Core-genome-mediated promising alternative drug and multi-epitope vaccine targets prioritization against infectious Clostridium difficile.

Prevention of Clostridium difficile infection is challenging worldwide owing to its high morbidity and mortality rates. C. difficile is currently being classified as an urgent threat by the CDC. Devising a new therapeutic strategy become indispensable against C. difficile infection due to its high rates of reinfection and increasing antimicrobial resistance. The current study is based on core proteome data of C. difficile to identify promising vaccine and drug candidates. Immunoinformatics and vaccinomics approaches were employed to construct multi-epitope-based chimeric vaccine constructs from top-ranked T- and B-cell epitopes. The efficacy of the designed vaccine was assessed by immunological analysis, immune receptor binding potential and immune simulation analyses. Additionally, subtractive proteomics and druggability analyses prioritized several promising and alternative drug targets against C. difficile. These include FMN-dependent nitroreductase which was prioritized for pharmacophore-based virtual screening of druggable molecule databases to predict potent inhibitors. A MolPort-001-785-965 druggable molecule was found to exhibit significant binding affinity with the conserved residues of FMN-dependent nitroreductase. The experimental validation of the therapeutic targets prioritized in the current study may worthy to identify new strategies to combat the drug-resistant C. difficile infection.

Vaccinomics-aided next-generation novel multi-epitope-based vaccine engineering against multidrug resistant Shigella Sonnei: Immunoinformatics and chemoinformatics approaches.

Shigella sonnei is a gram-negative bacterium and is the primary cause of shigellosis in advanced countries. An exceptional rise in the prevalence of the disease has been reported in Asia, the Middle East, and Latin America. To date, no preventive vaccine is available against S. sonnei infections. This pathogen has shown resistances towards both first- and second-line antibiotics. Therefore, an effective broad spectrum vaccine development against shigellosis is indispensable. In the present study, vaccinomics-aided immunoinformatics strategies were pursued to identify potential vaccine candidates from the S. sonnei whole proteome data. Pathogen essential proteins that are non-homologous to human and human gut microbiome proteome set, are feasible candidates for this purpose. Three antigenic outer membrane proteins were prioritized to predict lead epitopes based on reverse vaccinology approach. Multi-epitope-based chimeric vaccines was designed using lead B- and T-cell epitopes combined with suitable linker and adjuvant peptide sequences to enhance immune responses against the designed vaccine. The SS-MEVC construct was prioritized based on multiple physicochemical, immunological properties, and immune-receptors docking scores. Immune simulation analysis predicted strong immunogenic response capability of the designed vaccine construct. The Molecular dynamic simulations analysis ensured stable molecular interactions of lead vaccine construct with the host receptors. In silico restriction and cloning analysis predicted feasible cloning capability of the SS-MEVC construct within the E. coli expression system. The proposed vaccine construct is predicted to be more safe, effective and capable of inducing robust immune responses against S. sonnei infections and may be worthy of examination via in vitro/in vivo assays.

Vaccinomics-based next-generation multi-epitope chimeric vaccine models prediction against Leishmania tropica - a hierarchical subtractive proteomics and immunoinformatics approach.

Leishmania tropica is a vector-borne parasitic protozoa that is the leading cause of leishmaniasis throughout the global tropics and subtropics. L. tropica is a multidrug-resistant parasite with a diverse set of serological, biochemical, and genomic features. There are currently no particular vaccines available to combat leishmaniasis. The present study prioritized potential vaccine candidate proteins of L. tropica using subtractive proteomics and vaccinomics approaches. These vaccine candidate proteins were downstream analyzed to predict B- and T-cell epitopes based on high antigenicity, non-allergenic, and non-toxic characteristics. The top-ranked overlapping MHC-I, MHC-II, and linear B-cell epitopes were prioritized for model vaccine designing. The lead epitopes were linked together by suitable linker sequences to design multi-epitope constructs. Immunogenic adjuvant sequences were incorporated at the N-terminus of the model vaccine constructs to enhance their immunological potential. Among different combinations of constructs, four vaccine designs were selected based on their physicochemical and immunological features. The tertiary structure models of the designed vaccine constructs were predicted and verified. The molecular docking and molecular dynamic (MD) simulation analyses indicated that the vaccine design V1 demonstrated robust and stable molecular interactions with toll-like receptor 4 (TLR4). The top-ranked vaccine construct model-IV demonstrated significant expressive capability in the E. coli expression system during in-silico restriction cloning analysis. The results of the present study are intriguing; nevertheless, experimental bioassays are required to validate the efficacy of the predicted model chimeric vaccine.

