Abraham J. P.
Teunissen
ab,
Tim F. E.
Paffen
ab,
Ivo A. W.
Filot
ac,
Menno D.
Lanting
ab,
Roy J. C.
van der Haas
ab,
Tom F. A.
de Greef
*ad and
E. W.
Meijer
*ab
aInstitute for Complex Molecular Systems, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands. E-mail: e.w.meijer@tue.nl; t.a.f.d.greef@tue.nl
bLaboratory of Macromolecular and Organic Chemistry, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands
cSchuit Institute for Catalysis, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands
dComputational Biology, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands
First published on 14th August 2019
The adaptivity of biological reaction networks largely arises through non-covalent regulation of catalysts' activity. Such type of catalyst control is still nascent in synthetic chemical networks and thereby hampers their ability to display life-like behavior. Here, we report a bio-inspired system in which non-covalent interactions between two complementary phase-transfer catalysts are used to regulate reaction kinetics. While one catalyst gives bimolecular kinetics, the second displays autoinductive feedback, resulting in sigmoidal kinetics. When both catalysts are combined, the interactions between them allow rational control over the shape of the kinetic curves. Computational models are used to gain insight into the structure, interplay, and activity of each catalytic species, and the scope of the system is examined by optimizing the linearity of the kinetic curves. Combined, our findings highlight the effectiveness of regulating reaction kinetics using non-covalent catalyst interactions, but also emphasize the risk for unforeseen catalytic contributions in complex systems and the necessity to combine detailed experiments with kinetic modelling.
Regulatable catalysts have proven to be a useful element in synthetic systems as well. For example, the binding of metals9–12 and other atoms13,14 has been used to create catalysts which can be switched “on” or “off”, or whose enantioselectivity can be altered. However, the catalyst-ligand binding strengths in such systems are usually too large to allow for dynamic competition and the possibility to perturb the system by small changes in concentration, temperature, or solvent composition.15,16 In addition, this type of regulation simply alters the reaction's overall rate or selectivity, and not the shape of its kinetic curves, as is the case in natural systems (e.g., the “sigmoidalness” of certain enzymes' reaction kinetics can be regulated by altering their sensitivity to autocatalytic feedback).17 To enhance synthetic catalysts' adaptability, single catalysts composed of multiple non-covalently bound molecules have been developed.18–22 Because such supramolecular catalysts are typically held together by relatively weak hydrogen bonds, their compositions – and thereby their activities and selectivities – are more open to gradual and dynamic regulation (e.g., by inhibition through the addition of a competing binding motif).23–26 Furthermore, the dynamic nature of supramolecular catalysts enhances their susceptibility to interact with other reaction components, which facilitates feedback mechanisms and communication between otherwise distinct reactions. Overall, the advancement of life-like synthetic systems is expected to benefit from dynamic control over both the overall reaction rate as well as the type of kinetics displayed by a reaction, and this can be achieved by employing multiple catalysts that interact with each other as well as with different reaction components.
