Catalytic Control in Cyclizations: From Computational Mechanistic Understanding to Selectivity Prediction

Area of Science:

• Organic Chemistry
• Computational Chemistry
• Catalysis

Background:

• Cyclic molecules are fundamental in organic synthesis, with cyclization reactions being key to their formation.
• Predictive models for chemical reactivity, such as Baldwin's rules and Woodward-Hoffmann rules, have been developed based on cyclization reactions.
• Catalytic mechanisms and selectivity in ring formation are areas of active research, benefiting from computational and experimental approaches.

Purpose of the Study:

• To utilize quantum-chemical calculations to understand the mechanisms of selective cyclization reactions.
• To develop novel catalysts for highly selective cyclization reactions, particularly asymmetric cycloisomerizations.
• To explore the mechanistic pathways of various cyclization reactions, including cation-directed 5-endo cyclizations and transition-metal-catalyzed reactions.

Main Methods:

• Quantum-chemical calculations were employed to study reaction mechanisms and transition structures.
• Computational predictions were used to guide the design and development of new catalysts.
• Case studies from laboratory experiments were integrated with computational findings.

Main Results:

• Computational analysis revealed polar mechanisms for cation-directed 5-endo ring-closing reactions, contradicting electrocyclic notions.
• Subtle substrate effects were identified as crucial for achieving selectivity in 5-endo-trig ring closures.
• The mode of action of chiral ammonium counterions was elucidated through transition state analysis, involving nonclassical hydrogen bonds.
• Computational insights led to the development of new catalysts for enantioselective cycloisomerizations, including those for intramolecular Michael additions and [5 + 2] cycloisomerizations of ynamides.
• New phosphoramidite ligands were designed for double-stereodifferentiating cycloisomerizations.

Conclusions:

• Quantum-chemical calculations provide deep mechanistic understanding of catalytic cyclizations.
• Computational predictions accelerate the discovery and development of catalysts for highly selective cyclization reactions.
• This work demonstrates the power of integrating computational and experimental methods to advance organic synthesis and catalysis.