study is dedicated to the repositioning of pharmaceuticals for sporotrichosis therapy. To achieve this goal, we designed a pipeline with the following steps: (a) compilation and preparation of Sporothrix genome data; (b) identification of orthologous proteins among the species; (c) identification of homologous proteins in publicly available drug-target databases; (d) selection of Sporothrix essential targets using validated genes from Saccharomyces cerevisiae; (e) molecular modeling studies; and (f) experimental validation of selected candidates. Based on this approach, we were able to prioritize eight drugs for in vitro experimental validation. Among the evaluated compounds, everolimus and bifonazole demonstrated minimum inhibitory concentration (MIC) values of 0.5 µg/mL and 4.0 µg/mL, respectively. Subsequently, molecular docking studies suggest that bifonazole and everolimus may target specific proteins within S. brasiliensis- namely, sterol 14-α-demethylase and serine/threonine-protein kinase TOR, respectively. These findings shed light on the potential binding affinities and binding modes of bifonazole and everolimus with their probable targets, providing a preliminary understanding of the antifungal mechanism of action of these compounds. In conclusion, our research advances the understanding of the therapeutic potential of bifonazole and everolimus, supporting their further investigation as antifungal agents for sporotrichosis in prospective hit-to-lead and preclinical investigations.

Antibiotic discovery with artificial intelligence for the treatment of Acinetobacter baumannii infections

Global challenges presented by multidrug-resistant Acinetobacter baumannii infections have stimulated the development of new treatment strategies. We reported that outer membrane protein W (OmpW) is a potential therapeutic target in A. baumannii. Here, a library of 11,648 natural compounds was subjected to a primary screening using quantitative structure-activity relationship (QSAR) models generated from a ChEMBL data set with >7,000 compounds with their reported minimal inhibitory concentration (MIC) values against A. baumannii followed by a structure-based virtual screening against OmpW. In silico pharmacokinetic evaluation was conducted to assess the drug-likeness of these compounds. The ten highest-ranking compounds were found to bind with an energy score ranging from -7.8 to -7.0 kcal/mol where most of them belonged to curcuminoids. To validate these findings, one lead compound exhibiting promising binding stability as well as favorable pharmacokinetics properties, namely demethoxycurcumin, was tested against a panel of A. baumannii strains to determine its antibacterial activity using microdilution and time-kill curve assays. To validate whether the compound binds to the selected target, an OmpW-deficient mutant was studied and compared with the wild type. Our results demonstrate that demethoxycurcumin in monotherapy and in combination with colistin is active against all A. baumannii strains. Finally, the compound was found to significantly reduce the A. baumannii interaction with host cells, suggesting its anti-virulence properties. Collectively, this study demonstrates machine learning as a promising strategy for the discovery of curcuminoids as antimicrobial agents for combating A. baumannii infections.

IMPORTANCE

Acinetobacter baumannii presents a severe global health threat, with alarming levels of antimicrobial resistance rates resulting in significant morbidity and mortality in the USA, ranging from 26% to 68%, as reported by the Centers for Disease Control and Prevention (CDC). To address this threat, novel strategies beyond traditional antibiotics are imperative. Computational approaches, such as QSAR models leverage molecular structures to predict biological effects, expediting drug discovery. We identified OmpW as a potential therapeutic target in A. baumannii and screened 11,648 natural compounds. We employed QSAR models from a ChEMBL bioactivity data set and conducted structure-based virtual screening against OmpW. Demethoxycurcumin, a lead compound, exhibited promising antibacterial activity against A. baumannii, including multidrug-resistant strains. Additionally, demethoxycurcumin demonstrated anti-virulence properties by reducing A. baumannii interaction with host cells. The findings highlight the potential of artificial intelligence in discovering curcuminoids as effective antimicrobial agents against A. baumannii infections, offering a promising strategy to address antibiotic resistance.

Subtractive proteomics-based vaccine targets annotation and reverse vaccinology approaches to identify multiepitope vaccine against Plesiomonas shigelloides

Plesiomonas shigelloides, an aquatic bacterium belonging to the Enterobacteriaceae family, is a frequent cause of gastroenteritis with diarrhea and gastrointestinal severe disease. Despite decades of research, discovering a licensed and globally accessible vaccine is still years away. Developing a putative vaccine that can combat the Plesiomonas shigelloides infection by boosting population immunity against P. shigelloides is direly needed. In the framework of the current study, the entire proteome of P. shigelloides was explored using subtractive genomics integrated with the immunoinformatics approach for designing an effective vaccine construct against P. shigelloides. The overall stability of the vaccine construct was evaluated using molecular docking, which demonstrated that MEV showed higher binding affinities with toll-like receptors (TLR4: 51.5 ± 10.3, TLR2: 60.5 ± 9.2) and MHC receptors(MHCI: 79.7 ± 11.2 kcal/mol, MHCII: 70.4 ± 23.7). Further, the therapeutic efficacy of the vaccine construct for generating an efficient immune response was evaluated by computational immunological simulation. Finally, computer-based cloning and improvement in codon composition without altering amino acid sequence led to the development of a proposed vaccine. In a nutshell, the findings of this study add to the existing knowledge about the pathogenesis of this infection. The schemed MEV can be a possible prophylactic agent for individuals infected with P. shigelloides. Nevertheless, further authentication is required to guarantee its safeness and immunogenic potential.

Evaluation of humoral and cellular immune responses against Vibrio cholerae using oral immunization by multi-epitope-phage-based vaccine

INTRODUCTION

Cholera is a severe gastrointestinal disease that manifests with rapid onset of diarrhea, vomiting, and high mortality rates. Due to its widespread occurrence in impoverished communities with poor water sanitation, there is an urgent demand for a cost-effective and highly efficient vaccine. Multi-epitope vaccines containing dominant immunological epitopes and adjuvant compounds have demonstrated potential in boosting the immune response.

MATERIAL AND METHODS

B and T epitopes of OMPU, OMPW, TCPA, CTXA, and CTXB proteins were predicted using bioinformatics methods. Subsequently, highly antigenic multi-epitopes that are non-allergenic and non-toxic were synthesized. These multi-epitopes were then cloned into the pCOMB phagemid. A plasmid M13KO7ΔpIII containing all helper phage proteins except pIII was created to produce the recombinant phage. Female Balb/c mice were divided into three groups and immunized accordingly. The mice received the helper phage, recombinant phage or PBS via gavage feeding thrice within two weeks. Serum samples were collected before and after immunization for the ELISA test as well as evaluating immune system induction through ELISpot testing of spleen lymphocytes.

RESULTS

The titer of the recombinant phage was determined to be 1011 PFU/ml. The presence of the recombinant phage was confirmed through differences in optical density between sample and control groups in the ELISA phage technique, as well as by observing transduction activity, which demonstrated successful production of a recombinant phage displaying the Vibrio multi-epitope on M13 phage pIII. ELISA results revealed significant differences in phage antibodies before and after inoculation, particularly notable in the negative control mice. Mice treated with multi-epitope phages exhibited antibodies against Vibrio cholerae lysate. Additionally, ELISpot results indicated activation of cellular immunity in mice receiving both Vibrio and helper phage.

CONCLUSION

This study emphasizes the potential of multi-epitope on phage to enhance both cellular and humoral immunity in mice, demonstrating how phages can be used as adjuvants to stimulate mucosal immunity and act as promising candidates for oral vaccination.

