Leveraging Triphenylphosphine-Containing Polymers to Explore Design Principles for Protein-Mimetic Catalysts.

Complex interactions between noncoordinating residues are significant yet commonly overlooked components of macromolecular catalyst function. While these interactions have been demonstrated to impact binding affinities and catalytic rates in metalloenzymes, the roles of similar structural elements in synthetic polymeric catalysts remain underexplored. Using a model Suzuki-Miyuara cross-coupling reaction, we performed a series of systematic studies to probe the interconnected effects of metal-ligand cross-links, electrostatic interactions, and local rigidity in polymer catalysts. To achieve this, a novel bifunctional triphenylphosphine acrylamide (BisTPPAm) monomer was synthesized and evaluated alongside an analogous monofunctional triphenylphosphine acrylamide (TPPAm). In model copolymer catalysts, increased initial reaction rates were observed for copolymers untethered by Pd complexation (BisTPPAm-containing) compared to Pd-cross-linked catalysts (TPPAm-containing). Further, incorporating local rigidity through secondary structure-like and electrostatic interactions revealed nonmonotonic relationships between composition and the reaction rate, demonstrating the potential for tunable behavior through secondary-sphere interactions. Finally, through rigorous cheminformatics featurization strategies and statistical modeling, we quantitated relationships between chemical descriptors of the substrate and reaction conditions on catalytic performance. Collectively, these results provide insights into relationships among the composition, structure, and function of protein-mimetic catalytic copolymers.

Tailoring Hierarchical Structure and Rare Earth Affinity of Compositionally Identical Polymers via Sequence Control.

Macromolecule sequence, structure, and function are inherently intertwined. While well-established relationships exist in proteins, they are more challenging to define for synthetic polymer nanoparticles due to their molecular weight, sequence, and conformational dispersities. To explore the impact of sequence on nanoparticle structure, we synthesized a set of 16 compositionally identical, sequence-controlled polymers with distinct monomer patterning of dimethyl acrylamide and a bioinspired, structure-driving di(phenylalanine) acrylamide (FF). Sequence control was achieved through multiblock polymerizations, yielding unique ensembles of polymer sequences which were simulated by kinetic Monte Carlo simulations. Systematic analysis of the global (tertiary- and quaternary-like) structure in this amphiphilic copolymer series revealed the effect of multiple sequence descriptors: the number of domains, the hydropathy of terminal domains, and the patchiness (density) of FF within a domain, each of which impacted both chain collapse and the distribution of single- and multichain assemblies. Furthermore, both the conformational freedom of chain segments and local-scale, ß-sheet-like interactions were sensitive to the patchiness of FF. To connect sequence, structure, and target function, we evaluated an additional series of nine sequence-controlled copolymers as sequestrants for rare earth elements (REEs) by incorporating a functional acrylic acid monomer into select polymer scaffolds. We identified key sequence variables that influence the binding affinity, capacity, and selectivity of the polymers for REEs. Collectively, these results highlight the potential of and boundaries of sequence control via multiblock polymerizations to drive primary sequence ensembles hierarchical structures, and ultimately the functionality of compositionally identical polymeric materials.

Revisiting kinetic Monte Carlo algorithms for time-dependent processes: From open-loop control to feedback control.

Simulating stochastic systems with feedback control is challenging due to the complex interplay between the system's dynamics and the feedback-dependent control protocols. We present a single-step-trajectory probability analysis to time-dependent stochastic systems. Based on this analysis, we revisit several time-dependent kinetic Monte Carlo (KMC) algorithms designed for systems under open-loop-control protocols. Our analysis provides a unified alternative proof to these algorithms, summarized into a pedagogical tutorial. Moreover, with the trajectory probability analysis, we present a novel feedback-controlled KMC algorithm that accurately captures the dynamics systems controlled by an external signal based on the measurements of the system's state. Our method correctly captures the system dynamics and avoids the artificial Zeno effect that arises from incorrectly applying the direct Gillespie algorithm to feedback-controlled systems. This work provides a unified perspective on existing open-loop-control KMC algorithms and also offers a powerful and accurate tool for simulating stochastic systems with feedback control.

Investigating Fundamental Principles of Nonequilibrium Assembly Using Temperature-Sensitive Copolymers.

Both natural biomaterials and synthetic materials benefit from complex energy landscapes that provide the foundation for structure-function relationships and environmental sensitivity. Understanding these nonequilibrium dynamics is important for the development of design principles to harness this behavior. Using a model system of poly(ethylene glycol) methacrylate-based thermoresponsive lower critical solution temperature (LCST) copolymers, we explored the impact of composition and stimulus path on nonequilibrium thermal hysteretic behavior. Through turbidimetry analysis of nonsuperimposable heat-cool cycles, we observe that LCST copolymers show clear hysteresis that varies as a function of pendent side chain length and hydrophobicity. Hysteresis is further impacted by the temperature ramp rate, as insoluble states can be kinetically trapped under optimized temperature protocols. This systematic study brings to light fundamental principles that can enable the harnessing of out-of-equilibrium effects in synthetic soft materials.

