Assessing the Viability of Recovery of Hydroxycinnamic Acids from Lignocellulosic Biorefinery Alkaline Pretreatment Waste Streams
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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Structure-Based Rational Design of Two Enhanced Bacterial Lipocalin Blc Tags for Protein-PAINT Super
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Muslinkina, Liya↗
A family portrait of lanmodulin selectivity for enhanced rare-earth separations
Proteins offer a molecular design space to create bespoke ligands for the separation of critical metals like rare earth elements (REs). However, data-intensive approaches to tune metalloprotein selectivity are constrained by the low-throughput nature of existing characterization methods. Here we invented an assay called ‘SpyTag-Catcher Immobilization of Lanmodulin for Assaying Metal-Binding Selectivity’ (SpyCI-LAMBS) to measure metalloprotein selectivity en masse. This 96-format workflow was used to study the selectivity of 621 lanmodulin (LanM) orthologs for 15 REs, revealing eight distinct selectivity profiles based on sequence-to-function analyses. We discovered >200 LanMs with stronger selectivity against low-value LaIII relative to the prototypical LanM. This includes a LanM that can perform a challenging one-stage separation of PrIII from LaIII with up to >99.9 mol% purity and 83% yield. SpyCI-LAMBS is a powerful tool that can rapidly collect high-fidelity selectivity data to inform metal ion separations and machine-learning-assisted metalloprotein design.
59 BASIC BIOLOGICAL SCIENCES↗
Targeted sulfur(VI) fluoride exchange-mediated covalent modification of a tyrosine residue in the catalytic pocket of tyrosyl-DNA phosphodiesterase 1
Abstract Developing effective inhibitors of the DNA repair enzyme tyrosyl-DNA phosphodiesterase 1 (TDP1) has been challenging because of the enzyme shallow catalytic pocket and non-specific substrate binding interactions. Recently, we discovered a quinolone-binding hot spot in TDP1’s active site proximal to the evolutionary conserved Y204 and F259 residues that position DNA. Sulfur (VI) fluoride exchange (SuFEx) is a biocompatible click chemistry reaction that enables acylation of protein residues, including tyrosine. Selective protein modifications can provide insights into the biological roles of proteins and inform ligand design. As we report herein, we used SuFEx chemistries to prepare covalent TDP1-bound binders showing site-specific covalent bonds with Y204. Our work presents the first application of SuFEx chemistries to TDP1 ligands. It validates the ability to covalently modify specific TDP1 residues by designed targeting and adds to the chemical biology resource toolbox for studying TDP1.
Chemistry↗
Generating forces in confinement via polymerization
Understanding how to produce forces using biomolecular building blocks is essential for the development of adaptive synthetic cells and living materials. Here we ask whether a dynamic polymer system can generate deformation forces in soft shells by pure self-assembly, motivated by the fact that biological polymer networks like the cytoskeleton can exert forces, move objects, and deform membranes by simply growing, even in the absence of molecular motors. We address this question by investigating polymer force generation by varying the release rate, the structure, and the interactions of self-assembling monomers. First, we develop a toy computational model of polymerization in a soft elastic shell that reveals the emergence of spontaneous bundling which enhances shell deformation. We then extend our model to account more explicitly for monomer binding dynamics. We find that the rate at which monomers are released into the interior of the shell is a crucial parameter for achieving deformation through polymer growth. Lastly, we demonstrate that the introduction of multivalent particles that can join polymers can either improve or impede polymer performance, depending on the amount and on the structure of the multivalent particles. Our results provide guidance for the experimental realization of polymer systems that can perform work at the nanoscale, for example through rationally designed self-assembling proteins or nucleic acids.
