ArticleAnalytical chemistry2024
Accelerated Screening of Protein-Ligand Interactions via Parallel
Article in Analytical chemistry, 2024. 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.
- Parallelized 61-Sample Inhibition Screening Accelerated bySmall methods · 2026Article
- Article
- Protein recognition methods for diagnostics and therapy.BBA advances · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In drug discovery, ligands are sought that modulate the (mal-)function of medicinally relevant target proteins. In order to develop new drugs, typically a multitude of potential ligands are initially screened for binding and subsequently characterized for their affinity. Nuclear magnetic resonance (NMR) is a well-established and highly sensitive technology for characterizing such interactions. However, it has limited throughput, because only one sample can be measured at a time. In contrast, magnetic resonance imaging (MRI) is inherently parallel and MR parameters can conveniently be encoded in its images, potentially offering increased sample throughput. We explore this application using a custom-built 9-fold sample holder and a
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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.