Exploring Emergent Properties in Enzymatic Reaction Networks: Design and Control of Dynamic Functional Systems.

The intricate and complex features of enzymatic reaction networks (ERNs) play a key role in the emergence and sustenance of life. Constructing such networks in vitro enables stepwise build up in complexity and introduces the opportunity to control enzymatic activity using physicochemical stimuli. Rational design and modulation of network motifs enable the engineering of artificial systems with emergent functionalities. Such functional systems are useful for a variety of reasons such as creating new-to-nature dynamic materials, producing value-added chemicals, constructing metabolic modules for synthetic cells, and even enabling molecular computation. In this review, we offer insights into the chemical characteristics of ERNs while also delving into their potential applications and associated challenges.

Correction to "Strategies for Transferring Photobiocatalysis to Continuous Flow Exemplified by the Photodecarboxylation of Fatty Acids".

[This corrects the article DOI: 10.1021/acscatal.2c04444.].

Strategies for Transferring Photobiocatalysis to Continuous Flow Exemplified by Photodecarboxylation of Fatty Acids.

The challenges of light-dependent biocatalytic transformations of lipophilic substrates in aqueous media are manifold. For instance, photolability of the catalyst as well as insufficient light penetration into the reaction vessel may be further exacerbated by a heterogeneously dispersed substrate. Light penetration may be addressed by performing the reaction in continuous flow, which allows two modes of applying the catalyst: (i) heterogeneously, immobilized on a carrier, which requires light-permeable supports, or (ii) homogeneously, dissolved in the reaction mixture. Taking the light-dependent photodecarboxylation of palmitic acid catalyzed by fatty-acid photodecarboxylase from Chlorella variabilis (CvFAP) as a showcase, strategies for the transfer of a photoenzyme-catalyzed reaction into continuous flow were identified. A range of different supports were evaluated for the immobilization of CvFAP, whereby Eupergit C250 L was the carrier of choice. As the photostability of the catalyst was a limiting factor, a homogeneous system was preferred instead of employing the heterogenized enzyme. This implied that photolabile enzymes may preferably be applied in solution if repair mechanisms cannot be provided. Furthermore, when comparing different wavelengths and light intensities, extinction coefficients may be considered to ensure comparable absorption at each wavelength. Employing homogeneous conditions in the CvFAP-catalyzed photodecarboxylation of palmitic acid afforded a space-time yield unsurpassed by any reported batch process (5.7 g·L-1·h-1, 26.9 mmol·L-1·h-1) for this reaction, demonstrating the advantage of continuous flow in attaining higher productivity of photobiocatalytic processes.

A Bayesian Approach to Extracting Kinetic Information from Artificial Enzymatic Networks.

In order to create artificial enzymatic networks capable of increasingly complex behavior, an improved methodology in understanding and controlling the kinetics of these networks is needed. Here, we introduce a Bayesian analysis method allowing for the accurate inference of enzyme kinetic parameters and determination of most likely reaction mechanisms, by combining data from different experiments and network topologies in a single probabilistic analysis framework. This Bayesian approach explicitly allows us to continuously improve our parameter estimates and behavior predictions by iteratively adding new data to our models, while automatically taking into account uncertainties introduced by the experimental setups or the chemical processes in general. We demonstrate the potential of this approach by characterizing systems of enzymes compartmentalized in beads inside flow reactors. The methods we introduce here provide a new approach to the design of increasingly complex artificial enzymatic networks, making the design of such networks more efficient, and robust against the accumulation of experimental errors.

Modular Design of Small Enzymatic Reaction Networks Based on Reversible and Cleavable Inhibitors.

Systems chemistry aims to mimic the functional behavior of living systems by constructing chemical reaction networks with well-defined dynamic properties. Enzymes can play a key role in such networks, but there is currently no general and scalable route to the design and construction of enzymatic reaction networks. Here, we introduce reversible, cleavable peptide inhibitors that can link proteolytic enzymatic activity into simple network motifs. As a proof-of-principle, we show auto-activation topologies producing sigmoidal responses in enzymatic activity, explore cross-talk in minimal systems, design a simple enzymatic cascade, and introduce non-inhibiting phosphorylated peptides that can be activated using a phosphatase.

An Epitope-Imprinted Biointerface with Dynamic Bioactivity for Modulating Cell-Biomaterial Interactions.

In this study, an epitope-imprinting strategy was employed for the dynamic display of bioactive ligands on a material interface. An imprinted surface was initially designed to exhibit specific affinity towards a short peptide (i.e., the epitope). This surface was subsequently used to anchor an epitope-tagged cell-adhesive peptide ligand (RGD: Arg-Gly-Asp). Owing to reversible epitope-binding affinity, ligand presentation and thereby cell adhesion could be controlled. As compared to current strategies for the fabrication of dynamic biointerfaces, for example, through reversible covalent or host-guest interactions, such a molecularly tunable dynamic system based on a surface-imprinting process may unlock new applications in in situ cell biology, diagnostics, and regenerative medicine.