Browsing by Author "Oluwaseun, Fadaka Adewale"

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    Aptamer-Based Diagnostic Systems for the Rapid Screening of TB at the Point-of-Care
    (MDPI, 2021) Darius, Riziki; Sibuyi, Nicole Remaliah Samantha; Oluwaseun, Fadaka Adewale
    The transmission of Tuberculosis (TB) is very rapid and the burden it places on health care systems is felt globally. The effective management and prevention of this disease requires that it is detected early. Current TB diagnostic approaches, such as the culture, sputum smear, skin tuberculin, and molecular tests are time-consuming, and some are unaffordable for low-income countries. Rapid tests for disease biomarker detection are mostly based on immunological assays that use antibodies which are costly to produce, have low sensitivity and stability. Aptamers can replace antibodies in these diagnostic tests for the development of new rapid tests that are more cost effective; more stable at high temperatures and therefore have a better shelf life; do not have batch-to-batch variations, and thus more consistently bind to a specific target with similar or higher specificity and selectivity and are therefore more reliable. Advancements in TB research, in particular the application of proteomics to identify TB specific biomarkers, led to the identification of a number of biomarker proteins, that can be used to develop aptamer-based diagnostic assays able to screen individuals at the point-of-care (POC) more efficiently in resource-limited settings.
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    Evaluation of selected carotenoids of Lycopersicon esculentum variants as therapeutic targets for 'Alzheimer's disease: an in silico approach BMC Molecular and Cell Biology
    (Springer, 2021-10) Bakare, Olalekan; Oluwaseun, Fadaka Adewale; Akanbi, Musa Oyebowale
    The seriousness and menace of the worldwide weight of 'Alzheimer's disease have been related to a few factors, which incorporate antioxidant system depletion, mutation of proteins, and high expression of cholinesterases due to ageing, environmental influence, diet, infectious agents, and hormonal imbalance. Overexpression of cholinesterases has been emphatically connected to 'Alzheimer's disease because of the unreasonable hydrolysis of acetylcholine and butyrylcholine. Certain plant phytochemicals, for example, beta-carotenoids, lutein, neoxanthin, and viola-xanthine from Lycopersicon esculentum Mill. Var. esculentum (ESC) and Lycopersicon esculentum Mill. Var. cerasiforme (CER) has been utilized altogether as a therapeutic candidate for the treatment of 'Alzheimer's disease. Therefore, this research sought to investigate the drug-likeness of the individual carotenoids as detailed for cholinesterase inhibition in the treatment of 'Alzheimer's disease. Four potential cholinesterase inhibitors from ESC and CER were retrieved from the PubChem database. Investigation of their drug-likeness, toxicity prediction, molecular docking, and dynamic simulations were carried out using Molinspiration, PreADMET V.2.0, Patchdock server, and Schrodinger Maestro software respectively. Neoxanthin was ranked the safest with a greater tendency to inhibit the cholinesterases with high binding affinity. In addition, its stability after simulation in a mimicked biological environment suggests its relevance as a potential drug candidate for the treatment of 'Alzheimer's disease through the inhibition of cholinesterases.
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    Immunoinformatics design of a novel epitope-based vaccine candidate against dengue virus
    (Springer, 2021-10) Oluwaseun, Fadaka Adewale; Sibuyi, Nicole Remaliah Samantha; Darius, Riziki
    Dengue poses a global health threat, which will persist without therapeutic intervention. Immunity induced by exposure to one serotype does not confer long-term protection against secondary infection with other serotypes and is potentially capable of enhancing this infection. Although vaccination is believed to induce durable and protective responses against all the dengue virus (DENV) serotypes in order to reduce the burden posed by this virus, the development of a safe and efficacious vaccine remains a challenge. Immunoinformatics and computational vaccinology have been utilized in studies of infectious diseases to provide insight into the host–pathogen interactions thus justifying their use in vaccine development. Since vaccination is the best bet to reduce the burden posed by DENV, this study is aimed at developing a multi-epitope based vaccines for dengue control. Combined approaches of reverse vaccinology and immunoinformatics were utilized to design multi-epitope based vaccine from the sequence of DENV. Specifically, BCPreds and IEDB servers were used to predict the B-cell and T-cell epitopes, respectively. Molecular docking was carried out using Schrödinger, PATCHDOCK and FIREDOCK. Codon optimization and in silico cloning were done using JCAT and SnapGene respectively. Finally, the efficiency and stability of the designed vaccines were assessed by an in silico immune simulation and molecular dynamic simulation, respectively. The predicted epitopes were prioritized using in-house criteria. Four candidate vaccines (DV-1–4) were designed using suitable adjuvant and linkers in addition to the shortlisted epitopes. The binding interactions of these vaccines against the receptors TLR-2, TLR-4, MHC-1 and MHC-2