An integrated in silico approach for the identification of novel potential drug target and chimeric vaccine against Neisseria meningitides strain 331401 serogroup X by subtractive genomics and reverse vaccinology

Neisseria meningitidis, commonly known as the meningococcus, leads to substantial illness and death among children and young adults globally, revealing as either epidemic or sporadic meningitis and/or septicemia. In this study, we have designed a novel peptide-based chimeric vaccine candidate against the N. meningitidis strain 331,401 serogroup X. Through rigorous analysis of subtractive genomics, two essential cytoplasmic proteins, namely UPI000012E8E0(UDP-3-O-acyl-GlcNAc deacetylase) and UPI0000ECF4A9(UDP-N-acetylglucosamine acyltransferase) emerged as potential drug targets. Additionally, using reverse vaccinology, the outer membrane protein UPI0001F4D537 (Membrane fusion protein MtrC) identified by subcellular localization and recognized for its known indispensable role in bacterial survival was identified as a novel chimeric vaccine target. Following a careful comparison of MHC-I, MHC-II, T-cell, and B-cell epitopes, three epitopes derived from UPI0001F4D537 were linked with three types of linkers-GGGS, EAAAK, and the essential PADRE-for vaccine construction. This resulted in eight distinct vaccine models (V1-V8). Among them V1 model was selected as the final vaccine construct. It exhibits exceptional immunogenicity, safety, and enhanced antigenicity, with 97.7 % of its residues in the Ramachandran plot's most favored region. Subsequently, the vaccine structure was docked with the TLR4/MD2 complex and six different HLA allele receptors using the HADDOCK server. The docking resulted in the lowest HADDOCK score of 39.3 ± 9.0 for TLR/MD2. Immune stimulation showed a strong immune response, including antibodies creation and the activation of B-cells, T Cytotoxic cells, T Helper cells, Natural Killer cells, and interleukins. Furthermore, the vaccine construct was successfully expressed in the Escherichia coli system by reverse transcription, optimization, and ligation in the pET-28a (+) vector for the expression study. The current study proposes V1 construct has the potential to elicit both cellular and humoral responses, crucial for the developing an epitope-based vaccine against N. meningitidis strain 331,401 serogroup X.

Epitope screening and self-assembled nanovaccine molecule design of PDCoV-S protein based on immunoinformatics

Based on the whole virus or spike protein of pigs, δ coronavirus (PDCoV) as an immunogen may have unrelated antigenic epitope interference. Therefore, it is essential for screening and identifying advantageous protective antigen epitopes. In addition, immunoinformatic tools are described as an important aid in determining protective antigenic epitopes. In this study, the primary, secondary, and tertiary structures of vaccines were measured using ExPASy, PSIPRED 4.0, and trRosetta servers. Meanwhile, the molecular docking analysis and vector of the candidate nanovaccine were constructed. The immune response of the candidate vaccine was simulated and predicted using the C-ImmSim server. This experiment screened B cell epitopes with strong immunogenicity and high conservation, CTL epitopes, and Th epitopes with IFN-γ and IL-4 positive spike proteins. Ferritin is used as a self-assembled nanoparticle element for designing candidate nanovaccine. After analysis, it has been found to be soluble, stable, non-allergenic, and has a high affinity for its target receptor, TLR-3. The preliminary simulation analysis results show that the candidate nanovaccine has the ability to induce a humoral and cellular immune response. Therefore, it may provide a new theoretical basis for research on coronavirus self-assembled nanovaccines. It may be an effective candidate vaccine for controlling and preventing PDCoV.

Decoding the Structure-Function Relationship of the Muramidase Domain in E. coli O157.H7 Bacteriophage Endolysin: A Potential Building Block for Chimeric Enzybiotics

Bacteriophage endolysins are potential alternatives to conventional antibiotics for treating multidrug-resistant gram-negative bacterial infections. However, their structure-function relationships are poorly understood, hindering their optimization and application. In this study, we focused on the individual functionality of the C-terminal muramidase domain of Gp127, a modular endolysin from E. coli O157:H7 bacteriophage PhaxI. This domain is responsible for the enzymatic activity, whereas the N-terminal domain binds to the bacterial cell wall. Through protein modeling, docking experiments, and molecular dynamics simulations, we investigated the activity, stability, and interactions of the isolated C-terminal domain with its ligand. We also assessed its expression, solubility, toxicity, and lytic activity using the experimental data. Our results revealed that the C-terminal domain exhibits high activity and toxicity when tested individually, and its expression is regulated in different hosts to prevent self-destruction. Furthermore, we validated the muralytic activity of the purified refolded protein by zymography and standardized assays. These findings challenge the need for the N-terminal binding domain to arrange the active site and adjust the gap between crucial residues for peptidoglycan cleavage. Our study shed light on the three-dimensional structure and functionality of muramidase endolysins, thereby enriching the existing knowledge pool and laying a foundation for accurate in silico modeling and the informed design of next-generation enzybiotic treatments.

Exploring the structural assembly of rice ADP-glucose pyrophosphorylase subunits using MD simulation

ADP-glucose pyrophosphorylase plays a pivotal role as an allosteric enzyme, essential for starch biosynthesis in plants. The higher plant AGPase comparises of a pair of large and a pair of small subunits to form a heterotetrameric complex. Growing evidence indicates that each subunit plays a distinct role in regulating the underlying mechanism of starch biosynthesis. In the rice genome, there are four large subunit genes (OsL1-L4) and three small subunit genes (OsS1, OsS2a, and OsS2b). While the structural assembly of cytosolic rice AGPase subunits (OsL2:OsS2b) has been elucidated, there is currently no such documented research available for plastidial rice AGPases (OsL1:OsS1). In this study, we employed protein modeling and MD simulation approaches to gain insights into the structural association of plastidial rice AGPase subunits. Our results demonstrate that the heterotetrameric association of OsL1:OsS1 is very similar to that of cytosolic OsL2:OsS2b and potato AGPase heterotetramer (StLS:StSS). Moreover, the yeast-two-hybrid results on OsL1:OsS1, which resemble StLS:StSS, suggest a differential protein assembly for OsL2:OsS2b. Thus, the regulatory and catalytic mechanisms for plastidial AGPases (OsL1:OsS1) could be different in rice culm and developing endosperm compared to those of OsL2:OsS2b, which are predominantly found in rice endosperm.

Exploring malaria parasite surface proteins to devise highly immunogenic multi-epitope subunit vaccine for Plasmodium falciparum

BACKGROUND

Malaria has remained a major health concern for decades among people living in tropical and sub-tropical countries. Plasmodium falciparum is one of the critical species that cause severe malaria and is responsible for major mortality. Moreover, the parasite has generated resistance against all WHO recommended drugs and therapies. Therefore, there is an urgent need for preventive measures in the form of reliable vaccines to achieve the target of a malaria-free world. Surface proteins are the preferable choice for subunit vaccine development because they are rapidly detected and engaged by host immune cells and vaccination-induced antibodies. Additionally, abundant surface or membrane proteins may contribute to the opsonization of pathogens by vaccine-induced antibodies.

RESULTS

In our study, we have listed all those surface proteins from the literature that could be functionally important and essential for infection and immune evasion of the malaria parasite. Eight Plasmodium surface and membrane proteins from the pre-erythrocyte and erythrocyte stages were shortlisted. Thirty-seven epitopes (B-cell, CTL, and HTL epitopes) from these proteins were predicted using immune-informatic tools and joined with suitable peptide linkers to design a vaccine construct. A TLR-4 agonist peptide adjuvant was added at the N-terminus of the multi-epitope series, followed by the PADRE sequence and EAAAK linker. The TLR-4 receptor was docked with the construct's anticipated model structure. The complex of vaccine and TLR-4, with the lowest energy -1514, was found to be stable under simulated physiological settings.

CONCLUSION

This study has provided a novel multi-epitope construct that may be exploited further for the development of an efficient vaccine for malaria.

