期刊
PROTEIN ENGINEERING DESIGN & SELECTION
卷 31, 期 11, 页码 409-418出版社
OXFORD UNIV PRESS
DOI: 10.1093/protein/gzz002
关键词
aggregation; CDR; mAb; non-specific binding; polyspecificity
资金
- National Institutes of Health [R01GM104130, R01AG050598]
- National Science Foundation [CBET 1159943, 1605266, 1813963]
- Albert M. Mattocks Chair
- Directorate For Engineering [1813963] Funding Source: National Science Foundation
- Directorate For Engineering
- Div Of Chem, Bioeng, Env, & Transp Sys [1605266] Funding Source: National Science Foundation
- Div Of Chem, Bioeng, Env, & Transp Sys [1813963] Funding Source: National Science Foundation
Specificity is one of the most important and complex properties that is central to both natural antibody function and therapeutic antibody efficacy. However, it has proven extremely challenging to define robust guidelines for predicting antibody specificity. Here we evaluated the physicochemical determinants of antibody specificity for multiple panels of antibodies, including >100 clinical-stage antibodies. Surprisingly, we find that the theoretical net charge of the complementarity-determining regions (CDRs) is a strong predictor of antibody specificity. Antibodies with positively charged CDRs have a much higher risk of low specificity than antibodies with negatively charged CDRs. Moreover, the charge of the entire set of six CDRs is a much better predictor of antibody specificity than the charge of individual CDRs, variable domains (V-H or V-L) or the entire variable fragment (F-v). The best indicators of antibody specificity in terms of CDR amino acid composition are reduced levels of arginine and lysine and increased levels of aspartic and glutamic acid. Interestingly, clinical-stage antibodies with negatively charged CDRs also have a lower risk for poor biophysical properties in general, including a reduced risk for high levels of self-association. These findings provide powerful guidelines for predicting antibody specificity and for identifying safe and potent antibody therapeutics.
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