Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “protein dynamics”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Electrochemical Characterization of Photo-Driven Hole-Scavenging by Cadmium Sulfide Quantum Dot-Nitrogenase Biohybrid Complexes

Light-driven biohybrid systems that couple semiconductor nanocrystals with enzymes offer a promising strategy for solar-to-chemical energy-conserving reduction reactions, yet are often limited by inefficient hole scavenging. Hole scavenging is critical for maintaining charge separation in the light-absorbing electron donor molecule and, thus, for sustaining catalytic turnover, making quantification essential to improving system efficiency. Here, we introduce a photoelectrochemical approach for real-time monitoring of hole scavenging in cadmium sulfide (CdS) quantum dot (QD)-nitrogenase MoFe protein biohybrids that catalyze the reduction of H+ and N2. Using hydroquinone (HQ) as the sacrificial electron donor (SED), oxidation of HQ to benzoquinone (BQ) by photogenerated valence-band holes is coupled to the electrochemical reduction of BQ at an electrode, enabling quantification of the hole-scavenging reaction via chronoamperometry. This approach provides a continuous, real-time readout of charge-transfer dynamics under illumination. Systematic variation of light intensity and donor concentration reveals that hole scavenging scales with photon flux and exhibits a non-linear dependence on SED concentration, with an optimum at intermediate HQ concentrations. These results establish chronoamperometry as a powerful tool for probing photoinduced charge transfer, advancing the quantitative understanding of hole-scavenging in biohybrid systems, and offering a generalizable framework for optimizing solar-driven biocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Engineering a photoenzyme to use red light

Photoenzymatic reactions involving flavin-dependent “ene”-reductases (EREDs) rely on protein-templated charge transfer (CT) complexes between the cofactor and substrate for radical initiation. These complexes typically absorb in the blue region of the electromagnetic spectrum. Here, we engineered an ERED to form CT complexes that absorb red light. Mechanistic studies indicate that red-light activity is due to the growth of a red-absorbing shoulder off the previously identified cyan absorption feature. Molecular dynamics simulations, docking, and excited-state calculations suggest that the cyan feature involves a π→π* transition on flavin, whereas the red-light absorption is a π→π* transition between flavin and the substrate. Furthermore, differences in the electronic transition are due to changes in the substrate-binding conformation and allosteric tuning of the electronic structure of the cofactor-substrate complex. Microenvironment tuning of the CT complex for red-light activity is observed with other engineered photoenzymatic reactions, highlighting this effect’s generality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Electrically controlling and optically observing the membrane potential of supported lipid bilayers

Supported lipid bilayers are a well-developed model system for the study of membranes and their associated proteins, such as membrane channels, enzymes, and receptors. These versatile model membranes can be made from various components, ranging from simple synthetic phospholipids to complex mixtures of constituents, mimicking the cell membrane with its relevant physiochemical and molecular phenomena. In addition, the high stability of supported lipid bilayers allows for their study via a wide array of experimental probes. In this work, we describe a platform for supported lipid bilayers that is accessible both electrically and optically, and demonstrate direct optical observation of the transmembrane potential of supported lipid bilayers. We show that the polarization of the supported membrane can be electrically controlled and optically probed using voltage-sensitive dyes. Membrane polarization dynamics is understood through electrochemical impedance spectroscopy and the analysis of an equivalent electrical circuit model. In addition, we describe the effect of the conducting electrode layer on the fluorescence of the optical probe through metal-induced energy transfer, and show that while this energy transfer has an adverse effect on the voltage sensitivity of the fluorescent probe, its strong distance dependency allows for axial localization of fluorescent emitters with ultrahigh accuracy. We conclude with a discussion on possible applications of this platform for the study of voltage-dependent membrane proteins and other processes in membrane biology and surface science.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A temporal hierarchy underpins the transcription factor–DNA interactome of the maize UPR

Adverse environmental conditions reduce crop productivity and often increase the load of unfolded or misfolded proteins in the endoplasmic reticulum (ER). This potentially lethal condition, known as ER stress, is buffered by the unfolded protein response (UPR), a set of signaling pathways designed to either recover ER functionality or ignite programmed cell death. Despite the biological significance of the UPR to the life of the organism, the regulatory transcriptional landscape underpinning ER stress management is largely unmapped, especially in crops. To fill this significant knowledge gap, we performed a large–scale systems–level analysis of the protein–DNA interaction (PDI) network in maize (Zea mays). Using 23 promoter fragments of six UPR marker genes in a high–throughput enhanced yeast one–hybrid assay, we identified a highly interconnected network of 262 transcription factors (TFs) associated with significant biological traits and 831 PDIs underlying the UPR. We established a temporal hierarchy of TF binding to gene promoters within the same family as well as across different families of TFs. Cistrome analysis revealed the dynamic activities of a variety of cis–regulatory elements (CREs) in ER stress–responsive gene promoters. By integrating the cistrome results into a TF network analysis, we mapped a subnetwork of TFs associated with a CRE that may contribute to UPR management. Lastly, we validated the role of a predicted network hub gene using the Arabidopsis system. The PDIs, TF networks, and CREs identified in our work are foundational resources for understanding transcription–regulatory mechanisms in the stress responses and crop improvement.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Quantitative multiplexed analysis of gene and protein expression patterns in Yarrowia lipolytica

