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Dynamic Combinatorial Chemistry: A New Methodology Comes of Age
Author(s) -
Frei Priska,
Hevey Rachel,
Ernst Beat
Publication year - 2019
Publication title -
chemistry – a european journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.687
H-Index - 242
eISSN - 1521-3765
pISSN - 0947-6539
DOI - 10.1002/chem.201803365
Subject(s) - ambiguity , computer science , chemistry , macromolecule , identification (biology) , biological system , computational biology , combinatorial chemistry , biology , biochemistry , programming language , botany
Dynamic combinatorial chemistry (DCC) has repeatedly proven to be an effective approach to generate directed ligand libraries for macromolecular targets. In the absence of an external stimulus, a dynamic library forms from reversibly reacting building blocks and reaches a stable thermodynamic equilibrium. However, upon addition of a macromolecular host which can bind and stabilize certain components of the library, the equilibrium composition changes and induces an evolution‐like selection and enrichment of high‐affinity ligands. A valuable application of this so‐called target‐directed DCC (tdDCC) is the identification of potent ligands for pharmacologically relevant targets. Over time, the term tdDCC has been applied to describe a number of different experimental setups, leading to some ambiguity concerning its definition. This article systematically classifies known procedures for tdDCC and related approaches, with a special focus on the methods used for analysis and evaluation of experiments.