Investigation of codon alternation patterns in two neurodegenerative diseases through numerical representation and codon classification

Abstract

Several evidences claim similarities between two neuro-degenerative diseases viz.Parkinson's disease and Glaucoma. But proper pathogenetic factors specially in bio-molecular level are still not cleared. Hence, the prime objectives of the study here is to investigate evolutionary relationships among the genes involved in the diseases and to understand the pattern of mutations responsible in the two disease pathogenesis. Reported research work established that the strengths of nucleotides (according to number of hydrogen bonds they have) have a deep impact on protein formation. Moreover, depending upon the position the virulence of mutation differs. Effective mutation analysis can help to predict the fate of the diseased individual which can be validated later by in-vitro experiments. In this present study, PARKIN, PINK1, and DJ1 genes are taken for Parkinson's disease and CYP1B1 and MYOC for Glaucoma. Importance has been given to the nucleotides existing at first and second positions of a codon. We followed Rumer's classification of doublets based on the strength of nucleotides and Duplij’s numeric interpretation of the strength of each nucleotide as “determinative degree” to classify the 64 codons and corresponding amino acids into three major classes viz. strong, transitional, and weak. The determinative degrees of all 64 codons and corresponding 20 amino acids are calculated to define their strengths. The complete analysis is carried out based on this classification scheme. Further we proposed an alignment-free method SSADDA (Sequence Similarity Analysis using Determinative Degree of Amino acid) based on determinative degree of amino acid and applied to the wild type amino acid sequences to measure proximity among themselves. The methodology gives us a more microscopic view of the existing genetic code table.