Hasegawa, J.-Y.; Lehnert, N.

J. Am. Chem. Soc. 2017, 139, 17265-17268, 10.1021/jacs.7b10154

Myoglobin reconstituted with iron porphycene catalyzes the cyclopropanation of styrene with ethyl diazoacetate. Compared to native myoglobin, the reconstituted protein significantly accelerates the catalytic reaction and the kcat/Km value is 26-fold enhanced. Mechanistic studies indicate that the reaction of the reconstituted protein with ethyl diazoacetate is 615-fold faster than that of native myoglobin. The metallocarbene species reacts with styrene with the apparent second-order kinetic constant of 28 mM–1 s–1 at 25 °C. Complementary theoretical studies support efficient carbene formation by the reconstituted protein that results from the strong ligand field of the porphycene and fewer intersystem crossing steps relative to the native protein. From these findings, the substitution of the cofactor with an appropriate metal complex serves as an effective way to generate a new biocatalyst.

Maréchal, J.-D.

ACS Catal. 2014, 4, 833-842, 10.1021/cs400921n

We present a computational study that combines protein–ligand docking, quantum mechanical, and quantum mechanical/molecular mechanical calculations to scrutinize the mechanistic behavior of the first artificial enzyme able to enantioselectively reduce cyclic imines. We applied a novel strategy that allows the characterization of transition state structures in the protein host and their associated reaction paths. Of the most striking results of our investigation is the identification of major conformational differences between the transition state geometries of the lowest energy paths leading to (R)- and (S)-reduction products. The molecular features of (R)- and (S)-transition states highlight distinctive patterns of hydrophobic and polar complementarities between the substrate and the binding site. These differences lead to an activation energy gap that stands in very good agreement with the experimentally determined enantioselectivity. This study sheds light on the mechanism by which transfer hydrogenases operate and illustrates how the change of environment (from homogeneous solution conditions to the asymmetric protein frame) affect the reactivity of the organometallic cofactor. It provides novel insights on the complexity in integrating unnatural organometallic compounds into biological scaffolds. The modeling strategy that we pursued, based on the generation of “pseudo transition state” structures, is computationally efficient and suitable for the discovery and optimization of artificial enzymes. Alternatively, this approach can be applied on systems for which a large conformational sampling is needed to identify relevant transition states.

Maréchal, J.-D.; Roelfes, G.

Chem. Sci. 2017, 8, 7228-7235, 10.1039/C7SC03477F

The design of artificial metalloenzymes is a challenging, yet ultimately highly rewarding objective because of the potential for accessing new-to-nature reactions. One of the main challenges is identifying catalytically active substrate–metal cofactor–host geometries. The advent of expanded genetic code methods for the in vivo incorporation of non-canonical metal-binding amino acids into proteins allow to address an important aspect of this challenge: the creation of a stable, well-defined metal-binding site. Here, we report a designed artificial metallohydratase, based on the transcriptional repressor lactococcal multidrug resistance regulator (LmrR), in which the non-canonical amino acid (2,2′-bipyridin-5yl)alanine is used to bind the catalytic Cu(II) ion. Starting from a set of empirical pre-conditions, a combination of cluster model calculations (QM), protein–ligand docking and molecular dynamics simulations was used to propose metallohydratase variants, that were experimentally verified. The agreement observed between the computationally predicted and experimentally observed catalysis results demonstrates the power of the artificial metalloenzyme design approach presented here.

Maréchal, J.-D.; Ward, T.R.

Angew. Chem. Int. Ed. 2018, 57, 1863-1868, 10.1002/anie.201711016

Artificial metalloenzymes, resulting from incorporation of a metal cofactor within a host protein, have received increasing attention in the last decade. The directed evolution is presented of an artificial transfer hydrogenase (ATHase) based on the biotin‐streptavidin technology using a straightforward procedure allowing screening in cell‐free extracts. Two streptavidin isoforms were yielded with improved catalytic activity and selectivity for the reduction of cyclic imines. The evolved ATHases were stable under biphasic catalytic conditions. The X‐ray structure analysis reveals that introducing bulky residues within the active site results in flexibility changes of the cofactor, thus increasing exposure of the metal to the protein surface and leading to a reversal of enantioselectivity. This hypothesis was confirmed by a multiscale approach based mostly on molecular dynamics and protein–ligand dockings.

Hyster, T.K.; Ward, T.R.

Angew. Chem. Int. Ed. 2016, 55, 7344-7357, 10.1002/anie.201508816

Artificial metalloenzymes have received increasing attention over the last decade as a possible solution to unaddressed challenges in synthetic organic chemistry. Whereas traditional transition‐metal catalysts typically only take advantage of the first coordination sphere to control reactivity and selectivity, artificial metalloenzymes can modulate both the first and second coordination spheres. This difference can manifest itself in reactivity profiles that can be truly unique to artificial metalloenzymes. This Review summarizes attempts to modulate the second coordination sphere of artificial metalloenzymes by using genetic modifications of the protein sequence. In doing so, successful attempts and creative solutions to address the challenges encountered are highlighted.

Maréchal, J.-D.

