Evidence map›Paper›PMID 40337923›Full record

ArticleNucleic acids research2025

E3Docker: a docking server for potential E3 binder discovery.

Kejia Yan, Wangqiu He, Mingwei Pang, Xufeng Lu, Zhou Chen, Lianhua Piao, Han Zhang, Yu Wang, Shan Chang, Ren Kong

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nucleic acids research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Kejia YanInstitute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China.
Wangqiu HeInstitute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China.
Mingwei PangInstitute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China.
Xufeng LuPrimary Biotechnology Co., Ltd, Changzhou 213125, China.
Zhou ChenInstitute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China.
Lianhua PiaoInstitute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China.
Han ZhangInstitute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
Yu WangInstitute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
Shan ChangInstitute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China.ORCID 0000-0001-7169-9398
Ren KongInstitute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China.ORCID 0000-0001-9010-1750

Funding

Jiangsu University of TechnologyNational Guidance Fund on Developing Local Science and Technology for Sichuan Province 2023ZYD0167National Natural Science Foundation of China 62373172
6 · The paper itself

Abstract

Targeted protein degradation (TPD) has emerged as a promising therapeutic strategy for modulating protein levels in cells. Proteolysis-targeting chimeras and molecular glues facilitate the formation of a complex between the protein of interest (POI) and a specific E3 ligase, leading to POI ubiquitination and subsequent degradation by the proteasome. Considering over 600 E3s in the human genome, it is of great potential to find novel E3 binders and recruit new E3 ligase for TPD related drug discovery. Here we introduce E3Docker, an online computational tool for E3 binder discovery. A total of 1075 Homo sapiens E3 ligases are collected from databases and literature, and 4474 three-dimensional structures of these E3 ligases, in either apo or complex forms, are integrated into the web server. The druggable pockets for each E3 ligase are defined by experimentally bound ligand from PDB or predicted by using DeepPocket. CoDock-Ligand is employed as docking engine for potential E3 binder estimation. With a user-friendly interface, E3Docker facilitates the generation of binding poses and affinity scores for compounds with over 1000 kinds of E3 ligases and may benefit for novel E3 binder discovery. The E3Docker server and tutorials are freely available at https://e3docker.schanglab.org.cn/.

Indexed as

Molecular Docking SimulationSoftwareUbiquitin-Protein LigasesBinding SitesDatabases, ProteinDrug DiscoveryHumansInternetLigandsProtein BindingProteolysisUbiquitinationLigandsUbiquitin-Protein Ligases

Identifiers

PMID40337923
PMCPMC12230658

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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.