In this report, we present coordinated observations of protein and mRNA transcript counts at the single-cell level in the oleaginous yeast model Yarrowia lipolytica. The transcription factor Xbp1p regulates entry into a quiescent state, representing a shift of resources to sequestration of nutrients rather than cell division. We observed the responses of wild-type and Δxbp1 cells to protein (by fluorescence) and transcript quantification and localization at both single-cell and population-averaged levels. Data were collected via single-molecule fluorescence in situ hybridization (smFISH) and qPCR under nitrogen depletion, a condition that drives lipid accumulation. These techniques reveal a complex and heterogeneous population of Xbp1p dynamics and downstream regulation. Our findings highlight the need for single-cell resolution analyses to describe cellular dynamics and regulatory processes.

Yarrowia lipolytica↗
DOE OSTI2023

Cooperative actin filament nucleation by the Arp2/3 complex and formins maintains the homeostatic cortical array in Arabidopsis epidermal cells

Abstract Precise control over how and where actin filaments are created leads to the construction of unique cytoskeletal arrays within a common cytoplasm. Actin filament nucleators are key players in this activity and include the conserved actin-related protein 2/3 (Arp2/3) complex as well as a large family of formins. In some eukaryotic cells, these nucleators compete for a common pool of actin monomers and loss of one favors the activity of the other. To test whether this mechanism is conserved, we combined the ability to image single filament dynamics in the homeostatic cortical actin array of living Arabidopsis (Arabidopsis thaliana) epidermal cells with genetic and/or small molecule inhibitor approaches to stably or acutely disrupt nucleator activity. We found that Arp2/3 mutants or acute CK-666 treatment markedly reduced the frequency of side-branched nucleation events as well as overall actin filament abundance. We also confirmed that plant formins contribute to side-branched filament nucleation in vivo. Surprisingly, simultaneous inhibition of both classes of nucleator increased overall actin filament abundance and enhanced the frequency of de novo nucleation events by an unknown mechanism. Collectively, our findings suggest that multiple actin nucleation mechanisms cooperate to generate and maintain the homeostatic cortical array of plant epidermal cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Dynamic molecular architecture of the synaptonemal complex

During meiosis, pairing between homologous chromosomes is stabilized by the assembly of the synaptonemal complex (SC). The SC ensures the formation of crossovers between homologous chromosomes and regulates their distribution. However, how the SC regulates crossover formation remains elusive. We isolated an unusual mutation in Caenorhabditis elegans that disrupts crossover interference but not SC assembly. This mutation alters the unique C terminal domain of an essential SC protein, SYP-4, a likely ortholog of the vertebrate SC protein SIX6OS1. We use three-dimensional stochastic optical reconstruction microscopy (3D-STORM) to interrogate the molecular architecture of the SC from wild-type and mutant C. elegans animals. Using a probabilistic mapping approach to analyze super-resolution image data, we detect changes in the organization of the synaptonemal complex in wild-type animals that coincide with crossover designation. We also found that our syp-4 mutant perturbs SC architecture. Our findings add to growing evidence that the SC is an active material whose molecular organization contributes to chromosome-wide crossover regulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Unraveling Bacterial Adaptation Strategies in the Microbiome Shaped by the Chemical Environment of the Plant Rhizosphere

The rhizosphere is a dynamic environment where rhizodeposits that include primary and secondary metabolites and mucilage serve as nutrient sources for soil microorganisms, attracting them toward plant roots. However, understanding how these microbes specifically respond to plant root chemical signals has been hindered by the challenges of disentangling physical and chemical interactions between the microbes and plant roots. To address this, we implemented an innovative filter-based experimental setup on plant roots that creates a physical barrier while facilitating the exchange of chemical signals. The proteomic analysis of 10 Populus root-associated bacterial strains grown in the presence or absence of a plant in either individual or mixed community conditions provided detailed insights into the functional responses of these strains to the root chemical environment. Additionally, this approach allowed us to discern the impact of root exudates on overall community dynamics. In particular, metaproteomic analyses revealed that each of these 10 microbial members responds uniquely to the presence of the plant, with Bacillus and Pantoea exhibiting the most dramatic favorable impact. Proteomic examination revealed the details of metabolism fine-tuning, including processes such as chemotaxis and ATP-binding cassette transporter proteins. This study demonstrates the application of a filter-based experimental setup to study microbial responses to plant chemicals and sheds light on adaptation strategies employed by various bacterial strains for survival in the rhizosphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

We developed Distilled Graph Attention Policy Network (DGAPN), a reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. The framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention (sGAT) mechanism that leverages self-attention over both node and edge attributes as well as encoding the spatial structure --- this capability is of considerable interest in synthetic biology and drug discovery. An attentional policy network is introduced to learn the decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with stability. Exploration is driven by the stochasticity of the action space design and the innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while reducing the complexity of paths to chemical synthesis.