Here, we present a combined theoretical and experimental study of a catalytic system in which the interactions between two complementary phase-transfer catalysts allow tuning of reaction kinetics ranging from bimolecular, to pseudo 0th order, to sigmoidal. This system builds upon our earlier findings demonstrating that the supramolecular binding motif 1,8-naphthyridine (NaPy) is able to function as a K2CO3 solubilizing phase-transfer catalyst for the Michael addition, for example in the reaction between maleimide and 2,4-pentanedione in chloroform (Fig. 1a).26 It was shown that this reaction displays bimolecular reaction kinetics and that the overall reaction rate can be regulated by inhibition using the NaPy complementary ureidopyrimidinone (UPy) motif.26 We also showed that a fixed ratio of NaPy and ditopic UPy can be diluted while buffering the concentration of catalytically active free NaPy, thereby desensitizing the Michael additions' rate to dilution.24–27
Fig. 1 Chemical structure of the compounds used and their role in the Michael addition. (a) Structure of the substrates of the Michael addition (Malref3 and Pentref4), as well as the K2CO3 solubilizing phase-transfer catalysts used (NaPy 1 and UPy 2). (b) The catalytic activity and type of kinetics associated with each species in the K2CO3 catalyzed Michael addition, and the equilibria between UPy 2 (Kdim = 6 × 107 M−1 at 25 °C in CHCl3)28 and NaPy 1 (Ka = 5.2 × 105 M−1 for UPy 2 and NaPy 1 in CDCl3, see Fig. S2† for experimental results of binding constant determination by 1H NMR). |
We now show that UPy motifs functionalized with an ester moiety on their alkylidene position can also function as phase-transfer catalyst and that the interactions between such catalytically active UPys and the NaPy catalyst can be used to regulate the kinetics of the Michael addition (Fig. 1b). Interestingly, sigmoidal kinetics are observed when the Michael addition is catalyzed by ester functionalized UPys which results from the Michael product stabilizing the catalytically active complex between UPy and K2CO3 (diUPy·K2CO3), thereby enhancing the latter's rate of formation (autoinduction). Besides stabilizing the diUPy·K2CO3 catalyst, the Michael product can also act as an individual phase-transfer catalyst by forming a complex with K2CO3 (product·K2CO3), thereby giving rise to autocatalysis. Kinetic models and density functional theory (DFT) calculations are used to obtain insight in the catalytic species' structures and the interplay between them. It is shown that the non-covalent interactions between the UPy and NaPy catalysts can be used to regulate reaction kinetics from bimolecular to strongly sigmoidal (Fig. 1b). In addition, we examine the extent to which the kinetics can be controlled by optimizing the linearity of the kinetic curves, thereby creating pseudo 0th order kinetics. The engineering of such bioinspired reaction networks containing interacting catalysts and multiple feedback loops will aid the development of autonomous chemical systems that sense their environment, processes chemical stimuli, and respond at the molecular level.
During our investigation of NaPy's catalytic role, we found that reactions catalyzed by K2CO3 and pre-added product display slightly faster rates than those catalyzed by K2CO3 only (Fig. 2b). We therefore propose that in addition to NaPy, also the product is able to complex and solubilize K2CO3. A plausible structure of such a catalytic complex in which the Michael product binds K2CO3 (product·K2CO3) was provided by DFT calculations, showing coordination of several of the Michael product's carbonyl moieties to K2CO3 (Fig. 2d). Such product-mediated catalyst activation represents an uncommon form of ligand-acceleration,32 which has been classified both as autoinductive33 and autocatalytic.34,35 We chose to use the term autocatalysis to describe product·K2CO3-mediated rate acceleration, as this is in agreement with other systems in which the reaction product promotes its own formation by functioning as phase-transfer catalyst.35–37 Interestingly, no significant increase in reaction rate was observed when the diNaPy·K2CO3 catalyzed reaction was performed in the presence of additional Michael product (Fig. 2b). Subsequent kinetic analysis of these results showed that the high catalytic activity of NaPy 1 reduces the product's contribution to the overall conversion to just a few percent (see Fig. S13C† for computational fits and simulations). Combined, our results show that the kinetics of the NaPy catalyzed Michael addition are composed of diNaPy·K2CO3 catalysis, autocatalysis, and a K2CO3 background reaction, and that the overall kinetics of this reaction can be accurately described using a kinetic model that includes these contributions (Fig. 2e and S12E†).