Delineating the mechanistic relevance of the TP53 gene and its mutational impact on gene expression and patients' survival in bladder cancer

Bladder carcinoma (BLCA) is a widespread urological malignancy causing significant global mortality, often hindered by delayed diagnosis and limited treatments. BLCA frequently exhibits TP53 mutations, playing a pivotal role in its pathogenesis and underscoring the potential of targeting TP53 as a therapeutic approach for this prevalent urological malignancy. Tumor tissues from 50 bladder cancer patients were used for mutational analysis in TP53's mutation-rich exons (5, 7, & 8). The gene expression of the TP53 gene, along with a TP53-target gene B-cell translocation gene 2 (BTG2) was also assessed in the cDNA samples from the same BLCA tissues and 15 urine controls of healthy people. The analysis revealed 22 % of patients with somatic hotspot mutations, 18 % with pathogenic missense mutations, and 12 % with intronic variants. Patients with somatic mutations exhibited the worst prognosis, supported by survival analysis from The Cancer Genome Atlas (TCGA) BLCA data. Interestingly, H296Y missense mutation correlated with higher TP53 expression and improved survival, while intronic SNPs were linked to worse outcomes. Additionally, upregulated BTG2 expression in mutated patients was observed which was correlated with poor prognosis, emphasizing the role of TP53 mutations in bladder cancer progression. The multivariate analysis highlighted the predictive power of TP53 mutations, with a high frequency of high-grade tumors (78.57 %) in mutated patients, underscoring their role in cancer progression. In conclusion, this study emphasizes the crucial role of TP53 mutations in bladder cancer patients from Bangladesh.

Efficient Refinement of Complex Structures of Flexible Histone Peptides Using Post-Docking Molecular Dynamics Protocols

Histones are keys to many epigenetic events and their complexes have therapeutic and diagnostic importance. The determination of the structures of histone complexes is fundamental in the design of new drugs. Computational molecular docking is widely used for the prediction of target-ligand complexes. Large, linear peptides like the tail regions of histones are challenging ligands for docking due to their large conformational flexibility, extensive hydration, and weak interactions with the shallow binding pockets of their reader proteins. Thus, fast docking methods often fail to produce complex structures of such peptide ligands at a level appropriate for drug design. To address this challenge, and improve the structural quality of the docked complexes, post-docking refinement has been applied using various molecular dynamics (MD) approaches. However, a final consensus has not been reached on the desired MD refinement protocol. In this present study, MD refinement strategies were systematically explored on a set of problematic complexes of histone peptide ligands with relatively large errors in their docked geometries. Six protocols were compared that differ in their MD simulation parameters. In all cases, pre-MD hydration of the complex interface regions was applied to avoid the unwanted presence of empty cavities. The best-performing protocol achieved a median of 32% improvement over the docked structures in terms of the change in root mean squared deviations from the experimental references. The influence of structural factors and explicit hydration on the performance of post-docking MD refinements are also discussed to help with their implementation in future methods and applications.

Systems approach to design multi-epitopic peptide vaccine candidate against fowl adenovirus structural proteins for Gallus gallus domesticus

Introduction

Fowl adenovirus (FAdV) is a significant pathogen in poultry, causing various diseases such as hepatitis-hydropericardium, inclusion body hepatitis, and gizzard erosion. Different serotypes of FAdV are associated with specific conditions, highlighting the need for targeted prevention strategies. Given the rising prevalence of FAdV-related diseases globally, effective vaccination and biosecurity measures are crucial. In this study, we explore the potential of structural proteins to design a multi-epitope vaccine targeting FAdV.

Methods

We employed an in silico approach to design the multi-epitope vaccine. Essential viral structural proteins, including hexon, penton, and fiber protein, were selected as vaccine targets. T-cell and B-cell epitopes binding to MHC-I and MHC-II molecules were predicted using computational methods. Molecular docking studies were conducted to validate the interaction of the multi-epitope vaccine candidate with chicken Toll-like receptors 2 and 5.

Results

Our in silico methodology successfully identified potential T-cell and B-cell epitopes within the selected viral structural proteins. Molecular docking studies revealed strong interactions between the multi-epitope vaccine candidate and chicken Toll-like receptors 2 and 5, indicating the structural integrity and immunogenic potential of the designed vaccine.

Discussion

The designed multi-epitope vaccine presents a promising approach for combating FAdV infections in chickens. By targeting essential viral structural proteins, the vaccine is expected to induce a robust immunological response. The in silico methodology utilized in this study provides a rapid and cost-effective means of vaccine design, offering insights into potential vaccine candidates before experimental validation. Future studies should focus on in vitro and in vivo evaluations to further assess the efficacy and safety of the proposed vaccine.

Investigating the Taenia solium Fatty Acid Binding Protein Superfamily for Their Immunological Outlook and Prospect for Therapeutic Targets

Taenia solium, like other helminthic parasites, lacks key components of cellular machinery required for endogenous lipid biosynthesis. This deficiency compels the parasite to obtain all of its lipid requirements from its host. The passage of lipids across the cell membrane is tightly regulated. To facilitate effective lipid transport, the cestode parasite utilizes certain lipid binding proteins called FABPs. These FABPs bind with the lipid ligands and allow the transport of lipids across the membranes and into the cytosol. Here, by integrating a computational with homology protein prediction tools, we had identified five FABPs in the T. solium proteome. We confirmed their presence by RNA expression analysis of respective genes from the parasite's cysticerci transcript. During the molecular modeling and MD simulation studies, two of them, TsM_000544100 and TsM_001185100, were most stable. Furthermore, they had a robust interaction with the IgG1 molecule, as evidenced by MD simulation. In addition, by employing in silico screening, we had identified potential ligand interacting residues that are present on the probable druggable site. In combination with in vitro cysticidal assays, enalaprilat dihydrate showed efficacy against cysticerci, which suggests that FABPs play a significant role in the cysticercus life cycle. Together, we provided a detailed distribution of all FABPs expressed by T. solium cysticerci and the critical role of TsM_001185100 in cysticercus viability.

Mitigating candidiasis with acarbose by targeting Candida albicans α-glucosidase: in-silico, in-vitro and transcriptomic approaches

Biofilm-associated candidiasis poses a significant challenge in clinical settings due to the limited effectiveness of existing antifungal treatments. The challenges include increased pathogen virulence, multi-drug resistance, and inadequate penetration of antimicrobials into biofilm structures. One potential solution to this problem involves the development of novel drugs that can modulate fungal virulence and biofilm formation, which is essential for pathogenesis. Resistance in Candida albicans is initiated by morphological changes from yeast to hyphal form. This transition triggers a series of events such as cell wall elongation, increased adhesion, invasion of host tissues, pathogenicity, biofilm formation, and the initiation of an immune response. The cell wall is a critical interface for interactions with host cells, primarily through various cell wall proteins, particularly mannoproteins. Thus, cell wall proteins and enzymes are considered potential antifungal targets. In this regard, we explored α-glucosidase as our potential target which plays a crucial role in processing mannoproteins. Previous studies have shown that inhibition of α-glucosidase leads to defects in cell wall integrity, reduced adhesion, diminished secretion of hydrolytic enzymes, alterations in immune recognition, and reduced pathogenicity. Since α-glucosidase, primarily converts carbohydrates, our study focuses on FDA-approved carbohydrate mimic drugs (Glycomimetics) with well-documented applications in various biological contexts. Through virtual screening of 114 FDA-approved carbohydrate-based drugs, a pseudo-sugar Acarbose, emerged as a top hit. Acarbose is known for its pharmacological potential in managing type 2 diabetes mellitus by targeting α-glucosidase. Our preliminary investigations indicate that Acarbose effectively inhibits C. albicans biofilm formation, reduces virulence, impairs morphological switching, and hinders the adhesion and invasion of host cells, all at very low concentrations in the nanomolar range. Furthermore, transcriptomic analysis reveals the mechanism of action of Acarbose, highlighting its role in targeting α-glucosidase.

