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At least 145 records · Page 8

Crystallography Reveals Metal‐Triggered Restructuring of β‐Hairpins

Abstract Metal binding to β‐sheets occurs in many metalloproteins and is also implicated in the pathology of Alzheimer's disease. De novo designed metallo‐β‐sheets have been pursued as models and mimics of these proteins. However, no crystal structures of canonical β‐sheet metallopeptides have yet been obtained, in stark contrast to many examples for ɑ‐helical metallopeptides, leading to a poor understanding for their chemistry. To address this, we have engineered tryptophan zippers, stable 12‐residue β‐sheet peptides, to bind Cu(II) ions and obtained crystal structures through single crystal X‐ray diffraction (SC‐XRD). We find that metal binding triggers several unexpected supramolecular assemblies that demonstrate the range of higher‐order structures available to metallo‐β‐sheets. Overall, these findings underscore the importance of crystallography in elucidating the rich structural landscape of metallo‐β‐sheet peptides.

Thuc Dang, Viet↗

Efficient genetic code expansion tools enable in vivo study of lysine acetylation in non-model bacteria

Recent proteomic advancements have revealed widespread Nε-lysine acetylation in pathways governing pathogenicity, metabolism, and antibiotic resistance in bacteria. The spontaneous, non-specific nature of this modification in prokaryotes obscures its biological role, necessitating prokaryotic specific in vivo interrogation systems. Genetic Code Expansion (GCE) offers a powerful method to investigate the roles and regulation dynamics of acetyl-lysine in vivo with the precise incorporation of a suite of non-canonical amino acids, including acetyl-lysine analogs. However, its use has been largely restricted to E. coli strains due to challenges associated with implementation and optimization of the technology in more diverse bacterial strains. Here, we present a bacterial host-agnostic, readily optimizable GCE platform designed to site-specifically incorporate non-canonical amino acids into target proteins within living bacteria. We further demonstrate the versatility of this technology by showcasing, for the first time, the successful incorporation of acetyl-lysine in a non- E. coli bacterium.

59 BASIC BIOLOGICAL SCIENCES↗

Random heteropolymers as enzyme mimics

Despite successes in replicating the primary–secondary–tertiary structure hierarchy of protein, it remains elusive to synthetically materialize protein functions that are deeply rooted in their chemical, structural and dynamic heterogeneities. We propose that for polymers with backbone chemistries different from that of proteins, programming spatial and temporal projections of sidechains at the segmental level can be effective in replicating protein behaviours; and leveraging the rotational freedom of polymer can mitigate deficiencies in monomeric sequence specificity and achieve behaviour uniformity at the ensemble level. Here, guided by the active site analysis of about 1,300 metalloproteins, we design random heteropolymers (RHPs) as enzyme mimics based on one-pot synthesis. We introduce key monomers as the equivalents of the functional residues of protein and statistically modulate the chemical characteristics of key monomer-containing segments, such as segmental hydrophobicity. The resultant RHPs form pseudo-active sites that provide key monomers with protein-like microenvironments, co-localize substrates with catalytic or cofactor-binding sidechains and catalyse reactions such as oxidation and cyclization of citronellal with isopulegol/menthoglycol selectivity. This RHP design led to enzyme-like materials that can retain catalytic activity under non-biological conditions, are compatible with scalable processing and have expanded substrate scope, including environmentally long-lasting antibiotic tetracycline.

36 MATERIALS SCIENCE↗

Design and Function of α-Helix-Rich, Heme-Binding Peptide Materials

Peptide materials often employ short peptides that self-assemble into unique nanoscale architectures and have been employed across many fields relevant to medicine and energy. A majority of peptide materials are high in beta-sheet, secondary structure content, including heme-binding peptide materials. To broaden the structural diversity of heme-binding peptide materials, a small series of peptides were synthesized to explore the design criteria required for (1) folding into an alpha-helix structure, (2) assembling into a nanoscale material, (3) binding heme, and (4) demonstrating functions similar to that of heme proteins. One peptide was identified to meet all four criteria, including the heme protein function of CO binding and its microsecond-to-millisecond recombination rates, as measured by transient absorption spectroscopy. In conclusion, implications of new design criteria and peptide material function through heme incorporation are discussed.