Osmanović, Dino [University of California at Los A↗
DiB-splits: nature-guided design of a novel fluorescent labeling split system
Fluorogen-activating proteins (FAPs) are innovative fluorescent probes combining advantages of genetically-encoded proteins such as green fluorescent protein and externally added fluorogens that allow for highly tunable and on demand fluorescent signaling. Previously, a panel of green- and red-emitting FAPs has been created from bacterial lipocalin Blc (named DiBs). Here we present a rational design as well as functional and structural characterization of the first self-assembling FAP split system, DiB-splits. This new system decreases the size of the FAP label to ~8–12 kDa while preserving DiBs’ unique properties: strong increase in fluorescence intensity of the chromophore upon binding, binding affinities to the chromophore in nanomolar to low micromolar range, and high photostability of the protein-ligand complex. These properties allow for use of DiB-splits for wide-field, confocal, and super-resolution fluorescence microscopy. DiB-splits also represent an attractive starting point for further design of a protein-protein interaction detection system as well as novel FAP-based sensors.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Elucidating the origins of phycocyanobilin biosynthesis and phycobiliproteins
Terrestrial ecosystems and human societies depend on oxygenic photosynthesis, which began to reshape our atmosphere approximately 2.5 billion years ago. The earliest known organisms carrying out oxygenic photosynthesis are the cyanobacteria, which use large complexes of phycobiliproteins as light-harvesting antennae. Phycobiliproteins rely on phycocyanobilin (PCB), a linear tetrapyrrole (bilin) chromophore, as the light-harvesting pigment that transfers absorbed light energy from phycobilisomes to the chlorophyll-based photosynthetic apparatus. Cyanobacteria synthesize PCB from heme in two steps: A heme oxygenase converts heme into biliverdin IXα (BV), and the ferredoxin-dependent bilin reductase (FDBR) PcyA then converts BV into PCB. In the current work, we examine the origins of this pathway. We demonstrate that PcyA evolved from pre-PcyA proteins found in nonphotosynthetic bacteria and that pre-PcyA enzymes are active FDBRs that do not yield PCB. Pre-PcyA genes are associated with two gene clusters. Both clusters encode bilin-binding globin proteins, phycobiliprotein paralogs that we designate as BBAGs (bilin biosynthesis-associated globins). Some cyanobacteria also contain one such gene cluster, including a BBAG, two V4R proteins, and an iron–sulfur protein. Phylogenetic analysis shows that this cluster is descended from those associated with pre-PcyA proteins and that light-harvesting phycobiliproteins are also descended from BBAGs found in other bacteria. We propose that PcyA and phycobiliproteins originated in heterotrophic, nonphotosynthetic bacteria and were subsequently acquired by cyanobacteria.
59 BASIC BIOLOGICAL SCIENCES↗
Structure-based design of a strain transcending AMA1-RON2L malaria vaccine
Apical membrane antigen 1 (AMA1) is a key malaria vaccine candidate and target of neutralizing antibodies. AMA1 binds to a loop in rhoptry neck protein 2 (RON2L) to form the moving junction during parasite invasion of host cells, and this complex is conserved among apicomplexan parasites. AMA1-RON2L complex immunization achieves higher growth inhibitory activity than AMA1 alone and protects mice against Plasmodium yoelii challenge. Here, three single-component AMA1-RON2L immunogens were designed that retain the structure of the two-component AMA1-RON2L complex: one structure-based design (SBD1) and two insertion fusions. All immunogens elicited high antibody titers with potent growth inhibitory activity, yet these antibodies did not block RON2L binding to AMA1. The SBD1 immunogen induced significantly more potent strain-transcending neutralizing antibody responses against diverse strains of Plasmodium falciparum than AMA1 or AMA1-RON2L complex vaccination. This indicates that SBD1 directs neutralizing antibody responses to strain-transcending epitopes in AMA1 that are independent of RON2L binding. This work underscores the importance of neutralization mechanisms that are distinct from RON2 blockade. The stable single-component SBD1 immunogen elicits potent strain-transcending protection that may drive the development of next-generation vaccines for improved malaria and apicomplexan parasite control.
60 APPLIED LIFE SCIENCES↗
Leveraging Artificial Intelligence to Expedite Antibody Design and Enhance Antibody–Antigen Interactions
This perspective sheds light on the transformative impact of recent computational advancements in the field of protein therapeutics, with a particular focus on the design and development of antibodies. Cutting-edge computational methods have revolutionized our understanding of protein–protein interactions (PPIs), enhancing the efficacy of protein therapeutics in preclinical and clinical settings. Central to these advancements is the application of machine learning and deep learning, which offers unprecedented insights into the intricate mechanisms of PPIs and facilitates precise control over protein functions. Despite these advancements, the complex structural nuances of antibodies pose ongoing challenges in their design and optimization. Our review provides a comprehensive exploration of the latest deep learning approaches, including language models and diffusion techniques, and their role in surmounting these challenges. We also present a critical analysis of these methods, offering insights to drive further progress in this rapidly evolving field. The paper includes practical recommendations for the application of these computational techniques, supplemented with independent benchmark studies. These studies focus on key performance metrics such as accuracy and the ease of program execution, providing a valuable resource for researchers engaged in antibody design and development. Through this detailed perspective, we aim to contribute to the advancement of antibody design, equipping researchers with the tools and knowledge to navigate the complexities of this field.