Development of multi epitope subunit vaccines against emerging carp viruses Cyprinid herpesvirus 1 and 3 using immunoinformatics approach

Cyprinid herpesvirus is a causative agent of a destructive disease in common and koi carp (Cyprinus carpio), which leads to substantial global financial losses in aquaculture industries. Among the strains of C. herpesvirus, C. herpesvirus 1 (CyHV-1) and C. herpesvirus 3 (CyHV-3) are known as highly pathogenic to carp fishes in Europe, Asia, and Africa. To date, no effective vaccine has been developed to combat these viruses. This study aimed to develop unique multi-epitope subunit vaccines targeting the CyHV-1 and CyHV-3 using a reverse vaccinology approach. The study began with a comprehensive literature review to identify the most critical proteins, which were then subjected to in silico analyses to predict highly antigenic epitopes. These analyses involved assessing antigenicity, transmembrane topology screening, allergenecity, toxicity, and molecular docking approaches. We constructed two multi-epitope-based vaccines incorporating a suitable adjuvant and appropriate linkers. It revealed that both the vaccines are non-toxic and immunogenic. The tertiary structures of the vaccine proteins were generated, refined, and validated to ensure their suitability. The binding affinity between the vaccine constructs and TLR3 and TLR5 receptors were assessed by molecular docking studies. Molecular dynamics simulations indicated that vaccine construct V1 exhibited greater stability with both TLR3 and TLR5 based on RMSD analysis. Hydrogen bond analysis revealed a stronger binding affinity between the vaccine constructs and TLR5 compared to TLR3. Furthermore, MM-PBSA analysis suggested that both vaccine constructs exhibited a better affinity for TLR5. Considering all aspects, the results suggest that in silico development of CyHV vaccines incorporating multiple epitopes holds promise for management of diseases caused by CyHV-1 and CyHV-3. However, further in vivo trials are highly recommended to validate the efficacies of these vaccines.

Exploring the Antibacterial Potential of Artemisia judaica Compounds Targeting the Hydrolase/Antibiotic Protein in Klebsiella pneumoniae: In Vitro and In Silico Investigations

Carbapenem antibiotic resistance is an emerging medical concern. Bacteria that possess the Klebsiella pneumoniae carbapenemase (KPC) protein, an enzyme that catalyzes the degradation of carbapenem antibiotics, have exhibited remarkable resistance to traditional and even modern therapeutic approaches. This study aimed to identify potential natural drug candidates sourced from the leaves of Artemisia judaica (A. judaica). The phytoconstituents present in A. judaica dried leaves were extracted using ethanol 80%. A reasonable amount of the extract was used to identify these phytochemicals via gas chromatography/mass spectrometry (GC/MS). One hundred twenty-two bioactive compounds from A. judaica were identified and subjected to docking analysis against the target bacterial protein. Four compounds (PubChem CID: 6917974, 159099, 628694, and 482788) were selected based on favorable docking scores (-9, -7.8, -7.7, and -7.5 kcal/mol). This computational investigation highlights the potential of these four compounds as promising antibacterial candidates against the specific KPC protein. Additionally, in vitro antibacterial assays using A. judaica extracts were conducted. The minimum inhibitory concentration (MIC) against the bacterium K. pneumonia was 125 μg/mL. Well-disk diffusion tests exhibited inhibition zones ranging from 10.3 ± 0.5 mm to 17 ± 0.5 mm at different concentrations, and time-kill kinetics at 12 h indicated effective inhibition of bacterial growth by A. judaica leaf extracts. Our findings have revealed the pharmaceutical potential of Artemisia judaica as a natural source for drug candidates against carbapenem-resistant pathogens.

Integrating 16S rRNA profiling and in-silico analysis for an epitope-based vaccine strategy against Achromobacter xylosoxidans infection

Achromobacter xylosoxidans is an aerobic, catalase-positive, non-pigment-forming, Gram-negative, and motile bacterium. It potentially causes a wide range of human infections in cystic fibrosis and non-cystic fibrosis patients. However, developing a safe preventive or therapeutic solution against A. xylosoxidans remains challenging. This study aimed to construct an epitope-based vaccine candidate using immunoinformatic techniques. A. xylosoxidans was isolated from an auto workshop in Lahore, and its identification was confirmed through 16S rRNA amplification and bioinformatic analysis. Two protein targets with GenBank accession numbers AKP90890.1 and AKP90355.1 were selected for the vaccine construct. Both proteins exhibited antigenicity, with scores of 0.757 and 0.580, respectively and the epitopes were selected based on the IC50 value using the ANN 4.0 and NN-align 2.3 epitope prediction method for MHC I and MHC II epitopes respectively and predicted epitopes were analyzed for antigenicity, allergenicity and pathogenicity. The vaccine construct demonstrated structural stability, thermostability, solubility, and hydrophilicity. The vaccine produced 250 B-memory cells per mm3 and approximately 16,000 IgM + IgG counts, indicating an effective immune response against A. xylosoxidans. Moreover, the vaccine candidate interacted stably with toll-like receptor 5, a pattern recognition receptor, with a confidence score of 0.98. These results highlight the potency of the designed vaccine candidate, suggesting its potential to withstand rigorous in vitro and in vivo clinical trials. This epitope-based vaccine could serve as the first preventive immunotherapy against A. xylosoxidans infections, addressing this bacterium's health and financial burdens. The findings demonstrate the value of employing immunoinformatic tools in vaccine development, paving the way for more precise and tailored approaches to combating microbial threats.

Isolation and Characterization of the Vascular Endothelial Growth Factor Receptor Targeting ScFv Antibody Fragments Derived from Phage Display Technology

Angiogenesis, as a tumor hallmark, plays an important role in the growth and development of the tumor vasculature system. There is a huge amount of evidence suggesting that the vascular endothelial growth factor receptor (VEGFR-2)/VEGF-A axis is one of the main contributors to tumor angiogenesis and metastasis. Thus, inhibition of the VEGFR-2 signaling pathway by anti-VEGFR-2 mAb can retard tumor growth. In this study, we employ phage display technology and solution-phase biopanning (SPB) to isolate specific single-chain variable fragments (scFvs) against VEGFR-2 and report on the receptor binding characteristics of the candidate scFvs A semisynthetic phage antibody library to isolate anti-VEGFR-2 scFvs through an SPB performed with decreasing concentrations of the VEGFR-2-His tag and VEGFR-2-biotin. After successful expression and purification, the specificity of the selected scFv clones was further analyzed by enzyme-linked immunosorbent assay (ELISA), flow cytometry, and immunoblotting. The competition assay was undertaken to identify the VEGFR-2 receptor-blocking properties of the scFvs. Furthermore, the molecular binding characteristics of candidate scFvs were extensively studied by peptide-protein docking. Polyclonal ELISA analysis subsequent to four rounds of biopanning showed a significant enrichment of VEGFR-2-specific phage clones by increasing positive signals from the first round toward the fourth round of selection. The individual VEGFR-2-reactive scFv phage clones were identified by monoclonal phage ELISA. The sequence analysis and complementarity-determining region alignment identified the four unique anti-VEGFR-2-scFv clones. The soluble and purified scFvs displayed binding activity against soluble and cell-associated forms of VEGFR-2 protein in the ELISA and flow cytometry assays. Based on the inference from the molecular docking results, scFvs D3, E1, H1, and E9 recognized domains 2 and 3 on the VEGFR-2 protein and displayed competition with VEGF-A for binding to VEGFR-2. The competition assay confirmed that scFvs H1 and D3 can block the VEGFR-2/VEGF-A interaction. In conclusion, we identified novel VEGFR-2-blocking scFvs that perhaps exhibit the potential for angiogenesis inhibition in VEGFR-2-overexpressed tumor cells.

In silico design and evaluation of a multiepitope vaccine targeting the nucleoprotein of Puumala orthohantavirus

The Puumala orthohantavirus is present in the body of the bank vole (Myodes glareolus). Humans infected with this virus may develop hemorrhagic fever accompanying renal syndrome. In addition, the infection may further lead to the failure of an immune system completely. The present study aimed to propose a possible vaccine by employing bioinformatics techniques to identify B and T-cell antigens. The best multi-epitope of potential immunogenicity was generated by combining epitopes. Additionally, the linkers EAAAK, AAY, and GPGPG were utilized in order to link the epitopes successfully. Further, C-ImmSim was used to perform in silico immunological simulations upon the vaccine. For the purpose of conducting expression tests in Escherichia coli, the chimeric protein construct was cloned using Snapgene into the pET-9c vector. The designed vaccine showed adequate results, evidenced by the global population coverage and favorable immune response. The developed vaccine was found to be highly effective and to have excellent population coverage in a number of computer-based assessments. This work is fully dependent on the development of nucleoprotein-based vaccines, which would constitute a significant step forward if our findings were used in developing a global vaccination to combat the Puumala virus.

