Evidence map›Paper›PMID 38827451›Full record

ArticleArXiv2025

Assessing the potential of deep learning for protein-ligand docking.

Alex Morehead, Nabin Giri, Jian Liu, Pawan Neupane, Jianlin Cheng

Abstract readPreprint
PubMed Full text at PMC
In one paragraph

Article in ArXiv, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Alex MoreheadNERSC, Lawrence Berkeley National Laboratory, Berkeley, California, USA.
Nabin GiriElectrical Engineering & Computer Science, NextGen Precision Health, University of Missouri, Columbia, Missouri, USA.
Jian LiuElectrical Engineering & Computer Science, NextGen Precision Health, University of Missouri, Columbia, Missouri, USA.
Pawan NeupaneElectrical Engineering & Computer Science, NextGen Precision Health, University of Missouri, Columbia, Missouri, USA.
Jianlin ChengElectrical Engineering & Computer Science, NextGen Precision Health, University of Missouri, Columbia, Missouri, USA.

Funding

Integrated Prediction of Protein Struture at 1D, 2D and 3D LevelsR01GM093123 · NIGMS · UNIVERSITY OF MISSOURI-COLUMBIA · PI CHENG, JIANLIN · 2010 to 2023
$3.8M
Deep learning methods for automated and accurate reconstruction of protein structures from cryo-EM image dataR01GM146340 · NIGMS · UNIVERSITY OF MISSOURI-COLUMBIA · PI CHENG, JIANLIN · 2022 to 2025
$1.4M
NIGMS NIH HHS R01 GM093123NIGMS NIH HHS R01 GM146340
6 · The paper itself

Abstract

The effects of ligand binding on protein structures and their

Indexed as

BenchmarksDeep learningMolecular dockingProtein-ligand interactions

Identifiers

PMID38827451
PMCPMC11142318

What OpenQuestion holds

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LicenceCC BY
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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.