IN SILICO STUDY OF DELETERIOUS SINGLE NUCLEOTIDE POLYMORPHISMS IN HUMAN HTRA2 GENE WITH THE PARKINSON’S DISEASE

Abstract

One of the most prevalent neurodegenerative illnesses that affects the elderly and is incurable is Parkinson's disease. Effective remedies for these illnesses are sometimes expensive, time-consuming, and coincidental to find. Prior research comparing several model organisms has shown that the majority of animals have comparable cellular and molecular traits. The Bioinformatics tools were used to find non-synonymous single nucleotide polymorphisms SIFTand Mutpred. The HTRA2 protein, a protein linked to Parkinson's disease, was used to predict nsSNPs.

This study is based on the analysis of single nucleotide polymorphisms in the human HTRA2 gene that cause Parkinson's disease. By determining the most effective prediagnosis techniques and Biological markers for illness prediction.

Our goal is to identify the most effective prediagnosis method for Parkinson's disease. A specific SNP is to serve as a molecular marker for the illness's prediagnosis. The analysis of non-synonymous SNPs (nsSNPs) in several Bioinformatics methods may facilitate the identification of critical diagnoses for the disease and enhance the treatment process for Parkinson's disease (PD).

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