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Enabling Efficient Late‐Stage Functionalization of Drug‐Like Molecules with LC‐MS and Reaction‐Driven Data Processing
Author(s) -
Yao Huifang,
Liu Yong,
Tyagarajan Sriram,
Streckfuss Eric,
Reibarkh Mikhail,
Chen Kuanchang,
Zamora Ismael,
Fontaine Fabien,
Goracci Laura,
Helmy Roy,
Bateman Kevin P.,
Krska Shane W.
Publication year - 2017
Publication title -
european journal of organic chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.825
H-Index - 155
eISSN - 1099-0690
pISSN - 1434-193X
DOI - 10.1002/ejoc.201701573
Subject(s) - chemistry , surface modification , combinatorial chemistry , drug discovery , workflow , biochemical engineering , nanotechnology , computer science , biochemistry , database , engineering , materials science
Late‐stage functionalization (LSF) through C–H functionalization of drug leads is a powerful synthetic strategy for drug discovery. A key challenge in LSF is that multiple regioisomeric products are often generated, which requires slow and laborious product isolation and structure confirmation steps. To address this, an analytical approach using LC‐HR‐MS/MS coupled with automated chemically aware data processing was developed. Using this method to analyse reaction screening arrays based on three common C–H functionalization chemistries with a set of marketed drugs, the relative amount and localization of chemical modification could be determined for each regioisomeric product generated in the screening. This approach allows one to construct a workflow in which the various regioisomeric products of a given transformation are triaged according to their site of modification, allowing downstream isolation and structure elucidation efforts to focus on those analogues of highest interest, leading to an overall increase in productivity of the LSF strategy.

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