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At least 19 records

Nicotinamide Cofactor Biomimetics: Design and Structure Activity Relationships

Biocatalysis is an attractive methodology due to its sustainable metrics, combined with its vaunted regio-, chemo-, and stereoselectivity. Among biocatalysts, oxidoreductases catalyze redox transformations on a wide variety of substrates and are thus particularly attractive for synthetic applications. Many oxidoreductases depend on nicotinamide-based cofactors; however, the high cost and poor atom economy of such cofactors can negate the advantage of biosynthetic processes. The native cofactors (i.e., NADH or NADPH) can be replaced by nicotinamide cofactor biomimetics (NCBs) to address these issues. Additionally, NCBs can enhance enzyme activity due to structures with expanded redox properties. These capabilities open possibilities for reactivity and biorthogonality. Thus, the field has responded with new NCB structures, including variation in their electronic and molecular recognition properties. This perspective focuses on structure-activity relationships of simple NCBs, including their function, stability, and other properties, along with methods for their regeneration in biosynthesis.

agricultural chemistry↗

Designing Biomimetic, Dissipative Material Systems

Throughout human history, new materials have been the foundation of transformative technologies: from bronze, paper, and ceramics to steel, silicon, and polymers, each material has enabled far-reaching advances. Today, another new class of materials is emerging—one with both the potential to provide radically new functions and to challenge our notion of what constitutes a “material”. These materials would harvest, transduce, or dissipate energy to perform autonomous, dynamic functions that mimic the behaviors of living organisms. Herein, we discuss the challenges and benefits of creating “dissipative” materials that can potentially blur the boundaries between living and non-living matter.

36 MATERIALS SCIENCE↗

Utilizing Additive Manufacturing for Biomimetic Designs

Chronic kidney disease effects 15% of adult Americans. Current technology utilizes polymer membranes for separation of toxins and waste from the blood. Yet there still is room for development of new materials to improve anti-biofouling characteristics and able to filter a range of molecular weights. This short review describes nano-porous membranes for molecular separation as well as limitations with current membrane designs.

36 MATERIALS SCIENCE↗

Retrieval-Augmented Generation and LLM Agents for Biomimicry Design Solutions

We present BIDARA, a Bio-Inspired Design And Research Assistant, to address the complexity of biomimicry – the practice of designing modern-day engineering solutions inspired by biological phenomena. Large Language Models (LLMs) have been shown to act as sufficient general purpose task solvers, but they often hallucinate and fail in regimes that require domain-specific and up-to-date knowledge. We integrate Retrieval-Augmented Generation (RAG) and Reasoning-and-Action agents to aid LLMs in avoiding hallucination and utilizing updated knowledge during generation of biomimetic design solutions. We find that incorporating RAG increases the feasibility of the design solutions in both prompting and agent settings, and we use these findings to guide our ongoing work. To the extent of our knowledge, this is the first work that integrates and evaluates Retrieval-Augmented Generation within LLM-generated biomimetic design solutions.

biomimicry↗

Retrieval-Augmented Generation and LLM Agents for Biomimicry Design Solutions

We present BIDARA, a Bio-Inspired Design And Research Assistant, to address the complexity of biomimicry – the practice of designing modern-day engineering solutions inspired by biological phenomena. Large Language Models (LLMs) have been shown to act as sufficient general purpose task solvers, but they often hallucinate and fail in regimes that require domain-specific and up-to-date knowledge. We integrate Retrieval-Augmented Generation (RAG) and Reasoning-and-Action agents to aid LLMs in avoiding hallucination and utilizing updated knowledge during generation of biomimetic design solutions. We find that incorporating RAG increases the feasibility of the design solutions in both prompting and agent settings, and we use these findings to guide our ongoing work. To the extent of our knowledge, this is the first work that integrates and evaluates Retrieval-Augmented Generation within LLM-generated biomimetic design solutions.

