One-Pot Biocatalytic Synthesis of rac-Syringaresinol from a Lignin-Derived Phenol.

The drive for a circular bioeconomy has resulted in a great demand for renewable, biobased chemicals. We present a one-pot biocatalytic cascade reaction for the production of racemic syringaresinol, a lignan with applications as a nutraceutical and in polymer chemistry. The process consumes dihydrosinapyl alcohol, which can be produced renewably from the lignocellulosic material. To achieve this, a variant of eugenol oxidase was engineered for the oxidation of dihydrosinapyl alcohol into sinapyl alcohol with good conversion and chemoselectivity. The crystal structure of the engineered oxidase revealed the molecular basis of the influence of the mutations on the chemoselectivity of the oxidation of dihydrosinapyl alcohol. By using horseradish peroxidase, the subsequent oxidative dimerization of sinapyl alcohol into syringaresinol was achieved. Conditions for the one-pot, two-enzyme synthesis were optimized, and a high yield of syringaresinol was achieved by cascading the oxidase and peroxidase steps in a stepwise fashion. This study demonstrates the efficient production of syringaresinol from a compound that can be renewed by reductive catalytic fractionation of lignocellulose, providing a biocatalytic route for generating a valuable compound from lignin.

Enzyme immobilization studied through molecular dynamic simulations.

In recent years, simulations have been used to great advantage to understand the structural and dynamic aspects of distinct enzyme immobilization strategies, as experimental techniques have limitations in establishing their impact at the molecular level. In this review, we discuss how molecular dynamic simulations have been employed to characterize the surface phenomenon in the enzyme immobilization procedure, in an attempt to decipher its impact on the enzyme features, such as activity and stability. In particular, computational studies on the immobilization of enzymes using i) nanoparticles, ii) self-assembled monolayers, iii) graphene and carbon nanotubes, and iv) other surfaces are covered. Importantly, this thorough literature survey reveals that, while simulations have been primarily performed to rationalize the molecular aspects of the immobilization event, their use to predict adequate protocols that can control its impact on the enzyme properties is, up to date, mostly missing.

Rationally Guided Improvement of NOV1 Dioxygenase for the Conversion of Lignin-Derived Isoeugenol to Vanillin.

Biocatalysis is a key tool in both green chemistry and biorefinery fields. NOV1 is a dioxygenase that catalyzes the one-step, coenzyme-free oxidation of isoeugenol into vanillin and holds enormous biotechnological potential for the complete valorization of lignin as a sustainable starting material for biobased chemicals, polymers, and materials. This study integrates computational, kinetic, structural, and biophysical approaches to characterize a new NOV1 variant featuring improved activity and stability compared to those of the wild type. The S283F replacement results in a 2-fold increased turnover rate (kcat) for isoeugenol and a 4-fold higher catalytic efficiency (kcat/Km) for molecular oxygen compared to those of the wild type. Furthermore, the variant exhibits a half-life that is 20-fold higher than that of the wild type, which most likely relates to the enhanced stabilization of the iron cofactor in the active site. Molecular dynamics supports this view, revealing that the S283F replacement decreases the optimal pKa and favors conformations of the iron-coordinating histidines compatible with an increased level of binding to iron. Importantly, whole cells containing the S283F variant catalyze the conversion of ≤100 mM isoeugenol to vanillin, yielding >99% molar conversion yields within 24 h. This integrative strategy provided a new enzyme for biotechnological applications and mechanistic insights that will facilitate the future design of robust and efficient biocatalysts.

Structure- and computational-aided engineering of an oxidase to produce isoeugenol from a lignin-derived compound.

Various 4-alkylphenols can be easily obtained through reductive catalytic fractionation of lignocellulosic biomass. Selective dehydrogenation of 4-n-propylguaiacol results in the formation of isoeugenol, a valuable flavor and fragrance molecule and versatile precursor compound. Here we present the engineering of a bacterial eugenol oxidase to catalyze this reaction. Five mutations, identified from computational predictions, are first introduced to render the enzyme more thermostable. Other mutations are then added and analyzed to enhance chemoselectivity and activity. Structural insight demonstrates that the slow catalytic activity of an otherwise promising enzyme variant is due the formation of a slowly-decaying covalent substrate-flavin cofactor adduct that can be remedied by targeted residue changes. The final engineered variant comprises eight mutations, is thermostable, displays good activity and acts as a highly chemoselective 4-n-propylguaiacol oxidase. We lastly use our engineered biocatalyst in an illustrative preparative reaction at gram-scale. Our findings show that a natural enzyme can be redesigned into a tailored biocatalyst capable of valorizing lignin-based monophenols.

Getting Deeper into the Molecular Events of Heme Binding Mechanisms: A Comparative Multi-level Computational Study of HasAsm and HasAyp Hemophores.

