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A Receptor‐Guided Design Strategy for Ligand Identification
Author(s) -
Rosenthal Malte,
Pfeiffer Franziska,
Mayer Günter
Publication year - 2019
Publication title -
angewandte chemie international edition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.831
H-Index - 550
eISSN - 1521-3773
pISSN - 1433-7851
DOI - 10.1002/anie.201903479
Subject(s) - computational biology , identification (biology) , nanotechnology , selection (genetic algorithm) , ligand (biochemistry) , computer science , combinatorial chemistry , chemistry , receptor , biology , biochemistry , materials science , artificial intelligence , botany
Biomedical sciences require effective tools to manipulate, detect, and study biological phenomena. Oligo(deoxy)nucleotide ligands represent such tools, but the current strategies to generate them are restricted. Their limited availability is insufficient to address the broad range of targets related to biomedical research. Exemplified by targeting the hydrophobic molecule (−)‐Δ 9 ‐tetrahydrocannabinol (THC), we report a receptor‐guided design (RGD) strategy to generate chemically modified oligodeoxynucleotide libraries for the tailored selection of clickmers.