CMI Project 1.2.11: New in-silico molecular design methods for improved separations

Principal Researchers

Marilu Perez at Ames Laboratory leads the CMI project "New in-silico molecular design methods for improved separations"

This project intends to enable, for the first time, the deliberate design of organic ligands with predetermined metal ion selectivity. To achieve this objective, the project will develop two connected computational methods, involving machine learning and molecular mechanics that predict absolute log K values for the formation of metal-ligand complexes in aqueous solution to an accuracy of +/- 0.3 log K units. Novel log K predicting software will be implemented within existing HostDesigner code to yield the next generation ligand design software capable of identifying novel ligand compositions with optimal affinity and selectivity for a targeted metal ion species.

See more about HostDesigner and other open source software developed by CMI researchers link