Data Science-Driven Discovery of Optimal Conditions and a Condition-Selection Model for the Chan-Lam Coupling of Primary Sulfonamides.

ABSTRACT: Secondary N-arylsulfonamides are common in pharmaceutical compounds owing to their valuable physicochemical properties. Direct N-arylation of primary sulfonamides presents a modular approach to this scaffold but remains a challenging disconnection for transition metal-catalyzed cross coupling broadly, including the Chan-Lam (CL) coupling of nucleophiles with (hetero)aryl boronic acids. Although the CL coupling reaction typically operates under mild conditions, it is also highly substrate-dependent and prone to over-arylation, limiting its generality and predictivity. To address these gaps, we employed data science tools in tandem with high-throughput experimentation to study and model the CL N-arylation of primary sulfonamides. To minimize bias in training set design,

SUBMITTER: Gandhi SS 

PROVIDER: S-EPMC12574657 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature