Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface

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 at...

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Autores principales: Yu, Chung-Ming, Peng, Hung-Pin, Chen, Ing-Chien, Lee, Yu-Ching, Chen, Jun-Bo, Tsai, Keng-Chang, Chen, Ching-Tai, Chang, Jeng-Yih, Yang, Ei-Wen, Hsu, Po-Chiang, Jian, Jhih-Wei, Hsu, Hung-Ju, Chang, Hung-Ju, Hsu, Wen-Lian, Huang, Kai-Fa, Ma, Alex Che, Yang, An-Suei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3310866/
https://www.ncbi.nlm.nih.gov/pubmed/22457753
http://dx.doi.org/10.1371/journal.pone.0033340
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author Yu, Chung-Ming
Peng, Hung-Pin
Chen, Ing-Chien
Lee, Yu-Ching
Chen, Jun-Bo
Tsai, Keng-Chang
Chen, Ching-Tai
Chang, Jeng-Yih
Yang, Ei-Wen
Hsu, Po-Chiang
Jian, Jhih-Wei
Hsu, Hung-Ju
Chang, Hung-Ju
Hsu, Wen-Lian
Huang, Kai-Fa
Ma, Alex Che
Yang, An-Suei
author_facet Yu, Chung-Ming
Peng, Hung-Pin
Chen, Ing-Chien
Lee, Yu-Ching
Chen, Jun-Bo
Tsai, Keng-Chang
Chen, Ching-Tai
Chang, Jeng-Yih
Yang, Ei-Wen
Hsu, Po-Chiang
Jian, Jhih-Wei
Hsu, Hung-Ju
Chang, Hung-Ju
Hsu, Wen-Lian
Huang, Kai-Fa
Ma, Alex Che
Yang, An-Suei
author_sort Yu, Chung-Ming
collection PubMed
description 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.
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spelling pubmed-33108662012-03-28 Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface Yu, Chung-Ming Peng, Hung-Pin Chen, Ing-Chien Lee, Yu-Ching Chen, Jun-Bo Tsai, Keng-Chang Chen, Ching-Tai Chang, Jeng-Yih Yang, Ei-Wen Hsu, Po-Chiang Jian, Jhih-Wei Hsu, Hung-Ju Chang, Hung-Ju Hsu, Wen-Lian Huang, Kai-Fa Ma, Alex Che Yang, An-Suei PLoS One Research Article 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. Public Library of Science 2012-03-22 /pmc/articles/PMC3310866/ /pubmed/22457753 http://dx.doi.org/10.1371/journal.pone.0033340 Text en Yu et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Yu, Chung-Ming
Peng, Hung-Pin
Chen, Ing-Chien
Lee, Yu-Ching
Chen, Jun-Bo
Tsai, Keng-Chang
Chen, Ching-Tai
Chang, Jeng-Yih
Yang, Ei-Wen
Hsu, Po-Chiang
Jian, Jhih-Wei
Hsu, Hung-Ju
Chang, Hung-Ju
Hsu, Wen-Lian
Huang, Kai-Fa
Ma, Alex Che
Yang, An-Suei
Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface
title Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface
title_full Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface
title_fullStr Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface
title_full_unstemmed Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface
title_short Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface
title_sort rationalization and design of the complementarity determining region sequences in an antibody-antigen recognition interface
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3310866/
https://www.ncbi.nlm.nih.gov/pubmed/22457753
http://dx.doi.org/10.1371/journal.pone.0033340
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