59 BASIC BIOLOGICAL SCIENCES↗

Automated Strain Construction for Biosynthetic Pathway Screening in Yeast

Automation accelerates the Design-Build-Test-Learn (DBTL) cycle for synthetic biology; however, most strain construction pipelines lack robotic integration. Here, in this study, we present the workflow design and source code for a modular, integrated protocol that automates the Build step in Saccharomyces cerevisiae. We programmed the Hamilton Microlab VANTAGE to integrate off-deck hardware via its central robotic arm, enabling automated steps that increased throughput to 2,000 transformations per week. We developed a user interface with the Hamilton VENUS software to support on-demand parameter customization. As a proof of concept, we screened a gene library in an engineered yeast strain producing verazine, a key intermediate in the biosynthesis of steroidal alkaloids. Our pipeline rapidly identified pathway bottlenecks and genes that enhanced verazine production by 2.0- to 5-fold. This technical note provides resources for synthetic biologists designing yeast workflows for biofoundries to screen libraries for pathway discovery/optimization, combinatorial biosynthesis, and protein engineering.

automation↗

Sequence-based generative AI design of versatile tryptophan synthases

Enzymes are powerful and sustainable catalysts, but their widespread application is limited by the difficulty of identifying functional starting points for optimization, creating a major bottleneck in early- stage biocatalyst discovery. Designing libraries of such starting enzymes remains particularly challenging. Here, we use the GenSLM protein language model to generate novel β-subunit of tryptophan synthase (TrpB) enzymes that express in Escherichia coli and are both stable and catalytically active. Many generated TrpBs also display significant substrate promiscuity, outperforming their natural counterparts on non-native substrates. Some even surpass laboratory-evolved TrpBs. Comparison of the most-active and most-promiscuous generated TrpB to its closest natural homolog confirms that the enhanced versatility is absent from the natural enzyme, highlighting the creative potential of generative models. These results demonstrate that the generated TrpBs not only preserve natural structure and function but also acquire non-natural properties, establishing generative models as powerful tools for biocatalyst discovery and engineering.

biocatalysis↗

A protective and broadly binding antibody class engages the influenza virus hemagglutinin head at its stem interface

ABSTRACT Influenza infection and vaccination impart strain-specific immunity that protects against neither seasonal antigenic variants nor the next pandemic. However, antibodies directed to conserved sites can confer broad protection. Here, we identify and characterize a class of human antibodies that engage a previously undescribed, conserved epitope on the influenza hemagglutinin (HA) protein. Prototype antibody S8V1-157 binds at the normally occluded interface between the HA head and stem. Antibodies to this HA head–stem interface epitope are non-neutralizingin vitrobut protect against lethal influenza infection in mice. These antibodies bind to most influenza A subtypes and seasonal human variants, and are present at low frequencies in the memory B cell populations of multiple human donors. Vaccines designed to elicit these antibodies might contribute to “universal” influenza immunity. IMPORTANCE Antibodies to the influenza virus hemagglutinin (HA) protein confer the strongest protection against infection. Human antibodies elicited by infection and/or vaccination fail to protect against antigenically novel animal, pandemic, or human seasonal viruses. Improved vaccines are needed. We identify a novel class of antibodies that bind most divergent HA subtypes and all seasonal human HA antigenic variants tested. These antibodies confer protection from lethal influenza challenge in animal models. The corresponding epitope on the HA head is occluded by its interaction with the stem and is inaccessible in the well-resolved prefusion state. The immunogenicity of this head–stem interface indicates that poorly understood conformations of HA presenting widely conserved surfaces are explored in biochemical, cell-based, andin vivoassays. Head–stem interface antibodies warrant further investigation as an avenue to improve influenza vaccines and therapeutics.

