ReviewAnti-cancer agents in medicinal chemistry2026
Novel PD-L1 Small-Molecule Inhibitors Advancing Cancer Immunotherapy.
Review in Anti-cancer agents in medicinal chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Integrated Machine Learning and Molecular Simulation-Guided Discovery of Novel Small-Molecule PD-L1 Inhibitors.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Special Issue "Molecular Advances in Cancer Immunotherapy".International journal of molecular sciences · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe emergence of immune checkpoint inhibitors has revolutionized the treatment of cancer. Among these, the programmed cell death protein-1 (PD-1)/programmed death-ligand 1 (PD-L1) axis remains a critical target. However, resistance to current biologics necessitates the development of novel Small- Molecule Inhibitors (SMIs) with distinct mechanisms and improved pharmacological profiles. This review provides a comprehensive analysis of recent progress in PD-L1-targeting SMIs, including original compounds from our laboratory.
methodsWe conducted a structured literature review using electronic databases such as PubMed, Scopus, and Web of Science. Articles published between 2015 and 2025 were included based on relevance to small-molecule PD-L1 inhibitors in cancer immunotherapy. Key data were extracted and synthesized regarding molecular design strategies, mechanisms of action, pharmacokinetics, and therapeutic efficacy. Compounds synthesized in our laboratory (Compounds 5-10 [A56]) were evaluated using in vitro assays, including PD-L1/PD-1 binding inhibition, cancer cell viability assays, and gene expression profiling.
resultsRecent SMIs exhibit diverse functional profiles: direct blockade of PD-1/PD-L1 interaction, intracellular PD-L1 modulation, and transcriptional downregulation. Notably, Compound 7 demonstrated significant suppression of PD-L1 mRNA expression, while Compounds 9 and 10 (A56) achieved nanomolar-level binding affinity. These findings reflect innovative approaches to overcoming immune resistance and enhancing antitumor responses. DISCUSSIONS: Our findings underscore a trend toward multifunctional PD-L1-targeting SMIs that operate through both extracellular and intracellular mechanisms. Compounds from our laboratory represent potential leads for further optimization and clinical translation. However, challenges remain regarding oral bioavailability, metabolic stability, and immune-related adverse events.
conclusionSmall-molecule PD-L1 inhibitors offer a promising avenue for expanding cancer immunotherapy. Our review highlights key advances and introduces novel small-molecule PD-L1 inhibitors with strong potential for future development, particularly in combination regimens.
Indexed as
Identifiers
41051039What OpenQuestion holds
Registered trials
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.