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abdelmoneim, a. h.

Publications and source records attributed to abdelmoneim, a. h..

2 recordsLinked to original sources

Multi-epitope Peptide Vaccine Prediction for Candida albicans targeting Pyruvate Kinase Protein; an Immunoinformatics Approach

The fungus Candida albicans is an opportunistic pathogen that causes a wide range of infections. Its the primary cause of candidiasis and the fourth most common cause of nosocomial infection. In addition, disseminated invasive candidiasis which is a major complication of the disease has an estimated mortality rate of 40%-60% even with the use of antifungal drugs. Over the last decades, several different anti-Candida vaccines have been suggested with different strategies for immunization against candidiasis such as, live-attenuated fungi, recombinant proteins, and glycoconjugates but none has been approved by the FDA, yet. This study aims to introduce a new possible vaccine for C. albicans through analyzing peptides of its pyruvate kinase (PK) protein as an immunogenic stimulant computationally.\n\nA total number of 28 C. albicans, pyruvate kinase proteins were obtained from NCBI on the 9th of February 2019 and were subjected to multiple sequence alignment using Bioedit for conservancy. The main analytical tool was IEDB, Chimera for homology modelling, and MOE for docking.\n\nAmong the tested peptides, fifteen promising T-cell peptides were predicted. Five peptides were more important than the others (HMIFASFIR, YRGVYPFIY, AVAAVSAAY, LRWAVSEAV, and IFASFIRTA) They show high Binding Affinity to MHC molecules, low binding energy required indicating more stable bonds, and their ideal length of nine peptides. (PTRAEVSDV) peptide is the most promising linear B-cell peptide due to its physiochemical parameters and optimal length (nine amino acids). Its highly recommended to have these five strong candidates in future in vivo and in vitro analysis studies.

bioinformatics

In silico analysis of coding SNPs and 3′-UTR associated miRNAs in DCAF17 gene that may affect the regulation and pathogenesis of Woodhouse-Sakati Syndrome

BackgroundWoodhouse-Sakati Syndrome refers to a group of inherited disorders characterized by alopecia, hypogonadism, diabetes mellitus, hypothyroidism and progressive extrapyramidal signs. The aim of this study is to identify the pathogenic SNPs in the DCAF17 gene with their related mciroRNAs and their effect on the structure and function of the protein.\n\nMaterial and MethodsWe used different bioinformatics tools to predict the effect of each SNP on the structure and function of the protein. After that we defined the miRNAs founded in the 3'-UTR region on the DCAF17 gene and studied the annotations relative to it.\n\nResultsTen deleterious SNPs out of 339 were found to have a damaging effect on the protein structure and function, with one significant micoRNA in the 3'-UTR region.\n\nConclusionThis was the first in silico analysis of DCAF17 gene, in which 10 novel mutations were found using different bioinformatics tools that could be used as a diagnostic markers for Woodhouse-Sakati syndrome, with one relevant microRNA that can regulate the function of the protein.

bioinformatics