Codon optimization method based on immune algorithm

Abstract

The invention relates to a codon optimization method based on an immune algorithm. The codon optimization method is characterized in that an immune algorithm and a genetic algorithm are sequentially used for respectively carrying out local multi-objective optimization and global multi-objective optimization on a protein coding sequence, and then an exhaustion method is used for carrying out fine tuning optimization on the sequence, so that an optimal expression sequence is searched to the greatest extent. According to the codon optimization method based on an immune algorithm, the characteristics of random global parallel search of the genetic algorithm are reserved, and immature convergence is avoided to a great extent, and rapid convergence to a globally optimal solution is ensured. According to the codon optimization method based on an immune algorithm, the advantages of accuracy and efficiency of an immune algorithm and a genetic algorithm are combined and utilized for the first time; codon optimization is carried out through a step-by-step process (sequentially including local optimization, global optimization and fine tuning optimization); and the high efficiency of codon optimization carried out through the algorithm is proved through instance testing.

Description

technical field [0001] The present invention relates to a protein engineering technology, in particular to a codon optimization method in protein engineering, in particular to a codon optimization method based on immune algorithm. Background technique [0002] Codon degeneracy refers to the phenomenon that an amino acid can be encoded by multiple different codons during protein translation. Different codons encoding the same amino acid are called synonymous codons. A protein with a length of 200 amino acids is generally can be made by more than 10 20 encoded by different DNA sequences. In different species, the frequencies of synonymous codons are not the same, this phenomenon is called codon bias. Codon optimization is mainly based on factors such as the codon preference of the host expression system, using computer algorithms to screen out the DNA that can express the protein most efficiently in the host expression system from a large number of DNA coding sequences witho...

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Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that the existing codon optimization method has too long period and poor expression accuracy, and invent a method that can effectively complete the large-scale search of the codon optimization space in a limited time, that is, from Codon Optimization Method Based on Immune Algorithm for Screening the Most Efficiently Expressed DNA Sequences from Protein Coding Sequences

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