Efficient Screening of Target‐Specific Selected Compounds in Mixtures by 19F NMR Binding Assay with Predicted 19F NMR Chemical Shifts. (12th May 2022)

• Record Type: Journal Article
• Authors: Vulpetti, Anna; Lingel, Andreas; Dalvit, Claudio; Schiering, Nikolaus; Oberer, Lukas; Henry, Christelle; Lu, Yipin
• Is Part Of: ChemMedChem. Volume 17:Number 13(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-05-12
• Subjects: Machine learning -- 19F NMR screening -- 19F NMR chemical shift -- Hit finding -- Fragment based screening; Pharmaceutical chemistry -- Periodicals; 615.19005
• DOI: 10.1002/cmdc.202200163
• Languages: English
• ISSNs: 1860-7179

Abstract

Abstract: Ligand‐based 19 F NMR screening is a highly effective and well‐established hit‐finding approach. The high sensitivity to protein binding makes it particularly suitable for fragment screening. Different criteria can be considered for generating fluorinated fragment libraries. One common strategy is to assemble a large, diverse, well‐designed and characterized fragment library which is screened in mixtures, generated based on experimental 19 F NMR chemical shifts. Here, we introduce a complementary knowledge‐based 19 F NMR screening approach, named 19 Focused screening, enabling the efficient screening of putative active molecules selected by computational hit finding methodologies, in mixtures assembled and on‐the‐fly deconvoluted based on predicted 19 F NMR chemical shifts. In this study, we developed a novel approach, named LEFshift, for 19 F NMR chemical shift prediction using rooted topological fluorine torsion fingerprints in combination with a random forest machine learning method. A demonstration of this approach to a real test case is reported. Abstract : The 19 Focused screening is a novel hit‐finding approach that efficiently combines 19 F NMR binding assay of mixtures with compounds selection by virtual screening. The method promises to be very valuable for accelerating hit identification and optimization for challenging targets.