Acc. Chem. Res. 2020, 53, 896-905, 10.1021/acs.accounts.0c00031

Artificial metalloenzymes (ArMs) are obtained by inserting homogeneous catalysts into biological scaffolds and are among the most promising strategies in the quest for new-to-nature biocatalysts. The quality of their design strongly depends on how three partners interact: the biological host, the “artificial cofactor,” and the substrate. However, structural characterization of functional artificial metalloenzymes by X-ray or NMR is often partial, elusive, or absent. How the cofactor binds to the protein, how the receptor reorganizes upon the binding of the cofactor and the substrate, and which are the binding mode(s) of the substrate for the reaction to proceed are key questions that are frequently unresolved yet crucial for ArM design. Such questions may eventually be solved by molecular modeling but require a step change beyond the current state-of-the-art methodologies. Here, we summarize our efforts in the study of ArMs, presenting both the development of computational strategies and their application. We first focus on our integrative computational framework that incorporates a variety of methods such as protein–ligand docking, classical molecular dynamics (MD), and pure quantum mechanical (QM) methods, which, when properly combined, are able to depict questions that range from host–cofactor binding predictions to simulations of entire catalytic mechanisms. We also pay particular attention to the protein–ligand docking strategies that we have developed to accurately predict the binding of transition metal-containing molecules to proteins. While this aspect is fundamental to many bioinorganic fields beyond ArMs, it has been disregarded from the molecular modeling landscape until very recently. Next we describe how to apply this computational framework to particular ArMs including systems previously characterized experimentally as well as others where computation served to guide the design. We start with the prediction of the interactions between homogeneous catalysts and biological hosts. Protein–ligand docking is pivotal at that stage, but it needs to be combined with QM/MM or MD approaches when the binding of the cofactor implies significant conformational changes of the protein or involve changes of the electronic state of the metal. Then, we summarize molecular modeling studies aimed at identifying cofactor–substrate arrangements inside the ArM active pocket that are consistent with its reactivity. These calculations stand on “Theozyme”-like dockings, MD-refined or not, which provide molecular rationale of the catalytic profiles of the artificial systems. In the third section, we present case studies to decode the entire catalytic mechanism of two ArMs: (1) an iridium based asymmetric transfer hydrogenase obtained by insertion of Noyori’s catalyst into streptavidin and (2) a metallohydrolase achieved by including a receptor. Transition states, second coordination sphere effects, as well as motions of the cofactors are identified as drivers of the enantiomeric profiles. Finally, we report computer-aided designs of ArMs to guide experiments toward chemical and mutational changes that improve their activity and/or enantioselective profiles and expand toward future directions.

Maréchal, J.-D.; Ward, T.R.

J. Am. Chem. Soc. 2014, 136, 15676-15683, 10.1021/ja508258t

An artificial imine reductase results upon incorporation of a biotinylated Cp*Ir moiety (Cp* = C5Me5–) within homotetrameric streptavidin (Sav) (referred to as Cp*Ir(Biot-p-L)Cl] ⊂ Sav). Mutation of S112 reveals a marked effect of the Ir/streptavidin ratio on both the saturation kinetics as well as the enantioselectivity for the production of salsolidine. For [Cp*Ir(Biot-p-L)Cl] ⊂ S112A Sav, both the reaction rate and the selectivity (up to 96% ee (R)-salsolidine, kcat 14–4 min–1 vs [Ir], KM 65–370 mM) decrease upon fully saturating all biotin binding sites (the ee varying between 96% ee and 45% ee R). In contrast, for [Cp*Ir(Biot-p-L)Cl] ⊂ S112K Sav, both the rate and the selectivity remain nearly constant upon varying the Ir/streptavidin ratio [up to 78% ee (S)-salsolidine, kcat 2.6 min–1, KM 95 mM]. X-ray analysis complemented with docking studies highlight a marked preference of the S112A and S112K Sav mutants for the SIr and RIr enantiomeric forms of the cofactor, respectively. Combining both docking and saturation kinetic studies led to the formulation of an enantioselection mechanism relying on an “induced lock-and-key” hypothesis: the host protein dictates the configuration of the biotinylated Ir-cofactor which, in turn, by and large determines the enantioselectivity of the imine reductase.

Maréchal, J.-D.

ACS Catal. 2015, 5, 2469-2480, 10.1021/acscatal.5b00010

The development of artificial enzymes aims at expanding the scope of biocatalysis. Over recent years, artificial metalloenzymes based on the insertion of homogeneous catalysts in biomolecules have received an increasing amount of attention. Rational or pseudorational design of these composites is a challenging task because of the complexity of the identification of efficient complementarities among the cofactor, the substrate, and the biological partner. Molecular modeling represents an interesting alternative to help in this task. However, little attention has been paid to this field so far. In this manuscript, we aim at reviewing our efforts in developing strategies efficient to computationally drive the design of artificial metalloenzymes. From protein–ligand dockings to multiscale approaches, we intend to demonstrate that modeling could be useful at the different steps of the design. This Perspective ultimately aims at providing computational chemists with illustration of the applications of their tools for artificial metalloenzymes and convincing enzyme designers of the capabilities, qualitative and quantitative, of computational methodologies.