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Chemo-Mechanical and Chemo-Structural pH-Feedback Mechanisms to Program Transient and Autonomous Self-Assembling Systems

Subject Area Preparatory and Physical Chemistry of Polymers
Term from 2014 to 2022
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 258922244
 
Final Report Year 2022

Final Report Abstract

This project aimed to develop and understand generalizable self-regulating chemically fueled reaction networks with higher level of complexity as well as chemo-mechanical and chemo-structural feedback systems based on pH-modulating enzymes and chemical reaction networks. We have developed a robust autonomous logic gate exploiting the functional interconnection and pH-dependent activity optima of the invertase/β-galactosidase and glucose oxidase cascades to precisely control transient pH profiles by metabolization of sucrose or lactose as dormant deactivators (DD). Moreover, we found that conversion of the DD into glucose was decisive for governing the regulatory mechanisms of the system. Inspired by biological systems, we have introduced layered compartments enriched with the antagonistic enzymes urease and esterase, respectively, to generate transient basic and acidic pH flips not possible in homogeneous solution due to a kinetic mismatch and pH-dependency of the enzymatic activities, therefore driving signaling in artificial systems closer towards orchestration of spatiotemporal domains as observed in biological systems. We integrated the urease-esterase system into microgel spheres, which enabled spatial and temporal control of the local pH environment that could be further modulated by integration of an alginate/poly(acrylic acid) shell, yielding programmable membrane activity. Strikingly, urease spheres were not only able to communicate with distinct esterase spheres, but also initiated inter-sphere attraction by diffusiophoretic driving forces. Moreover, we used urease-loaded microgel spheres as seeds for the autonomous, mild and shear-free growth of soft Fmoc-Et-NH2 hydrogels of various shapes without the need for 3D printing and other molds. In the final section of this project, we evolved experiment-supported theoretical concepts for a deeper physical understanding of chemically fueled autonomous self-assembly. To this end, we employed an EDC-fueled chemical reaction network for transient formation of anhydrides from neighboring carboxyl moieties (i) to induce transient volume phase transition in poly(methacrylic acid) (PMAA) microgels and (ii) to drive reversible spinodal decomposition of poly(norbornene dicarboxylic acid) (PNDAc) by temporarily increasing the hydrophobicity of the respective systems. We rationalized the behavior of these systems by using molecular dynamics simulations for calculating surface-area-normalized octanol/water partition coefficients (logP SA-1) as a measure of hydrophobicity. By combination of this thermodynamic characterization with an experimentally derived kinetic model, we were able to precisely predict the lifetimes of spinodal decomposition of PNDAc under various conditions. Thus, we have shown that logP SA-1 calculations are a simple yet powerful tool for gaining deeper insights into polymer-based, out-of-equilibrium systems and opened an avenue for predictive full in silico design in the future.

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