Mapping synthetic binding proteins epitopes on diverse protein targets by protein structure prediction and protein-protein docking.


Journal

Computers in biology and medicine
ISSN: 1879-0534
Titre abrégé: Comput Biol Med
Pays: United States
ID NLM: 1250250

Informations de publication

Date de publication:
09 2023
Historique:
received: 16 04 2023
revised: 12 06 2023
accepted: 13 06 2023
medline: 21 8 2023
pubmed: 23 6 2023
entrez: 23 6 2023
Statut: ppublish

Résumé

Synthetic binding proteins (SBPs) are a class of artificial proteins engineered from privileged protein scaffolds, which can form highly specific molecular recognition interfaces with a variety of targets. Due to the characteristics of small size, high stability, and good tissue permeability, SBPs have important applications in biomedical research, disease diagnosis and treatment. However, knowledge of SBPs epitopes on the structures of target proteins is still limited, which hinder the development of novel SBPs. In this study, based on the currently available information of SBPs and their targets, 96 pairs of interacting proteins referring to 96 representative SBPs and 80 different targets, were systemically investigated using the state-of-the-art computational modeling techniques including AlphaFold2 protein structure prediction and Rosetta protein-protein docking. As a result, 71 out of the 96 pairs were successfully docked, of which 18, 33, and 20 pairs were defined as models with high, medium, and acceptable quality, respectively. In addition, the interface information was analyzed to decipher the interaction types driven SBPs and targets recognition. Overall, this work not only provides important structural information for understanding the mechanism of action of other SBPs with same protein scaffold, but also for aiding the rational protein engineering and to design of novel SBPs with biomedical applications.

Identifiants

pubmed: 37352638
pii: S0010-4825(23)00648-0
doi: 10.1016/j.compbiomed.2023.107183
pii:
doi:

Substances chimiques

Carrier Proteins 0
Proteins 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

107183

Informations de copyright

Copyright © 2023 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that there are no competing interests associated with the manuscript.

Auteurs

Arzu Mijit (A)

Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing, 401331, China.

Xiaona Wang (X)

Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing, 401331, China.

Yanlin Li (Y)

Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing, 401331, China.

Hangwei Xu (H)

School of Medicine, Hangzhou City University, Hangzhou, 310000, China.

Yingjun Chen (Y)

Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing, 401331, China. Electronic address: cxue2006@126.com.

Weiwei Xue (W)

Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing, 401331, China. Electronic address: xueww@cqu.edu.cn.

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Classifications MeSH