Quantifying and Designing for Electrostatic Preorganization in Enzymes

University Of California-Los Angeles, Los Angeles CA

Investigators

Abstract

Enzymes are essential protein molecules that facilitate or catalyze the chemical reactions required for life in all organisms. With this award, the Chemistry of Life Processes Program in the Chemistry Division is funding Dr. Anastassia Alexandrova from the University of California, Los Angeles, and Dr. Mark Eberhart from the Colorado School of Mines to investigate how the entirety of the protein molecule, consisting of thousands or even tens of thousands of atoms, creates local electric fields that allow enzymes to function as highly efficient and specific catalysts. This effect at the enzyme's active site, called electrostatic preorganization, is detected through quantum mechanical tools. The understanding of electrostatic preorganization and the development of these quantum mechanical tools are applied to engineer artificial enzymes with enhanced catalytic functions. The resulting artificial enzymes are potentially important in disease prevention, industrial production of chemicals, and environmental remediation. In addition, the project promotes professional development and training of high school science teachers through an initiative called "See the chemical bond". This initiative uses visual and quantum mechanically enabled techniques in a classroom setting to give substance to the important though often poorly understood concept of chemical bonds. This proposal develops quantum-mechanically rigorous computational techniques to probe electrostatic preorganization, and assesses its effect on the proficiency of both natural and artificial enzymes. An extension of the Quantum Theory of Atoms in Molecules (QTAIM) in conjunction with dynamics simulations will be developed to determine the perturbative influence of the full protein structure to the charge density (rho) in an enzyme's active site. The directed evolution of artificial enzymes are followed using these probes, while interrogating the progression of preorganization. These studies detect the extent to which enzymes evolve toward improved long-range electrostatics. The insight resulting from these computational investigations allow integration of preorganization into enzyme design by strategically improving electrostatics through remote mutations, with the predictions tested experimentally. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.