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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...

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Autores principales: Vaid, Tasneem M., Demissie, Robel, Kwon, Youngjin, Tran, Thao, Moon, Hyung-Geun, Villegas, José A., Park, Gye Young, Johnson, Michael E., Lee, Hyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
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.
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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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