Abrogation of ORF8-IRF3 binding interface with Carbon nanotube derivatives to rescue the host immune system against SARS-CoV-2 by using molecular screening and simulation approaches

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to over six million deaths worldwide. In human immune system, the type 1 interferon (IFN) pathway plays a crucial role in fighting viral infections. However, the ORF8 protein of the virus evade the immune system by interacting with IRF3, hindering its nuclear translocation and consequently downregulate the type I IFN signaling pathway. To block the binding of ORF8-IRF3 and inhibit viral pathogenesis a quick discovery of an inhibitor molecule is needed. Therefore, in the present study, the interface between the ORF8 and IRF3 was targeted on a high-affinity carbon nanotube by using computational tools. After analysis of 62 carbon nanotubes by multiple docking with the induced fit model, the top five compounds with high docking scores of - 7.94 kcal/mol, - 7.92 kcal/mol, - 7.28 kcal/mol, - 7.19 kcal/mol and - 7.09 kcal/mol (top hit1-5) were found to have inhibitory activity against the ORF8-IRF3 complex. Molecular dynamics analysis of the complexes revealed the high compactness of residues, stable binding, and strong hydrogen binding network among the ORF8-nanotubes complexes. Moreover, the total binding free energy for top hit1-5 was calculated to be - 43.21 ± 0.90 kcal/mol, - 41.17 ± 0.99 kcal/mol, - 48.85 ± 0.62 kcal/mol, - 43.49 ± 0.77 kcal/mol, and - 31.18 ± 0.78 kcal/mol respectively. These results strongly suggest that the identified top five nanotubes (hit1-5) possess significant potential for advancing and exploring innovative drug therapies. This underscores their suitability for subsequent in vivo and in vitro experiments, marking them as promising candidates worthy of further investigation.

Decrypting the multi-genome data for chimeric vaccine designing against the antibiotic resistant Yersinia pestis

Yersinia pestis, the causative agent of plague, is a gram-negative bacterium that can be fatal if not treated properly. Three types of plague are currently known: bubonic, septicemic, and pneumonic plague, among which the fatality rate of septicemic and pneumonic plague is very high. Bubonic plague can be treated, but only if antibiotics are used at the initial stage of the infection. But unfortunately, Y. pestis has also shown resistance to certain antibiotics such as kanamycin, minocycline, tetracycline, streptomycin, sulfonamides, spectinomycin, and chloramphenicol. Despite tremendous progress in vaccine development against Y. pestis, there is no proper FDA-approved vaccine available to protect people from its infections. Therefore, effective broad-spectrum vaccine development against Y. pestis is indispensable. In this study, vaccinomics-assisted immunoinformatics techniques were used to find possible vaccine candidates by utilizing the core proteome prepared from 58 complete genomes of Y. pestis. Human non-homologous, pathogen-essential, virulent, and extracellular and membrane proteins are potential vaccine targets. Two antigenic proteins were prioritized for the prediction of lead epitopes by utilizing reverse vaccinology approaches. Four vaccine designs were formulated using the selected B- and T-cell epitopes coupled with appropriate linkers and adjuvant sequences capable of inducing potent immune responses. The HLA allele population coverage of the T-cell epitopes selected for vaccine construction was also analyzed. The V2 constructs were top-ranked and selected for further analysis on the basis of immunological, physicochemical, and immune-receptor docking interactions and scores. Docking and molecular dynamic simulations confirmed the stability of construct V2 interactions with the host immune receptors. Immune simulation analysis anticipated the strong immune profile of the prioritized construct. In silico restriction cloning ensured the feasible cloning ability of the V2 construct in the expression system of E. coli strain K12. It is anticipated that the designed vaccine construct may be safe, effective, and able to elicit strong immune responses against Y. pestis infections and may, therefore, merit investigation using in vitro and in vivo assays.

Deflamin Attenuated Lung Tissue Damage in an Ozone-Induced COPD Murine Model by Regulating MMP-9 Catalytic Activity

Chronic obstructive pulmonary disease (COPD) is comprised of histopathological alterations such as pulmonary emphysema and peribronchial fibrosis. Matrix metalloproteinase 9 (MMP-9) is one of the key enzymes involved in both types of tissue remodeling during the development of lung damage. In recent studies, it was demonstrated that deflamin, a protein component extracted from Lupinus albus, markedly inhibits the catalytic activity of MMP-9 in experimental models of colon adenocarcinoma and ulcerative colitis. Therefore, in the present study, we investigated for the first time the biological effect of deflamin in a murine COPD model induced by chronic exposure to ozone. Ozone exposure was carried out in C57BL/6 mice twice a week for six weeks for 3 h each time, and the treated group was orally administered deflamin (20 mg/kg body weight) after each ozone exposure. The histological results showed that deflamin attenuated pulmonary emphysema and peribronchial fibrosis, as evidenced by H&E and Masson's trichrome staining. Furthermore, deflamin administration significantly decreased MMP-9 activity, as assessed by fluorogenic substrate assay and gelatin zymography. Interestingly, bioinformatic analysis reveals a plausible interaction between deflamin and MMP-9. Collectively, our findings demonstrate the therapeutic potential of deflamin in a COPD murine model, and suggest that the attenuation of the development of lung tissue damage occurs by deflamin-regulated MMP-9 catalytic activity.

Enhancing tuberculosis vaccine development: a deconvolution neural network approach for multi-epitope prediction

Tuberculosis (TB) a disease caused by Mycobacterium tuberculosis (Mtb) poses a significant threat to human life, and current BCG vaccinations only provide sporadic protection, therefore there is a need for developing efficient vaccines. Numerous immunoinformatic methods have been utilized previously, here for the first time a deep learning framework based on Deconvolutional Neural Networks (DCNN) and Bidirectional Long Short-Term Memory (DCNN-BiLSTM) was used to predict Mtb Multiepitope vaccine (MtbMEV) subunits against six Mtb H37Rv proteins. The trained model was used to design MEV within a few minutes against TB better than other machine learning models with 99.5% accuracy. The MEV has good antigenicity, and physiochemical properties, and is thermostable, soluble, and hydrophilic. The vaccine's BLAST search ruled out the possibility of autoimmune reactions. The secondary structure analysis revealed 87% coil, 10% beta, and 2% alpha helix, while the tertiary structure was highly upgraded after refinement. Molecular docking with TLR3 and TLR4 receptors showed good binding, indicating high immune reactions. Immune response simulation confirmed the generation of innate and adaptive responses. In-silico cloning revealed the vaccine is highly expressed in E. coli. The results can be further experimentally verified using various analyses to establish a candidate vaccine for future clinical trials.

Immunoinformatics design of a structural proteins driven multi-epitope candidate vaccine against different SARS-CoV-2 variants based on fynomer

The ideal vaccines for combating diseases that may emerge in the future require more than simply inactivating a few pathogenic strains. This study aims to provide a peptide-based multi-epitope vaccine effective against various severe acute respiratory syndrome coronavirus 2 strains. To design the vaccine, a library of peptides from the spike, nucleocapsid, membrane, and envelope structural proteins of various strains was prepared. Then, the final vaccine structure was optimized using the fully protected epitopes and the fynomer scaffold. Using bioinformatics tools, the antigenicity, allergenicity, toxicity, physicochemical properties, population coverage, and secondary and three-dimensional structures of the vaccine candidate were evaluated. The bioinformatic analyses confirmed the high quality of the vaccine. According to further investigations, this structure is similar to native protein and there is a stable and strong interaction between vaccine and receptors. Based on molecular dynamics simulation, structural compactness and stability in binding were also observed. In addition, the immune simulation showed that the vaccine can stimulate immune responses similar to real conditions. Finally, codon optimization and in silico cloning confirmed efficient expression in Escherichia coli. In conclusion, the fynomer-based vaccine can be considered as a new style in designing and updating vaccines to protect against coronavirus disease.