59 BASIC BIOLOGICAL SCIENCES↗
Examining polymer‐protein biophysical interactions with small‐angle x‐ray scattering and quartz crystal microbalance with dissipation
Abstract Polymer‐protein hybrids can be deployed to improve protein solubility and stability in denaturing environments. While previous work used robotics and active machine learning to inform new designs, further biophysical information is required to ascertain structure–function behavior. Here, we show the value of tandem small‐angle x‐ray scattering (SAXS) and quartz crystal microbalance with dissipation (QCMD) experiments to reveal detailed polymer‐protein interactions with horseradish peroxidase (HRP) as a test case. Of particular interest was the process of polymer‐protein complex formation under thermal stress whereby SAXS monitors formation in solution while QCMD follows these dynamics at an interface. The radius of gyration ( R g ) of the protein as measured by SAXS does not change significantly in the presence of polymer under denaturing conditions, but thickness and dissipation changes were observed in QCMD data. SAXS data with and without thermal stress were utilized to create bead models of the potential complexes and denatured enzyme, and each model fit provided insight into the degree of interactions. Additionally, QCMD data demonstrated that HRP deforms by spreading upon surface adsorption at low concentration as shown by longer adsorption times and smaller frequency shifts. In contrast, thermally stressed and highly inactive HRP had faster adsorption kinetics. The combination of SAXS and QCMD serves as a framework for biophysical characterization of interactions between proteins and polymers which could be useful in designing polymer‐protein hybrids.
60 APPLIED LIFE SCIENCES↗
Artificial intelligence tools for enzyme engineering and metabolic engineering
Enzyme engineering and metabolic engineering drive innovation in energy biotechnology. In recent years, artificial intelligence (AI) has supported successful applications in designing effective enzymes and productive microbial cell factories. This review summarizes recent advances in enzyme redesign using protein language models, de novo enzyme design with generative models, and AI tools for engineering metabolism and related cellular phenotypes. Across these areas, AI models are shifting from single modality inputs to integrated representations of protein function, metabolic pathways, and cell states. We emphasize that unifying the diverse data representations across scales will be necessary for advancements in energy biotechnology.
Volk, Michael [Univ. of Illinois at Urbana-Champai↗
Multimerization of Ebola GPΔmucin on protein nanoparticle vaccines has minimal effect on elicitation of neutralizing antibodies
Ebola virus (EBOV), a member of the Filoviridae family of viruses and a causative agent of Ebola Virus Disease (EVD), is a highly pathogenic virus that has caused over twenty outbreaks in Central and West Africa since its formal discovery in 1976. The only FDA-licensed vaccine against Ebola virus, rVSV-ZEBOV-GP (Ervebo®), is efficacious against infection following just one dose. However, since this vaccine contains a replicating virus, it requires ultra-low temperature storage which imparts considerable logistical challenges for distribution and access. Additional vaccine candidates could provide expanded protection to mitigate current and future outbreaks. Here, we designed and characterized two multimeric protein nanoparticle subunit vaccines displaying 8 or 20 copies of GPΔmucin, a truncated form of the EBOV surface protein GP. Single-dose immunization of mice with GPΔmucin nanoparticles revealed that neutralizing antibody levels were roughly equivalent to those observed in mice immunized with non-multimerized GPΔmucin trimers. These results suggest that some protein subunit antigens do not elicit enhanced antibody responses when displayed on multivalent scaffolds and can inform next-generation design of stable Ebola virus vaccine candidates.
60 APPLIED LIFE SCIENCES↗
Enabling simultaneous photoluminescence spectroscopy and X-ray footprinting mass spectrometry to study protein conformation and interactions
A novel integrated hybrid spectroscopy and X-ray footprinting mass spectrometry system designed to study both global and local protein conformation and interactions simultaneously.
Gupta, Sayan [Molecular Biophysics and Integrated ↗
evSeq: Cost-Effective Amplicon Sequencing of Every Variant in a Protein Library
Widespread availability of protein sequence-fitness data would revolutionize both our biochemical understanding of proteins and our ability to engineer them. Unfortunately, even though thousands of protein variants are generated and evaluated for fitness during a typical protein engineering campaign, most are never sequenced, leaving a wealth of potential sequence-fitness information untapped. Primarily, this is because sequencing is unnecessary for many protein engineering strategies; the added cost and effort of sequencing is thus unjustified. It also results from the fact that, even though many lower cost sequencing strategies have been developed, they often require at least some sequencing or computational resources, both of which can be barriers to access. In this work, we present every variant sequencing (evSeq), a method and collection of tools/standardized components for sequencing a variable region within every variant gene produced during a protein engineering campaign at a cost of cents per variant. evSeq was designed to democratize low-cost sequencing for protein engineers and, indeed, anyone interested in engineering biological systems. Execution of its wet-lab component is simple, requires no sequencing experience to perform, relies only on resources and services typically available to biology labs, and slots neatly into existing protein engineering workflows. Analysis of evSeq data is likewise made simple by its accompanying software (found at github.com/fhalab/evSeq, documentation at fhalab.github.io/evSeq), which can be run on a personal laptop and was designed to be accessible to users with no computational experience. Here, low-cost and easy to use, evSeq makes collection of extensive protein variant sequence-fitness data practical.
