Evidence map›Paper›PMID 42087554›Full record

ArticleNucleic acids research2026

CB-Dock3: an enhanced web server for protein-ligand blind docking.

Yang Liu, Ji Ding, Jianhong Gan, Xiaoman Xiong, Fanjie Zong, Zhi-Xiong Xiao, Yang Cao

Abstract read
In one paragraph

Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Neuroprotective Potential ofBiomolecules · 2026
    Article
  2. Article
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

7 authors.

Yang LiuCenter of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, Sichuan, 610065, China.ORCID 0000-0002-2517-9436
Ji DingCenter of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, Sichuan, 610065, China.
Jianhong GanCenter of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, Sichuan, 610065, China.
Xiaoman XiongCenter of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, Sichuan, 610065, China.
Fanjie ZongCenter of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, Sichuan, 610065, China.
Zhi-Xiong XiaoCenter of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, Sichuan, 610065, China.
Yang CaoCenter of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, Sichuan, 610065, China.ORCID 0000-0002-1925-2123

Funding

Prevention and Control of Emerging and Major Infectious Diseases-National Science and Technology Major Project 2025ZD01904100
6 · The paper itself

Abstract

Elucidating protein-ligand interactions is pivotal for understanding biological mechanisms and accelerating drug discovery. Blind docking, which identifies binding sites without prior knowledge, has become an indispensable computational strategy for analyzing the surge of protein structures generated by Cryo-EM and AI-based prediction tools like AlphaFold3. Our previous server, CB-Dock2, has been widely adopted by the global research community, averaging over 1000 daily submissions since July 2022 due to its accuracy and user-friendliness. Building on this foundation and incorporating extensive user feedback, we present CB-Dock3, a substantially enhanced platform. Key upgrades include a refined docking engine, an expanded template library, and support for diverse file formats. Benchmark evaluations on CASF-2016 demonstrate that CB-Dock3 achieves a success rate of 67.4% (RMSD ≤ 2.0 Å), representing a 10.6 percentage-point absolute improvement over its predecessor and outperforming other popular blind docking tools. Additionally, CB-Dock3 introduces critical new features driven by community needs: support for user-defined docking regions to handle large complexes, and a metal-aware protocol that explicitly retains essential metal ions and cofactors during simulation. CB-Dock3 stands as an accurate, rapid, and accessible resource for the scientific community, freely available at https://cadd.labshare.cn/cb-dock3/.

Indexed as

Molecular Docking SimulationProteinsSoftwareBinding SitesInternetLigandsProtein BindingProtein ConformationLigandsProteins

Identifiers

PMID42087554
PMCPMC13355045

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.