Multi-epitopevaccines, from design to expression; an in silico approach

The development of vaccines against a wide range of infectious diseases and pathogens often relies on multi-epitope strategies that can effectively stimulate both humoral and cellular immunity. Immunoinformatics tools play a pivotal role in designing such vaccines, enhancing immune response potential, and minimizing the risk of failure. This review presents a comprehensive overview of practical tools for epitope prediction and the associated immune responses. These immunoinformatics tools facilitate the selection of epitopes based on parameters such as antigenicity, absence of toxic and allergenic sequences, secondary and tertiary structures, sequence conservation, and population coverage. The chosen epitopes can be tailored for B-cells or T-cells, both of which require further assessments covered in this study. We offer a range of suitable linkers that effectively separate cytotoxic T lymphocyte and helper T lymphocyte epitopes while preserving their functionality. Additionally, we identify various adjuvants for specific purposes. We delve into the evaluation of MHC-epitope interactions, MHC clusters, and the simulation of final constructs through molecular docking techniques. We provide diverse linkers and adjuvants optimized for epitope functions to bolster immune responses through epitope attachment. By leveraging these comprehensive tools, the development of multi-epitope vaccines holds the promise of robust immunity and a significant reduction in experimental costs.

Immunoinformatics approach for designing a multiepitope subunit vaccine against porcine epidemic diarrhea virus genotype IIA spike protein

Background

Porcine epidemic diarrhea (PED), caused by the porcine epidemic diarrhea virus (PEDV), is associated with high mortality and morbidity rates, especially in neonatal pigs. This has resulted in significant economic losses for the pig industry. PEDV genotype II-based vaccines were found to confer better immunity against both heterologous and homologous challenges; specifically, spike (S) proteins, which are known to play a significant role during infection, are ideal for vaccine development.

Aim

This study aims to design a multi-epitope subunit vaccine targeting the S protein of the PEDV GIIa strain using an immunoinformatics approach.

Methods

Various bioinformatics tools were used to predict HTL, CTL, and B-cell epitopes. The epitopes were connected using appropriate linkers and conjugated with the CTB adjuvant and M-ligand. The final multiepitope vaccine construct (fMEVc) was then docked to toll-like receptor 4 (TLR4). The stability of the fMEVc-TLR4 complex was then simulated using GROMACS. C-immsim was then used to predict the in vitro immune response of the fMEVc.

Results

Six epitopes were predicted to induce antibody production, ten epitopes were predicted to induce CTL responses, and four epitopes were predicted to induce HTL responses. The assembled epitopes conjugated with the CTB adjuvant and M-ligand, fMEVc, is antigenic, non-allergenic, stable, and soluble. The construct showed a favorable binding affinity for TLR4, and the protein complex was shown to be stable through molecular dynamics simulations. A robust immune response was induced after immunization, as demonstrated through immune stimulation.

Conclusion

In conclusion, the multi-epitope subunit vaccine construct for PEDV designed in this study exhibits promising antigenicity, stability, and immunogenicity, eliciting robust immune responses and suggesting its potential as a candidate for further vaccine development.

In silico design of a novel multi-epitope vaccine against HCV infection through immunoinformatics approaches

Infection with the hepatitis C virus (HCV) is one of the causes of liver cancer, which is the world's sixth most prevalent and third most lethal cancer. The current treatments do not prevent reinfection; because they are expensive, their usage is limited to developed nations. Therefore, a prophylactic vaccine is essential to control this virus. Hence, in this study, an immunoinformatics method was applied to design a multi-epitope vaccine against HCV. The best B- and T-cell epitopes from conserved regions of the E2 protein of seven HCV genotypes were joined with the appropriate linkers to design a multi-epitope vaccine. In addition, cholera enterotoxin subunit B (CtxB) was included as an adjuvant in the vaccine construct. This study is the first to present this epitopes-adjuvant combination. The vaccine had acceptable physicochemical characteristics. The vaccine's 3D structure was predicted and validated. The vaccine's binding stability with Toll-like receptor 2 (TLR2) and TLR4 was confirmed using molecular docking and molecular dynamics (MD) simulation. The immune simulation revealed the vaccine's efficacy by increasing the population of B and T cells in response to vaccination. In silico expression in Escherichia coli (E. coli) was also successful.

Design of multi-epitope chimeric vaccine against Monkeypox virus and SARS-CoV-2: A vaccinomics perspective

The current era we experience is full with pandemic infectious agents that no longer threatens the major local source but the whole globe. Almost the most emerging infectious agents are severe acute respiratory syndrome coronavirus-2 (SARS CoV-2), followed by monkeypox virus (MPXV). Since no approved antiviral drugs nor licensed active vaccines are yet available, we aimed to utilize immunoinformatics approach to design chimeric vaccine against the two mentioned viruses. This is the first study to deal with design divalent vaccine against SARS-CoV-2 and MPXV. ORF8, E and M proteins from Omicron SARS-CoV-2 and gp182 from MPXV were used as the protein precursor from which multi-epitopes (inducing B-cell, helper T cells, cytotoxic T cells and interferon-ɣ) chimeric vaccine was contrived. The structure of the vaccine construct was predicted, validated, and docked to toll-like receptor-2 (TLR-2). Moreover, its sequence was also used to examine the immune simulation profile and was then inserted into the pET-28a plasmid for in silico cloning. The vaccine construct was probable antigen (0.543) and safe (non-allergen) with strong binding energy to TLR-2 (-1169.8 kcal/mol) and found to have significant immune simulation profile. In conclusion, the designed chimeric vaccine was potent and safe against SARS-CoV-2 and MPXV, which deserves further consideration.

A Multi-epitope Subunit Vaccine Identification and Development Against Scrub Typhus (Orientia tsutsugamushi) Using Immunoinformatics Approaches

Background The pathogen Orientia tsutsugamushi, which causes scrub typhus, is rapidly spreading throughout the tropics. As a measure to improve public health, the development of a vaccine for human use is essential. Scrub typhus is listed as one of the underdiagnosed and underreported febrile infections. This vector-borne zoonotic infection appears as eschar on the patient's skin. Methods Immunoinformatics was employed to predict the multi-epitope subunit vaccine that will activate both B and T cells. The final vaccine includes lipoprotein LprA as an adjuvant at the N-terminus along with B-cell, helper T lymphocyte (HTL), and cytotoxic T lymphocyte (CTL)-binding epitopes to boost immunogenicity. Assessing the vaccine's physiochemistry demonstrates that it is both antigenic and non-allergic. The vaccine structure was developed, enhanced, confirmed, and disulfide-engineered to provide the best possible model. Using molecular docking, the interaction of the produced vaccine with toll-like receptor 2 (TLR2) was analyzed, and the vaccine-receptor complex was stabilized by molecular dynamics (MD) simulation. According to in silico cloning, Escherichia coli can efficiently produce the recommended vaccine. Additionally, the efficacy of the in silico-developed vaccine must be evaluated in an in vitro and in vivo experiment. Results The developed vaccine successfully stimulates cellular and humoral immune responses. The vaccine, which has three B-cell epitopes, three HCL epitopes, and nine CTL epitopes, can bind firmly to immunological receptors. Dynamic investigations of the vaccine-receptor complex show a strong interaction and stable conformation. Conclusion In this study, the vaccine candidate demonstrated strong antigenicity, stability, and solubility while also being non-allergenic to host cells. The vaccine candidate's stability with the TLR2 immune receptor is established by binding studies, and in silico cloning verifies efficient and stable expression in the bacterial system.

