Molecular insights and risk estimating computational database for Parkinson’s disease (PDASD)

Parkinson's disease (PD) is a more prevalent neurological disorder that typically manifests in adults. It is primarily caused
by the death of dopaminergic neurons in the substantia nigra, which leads to the degeneration of cardinal motor symptoms.
Several epigenetic elements are linked to the development of PD. The Parkin, PINK1, DJ-1, UCHL1, LRRK2, NURR1,
ATP13A2, GSK3B, and SNCA are important genes that are involved in the regulatory processes and development of PD.
The objective of the study is to develop a knowledge-based database for PD. “Parkinson Disease Associated SNP Database
(PDASD)" has been created to establish connections between PD-associated SNPs, related pathways, proteins, risk assessment, and molecular mechanisms, available FDA drugs for PD, nutrition involvement of PD and available PD literature
through the utilization of HTML and Java programming languages. This PDASD database has been amalgamated with 13
distinct databases to improve the accessibility of SNP data. The implementation of PDASD is anticipated to expedite the
process and facilitate the identifcation of innovative drug candidates for PD through the application of computational drug
design techniques in PD therapeutics. The PDASD database serves as a secondary resource that enhances the existing data
from various tools to predict the status of SNPs, specifcally missense variant risk factors. This platform consolidates the
efects of all identifed SNPs, facilitating easier access to their positional information and thereby optimizing time efciency
for users. A novelty of this database is its capacity to inform common people about the progression of PD through accessible
molecular mechanisms and information regarding nutritional benefts. It will be useful to understand the interconnection
of signaling pathways, molecular mechanisms, and risk-associated SNPs of PD, which may contribute to improving human
health, especially for the community with PD. The PDASD is an open and accessed database connected via the following
URL: https://www.generisk.in/PDASD/