Literature DB >> 30770934

Net charge of antibody complementarity-determining regions is a key predictor of specificity.

Lilia A Rabia1,2,3, Yulei Zhang3, Seth D Ludwig1, Mark C Julian1, Peter M Tessier1,2,3,4.   

Abstract

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 (VH or VL) or the entire variable fragment (Fv). 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.
© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  CDR; aggregation; mAb; non-specific binding; polyspecificity

Mesh:

Substances:

Year:  2018        PMID: 30770934      PMCID: PMC6524611          DOI: 10.1093/protein/gzz002

Source DB:  PubMed          Journal:  Protein Eng Des Sel        ISSN: 1741-0126            Impact factor:   1.650


  12 in total

1.  Physicochemical Rules for Identifying Monoclonal Antibodies with Drug-like Specificity.

Authors:  Yulei Zhang; Lina Wu; Priyanka Gupta; Alec A Desai; Matthew D Smith; Lilia A Rabia; Seth D Ludwig; Peter M Tessier
Journal:  Mol Pharm       Date:  2020-06-11       Impact factor: 4.939

2.  Separating clinical antibodies from repertoire antibodies, a path to in silico developability assessment.

Authors:  Christopher Negron; Joyce Fang; Michael J McPherson; W Blaine Stine; Andrew J McCluskey
Journal:  MAbs       Date:  2022 Jan-Dec       Impact factor: 6.440

3.  Nature-inspired design and evolution of anti-amyloid antibodies.

Authors:  Mark C Julian; Lilia A Rabia; Alec A Desai; Ammar Arsiwala; Julia E Gerson; Henry L Paulson; Ravi S Kane; Peter M Tessier
Journal:  J Biol Chem       Date:  2019-03-27       Impact factor: 5.486

4.  Antibodies with Weakly Basic Isoelectric Points Minimize Trade-offs between Formulation and Physiological Colloidal Properties.

Authors:  Priyanka Gupta; Emily K Makowski; Sandeep Kumar; Yulei Zhang; Justin M Scheer; Peter M Tessier
Journal:  Mol Pharm       Date:  2022-02-02       Impact factor: 5.364

5.  Interaction of clinical-stage antibodies with heme predicts their physiochemical and binding qualities.

Authors:  Maxime Lecerf; Alexia Kanyavuz; Sofia Rossini; Jordan D Dimitrov
Journal:  Commun Biol       Date:  2021-03-23

6.  Biochemical patterns of antibody polyreactivity revealed through a bioinformatics-based analysis of CDR loops.

Authors:  Christopher T Boughter; Marta T Borowska; Jenna J Guthmiller; Albert Bendelac; Patrick C Wilson; Benoit Roux; Erin J Adams
Journal:  Elife       Date:  2020-11-10       Impact factor: 8.140

7.  Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space.

Authors:  Emily K Makowski; Patrick C Kinnunen; Jie Huang; Lina Wu; Matthew D Smith; Tiexin Wang; Alec A Desai; Craig N Streu; Yulei Zhang; Jennifer M Zupancic; John S Schardt; Jennifer J Linderman; Peter M Tessier
Journal:  Nat Commun       Date:  2022-07-01       Impact factor: 17.694

Review 8.  Toward Drug-Like Multispecific Antibodies by Design.

Authors:  Manali S Sawant; Craig N Streu; Lina Wu; Peter M Tessier
Journal:  Int J Mol Sci       Date:  2020-10-12       Impact factor: 5.923

Review 9.  Discovery-stage identification of drug-like antibodies using emerging experimental and computational methods.

Authors:  Emily K Makowski; Lina Wu; Priyanka Gupta; Peter M Tessier
Journal:  MAbs       Date:  2021 Jan-Dec       Impact factor: 5.857

10.  Highly sensitive detection of antibody nonspecific interactions using flow cytometry.

Authors:  Emily K Makowski; Lina Wu; Alec A Desai; Peter M Tessier
Journal:  MAbs       Date:  2021 Jan-Dec       Impact factor: 5.857

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