Immunoinformatics-based potential multi-peptide vaccine designing against Jamestown Canyon Virus (JCV) capable of eliciting cellular and humoral immune responses.

Jamestown Canyon virus (JCV) is a deadly viral infection transmitted by various mosquito species. This mosquito-borne virus belongs to Bunyaviridae family, posing a high public health threat in the in tropical regions of the United States causing encephalitis in humans. Common symptoms of JCV include fever, headache, stiff neck, photophobia, nausea, vomiting, and seizures. Despite the availability of resources, there is currently no vaccine or drug available to combat JCV. The purpose of this study was to develop an epitope-based vaccine using immunoinformatics approaches. The vaccine aimed to be secure, efficient, bio-compatible, and capable of stimulating both innate and adaptive immune responses. In this study, the protein sequence of JCV was obtained from the NCBI database. Various bioinformatics methods, including toxicity evaluation, antigenicity testing, conservancy analysis, and allergenicity assessment were utilized to identify the most promising epitopes. Suitable linkers and adjuvant sequences were used in the design of vaccine construct. 50s ribosomal protein sequence was used as an adjuvant at the N-terminus of the construct. A total of 5 CTL, 5 HTL, and 5 linear B cell epitopes were selected based on non-allergenicity, immunological potential, and antigenicity scores to design a highly immunogenic multi-peptide vaccine construct. Strong interactions between the proposed vaccine and human immune receptors, i.e., TLR-2 and TLR-4, were revealed in a docking study using ClusPro software, suggesting their possible relevance in the immunological response to the vaccine. Immunological and physicochemical properties assessment ensured that the proposed vaccine demonstrated high immunogenicity, solubility and thermostability. Molecular dynamics simulations confirmed the strong binding affinities, as well as dynamic and structural stability of the proposed vaccine. Immune simulation suggest that the vaccine has the potential to effectively stimulate cellular and humoral immune responses to combat JCV infection. Experimental and clinical assays are required to validate the results of this study.

Immunoinformatics-based multi-epitope vaccine design for the re-emerging monkeypox virus.

BACKGROUND: On May 7, 2022, WHO reported a new monkeypox case. By May 2023 over 80,000 cases had been reported worldwide outside previously endemic nations. (This primarily affected the men who have sex with men (MSM) community in rich nations). The present research aims to develop a multi-epitope vaccine for the monkeypox virus (MPXV) using structural and cell surface proteins. METHODS: The first part of the research involved retrieving protein sequences. The Immune Epitope Database (IEDB) was then used to analyze the B and T lymphocyte epitopes. After analyzing the sensitizing properties, toxicity, antigenicity, and molecular binding, appropriate linkers were utilizedto connect selected epitopes to adjuvants, and the structure of the vaccine was formulated. Algorithms from the field of immunoinformatics predicted the secondary and tertiary structures of vaccines. The physical, chemical, and structural properties were refined and validated to achieve maximum stability. Molecular docking and molecular dynamic simulations were subsequently employed to assess the vaccine's efficacy. Afterward, the ability of the vaccine to interact with toll-like receptors 3 and 4 (TLR3 and TLR4) was evaluated. Finally, the optimized sequence was then introduced into the Escherichia coli (E. coli) PET30A + vector. RESULTS: An immunoinformatics evaluation suggested that such a vaccine might be safe revealed that this vaccine is safe, hydrophilic, temperature- and condition-stable, and can stimulate innate immunity by binding to TLR3 and TLR4. CONCLUSION: Our findings suggest that the first step in MPXV pathogenesis is structural and cell surface epitopes. In this study, the most effective and promising epitopes were selected and designed throughprecision servers. Furthermore,through the utilization of multi-epitope structures and a combination of two established adjuvants, this research has the potential to be a landmarkin developing an antiviralvaccine against MPXV. However, additional in vitro and in vivo tests are required to confirm these results.

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.

A comprehensive protein interaction map and druggability investigation prioritized dengue virus NS1 protein as promising therapeutic candidate.

