Effective binding to protein antigens by antibodies from antibody libraries designed with enhanced protein recognition propensities.

Abstract:

:Antibodies provide immune protection by recognizing antigens of diverse chemical properties, but elucidating the amino acid sequence-function relationships underlying the specificity and affinity of antibody-antigen interactions remains challenging. We designed and constructed phage-displayed synthetic antibody libraries with enriched protein antigen-recognition propensities calculated with machine learning predictors, which indicated that the designed single-chain variable fragment variants were encoded with enhanced distributions of complementarity-determining region (CDR) hot spot residues with high protein antigen recognition propensities in comparison with those in the human antibody germline sequences. Antibodies derived directly from the synthetic antibody libraries, without affinity maturation cycles comparable to those in in vivo immune systems, bound to the corresponding protein antigen through diverse conformational or linear epitopes with specificity and affinity comparable to those of the affinity-matured antibodies from in vivo immune systems. The results indicated that more densely populated CDR hot spot residues were sustainable by the antibody structural frameworks and could be accompanied by enhanced functionalities in recognizing protein antigens. Our study results suggest that synthetic antibody libraries, which are not limited by the sequences found in antibodies in nature, could be designed with the guidance of the computational machine learning algorithms that are programmed to predict interaction propensities to molecules of diverse chemical properties, leading to antibodies with optimal characteristics pertinent to their medical applications.

journal_name

MAbs

journal_title

mAbs

authors

Jian JW,Chen HS,Chiu YK,Peng HP,Tung CP,Chen IC,Yu CM,Tsou YL,Kuo WY,Hsu HJ,Yang AS

doi

10.1080/19420862.2018.1550320

subject

Has Abstract

pub_date

2019-02-01 00:00:00

pages

373-387

issue

2

eissn

1942-0862

issn

1942-0870

journal_volume

11

pub_type

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