biomimicry↗

Bioinspired design toward nanocellulose-based materials

Nature provides lots of inspiration for material and structural design for various applications. Deriving design principles from the investigation of nature can provide a rich source of inspiration for the development of multifunctional materials. The bioinspired design templates mainly include mussels, nacre, and various plant species. As a sustainable and renewable feedstock, nanocellulose can be used to fabricate advanced materials with multifunctional properties through bioinspired designs. However, challenges and opportunities remain for realizing the full potential in the design of novel materials. Here, this article reviewed recent development in the bioinspired nanocellulose based materials and their application. This article summarizes the functions (e.g., surface wetting) and applications (e.g., composite) of bioinspired nanocellulose-based materials. The bioinspired design templates are discussed along with strategies, advantages, and challenges to the development of synthetic mimics. Additionally, mechanisms and processes (e.g., chemical modification, self-assembly) leading to biomimetic design are discussed. Finally, future research directions and opportunities of bioinspired nanocellulose-based materials are highlighted.

36 MATERIALS SCIENCE↗

Functional Design of Peptide Materials Based on Supramolecular Cohesion

Peptide materials offer a broad platform to design biomimetic soft matter, and filamentous networks that emulate those in extracellular matrices and the cytoskeleton are among the important targets. Given the vast sequence space, a combination of computational approaches and readily accessible experimental techniques is required to design peptide materials efficiently. Here, we report here on a strategy that utilizes this combination to predict supramolecular cohesion within filaments of peptide amphiphiles, a property recently linked to supramolecular dynamics and consequently bioactivity. Using established coarse-grained simulations on 10,000 randomly generated peptide sequences, we identified 3500 likely to self-assemble in water into nanoscale filaments. Atomistic simulations of small clusters were used to further analyze this subset of sequences and identify mathematical descriptors that are predictive of intermolecular cohesion, which was the main purpose of this work. We arbitrarily selected a small cohort of these sequences for chemical synthesis and verified their fiber morphology. With further characterization, we were able to link the latent heat associated with fiber to micelle transitions, an indicator of cohesion and potential supramolecular dynamicity within the filaments, to calculated hydrogen bond densities in the simulation clusters. Based on validation from in situ synchrotron X-ray scattering and differential scanning calorimetry, we conclude that the phase transitions can be easily observed by very simple polarized light microscopy experiments. We are encouraged by the methodology explored here as a relatively low-cost and fast way to design potential functions of peptide materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational optimization of synthetic water channels.

Membranes for liquid and gas separations and ion transport are critical to water purification, osmotic energy generation, fuel cells, batteries, supercapacitors, and catalysis. Often these membranes lack pore uniformity and robustness under operating conditions, which can lead to a decrease in performance. The lack of uniformity means that many pores are non-functional. Traditional membranes overcome these limitations by using thick membrane materials that impede transport and selectivity, which results in decreased performance and increased operating costs. For example, limitations in membrane performance demand high applied pressures to deionize water using reverse osmosis. In contrast, cellular membranes combine high flux and selective transport using membrane-bound protein channels operating at small pressure differences. Pore size and chemistry in the cellular channels is defined uniformly and with sub-nanometer precision through protein folding. The thickness of these cellular membranes is limited to that of the cellular membrane bilayer, about 4 nm thick, which enhances transport. Pores in the cellular membranes are robust under operating conditions in the body. Recent efforts to mimic cellular water channels for efficient water deionization produced a significant advance in membrane function. The novel biomimetic design achieved a 10-fold increase in membrane permeability to water flow compared to commercial membranes and still maintained high salt rejection. Despite this success, there is a lack of understanding about why this membrane performs so well. To address this lack of knowledge, we used highperformance computing to interrogate the structural and chemical environments experienced by water and electrolytes in the newly created biomimetic membranes. We also compared the solvation environments between the biomimetic membrane and cellular water channels. These results will help inform future efforts to optimize and tune the performance of synthetic biomimetic membranes for applications in water purification, energy, and catalysis.

