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      In silico designing of multiepitope-based-peptide (MBP) vaccine against MAPK protein express for Alzheimer's disease in Zebrafish

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          Abstract

          Understanding the role of the mitogen-activated protein kinases (MAPKs) signalling pathway is essential in advancing treatments for neurodegenerative disorders like Alzheimer's. In this study, we investigate in-silico techniques involving computer-based methods to extract the MAPK1 sequence. Our applied methods enable us to analyze the protein's structure, evaluate its properties, establish its evolutionary relationships, and assess its prevalence in populations. We also predict epitopes, assess their ability to trigger immune responses, and check for allergenicity using advanced computational tools to understand their immunological properties comprehensively. We apply virtual screening, docking, and structure modelling to identify promising drug candidates, analyze their interactions, and enhance drug design processes. We identified a total of 30 cell-targeting molecules against the MAPK1 protein, where we selected top 10 CTL epitopes (PAGGGPNPG, GGGPNPGSG, SAPAGGGPN, AVSAPAGGG, AGGGPNPGS, ATAAVSAPA, TAAVSAPAG, ENIIGINDI, INDIIRTPT, and NDIIRTPTI) for further evaluation to determine their potential efficacy, safety, and suitability for vaccine design based on strong binding potential. The potential to cover a large portion of the world's population with these vaccines is substantial—88.5 % for one type and 99.99 % for another. In exploring the molecular docking analyses, we examined a library of compounds from the ZINC database. Among them, we identified twelve compounds with the lowest binding energy. Critical residues in the MAPK1 protein, such as VAL48, LYS63, CYS175, ASP176, LYS160, ALA61, LEU165, TYR45, SER162, ARG33, PRO365, PHE363, ILE40, ASN163, and GLU42, are pivotal for interactions with these compounds. Our result suggests that these compounds could influence the protein's behaviour. Moreover, our docking analyses revealed that the predicted peptides have a strong affinity for the MAPK1 protein. These peptides form stable complexes, indicating their potential as potent inhibitors. This study contributes to the identification of new drug compounds and the screening of their desired properties. These compounds could potentially help reduce the excessive activity of MAPK1, which is linked to Alzheimer's disease.

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          VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines

          Background Vaccine development in the post-genomic era often begins with the in silico screening of genome information, with the most probable protective antigens being predicted rather than requiring causative microorganisms to be grown. Despite the obvious advantages of this approach – such as speed and cost efficiency – its success remains dependent on the accuracy of antigen prediction. Most approaches use sequence alignment to identify antigens. This is problematic for several reasons. Some proteins lack obvious sequence similarity, although they may share similar structures and biological properties. The antigenicity of a sequence may be encoded in a subtle and recondite manner not amendable to direct identification by sequence alignment. The discovery of truly novel antigens will be frustrated by their lack of similarity to antigens of known provenance. To overcome the limitations of alignment-dependent methods, we propose a new alignment-free approach for antigen prediction, which is based on auto cross covariance (ACC) transformation of protein sequences into uniform vectors of principal amino acid properties. Results Bacterial, viral and tumour protein datasets were used to derive models for prediction of whole protein antigenicity. Every set consisted of 100 known antigens and 100 non-antigens. The derived models were tested by internal leave-one-out cross-validation and external validation using test sets. An additional five training sets for each class of antigens were used to test the stability of the discrimination between antigens and non-antigens. The models performed well in both validations showing prediction accuracy of 70% to 89%. The models were implemented in a server, which we call VaxiJen. Conclusion VaxiJen is the first server for alignment-independent prediction of protective antigens. It was developed to allow antigen classification solely based on the physicochemical properties of proteins without recourse to sequence alignment. The server can be used on its own or in combination with alignment-based prediction methods. It is freely-available online at the URL: .
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            Potential for primary prevention of Alzheimer's disease: an analysis of population-based data.

