ArticleACS omega2023
Synergistic Inhibition Guided Fragment-Linking Strategy and Quantitative Structure-Property Relationship Modeling To Design Inhalable Therapeutics for Asthma Targeting CSF1R.
Article in ACS omega, 2023. 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
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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
1 citing paper in PubMed, 1 citations in OpenAlex.
- H3K18 lactylation promotes allergic airway inflammation in asthma via a CSF1/CSF1R/MAPK autocrine axis.Respiratory research · 2026Article
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
The colony-stimulating factor-1 receptor (CSF1R) is a tyrosine-protein kinase that is a potential target for asthma therapeutics. We have applied a fragment-lead combination approach to identify small fragments that act synergistically with GW2580, a known inhibitor of CSF1R. Two fragment libraries were screened in combination with GW2580 by surface plasmon resonance (SPR). Binding affinity measurements confirmed that thirteen fragments bind specifically to the CSF1R, and a kinase activity assay further validated the inhibitory effect of these fragments. Several fragment compounds enhanced the inhibitory activity of the lead inhibitor. Computational solvent mapping, molecular docking, and modeling studies suggest that some of these fragments bind adjacent to the binding site of the lead inhibitor and further stabilize the inhibitor-bound state. Modeling results guided the computational fragment-linking approach to design potential next-generation compounds. The inhalability of these proposed compounds was predicted using quantitative structure-property relationships (QSPR) modeling based on an analysis of 71 drugs currently on the market. This work provides new insights into the development of inhalable small molecule therapeutics for asthma.
Identifiers
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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.