Design and validation of a novel multi-epitopes vaccine against hantavirus

Hantavirus is a member of the order Bunyavirales and an emerging global pathogen. Hantavirus infections have affected millions of people globally based on available epidemiological data and research studies. Hemorrhagic fever with renal syndrome (HFRS) and hantavirus pulmonary syndrome (HPS) are the two main human diseases associated with hantavirus infections. Hence, efforts are required to develop a potent vaccine against the pathogen. The only vaccine that is in use for hantavirus is an inactivated virus vaccine, "Hantavax", but it failed to produce neutralizing antibodies. Vaccine development is of much importance in dealing with the surge of hantavirus globally. In this study, hantavirus five proteins (N protein, G1 and G2, L protein, and non-structural proteins) were used in NetCTL 1.2 program to predict T-cell epitopes. To predict major histocompatibility complex (MHC) binding alleles, an immune epitope database (IEDB) was used. All predicted epitopes were then investigated for different immunoinformatics analyses such as antigenicity and toxicity analyses. The good water-soluble, non-toxic, probable antigenic, and DRB*0101 binder was selected. A multi-epitopes-based vaccine designing was then done where linkers were used to connect the shortlisted epitopes. In addition, an adjuvant molecule was supplementary to the multi-epitopes peptide to improve the vaccine's immunogenic potential. The final vaccine construct's three-dimensional structure was modeled by ab initio method. The vaccine molecule was then evaluated for its binding potential with TLR-3 immune receptor, which is key for its recognition and processing by the host immune system. Docking studies were performed using HADDOCK software. The best-docked complex was selected and visualized for intermolecular binding and interactions using UCSF Chimera 1.16 software. The findings revealed that the designed vaccine might be a potential vaccine against hantavirus and can be used in experimental animal model testings.Communicated by Ramaswamy H. Sarma.

Design and computational evaluation of a novel multi-epitope hybrid vaccine against monkeypox virus: Potential targets and immunogenicity assessment for pandemic preparedness

Monkeypox is a type of DNA-enveloped virus that belongs to the orthopoxvirus family, closely related to the smallpox virus. It can cause an infectious disease in humans known as monkeypox disease. Although there are multiple drugs and vaccines designed to combat orthopoxvirus infections, with a primary focus on smallpox, the recent spread of the monkeypox virus to over 50 countries have ignited a mounting global concern. This unchecked viral proliferation has raised apprehensions about the potential for a pandemic corresponding to the catastrophic impact of COVID-19. This investigation explored the structural proteins of monkeypox virus as potential candidates for designing a novel hybrid multi-epitope vaccine. The epitopes obtained from the selected proteins were screened to ensure their non-allergenicity, non-toxicity, and antigenicity to trigger T and B-cell responses. The interaction of the vaccine with toll-like receptor-3 (TLR-3) and major histocompatibility complexes (MHCs) was assessed using Cluspro 2.0. To establish the reliability of the docked complexes, a comprehensive evaluation was conducted using Immune and MD Simulations and Normal Mode Analysis. However, to validate the computational results of this study, additional in-vitro and in-vivo research is essential.

Development of membrane protein-based vaccine against lumpy skin disease virus (LSDV) using immunoinformatic tools

INTRODUCTION

Lumpy skin disease, an economically significant bovine illness, is now found in previously unheard-of geographic regions. Vaccination is one of the most important ways to stop its further spread.

AIM

Therefore, in this study, we applied advanced immunoinformatics approaches to design and develop an effective lumpy skin disease virus (LSDV) vaccine.

METHODS

The membrane glycoprotein was selected for prediction of the different B- and T-cell epitopes by using the immune epitope database. The selected B- and T-cell epitopes were combined with the appropriate linkers and adjuvant resulted in a vaccine chimera construct. Bioinformatics tools were used to predict, refine and validate the 2D, 3D structures and for molecular docking with toll-like receptor 4 using different servers. The constructed vaccine candidate was further processed on the basis of antigenicity, allergenicity, solubility, different physiochemical properties and molecular docking scores.

RESULTS

The in silico immune simulation induced significant response for immune cells. In silico cloning and codon optimization were performed to express the vaccine candidate in Escherichia coli. This study highlights a good signal for the design of a peptide-based LSDV vaccine.

CONCLUSION

Thus, the present findings may indicate that the engineered multi-epitope vaccine is structurally stable and can induce a strong immune response, which should help in developing an effective vaccine towards controlling LSDV infection.

Mycosporine-Like Amino Acids as a Potential Inhibitor of Tyrosinase-Related Protein 1: Computational Screening, Pharmacokinetics, and Molecular Dynamics Simulation

Melanin is the major pigment responsible for the coloring of mammalian skin, hair, and eyes to defend against ultraviolet radiation. However, excessive melanin production has resulted in numerous types of hyperpigmentation disorders. Tyrosinase-related protein 1 (TYRP1) is a transmembrane glycoprotein enzyme found in many organisms, including humans, that plays an important role in melanogenesis. Thus, controlling the enzyme activity of TYRP1 with tyrosinase inhibitors is a vital step in the treatment of hyperpigmentation problems in humans. In the present investigation, virtual screening, pharmacokinetics, drug docking, and molecular dynamics (MD) simulation were used to find the most potent drug as an inhibitor of TYRP1 to effectively treat hyperpigmentation disorder. The 3D structure of TYRP1 was retrieved from the Protein Data Bank (PDB) database (PDB ID: 5M8M) and validated by the Ramachandran plot. Pharmacokinetics and drug-likeness showed that mycosporine 2 glycine (M2G) and shinorine (SHI) were the best compounds over other ligands in the same (P-1) structural pose. However, MD simulations of the M2G showed the highest CDOCKER interaction energy (-45.182 kcal/mol) and binding affinity (-65.0529 kcal/mol) as compared to SHI and reference drugs. The molecular binding modes RMSD and RMSF plots have exhibited more relevance to the M2G ligand in comparison to other drug ligands. The bioactivity and ligand efficiency profiles revealed that M2G is the most effective compound as a TYRP1 inhibitor. Thus, M2G could be used as a most effective drug for developing valuable sunscreen products to cure hyperpigmentation-related diseases.

Design of a multi-epitope-based vaccine candidate against Bovine Genital Campylobacteriosis using a reverse vaccinology approach

BACKGROUND

Bovine Genital Campylobacteriosis (BGC), a worldwide distributed venereal disease caused by Campylobacter fetus subsp. venerealis (Cfv), has a relevant negative economic impact in cattle herds. The control of BGC is hampered by the inexistence of globally available effective vaccines. The present in silico study aimed to develop a multi-epitope vaccine candidate against Cfv through reverse vaccinology.

RESULTS

The analysis of Cfv strain NCTC 10354 proteome allowed the identification of 9 proteins suitable for vaccine development. From these, an outer membrane protein, OmpA, and a flagellar protein, FliK, were selected for prediction of B-cell and T-cell epitopes. The top-ranked epitopes conservancy was assessed in 31 Cfv strains. The selected epitopes were integrated to form a multi-epitope fragment of 241 amino acids, which included 2 epitopes from OmpA and 13 epitopes from FliK linked by GPGPG linkers and connected to the cholera toxin subunit B by an EAAAK linker. The vaccine candidate was predicted to be antigenic, non-toxic, non-allergenic, and soluble upon overexpression. The protein structure was predicted and optimized, and the sequence was successfully cloned in silico into a plasmid vector. Additionally, immunological simulations demonstrated the vaccine candidate's ability to stimulate an immune response.

CONCLUSIONS

This study developed a novel vaccine candidate suitable for further in vitro and in vivo experimental validation, which may become a useful tool for the control of BGC.

