Quantitative, High-throughput Mechanistic Enzymology

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Project Summary Enzymes are the primary catalysts of biological transformations and have enormous value in medicine and industry. While decades of research have established that active site residues are essential for catalysis, we do not yet understand in detail the contributions of residues beyond the active site to efficiency and specificity. Of course a folded enzyme is required for catalysis, but beyond folding there is a complex functional interplay of residues throughout an enzyme: allosteric ligand binding and remote mutations alter and enhance catalysis, active site residues coevolve with remote residues and regions, and distal mutations arise in screens and selections for enzymes with enhanced functional properties. Given this inherent complexity, our central premise is that we need tools that extend the power of traditional mechanistic enzymology to systematically investigate residues throughout the entire protein and their interconnectivity. Our central technological innovation delivers the needed tools: High-throughput Microfluidics for Enzyme Kinetics (HT-MEK) and Stability (HT-MES) expresses, purifies, and quantitatively assays 1200 enzyme variants in parallel, rapidly and inexpensively, yielding accurate kinetic and thermodynamic constants for many substrates and ligands over many conditions. With these measurements we will map functional regions and linkages throughout proteins, allowing enzymology to address previously inaccessible challenges in mechanism, evolution, and biology. We first apply these tools to the Alkaline Phosphatase (AP) superfamily member E. meningoseptica PafA, leveraging extensive prior structural, mechanistic, and phylogenetic insights to guide assay development and test previously inaccessible models to deepen our understanding of enzyme catalysis. We will systematically and quantitatively determine kinetic parameters for cognate and promiscuous PafA substrates and affinities for ground and transition-state PafA inhibitors, and we will do so for multiple mutations of every PafA residue; these measurements will provide a comprehensive map of enzyme regions that contribute to specific components of catalytic function. Next, we will use multi-mutant cycles to determine the energetic and functional linkage of these regions to active site residues and specific catalytic features, as well as the connections within and between these regions. Extension to multiple AP superfamily members across evolutionary distances will identify the range and limits of generality of functional maps and identify the alterations that rewire functional connectivity. Expanding this approach to other targets, some of which are explored herein, will address fundamental and practical problems of broad interest. This carefully-reasoned, stepwise approach will usher in a new era of enzymology, in which the acquisition of multidimensional functional maps of enzymes addresses new questions in mechanism, evolution, and biology, and in which enzymology impacts biomedicine and engineering in new ways.