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Current Medicinal Chemistry

Editor-in-Chief

ISSN (Print): 0929-8673
ISSN (Online): 1875-533X

Review Article

Current Computational Methods for Protein-Peptide Complex Structure Prediction

In Press, (this is not the final "Version of Record"). Available online 06 October, 2023
Author(s): Chao Yang*, Xianjin Xu and Changcheng Xiang
Published on: 06 October, 2023

DOI: 10.2174/0109298673263447230920151524

Price: $95

Abstract

Peptide-mediated protein-protein interactions (PPIs) play an important role in various biological processes. The development of peptide-based drugs to modulate PPIs has attracted increasing attention due to the advantages of high specificity and low toxicity. In the development of peptide-based drugs, one of the most important steps is to determine the interaction details between the peptide and the target protein. In addition to experimental methods, recently developed computational methods provide a cost-effective way for studying protein-peptide interactions. In this article, we carefully reviewed recently developed protein-peptide docking methods, which were classified into three groups: template-based docking, template-free docking, and hybrid method. Then, we presented available benchmarking sets and evaluation metrics for assessing protein-peptide docking performance. Furthermore, we discussed the use of molecular dynamics simulations, as well as deep learning approaches in protein-peptide complex prediction.

Keywords: Protein-peptide docking, benchmarking sets, evaluation metrics, molecular dynamics simulations, deep learning, docking performance


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