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<p>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 identification 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, specifically missense variant risk factors. This platform consolidates the effects of all identified SNPs, facilitating easier access to their positional information and thereby optimizing time efficiency 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 benefits. 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: <a href="https://www.generisk.in/PDASD/">https://www.generisk.in/PDASD/</a></p>

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

  • 期刊论文

  • 发表日期：

    2025年5月28日

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  • Swetha Subramaniyan,
  • Ling Shing Wong,
  • Narayanasamy Marimuthu Prabhu,
  • Agnal Arumugam,
  • Radha Mahendran,
  • Karthikeyan Muthusamy

摘要

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 identification 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, specifically missense variant risk factors. This platform consolidates the effects of all identified SNPs, facilitating easier access to their positional information and thereby optimizing time efficiency 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 benefits. 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/