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Quantitative Assessment of Affinity Selection Performance by Using DNA‐Encoded Chemical Libraries
Author(s) -
Sannino Alessandro,
Gabriele Elena,
Bigatti Martina,
Mulatto Sara,
Piazzi Jacopo,
Scheuermann Jörg,
Neri Dario,
Donckele Etienne J.,
Samain Florent
Publication year - 2019
Publication title -
chembiochem
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.05
H-Index - 126
eISSN - 1439-7633
pISSN - 1439-4227
DOI - 10.1002/cbic.201800766
Subject(s) - dna , computational biology , combinatorial chemistry , selection (genetic algorithm) , genomic library , chemistry , selectivity , dna sequencing , biology , biochemistry , computer science , base sequence , artificial intelligence , catalysis
Abstract DNA‐encoded chemical libraries are often used for the discovery of ligands against protein targets of interest. These large collections of DNA‐barcoded chemical compounds are typically screened by using affinity capture methodologies followed by PCR amplification and DNA sequencing procedures. However, the performance of individual steps in the selection procedures has been scarcely investigated, so far. Herein, the quantitative analysis of selection experiments, by using three ligands with different affinity to carbonic anhydrase IX as model compounds, is described. In the first set of experiments, quantitative PCR (qPCR) procedures are used to evaluate the recovery and selectivity for affinity capture procedures performed on different solid‐phase supports, which are commonly used for library screening. In the second step, both qPCR and analysis of DNA sequencing results are used to assess the recovery and selectivity of individual carbonic anhydrase IX ligands in a library, containing 360 000 compounds. Collectively, this study reveals that selection procedures can be efficient for ligands with sub‐micromolar dissociation constants to the target protein of interest, but also that selection performance dramatically drops if 10 4 copies per library member are used as the input.