Iterative approach to computational enzyme design

Abstract

A general approach for the computational design of enzymes to catalyze arbitrary reactions is a goal at the forefront of the field of protein design. Recently, computationally designed enzymes have been produced for three chemical reactions through the synthesis and screening of a large number of variants. Here, we present an iterative approach that has led to the development of the most catalytically efficient computationally designed enzyme for the Kemp elimination to date. Previously established computational techniques were used to generate an initial design, HG-1, which was catalytically inactive. Analysis of HG-1 with molecular dynamics simulations (MD) and X-ray crystallography indicated that the inactivity might be due to bound waters and high flexibility of residues within the active site. This analysis guided changes to our design procedure, moved the design deeper into the interior of the protein, and resulted in an active Kemp eliminase, HG-2. The cocrystal structure of this enzyme with a transition state analog (TSA) revealed that the TSA was bound in the active site, interacted with the intended catalytic base in a catalytically relevant manner, but was flipped relative to the design model. MD analysis of HG-2 led to an additional point mutation, HG-3, that produced a further threefold improvement in activity. This iterative approach to computational enzyme design, including detailed MD and structural analysis of both active and inactive designs, promises a more complete understanding of the underlying principles of enzymatic catalysis and furthers progress toward reliably producing active enzymes.computational protein design | de novo enzyme design | proton transfer T he high efficiency, chemoselectivity, regio-and stereospecificity, and biodegradability of enzymes make them extremely attractive catalysts. However, the finite repertoire of naturally occurring enzymes limits their applicability to broad problems in biotechnology. A general method for the computational design of enzymes that can efficiently catalyze arbitrary chemical reactions would allow the benefits of enzymatic catalysis to be applied to chemical transformations of interest that are currently inaccessible via natural enzymes. Bolon and Mayo provided important early evidence that such an approach is feasible (1), which motivated significant progress toward this goal in recent years. Using quantum mechanics-based active site design and the Rosetta software suite, Baker, Houk, and coworkers designed enzymes for three chemically unrelated nonnatural reactions in a variety of catalytically inert scaffolds (2-4).In early incarnations of computational protein design, a strategy for methods development was put forth in terms of the so-called "protein design cycle" in which experimental evaluation of an initial design is used to inform adjustments to the design process for subsequent rounds of design (5, 6). Ideally, these steps would be continued iteratively until the protein sequences predicted by the algorithm exhibit the desired char...

Bridging the gaps in design methodologies by evolutionary optimization of the stability and proficiency of designed Kemp eliminase KE59

“…2A). Similar "flipping" of the stacking Trp was also observed in the apo structures of catalytic antibody 34E4 (31) and of KE design HG-1 (32). In the structures of KE59 variants with benzotriazole ligands, the position of W109 is more similar to the designed rotamer (Fig.…”

Designed protein reveals structural determinants of extreme kinetic stability

“…We demonstrate a high level of design success for ThreeFoil as evidenced by its: (i) reversible, cooperative, two-state (un)folding; and (ii) well folded and functional native structure which has high solubility and monodispersity, well diffracting crystals, and great resistance against H/D exchange (1), denaturation by chaotropes and detergent, and degradation by protease. Although the rational design of proteins with desired structure and function remains a great challenge and often require multiple cycles of design and/or selection to improve them, successes in designing both structures and/or functions, including ones not observed in nature, have been increasing (3,4,6,8,9,18,49,50). These results demonstrate the increasing understanding of fundamental principles and utility of computational protein design.…”

“…Although impressive recent successes have been reported in designing both natural and novel protein functions and/or structures (1-6), design remains difficult, often requiring multiple rounds of iterative improvements (7)(8)(9)(10). In depth biophysical characterization of protein design outcomes and an understanding of their molecular basis have been limited, and these are critical for improving future designs.…”

Molecular Modeling in Enzyme Design, Toward In Silico Guided Directed Evolution

“…Currently we find very few studies following such an approach, where we can underline, for example, Privett et al [203]. When thinking of future implementation, an initial less accurate in silico evolution could be tested in the lab and a more accurate second one performed only on those regions that show more promising experimental results.…”