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Epitope-Based Peptide Vaccine Design against Fructose Bisphosphate Aldolase of Candida glabrata : An Immunoinformatics Approach.

التفاصيل البيبلوغرافية
العنوان: Epitope-Based Peptide Vaccine Design against Fructose Bisphosphate Aldolase of Candida glabrata : An Immunoinformatics Approach.
المؤلفون: Elamin Elhasan LM; Faculty of Science and Technology, Department of Biotechnology, Omdurman Islamic University, Khartoum, Sudan., Hassan MB; Faculty of Medicine and Health Science, Omdurman Islamic University, Khartoum, Sudan., Elhassan RM; Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Sudan International University, Khartoum, Sudan., Abdelrhman FA; Department of Biotechnology, Africa City of Technology, Khartoum, Sudan., Salih EA; Biology and Technology Department, College of Applied and Industrial Sciences, University of Bahri, Khartoum, Sudan., Ibrahim H A; Faculty of Pharmacy, National Ribat University, Khartoum, Sudan., Mohamed AA; Al-Neelain Medical Research Center, Al-Neelain University, Khartoum, Sudan., Osman HS; Faculty of Medicine and Health Science, Omdurman Islamic University, Khartoum, Sudan., Khalil MSM; Al-Neelain Medical Research Center, Al-Neelain University, Khartoum, Sudan., Alsafi AA; Faculty of Science and Technology, Department of Biotechnology, Omdurman Islamic University, Khartoum, Sudan., Idris AB; Department of Medical Microbiology, Faculty of Medical Laboratory Sciences, University of Khartoum, Khartoum, Sudan., Hassan MA; Department of Biotechnology, Africa City of Technology, Khartoum, Sudan.; Department of Translation Bioinformatics, Detavax Biotech, Kayseri, Turkey.
المصدر: Journal of immunology research [J Immunol Res] 2021 May 04; Vol. 2021, pp. 8280925. Date of Electronic Publication: 2021 May 04 (Print Publication: 2021).
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Hindawi Publishing Corporation Country of Publication: Egypt NLM ID: 101627166 Publication Model: eCollection Cited Medium: Internet ISSN: 2314-7156 (Electronic) Linking ISSN: 23147156 NLM ISO Abbreviation: J Immunol Res Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Cairo, Egypt : Hindawi Publishing Corporation, [2014]-
مواضيع طبية MeSH: Candida glabrata/*immunology , Candidiasis/*therapy , Fructose-Bisphosphate Aldolase/*immunology , Fungal Proteins/*immunology , Fungal Vaccines/*immunology, Amino Acid Sequence/genetics ; Candida glabrata/enzymology ; Candida glabrata/genetics ; Candidiasis/immunology ; Candidiasis/microbiology ; Computational Biology ; Conserved Sequence/genetics ; Conserved Sequence/immunology ; Drug Design ; Epitope Mapping/methods ; Epitopes, B-Lymphocyte/genetics ; Epitopes, B-Lymphocyte/immunology ; Epitopes, T-Lymphocyte/genetics ; Epitopes, T-Lymphocyte/immunology ; Fructose-Bisphosphate Aldolase/genetics ; Fructose-Bisphosphate Aldolase/metabolism ; Fungal Proteins/genetics ; Fungal Proteins/metabolism ; Fungal Vaccines/administration & dosage ; Fungal Vaccines/genetics ; Histocompatibility Antigens Class I/immunology ; Histocompatibility Antigens Class I/metabolism ; Histocompatibility Antigens Class I/ultrastructure ; Histocompatibility Antigens Class II/immunology ; Histocompatibility Antigens Class II/metabolism ; Histocompatibility Antigens Class II/ultrastructure ; Humans ; Immunogenicity, Vaccine/genetics ; Molecular Docking Simulation ; Protein Structure, Tertiary ; Vaccines, Subunit/administration & dosage ; Vaccines, Subunit/genetics ; Vaccines, Subunit/immunology
مستخلص: Background: Candida glabrata is a human opportunistic pathogen that can cause life-threatening systemic infections. Although there are multiple effective vaccines against fungal infections and some of these vaccines are engaged in different stages of clinical trials, none of them have yet been approved by the FDA.
Aim: Using immunoinformatics approach to predict the most conserved and immunogenic B- and T-cell epitopes from the fructose bisphosphate aldolase (Fba1) protein of C. glabrata . Material and Method . 13 C. glabrata fructose bisphosphate aldolase protein sequences (361 amino acids) were retrieved from NCBI and presented in several tools on the IEDB server for prediction of the most promising epitopes. Homology modeling and molecular docking were performed.
Result: The promising B-cell epitopes were AYFKEH, VDKESLYTK, and HVDKESLYTK, while the promising peptides which have high affinity to MHC I binding were AVHEALAPI, KYFKRMAAM, QTSNGGAAY, RMAAMNQWL, and YFKEHGEPL. Two peptides, LFSSHMLDL and YIRSIAPAY, were noted to have the highest affinity to MHC class II that interact with 9 alleles. The molecular docking revealed that the epitopes QTSNGGAAY and LFSSHMLDL have the lowest binding energy to MHC molecules.
Conclusion: The epitope-based vaccines predicted by using immunoinformatics tools have remarkable advantages over the conventional vaccines in that they are more specific, less time consuming, safe, less allergic, and more antigenic. Further in vivo and in vitro experiments are needed to prove the effectiveness of the best candidate's epitopes (QTSNGGAAY and LFSSHMLDL). To the best of our knowledge, this is the first study that has predicted B- and T-cell epitopes from the Fba1 protein by using in silico tools in order to design an effective epitope-based vaccine against C. glabrata .
Competing Interests: The authors declare that there are no conflicts of interest.
(Copyright © 2021 Lina Mohamed Elamin Elhasan et al.)
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المشرفين على المادة: 0 (Epitopes, B-Lymphocyte)
0 (Epitopes, T-Lymphocyte)
0 (Fungal Proteins)
0 (Fungal Vaccines)
0 (Histocompatibility Antigens Class I)
0 (Histocompatibility Antigens Class II)
0 (Vaccines, Subunit)
EC 4.1.2.13 (Fructose-Bisphosphate Aldolase)
تواريخ الأحداث: Date Created: 20210526 Date Completed: 20211129 Latest Revision: 20220423
رمز التحديث: 20221213
مُعرف محوري في PubMed: PMC8116159
DOI: 10.1155/2021/8280925
PMID: 34036109
قاعدة البيانات: MEDLINE
الوصف
تدمد:2314-7156
DOI:10.1155/2021/8280925