A Comprehensive <sup>19</sup> F NMR Framework for Fragment‐Based Drug Discovery: The Validated Screening Library OpenFL600 and Efficient Affinity Ranking by CSAR

ABSTRACT Small‐molecule drug discovery relies on the identification of initial chemical starting points, or screening hits, and their subsequent optimization for potency and selectivity. Fragment‐based drug discovery (FBDD), particularly through NMR screening, is a powerful method for hit identification due to its high sensitivity. Here, we present the design and validation of a non‐proprietary NMR screening library (OpenFL600) capable of probing diverse binding pockets, as demonstrated for RNA, G protein‐coupled receptors (GPCRs), kinases, protein–protein interactions, and proteases. Our screening campaigns yielded specific hits for 11 respective targets and therefore valuable structure–activity relationship (SAR). The absence of promiscuous binders confirms the high quality of the OpenFL600 library, a result of both careful fragment selection and rigorous molecular quality control. Subsequent affinity ranking of identified hits—typically a laborious task—is considerably streamlined by fast chemical shift anisotropy (CSA) Affinity Ranking (CSAR). CSAR is enabled by providing CSA values for each fragment. This creates a highly efficient workflow, from initial hit screening to the prioritization of leads. In summary, we provide a comprehensive framework for NMR‐based screening across diverse target classes, assessing their druggability, and enabling efficient affinity ranking to facilitate hit‐to‐lead progression.

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Publication Details

Journal
Angewandte Chemie International Edition
Published
2026-07-23
DOI
https://doi.org/10.1002/anie.9964915
Primary Topic
Computational Drug Discovery Methods
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article
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article

A Comprehensive 19 F NMR Framework for Fragment‐Based Drug Discovery: The Validated Screening Library OpenFL600 and Efficient Affinity Ranking by CSAR

Giacomo Padroni, Sven Brüschweiler, Gerald Platzer, Antoine Cléry et al.
Angewandte Chemie International Edition
Computational Drug Discovery Methods
article

A Comprehensive 19 F NMR Framework for Fragment‐Based Drug Discovery: The Validated Screening Library OpenFL600 and Efficient Affinity Ranking by CSAR

Giacomo Padroni, Sven Brüschweiler, Gerald Platzer, Antoine Cléry, Christina Jordan, Gabriela R. Stadler, Simon Rüdisser, Katharina M. Siess, Sarah Skibinski, Alvar D. Gossert, Robert Konrat, Frédéric H.‐T. Allain, Daria Barbash, Timo T. Stühlinger, Sarah Kratzwald, Nils Lorz, M. Ruckstuhl
article en

Abstract

ABSTRACT Small‐molecule drug discovery relies on the identification of initial chemical starting points, or screening hits, and their subsequent optimization for potency and selectivity. Fragment‐based drug discovery (FBDD), particularly through NMR screening, is a powerful method for hit identification due to its high sensitivity. Here, we present the design and validation of a non‐proprietary NMR screening library (OpenFL600) capable of probing diverse binding pockets, as demonstrated for RNA, G protein‐coupled receptors (GPCRs), kinases, protein–protein interactions, and proteases. Our screening campaigns yielded specific hits for 11 respective targets and therefore valuable structure–activity relationship (SAR). The absence of promiscuous binders confirms the high quality of the OpenFL600 library, a result of both careful fragment selection and rigorous molecular quality control. Subsequent affinity ranking of identified hits—typically a laborious task—is considerably streamlined by fast chemical shift anisotropy (CSA) Affinity Ranking (CSAR). CSAR is enabled by providing CSA values for each fragment. This creates a highly efficient workflow, from initial hit screening to the prioritization of leads. In summary, we provide a comprehensive framework for NMR‐based screening across diverse target classes, assessing their druggability, and enabling efficient affinity ranking to facilitate hit‐to‐lead progression.

Angewandte Chemie International Edition
University of Vienna (AT), Healthcare Improvement Scotland (GB), ETH Zurich (CH), Magna (Austria) (AT), CIC bioGUNE (ES), Biotest (Austria) (AT)
Openalex Percentile: Top 7%
Computational Drug Discovery Methods
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