Evidence map›Paper›PMID 40362603›Full record

ArticleInternational journal of molecular sciences2025

Identification of Novel HPK1 Hit Inhibitors: From In Silico Design to In Vitro Validation.

Israa H Isawi, Rayan M Obeidat, Soraya Alnabulsi, Rufaida Al Zoubi

Abstract read
In one paragraph

Article in International journal of molecular sciences, 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

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.

Israa H IsawiDepartment of Medicinal Chemistry and Pharmacognosy, Faculty of Pharmacy, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan.ORCID 0000-0002-4342-5370
Rayan M ObeidatDepartment of Medicinal Chemistry and Pharmacognosy, Faculty of Pharmacy, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan.
Soraya AlnabulsiDepartment of Medicinal Chemistry and Pharmacognosy, Faculty of Pharmacy, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan.
Rufaida Al ZoubiDepartment of Medicinal Chemistry and Pharmacognosy, Faculty of Pharmacy, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan.ORCID 0000-0001-8417-4769

Funding

Deanship of Scientific Research at Jordan University of Science and Technology 20230410
6 · The paper itself

Abstract

Hematopoietic progenitor kinase 1 (HPK1), a negative regulator of T-cells, B-cells, and dendritic cells, has gained attention in antitumor immunotherapy research over the past decade. No HPK1 inhibitor has yet reached clinical approval, largely due to selectivity and drug-like limitations. Leveraging the available structural insights into HPK1, we conducted a rational hit identification using a structure-based virtual screening of over 600,000 drug-like molecules from ASINEX and OTAVA databases. A series of molecular docking studies, in vitro kinase assays, and molecular dynamics simulations were conducted to identify viable HPK1 inhibitor hits. This approach resulted in two promising novel hit scaffolds, 4H-Pyrido[1,2-a] thieno[2,3-d] pyrimidin-4-one (ISR-05) and quinolin-2(1H)-one (ISR-03), neither of which has previously been reported as an HPK1 inhibitor. ISR-05 and ISR-03 exhibited IC

Indexed as

Protein Kinase InhibitorsProtein Serine-Threonine KinasesComputer SimulationDrug DesignHumansMolecular Docking SimulationMolecular Dynamics Simulationhematopoietic progenitor kinase 1Protein Kinase InhibitorsProtein Serine-Threonine KinasesAnticancerHPK1 inhibitorimmunotherapymolecular dockingmolecular dynamicsvirtual screening

Identifiers

PMID40362603
PMCPMC12072202

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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.