Rationalization and design of the complementarity determining region sequences in an antibody-antigen recognition interface

Chung Ming Yu, Hung Pin Peng, Ing Chien Chen, Yu Ching Lee, Jun Bo Chen, Keng Chang Tsai, Ching Tai Chen, Jeng Yih Chang, Ei Wen Yang, Po Chiang Hsu, Jhih Wei Jian, Hung Ju Hsu, Hung Ju Chang, Wen Lian Hsu, Kai Fa Huang, Alex Che Ma, An Suei Yang

Research output: Contribution to journalArticlepeer-review

42 Citations (Scopus)


Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibody-VEGF (vascular endothelial growth factor) interaction as a model system, the experimentally observed amino acid preferences in the antibody-antigen interface can be rationalized with 3-dimensional distributions of interacting atoms derived from the database of protein structures. Machine learning models established on the rationalization can be generalized to design amino acid preferences in antibody-antigen interfaces, for which the experimental validations are tractable with current high throughput synthetic antibody display technologies. Leave-one-out cross validation on the benchmark system yielded the accuracy, precision, recall (sensitivity) and specificity of the overall binary predictions to be 0.69, 0.45, 0.63, and 0.71 respectively, and the overall Matthews correlation coefficient of the 20 amino acid types in the 24 interface CDR positions was 0.312. The structure-based computational antibody design methodology was further tested with other antibodies binding to VEGF. The results indicate that the methodology could provide alternatives to the current antibody technologies based on animal immune systems in engineering therapeutic and diagnostic antibodies against predetermined antigen epitopes.

Original languageEnglish
Article numbere33340
JournalPLoS One
Issue number3
Publication statusPublished - Mar 22 2012
Externally publishedYes

ASJC Scopus subject areas

  • General Agricultural and Biological Sciences
  • General Biochemistry,Genetics and Molecular Biology
  • General Medicine


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