Many biological systems obtain their activity by the inclusion of metalloporphyrins into one or several binding pockets. However, decoding the molecular mechanism under which these compounds bind to their receptors is something that has not been widely explored and is a field with open questions. In the present work, we apply computational techniques to unravel and compare the mechanisms of two heme-binding systems, concretely the HasA hemophores from Gram negative bacteria Serratiamarcescens (HasAsm) and Yersinia pestis (HasAyp). Despite the high sequence identity between both systems, the comparison between the X-ray structures of their apo and holo forms suggests different heme-binding mechanisms. HasAyp has extremely similar structures for heme-free and heme-bound forms, while HasAsm presents a very large displacement of a loop that ultimately leads to an additional coordination to the metal with respect to HasAyp. We combined Gaussian accelerated molecular dynamics simulations (GaMDs) in explicit solvent and protein-ligand docking optimized for metalloligands. GaMDs were first carried out on heme-free forms of both hemophores. Then, protein-ligand dockings of the heme were performed on cluster representatives of these simulations and the best poses were then subjected to a new series of GaMDs. A series of analyses reveal the following: (1) HasAyp has a conformational landscape extremely similar between heme-bound and unbound states with no to limited impact on the binding of the cofactor, (2) HasAsm presents as a slightly broader conformational landscape in its apo state but can only visit conformations similar to the X-ray of the holo form when the heme has been bound. Such behavior results from a complex cascade of changes in interactions that spread from the heme-binding pocket to the flexible loop previously mentioned. This study sheds light on the diversity of molecular mechanisms of heme-binding and discusses the weight between the pre-organization of the receptor as well as the induced motions resulting in association.

Cofactor Binding Dynamics Influence the Catalytic Activity and Selectivity of an Artificial Metalloenzyme.

We present an artificial metalloenzyme based on the transcriptional regulator LmrR that exhibits dynamics involving the positioning of its abiological metal cofactor. The position of the cofactor, in turn, was found to be related to the preferred catalytic reactivity, which is either the enantioselective Friedel-Crafts alkylation of indoles with ß-substituted enones or the tandem Friedel-Crafts alkylation/enantioselective protonation of indoles with α-substituted enones. The artificial metalloenzyme could be specialized for one of these catalytic reactions introducing a single mutation in the protein. The relation between cofactor dynamics and activity and selectivity in catalysis has not been described for natural enzymes and, to date, appears to be particular for artificial metalloenzymes.

Molecular Modeling for Artificial Metalloenzyme Design and Optimization.

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.

Defective AMH signaling disrupts GnRH neuron development and function and contributes to hypogonadotropic hypogonadism.

Congenital hypogonadotropic hypogonadism (CHH) is a condition characterized by absent puberty and infertility due to gonadotropin releasing hormone (GnRH) deficiency, which is often associated with anosmia (Kallmann syndrome, KS). We identified loss-of-function heterozygous mutations in anti-Müllerian hormone (AMH) and its receptor, AMHR2, in 3% of CHH probands using whole-exome sequencing. We showed that during embryonic development, AMH is expressed in migratory GnRH neurons in both mouse and human fetuses and unconvered a novel function of AMH as a pro-motility factor for GnRH neurons. Pathohistological analysis of Amhr2-deficient mice showed abnormal development of the peripheral olfactory system and defective embryonic migration of the neuroendocrine GnRH cells to the basal forebrain, which results in reduced fertility in adults. Our findings highlight a novel role for AMH in the development and function of GnRH neurons and indicate that AMH signaling insufficiency contributes to the pathogenesis of CHH in humans.

The Effect of Cofactor Binding on the Conformational Plasticity of the Biological Receptors in Artificial Metalloenzymes: The Case Study of LmrR.

The design of Artificial Metalloenzymes (ArMs), which result from the incorporation of organometallic cofactors into biological structures, has grown steadily in the last two decades and important new-to-Nature reactions have been reached. These type of exercises could greatly benefit from an understanding of the structural impact that the inclusion of organometallic moieties may have on the biological host. To date though, our understanding of this phenomenon is highly partial. This lack of knowledge is one of the elements that condition that first-generation ArMs generally display relatively poor catalytic profiles. In this work, we approach this matter by assessing the dynamics and stability of a series of ArMs resulting from the inclusion, via different anchoring strategies, of a variety of organometallic cofactors into the Lactococcal multidrug resistance regulator (LmrR) protein. To this aim, we coupled standard force field-based techniques such as Protein-Ligand Docking and Molecular Dynamics simulations with a variety of trajectory convergence analyses, capable of assessing both the stability and flexibility of the different systems under study upon the binding of cofactors. Together with the experimental evidence obtained in other studies, we provide an overview on how these changes can affect the catalytic outcomes obtained from the different ArMs. Fundamentally, our results show that the convergence analysis used in this work can assess how the inclusion of synthetic metallic cofactors in proteins can condition different structural modulations of their host. Those conformational modifications are key to the success of the desired catalytic activity and their proper identification can be wisely used to improve the quality and the rate of success of the ArMs.

An Artificial Heme Enzyme for Cyclopropanation Reactions.

An artificial heme enzyme was created through self-assembly from hemin and the lactococcal multidrug resistance regulator (LmrR). The crystal structure shows the heme bound inside the hydrophobic pore of the protein, where it appears inaccessible for substrates. However, good catalytic activity and moderate enantioselectivity was observed in an abiological cyclopropanation reaction. We propose that the dynamic nature of the structure of the LmrR protein is key to the observed activity. This was supported by molecular dynamics simulations, which showed transient formation of opened conformations that allow the binding of substrates and the formation of pre-catalytic structures.

Directed Evolution of an Artificial Imine Reductase.

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.

Design of an enantioselective artificial metallo-hydratase enzyme containing an unnatural metal-binding amino acid.

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.