59 BASIC BIOLOGICAL SCIENCES↗
Dynamic Interfacial Architectures: Cruciferin‐Stabilized Oil/Water Interfaces for Sustainable Emulsions
Stabilizing oil-water interfaces in emulsions by plant-based proteins provides sustainable and tunable ways for designing emulsions with specific properties, for food, healthcare, and pharmaceuticals. Cruciferin, a protein from rapeseed, has great potential as green emulsifier, but details about its structure and mobility at oil-water interfaces are largely unknown. Here, these properties are studied with small angle neutron and x-ray scattering, and neutron spin echo spectroscopy, analyzed by atomistic modelling of scattering curves and coarse-grained modelling, to gain insight into interface coverage, and molecular conformation and mobility at the interface. Cruciferin assumes trimeric conformations at the interface, as in solution, but with its protrusions from the central core of the subunits (“arms”) more compressed. Interfacial mobility is only marginally lower than in solution, indicating the arms still transiently extend and preserve a network, for the first time revealing the mechanism how cruciferin forms highly elastic 2d gel-like oil-water interfaces, as observed in macroscopic rheology. The high interfacial mobility may help in self-repairing non-stabilized interfacial fractions, reducing coalescence. These findings provide a deeper molecular level understanding of proteins at oil-water interfaces, which can stimulate development of new plant-based emulsion products, and contribute to the global protein transition.
cruciferin↗
Artificial intelligence–powered biofoundries for protein engineering and metabolic engineering
Synthetic biology is rapidly evolving through the integration of artificial intelligence (AI) and automated biofoundries. This convergence accelerates the design–build–test–learn cycle, shifting protein engineering and metabolic engineering from labor-intensive manual experimentation to autonomous experimentation. This review summarizes recent advances in workflow development, AI models, and their integration with biofoundries for automated or autonomous protein engineering and metabolic engineering. Particularly, we highlight the potential of AI-powered biofoundries for accelerated scientific discovery and innovation in synthetic biology.
Chen, Junyu [Univ. of Illinois at Urbana-Champaign↗
DNA Origami Incorporated into Solid-State Nanopores Enables Enhanced Sensitivity for Precise Analysis of Protein Translocations
The rapidly advancing field of nanotechnology is driving the development of precise sensing methods at the nanoscale, with solid-state nanopores emerging as promising tools for biomolecular sensing. Here, this study investigates the increased sensitivity of solid-state nanopores achieved by integrating DNA origami structures, leading to the improved analysis of protein translocations. Using holo human serum transferrin (holo-hSTf) as a model protein, we compared hybrid nanopores incorporating DNA origami with open solid-state nanopores. Results show a significant enhancement in holo-hSTf detection sensitivity with DNA origami integration, suggesting a unique role of DNA interactions beyond confinement. This approach holds potential for ultrasensitive protein detection in biosensing applications, offering advancements in biomedical research and diagnostic tool development for diseases with low-abundance protein biomarkers. Further exploration of origami designs and nanopore configurations promises even greater sensitivity and versatility in the detection of a wider range of proteins, paving the way for advanced biosensing technologies.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
Naegleria fowleri: Protein structures to facilitate drug discovery for the deadly, pathogenic free-living amoeba
Naegleria fowleri is a pathogenic, thermophilic, free-living amoeba which causes primary amebic meningoencephalitis (PAM). Penetrating the olfactory mucosa, the brain-eating amoeba travels along the olfactory nerves, burrowing through the cribriform plate to its destination: the brain’s frontal lobes. The amoeba thrives in warm, freshwater environments, with peak infection rates in the summer months and has a mortality rate of approximately 97%. A major contributor to the pathogen’s high mortality is the lack of sensitivity of N . fowleri to current drug therapies, even in the face of combination-drug therapy. To enable rational drug discovery and design efforts we have pursued protein production and crystallography-based structure determination efforts for likely drug targets from N . fowleri . The genes were selected if they had homology to drug targets listed in Drug Bank or were nominated by primary investigators engaged in N . fowleri research. In 2017, 178 N . fowleri protein targets were queued to the Seattle Structural Genomics Center of Infectious Disease (SSGCID) pipeline, and to date 89 soluble recombinant proteins and 19 unique target structures have been produced. Many of the new protein structures are potential drug targets and contain structural differences compared to their human homologs, which could allow for the development of pathogen-specific inhibitors. Five of the structures were analyzed in more detail, and four of five show promise that selective inhibitors of the active site could be found. The 19 solved crystal structures build a foundation for future work in combating this devastating disease by encouraging further investigation to stimulate drug discovery for this neglected pathogen.
59 BASIC BIOLOGICAL SCIENCES↗