Evidence map›Paper›PMID 42304341›Full record

ArticleBMC biotechnology2026

Library-based, multiplexed strategy for mapping protein interaction networks via crosslinking.

Yuxin Lu, Shuting Meng, Yi Zhang, Fei Wang, Tingting Shi, Yijia Chi, Song Chen, Dongxin Zhao

Abstract read
In one paragraph

Article in BMC biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Yuxin LuSchool of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing, China.
Shuting MengSchool of Pharmacy, Henan University, Kaifeng, China.
Yi ZhangSchool of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing, China.
Fei WangShanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China.
Tingting ShiSchool of Pharmacy, Henan University, Kaifeng, China.
Yijia ChiShanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China.
Song ChenWellcome Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, UK. sc43@sanger.ac.uk.
Dongxin ZhaoSchool of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing, China. zhaodongxin@simm.ac.cn.

Funding

Innovative Drug Research and Development National Science and Technology Major Project 2025ZD1804100National Natural Science Foundation of China 82373972Strategic Priority Research Program of the Chinese Academy of Sciences XDB1260302
6 · The paper itself

Abstract

backgroundProtein-protein interactions are fundamental to cellular function, yet resolving their interaction interfaces and dynamic behaviors in native biological contexts remains challenging, particularly for weak or transient interactions. Crosslinking strategies based on noncanonical amino acids offer an effective means to capture such interactions; however, traditional single-site incorporation provides limited coverage and may overlook critical interaction hotspots.

resultsBy employing a mutagenesis library, multiple interaction partners and cross-linking sites of a target protein can be simultaneously screened in a single experiment, without prior knowledge of its precise structural or functional features, enabling effective and unbiased analysis of its interaction network. In this study, we constructed an amber codon-scanning mutagenesis library of PSMD10, facilitating independent incorporation of the photocrosslinking ncAA p-azido-phenylalanine at multiple distinct residues. This approach allowed us to systematically interrogate and precisely map potential interaction regions across the protein surface. Coupled with crosslinking mass spectrometry, we identified multiple residues involved in intermolecular interactions, as well as previously unreported interaction partners, including T2FA, TBA1C, and ATRIP.

conclusionsThese findings expand our understanding of PSMD10-associated proteasome interactome, demonstrate a multiplexed strategy for in situ mapping of protein interaction interfaces with broad coverage, and offer a valuable platform for developing therapeutics that target protein-protein interactions.

Indexed as

Cross-Linking ReagentsProtein Interaction MappingProtein Interaction MapsAzidesMutagenesisPhenylalanineProteasome Endopeptidase ComplexProtein BindingAzidesCross-Linking ReagentsPhenylalanineProteasome Endopeptidase ComplexAmber codon scanningCrosslinking mass spectrometryPhoto-crosslinkingProtein-protein interactionsScanning mutagenesis library

Identifiers

PMID42304341
PMCPMC13551947

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.