Development of ACE and VIRTUAL CHEMIST

    The catalyst discovery process as practised now is time consuming , expensive, and often serendipitous. Computational prediction would enable the chemists to reduce the cost and accelerate the lead generation and optimization steps. Until recently, conventionally available computer power has been insufficient to tackle the combinatorial problem of molecular design through virtual screening. This computational power is now available and the time is ripe for the development of more predictive methods. Indeed, the use of computer-aided molecular design methods in the field of drug development is well established but focused almost exclusively on ground state structures.
    Meanwhile, few groups have focused on the development of rapid and predictive tools for de novo design of asymmetric organic reactions which require the more challenging and complex study of flexible transition state (TS) structures. Apart from the highly computer time-intensive density functional theory (DFT), ab initio and semi-empirical methods, which are restricted to small systems, little attention has been directed to TS structure analysis by fast and accurate in silico screening methods. In particular, few predictive molecular mechanics-based models have been designed to address TS structures.
    To this end, we have built a simple yet accurate strategy for describing transition states using molecular mechanics (MM) methods and a genetic algorithm to account for flexibility of the TS structures and implemented it into an independent program Ace, the workhorse of the computational platform Virtual Chemist, specifically designed for asymmetric catalyst discovery projects.
    Designed by chemists for chemists, Virtual Chemist allows users fast, accurate and user-friendly computations to design new catalysts for a variety of reactions. Our synthetic chemists are in continuous collaboration with the computational chemists developing these tools: the newly designed and computationally-tested catalysts are synthesized, and their reactivity and enantioselectivity determined. These results allow us to continuously improve the platform and to expand its reaction range even further.
Keywords : · Molecular Mechanics (MM) · Catalyst design and synthesis · Virtual Chemist · Ace · Enantioselectivity
Key people involved in the project : Mihai Burai Patrascu (PhD '20, PDF), Sharon Pinus (graduate student), Josh Pottel (PhD '15), Chris Corbeil (PhD '08)
Key publications related to the project : here