Computational Design of Metal Ion Sequestering Agents

Abstract

Organic ligands that exhibit a high degree of metal ion recognition are essential precursors for developing separation processes and sensors for metal ions. Since the beginning of the nuclear era, much research has focused on discovering ligands that target specific radionuclides. Members of the Group 1A and 2A cations (e.g., Cs, Sr, Ra) and the f-block metals (actinides and lanthanides) are of primary concern to the U.S. Department of Energy (DOE). Although there has been some success in identifying ligand architectures that exhibit a degree of metal ion recognition, the ability to control binding affinity and selectivity remains a significant challenge. The traditional approach for discovering such ligands has involved lengthy programs of organic synthesis and testing that, in the absence of reliable methods for screening compounds before synthesis, have resulted in much wasted research effort. This project seeks to enhance and strengthen the traditional approach through computer-aided design of new and improved host molecules. Accurate electronic structure calculations are coupled with experimental data to provide fundamental information about ligand structure and the nature of metal-donor group interactions (design criteria). This fundamental information then is used in a molecular mechanics model (MM3) that helps us rapidly screen proposed ligand architectures and select the best members from a set of potential candidates. By using combinatorial methods, molecule building software has been developed that generates large numbers of candidate architectures for a given set of donor groups. The specific objectives of this project are as follows: (1) Further understand the structural and energetic aspects of individual donor group- metal ion interactions and incorporate this information within the framework of MM3. (2) Further develop and evaluate approaches for correlating ligand structure with reactivity toward metal ions, in other words, screening capability. (3) Use molecule structure building software to generate large numbers of candidate ligand architectures for given sets of donor groups. (4) Screen candidates and identify ligand architectures that will exhibit enhanced metal ion recognition. These new capabilities are being applied to ligand systems identified under other DOE sponsored projects in which studies have suggested that modifying existing architectures will lead to dramatic enhancements in metal ion binding affinity and selectivity. With this in mind, we are collaborating with researchers at the University of New Mexico, University of California at Berkeley, University of Oregon, and Oak Ridge National Laboratory to obtain experimental validation of the predicted new ligand structures. Successful completion of this study will yield molecular-level insight into the role that ligand architecture plays in controlling metal ion complexation and will provide a computational approach to ligand design.