Dengue Virus (DENV) is a serious threat to human life worldwide and is one of the most dangerous vector-borne diseases, causing thousands of deaths annually. We constructed a comprehensive PPI map of DENV with its host Homo sapiens and performed various bioinformatics analyses. We found 1195 interactions between 858 human and 10 DENV proteins. Pathway enrichment analysis was performed on the two sets of gene products, and the top 5 human proteins with the maximum number of interactions with dengue viral proteins revealed noticeable results. The non-structural protein NS1 in DENV had the maximum number of interactions with the host protein, followed by NS5 and NS3. Among the human proteins, HBA1 and UBE2I were associated with 7 viral proteins, and 3 human proteins (CSNK2A1, RRP12, and HSP90AB1) were found to interact with 6 viral proteins. Pharmacophore-based virtual screening of millions of compounds in the public databases was performed to identify potential DENV-NS1 inhibitors. The lead compounds were selected based on RMSD values, docking scores, and strong binding affinities. The top ten hit compounds were subjected to ADME profiling which identified compounds C2 (MolPort-044-180-163) and C6 (MolPort-001-742-737) as lead inhibitors against DENV-NS1. Molecular dynamics trajectory analysis and intermolecular interactions between NS1 and the ligands displayed the molecular stability of the complexes in the cellular environment. The in-silico approaches used in this study could pave the way for the development of potential specie-specific drugs and help in eliminating deadly viral infections. Therefore, experimental and clinical assays are required to validate the results of this study.

Annotation of Potential Vaccine Targets and Designing of mRNA-Based Multi-Epitope Vaccine against Lumpy Skin Disease Virus via Reverse Vaccinology and Agent-Based Modeling.

Lumpy skin disease is a fatal emerging disease of cattle, which has started to gain extensive attention due to its rapid incursions across the globe. The disease epidemic causes economic loss and cattle morbidity. Currently, there are no specific treatments and safe vaccines against the lumpy skin disease virus (LSDV) to halt the spread of the disease. The current study uses genome-scan vaccinomics analyses to prioritize promiscuous vaccine candidate proteins of the LSDV. These proteins were subjected to top-ranked B- and T-cell epitope prediction based on their antigenicity, allergenicity, and toxicity values. The shortlisted epitopes were connected using appropriate linkers and adjuvant sequences to design multi-epitope vaccine constructs. Three vaccine constructs were prioritized based on their immunological and physicochemical properties. The model constructs were back-translated to nucleotide sequences and codons were optimized. The Kozak sequence with a start codon along with MITD, tPA, Goblin 5', 3' UTRs, and a poly(A) tail sequences were added to design a stable and highly immunogenic mRNA vaccine. Molecular docking followed by MD simulation analysis predicted significant binding affinity and stability of LSDV-V2 construct within bovine immune receptors and predicted it to be the top-ranked candidate to stimulate the humeral and cellular immunogenic responses. Furthermore, in silico restriction cloning predicted feasible gene expression of the LSDV-V2 construct in a bacterial expression vector. It could prove worthwhile to validate the predicted vaccine models experimentally and clinically against LSDV.

Comparative Proteomics and Genome-Wide Druggability Analyses Prioritized Promising Therapeutic Targets against Drug-Resistant Leishmania tropica.

Leishmania tropica is a tropical parasite causing cutaneous leishmaniasis (CL) in humans. Leishmaniasis is a serious public health threat, affecting an estimated 350 million people in 98 countries. The global rise in antileishmanial drug resistance has triggered the need to explore novel therapeutic strategies against this parasite. In the present study, we utilized the recently available multidrug resistant L. tropica strain proteome data repository to identify alternative therapeutic drug targets based on comparative subtractive proteomic and druggability analyses. Additionally, small drug-like compounds were scanned against novel targets based on virtual screening and ADME profiling. The analysis unveiled 496 essential cellular proteins of L. tropica that were nonhomologous to the human proteome set. The druggability analyses prioritized nine parasite-specific druggable proteins essential for the parasite's basic cellular survival, growth, and virulence. These prioritized proteins were identified to have appropriate binding pockets to anchor small drug-like compounds. Among these, UDPase and PCNA were prioritized as the top-ranked druggable proteins. The pharmacophore-based virtual screening and ADME profiling predicted MolPort-000-730-162 and MolPort-020-232-354 as the top hit drug-like compounds from the Pharmit resource to inhibit L. tropica UDPase and PCNA, respectively. The alternative drug targets and drug-like molecules predicted in the current study lay the groundwork for developing novel antileishmanial therapies.

Molecular Mimicry Analyses Unveiled the Human Herpes Simplex and Poxvirus Epitopes as Possible Candidates to Incite Autoimmunity.

