Evidence map›Paper›PMID 38783525›Full record

ArticleThe journal of physical chemistry. B2024

Utility of the Morgan Fingerprint in Structure-Based Virtual Ligand Screening.

Hongyi Zhou, Jeffrey Skolnick

Abstract read
In one paragraph

Article in The journal of physical chemistry. B, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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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.

Hongyi ZhouCenter for the Study of Systems Biology, School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
Jeffrey SkolnickCenter for the Study of Systems Biology, School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.ORCID 0000-0002-1877-4958

Funding

Purchase of a GPU cluster for deep learning applications in protein-protein interaction and supercomplex prediction and biochemical literature annotation.R35GM118039 · NIGMS · GEORGIA INSTITUTE OF TECHNOLOGY · PI JEFFREY SKOLNICK · 2016 to 2026
$5.8M
NIGMS NIH HHS R35 GM118039
6 · The paper itself

Abstract

In modern drug discovery, virtual ligand screening (VLS) is frequently applied to identify possible hits before experimental testing and refinement due to its cost-effective nature for large compound libraries. For decades, efforts have been devoted to developing VLS methods with high accuracy. These include the state-of-the-art FINDSITE suite of approaches FINDSITE

Indexed as

Drug DiscoveryDrug Evaluation, PreclinicalLigandsMachine LearningMolecular StructureLigands

Identifiers

PMID38783525
PMCPMC11163432

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.