ReviewCommunications chemistry2025
NMR-driven structure-based drug discovery by unveiling molecular interactions.
Review in Communications chemistry, 2025. 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.
- Bridging structure and function: artificial intelligence-based modelling of kidney proteins.Nature reviews. Nephrology · 2026Review
- Natural Products Beyond Inhibition: A Mechanistic Framework Spanning Pockets, Interfaces, and Kinetic Barriers.Molecules (Basel, Switzerland) · 2026Review
- AI fragmentation-based optimization of Sorafenib derivatives targeting VEGFR2 for angiogenesis-related pathologies: a structure-based in-silico study.Scientific reports · 2026Article
- How does NMR support SARS-CoV-2 protein-ligand interaction studies?Analytical and bioanalytical chemistry · 2026Review
- Article
- DFT Structural and UV-Vis Spectral Insights into Photosensitivity of Vandetanib: A Dual EGFR/SARS-CoV-2 Mpro Inhibitor.Pharmaceuticals (Basel, Switzerland) · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-resolution 3D structural information is crucial for drug discovery and routinely used in structure-guided optimization to improve initial hits from screening campaigns to clinical drug candidates. X-ray crystallography is commonly the method of choice to guide medicinal chemistry in the design process, but it has its limitations and shortcomings. Here, we discuss the use of solution-state NMR spectroscopy in combination with selective side-chain labeling and advanced computational workflows to generate protein-ligand ensembles. This provides reliable and accurate structural information about protein-ligand complexes for medicinal chemists that is also suitable for high-throughput.
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.