基于机器学习Rosetta的全人源化Spastin重组抗体的设计和验证

Design and validation of human recombinant antibodies against Spastin using machine learning software Rosetta

目的:基于机器学习软件Rosetta实现人源化Spastin重组抗体的设计、体外制备及验证。方法:使用Rosetta设计出针对人Spastin蛋白抗原表位的全人源化抗体,获得其抗体Fab段轻链及重链可变区的氨基酸序列,优化密码子后转化为核苷酸序列得到轻、重链的全长cDNA;随后将全人源化抗Spastin的轻、重链序列分别构建于重组表达载体;在293FT真核表达体系中表达并纯化该抗体;使用Western blot方法鉴定该抗体识别人Spastin重组蛋白信号的能力;通过Rosetta建模模拟抗体与抗原的结合及构象。结果:成功构建了全人源化Spastin重组抗体;该Spastin重组抗体能够在真核系统成功表达;构建的重组抗体轻、重链能够形成完整抗体,且能够特异性识别出人Spastin蛋白信号。结论:借助Rosetta软件成功设计了一种能够特异识别Spastin的重组全人源化抗体。

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.