Microbiology↗

Enhancing chemical bioproduction with rational control of bacterial post-translational modifications

Efficient conversion of inexpensive feedstocks to valuable chemicals by microbes is critical for a robust bioeconomy, but the ability to rationally design bacteria is hampered by insufficient knowledge of how post translational modifications (PTMs) control bacterial protein function and thus bioproduction phenotypes. Our study will focus on the lysine acetylation, a ubiquitous bacterial PTM that can affect the function of enzymes in central metabolism that are often critical for bioproduction processes, disrupt transcriptional regulation, and reduce translation. However, most lysine acetylation data is observational, which means that we do not know when, how, and what specific acetylated residues affect protein function and bacterial physiology. For our model host, we will use a Pseudomonas putida strain that we previously engineered to convert lignocellulosic feedstocks into chemicals such as itaconic acid (ITA). With this strain, we use a dynamic two-stage bioproduction process in which ITA is produced during a non-growth associated production phase. Production is highest during growth stages when lysine acetylation is low in other organisms (early stationary phase) and stalls in conditions where acetylation is highest (late stationary phase). The switch from high to stalled ITA production is also correlated with an unexpected increase in acetate levels – the precursor to non-enzymatic lysine acetylation. As such, we predict that lysine acetylation plays a substantial role in regulating the metabolic pathways required for ITA production. We will develop a generalizable approach that combines high-throughput genetic screens and cutting-edge genome engineering with state-of-the-art proteomics, metabolomics, and genetic code expansion methods to identify and modulate lysine acetylation patterns in bacteria. Ultimately, these strategies aim to manipulate protein expression and acetylation patterns to enhance bioproduction phenotypes (e.g., sustained ITA production in late stationary phase).

60 APPLIED LIFE SCIENCES↗

spammR: an R package designed for analysis and integration of spatial multi-omic measurements

Spatial omics is a young and evolving field and as such shows rapid development of novel technologies and analysis methods to measure transcripts, proteins, metabolites, and post-translational modifications at high spatial resolution. These advances in technology have enabled the simultaneous generation of abundance profiles for multiple different omics types and associated microscopy imaging data, as well as their analysis in a spatial context. However, most analytical tools are designed for spatial transcriptomics platforms and are challenging to use in other contexts such as mass spectrometry-based measurements or metagenomics. To this end we present spammR (spatial analysis of multi-omics measurements in R), an R package that enables end-to-end analysis with a specific focus on mass-spectrometry derived spatial omics datasets with (1) smaller sample sizes and spatial sparsity of samples, (2) considerable missingness, and (3) no a-priori knowledge about proteins or genes of interest, relying on a fully data-driven approach.

spammR↗

Powdery mildew effectors AVR A1 and BEC1016 target the ER J‐domain protein Hv ERdj3B required for immunity in barley

Abstract The barley powdery mildew fungus, Blumeria hordei (Bh), secretes hundreds of candidate secreted effector proteins (CSEPs) to facilitate pathogen infection and colonization. One of these, CSEP0008, is directly recognized by the barley nucleotide‐binding leucine‐rich‐repeat (NLR) receptor MLA1 and therefore is designated AVR A1 . Here, we show that AVR A1 and the sequence‐unrelated Bh effector BEC1016 (CSEP0491) suppress immunity in barley. We used yeast two‐hybrid next‐generation interaction screens (Y2H‐NGIS), followed by binary Y2H and in planta protein–protein interactions studies, and identified a common barley target of AVR A1 and BEC1016, the endoplasmic reticulum (ER)‐localized J‐domain protein Hv ERdj3B. Silencing of this ER quality control (ERQC) protein increased Bh penetration. Hv ERdj3B is ER luminal, and we showed using split GFP that AVR A1 and BEC1016 translocate into the ER signal peptide‐independently. Overexpression of the two effectors impeded trafficking of a vacuolar marker through the ER; silencing of Hv ERdj3B also exhibited this same cellular phenotype, coinciding with the effectors targeting this ERQC component. Together, these results suggest that the barley innate immunity, preventing Bh entry into epidermal cells, requires ERQC. Here, the J‐domain protein Hv ERdj3B appears to be essential and can be regulated by AVR A1 and BEC1016. Plant disease resistance often occurs upon direct or indirect recognition of pathogen effectors by host NLR receptors. Previous work has shown that AVR A1 is directly recognized in the cytosol by the immune receptor MLA1. We speculate that the AVR A1 J‐domain target being inside the ER, where it is inapproachable by NLRs, has forced the plant to evolve this challenging direct recognition.

