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Combining pharmacophore models derived from DNA-encoded chemical libraries with structure-based exploration to predict Tankyrase 1 inhibitors

Montoya, Alba L ; Glavatskikh, Marta ; Halverson, Brayden J ; Yuen, Lik Hang ; Schüler, Herwig LU orcid ; Kireev, Dmitri and Franzini, Raphael M (2023) In European Journal of Medicinal Chemistry 246. p.114980-114980
Abstract
DNA-encoded chemical libraries (DECLs) interrogate the interactions of a
target of interest with vast numbers of molecules. DECLs hence provide
abundant information about the chemical ligand space for therapeutic
targets, and there is considerable interest in methods for exploiting
DECL screening data to predict novel ligands. Here we introduce one such
approach and demonstrate its feasibility using the cancer-related
poly-(ADP-ribose)transferase tankyrase 1 (TNKS1) as a model target.
First, DECL affinity selections resulted in structurally diverse TNKS1
inhibitors with high potency including compound 2 with an IC50
value of 0.8 nM. Additionally, TNKS1 hits from four... (More)
DNA-encoded chemical libraries (DECLs) interrogate the interactions of a
target of interest with vast numbers of molecules. DECLs hence provide
abundant information about the chemical ligand space for therapeutic
targets, and there is considerable interest in methods for exploiting
DECL screening data to predict novel ligands. Here we introduce one such
approach and demonstrate its feasibility using the cancer-related
poly-(ADP-ribose)transferase tankyrase 1 (TNKS1) as a model target.
First, DECL affinity selections resulted in structurally diverse TNKS1
inhibitors with high potency including compound 2 with an IC50
value of 0.8 nM. Additionally, TNKS1 hits from four DECLs were
translated into pharmacophore models, which were exploited in
combination with docking-based screening to identify TNKS1 ligand
candidates in databases of commercially available compounds. This
computational strategy afforded TNKS1 inhibitors that are outside the
chemical space covered by the DECLs and yielded the drug-like lead
compound 12 with an IC50 value of 22 nM. The
study further provided insights in the reliability of screening data
and the effect of library design on hit compounds. In particular, the
study revealed that while in general DECL screening data are in good
agreement with off-DNA ligand binding, unpredictable interactions of the
DNA-attachment linker with the target protein contribute to the noise
in the affinity selection data. (Less)
Please use this url to cite or link to this publication:
author
; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Small Molecule Libraries/chemistry, Pharmacophore, Tankyrases/metabolism, Ligands, Reproducibility of Results, DNA/metabolism
in
European Journal of Medicinal Chemistry
volume
246
pages
16 pages
publisher
Elsevier Masson SAS
external identifiers
  • pmid:36495630
  • scopus:85145425559
ISSN
0223-5234
DOI
10.1016/j.ejmech.2022.114980
language
English
LU publication?
yes
additional info
Copyright © 2022 Elsevier Masson SAS. All rights reserved.
id
3abf7c74-1dbf-4179-a627-5954071d7dfd
date added to LUP
2023-01-05 12:25:01
date last changed
2024-09-17 22:36:00
@article{3abf7c74-1dbf-4179-a627-5954071d7dfd,
  abstract     = {{DNA-encoded chemical libraries (DECLs) interrogate the interactions of a<br>
 target of interest with vast numbers of molecules. DECLs hence provide <br>
abundant information about the chemical ligand space for therapeutic <br>
targets, and there is considerable interest in methods for exploiting <br>
DECL screening data to predict novel ligands. Here we introduce one such<br>
 approach and demonstrate its feasibility using the cancer-related <br>
poly-(ADP-ribose)transferase tankyrase 1 (TNKS1) as a model target. <br>
First, DECL affinity selections resulted in structurally diverse TNKS1 <br>
inhibitors with high potency including compound <strong>2</strong> with an IC<sub>50</sub><br>
 value of 0.8 nM. Additionally, TNKS1 hits from four DECLs were <br>
translated into pharmacophore models, which were exploited in <br>
combination with docking-based screening to identify TNKS1 ligand <br>
candidates in databases of commercially available compounds. This <br>
computational strategy afforded TNKS1 inhibitors that are outside the <br>
chemical space covered by the DECLs and yielded the drug-like lead <br>
compound <strong>12</strong> with an IC<sub>50</sub> value of 22 nM. The<br>
 study further provided insights in the reliability of screening data <br>
and the effect of library design on hit compounds. In particular, the <br>
study revealed that while in general DECL screening data are in good <br>
agreement with off-DNA ligand binding, unpredictable interactions of the<br>
 DNA-attachment linker with the target protein contribute to the noise <br>
in the affinity selection data.}},
  author       = {{Montoya, Alba L and Glavatskikh, Marta and Halverson, Brayden J and Yuen, Lik Hang and Schüler, Herwig and Kireev, Dmitri and Franzini, Raphael M}},
  issn         = {{0223-5234}},
  keywords     = {{Small Molecule Libraries/chemistry; Pharmacophore; Tankyrases/metabolism; Ligands; Reproducibility of Results; DNA/metabolism}},
  language     = {{eng}},
  month        = {{01}},
  pages        = {{114980--114980}},
  publisher    = {{Elsevier Masson SAS}},
  series       = {{European Journal of Medicinal Chemistry}},
  title        = {{Combining pharmacophore models derived from DNA-encoded chemical libraries with structure-based exploration to predict Tankyrase 1 inhibitors}},
  url          = {{http://dx.doi.org/10.1016/j.ejmech.2022.114980}},
  doi          = {{10.1016/j.ejmech.2022.114980}},
  volume       = {{246}},
  year         = {{2023}},
}