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Design and Generation of Highly Diverse Fluorinated Fragment Libraries and their Efficient Screening with Improved 19 F NMR Methodology
Author(s) -
Vulpetti Anna,
Dalvit Claudio
Publication year - 2013
Publication title -
chemmedchem
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.817
H-Index - 100
eISSN - 1860-7187
pISSN - 1860-7179
DOI - 10.1002/cmdc.201300351
Subject(s) - chemical space , drug discovery , nuclear magnetic resonance spectroscopy , chembl , combinatorial chemistry , chemistry , small molecule , chemical library , computer science , stereochemistry , biochemistry
Fragment screening performed with 19 F NMR spectroscopy is becoming increasingly popular in drug discovery projects. With this approach, libraries of fluorinated fragments are first screened using the direct‐mode format of the assay. The choice of fluorinated motifs present in the library is fundamental in order to ensure a large coverage of chemical space and local environment of fluorine (LEF). Mono‐ and poly‐fluorinated fragments to be included in the libraries for screening are selected from both in‐house and commercial collections, and those that are ad hoc designed and synthesized. Additional fluorinated motifs to be included in the libraries derive from the fragmentation of compounds in development and launched on the market, and compounds contained in other databases (such as Integrity, PDB and ChEMBL). Complex mixtures of highly diverse fluorine motifs can be rapidly screened and deconvoluted in the same NMR tube with a novel on the fly combined procedure for the identification of the active molecule(s). Issues and problems encountered in the design, generation and screening of diverse fragment libraries of fluorinated compounds with 19 F NMR spectroscopy are analyzed and technical solutions are provided to overcome them. The versatile screening methodology described here can be efficiently applied in laboratories with limited NMR setup and could potentially lead to the increasing role of 19 F NMR in the hit identification and lead optimization phases of drug discovery projects.