54 ENVIRONMENTAL SCIENCES↗

High throughput, accurate gene annotation through AI and HPC-enabled structural analysis

With the advances in next generation sequencing technologies, the number of sequenced genomes is growing exponentially, resulting in a technology bottleneck for the translation of sequence information into usable hypotheses about the function of each gene. We have proposed leveraging our leadership high-performance computing (HPC) resources to help break this annotation bottleneck. Here we design an HPC-based framework to infer gene function from gene sequence by incorporating information about protein structure and interactions predicted by deep learning approaches. Accurate functional prediction and gene annotation using computational methods will facilitate breakthroughs in the genomic sciences essential to understanding and harnessing life processes in bacteria, fungi and plants. The development and applications of the state-of-the-art deep neural networks to protein structural modeling, interaction prediction, sequence comparison, and quality assessment of protein structural models will be made possible by leadership computational resources. These HPC-enabled bioinformatics and molecular modeling tools will provide powerful insights into molecular functions of genes.

59 BASIC BIOLOGICAL SCIENCES↗

Enhancing Sensitivity in Targeted Single-Cell Proteomics by Coupling a Dual Ion Funnel Interface with Triple Quadrupole Mass Spectrometer

Single-cell proteomics (SCP) has emerged as a powerful approach for understanding cellular heterogeneity and biological processes at unprecedented resolution. However, the extremely limited protein content of individual cells (femtogram to picogram levels) pushes current mass spectrometry instrumentation to its sensitivity limits, creating a critical analytical bottleneck. While selected reaction monitoring (SRM) using triple quadrupole (QqQ) instruments 1 offers advantages in sensitivity and reproducibility for targeted proteomics quantification, SRM still struggles with sensitivity for quantification of moderate- or low-abundance proteins from single-cell sample amounts. Here, we report the development and systematic evaluation of a dual ion funnel interface designed to address the sensitivity limitation by significantly enhancing ion transmission efficiency in commercial QqQ mass spectrometers. The dual ion funnel interface, composed of a curved S-funnel followed by a conventional ion funnel, improves ion transmission efficiency while reducing chemical noise through selective ion focusing. The performance of the dual ion funnel interface was systematically compared to standard interface on a TSQ Vantage platform across samples with different levels of complexity. The dual funnel interface demonstrated to provide up to 25-fold improvement in sensitivity across a wide range of protein concentrations in different biological matrices (low complex mouse macrophage and high complex human cells). Critically, enhanced sensitivity was accompanied by increased analytical reproducibility with lower coefficient of variations. Most importantly, the dual funnel interface enabled reliable quantification of low-abundance proteins that were barely detectable or not detected by the standard interface, extending analysis to single-cell equivalent amounts while maintaining excellent reproducibility. These results demonstrate that the dual funnel interface addresses the critical bottleneck in quantitative targeted proteomics, providing a technological foundation for ultrasensitive targeted SCP that requires both high sensitivity and robust quantitative performance.

