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CHF6333   Click here for help

GtoPdb Ligand ID: 14269

Synonyms: CHF 6333 | CHF-6333 | Example 47 (cation) [US9828382] [1]
Compound class: Synthetic organic
Comment: CHF6333 is a lung-restricted (by inhalation) neutrophil elastase (NE) inhibitor [2]. It is formulated as a salt (e.g., as the methanesulfonate), and strictly this entry represents the CHF6333 cation. Local delivery to the lung is intended to minimise systemic exposure and off-target toxicity. NE inhibition is proposed to rebalance elevated NE activity that underlies disruption of vascular endothelium, vascular permeability and tissue damage in chronic inflammatory lung disease.
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Ligand Activity Visualisation Charts

These are box plot that provide a unique visualisation, summarising all the activity data for a ligand taken from ChEMBL and GtoPdb across multiple targets and species. Click on a plot to see the median, interquartile range, low and high data points. A value of zero indicates that no data are available. A separate chart is created for each target, and where possible the algorithm tries to merge ChEMBL and GtoPdb targets by matching them on name and UniProt accession, for each available species. However, please note that inconsistency in naming of targets may lead to data for the same target being reported across multiple charts.

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View interactive charts of activity data across species
2D Structure
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2D Structure

An image of the ligand's 2D structure. For small molecules with SMILES these are drawn using the NCI/CADD Chemical Identifier Resolver. Click on the image to access the chemical structure search tool with the ligand pre-loaded in the structure editor. For other types of ligands, e.g. longer nucleotides and peptides, a manually drawn representation of the molecule may be provided.

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Physico-chemical Properties
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Physico-chemical Properties

Calculated molecular properties are available for small molecules and natural products (not peptides). Properties were generated using the Chemistry Development Kit (CDK) (Willighagen EL et al. Journal of Cheminformatics vol. 9:33. 2017, doi:10.1186/s13321-017-0220-4; https://cdk.github.io/). All properties were selected to enable the prediction of the Lipinski Rule-of-Five profile or ‘druglikeness’ for each ligand. For more info on each category see the help pages.

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Hydrogen bond acceptors 8
Hydrogen bond donors 1
Rotatable bonds 8
Topological polar surface area 98.03
Molecular weight 541.55
XLogP 2.02
No. Lipinski's rules broken 1

Generated using the Chemistry Development Kit (CDK) (Willighagen EL et al. Journal of Cheminformatics vol. 9:33. 2017, doi:10.1186/s13321-017-0220-4; https://cdk.github.io/)
SMILES / InChI / InChIKey
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SMILES / InChI / InChIKey

SMILES (Simplified Molecular Input Line Entry Specification) A specification for unambiguously describing the structure of chemical molecules using short ASCII strings. Canonical SMILES specify a unique representation of the 2D structure without chiral or isotopic specifications. Isomeric SMILES include chiral specification and isotopes.

Standard InChI (IUPAC International Chemical Identifier) and InChIKey InChI is a non-proprietary, standard, textual identifier for chemical substances designed to facilitate linking of information and database searching. An InChIKey is a simplified version of a full InChI, designed for easier web searching.

Generated using the Chemistry Development Kit (CDK) (Willighagen EL et al. Journal of Cheminformatics vol. 9:33. 2017, doi:10.1186/s13321-017-0220-4; https://cdk.github.io/)

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Canonical SMILES CC1=C([C@@H](C2=CC=C(C=C2CC[N+](C)(C)C)C#N)N3C(=NNC3=O)N1C4=CC(=CC=C4)C(F)(F)F)C(=O)OC
Isomeric SMILES CC1=C([C@H](N2C(=O)NN=C2N1C3=CC=CC(=C3)C(F)(F)F)C4=C(C=C(C=C4)C#N)CC[N+](C)(C)C)C(=O)OC
InChI InChI=1S/C27H27F3N6O3/c1-16-22(24(37)39-5)23(21-10-9-17(15-31)13-18(21)11-12-36(2,3)4)35-25(32-33-26(35)38)34(16)20-8-6-7-19(14-20)27(28,29)30/h6-10,13-14,23H,11-12H2,1-5H3/p+1/t23-/m1/s1
InChI Key IHTRPSMRGYWUIM-HSZRJFAPSA-O

Generated using the Chemistry Development Kit (CDK) (Willighagen EL et al. Journal of Cheminformatics vol. 9:33. 2017, doi:10.1186/s13321-017-0220-4; https://cdk.github.io/)

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