Published November 10, 2020
| Version v1
Journal article
Open
Biochemical patterns of antibody polyreactivity revealed through a bioinformatics-based analysis of cdr loops
Creators
- 1. University of Chicago
Description
Antibodies are critical components of adaptive immunity, binding with high affinity to pathogenic epitopes. Antibodies undergo rigorous selection to achieve this high affinity, yet some maintain an additional basal level of low affinity, broad reactivity to diverse epitopes, a phenomenon termed "polyreactivity". While polyreactivity has been observed in antibodies isolated from various immunological niches, the biophysical properties that allow for promiscuity in a protein selected for high affinity binding to a single target remain unclear. Using a database of over 1,000 polyreactive and non-polyreactive antibody sequences, we created a bioinformatic pipeline to isolate key determinants of polyreactivity. These determinants, which include an increase in inter-loop crosstalk and a propensity for a neutral binding surface, are sufficient to generate a classifier able to identify polyreactive antibodies with over 75% accuracy. The framework from which this classifier was built is generalizable, and represents a powerful, automated pipeline for future immune repertoire analysis.
Data availability
All data generated and all code used for analysis in this study has been published on GitHub at http://github.com/ctboughter/AIMS (copy archived at https://archive.softwareheritage.org/swh:1:rev:f6c855ef4a7ce63f72dba6b34e9d0e9edd9200ce/).
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Additional details
Identifiers
- DOI
- 10.7554/eLife.61393
- Other
- oai:uchicago.tind.io:9862
Funding
- National Institute of Biomedical Imaging and Bioengineering
- EB009412
- National Institute of Allergy and Infectious Diseases
- AI147954
- National Institute of Allergy and Infectious Diseases
- AI115471
- National Science Foundation
- MCB-1517221
- National Institute of Allergy and Infectious Diseases
- AI125250