Min, Sehong↗

Chaotrope-Based Approach for Rapid In Vitro Assembly and Loading of Bacterial Microcompartment Shells

Bacterial microcompartments (BMCs) are proteinaceous organelles that self-assemble into selectively permeable shells that encapsulate enzymatic cargo. BMCs enhance catalytic pathways by reducing crosstalk among metabolites, preventing harmful intermediates from leaking into the cytosol and increasing reaction efficiency via enzyme colocalization. The intrinsic properties of BMCs make them attractive for biotechnological engineering. However, in vivo expression methods for shell synthesis have significant drawbacks that limit the potential design space for these nanocompartments. Here, we describe the development of an efficient and rapid method for the in vitro assembly of BMC shells from their protein building blocks. Our method enables large-scale construction of BMC shells by utilizing urea as a chaotropic agent to control self-assembly and provides an approach for encapsulation of both biotic and abiotic cargo under a broad range of reaction conditions. We demonstrate an enhanced level of control over the assembly of BMC shells in vitro and expand the design parameter space for engineering BMC systems with specialized and enhanced catalytic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Entropy is an important design principle in the photosystem II supercomplex

Photosystem II (PSII) can achieve near-unity quantum efficiency of light harvesting in ideal conditions and can dissipate excess light energy as heat to prevent the formation of reactive oxygen species (ROS) under light stress. Understanding how this pigment–protein complex accomplishes these opposing goals is a topic of great interest that has so far been explored primarily through the lens of the system energetics. Despite PSII’s known flat energy landscape, a thorough consideration of the entropic effects on energy transfer in PSII is lacking. In this work, we aim to discern the free energetic design principles underlying the PSII energy transfer network. To accomplish this goal, we employ a structure-based rate matrix and compute the free energy terms in time following a specific initial excitation to discern how entropy and enthalpy drive ensemble system dynamics. We find that the interplay between the entropy and enthalpy components differ among each protein subunit, which allows each subunit to fulfill a unique role in the energy transfer network. This individuality ensures that PSII can accomplish efficient energy trapping in the reaction center (RC), effective nonphotochemical quenching (NPQ) in the periphery, and robust energy trapping in the other-monomer RC if the same-monomer RC is closed. We also show that entropy, in particular, is a dynamically tunable feature of the PSII free energy landscape accomplished through regulation of LHCII binding. These findings help rationalize natural photosynthesis and provide design principles for more efficient solar energy harvesting technologies.

59 BASIC BIOLOGICAL SCIENCES↗

Conical Intersection Accessibility Dictates Brightness in Red Fluorescent Proteins

Red fluorescent protein (RFP) variants are highly sought after for in-vivo imaging since longer wavelengths improve depth and contrast in fluorescence imaging. However, the lower energy emission wavelength usually correlates with a lower fluorescent quantum yield compared to their green emitting counterparts. To guide the rational design of bright variants, we have theoretically assessed two variants (mScarlet and mRouge) which are reported to have very different brightness. Using an α-CASSCF QM/MM framework (chromophore and all protein residues within 6 Å of it in the QM region, for a total of more than 450 QM atoms), we identify key points on the ground and first excited state potential energy surfaces. The brighter variant mScarlet has a rigid scaffold, and the chromophore stays largely planar on the ground state. The dimmer variant mRouge shows more flexibility and can accommodate a pre-twisted chromophore conformation which provides easier access to conical intersections. Notably, the main difference between the variants lies in the intersection seam regions, which appear largely inaccessible in mScarlet but partially accessible in mRouge. This observation is mainly related with changes in the cavity charge distribution, the hydrogen-bonding network involving the chromophore and a key ARG/THR mutation (which changes both charge and steric hindrance).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advances in ionic liquid recycling for lignocellulosic biomass pretreatment

Ionic liquids (ILs) are promising solvents for the pretreatment of lignocellulosic biomass due to their ability to disrupt cellulose, hemicellulose, and lignin structures. However, large-scale implementation requires the development of efficient recovery and recycling methods. This review provides a comprehensive analysis of the recyclability potential of ILs used in biomass pretreatment, emphasizing their mechanisms, recent innovations, and ongoing challenges. We begin by discussing the structural diversity and tunability of ILs, which underlie their effectiveness in biomass deconstruction. The distinct roles of IL anions and cations in dissolving specific biomass components are systematically presented and compared. Advances in IL recycling techniques, including antisolvent precipitation methods, membrane separation, and distillation, are critically examined, with attention to how mechanistic insights can inform the design of more efficient and selective recovery strategies. Despite progress, significant challenges remain to scaling up IL-based biomass processing, including high cost, environmental concerns, and impact of biomass-derived impurities (e.g., lignin residues, sugars, proteins) on IL purity and functionality after reuse. We also review the applicability of different ILs based on life cycle assessments and techno-economic analyses. Lastly, we identify critical research gaps and propose future directions, including the design and development of next-generation ILs with improved recyclability, reduced toxicity, and enhanced economic viability for industrial-scale applications.