Designing of a multi-epitopes based vaccine against Haemophilius parainfluenzae and its validation through integrated computational approaches

Haemophilus parainfluenzae is a Gram-negative opportunist pathogen within the mucus of the nose and mouth without significant symptoms and has an ability to cause various infections ranging from ear, eye, and sinus to pneumonia. A concerning development is the increasing resistance of H. parainfluenzae to beta-lactam antibiotics, with the potential to cause dental infections or abscesses. The principal objective of this investigation is to utilize bioinformatics and immuno-informatic methodologies in the development of a candidate multi-epitope Vaccine. The investigation focuses on identifying potential epitopes for both B cells (B lymphocytes) and T cells (helper T lymphocytes and cytotoxic T lymphocytes) based on high non-toxic and non-allergenic characteristics. The selection process involves identifying human leukocyte antigen alleles demonstrating strong associations with recognized antigenic and overlapping epitopes. Notably, the chosen alleles aim to provide coverage for 90% of the global population. Multi-epitope constructs were designed by using suitable linker sequences. To enhance the immunological potential, an adjuvant sequence was incorporated using the EAAAK linker. The final vaccine construct, comprising 344 amino acids, was achieved after the addition of adjuvants and linkers. This multi-epitope Vaccine demonstrates notable antigenicity and possesses favorable physiochemical characteristics. The three-dimensional conformation underwent modeling and refinement, validated through in-silico methods. Additionally, a protein-protein molecular docking analysis was conducted to predict effective binding poses between the multi-epitope Vaccine and the Toll-like receptor 4 protein. The Molecular Dynamics (MD) investigation of the docked TLR4-vaccine complex demonstrated consistent stability over the simulation period, primarily attributed to electrostatic energy. The docked complex displayed minimal deformation and enhanced rigidity in the motion of residues during the dynamic simulation. Furthermore, codon translational optimization and computational cloning was performed to ensure the reliability and proper expression of the multi-Epitope Vaccine. It is crucial to emphasize that despite these computational validations, experimental research in the laboratory is imperative to demonstrate the immunogenicity and protective efficacy of the developed vaccine. This would involve practical assessments to ascertain the real-world effectiveness of the multi-epitope Vaccine.

Frequency of Fusion Inhibitor Resistance Mutations Among Therapy-Naïve HIV Patients

Glycoprotein 41 (gp41) of the human immunodeficiency virus type 1 (HIV-1) protein plays a critical role in membrane fusion. Gp41 binds to proteins in the plasma membrane of CD4+ T cells, particularly the T-cell antigen receptor (TCR). These findings indicate that gp41 is involved in the assembly of HIV-1 at the plasma membrane of T cells and affects the stimulation of the TCR. To control HIV-1, new inhibitors were introduced to target the gp41 protein. However, mutations in this region might reduce their efficacy. The Gp41 region was amplified from the sera of 30 patients using nested polymerase chain reaction. The sequences were analyzed by bioinformatics tools to identify mutations and gp41 structural features. Subtyping and the interaction between fusion inhibitors and gp41 proteins were also examined. As the first report from Iran, docking analysis between fusion inhibitors and Iranian gp41 proteins showed that mutations in gp41 could not reduce the efficacy of the fusion inhibitors. Most of the patients were infected with CRF35-AD. Several post-modification positions, including glycosylation and phosphorylation sites, were identified in the gp41 protein. Our findings revealed no known multinational drug resistance to gp41 inhibitors; thus, fusion inhibitors can effectively inhibit HIV in Iranian patients. In addition, the present study introduced a new gp41 region (36-44 aa), which considerably influences the interactions between gp41 inhibitors and the gp41 protein. This region may play a pivotal role in suppressing gp41 inhibitors in CFR35-AD. Furthermore, gp41 can be considered a good target for subtyping analysis via the phylogenetic method.

Computational approach for identifying immunogenic epitopes and optimizing peptide vaccine through in-silico cloning against Mycoplasma genitalium

Mycoplasma genitalium is a pathogenic microorganism linked to a variety of severe health conditions including ovarian cancer, prostate cancer, HIV transmission, and sexually transmitted diseases. A more effective approach to address the challenges posed by this pathogen, given its high antibiotic resistance rates, could be the development of a peptide vaccine. In this study, we used experimentally validated 13 membrane proteins and their immunogenicity to identify suitable vaccine candidates. Thus, based on immunogenic properties and high conservation among other Mycoplasma genitalium sub-strains, the P110 surface protein is considered for further investigation. Later on, we identified T-cell epitopes and B-cell epitopes from the P110 protein to construct a multiepitope-based vaccine. As a result, the 'NIAPISFSFTPFTAA' T-cell epitope and 'KVKYESSGSNNISFDS' B-cell epitope have shown 99.53% and 87.50% population coverage along with 100% conservancy among the subspecies, and both epitopes were found to be non-allergenic. Furthermore, focusing on molecular docking analysis showed the lowest binding energy for MHC-I (-137.5 kcal/mol) and MHC-II (-183.3 kcal/mol), leading to a satisfactory binding strength between the T-cell epitopes and the MHC molecules. However, the constructed multiepitope vaccine (MEV) consisting of 54 amino acids demonstrates favorable characteristics for a vaccine candidate, including a theoretical pI of 4.25 with a scaled solubility of 0.812 and high antigenicity probabilities. Additionally, structural analyses reveal that the MEV displays substantial alpha helices and extended strands, vital for its immunogenicity. Molecular docking with the human Toll-like receptors TLR1/2 heterodimer shows strong binding affinity, reinforcing its potential to elicit an immune response. Our immune simulation analysis demonstrates immune memory development and robust immunity, while codon adaptation suggests optimal expression in E. coli using the pET-28a(+) vector. These findings collectively highlight the MEV's potential as a valuable vaccine candidate against M. genitalium.

Peptide based vaccine designing against endemic causing mammarenavirus using reverse vaccinology approach

The rodent-borne Arenavirus in humans has led to the emergence of regional endemic situations and has deeply emerged into pandemic-causing viruses. Arenavirus have a bisegmented ambisense RNA that produces four proteins: glycoprotein, nucleocapsid, RdRp and Z protein. The peptide-based vaccine targets the glycoprotein of the virus encountered by the immune system. Screening of B-Cell and T-Cell epitopes was done based on their immunological properties like antigenicity, allergenicity, toxicity and anti-inflammatory properties were performed. Selected epitopes were then clustered and epitopes were stitched using linker sequences. The immunological and physico-chemical properties of the vaccine construct was checked and modelled structure was validated by a 2-step MD simulation. The thermostability of the vaccine was checked followed by the immune simulation to test the immunogenicity of the vaccine upon introduction into the body over the course of the next 100 days and codon optimization was performed. Finally a 443 amino acid long peptide vaccine was designed which could provide protection against several members of the mammarenavirus family in a variety of population worldwide as denoted by the epitope conservancy and population coverage analysis. This study of designing a peptide vaccine targeting the glycoprotein of mammarenavirues may help develop novel therapeutics in near future.

Designing a Novel Multiepitope Vaccine from the Human Papilloma Virus E1 and E2 Proteins for Indonesia with Immunoinformatics and Molecular Dynamics Approaches

One of the deadliest malignant cancer in women globally is cervical cancer. Specifically, cervical cancer is the second most common type of cancer in Indonesia. The main infectious agent of cervical cancer is the human papilloma virus (HPV). Although licensed prophylactic vaccines are available, cervical cancer cases are on the rise. Therapy using multiepitope-based vaccines is a very promising therapy for cervical cancer. This study aimed to develop a multiepitope vaccine based on the E1 and E2 proteins of HPV 16, 18, 45, and 52 using in silico. In this study, we develop a novel multiepitope vaccine candidate using an immunoinformatic approach. We predicted the epitopes of the cytotoxic T lymphocyte (CTL) and helper T lymphocyte (HTL) and evaluated their immunogenic properties. Population coverage analysis of qualified epitopes was conducted to determine the successful use of the vaccine worldwide. The epitopes were constructed into a multiepitope vaccine by using AAY linkers between the CTL epitopes and GPGPG linkers between the HTL epitopes. The tertiary structure of the multiepitope vaccine was modeled with AlphaFold and was evaluated by Prosa-web. The results of vaccine construction were analyzed for B-cell epitope prediction, molecular docking with Toll like receptor-4 (TLR4), and molecular dynamics simulation. The results of epitope prediction obtained 4 CTL epitopes and 7 HTL epitopes that are eligible for construction of multiepitope vaccines. Prediction of the physicochemical properties of multiepitope vaccines obtained good results for recombinant protein production. The interaction showed that the interaction of the multiepitope vaccine-TLR4 complex is stable based on the binding free energy value -106.5 kcal/mol. The results of the immune response simulation show that multiepitope vaccine candidates could activate the adaptive and humoral immune systems and generate long-term B-cell memory. According to these results, the development of a multiepitope vaccine with a reverse vaccinology approach is a breakthrough to develop potential cervical cancer therapeutic vaccines.