PITHA: A Webtool to Predict Immunogenicity for Humanized and Fully Human Therapeutic Antibodies.
Methods in molecular biology (Clifton, N.J.)(2023)
摘要
Immunogenicity is an important concern to therapeutic antibodies during antibody design and development. Based on the co-crystal structures of idiotypic antibodies and their antibodies, one can see that anti-idiotypic antibodies usually bind the complementarity-determining regions (CDR) of idiotypic antibodies. Sequence and structural features, such as cavity volume at the CDR region and hydrophobicity of CDR-H3 loop region, were identified for distinguishing immunogenic antibodies from non-immunogenic antibodies. These features were integrated together with a machine learning platform to predict immunogenicity for humanized and fully human therapeutic antibodies (PITHA). This method achieved an accuracy of 83% in a leave-one-out experiment for 29 therapeutic antibodies with available crystal structures. The web server of this method is accessible at http://mabmedicine.com/PITHA or http://sysbio.unl.edu/PITHA . This method, as a step of computer-aided antibody design, helps evaluate the safety of new therapeutic antibody, which can save time and money during the therapeutic antibody development.
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关键词
B-cell epitopes,Data mining,Immunogenicity,Prediction methods,Protein structures,Therapeutic antibodies
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