Clinical epidemiological studies have reported that viral infections cause autoimmune pathology in humans. Host-pathogen protein sequences and structure-based molecular mimicry cause autoreactive T cells to cross-activate. The aim of the current study was to implement immunoinformatics approaches to infer sequence- and structure-based molecular mimicry between viral and human proteomic datasets. The protein sequences of all the so far known human-infecting viruses were obtained from the VIPR database, and complete human proteome data were retrieved from the NCBI repository. Based on a predefined, stringent threshold of comparative sequence analyses, 24 viral proteins were identified with significant sequence similarity to human proteins. PathDIP identified the enrichment of these homologous proteins in nine metabolic pathways with a p-value < 0.0001. Several viral and human mimic epitopes from these homologous proteins were predicted as strong binders of human HLA alleles, with IC50 < 50 nM. Downstream molecular docking analyses identified that lead virus-human homologous epitopes feasibly interact with HLA and TLR4 types of immune receptors. The vast majority of these top-hit homolog epitopic peptides belong to the herpes simplex and poxvirus families. These lead epitope biological sequences and 3D structural-based molecular mimicry may be promising for interpreting herpes simplex virus and poxvirus infection-mediated autoimmune disorders in humans.

Multi-epitope chimeric vaccine design against emerging Monkeypox virus via reverse vaccinology techniques- a bioinformatics and immunoinformatics approach.

The emerging monkeypox virus (MPXV) is a zoonotic orthopoxvirus that causes infections in humans similar to smallpox. Since May 2022, cases of monkeypox (MPX) have been increasingly reported by the World Health Organization (WHO) worldwide. Currently, there are no clinically validated treatments for MPX infections. In this study, an immunoinformatics approach was used to identify potential vaccine targets against MPXV. A total of 190 MPXV-2022 proteins were retrieved from the ViPR database and subjected to various analyses including antigenicity, allergenicity, toxicity, solubility, IFN-γ, and virulence. Three outer membrane and extracellular proteins were selected based on their respective parameters to predict B-cell and T-cell epitopes. The epitopes are conserved among different strains of MPXV and the population coverage is 100% worldwide, which will provide broader protection against various strains of the virus globally. Nine overlapping MHC-I, MHC-II, and B-cell epitopes were selected to design multi-epitope vaccine constructs linked with suitable linkers in combination with different adjuvants to enhance the immune responses of the vaccine constructs. Molecular modeling and structural validation ensured high-quality 3D structures of vaccine constructs. Based on various immunological and physiochemical properties and docking scores, MPXV-V2 was selected for further investigation. In silico cloning revealed a high level of gene expression for the MPXV-V2 vaccine within the bacterial expression system. Immune and MD simulations confirmed the molecular stability of the MPXV-V2 construct, with high immune responses within the host cell. These results may aid in the development of experimental vaccines against MPXV with increased potency and improved safety.

Protein-protein interactions: Methods, databases, and applications in virus-host study.

Almost all the cellular processes in a living system are controlled by proteins: They regulate gene expression, catalyze chemical reactions, transport small molecules across membranes, and transmit signal across membranes. Even, a viral infection is often initiated through virus-host protein interactions. Protein-protein interactions (PPIs) are the physical contacts between two or more proteins and they represent complex biological functions. Nowadays, PPIs have been used to construct PPI networks to study complex pathways for revealing the functions of unknown proteins. Scientists have used PPIs to find the molecular basis of certain diseases and also some potential drug targets. In this review, we will discuss how PPI networks are essential to understand the molecular basis of virus-host relationships and several databases which are dedicated to virus-host interaction studies. Here, we present a short but comprehensive review on PPIs, including the experimental and computational methods of finding PPIs, the databases dedicated to virus-host PPIs, and the associated various applications in protein interaction networks of some lethal viruses with their hosts.

A systems biology-driven approach to construct a comprehensive protein interaction network of influenza A virus with its host.

BACKGROUND: Influenza A virus (IAV) infection is a serious public health problem not only in South East Asia but also in European and African countries. Scientists are using network biology to dig deep into the essential host factors responsible for regulation of virus infections. Researchers can explore the virus invasion into the host cells by studying the virus-host relationship based on their protein-protein interaction network. METHODS: In this study, we present a comprehensive IAV-host protein-protein interaction network that is obtained based on the literature-curated protein interaction datasets and some important interaction databases. The network is constructed in Cytoscape and analyzed with its plugins including CytoHubba, CytoCluster, MCODE, ClusterViz and ClusterOne. In addition, Gene Ontology and KEGG enrichment analyses are performed on the highly IAV-associated human proteins. We also compare the current results with those from our previous study on Hepatitis C Virus (HCV)-host protein-protein interaction network in order to find out valuable information. RESULTS: We found out 1027 interactions among 829 proteins of which 14 are viral proteins and 815 belong to human proteins. The viral protein NS1 has the highest number of associations with human proteins followed by NP, PB2 and so on. Among human proteins, LNX2, MEOX2, TFCP2, PRKRA and DVL2 have the most interactions with viral proteins. Based on KEGG pathway enrichment analysis of the highly IAV-associated human proteins, we found out that they are enriched in the KEGG pathway of basal cell carcinoma. Similarly, the result of KEGG analysis of the common host factors involved in IAV and HCV infections shows that these factors are enriched in the infection pathways of Hepatitis B Virus (HBV), Viral Carcinoma, measles and certain other viruses. CONCLUSION: It is concluded that the list of proteins we identified might be used as potential drug targets for the drug design against the infectious diseases caused by Influenza A Virus and other viruses.

