Evidence map›Paper›PMID 42756147›Full record

ArticleFrontiers in immunology2026

Rational design of D(+)-biotin-conjugated resorcinol dibenzyl ethers as tumor-targeted PD-L1 inhibitors for precision cancer immunotherapy.

Jing-Jing Du, Rongling Liu, Lei Chen, Jian Zhang

Abstract read
PubMed Full text at PMC Publisher
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Article in Frontiers in immunology, 2026. 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
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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.

Jing-Jing DuHubei Provincial Key Laboratory of Occurrence and Intervention of Kidney Diseases, Hubei Provincial Engineering Research Center of Immunotherapy Drugs for Renal Tumors, Hubei Polytechnic University, School of Medicine, Huangshi, Hubei, China.
Rongling LiuHubei Provincial Key Laboratory of Occurrence and Intervention of Kidney Diseases, Hubei Provincial Engineering Research Center of Immunotherapy Drugs for Renal Tumors, Hubei Polytechnic University, School of Medicine, Huangshi, Hubei, China.
Lei ChenHubei Provincial Key Laboratory of Occurrence and Intervention of Kidney Diseases, Hubei Provincial Engineering Research Center of Immunotherapy Drugs for Renal Tumors, Hubei Polytechnic University, School of Medicine, Huangshi, Hubei, China.
Jian ZhangHuangshi Central Hospital, Huangshi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study aims to discover and characterize novel D(+)-biotin-conjugated PD-L1 inhibitors for precision tumor-targeted cancer immunotherapy. Methods: Integrated strategies, including computer-aided molecular simulation, antiproliferative activity (CCK8) assay, surface plasmon resonance (SPR), pharmacokinetic evaluation, and Results: Compound SW-1 showed potent and selective inhibitory activity against PD-1/PD-L1 interaction with an IC Conclusions: SW-1, as a highly potent biotin-conjugated PD-L1 small-molecule inhibitor, exhibits outstanding target activity, favorable pharmacokinetic properties, potent antitumor efficacy, and high safety. These results highlight SW-1 as a promising lead candidate for further development in precision tumor-targeted immunotherapy.

Indexed as

B7-H1 AntigenBiotinImmune Checkpoint InhibitorsImmunotherapyResorcinolsAnimalsCell Line, TumorDrug DesignHumansMelanoma, ExperimentalMiceMice, Inbred C57BLMolecular Docking SimulationMolecular Dynamics SimulationRatsTumor MicroenvironmentB7-H1 AntigenBiotinCD274 protein, humanImmune Checkpoint InhibitorsresorcinolResorcinolsD(+)−biotinPD−1/PD−L1precision cancer immunotherapysmall−molecule PD−L1 inhibitortumor−targeted

Identifiers

PMID42756147
PMCPMC13582261

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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.