Behavior of Protein-Inspired Synthetic Random Heteropolymers

Revealing the Folding of Single-Chain Polymeric Nanoparticles at the Atomistic Scale by Combining Computational Modeling and X-ray Scattering

Predicting 3D structures of synthetic heterograft polymers in solution starting from a chemical structure remains a great challenge. Here, we get grip on the 3D structures formed by amphiphilic, random heterograft polymers in water depending on the nature of the hydrophilic graft. Atomistic MD simulations in explicit water on a μs time scale show that large Jeffamine-based grafts combined with randomly distributed hydrophobic grafts induce the formation of worm-like structures with local hydrophobic domains. Replacing Jeffamine by glucose affords core-shell ellipsoidal structures. The simulated small-angle X-ray scattering (SAXS) curves from the simulation results show excellent agreement with experimental SAXS results for the Jeffamine-based copolymers. For the glucose-based copolymers, the experimental SAXS results also indicated the presence of core-shell structures, albeit that (some) multichain aggregation was present. Our work highlights that global conformations of very large heterograft polymers (up to ∼30,000 atoms) can now be studied with (accelerated) MD simulations at the atomic scale in solvent (up to 2.5 million atoms). This joint approach constitutes a reliable tool to understand the folding and possible aggregation behavior of heterograft polymers in solution, paving the way toward predictive modeling of nanoparticle structures from a polymer's chemical structure.

Pepticombisomes: Biomimetic Vesicles Crafted From Recombinant Supercharged Polypeptides with Uniformly Distributed Side-Chains

Cell membranes play a key role in bottom-up synthetic biology, as they enable interaction control, transport, and other essential functions. These ultra-thin, flexible, yet stable structures form through the self-assembly of lipids and proteins. While liposomes are common mimics, their synthetic membranes often fail to replicate natural properties due to poor structural control. To address this, pepticombs are introduced, a new family of supramolecular building blocks. They are synthesized by regularly appending anionic surfactants with lipid-long alkyl tails to cationic amino acid residues of recombinant elastin-like supercharged unfolded polypeptides (SUPs). Using microscopy techniques and molecular dynamics simulations, the formation of giant unilamellar vesicles, termed pepticombisomes, is demonstrated and their membrane properties are characterized. The molecular topology of pepticombs allows for precise mimicry of membrane thickness and flexibility, beyond classic polymersomes. Unlike the previously introduced ionically-linked comb polymers, all pepticombs exhibit a uniform degree of polymerization, composition, sequence, and spontaneous curvature. This uniformity ensures consistent hydrophobic tail distribution, facilitating intermolecular hydrogen bonding within the backbone. This generates elastic heterogeneities and the concomitant formation of non-icosahedral faceted vesicles, as previously predicted. Additionally, pepticombisomes can incorporate functional lipids, enhancing design flexibility.

Designing single-polymer-chain nanoparticles to mimic biomolecular hydration frustration

Native folded proteins rely on sculpting the local chemical environment of their active or binding sites, as well as their shapes, to achieve functionality. In particular, proteins use hydration frustration-control over the dehydration of hydrophilic residues and the hydration of hydrophobic residues-to amplify their chemical or binding activity. Here we uncover that single-polymer-chain nanoparticles formed by random heteropolymers comprising four or more components can display similar levels of hydration frustration. We categorize these nanoparticles into three types based on whether either hydrophobic or hydrophilic residues, or both types, display frustrated states. We propose a series of physicochemical rules that determine the state of these nanoparticles. We demonstrate the generality of these rules in atomistic and simplified Monte Carlo models of single-polymer-chain nanoparticles with different backbones and residues. Our work provides insights into the design of single-chain nanoparticles, an emerging polymer modality that achieves the ease and cost of fabrication of polymeric material with the functionality of biological proteins.