To investigate the influence of the Michael product on the UPy 2 catalyzed reaction, the reaction between Malref3 and Pentref4 was performed in the presence of UPy 2, K2CO3, and additional product, added at the start of the reaction (Fig. 3f). Compared to the reactions catalyzed by UPy 2 and K2CO3 only, this led to a much shorter lag-phase and significantly faster reaction rates. Although the Michael product can act as a separate phase-transfer catalyst (vide supra), our model shows that the autocatalysis – determined by analyzing the reaction catalyzed by Michael product and K2CO3 only, Fig. 2b – is not strong enough to explain the observed rate-acceleration. Instead, our kinetic model and DFT calculations suggest that the product stabilizes the diUPy·K2CO3 complex by forming a structure in which K2CO3 is chelated by both the UPy dimer as well as the Michael product (Fig. 3g). Although this diUPy·product·K2CO3 complex catalyzes the Michael addition with a similar rate constant as the diUPy·K2CO3 complex, it is more stable and formed significantly faster, thereby giving rise to rate acceleration. Such product-mediated catalyst activation is termed autoinduction (see Fig. S15† for validation of inclusion of autoinduction in the kinetic model, and Fig. S12E† and DFT results for the determined rate constants and complex stabilities). Combined, our results show that although the product can act as an orthogonal catalyst (autocatalysis), in this reaction it functions mainly as an activator for the diUPy·K2CO3 catalyst (autoinduction, Fig. 3h and i). This autoinductive mechanism is therefore the predominant cause of the sigmoidal kinetic curves observed for the UPy catalyzed Michael addition (see Fig. S14 and S15†).
Fig. 4 Experimental and computational data related to the Michael addition catalyzed by K2CO3 and combinations of NaPy 1 and UPy 2. (a) Schematic depiction of the NaPy 1, UPy 2 and K2CO3 catalyzed Michael addition between Malref3 and Pentref4. Part of the UPy and NaPy will form UPy–NaPy heterodimers in solution, which are catalytically inactive. (b) The conversion of the Michael addition between Malref3 (c = 4 mM) and Pentref4 (c = 4 mM) in the presence of K2CO3 (c = 36 mM), NaPy 1 (c = 8 mM) and various amounts of UPy 2 in CDCl3 at room temperature (symbols). In addition, the best fits of the kinetic model based on mass action kinetics of NaPy, diUPy and UPy–NaPy phase-transfer catalysis, autocatalysis as a result of the Michael product functioning as an additional phase-transfer catalyst, and autoinduction caused by the Michael product binding and thereby activating the already catalytically active diUPy·K2CO3 complex (lines, see Fig. S12† for details on the kinetic model) are shown. The insets depict the speciation of UPy and NaPy at the start of each reaction and the time required to reach 50% conversion using the different equivalents of UPy 2. All reactions were performed in CDCl3 at room temperature, all components were combined simultaneously. (c) Schematic of the expanded kinetic mass action model including the background reaction, autocatalysis, diUPy·K2CO3 complexation, autoinduction, NaPy catalysis, and UPy–NaPy catalysis. The formation of product·K2CO3, diNaPy·K2CO3 and UPy–NaPy·K2CO3 complexes was not included in the model as this is not required to obtain a proper fit of the data, instead their formation is viewed as instantaneous. (d) Catalytic contributions of the background reaction, autocatalysis, UPy catalysis, UPy autoinduction, NaPy catalysis, and UPy–NaPy catalysis in the Michael addition catalyzed by K2CO3, NaPy (c = 8 mM), and UPy (c = 12 mM = 1.5 eq.), simulated using the optimized parameters of the best fit. |
To test this hypothesis, the Michael addition between Malref3 and Pentref4 was performed in the presence of NaPy 1, K2CO3, and various amounts of UPy 2 (Fig. 4b). We observed that the addition of small amounts of UPy 2 (0.3 and 0.9 equivalents with respect to NaPy 1), led to a decrease of the overall reaction rate compared to the reaction performed without UPy 2 present. Increasing the UPy 2 concentration to 1.5 equivalents did not lead to a further reduction in the overall reaction rate, but notably altered the shape of the kinetic curve from bimolecular to a more linear character. Interestingly, performing the reaction with even more UPy 2 present (2.5 equivalents) led to an increase in the overall reaction rate and slightly sigmoidal kinetics.
