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

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.

Bayesian optimization of glycopolymer structures for the interaction with cholera toxin B subunit

The optimal structure of synthetic glycopolymers for GM1 mimetics was determined through Bayesian optimization. The interactions of glycopolymers carrying galactose and neuraminic acid units in different compositions with cholera toxin B subunit (CTB) were assessed by an enzyme-linked immunosorbent assay (ELISA). Gaussian process regression, using the ELISA results, predicted the composition of glycopolymers that would exhibit stronger interactions with CTB. Following five cycles of optimization, the glycopolymers carrying 60 mol% galactose and 25 mol% neuraminic acid demonstrated an IC50 value of 75 μM for CTB, representing the lowest value among the synthesized glycopolymers.

Mapping Composition Evolution through Synthesis, Purification, and Depolymerization of Random Heteropolymers

Random heteropolymers (RHPs) consisting of three or more comonomers have been routinely used to synthesize functional materials. While increasing the monomer variety diversifies the side-chain chemistry, this substantially expands the sequence space and leads to ensemble-level sequence heterogeneity. Most studies have relied on monomer composition and simulated sequences to design RHPs, but the questions remain unanswered regarding heterogeneities within each RHP ensemble and how closely these simulated sequences reflect the experimental outcomes. Here, we quantitatively mapped out the evolution of monomer compositions in four-monomer-based RHPs throughout a design-synthesis-purification-depolymerization process. By adopting a Jaacks method, we first determined 12 reactivity ratios directly from quaternary methacrylate RAFT copolymerization experiments to account for the influences of competitive monomer addition and the reversible activation/deactivation equilibria. The reliability of in silico analysis was affirmed by a quantitative agreement (<4% difference) between the simulated RHP compositions and the experimental results. Furthermore, we mapped out the conformation distribution within each ensemble in different solvents as a function of monomer chemistry, composition, and segmental characteristics via high-throughput computation based on self-consistent field theory (SCFT). These comprehensive studies confirmed monomer composition as a viable design parameter to engineer RHP-based functional materials as long as the reactivity ratios are accurately determined and the livingness of RHP synthesis is ensured.

Enhanced Efficiency of Pd(0)-Based Single Chain Polymeric Nanoparticles for in Vitro Prodrug Activation by Modulating the Polymer's Microstructure

Bioorthogonal catalysis employing transition metal catalysts is a promising strategy for the in situ synthesis of imaging and therapeutic agents in biological environments. The transition metal Pd has been widely used as a bioorthogonal catalyst, but bare Pd poses challenges in water solubility and catalyst stability in cellular environments. In this work, Pd(0) loaded amphiphilic polymeric nanoparticles are applied to shield Pd in the presence of living cells for the in situ generation of a fluorescent dye and anticancer drugs. Pd(0) loaded polymeric nanoparticles prepared by the reduction of the corresponding Pd(II)-polymeric nanoparticles are highly active in the deprotection of pro-rhodamine dye and anticancer prodrugs, giving significant fluorescence enhancement and toxigenic effects, respectively, in HepG2 cells. In addition, we show that the microstructure of the polymeric nanoparticles for scaffolding Pd plays a critical role in tuning the catalytic efficiency, with the use of the ligand triphenylphosphine as a key factor for improving the catalyst stability in biological environments.

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.