Sequence-Sensitivity in Functional Synthetic Polymer Properties

Recently, a new class of synthetic methyl methacrylate-based random heteropolymers (MMA-based RHPs) has displayed protein-like properties. Their function appears to be insensitive to the precise sequence. Here, through atomistic molecular dynamics simulation, we show that there are universal protein-like features of MMA-based RHPs that are insensitive to the sequence, and mostly depend on the overall composition. In particular, we find that MMA-based RHPs "fold" into globules with heterogeneous hydration patterns. However, the insensitivity to sequence identity observed in MMA-based RHPs dramatically changes when we substitute the backbone architecture with acrylate or replace the oxygen atom in the side chain with a nitrogen atom (methacrylamide or acrylamide). In such scenarios, the sequence contributes significantly to the compactness and the hydration of monomers. Using principal component analysis and an intersection-over-union based index, we demonstrate that different sequences may not overlap in the property space, meaning that their properties are controlled by the sequence rather than fixed composition. We further investigate the sequence-insensitive capability of the MMA-based RHPs as previously reported on bacterial phospholipase OmpLA stabilization through heterodimerization. As experimentally observed, such polymers enhance the stability of OmpLA as reliably as its native bilayer environment. The design of such MMA-based RHPs provides a sequence-insensitive alternative to protein-mimetic biomaterials that is orthogonal to the sequence-structure-function paradigm of proteins.

RAFT Polymerization for Advanced Morphological Control: From Individual Polymer Chains to Bulk Materials

Control of the morphology of polymer systems is achieved through reversible-deactivation radical polymerization techniques such as Reversible Addition-Fragmentation chain Transfer (RAFT). Advanced RAFT techniques offer much more than just "living" polymerization - the RAFT toolkit now enables morphological control of polymer systems across many decades of length-scale. Morphological control is explored at the molecular-level in the context of syntheses where individual monomer unit insertion provides sequence-defined polymers (single unit monomer insertion, SUMI). By being able to define polymer architectures, the synthesis of bespoke shapes and sizes of nanostructures becomes possible by leveraging self-assembly (polymerization induced self-assembly, PISA). Finally, it is seen that macroscopic materials can be produced with nanoscale detail, based on phase-separated nanostructures (polymerization induced microphase separation, PIMS) and microscale detail based on 3D-printing technologies. RAFT control of morphology is seen to cross from molecular level to additive manufacturing length-scales, with complete morphological control over all length-scales.

Degradable poly(β-amino ester) microparticles for cleansing products and food fortification

Microplastic pollution is a pressing global crisis caused by the extensive use of nondegradable microplastic materials in daily activities. One effective approach to mitigate this issue is to replace nondegradable plastics with degradable materials that have properties amendable for targeted applications. Here we present the development of a degradable microparticle (MP) platform based on a poly(β-amino ester) (PAE) that degrades into sugar and amino acid derivatives. This PAE MP platform showed functional replacement of nondegradable microplastics used in cleansing products and food fortification. In cleansing products, PAE MPs effectively enhanced the cleansing efficiency of a representative rinse-off product and showed effective removal of potentially toxic elements, as an alternative of traditional nondegradable microbeads. In food fortification, PAE MPs provided robust protection for multiple essential vitamins and minerals against extensive cooking and storage conditions with rapid nutrient release in a simulated human digestion system. Collectively, these PAE MPs present a potential platform to replace microplastic usage on a global scale in many applications.

Polymers for Disrupting Protein-Protein Interactions: Where Are We and Where Should We Be?

Protein-protein interactions (PPIs) are central to the cellular signaling and regulatory networks that underlie many physiological and pathophysiological processes. It is challenging to target PPIs using traditional small molecule or peptide-based approaches due to the frequent lack of well-defined binding pockets at the large and flat PPI interfaces. Synthetic polymers offer an opportunity to circumvent these challenges by providing unparalleled flexibility in tuning their physiochemical properties to achieve the desired binding properties. In this review, we summarize the current state of the field pertaining to polymer-protein interactions in solution, highlighting various polyelectrolyte systems, their tunable parameters, and their characterization. We provide an outlook on how these architectures can be improved by incorporating sequence control, foldability, and machine learning to mimic proteins at every structural level. Advances in these directions will enable the design of more specific protein-binding polymers and provide an effective strategy for targeting dynamic proteins, such as intrinsically disordered proteins.

Statistical Copolymerization-Induced Self-Assembly

Statistical copolymers have been extensively used in chemical industries and our daily lives, owing to their ease of synthesis and functionalization. However, self-assembly based on statistical copolymers has been haunted by high interfacial energy, poor stability, and low concentration. We proposed the statistical copolymerization-induced self-assembly (stat-PISA) as a general strategy for one-step preparing stable statistical copolymer assemblies with high solids content. The concept was demonstrated through a model dispersion polymerization system comprising a charged hydrophilic monomer and a core-forming monomer, producing spherical micelles via a spinodal decomposition mechanism with an interconnected network intermediate. The stat-PISA was tunable by varying the fraction of charged monomer, the polymer chain length, and the solids content. The statistical copolymer micelles were demonstrated to be a potential Pickering emulsifier with superior stabilizing performances compared to their block copolymer counterparts. The general applicability of stat-PISA was demonstrated by preparing statistical copolymer assemblies with varying surface charges and chemical compositions. Particularly, this strategy is feasible for conventional free radical polymerization, promising for industrial scale-up.

