Evidence map›Paper›PMID 40758915›Full record

ArticleChemphyschem : a European journal of chemical physics and physical chemistry2025

Accurate and Rapid Ranking of Protein-Ligand Binding Affinities Using Density Matrix Fragmentation and Physics-Informed Machine Learning Dispersion Potentials.

Ka Un Lao, Danyang Wang

Abstract read
In one paragraph

Article in Chemphyschem : a European journal of chemical physics and physical chemistry, 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. 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

2 authors.

Ka Un LaoDepartment of Chemistry, Virginia Commonwealth University, Richmond, 23284, VA, USA.ORCID 0000-0002-3993-536X
Danyang WangDepartment of Chemistry, Virginia Commonwealth University, Richmond, 23284, VA, USA.

Funding

Seed Awards from the Virginia Commonwealth University College of Humanities and Sciences
6 · The paper itself

Abstract

The generalized many-body expansion for building density matrices (GMBE-DM), truncated at the one-body level and combined with a purification scheme, is applied to rank protein-ligand binding affinities across two cyclin-dependent kinase 2 (CDK2) datasets and one Janus kinase 1 (JAK1) dataset, totaling 28 ligands. This quantum fragmentation-based method achieves strong correlation with experimental binding free energies (R

Indexed as

Cyclin-Dependent Kinase 2Machine LearningHumansLigandsProtein BindingThermodynamicsCyclin-Dependent Kinase 2Ligandsdispersionfragmentationmachine learningprotein–ligand bindingquantum chemistry

Identifiers

PMID40758915
PMCPMC12503914

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.