Simulated evolution applied to study the genetic code optimality using a model of codon reassignments

Background: As the canonical code is not universal, different theories about its origin and organization have appeared. The optimization or level of adaptation of the canonical genetic code was measured taking into account the harmful consequences resulting from point mutations leading to the replacement of one amino acid for another. There are two basic theories to measure the level of optimization: the statistical approach, which compares the canonical genetic code with many randomly generated alternative ones, and the engineering approach, which compares the canonical code with the best possible alternative. Results: Here we used a genetic algorithm to search for better adapted hypothetical codes and as a method to guess the difficulty in finding such alternative codes, allowing to clearly situate the canonical code in the fitness landscape. This novel proposal of the use of evolutionary computing provides a new perspective in the open debate between the use of the statistical appr...

• Type: Journal
• Year: 2011
• Where: BMCBI
• Authors: Jose Santos, Ángel Monteagudo
• Keywords: Artificial Intelligence, BMCBI 2011, Canonical Code, Canonical Genetic Code, Code