Immunoinformatics design of multiepitopes peptide-based universal cancer vaccine using matrix metalloproteinase-9 protein as a target.

A new approach toward cancer therapy is the use of cancer vaccine, yet the different molecular bases of cancers, reduce the effectiveness of this approach. In this article, we aim to use matrix metalloproteinase-9 protein (MMP9) which is an essential molecule in the survival and metastasis of all types of cancers as a target for universal cancer vaccine design. The reference sequence of MMP9 protein was obtained from NCBI databases.

Design of a Multiepitope-Based Peptide Vaccine against the E Protein of Human COVID-19: An Immunoinformatics Approach.

Background: A new endemic disease has spread across Wuhan City, China, in December 2019. Within few weeks, the World Health Organization (WHO) announced a novel coronavirus designated as coronavirus disease 2019 (COVID-19). In late January 2020, WHO declared the outbreak of a "public-health emergency of international concern" due to the rapid and increasing spread of the disease worldwide.

Epitope-Based Peptide Vaccine against Glycoprotein G of Nipah Using Immunoinformatics Approaches.

Background: Nipah belongs to the genus and the . It is an endemic most commonly found at South Asia and has first emerged in Malaysia in 1998. Bats are found to be the main reservoir for this virus, causing disease in both humans and animals.

Extensive Analysis of Gene : Discovered Five Mutations That May Cause Hereditary Spastic Paraplegia Type 3A.

Background: Hereditary spastic paraplegia type 3A (SPG3A) is a neurodegenerative disease inherited type of Hereditary spastic paraplegia (HSP). It is the second most frequent type of HSP which is characterized by progressive bilateral and mostly symmetric spasticity and weakness of the legs. SPG3A gene mutations and the phenotype-genotype correlations have not yet been recognized.

In Silico Genetics Revealing 5 Mutations in Gene Associated With Acute Myeloid Leukemia.

Background: Acute myeloid leukemia (AML) is an extremely heterogeneous malignant disorder; AML has been reported as one of the main causes of death in children. The objective of this work was to classify the most deleterious mutation in CCAAT/enhancer-binding protein-alpha () and to predict their influence on the functional, structural, and expression levels by various Bioinformatics analysis tools.

Methods: The single nucleotide polymorphisms (SNPs) were claimed from the National Center for Biotechnology Information (NCBI) database and then submitted into various functional analysis tools, which were done to predict the influence of each SNP, followed by structural analysis of modeled protein followed by predicting the mutation effect on energy stability; the most damaging mutations were chosen for additional investigation by Mutation3D, Project hope, ConSurf, BioEdit, and UCSF Chimera tools.