            Recent estimates suggesting that over half of Alzheimer's disease burden worldwide might be attributed to potentially modifiable risk factors do not take into account risk-factor non-independence. We aimed to provide specific estimates of preventive potential by accounting for the association between risk factors. Using relative risks from existing meta-analyses, we estimated the population-attributable risk (PAR) of Alzheimer's disease worldwide and in the USA, Europe, and the UK for seven potentially modifiable risk factors that have consistent evidence of an association with the disease (diabetes, midlife hypertension, midlife obesity, physical inactivity, depression, smoking, and low educational attainment). The combined PAR associated with the risk factors was calculated using data from the Health Survey for England 2006 to estimate and adjust for the association between risk factors. The potential of risk factor reduction was assessed by examining the combined effect of relative reductions of 10% and 20% per decade for each of the seven risk factors on projections for Alzheimer's disease cases to 2050. Worldwide, the highest estimated PAR was for low educational attainment (19·1%, 95% CI 12·3-25·6). The highest estimated PAR was for physical inactivity in the USA (21·0%, 95% CI 5·8-36·6), Europe (20·3%, 5·6-35·6), and the UK (21·8%, 6·1-37·7). Assuming independence, the combined worldwide PAR for the seven risk factors was 49·4% (95% CI 25·7-68·4), which equates to 16·8 million attributable cases (95% CI 8·7-23·2 million) of 33·9 million cases. However, after adjustment for the association between the risk factors, the estimate reduced to 28·2% (95% CI 14·2-41·5), which equates to 9·6 million attributable cases (95% CI 4·8-14·1 million) of 33·9 million cases. Combined PAR estimates were about 30% for the USA, Europe, and the UK. Assuming a causal relation and intervention at the correct age for prevention, relative reductions of 10% per decade in the prevalence of each of the seven risk factors could reduce the prevalence of Alzheimer's disease in 2050 by 8·3% worldwide. After accounting for non-independence between risk factors, around a third of Alzheimer's diseases cases worldwide might be attributable to potentially modifiable risk factors. Alzheimer's disease incidence might be reduced through improved access to education and use of effective methods targeted at reducing the prevalence of vascular risk factors (eg, physical inactivity, smoking, midlife hypertension, midlife obesity, and diabetes) and depression. National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care for Cambridgeshire and Peterborough. Copyright © 2014 Elsevier Ltd. All rights reserved.
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              Oxidative stress and the amyloid beta peptide in Alzheimer’s disease

              Oxidative stress is known to play an important role in the pathogenesis of a number of diseases. In particular, it is linked to the etiology of Alzheimer’s disease (AD), an age-related neurodegenerative disease and the most common cause of dementia in the elderly. Histopathological hallmarks of AD are intracellular neurofibrillary tangles and extracellular formation of senile plaques composed of the amyloid-beta peptide (Aβ) in aggregated form along with metal-ions such as copper, iron or zinc. Redox active metal ions, as for example copper, can catalyze the production of Reactive Oxygen Species (ROS) when bound to the amyloid-β (Aβ). The ROS thus produced, in particular the hydroxyl radical which is the most reactive one, may contribute to oxidative damage on both the Aβ peptide itself and on surrounding molecule (proteins, lipids, …). This review highlights the existing link between oxidative stress and AD, and the consequences towards the Aβ peptide and surrounding molecules in terms of oxidative damage. In addition, the implication of metal ions in AD, their interaction with the Aβ peptide and redox properties leading to ROS production are discussed, along with both in vitro and in vivo oxidation of the Aβ peptide, at the molecular level.
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                Author and article information

                Contributors
                Journal
                Heliyon
                Heliyon
                Heliyon
                Elsevier
                2405-8440
                12 November 2023
                November 2023
                12 November 2023
                : 9
                : 11
                : e22204
                Affiliations
                [a ]Department of Biotechnology, Faculty of Life Sciences, University of Okara, Okara, 56300, Pakistan
                [b ]Department of Bioinformatics and Computational Biology, Virtual University, Punjab, 54700, Pakistan
                [c ]Department of Bioinformatics, Institute of Biochemistry, Biotechnology and Bioinformatics, The Islamia University of Bahawalpur, Bahawalpur, Pakistan
                [d ]Department of Parasitology, Faculty of Veterinary Science, Cholistan University of Veterinary and Animal Sciences, Bahawalpur, Pakistan
                [e ]Department of Environmental Sciences, Institute of Environmental and Agricultural Sciences, University of Okara, Okara, 56300, Pakistan
                [f ]Division of Fish Genetics and Biotechnology, Faculty of Fisheries, Rangil- Gandarbal (SKAUST-K), India
                [g ]Pharmaceutical Biotechnology Laboratory, Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, 11451, Saudi Arabia
                [h ]Department of Pharmacy, Faculty of Allied Health Sciences, Daffodil International, University, Dhaka, Bangladesh
                [i ]Department of Chemistry, Faculty of Science, University of Hradec Králové, Hradec Králové, 50 003, Czech Republic
                [j ]Biomedical Research Center, University Hospital Hradec Kralove, 50005, Hradec Kralove, Czech Republic
                [k ]Department of Rasashastra and Bhaishajya Kalpana, Faculty of Ayurveda, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
                Author notes
                []Corresponding author. shopnil.ph@ 123456gmail.com
                [∗∗ ]Corresponding author. arslansehgal@ 123456yahoo.com
                [∗∗∗ ]Corresponding author. rohitsharma@ 123456bhu.ac.in
                Article
                S2405-8440(23)09412-4 e22204
                10.1016/j.heliyon.2023.e22204
                10695983
                38058625
                79365671-bae8-407e-9b2e-8297450a7721
                © 2023 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 17 May 2023
                : 24 October 2023
                : 6 November 2023
                Categories
                Research Article

                pharmacophore,virtual screening,molecular docking,multiepitope,vaccine design,mapk1,alzheimer,zebrafish

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