A RESIDUE NUMBER SYSTEM (RNS) ANTI-CODON TABLE FOR PROTEIN SYNTHESIS

Abstract

Purpose: This study aims to optimise the representation and processing of genetic information through RNS encoding. Design/Methodology/Approach: The RNS anti-codon table is constructed as a table of RNS genetic code using the concept of number trees. The complementarity of bases suggests the swap of bases leading to the generation of 64 anti-codons for all possible codons of the genetic code. These are algorithmically reduced to less than 40 known anti-codons due to wobbling. Findings: The finding indicates that the decimal values change as the moduli sets vary, but the residue digits remain the same. Codons and anti-codons are static with some bases, in this case, moduli set and vary with the third base. Research Limitations: The current RNS implementation may experience overflow issues when dealing with extensive protein sequences and difficulty in verifying results across different organism types Practical Implications: This research answers the compelling cases of a quarternary number system in molecular biology applications. In the era of Artificial Intelligence (AI) and machine learning and the desire for gene editing, gene therapy, and personalised medicine, digital implementations are enhanced with number systems. Social Implication: The findings demonstrate the far-reaching impact of implementing RNS anticodon tables in protein synthesis, highlighting the need for careful consideration and planning in its deployment and integration into society. Originality/ Value: This research represents a significant departure from conventional approaches to genetic information processing, introducing multiple layers of innovation that advance theoretical understanding and practical applications in the field. � African Journal of Applied Research Arca Academic Publisher.