Immunogenicity Assessment of Therapeutic Peptides

Overview

Journal Curr Med Chem

Publisher Bentham Science Publishers

Specialty Chemistry

Date 2024 Jan 26

PMID 38275064

Authors

Wenzhen Li

Jinyi Wei

Qianhu Jiang

Yuwei Zhou

Xingru Yan

ChangCheng Xiang

Jian Huang

Affiliations

Soon will be listed here.

Abstract

The application of therapeutic peptides in clinical practice has significantly progressed in the past decades. However, immunogenicity remains an inevitable and crucial issue in the development of therapeutic peptides. The prediction of antigenic peptides presented by MHC class II is a critical approach to evaluating the immunogenicity of therapeutic peptides. With the continuous upgrade of algorithms and databases in recent years, the prediction accuracy has been significantly improved. This has made evaluation an important component of immunogenicity assessment in therapeutic peptide development. In this review, we summarize the development of peptide-MHC-II binding prediction methods for antigenic peptides presented by MHC class II molecules and provide a systematic explanation of the most advanced ones, aiming to deepen our understanding of this field that requires particular attention.

Citing Articles

Computational Methods and Artificial Intelligence in the Discovery and Development of Therapeutic Peptides and Beyond.

Huang J Curr Med Chem. 2024; 31(26):4057.

PMID: 39081040 DOI: 10.2174/092986733126240531153954.

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