In Silico Immunogenicity Assessment of Therapeutic Peptides


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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 in silico 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.

About the authors

Wenzhen Li

School of Life Science and Technology, University of Electronic Science and Technology of China

Email: info@benthamscience.net

Jinyi Wei

School of Life Science and Technology, University of Electronic Science and Technology of China

Email: info@benthamscience.net

Qianhu Jiang

School of Life Science and Technology, University of Electronic Science and Technology of China

Email: info@benthamscience.net

Yuwei Zhou

School of Life Science and Technology, University of Electronic Science and Technology of China

Email: info@benthamscience.net

Xingru Yan

School of Biological Sciences, University of Auckland

Email: info@benthamscience.net

Changcheng Xiang

School of Computer Science and Technology, Aba Teachers University

Author for correspondence.
Email: info@benthamscience.net

Jian Huang

School of Life Science and Technology, University of Electronic Science and Technology of China

Author for correspondence.
Email: info@benthamscience.net

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