# The Role of Mutations, Addition of Amino Acids, and Exchange of Genetic Information in the Coevolution of Primitive Coding Systems

## TL;DR

This paper explores how early genetic codes evolved into stable systems by simulating mutations, adding amino acids, and exchanging information.

## Contribution

A novel evolutionary algorithm is introduced to simulate the coevolution of primitive coding systems.

## Key findings

- Stable coding systems emerged through mutations and information exchange.
- Information exchange significantly accelerated the encoding of 21 amino acids.
- The process led to diversified protein production and higher coding capacity.

## Abstract

The standard genetic code (SGC) plays a fundamental role in encoding biological information, but its evolutionary origins remain unresolved and widely debated. Thus, we used a methodology based on the evolutionary algorithm to investigate the emergence of stable coding systems. The simulation began with a population of varied primitive genetic codes that ambiguously encoded only a limited set of amino acids (labels). These codes underwent mutation, modeled by dynamic reassignment of labels to codons, gradual incorporation of new amino acids, and information exchange between themselves. Then, the best codes were selected using a specific fitness function F that measured the accuracy of reading genetic information and coding potential. The evolution converged towards stable and unambiguous coding systems with a higher coding capacity facilitating the production of more diversified proteins. A crucial factor in this process was the exchange of encoded information among evolving codes, which significantly accelerated the emergence of genetic systems capable of encoding 21 labels. The findings shed light on key factors that may have influenced the development of the current genetic code structure.