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

Results: For our current study, we consider neurodegenerative and monogenic diseases. We use numerical representation based on a determinative degree and classification of codons as well as amino acids into three different classes (Strong, Weak and Transition) for the analysis. 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. 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.