Design and validation of human recombinant antibodies against Spastin using machine learning software Rosetta
Objective:This study aimed to achieve the design,in vitro preparation and validation of recombinant antibodies against human Spastin using the machine learning software Rosetta.Methods:Antibodies targeting the antigenic determinant of human Spastin protein were designed using Rosetta.The amino acid sequences of the Fab segment's light and heavy chains variable regions were obtained and converted into nucleotide sequences to obtain the full-length cDNA of the light and heavy chains after codon optimization.Subsequently,the sequences of the full human-derived anti-Spastin light and heavy chains were constructed in recombinant expression vectors.The antibodies were expressed and purified in the 293FT eukaryotic expression system.The ability of the antibodies to recognize the recombinant human Spastin protein were identified using Western blot.The binding and conformation of the antibody-antigen complex were simulated through Rosetta modeling.Results:The recombinant antibodies against human Spastin were successfully constructed and expressed in the eukaryotic system.The recombinant antibody's light and heavy chains formed complete antibodies that could specifically recognize the human Spastin protein.Conclusion:Using Rosetta software,this study successfully designed recombinant antibodies capable of specifically recognizing Spastin.
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