ArticleMedical oncology (Northwood, London, England)2023
A multitier virtual screening of antagonists targeting PD-1/PD-L1 interface for the management of triple-negative breast cancer.
Article in Medical oncology (Northwood, London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 11 citations in OpenAlex.
- Machine learning-assisted screening of natural product database for the identification of novel chalcone-based derivative as a potent DHODH inhibitor in cancer therapy.Discover oncology · 2026Article
- Rational discovery of peptide inhibitors targeting Keap1: a focus on neurodegenerative diseases.Frontiers in bioinformatics · 2026Article
- Discovering TEAD4 modulators for hepatocellular carcinoma: a GAN-enabled generative modelling framework.Frontiers in bioinformatics · 2026Article
- Identification of novel dihydroorotate dehydrogenase (DHODH) inhibitors for cancer: computational drug repurposing strategy.BMC pharmacology & toxicology · 2025Article
- A Comparative Molecular Dynamics Study of Food-Derived Compounds as PD-L1 Inhibitors: Insights Across Six Flavonoid Subgroups.Molecules (Basel, Switzerland) · 2025Article
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Authors and funding
2 authors at 1 institution in 1 country.
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Abstract
Immunotherapies are promising therapeutic options for the management of triple-negative breast cancer because of its high mutation rate and genomic instability. Of note, the blockade of the immune checkpoint protein PD-1 and its ligand PD-L1 has been proven to be an efficient and potent strategy to combat triple-negative breast cancer. To date, various anti-PD-1/anti-PD-L1 antibodies have been approved. However, the intrinsic constraints of these therapeutic antibodies significantly limit their application, making small molecules a potentially significant option for PD-1/PD-L1 inhibition. In light of this, the current study aims to use a high-throughput virtual screening technique to identify potential repurposed candidates as PD-L1 inhibitors. Thus, the present study explored binding efficiency of 2509 FDA-approved compounds retrieved from the drug bank database against PD-L1 protein. The binding affinity of the compounds was determined using the glide XP docking programme. Furthermore, prime-MM/GBSA, DFT calculations, and RF score were used to precisely re-score the binding free energy of the docked complexes. In addition, the ADME and toxicity profiles for the lead compounds were also examined to address PK/PD characteristics. Altogether, the screening process identified three molecules, namely DB01238, DB06016 and DB01167 as potential therapeutics for the PD-L1 protein. To conclude, a molecular dynamic simulation of 100 ns was run to characterise the stability and inhibitory action of the three lead compounds. The results from the simulation study confirm the robust structural and thermodynamic stability of DB01238 than other investigated molecules. Thus, our findings hypothesize that DB01238 could serve as potential PD-L1 inhibitor in the near future for triple-negative breast cancer patients.
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