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Synergistic Inhibition Guided Fragment-Linking Strategy and Quantitative Structure–Property Relationship Modeling To Design Inhalable Therapeutics for Asthma Targeting CSF1R
[Image: see text] 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 f...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10268011/ https://www.ncbi.nlm.nih.gov/pubmed/37323402 http://dx.doi.org/10.1021/acsomega.3c00803 |
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author | Vaid, Tasneem M. Demissie, Robel Kwon, Youngjin Tran, Thao Moon, Hyung-Geun Villegas, José A. Park, Gye Young Johnson, Michael E. Lee, Hyun |
author_facet | Vaid, Tasneem M. Demissie, Robel Kwon, Youngjin Tran, Thao Moon, Hyung-Geun Villegas, José A. Park, Gye Young Johnson, Michael E. Lee, Hyun |
author_sort | Vaid, Tasneem M. |
collection | PubMed |
description | [Image: see text] 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. |
format | Online Article Text |
id | pubmed-10268011 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-102680112023-06-15 Synergistic Inhibition Guided Fragment-Linking Strategy and Quantitative Structure–Property Relationship Modeling To Design Inhalable Therapeutics for Asthma Targeting CSF1R Vaid, Tasneem M. Demissie, Robel Kwon, Youngjin Tran, Thao Moon, Hyung-Geun Villegas, José A. Park, Gye Young Johnson, Michael E. Lee, Hyun ACS Omega [Image: see text] 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. American Chemical Society 2023-06-01 /pmc/articles/PMC10268011/ /pubmed/37323402 http://dx.doi.org/10.1021/acsomega.3c00803 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Vaid, Tasneem M. Demissie, Robel Kwon, Youngjin Tran, Thao Moon, Hyung-Geun Villegas, José A. Park, Gye Young Johnson, Michael E. Lee, Hyun Synergistic Inhibition Guided Fragment-Linking Strategy and Quantitative Structure–Property Relationship Modeling To Design Inhalable Therapeutics for Asthma Targeting CSF1R |
title | Synergistic Inhibition
Guided Fragment-Linking Strategy
and Quantitative Structure–Property Relationship Modeling To
Design Inhalable Therapeutics for Asthma Targeting CSF1R |
title_full | Synergistic Inhibition
Guided Fragment-Linking Strategy
and Quantitative Structure–Property Relationship Modeling To
Design Inhalable Therapeutics for Asthma Targeting CSF1R |
title_fullStr | Synergistic Inhibition
Guided Fragment-Linking Strategy
and Quantitative Structure–Property Relationship Modeling To
Design Inhalable Therapeutics for Asthma Targeting CSF1R |
title_full_unstemmed | Synergistic Inhibition
Guided Fragment-Linking Strategy
and Quantitative Structure–Property Relationship Modeling To
Design Inhalable Therapeutics for Asthma Targeting CSF1R |
title_short | Synergistic Inhibition
Guided Fragment-Linking Strategy
and Quantitative Structure–Property Relationship Modeling To
Design Inhalable Therapeutics for Asthma Targeting CSF1R |
title_sort | synergistic inhibition
guided fragment-linking strategy
and quantitative structure–property relationship modeling to
design inhalable therapeutics for asthma targeting csf1r |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10268011/ https://www.ncbi.nlm.nih.gov/pubmed/37323402 http://dx.doi.org/10.1021/acsomega.3c00803 |
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