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Diaryliodonium salts are well-known to transfer an aryl group to carbon and heteroatom nucleophiles, and in some cases a base is required [1]. However, transition metal catalysts and supporting ligands are not needed. Moreover, reactions conducted with diaryliodonium salts are operationally simple because they are non-toxic and are not sensitive to air or moisture. Therefore diaryliodonium salts offer an important alternative to metal-catalyzed arylation reactions. Despite these attractive characteristics, a major obstacle to their adoption in chemical synthesis and discovery chemistry has been commercial availability.
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It is proved that a diverse compound library is the most successful and straightforward starting point to find new leads. Moreover, it is the best way to enhance your research compound collections by adding new substances with different chemotypes.
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The OTAVA G9a Targeted Library comprises 561 carefully curated small molecules aimed at modulating the activity of histone methyltransferase G9a (EHMT2)—a master regulator of transcriptional repression through histone H3 lysine 9 (H3K9) methylation. This collection provides a powerful resource for researchers exploring epigenetics-driven mechanisms in cancer, neurodegeneration, inflammation, and stem cell reprogramming.
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Our Halogen-Enriched Fragment Library comprises 708 brominated fragments that can explore binding sites for favorable halogen bond interactions to identify unique binding modes that are complementary to those obtained from classical fragment-based screening.
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In recent years, structured RNAs have become tractable drug targets, enabling the discovery of selective modulators for riboswitches, long noncoding RNAs, G-quadruplexes, and RNA–protein complexes.
Breakthrough advances in library design, screening methodologies, and AI-based prioritization have expanded the scope of RNA-targeted drug discovery (Kovachka et al., Nat Rev Chem 2024; Lundquist et al., SLAS Discovery 2025; Morishita, ChemMedChem 2022; Momentum Bio, 2024).
Modern RNA-focused screening now combines:
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SPR/BLI for kinetic profiling and specificity ranking,
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AI-guided virtual enrichment to prioritize compounds with high “RNA-likeness” before experimental testing (Graff et al., Chem Sci 2020; Cao et al., Nat Mach Intell 2023).
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