Prediction of Stereochemistry using Q2MM.

Area of Science:

• Computational chemistry
• Catalysis
• Organic synthesis

Background:

• Traditional ligand screening for asymmetric catalysis is experimentally intensive, time-consuming, and resource-demanding.
• Predicting stereoselectivity computationally requires efficient conformational sampling of transition states.
• Existing electronic structure calculations are too slow for rapid screening.

Purpose of the Study:

• To develop and validate a computational method for accurate and fast prediction of stereoselectivity in transition metal-catalyzed reactions.
• To enable rapid virtual screening of ligand libraries, reducing experimental effort.
• To provide insights into the mechanisms of stereoselectivity.

Main Methods:

• Development of Quantum-guided Molecular Mechanics (Q2MM) for automated generation of reaction-specific transition state force fields (TSFFs).
• Utilizing Hessian matrix in Q2MM parametrization to prevent overfitting of TSFFs.
• Fast conformational sampling of TSFFs using Monte Carlo simulations and Boltzmann-averaged energy calculations for stereoselectivity prediction.

Main Results:

• Q2MM successfully generated accurate TSFFs for various transition metal-catalyzed reactions, including Pd-catalyzed allylation, OsO4-catalyzed dihydroxylation, and Rh/Ru-catalyzed hydrogenations.
• Calculated enantiomeric excess (ee) values show strong correlation (0.8-0.9) with experimental data across diverse substrate-ligand combinations.
• The method achieves approximately 80% accuracy in predicting suitable ligands for specific substrates.

Conclusions:

• Q2MM offers a powerful and efficient approach for virtual ligand screening in asymmetric catalysis.
• This computational strategy significantly accelerates the discovery of effective ligands, focusing experimental efforts.
• Q2MM-derived TSFFs provide a valuable tool for both academic and industrial research in catalysis.