Inferring Virus-Host relationship between HPV and its host Homo sapiens using protein interaction network.

Human papilloma virus (HPV) is a serious threat to human life globally with over 100 genotypes including cancer causing high risk HPVs. Study on protein interaction maps of pathogens with their host is a recent trend in 'omics' era and has been practiced by researchers to find novel drug targets. In current study, we construct an integrated protein interaction map of HPV with its host human in Cytoscape and analyze it further by using various bioinformatics tools. We found out 2988 interactions between 12 HPV and 2061 human proteins among which we identified MYLK, CDK7, CDK1, CDK2, JAK1 and 6 other human proteins associated with multiple viral oncoproteins. The functional enrichment analysis of these top-notch key genes is performed using KEGG pathway and Gene Ontology analysis, which reveals that the gene set is enriched in cell cycle a crucial cellular process, and the second most important pathway in which the gene set is involved is viral carcinogenesis. Among the viral proteins, E7 has the highest number of associations in the network followed by E6, E2 and E5. We found out a group of genes which is not targeted by the existing drugs available for HPV infections. It can be concluded that the molecules found in this study could be potential targets and could be used by scientists in their drug design studies.

The In Silico Characterization of a Salicylic Acid Analogue Coding Gene Clusters in Selected Pseudomonas fluorescens Strains.

BACKGROUND: The microbial genome sequences provide solid in silico framework for interpretation of their drug-like chemical scaffolds biosynthetic potentials. Pseudomonas fluorescens strains are metabolically versatile and producing therapeutically important natural products. OBJECTIVES: The key objective of the present study was to mine the publically available data of P. fluorescens strains genomes for putative drug-like metabolites identification. MATERIALS AND METHODS: We implemented the computational biology resources of AntiSMASH and BAGEL3 for the secondary metabolites prediction from P. fluorescens strains genome sequences. The predicted secondary metabolites were evaluated using drug discovery chemoinformatics resources, like Drugbank database search and molecular docking inspection. RESULTS: The analyses unveiled a wide array of chemical scaffolds biosynthesis in different P. fluorescens strains. Subsequently, the drug-like potential evaluation of these metabolites identified few strains, including P. fluorescens PT14, P. fluorescens A5O6, and P. fluorescens FW300-N2E3 that harbor the biosynthetic gene clusters for salicylic acid-like metabolite biosynthesis. The molecular docking inspection of this metabolite against human cyclooxygenase and aldo-keto reductase targets revealed its feasible inhibitory potentials like other salicylate compounds. CONCLUSION: The computational biology and drug discovery analyses identified different gene clusters in P. fluorescens genomes coding for salicylic acid-like chemotypes biosynthesis. These gene clusters may worthy to target through metabolic engineering for the massive production of salicylates-like chemical scaffolds from microbial resources.

The in silico identification of small molecules for protein-protein interaction inhibition in AKAP-Lbc-RhoA signaling complex.

The rational design of small molecules that mimic key residues at the interface of interacting proteins can be a successful approach to target certain biological signaling cascades causing pathophysiological outcome. The A-Kinase Anchoring Protein, i.e. AKAP-Lbc, catalyses nucleotide exchange on RhoA and is involved in cardiac repolarization. The oncogenic AKAP-Lbc induces the RhoA GTPase hyperactivity and aberrantly amplifies the signaling pathway leading to hypertrophic cardiomyocytes. We took advantage of the AKAP-Lbc-RhoA complex crystal structure to design in silico small molecules predicted to inhibit the associated pathological signaling cascade. We adopted the strategies of pharmacophore building, virtual screening and molecular docking to identify the small molecules capable to target AKAP-Lbc and RhoA interactions. The pharmacophore model based virtual screening unveils two lead compounds from the TIMBAL database of small molecules modulating the targeted protein-protein interactions. The molecular docking analysis revealed the lead compounds' potentialities to establish the essential chemical interactions with the key interactive residues of the complex. These features provided a road map for designing additional potent chemical derivatives and fragments of the original lead compounds to perturb the AKAP-Lbc and RhoA interactions. Experimental validations may elucidate the therapeutic potential of these lead chemical scaffolds to deal with aberrant AKAP-Lbc signaling based cardiac hypertrophy.