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Recent Progress in Antibody Epitope Prediction

Recent progress in epitope prediction has shown promising results in the development of vaccines and therapeutics against various diseases. However, the overall accuracy and success rate need to be improved greatly to gain practical application significance, especially conformational epitope predict...

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Detalles Bibliográficos
Autores principales: Zeng, Xincheng, Bai, Ganggang, Sun, Chuance, Ma, Buyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10443277/
https://www.ncbi.nlm.nih.gov/pubmed/37606436
http://dx.doi.org/10.3390/antib12030052
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author Zeng, Xincheng
Bai, Ganggang
Sun, Chuance
Ma, Buyong
author_facet Zeng, Xincheng
Bai, Ganggang
Sun, Chuance
Ma, Buyong
author_sort Zeng, Xincheng
collection PubMed
description Recent progress in epitope prediction has shown promising results in the development of vaccines and therapeutics against various diseases. However, the overall accuracy and success rate need to be improved greatly to gain practical application significance, especially conformational epitope prediction. In this review, we examined the general features of antibody–antigen recognition, highlighting the conformation selection mechanism in flexible antibody–antigen binding. We recently highlighted the success and warning signs of antibody epitope predictions, including linear and conformation epitope predictions. While deep learning-based models gradually outperform traditional feature-based machine learning, sequence and structure features still provide insight into antibody–antigen recognition problems.
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spelling pubmed-104432772023-08-23 Recent Progress in Antibody Epitope Prediction Zeng, Xincheng Bai, Ganggang Sun, Chuance Ma, Buyong Antibodies (Basel) Review Recent progress in epitope prediction has shown promising results in the development of vaccines and therapeutics against various diseases. However, the overall accuracy and success rate need to be improved greatly to gain practical application significance, especially conformational epitope prediction. In this review, we examined the general features of antibody–antigen recognition, highlighting the conformation selection mechanism in flexible antibody–antigen binding. We recently highlighted the success and warning signs of antibody epitope predictions, including linear and conformation epitope predictions. While deep learning-based models gradually outperform traditional feature-based machine learning, sequence and structure features still provide insight into antibody–antigen recognition problems. MDPI 2023-08-08 /pmc/articles/PMC10443277/ /pubmed/37606436 http://dx.doi.org/10.3390/antib12030052 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Zeng, Xincheng
Bai, Ganggang
Sun, Chuance
Ma, Buyong
Recent Progress in Antibody Epitope Prediction
title Recent Progress in Antibody Epitope Prediction
title_full Recent Progress in Antibody Epitope Prediction
title_fullStr Recent Progress in Antibody Epitope Prediction
title_full_unstemmed Recent Progress in Antibody Epitope Prediction
title_short Recent Progress in Antibody Epitope Prediction
title_sort recent progress in antibody epitope prediction
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10443277/
https://www.ncbi.nlm.nih.gov/pubmed/37606436
http://dx.doi.org/10.3390/antib12030052
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