Quantifying and Designing for Electrostatic Preorganization in Enzymes

University Of California-Los Angeles, Los Angeles CA

Investigators

Abstract

With the support of the Chemistry of Life Processes (CLP) program in the Chemistry Division, Dr. Anastassia Alexandrova from the University of California, Los Angeles, and Dr. Mark Eberhart from the Colorado School of Mines are developing tools and methods to enable the design of artificial enzymes. Enzymes are general protein-based and serve as the workhorses for biological catalysis. One of the great challenges confronting modern chemistry is to illuminate the mechanisms responsible for the catalytic efficiency displayed by most enzymes that is the products of bimolecular evolution are Darwinian selection pressure for biological function. This program will explore the role of enzyme structure distal to the site of catalytic activity; namely, the active site. Such long range interactions are thought to be a key feature distinguishing natural enzymes from their artificial counterparts. This investigation will combine advances in computational chemistry with experimental testing and benchmarking. Experimental approaches will be used to assess the effect of distal changes in enzyme structure upon catalytic efficiency. The novel computational methods will be employed to determine how these distant structural changes specifically alter the proximal reaction site environment and promote or inhibit enzyme catalysis. The approach taken will be to first predict the effects of specific structural alterations to enzyme efficiency, followed by the expression of the mutant, designed enzymes, followed by experimental testing their catalytic efficiency. In this way, there will be an inherent feedback loop between computation and experiment in this research. The computational tools developed in this investigation will be made available to other research groups exploring computationally-aided molecular design. This project also includes an outreach program intended to familiarize K-12 students with the great challenges and opportunities afforded by the advances in molecular biology and chemistry when coupled with equivalent advances in computation. This project will develop new computational tools based on charge density-partitioning to assess the effects of enzyme structure on electrostatic pre-organization in natural and designed enzymes. These tools will be used, and concurrently refined, to study pre-organization in several representative enzyme classes, and to interrogate the progress of pre-organization accompanying natural and laboratory enzyme evolution. The goal of these studies is to uncover relationships between enzymatic structure, active site charge density, reaction barriers, and catalytic efficiency and specificity. If successful, the insight resulting from these investigations will facilitate the inclusion of pre-organization into enzyme design paradigms. Ultimately, such predictions are experimentally testable, and such have the potential for broad impact in the protein design field by introducing tools to effectively predict and design strategic electrostatic environments that promote the desired catalytic function. 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.