Rogers, David Michael↗

Artificial extracellular matrix scaffolds of mobile molecules enhance maturation of human stem cell-derived neurons

Human induced pluripotent stem cell (hiPSC) technologies offer a unique resource for modeling neurological diseases. However, iPSC models are fraught with technical limitations including abnormal aggregation and inefficient maturation of differentiated neurons. These problems are in part due to the absence of synergistic cues of the native extracellular matrix (ECM). We report on the use of three artificial ECMs based on peptide amphiphile (PA) supramolecular nanofibers. All nanofibers display the laminin-derived IKVAV signal on their surface but differ in the nature of their non-bioactive domains. Here, we find that nanofibers with greater intensity of internal supramolecular motion have enhanced bioactivity toward hiPSC-derived motor and cortical neurons. Proteomic, biochemical, and functional assays reveal that highly mobile PA scaffolds caused enhanced β1-integrin pathway activation, reduced aggregation, increased arborization, and matured electrophysiological activity of neurons. Our work highlights the importance of designing biomimetic ECMs to study the development, function, and dysfunction of human neurons.

60 APPLIED LIFE SCIENCES↗

Rational Design of Novel Biomimetic Sequence-Defined Polymers for Mineralization Applications

Silica biomineralization is a naturally occurring process, wherein organisms use proteins and other biological structures to direct the formation of complex, hierarchical nanostructures. Discovery and characterization of such proteins and their underlying mechanisms spurred significant efforts to identify routes for biomimetic mineralization that reproduce the exquisite shapes and size selectivities found in nature. A common strategy has been the use of short peptide sequences with chemistry mimicking those found in natural systems, such as the use of the silaffin-derived R5 peptide. While progress has been made using this approach, there are many limitations that have prevented breakthroughs in biomimicry. To advance our ability to use charged macromolecules for silica formation, we propose to use sequence-defined synthetic polymers known as peptoids, or N-substituted polyglycines, which present significant capability for the precise tuning of sequence and structure beyond what can often be achieved with peptides alone. This study presents a computationally predicted design of these polymers that leads to the controlled formation of silica nanomaterials. We investigate surface adsorption and the mineralization process through analysis of binding mechanisms and energetics of the R5 system. Next, we synthesized two R5-inspired peptoids and validated our prediction in the design of mineralization polymers through characterization using surface plasmon resonance and electron microscopy. Here, this computationally guided study holds great promise for designing new sequences with unprecedented control of the placement of chemical functional groups, thus allowing for further unraveling of silicification mechanisms and the eventual design of sequence-defined synthetic polymers leading to the predictive synthesis of nanostructured functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computer-aided design of stability enhanced nicotinamide cofactor biomimetics for cell-free biocatalysis

Cell-free biocatalysis (CFB) is an efficient and environmentally friendly method to synthesize molecules such as pharmaceuticals, biochemicals, and biofuels through the in vitro use of enzyme cascades. These enzymes often require redox cofactors to drive chemical reactions. Natural redox cofactors (NAD(P)H) are expensive to isolate, motivating synthetic nicotinamide cofactor biomimetics (NCBs) as a cost-effective solution. A select handful of NCBs have been identified as potential NAD(P)H alternatives with comparable or improved redox capabilities, however, they display a tendency to degrade in common buffers. In this study, a library of 132 NCB candidates is systematically generated, over 85% of which have not been characterized in the literature, to expand the diversity of currently explored NCBs. The decomposition mechanism of NCBs in phosphate is evaluated using density functional theory (DFT), revealing protonation at the nicotinamide C5 position as a reporter of cofactor stability. Based on this result, we trained a linear regression model on DFT calculated descriptors to predict NCB stability in phosphate buffer, achieving mean absolute error (MAE) and root mean squared error (RMSE) values within computational accuracy. Analysis of key atomic descriptors and qualitative trends in our dataset informed the design of novel NCB candidates we propose with optimized stability. This work enables researchers to predict the relative stability of NCBs before synthesis, thereby streamlining the process to make CFB more affordable and viable at industry scales.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Biomimetic catalysts responsive to specific chemical signals

