A General Tool for Engineering the NAD/NADP Cofactor Preference of Oxidoreductases

Abstract

The ability to control enzymatic nicotinamide cofactor utilization is critical for engineering efficient metabolic pathways. However, the complex interactions that determine cofactor-binding preference render this engineering particularly challenging. Physics-based models have been insufficiently accurate and blind directed evolution methods too inefficient to be widely adopted. Building on a comprehensive survey of previous studies and our own prior engineering successes, we present a structure-guided, semirational strategy for reversing enzymatic nicotinamide cofactor specificity. This heuristic-based approach leverages the diversity and sensitivity of catalytically productive cofactor binding geometries to limit the problem to an experimentally tractable scale. We demonstrate the efficacy of this strategy by inverting the cofactor specificity of four structurally diverse NADP-dependent enzymes: glyoxylate reductase, cinnamyl alcohol dehydrogenase, xylose reductase, and iron-containing alcohol dehydrogenase. The analytical components of this approach have been fully automated and are available in the form of an easy-to-use web tool: Cofactor Specificity Reversal-Structural Analysis and Library Design (CSR-SALAD).

Keywords: cofactor specificity; library design; oxidoreductases; protein engineering; semirational engineering.

Figure 1.

Cofactors nicotinamide adenine dinucleotide (NAD, top) and nicotinamide adenine dinucleotide phosphate (NADP, bottom) in representative Rossmann fold binding pockets (PDBs 4XDY and 4TSK, respectively). The highlighted 2’ recognition element (the phosphate of NADP or hydroxyl of NAD) and the chemically relevant hydride-bearing nicotinamide are separated in space and by multiple covalent bonds. In this paper, we use NAD and NADP, collectively NAD(P), when speaking generally about these cofactors, independent of their oxidation state, and only indicate the state, i.e. NADH / NAD+, when referring to those compounds specifically, such as for experimental details.

Figure 2.

CSR-SALAD performs three tasks: structure analysis, design of cofactor-switching libraries, and identification of positions for activity recovery.