36 MATERIALS SCIENCE↗

Enhanced polymorph metastability drives glycine nucleation in aqueous salt solutions

Crystal nucleation from aqueous solutions influences countless geological, biochemical, astrophysical, environmental, and materials science–related phenomena, including ice formation, the manufacturing of active pharmaceutical ingredients, development of diseases such as Alzheimer’s and the origin of life itself. Understanding and controlling nucleation is essential for designing materials with specific properties, developing strategies to inhibit or promote crystallization in various contexts and preventing pathological aggregation in neurodegenerative diseases. Similar to the protein structure prediction problem—where a single amino acid sequence can in theory adopt one most stable conformation but in practice may sample multiple competing conformations—crystal nucleation faces a parallel challenge: the same chemical species can form diverse polymorphs under different environmental conditions (e.g., temperature, pressure, solvent). Each polymorph presents its own set of physical and chemical properties, highlighting the importance of understanding and controlling polymorph selection in fields ranging from pharmaceuticals to materials design. Despite advances in experimental and computational methods for studying phase transitions and polymorph stability, nucleation remains challenging due to its nanoscale nature. Furthermore, in practical settings, salts and impurities can further influence crystal nucleation in diverse contexts, from scaling in pipelines and desalination plants to the durability of concrete and the efficiency of battery materials. This can lead to the formation of polymorphs that may differ from the most stable phase in pure solutions. Or, even though the final structure might appear same irrespective of whether the environment contained impurities or not, the mechanism through which it was formed might be completely different and not intuitive.

Wang, Ruiyu [University of Maryland, College Park,↗

Light-induced electron spin qubit coherences in the purple bacteria reaction center protein

Photosynthetic reaction center proteins (RCs) provide ideal model systems for studying quantum entanglement between multiple spins, a quantum mechanical phenomenon wherein the properties of the entangled particles become inherently correlated. Following light-generated sequential electron transfer, RCs generate spin-correlated radical pairs (SCRPs), also referred to as entangled spin qubit (radical) pairs (SQPs). Understanding and controlling coherence mechanisms in SCRP/SQPs is important for realizing practical uses of electron spin qubits in quantum sensing applications. The bacterial RC (bRC) provides an experimental system for exploring quantum effects in the SCRP P 865 + Q A − , where P 865 , a special pair of bacteriochlorophylls, is the primary donor, and Q A is the primary quinone acceptor. In this study, we focus on understanding how local molecular environments and isotopic substitution, particularly deuteration, influence spin coherence times (T M ). Using high-frequency electron paramagnetic resonance (EPR) spectroscopy, we observed that the local environment surrounding P 865 and Q A plays a significant role in determining T M . Our findings show that while deuteration led to a modest increase in T M , particularly at low temperatures, but the effect was substantially smaller than predicted by classical nuclear spin diffusion alone. This result is in contrast to our previous study of the photosystem I (PSI) RC, where no increase in T M was observed upon deuteration. Theoretical modeling identified several methyl groups at key distances from the spin centers of both bRC and PSI, and methyl group tunneling at low temperatures has been previously suggested as a mechanism for enhanced spin decoherence. Additionally, our study revealed a strong dependence of spin coherence on the orientation of the external magnetic field, highlighting the influence of the protein microenvironment on spin dynamics. In conclusion, these results offer new insights for optimizing coherence times in quantum system design for quantum information science and sensing applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