Computer antibody combination mutation evolution system and method, information data processing terminal

Abstract

The invention belongs to the technical field of computer software, discloses a system and method for computing antibody combination mutation evolution, an Information Data Processing Terminal. The computer antibody combinatorial mutation evolution method adopts a genetic algorithm searching strategy, and generates a structural database of combinatorial mutants according to a plurality of amino acid sites in an antibody binding pocket through multiple cycles of calculation, and takes a specific binding free energy function as an affinity evaluation method to automatically evolve to obtain a combinatorial mutation antibody. The computer antibody combinatorial mutation evolution method adopts a genetic algorithm searching strategy, and generates a structural database of combinatorial mutantsaccording to a plurality of amino acid sites in an antibody binding pocket through multiple cycles of calculation, and takes a specific binding free energy function as an affinity evaluation method toautomatically evolve to obtain a combinatorial mutation antibody.

Description

technical field [0001] The invention belongs to the technical field of computer software, and in particular relates to a computer antibody combinatorial mutation evolution system and method, and an information data processing terminal. Background technique [0002] At present, the existing technologies commonly used in the industry are as follows: Using computer to simulate and predict is an important and effective method to improve the binding force of protein molecules. Antibody is a typical protein. Enhancing antibody binding affinity is of great significance for improving the detection sensitivity of antibodies, reducing the dosage of drugs and enhancing the efficacy of drugs. Compared with the traditional antibody library experiment technology, the method of using computer to design antibodies and improve their binding force can construct a computer virtual mutation library for simulated screening and predict potential high-affinity antibodies, which can greatly save m...

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Problems solved by technology

[0004] (1) The design method of artificial selection mutation only selects individual residue sites to try mutation design, and many potential excellent mutants are not included in the design scope for comprehensive evaluation, so it is difficult to screen for ideal design results. Mutants have poorer binding predictions than the naive or wild-type antibody, and the entire antibody design process must be redone

[0005] (2) The computer automatic mutation design method only uses random replacement of character strings to imitate various mutations at protein sequence sites, and the evaluation method used to evaluate the pros and cons of various mutations fails to consider the three-dimensional interaction information of antigens and antibodies, It is also difficult to achieve the desired effect

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