A p- adic approach to the TSPO gene
Elif Esenoğlu Bilgin1, Dilek Pirim2, Gökhan Soydan1
1Bursa Uludağ University, Faculty of Arts and Sciences, Department of Mathematics, Görükle Campus, Bursa, 16059, Türkiye.
Abstract:
TSPO protein is known to be involved in various cellular functions and dysregulations of TSPO expression has been found to be associated with pathologies of different human diseases, including cardiovascular disease, cancer, neuroinflammatory, neurodegenerative, neoplastic disorders. However, there are limited studies in the literature on the effects of sequence variations in the TSPO gene on the function of the protein and their relationship with human diseases. Evaluating the pathogenicity of genetic variants is crucial in terms of prioritizing the functional importance and clinical use. Therefore, various in-silico prediction tools have been developed that combine different algorithms to predict the effects of sequence variations on protein functions or gene regulation. In this study, the p-adic distance approach in modeling the genetic code, proposed and developed by Dragovich and Dragovich, was discussed in order to obtain an alternative to the existing in-silico prediction tools. Dragovichs' approach is expressed as follows: A 5-adic space of codons is constructed and 5-adic and 2-adic distances between codons are taken into account. As a result, two codons with the smallest value of 5-adic and 2-adic distances are obtained, encoded for the same amino acid and stop signal. This model describes well the degeneration of the genetic code. This study combined the data obtained from in-silico prediction tools and used a bioinformatics approach to determine the functional relevance of coding SNPs in the TSPO. Overall, we evaluate the potential utility of Dragovichs' approach by comparing it with other existing prediction tools for variant classification and prioritization.
Insights
This study explores a novel p-adic distance approach to predict the functional impact of genetic variations in the TSPO gene, offering a new tool for disease-associated variant analysis.
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.
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