ReviewNature communications2026
Developments and challenges in hit progression within fragment-based drug discovery.
Review in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Artificial intelligence and ultra-high performance computing methods and experiments for drug discovery: virtual screening, deep learning, molecular dynamics simulations, ADMET modelling, and experimental validation.Molecular biomedicine · 2026Review
- A resource-efficient structure-based workflow for fragment progression enables parallel hit discovery and validation of functionally diverse modulators of NCS-1 protein-protein interactions.Chemical science · 2026Article
- Dual-Mode Native Mass Spectrometry Screening Identifies Ginsenoside Ligands of 6-Hydroxymethyl-7,8-Dihydropterin Pyrophosphokinase (HPPK).Molecules (Basel, Switzerland) · 2026Article
- Early-stage drug discovery in a new-generation ultrahigh-throughput mass spectrometry platform.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Biophysical Sensing Tools in Drug Discovery: Integrating Kinetics, Thermodynamics, Cellular Target Engagement and Structure.Sensors (Basel, Switzerland) · 2026Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Fragment-based Drug Discovery (FBDD) is a proven methodology for the discovery of new therapeutics. After the identification of small molecular fragments, subsequent steps are guided by the "Design, Make, Test" (DMT) cycle. During the "Design" phase, chemical modifications are proposed that generate Structure-Activity Relationship information, improve interaction profiles and physicochemical properties. In the "Make" phase, designs are synthesised into viable compounds, with an emphasis on feasibility, scalability and the incorporation of novel chemistries enabling broad chemical space sampling. Finally, the "Test" phase evaluates these compounds through a series of assays, identifying binders and enabling Structure-Activity Relationship models that guide subsequent designs. Within DMT cycles, fragment progression - the process of converting initial hits into more potent follow-up lead compounds - is an essential component, but has many challenges associated with it. Here, we review such challenges along with recent developments designed to mitigate them.
Indexed as
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.