Four-Component Statistical Copolymers by RAFT Polymerization

This manuscript serves as the starting point for in-depth research of multicomponent, statistical, methacrylate-based copolymers that potentially mimic the behavior of proteins in aqueous solutions. These synthetic macromolecules are composed of specially chosen comonomers: methacrylic acid (MAA), oligoethylene glycol methyl ether methacrylate (OEGMA475), 2-(dimethylamino)ethyl methacrylate (DMAEMA) and benzyl methacrylate (BzMA). Monomer choice was based on factors such as the chemical nature of pendant functional groups, the polyelectrolyte/polyampholyte and amphiphilic character and the overall hydrophobic-hydrophilic balance (HLB) of the obtained quaterpolymers. Their synthesis was achieved via a one-pot reversible addition fragmentation chain transfer (RAFT) polymerization in two distinct compositions and molecular architectures, linear and hyperbranched, respectively, in order to explore the effects of macromolecular topology. The resulting statistical quaterpolymers were characterized via 1H-NMR and ATR-FTIR spectroscopies. Their behavior in aqueous solutions was studied by dynamic (DLS) and electrophoretic light scattering (ELS) and fluorescence spectroscopy (FS), producing vital information concerning their self-assembly and the structure of the formed aggregates. The physicochemical studies were extended by tuning parameters such as the solution pH and ionic strength. Finally, the quaterpolymer behavior in FBS/PBS solutions was investigated to test their colloid stability and biocompatibility in an in vivo-mimicking, biological fluid environment.

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.

Data-Driven Design of Polymer-Based Biomaterials: High-throughput Simulation, Experimentation, and Machine Learning

Polymers, with the capacity to tunably alter properties and response based on manipulation of their chemical characteristics, are attractive components in biomaterials. Nevertheless, their potential as functional materials is also inhibited by their complexity, which complicates rational or brute-force design and realization. In recent years, machine learning has emerged as a useful tool for facilitating materials design via efficient modeling of structure-property relationships in the chemical domain of interest. In this Spotlight, we discuss the emergence of data-driven design of polymers that can be deployed in biomaterials with particular emphasis on complex copolymer systems. We outline recent developments, as well as our own contributions and takeaways, related to high-throughput data generation for polymer systems, methods for surrogate modeling by machine learning, and paradigms for property optimization and design. Throughout this discussion, we highlight key aspects of successful strategies and other considerations that will be relevant to the future design of polymer-based biomaterials with target properties.

Optical sequencing of single synthetic polymers

Microscopic sequences of synthetic polymers play crucial roles in the polymer properties, but are generally unknown and inaccessible to traditional measurements. Here we report real-time optical sequencing of single synthetic copolymer chains under living polymerization conditions. We achieve this by carrying out multi-colour imaging of polymer growth by single catalysts at single-monomer resolution using CREATS (coupled reaction approach toward super-resolution imaging). CREATS makes a reaction effectively fluorogenic, enabling single-molecule localization microscopy of chemical reactions at higher reactant concentrations. Our data demonstrate that the chain propagation kinetics of surface-grafted polymerization contains temporal fluctuations with a defined memory time (which can be attributed to neighbouring monomer interactions) and chain-length dependence (due to surface electrostatic effects). Furthermore, the microscopic sequences of individual copolymers reveal their tendency to form block copolymers, and, more importantly, quantify the size distribution of individual blocks for comparison with theoretically random copolymers. Such sequencing capability paves the way for single-chain-level structure-function correlation studies of synthetic polymers.

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.

