Evidence map›Paper›PMID 37676594›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

GRAMM Web Server for Protein Docking.

Amar Singh, Matthew M Copeland, Petras J Kundrotas, Ilya A Vakser

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers.

0numbers the graph read from it
0cells of the map it votes in
78citing 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

78 citing papers in PubMed.

  1. Article
  2. High-Density Type I Collagen Promotes IFN-γAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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  17. Chinese cobra (Naja atra) SVPLACommunications biology · 2026
    Article
  18. Article
  19. Review
  20. Article

18 more citing papers are in PubMed but not listed here.

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.

Amar SinghComputational Biology Program and Department of Molecular Biosciences, The University of Kansas, Lawrence, KS, USA.
Matthew M CopelandComputational Biology Program and Department of Molecular Biosciences, The University of Kansas, Lawrence, KS, USA.
Petras J KundrotasComputational Biology Program and Department of Molecular Biosciences, The University of Kansas, Lawrence, KS, USA. pkundro@ku.edu.
Ilya A VakserComputational Biology Program and Department of Molecular Biosciences, The University of Kansas, Lawrence, KS, USA. vakser@ku.edu.

Funding

Integrated Resource for Protein Recognition StudiesR01GM074255 · NIGMS · UNIVERSITY OF KANSAS LAWRENCE · PI VAKSER, ILYA · 2005 to 2024
$6.2M
NIGMS NIH HHS R01 GM074255
6 · The paper itself

Abstract

Prediction of the structure of protein complexes by docking methods is a well-established research field. The intermolecular energy landscapes in protein-protein interactions can be used to refine docking predictions and to detect macro-characteristics, such as the binding funnel. A new GRAMM web server for protein docking predicts a spectrum of docking poses that characterize the intermolecular energy landscape in protein interaction. A user-friendly interface provides options to choose free or template-based docking, as well as other advanced features, such as clustering of the docking poses, and interactive visualization of the docked models.

Indexed as

ComputersCluster AnalysisEnergy landscapeFree dockingProtein–protein interactionsTemplate-based dockingWeb-based resource

Identifiers

PMID37676594

What OpenQuestion holds

Textmetadata
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.