Optimisation of in silico techniques for homogeneous transition metal based catalysis research

Abstract

Many drugs cannot be made without homogeneous catalysis. To increase the yield of drug synthesis, the search for new catalysts continues. Computational catalysis is becoming a more prominent tool since it en- ables to screen many catalysts without performing (m)any laboratory experiments. In this research a com- putational workflow has been created to calculate both electronic (e.g. dipole, ionisation potential, nucle- ophilicity, etc.) and steric (bite angle, buried volume, cone angle, etc.) molecular descriptors. The structures were automatically created starting from the metal centre, some bidentate phosphorus ligands, auxiliary lig- ands, and the substrate. An in-house computational workflow, MACE, is used for for high-throughput gen- eration of structures from the starting bidentate phosphorus ligands, by generating stereo-isomers around to metal centre. Afterwards small substituents (H, CH3, Ph, etc.) are changed by ChemSpaX increasing the number of structures combinatorically. To reduce the computational cost of this workflow, it has been re- searched whether properties of the octahedral geometry could be predicted using properties from a simple model structure containing only the metal centre and the bidentate phosphorus ligand. This model structure did not show a correlation except for the electronic energy and the solvent accessible surface area, which are both primarily influenced by the number of electrons. Other correlations may be found if some other descriptors were calculated which where excluded now, like the HOMO-LUMO gap and the substrate bind- ing energy. The workflow could be extended to machine learning and improved by including symmetry and optical isomerism.