A synergistic investigation of azo-thiazole derivatives incorporating thiazole moieties: a comprehensive exploration of their synthesis, characterization, computational insights, solvatochromism, and multimodal biological activity assessment

In the present study, a novel series of azo-thiazole derivatives (3a-c) containing a thiazole moiety was successfully synthesized. The structure of these derivatives was examined by spectroscopic techniques, including 1H NMR, 13C NMR, FT-IR, and HRMS. Further, the novel synthesized compounds were evaluated for their in vitro biological activities, such as antibacterial and anti-inflammatory activities, and an in silico study was performed. The antibacterial results demonstrated that compounds 3a and 3c (MIC = 10 μg mL-1) have a notable potency against Staphylococcus aureus compared to azithromycin (MIC = 40 μg mL-1). Alternatively, compound 3b displayed a four-fold higher potency (24 recovery days, 1.83 mg day-1) than Hamazine (28 recovery days, 4.14 mg day-1) in promoting burn wound healing, and it also exhibited a comparable inhibitory activity against screened bacterial pathogens compared to the reference drug. Docking on 1KZN, considering the excellent impact of compounds on the crystal structure of E. coli1KZN, a 24 kDa domain, in complex with clorobiocin, indicated the close binding of compounds 3a-c with the active site of the 1KZN protein, which is consistent with their observed biological activity. Additionally, we conducted molecular dynamics simulations on the docked complexes of compounds 3a-c with 1KZN retrieved from the PDB to assess their stability and molecular interactions. Furthermore, we assessed their electrochemical characteristics via DFT calculations. Employing PASS and pkCSM platforms, we gained insights into controlling the bioactivity and physicochemical features of these compounds, highlighting their potential as new active agents.

Dynamic transformation of bio-inspired single-chain nanoparticles at interfaces

The interfacial behavior of macromolecules dictates their intermolecular interactions, which can impact the processing and application of polymers for pharmaceutical and synthetic use. Using molecular dynamics simulations, we observe the evolution of a random heteropolymer in the presence of liquid-liquid interfaces. The system of interest forms single-chain nanoparticles through hydrophobic collapse in water, lacking permanent crosslinks and making their morphology mutable in new environments. Complex amphiphilic polymers are shown to be capable of stabilizing high interfacial tension water-hexane interfaces, often unfolding to maximize surface coverage. Despite drastic changes to polymer conformation, monomer presence in the water phase is generally maintained and most changes are due to increased hydrophobic solvent exposure toward the oil phase. These results are then compared to the behavior at the water-graphene interface, where the macromolecules adsorb but do not remodel. The polymer's behavior is shown to depend significantly on both its own amphiphilic character and the deformability of the interface.

Ensembles of synthetic polymers mimic biological fluids

Recently a report by Ruan et al. in Nature described how relatively simple random heteropolymers can replicate the properties of biological fluids. These polymers capture the segmental-level interactions between proteins and could enhance folding of membrane proteins, improve stability, and enable DNA sequestration in a chemistry specific manner.

Protein-Inspired Control over Synthetic Polymer Folding for Structured Functional Nanoparticles in Water

The folding of proteins into functional nanoparticles with defined 3D structures has inspired chemists to create simple synthetic systems mimicking protein properties. The folding of polymers into nanoparticles in water proceeds via different strategies, resulting in the global compaction of the polymer chain. Herein, we review the different methods available to control the conformation of synthetic polymers and collapse/fold them into structured, functional nanoparticles, such as hydrophobic collapse, supramolecular self-assembly, and covalent cross-linking. A comparison is made between the design principles of protein folding to synthetic polymer folding and the formation of structured nanocompartments in water, highlighting similarities and differences in design and function. We also focus on the importance of structure for functional stability and diverse applications in complex media and cellular environments.

Population-based heteropolymer design to mimic protein mixtures

Biological fluids, the most complex blends, have compositions that constantly vary and cannot be molecularly defined1. Despite these uncertainties, proteins fluctuate, fold, function and evolve as programmed2-4. We propose that in addition to the known monomeric sequence requirements, protein sequences encode multi-pair interactions at the segmental level to navigate random encounters5,6; synthetic heteropolymers capable of emulating such interactions can replicate how proteins behave in biological fluids individually and collectively. Here, we extracted the chemical characteristics and sequential arrangement along a protein chain at the segmental level from natural protein libraries and used the information to design heteropolymer ensembles as mixtures of disordered, partially folded and folded proteins. For each heteropolymer ensemble, the level of segmental similarity to that of natural proteins determines its ability to replicate many functions of biological fluids including assisting protein folding during translation, preserving the viability of fetal bovine serum without refrigeration, enhancing the thermal stability of proteins and behaving like synthetic cytosol under biologically relevant conditions. Molecular studies further translated protein sequence information at the segmental level into intermolecular interactions with a defined range, degree of diversity and temporal and spatial availability. This framework provides valuable guiding principles to synthetically realize protein properties, engineer bio/abiotic hybrid materials and, ultimately, realize matter-to-life transformations.