To obtain more insight into this system, a kinetic model was constructed containing background catalysis by non-complexed K2CO3, phase-transfer catalysis by binding of either UPy–NaPy heterodimers, UPy homodimers, or the Michael product to K2CO3, and lastly, autoinduction by the Michael product enhancing the diUPy·K2CO3 catalyst's stability and rate of formation (Fig. 4c). Interestingly, when we used the optimized parameters obtained from modelling the reactions catalyzed by K2CO3 and UPy only, we were unable to model those catalyzed by both K2CO3, UPy and NaPy. Therefore, all parameters used to model the reactions catalyzed by both UPy and NaPy were set free. This discrepancy seems to be caused by an activating role of NaPy on the UPy catalysis vide infra. Gratifying, the computational model revealed that an increase in UPy 2 concentration leads to a rise in the UPy homodimer and UPy–NaPy heterodimer concentrations, as well as a decrease in the free NaPy concentration (Fig. 4b). The effects of the increasing amounts of UPy 2 on the reaction kinetics can thus be qualitatively explained by a decreasing contribution of the bimolecular kinetics resulting from diNaPy·K2CO3 catalysis, and an increasing influence of the sigmoidal kinetics brought about by the diUPy·K2CO3 catalyst. Similarly, the changes in the overall reaction rate arise from the varying amounts of diNaPy·K2CO3 and diUPy·K2CO3 catalyst present.
Although the observed changes in kinetics can be qualitatively explained by the varying concentrations of diNaPy·K2CO3 and diUPy·K2CO3 catalyst, a detailed analysis of our results revealed a complex interplay between these species. First, our DFT calculations revealed that the catalytically inactive UPy–NaPy dimers are able to form a stable complex with K2CO3 (UPy·NaPy·K2CO3), and that this proceeds through a UPy-type mechanism, i.e., the ester moiety on the UPy binds one of the K+ ions, while NaPy does not directly interact with K2CO3 (see ESI† for an optimized DFT structure of UPy·NaPy·K2CO3). This stability of UPy·NaPy·K2CO3 is somewhat surprising, as our kinetic analysis shows that it does not contribute to the overall catalysis (Fig. 4d). While we were not able to isolate UPy·NaPy·K2CO3 for further investigation, its lack of catalytic activity could be explained if multiple UPy–NaPy dimers are required to form an efficient phase-transfer catalyst. Such a structure comprising K2CO3 and several UPy–NaPy dimers might not be formed at concentrations high enough to produce a noticeable effect on the overall reaction rate, which agrees with the high reaction order suggested by our kinetic analysis (Fig. S12F†). Secondly, our kinetic analyses reveal that – although UPy and NaPy partially deactivate each other through the formation of UPy–NaPy dimers – the diUPy·K2CO3 catalyst itself has a higher catalytic activity and rate of formation when in the presence of NaPy 1 (Fig. S12E and F†). This could be explained by K2CO3 exchanging between fast forming diNaPy·K2CO3 and the more stable diUPy·K2CO3 (see ESI† for DFT calculated stabilities of all catalytic species). Lastly, our 1H NMR data suggests that binding of the Michael product to diUPy·K2CO3 (i.e., the autoinduction) shifts the UPy–NaPy equilibria from catalytically inactive UPy–NaPy heterodimers towards catalytically active UPy homodimers and free NaPy (not shown, as quantification of this phenomenon was troubled by gradual deuteration of UPy and NaPy). Such a shift in equilibria would agree with the Michael products' stabilizing influence on the diUPy·K2CO3 catalyst as determined by DFT, and would represent an additional source of rate acceleration by generating additional free NaPy and diUPy phase-transfer catalyst. Combined, these results show that the non-covalent interactions between NaPy 1 and UPy 2 give rise to a complex catalytic system which cannot be fully explained by a simple linear combination of the NaPy and diUPy phase-transfer catalysts.
Our results show that increasing the ratio of UPy 2 to NaPy 1 allows regulation of the Michael addition's kinetics from bimolecular to sigmoidal, with moderately linear kinetics obtained at intermediate UPy 2 concentrations (i.e., 1.5 eq.). However, the rate acceleration induced by UPy catalysis is not sufficient to counteract the influence of the decreasing substrate concentration on the reaction rate, and as a result all curves start to level off above ≈70% conversion (Fig. 4b). To examine the extent to which the kinetics in our system can be regulated – and test our kinetic model – we set out to optimize the linearity of the kinetic profiles. This specific goal was chosen because it requires delicate balancing of the biomolecular and sigmoidal contributions to the overall reaction rate, which will likely provide additional insight in the respective catalysts' properties. To achieve this, two goals need to be met. Firstly, it is essential that the reaction rates at higher conversions are increased, i.e., the rate acceleration resulting from autoinduction needs to be enhanced. Secondly, the optimal amount of NaPy required to linearize the kinetics has to be determined.
