In silico SNP prediction of selected protein orthologues in insect models for Alzheimer's, Parkinson's, and Huntington's diseases.

ABSTRACT: Alzheimer's, Parkinson's, and Huntington's are the most common neurodegenerative diseases that are incurable and affect the elderly population. Discovery of effective treatments for these diseases is often difficult, expensive, and serendipitous. Previous comparative studies on different model organisms have revealed that most animals share similar cellular and molecular characteristics. The meta-SNP tool includes four different integrated tools (SIFT, PANTHER, SNAP, and PhD-SNP) was used to identify non synonymous single nucleotide polymorphism (nsSNPs). Prediction of nsSNPs was conducted on three representative proteins for Alzheimer's, Parkinson's, and Huntington's diseases; APPl in Drosophila melanogaster, LRRK1 in Aedes aegypti, and VCPl in Tribolium castaneum. With the possibility of

SUBMITTER: Al-Ayari EA 

PROVIDER: S-EPMC10624829 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature