4.5 Article

Binding symmetry and surface flexibility mediate antibody self-association

Journal

MABS
Volume 11, Issue 7, Pages 1300-1318

Publisher

TAYLOR & FRANCIS INC
DOI: 10.1080/19420862.2019.1632114

Keywords

Aggregation; native folding; single point mutation; structure-aggregation relationship; prediction method

Funding

  1. Natural Sciences and Engineering Research Council (NSERC) of Canada [436202]
  2. Canada Foundation for Innovation
  3. NSERC
  4. University of Saskatchewan
  5. Government of Saskatchewan
  6. Western Economic Diversification Canada
  7. National Research Council Canada
  8. Canadian Institutes of Health Research

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Solution stability is an important factor in the optimization of engineered biotherapeutic candidates such as monoclonal antibodies because of its possible effects on manufacturability, pharmacology, efficacy and safety. A detailed atomic understanding of the mechanisms governing self-association of natively folded protein monomers is required to devise predictive tools to guide screening and re-engineering along the drug development pipeline. We investigated pairs of affinity-matured full-size antibodies and observed drastically different propensities to aggregate from variants differing by a single amino-acid. Biophysical testing showed that antigen-binding fragments (Fabs) from the aggregating antibodies also reversibly associated with equilibrium dissociation constants in the low-micromolar range. Crystal structures (PDB accession codes 6MXR, 6MXS, 6MY4, 6MY5) and bottom-up hydrogen-exchange mass spectrometry revealed that Fab self-association occurs in a symmetric mode that involves the antigen complementarity-determining regions. Subtle local conformational changes incurred upon point mutation of monomeric variants foster formation of complementary polar interactions and hydrophobic contacts to generate a dimeric Fab interface. Testing of popular in silico tools generally indicated low reliabilities for predicting the aggregation propensities observed. A structure-aggregation data set is provided here in order to stimulate further improvements of in silico tools for prediction of native aggregation. Incorporation of intermolecular docking, conformational flexibility, and short-range packing interactions may all be necessary features of the ideal algorithm.

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