Fig. 5 Experimental and computational data related to the Michael addition catalyzed by UPypent5 and K2CO3. (a) The reaction between Malref3 and UPypent5, showing how the fraction of each type of diUPy catalyst changes with conversion. (b) The conversion of the K2CO3 catalyzed Michael addition between equimolar mixtures of Malref3 and UPypent5 (symbols) and the best fits of the kinetic model based on mass action kinetics of diUPypent, UPypent·UPyproduct, and diUPyproduct K2CO3 complexation and subsequent inter- and intramolecular catalysis (lines). The concentration of K2CO3 is kept constant (c = 36 mM), while the concentrations of Malref3 and UPypent5 are changed simultaneously (c = 1, 2, 4 and 8 mM). The reactions were performed in duplicate in CDCl3 at room temperature, all components were combined simultaneously. The results show that diluting both substrates by a factor eight does not notably reduce the reaction rate. (c) Schematic of the kinetic mass action model for the Michael addition between Malref3 and UPypent5 including diUPy·K2CO3 complexation, and inter- and intramolecular catalysis, see ESI† for details on the computational model, fits of the experimental results, and obtained reaction constants. |
To test the influence of covalently linking UPy to pentanedione on the reaction kinetics, UPypent5 was reacted with Malref3. Interestingly, the reaction between 5 and 3 is much faster compared to reactions between Michael substrates 3 and 4 catalyzed by similar amounts of UPy 2 (Fig. 3b and 5b). As the high activity of UPypent5 is proposed to result from intramolecular interactions, and the equilibrium between intra- and intermolecular contacts depends strongly on concentration,39,40 we investigated the influence of concentration on the Michael addition catalyzed by UPypent5 and K2CO3. Surprisingly, reducing the concentration of UPypent5 and Malref3 by a factor eight resulted in only a slight decrease in reaction rate (Fig. 5b). This insensitivity could be described by a kinetic mass action model that includes the effects described (Fig. 5c), and revealed that the catalysts' efficiency increases from diUPypent (UD2) to UPypent·UPyproduct (UDUP) to diUPyproduct (see Fig. S16† for calculated reaction constants).
In our current study we have mainly altered the UPy–NaPy equilibria by changing the ratio of these motifs. However, it has been shown that many stimuli, such as light,41 pH,42 temperature,28 redox chemistry,43,44 and disulfide exchange45 can also be used to influence UPy–NaPy dimerization. In addition, changing the molecular structure of UPy or NaPy,15,27,46 or the addition of complementary binding motifs,47,48 have also proven excellent means of controlling these equilibria. Incorporating such mechanisms in our system will likely generate alternative means to enhance its applicability.
Nevertheless, our study also highlights the challenges associated with further increasing the system's complexity. It underscores the high likelihood of (unexpected) interactions arising in complex catalytic systems and the difficulties associated with fully comprehending and modeling these. For example, while our kinetic models could accurately describe the reaction progress curves, we were not able to precisely determine the value of all reaction rate constants. Furthermore, certain rate constants seem to vary with the complexity of the system (e.g., the rate constants obtained from experiments with UPy only could not be used to satisfyingly predict the kinetics of reactions catalyzed by both UPy and NaPy). As explained, these limitations result from the exclusion of certain processes in our model, including transfer of K2CO3 between both catalysts and gradual shifts in the UPy–NaPy equilibria. Therefore, we believe that the further advancement of complex catalytic systems will increasingly rely on extensive kinetic modeling and the meticulous analysis of all interactions.
Footnote |
† Electronic supplementary information (ESI) available. See DOI: 10.1039/c9sc02357g |
This journal is © The Royal Society of Chemistry 2019 |