Computational formulation of a multiepitope vaccine unveils an exceptional prophylactic candidate against Merkel cell polyomavirus

Merkel cell carcinoma (MCC) is a rare neuroendocrine skin malignancy caused by human Merkel cell polyomavirus (MCV), leading to the most aggressive skin cancer in humans. MCV has been identified in approximately 43%–100% of MCC cases, contributing to the highly aggressive nature of primary cutaneous carcinoma and leading to a notable mortality rate. Currently, no existing vaccines or drug candidates have shown efficacy in addressing the ailment caused by this specific pathogen. Therefore, this study aimed to design a novel multiepitope vaccine candidate against the virus using integrated immunoinformatics and vaccinomics approaches. Initially, the highest antigenic, immunogenic, and non-allergenic epitopes of cytotoxic T lymphocytes, helper T lymphocytes, and linear B lymphocytes corresponding to the virus whole protein sequences were identified and retrieved for vaccine construction. Subsequently, the selected epitopes were linked with appropriate linkers and added an adjuvant in front of the construct to enhance the immunogenicity of the vaccine candidates. Additionally, molecular docking and dynamics simulations identified strong and stable binding interactions between vaccine candidates and human Toll-like receptor 4. Furthermore, computer-aided immune simulation found the real-life-like immune response of vaccine candidates upon administration to the human body. Finally, codon optimization was conducted on the vaccine candidates to facilitate the in silico cloning of the vaccine into the pET28+(a) cloning vector. In conclusion, the vaccine candidate developed in this study is anticipated to augment the immune response in humans and effectively combat the virus. Nevertheless, it is imperative to conduct in vitro and in vivo assays to evaluate the efficacy of these vaccine candidates thoroughly. These evaluations will provide critical insights into the vaccine’s effectiveness and potential for further development

In silico formulation of a next-generation multiepitope vaccine for use as a prophylactic candidate against Crimean-Congo hemorrhagic fever

Abstract Background Crimean-Congo hemorrhagic fever (CCHF) is a widespread disease transmitted to humans and livestock animals through the bite of infected ticks or close contact with infected persons’ blood, organs, or other bodily fluids. The virus is responsible for severe viral hemorrhagic fever outbreaks, with a case fatality rate of up to 40%. Despite having the highest fatality rate of the virus, a suitable treatment option or vaccination has not been developed yet. Therefore, this study aimed to formulate a multiepitope vaccine against CCHF through computational vaccine design approaches. Methods The glycoprotein, nucleoprotein, and RNA-dependent RNA polymerase of CCHF were utilized to determine immunodominant T- and B-cell epitopes. Subsequently, an integrative computational vaccinology approach was used to formulate a multi-epitopes vaccine candidate against the virus. Results After rigorous assessment, a multiepitope vaccine was constructed, which was antigenic, immunogenic, and non-allergenic with desired physicochemical properties. Molecular dynamics (MD) simulations of the vaccine-receptor complex show strong stability of the vaccine candidates to the targeted immune receptor. Additionally, the immune simulation of the vaccine candidates found that the vaccine could trigger real-life-like immune responses upon administration to humans. Conclusions Finally, we concluded that the formulated multiepitope vaccine candidates would provide excellent prophylactic properties against CCHF

Neuropharmacological assessment and identification of possible lead compound (apomorphine) from <i>Hygrophila spinosa</i> through <i>in-vivo</i> and <i>in-silico</i> approaches

The aim of this research is to examine possible neurological activity of methanol, ethyl acetate, and aqueous extracts of Hygrophila spinosa and identify possible lead compounds through in silico analysis. In vivo, neuropharmacological activity was evaluated by using four distinct neuropharmacological assessment assays. Previously reported GC-MS data and earlier literature were utilized to identify the phytochemicals present in Hygrophila spinosa. Computational studies notably molecular docking and molecular dynamic simulations were conducted with responsible receptors to assess the stability of the best interacting compound. Pharmacokinetics properties like absorption, distribution, metabolism, excretion, and toxicity were considered to evaluate the drug likeliness properties of the identified compounds. All the in vivo results support the notion that different extracts (methanol, ethyl acetate, and aqueous) of Hygrophila spinosa have significant (*p = 0.05) sedative-hypnotic, anxiolytic, and anti-depressant activity. Among all the extracts, specifically methanol extracts of Hygrophila spinosa (MHS 400 mg/kg.b.w.) showed better sedative, anxiolytic and antidepressant activity than aqueous and ethyl acetate extracts. In silico molecular docking analysis revealed that among 53 compounds 7 compounds showed good binding affinities and one compound, namely apomorphine (CID: 6005), surprisingly showed promising binding affinity to all the receptors . An analysis of molecular dynamics simulations confirmed that apomorphine (CID: 6005) had a high level of stability at the protein binding site. Evidence suggests that Hygrophila spinosa has significant sedative, anxiolytic, and antidepressant activity. In silico analysis revealed that a particular compound (apomorphine) is responsible for this action. Further research is required in order to establish apomorphine as a drug for anxiety, depression, and sleep disorders. Communicated by Ramaswamy H. Sarma</p