Sequence Design of Random Heteropolymers as Protein Mimics

Random heteropolymers (RHPs) have been computationally designed and experimentally shown to recapitulate protein-like phase behavior and function. However, unlike proteins, RHP sequences are only statistically defined and cannot be sequenced. Recent developments in reversible-deactivation radical polymerization allowed simulated polymer sequences based on the well-established Mayo-Lewis equation to more accurately reflect ground-truth sequences that are experimentally synthesized. This led to opportunities to perform bioinformatics-inspired analysis on simulated sequences to guide the design, synthesis, and interpretation of RHPs. We compared batches on the order of 10000 simulated RHP sequences that vary by synthetically controllable and measurable RHP characteristics such as chemical heterogeneity and average degree of polymerization. Our analysis spans across 3 levels: segments along a single chain, sequences within a batch, and batch-averaged statistics. We discuss simulator fidelity and highlight the importance of robust segment definition. Examples are presented that demonstrate the use of simulated sequence analysis for in-silico iterative design to mimic protein hydrophobic/hydrophilic segment distributions in RHPs and compare RHP and protein sequence segments to explain experimental results of RHPs that mimic protein function. To facilitate the community use of this workflow, the simulator and analysis modules have been made available through an open source toolkit, the RHPapp.

Biomimetic Artificial Proton Channels

One of the most common biochemical processes is the proton transfer through the cell membranes, having significant physiological functions in living organisms. The proton translocation mechanism has been extensively studied; however, mechanistic details of this transport are still needed. During the last decades, the field of artificial proton channels has been in continuous growth, and understanding the phenomena of how confined water and channel components mediate proton dynamics is very important. Thus, proton transfer continues to be an active area of experimental and theoretical investigations, and acquiring insights into the proton transfer mechanism is important as this enlightenment will provide direct applications in several fields. In this review, we present an overview of the development of various artificial proton channels, focusing mostly on their design, self-assembly behavior, proton transport activity performed on bilayer membranes, and comparison with protein proton channels. In the end, we discuss their potential applications as well as future development and perspectives.

Solvent Remodeling in Single-Chain Amphiphilic Heteropolymer Systems

This work demonstrates the remodeling of single-chain nanoparticles (SCNPs) upon a transition to organic solvent through molecular dynamics simulations. Methacrylate-based random heteropolymers (RHPs), assembled via transient non-covalent linkages in water, have shown promise in an assortment of applications that harness their bio-inspired properties. While their molecular behavior has been broadly characterized in aqueous environments, many newer applications include the use of organic solvent rather than bio-mimetic conditions. The polymer assemblies, typically driven by the hydrophobic effect in water, are less well understood in non-aqueous solution. Here, a specific RHP system is examined which forms compact globular morphologies in highly polar or highly non-polar environments while adopting extended conformations in solvents of intermediate polarity. The pivotal role of electrostatic interactions between charge groups in low dielectric mediums is also observed. Finally, high temperature anneal cycles are compared to room temperature transformations to illuminate barriers to remodeling upon environmental changes. This article is protected by copyright. All rights reserved.

Origin of Proteolytic Stability of Peptide-Brush Polymers as Globular Proteomimetics

Peptide-brush polymers (PBPs), wherein every side-chain of the polymers is peptidic, represent a new class of proteomimetic with unusually high proteolytic resistance while maintaining bioactivity. Here, we sought to determine the origin of this behavior and to assess its generality via a combined theory and experimental approach. A series of PBPs with various polymer backbone structures were prepared and examined for their proteolytic stability and bioactivity. We discovered that an increase in the hydrophobicity of the polymer backbones is predictive of an elevation in proteolytic stability of the side-chain peptides. Computer simulations, together with small-angle X-ray scattering (SAXS) analysis, revealed globular morphologies for these polymers, in which pendant peptides condense around hydrophobic synthetic polymer backbones driven by the hydrophobic effect. As the hydrophobicity of the polymer backbones increases, the extent of solvent exposure of peptide cleavage sites decreases, reducing their accessibility to proteolytic enzymes. This study provides insight into the important factors driving PBP aqueous-phase structures to behave as globular, synthetic polymer-based proteomimetics.