A Numerical Representation and Classification of Codons to Investigate Codon Alternation Patterns during Genetic Mutations on Disease Pathogenesis

Abstract

AbstractAlteration of amino acid is possible due to mutation in codons that could have potential reasons to occur disease. Effective mutation analysis can help to predict the fate of the diseased individual which can be validated later by in-vitro experiments. It may also help an individual who is asymptomatic but having a particular genetic change for early detection and diagnosis during any terminal diseases. We try to investigate the codon alteration patterns and its impact during mutation for the genes known to be responsible for a particular disease. For our current study, we consider two neurodegenerative diseases, Parkinson’s disease and Glaucoma. We use numerical representation of four nucleotides based on the number of hydrogen bonds in their chemical structures and make classification of 64 codons as well as amino acids into three different classes (Strong, Weak and Transition). The entire analysis has been carried out based on these classifications. Our analysis reveals that the strong class codons are highly mutated followed by weak and transition class. We observe that most of the mutations occur in the first or second positions in the codon rather than the third. While looking into the chemical properties of amino acid, we observe that amino acids belong to the aliphatic group are affected most during missense mutations. Our investigation further emphasises that in most of the cases the change in the determinative degree of codon due to mutation is directly proportional to the physical density property. Further calculation of determinative degree of 20 amino acids and getting determinative degree of any arbitrary set of amino acid sequences from them may help biologists to understand the evolutionary information of amino acid occurrence frequencies of in proteins. In addition, our scheme gives a more microscopic and alternative representation of the existing codon table that helps in deciphering interesting codon alteration patterns during mutations in disease pathogenesis.