A p- adic approach to the TSPO gene

Area of Science:

• Genetics
• Bioinformatics
• Computational Biology

Background:

• Translocator Protein (TSPO) gene dysregulation is linked to various human diseases.
• Limited research exists on how TSPO gene sequence variations affect protein function and disease association.
• Assessing genetic variant pathogenicity is vital for clinical applications.

Purpose of the Study:

• To introduce and evaluate the p-adic distance approach as an alternative in-silico tool for predicting genetic variant effects.
• To determine the functional relevance of coding Single Nucleotide Polymorphisms (SNPs) in the TSPO gene.
• To compare the efficacy of the p-adic approach with existing prediction tools for variant classification.

Main Methods:

• Utilized the p-adic distance approach, modeling the genetic code within a 5-adic space.
• Calculated 5-adic and 2-adic distances between codons to identify functionally similar codons.
• Integrated in-silico prediction tools and bioinformatics analysis to assess TSPO coding SNPs.

Main Results:

• The p-adic distance model effectively describes the degeneracy of the genetic code.
• Identified pairs of codons with minimal 5-adic and 2-adic distances encoding the same amino acid or stop signal.
• Demonstrated the potential utility of the p-adic approach in classifying and prioritizing TSPO variants.

Conclusions:

• The p-adic distance approach offers a novel method for analyzing genetic code degeneracy.
• This approach shows promise as a valuable tool in bioinformatics for evaluating the functional impact of genetic variants.
• Further validation is needed to establish its role alongside existing in-silico prediction tools for TSPO gene analysis.