ReviewChemical reviews2025
Drugging Challenging Cancer Targets Using Fragment-Based Methods.
Review in Chemical reviews, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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
3 citing papers in PubMed.
- Fragment-Based Discovery of Potent RNA-Competitive Inhibitors of the DEAH-Box RNA Helicase DHX8.Journal of medicinal chemistry · 2026Article
- NMR in the Age of Modern Biomedical Research and Drug Discovery.Journal of molecular biology · 2025Review
- Pharmacophore-driven antibody discovery on the yeast surface.bioRxiv : the preprint server for biology · 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
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There are many highly validated cancer targets that are difficult or impossible to drug due to the absence of suitable pockets that can bind small molecules. Fragment-based methods have been shown to be a useful approach for identifying ligands to proteins that were previously thought to be undruggable. In this review, I will give an overview of fragment-based ligand discovery and provide examples from our own work on how fragment-based methods were used to discover high affinity ligands for challenging cancer drug targets.
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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.