Makhawi, A. | Search bioRxiv

bioRxiv2020

Epitope-Based Peptide Vaccine against Bombali Ebolavirus Viral Protein 40: An Immunoinformatics Combined with Molecular Docking Studies

BackgroundBombali Ebolavirus is RNA viruses belong to the Filoviridae family. They are causing lethal hemorrhagic fever with high mortality rate. Despite having available molecular knowledge of this virus, no approved vaccine or antiviral drugs have been developed yet for the eradication of Bombali Ebolavirus infections in humans. Objectivethe present study described a multi epitope-based peptide vaccine against Bombali Ebolavirus matrix protein VP40, using several immunoinformatics tools. Materials and MethodsThe six strains of Ebolavirus were retrieved from NCBI and Uniprot databases and submitted to VaxiJen to identify the most antigenic protein among all. Then PSIPRED, SOPMA, QMEAN, and PROCHECK tools were used to check the protein quality. T-cell prediction, population coverage, and molecular docking analysis were achieved to select peptides containing multiple Bombali VP40 epitopes showing interaction with multiple HLA molecules for expected immune response across the world. ResultBombali Ebola (YP_009513276.1) was found to be the most antigenic protein among all. Which it has been used in all required analysis. For T cell three epitopes showed high affinity to MHC class I (YSFDSTTAA, VQLPQYFTF, and MVNVISGPK) and high population coverage against Africa and the world. Furthermore in MHC class II, six promising epitopes that associated with most common MHC class II alleles. ConclusionThe above result conclude that, these peptides capable of provoking T-cell response and being interacted with a wide range of HLA molecules have a strong potential to be a vaccine against Bombali Ebolavirus.

bioinformatics↗

bioRxiv2020

Identification of High risk nsSNPs in Human TP53 Gene Associated with Li Fraumeni Syndrome: An In Silico Analysis Approach

BackgroundLi-Fraumeni syndrome (LFS) is a cancer-prone conditions caused by a germline mutation of the TP53 gene on chromosome 17p13.1. It has an autosomal dominant pattern of inheritance with high penetrance. PurposeThe aim of this study is to identify the high-risk pathogenic nsSNPs in PT53 gene that could be involved in the pathogenesis of Li-Fraumeni syndrome. MethodsThe nsSNPs in the human PT53 gene retrieved from NCBI, were analyzed for their functional and structural consequences using various in silico tools to predict the pathogenicity of each SNP. SIFT, Polyphen, PROVEAN, SNAP2, SNPs&Go, PHD-SNP, and P-Mut were chosen to study the functional inference while I-Mutant 3.0, and MUPro tools were used to test the impact of amino acid substitutions on protein stability by calculating {Delta}{Delta}G value. The effects of the mutations on 3D structure of the PT53 protein were predicted using RaptorX and visualized by UCSF Chimera. ResultsA total of 845 PT53 nsSNPs were analyzed. Out of 7 nsSNPs of PT53 three of them (T118L, C242S, and I251N) were found high-risk pathogenic. ConclusionIn this study, out of 7 predicted high-risk pathogenic nsSNPs, three high-risk pathogenic nsSNPs of PT53 gene were identified, which could be used as diagnostic marker for this gene. The combination of sequence-based and structure-based approaches is highly effective for pointing pathogenic regions.

bioinformatics↗