Evidence map›Paper›PMID 41274550›Full record

ArticleJournal of molecular biology2026

Dockground: Expanding the Resource to Protein-DNA Complexes.

Keeley W Collins, Matthew M Copeland, Petras J Kundrotas, Ilya A Vakser

Abstract read
In one paragraph

Article in Journal of molecular biology, 2026. 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. 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

4 authors.

Keeley W CollinsComputational Biology Program, The University of Kansas, Lawrence, KS 66045, United States.
Matthew M CopelandComputational Biology Program, The University of Kansas, Lawrence, KS 66045, United States.
Petras J KundrotasComputational Biology Program, The University of Kansas, Lawrence, KS 66045, United States. Electronic address: pkundro@ku.edu.
Ilya A VakserComputational Biology Program, The University of Kansas, Lawrence, KS 66045, United States; Department of Molecular Biosciences, The University of Kansas, Lawrence, KS 66045, United States. Electronic address: vakser@ku.edu.

Funding

Integrated Resource for Protein Recognition StudiesR01GM074255 · NIGMS · UNIVERSITY OF KANSAS LAWRENCE · PI VAKSER, ILYA · 2005 to 2024
$6.2M
Modeling of macromolecular interactions in the cellR35GM156453 · NIGMS · UNIVERSITY OF KANSAS LAWRENCE · PI ILYA VAKSER · 2025 to 2026
$671k
NIGMS NIH HHS R01 GM074255NIGMS NIH HHS R35 GM156453
6 · The paper itself

Abstract

Proteins and nucleic acids function by interacting with each other and with other molecules. Protein interactions with DNA are the basis of key cellular processes, such as replication, transcription, packaging, and DNA repair. To understand the mechanisms of these processes, it is important to know the structure of the molecular components and their interactions. Structures of protein complexes with nucleic acids are especially difficult to solve experimentally due to their greater instability. Thus, relatively few experimentally determined structures of such complexes are available. Computational modeling is essential for understanding biomolecular mechanisms and for the development of our ability to modulate them. Advances in the protein structure prediction field have shown that protein models can routinely reach unprecedented levels of near-experimental accuracy. In this context, modeling macromolecular interactions has become a focal point in structural biology. The Dockground project increases our knowledge of macromolecular interfaces and provides data resources for the development of techniques for structure-based modeling of macromolecular interactions. The resource, which contains protein-protein and protein-RNA complexes, has now been expanded to protein-DNA interactions. To advance the scope and functionality of the resource, the expansion includes new automatic weekly update procedures and user-friendly web interface for search, analysis and download of the protein-DNA complexes. The utility of the new release of the resource is illustrated by an example of benchmarking AlphaFold3 predictions. Dockground is publicly available at https://dockground.compbio.ku.edu.

Indexed as

Computational BiologyDatabases, ProteinDNADNA-Binding ProteinsProteinsModels, MolecularProtein BindingProtein ConformationSoftwareDNADNA-Binding ProteinsProteinsmolecular databasesmolecular recognitionprotein-DNA complexesprotein dockingstructural modeling

Identifiers

PMID41274550
PMCPMC12728743

What OpenQuestion holds

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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.