Part 1. Design of Biomimetic Catalysts Based on Amphiphilic Systems The overall objective of our research is to create biomimetic catalysts from amphiphilic molecules. More specifically, we aim to create supramolecular systems that can be used to control the microenvironment around a catalytic center in a biomimetic fashion and apply the learning to construct supramolecular catalysts with novel functions found in enzymatic catalysts. We have prepared synthetic molecules (i.e., foldamers) that could fold into helical structures with nanometer-sized internal hydrophilic cavities. Cavities of this size are typically observed only in the tertiary and quaternary structures of proteins but were formed in our foldamer prepared in just a few steps from the monomer. Similar to many proteins, our foldamers displayed cooperativity in the folding/unfolding equilibrium and followed a two-state conformational transition. In addition, their conformational change could be triggered by solvent polarity, pH, or presence of metal ions and certain organic molecules. We studied their environmentally dependent conformational changes in solutions, surfactant micelles, and lipid bilayer membranes. Unlike conventional rigid supramolecular host, a foldamer undergoes conformational change during guest binding. Our study in the molecular recognition of an oligocholate host yielded some extremely exciting results. Cooperativity between host conformation and host–guest interactions was found to “magnify” weak binding interactions. In other words, since binding affinity is determined by the overall change of free energy during the binding, guest-induced conformational change of the host, whether near or far from the binding site, affects the binding. This study has strong implications in catalysis because enzymes have been hypothesized to harvest similar intramolecular forces to strengthen their binding with the transition state of an enzyme-catalyzed reaction. The supramolecular and amphiphilic principles used in the foldamer catalysts were extended to a few other systems, particularly to interfacially cross-linked reverse micelles and micelles. These features enabled unusual catalytic features such as basic/nucleophilic catalysis under acidic conditions. We were able to create highly active metal nanoclusters catalysts whose local environment could be tuned by the organic framework. We were even able to create a “catalytic nanomachine” that grabs the substrate to the encapsulated Au clusters, which efficiently convert the substrate to the product that is rapidly ejected due to its different binding properties. Our research has important impacts on fundamental and applied energy-related sciences. On the fundamental level, it tests important biocatalytic principles on relatively simple synthetic systems and is expected to afford deeper understanding of biological catalysis. On the practical level, the research is anticipated to lead to “smart” catalysts and open up exiting applications in chemical analysis, reaction control, and materials synthesis. Part 2. Electrochemical Reduction of CO₂ The primary objective of our research involving the electrochemical reduction of carbon dioxide is to apply a multidisciplinary approach toward developing a greater understanding of the problem of efficiently converting CO₂ to hydrocarbons through electrochemical routes. Our goal is to provide a better understanding of the principles that underlie the electrocatalytic reduction of CO₂ at electrode surfaces and the molecular pathways that lead to desired compounds. This understanding is essential for the design and development of new catalytic materials for the selective production of renewable feedstocks. The electrochemical reduction of CO₂ involves the formation of various reaction products and adsorbed intermediates whose distribution depends upon the nature of the electrode material and the electrochemical conditions, including applied potential, solvent, and electrolyte, used during reduction. Our efforts are focused on developing a detailed picture of how these various parameters impact the reaction pathway for CO₂ reduction and to tune this reaction to favor the formation of specific products by careful selection of electrode materials and reaction conditions. Our experimental plan includes a detailed examination of the electrode material as well as a quantitative evaluation of the reaction conditions using several in-situ analysis tools that give a direct measure of adsorbed and solution species that appear during CO₂ reduction. During the first year of funding for this aspect of the project, we have developed an on-line electrochemical measurement tool utilizing membrane-introduction mass spectrometry to detect reactions products directly during the electrochemical reduction of CO₂on various sputtered electrode materials. In addition, we have examined the role of a selection of different electrode compositions (including single component and binary electrodes) on product distributions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computationally designed coiled coil ‘bundlemers’ as model colloidal nanoparticles for solution assembly and materials design (Final Report)

As a collaborative team at the University of Delaware and the University of Pennsylvania, Kloxin, Pochan and Saven designed new biomimetic nanomaterials de novo, leveraging a variety of complementary areas of expertise: computational design of biopolymers (Saven at the University of Pennsylvania), and synthesis and characterization (Kloxin and Pochan at the University of Delaware). Overall activities included: sequence-specific peptide synthesis; covalent crosslinking; noncovalent assembly; site-specific functionalization; and nanostructural characterization using electron microscopy and solution-phase (x-ray and neutron) scattering. Using natural and non-natural amino acids, the team created modular, functional peptide building blocks for elaboration of new nanostructured materials. Ultimately, the development of robust peptide-based, building blocks provides tools for researchers to readily produce complex nanomaterial structures in a wide range of applications. The project had three, interconnecting goals in an effort to provide the broader scientific community with a new peptide-based paradigm for materials design and characterization. First, we further developed the coiled-coil bundle-based toolbox (otherwise known as the ‘bundlemer’ toolbox) via computational design with experimental bundle assembly verification. Second, we developed new uses of covalent interactions, in addition to desired physical (noncovalent) interactions, to assemble bundlemers into 1-D polymer chains with targeted chain rigidity, length, and dispersity. Thirds, we used the above designs to experimentally realize (physical or covalent) polymers to target the creation of liquid crystals or to realize interparticle assembly into nanoporous lattices. The close integration of the three groups was instrumental in success of the biomolecular materials design, formation, and understanding for future designs.

36 MATERIALS SCIENCE↗

Development of Integrated Biomimetic Framework with Intelligent Monitoring, Cognition and Decision Capabilities for Control of Advanced Energy Plants

The objective of the project entitled “Development of Integrated Biomimetic Framework with Intelligent Monitoring, Cognition, and Decision Capabilities for Control of Advanced Energy Plants” is to develop algorithms and methodologies for designing a biomimetic control system for optimal control of advanced energy plants. Traditionally, control systems have been designed based on assumed a priori knowledge of the process system. A number of variables are manipulated to accomplish disturbance rejection and/or servo control performance. While it is possible to adapt the process model based on available data, the control structure and the controllers rarely change. Thus, the knowledge learnt during process operation is lost or remains underutilized. In addition, the business models of today, especially for power plants, are rapidly changing. The power plant operators are being pushed to the edge due to the penetration of renewable energy derived power to the grid, the demand for high efficiency, ever-tightening environmental regulations, and requirements for increased plant availability. Thus, power plant operations need to be agile and should adapt quickly to the dynamic requirements. A number of characteristics distinguish biological systems from the traditional process control systems. Self-organization, distributed intelligence, adaptability, intelligent monitoring, cognition, and decision capabilities are some of the powerful characteristics of the biological world that can be effectively utilized in process control. At the top, the central nervous system (CNS) integrates the information from and coordinates the activities of all parts of the bodies (for bilaterian animals). Inspired by these distinct characteristics, this project seeks to develop methodologies and algorithms to accomplish: (i) self-organization of the control structure for maximizing the plant’s operating profit by mimicking the function of the cortical areas in the human brain, (ii) distributed and adaptive controllers that mimic the rule of pursuit present in ants, (iii) intelligent monitoring of the controllers powered with cognition and decision capabilities that mimic the artificial immune systems, and (iv) seamless coordination and integration in the control system that mimics the CNS.

20 FOSSIL-FUELED POWER PLANTS↗

Surface-Directed Assembly of Sequence-Defined Synthetic Polymers into Networks of Hexagonally Patterned Nanoribbons with Controlled Functionalities

The exquisite self-assembly of proteins and peptides in nature into highly ordered functional materials has inspired innovative approaches to biomimetic materials design and synthesis. Here we report the assembly of peptoids—a class of highly stable sequence-defined synthetic polymers—into biomimetic materials on mica surfaces. The assembling 12-mer peptoid contains alternating acidic and aromatic residues, and the presence of Ca2+ cations creates peptoid-peptoid and peptoid-mica interactions that drive assembly. In situ atomic force microscopy (AFM) shows that peptoids first assemble into discrete nanoparticles, these particles then transform into hexagonally-patterned nanoribbons on mica surfaces. AFM-based dynamic force spectroscopy (DFS) studies show that peptoid-mica interactions are much stronger than peptoidpeptoid interactions in the presence of Ca2+, illuminating the physical parameters that drive peptoid assembly. We further demonstrate the display of functional groups at the N-terminus of assembling peptoid sequence to produce biomimetic materials with similar hierarchical structures. This research demonstrates that surface-directed peptoid assembly can be used as a robust platform to develop biomimetic coating materials for applications.

Chen, Chun-Long↗