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Optimization of G‐Quadruplex Ligands through a SAR Study Combining Parallel Synthesis and Screening of Cationic Bis(acylhydrazones)
Author(s) -
Reznichenko Oksana,
Leclercq Denis,
Franco Pinto Jaime,
Mouawad Liliane,
Gabelica Valérie,
Granzhan Anton
Publication year - 2023
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.202202427
Subject(s) - combinatorial chemistry , chemistry , g quadruplex , cationic polymerization , nucleic acid , guanine , drug discovery , dna , computational biology , biology , biochemistry , nucleotide , organic chemistry , gene
Abstract G‐quadruplexes (G4s), secondary structures adopted by guanine‐rich DNA and RNA sequences, are implicated in numerous biological processes and have been suggested as potential drug targets. Accordingly, there is an increasing interest in developing high‐throughput methods that allow the generation of congeneric series of G4‐targeting molecules (“ligands”) and investigating their interactions with the targets. We have developed an operationally simple method of parallel synthesis to generate “ready‐to‐screen” libraries of cationic acylhydrazones, a motif that we have previously identified as a promising scaffold for potent, biologically active G4 ligands. Combined with well‐established screening techniques, such as fluorescence melting, this method enables the rapid synthesis and screening of combinatorial libraries of potential G4 ligands. Following this protocol, we synthesized a combinatorial library of 90 bis(acylhydrazones) and screened it against five different nucleic acid structures. This way, we were able to analyze the structure–activity relationships within this series of G4 ligands, and identified three novel promising ligands whose interactions with G4‐DNAs of different topologies were studied in detail by a combination of several biophysical techniques, including native mass spectrometry, and molecular modeling.