ArticleACS omega2025
Targeting Ubiquitin-Specific Protease 7 (USP7): A Pharmacophore-Guided Drug Repurposing and Physics-Based Molecular Simulation Study.
Article in ACS omega, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Targeting BCL-2 through Deep Learning-Based Drug Repurposing: A Multimodal Approach Combining Diffusion-Based Generative Modeling, Neural Relational Inference, and In Vitro Validation.Journal of chemical information and modeling · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ubiquitin-specific protease 7 (USP7) is a key regulator of tumor suppressors, oncoproteins, and epigenetic machinery, making it a compelling target for cancer therapy. Overexpression of USP7 correlates with worse survival of patients with multiple types of cancer, including multiple myeloma, and has been shown to contribute to chemoresistance. Here, we represent a structure-based drug repurposing pipeline to identify novel USP7 inhibitors from a curated library of 6654 FDA-approved and investigational small molecules. Using structure-based pharmacophore models derived from USP7-ligand crystal structures, we screened and prioritized hits based on pharmacophoric compatibility. The top 100 hits were subjected to short 10-ns molecular dynamics (MD) simulations and MM/GBSA binding free energy calculations, narrowing down to 36 promising ligands. These were further evaluated through longer (100 ns) MD simulations, binding energy refinement, ligand clustering based on molecular fingerprints, and cancer-specific activity predictions using a binary QSAR model. By integrating our findings, we propose 12 drugs as the most promising lead molecules: carafiban, alnespirone, morclofone, etofylline clofibrate, xantifibrate, cefmatilenum, cefovecin, puromycin, troglitazone, droxicam, vidarabine, and furbucillin. Further in vitro biological activity testing and validation of these potential USP7 inhibitors may lead to the discovery of highly promising USP7 inhibitors as anticancer drugs.
Identifiers
What 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.