Browsing by Author "Oladipo, Elijah Kolawole"

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    Designing a conserved peptide‑based subunit vaccine against SARS‑CoV‑2 using immunoinformatics approach
    (In Silico Pharmacology, 2021-01-06) Oladipo, Elijah Kolawole; Ajayi, Ayodeji Folorunsho; Onile, O.S.; Ariyo, Olumuyiwa Elijah; Jimah, Esther Moradeyo; Ezediuno, Louis Odinakaose
    The widespread of coronavirus (COVID-19) is a new global health crisis that poses a threat to the world. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originated in bats and was discovered first in Wuhan, Hubei province, China in December 2019. Immunoinformatics and bioinformatics tools were employed for the construction of a multi-epitope subunit vaccine to prevent the diseases. The antigenicity, toxicity and allergenicity of all epitopes used in the construction of the vaccine were predicted and then conjugated with adjuvants and linkers. Vaccine Toll-Like Receptors (2, 3, 4, 8 and 9) complex was also evaluated. The vaccine construct was antigenic, non-toxic and non-allergic, which indicates the vaccines ability to induce antibodies in the host, making it an effective vaccine candidate.
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    Exploration of surface glycoprotein to design multi-epitope vaccine for the prevention of Covid-19
    (Informatics in Medicine Unlocked, 2020-09-27) Oladipo, Elijah Kolawole; Ajayi, Ayodeji Folorunsho; Ariyo, Olumuyiwa Elijah; Onile, Samson Olugbenga
    Stimulation and generation of T and B cell-mediated long-term immune response are essential for the curbing of a deadly virus such as SAR-CoV-2 (Severe Acute Respiratory Corona Virus 2). Immunoinformatics approach in vaccine design takes advantage of antigenic and non-allergenic epitopes present on the spike glycoprotein of SARS-CoV-2 to elicit immune responses. T cells and B cells epitopes were predicted, and the selected residues were subjected to allergenicity, antigenicity and toxicity screening which were linked by appropriate linkers to form a multi-epitope subunit vaccine. The physiochemical properties of the vaccine construct were analyzed, and the molecular weight, molecular formula, theoretical isoelectric point value, half-life, solubility score, instability index, aliphatic index and GRAVY were predicted. The vaccine structure was constructed, refined, validated, and disulfide engineered to get the best model. Molecular binding simulation and molecular dynamics simulation were carried out to predict the stability and binding affinity of the vaccine construct with TLRs. Codon acclimatization and in silico cloning were performed to confirm the vaccine expression and potency. Results obtained indicated that this novel vaccine candidate is non-toxic, capable of initiating the immunogenic response and will not induce an allergic reaction. The highest binding energy was observed in TLR4 (Toll-like Receptor 4) (􀀀 1398.1), and the least is TLR 2 (􀀀 1479.6). The steady rise in Th (T-helper) cell population with memory development was noticed, and IFN-g (Interferon gamma) was provoked after simulation. At this point, the vaccine candidate awaits animal trial to validate its efficacy and safety for use in the prevention of the novel COVID-19 (Coronavirus Disease 2019) infections.