In silico comprehensive analysis of coding and non-coding SNPs in human mTOR protein

Area of Science:

• Genetics and Molecular Biology
• Bioinformatics and Computational Biology
• Disease Mechanisms

Background:

• The mechanistic target of rapamycin (mTOR) protein is a key regulator of cell growth, implicated in diseases such as cancer and diabetes.
• Non-synonymous single nucleotide polymorphisms (nsSNPs) in the mTOR gene have been observed in various cancers, potentially altering protein structure and function.

Purpose of the Study:

• To identify the most deleterious nsSNPs in the mTOR protein.
• To create a structured dataset of mTOR gene SNPs for potential use as biomarkers in disease treatment.
• To understand the impact of specific mutations on mTOR protein structure and interactions.

Main Methods:

• Utilized sequence and structure-based bioinformatics approaches to analyze mTOR protein SNPs.
• Filtered 2178 nsSNPs down to 11 deleterious variants and identified two non-coding variations.
• Employed various bioinformatics tools for comprehensive SNP analysis.

Main Results:

• All 11 identified nsSNPs were predicted to destabilize the mTOR protein structure and impair its function.
• Specific mutations (R619C, A1513D, T1977R) were shown to affect protein geometry (C alpha distances, bond angles).
• Several nsSNPs (L509Q, R619C, N2043S) were predicted to disrupt interactions with key proteins (NBS1) and complexes (FKBP1A/rapamycin).
• One non-coding SNP was found to alter miRNA binding sites, potentially affecting gene regulation.

Conclusions:

• Characterizing the detrimental effects of nsSNPs and non-coding SNPs on mTOR is crucial for understanding disease molecular mechanisms.
• These findings highlight the significant impact of mutations on protein structure and function.
• The identified SNPs and their functional consequences can serve as potential targets for disease diagnosis and therapeutic strategies.