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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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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. |
format | Online Article Text |
id | pubmed-10443277 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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