Versatile Triphenylphosphine-Containing Polymeric Catalysts and Elucidation of Structure-Function Relationships.

Synthetic polymers are a modular solution to bridging the two most common classes of catalysts: proteins and small molecules. Polymers offer the synthetic versatility of small-molecule catalysts while simultaneously having the ability to construct microenvironments mimicking those of natural proteins. We synthesized a panel of polymeric catalysts containing a novel triphenylphosphine acrylamide monomer and investigated how their properties impact the rate of a model Suzuki-Miyaura cross-coupling reaction. Systematic variation of polymer properties, such as the molecular weight, functional density, and comonomer identity, led to tunable reaction rates and solvent compatibility, including full conversion in an aqueous medium. Studies with bulkier substrates revealed connections between polymer parameters and reaction conditions that were further elucidated with a regression analysis. Some connections were substrate-specific, highlighting the value of the rapidly tunable polymer catalyst. Collectively, these results aid in building structure-function relationships to guide the development of polymer catalysts with tunable substrates and environmental compatibility.

Geometric approach to nonequilibrium hasty shortcuts.

Complex and even non-monotonic responses to external control can be found in many thermodynamic systems. In such systems, nonequilibrium shortcuts can rapidly drive the system from an initial state to a desired final state. One example is the Mpemba effect, where preheating a system allows it to cool faster. We present nonequilibrium hasty shortcuts-externally controlled temporal protocols that rapidly steer a system from an initial steady state to a desired final steady state. The term "hasty" indicates that the shortcut only involves fast dynamics without relying on slow relaxations. We provide a geometric analysis of such shortcuts in the space of probability distributions by using timescale separation and eigenmode decomposition. We further identify the necessary and sufficient condition for the existence of nonequilibrium hasty shortcuts in an arbitrary system. The geometric analysis within the probability space sheds light on the possible features of a system that can lead to hasty shortcuts, which can be classified into different categories based on their temporal pattern. We also find that the Mpemba-effect-like shortcuts only constitute a small fraction of the diverse categories of hasty shortcuts. This theory is validated and illustrated numerically in the self-assembly model inspired by viral capsid assembly processes.

Lipid-dependent regulation of exocytosis in S. cerevisiae by OSBP homolog (Osh) 4.

Polarized exocytosis is an essential process in many organisms and cell types for correct cell division or functional specialization. Previous studies established that homologs of the oxysterol-binding protein (OSBP) in S. cerevisiae, which comprise the Osh protein family, are necessary for efficient polarized exocytosis by supporting a late post-Golgi step. We define this step as the docking of a specific sub-population of exocytic vesicles with the plasma membrane. In the absence of other Osh proteins, yeast Osh4p can support this process in a manner dependent upon two lipid ligands, PI4P and sterol. Osh6p, which binds PI4P and phosphatidylserine, is also sufficient to support polarized exocytosis, again in a lipid-dependent manner. These data suggest that Osh-mediated exocytosis depends upon lipid binding and exchange without a strict requirement for sterol. We propose a two-step mechanism for Osh protein-mediated regulation of polarized exocytosis by using Osh4p as a model. We describe a specific in vivo role for lipid binding by an OSBP-related protein (ORP) in the process of polarized exocytosis, guiding our understanding of where and how OSBP and ORPs may function in more complex organisms.

Navigating the Expansive Landscapes of Soft Materials: A User Guide for High-Throughput Workflows.

Synthetic polymers are highly customizable with tailored structures and functionality, yet this versatility generates challenges in the design of advanced materials due to the size and complexity of the design space. Thus, exploration and optimization of polymer properties using combinatorial libraries has become increasingly common, which requires careful selection of synthetic strategies, characterization techniques, and rapid processing workflows to obtain fundamental principles from these large data sets. Herein, we provide guidelines for strategic design of macromolecule libraries and workflows to efficiently navigate these high-dimensional design spaces. We describe synthetic methods for multiple library sizes and structures as well as characterization methods to rapidly generate data sets, including tools that can be adapted from biological workflows. We further highlight relevant insights from statistics and machine learning to aid in data featurization, representation, and analysis. This Perspective acts as a "user guide" for researchers interested in leveraging high-throughput screening toward the design of multifunctional polymers and predictive modeling of structure-property relationships in soft materials.