Guiding Chemical Synthesis: Computational Prediction of the Regioselectivity of CH Functionalization

TL;DR

This paper introduces RegioSQM, a computational tool designed to predict the regioselectivity of CH functionalization reactions, aiming to assist synthetic chemists in optimizing chemical synthesis processes efficiently.

Contribution

The paper presents a new semiempirical quantum chemistry-based method and web interface for predicting regioselectivity in CH functionalization, making advanced computational predictions accessible to non-experts.

Findings

RegioSQM accurately predicts reactive CH bonds in various reactions.

The tool improves efficiency in drug discovery synthesis planning.

Experimental validation confirms the method's practical utility.

Abstract

We will develop a computational method (RegioSQM) for predicting the regioselectivity of CH functionalization reactions that can be used by synthetic chemists who are not experts in computational chemistry through a simple web interface (regiosqm.org). CH functionalization, i.e. replacing the hydrogen atom in a CH bond with another atom or molecule, is arguably single most promising technique for increasing the efficiency of chemical synthesis, but there are no generally applicable predictive tools that predict which CH bond is most reactive. RegioSQM uses semiempirical quantum chemistry methods to predict relative stabilities of reaction intermediates which correlates with reaction rate and our goal is to determine which quantum method and intermediate give the best result for each reaction type. Finally, we will experimentally demonstrate how RegioSQM can be used to make the chemical synthesis part of drug discovery more efficient.