Wu, Yulun↗
DOE OSTI2022

SPATIAL GRAPH ATTENTION AND CURIOSITY-DRIVEN POLICY FOR ANTIVIRAL DRUG DISCOVERY

We developed Distilled Graph Attention Policy Network (DGAPN), a reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. The framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention (sGAT) mechanism that leverages self-attention over both node and edge attributes as well as encoding the spatial structure - this capability is of considerable interest in synthetic biology and drug discovery. An attentional policy network is introduced to learn the decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with stability. Exploration is driven by the stochasticity of the action space design and the innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while reducing the complexity of paths to chemical synthesis.

Wu, Y↗
DOE OSTI2025

Coupling of Charge Regulation and Geometry in Soft Ionizable Molecular Assemblies

The size, shape, and charge of structures, such as proteins and amphiphile assemblies, respond in an interconnected manner to solution ionic conditions. Here, we analyze assemblies of an amphiphile (C 16 K 2 ), with two ionizable amino acids [lysine (K)] coupled to a 16-carbon alkyl tail, via small-angle X-ray scattering (SAXS), nonlinear Poisson–Boltzmann theory (nl-PB), and hybrid Monte Carlo-molecular dynamics (MC-MD) simulations. SAXS revealed structural transitions from spherical micelles to cylindrical micelles to bilayers with increasing pH. By combining SAXS-determined structural information and nl-PB, we derived the molecular degree of ionization as a function of pH. The back-calculated titration curves matched the experimental data over an extended pH range, without adjustable parameters. Similarly, the SAXS data on the evolution of spherical micelle structure with ionic strength were combined with nl-PB and MC-MD to derive the bare and effective charges. MC-MD, which considered finite ion sizes, showed that bare and effective charges saturate quickly with increasing salt concentration. Furthermore, the calculated effective charges closely matched results from Zeta-potential measurements. The presented approach has advantages over customary methods for charge regulation, such as the Henderson–Hasselbalch (HH) or Hill models, where molecular ionization/deionization in assemblies is described by effective pKs that are distinct from the pK for isolated molecules. However, these models lack a physical explanation for these pK shifts. By contrast, our approach of combining structural details with an electrostatic model and simulations provides a more intuitive understanding of structure-charge coupling and a framework for understanding charge regulation in many synthetic and biological systems.

ionization↗
DOE OSTI2025

Decoding substrate specificity determining factors in glycosyltransferase-B enzymes – insights from machine learning models

Substrate specificity is an essential characteristic of any enzyme's function and an understanding of the factors that determine this specificity is crucial for enzyme engineering. Unlike the structure of an enzyme which is directly impacted by its sequence, substrate specificity as an enzyme attribute involves a rather indirect relationship with sequence as it also depends on structural aspects that dictate substrate accessibility and active site dynamics. In this study, we explore the performance of classifier-based machine learning models trained on curated sequence and structural data for a class of glycosyltransferases (GTs), namely GT-Bs, to understand their substrate specificity determining factors. GTs enable the transfer of sugar moieties to other biomolecules such as oligosaccharides or proteins and are found in all kingdoms of life. In plants, GTs participate in the biosynthesis of plant cell wall biopolymers (e.g.: hemicelluloses and pectins) and are an integral part of the enzymatic machinery that enables the storage of carbon and energy as plant biomass. To elucidate the substrate specificity of uncharacterized GT-Bs, we constructed multi-label machine learning models (Support Vector Classifier, K-Nearest Neighbors, Gaussian Naïve-Bayes, Random Forest) that incorporate both sequence and structural features. These models achieve good predictive accuracies on test datasets. However, despite our use of structural information, we highlight that there is further scope for improvement in training these models to draw interpretable relationships between sequence, structure and substrate specificity determining motifs in GT-Bs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Failure Mode Identification of Insulin Drug Products – Impact of Relevant Stress Conditions on the Quality of the Drug

Fast-acting insulin drug products (DPs) are carried and administered by diabetic patients to maintain their blood glucose level throughout the day, exposing the DPs to stress conditions. Apidra, Novolog, and Humalog insulin DPs were tested under various stress conditions. Dynamic light scattering (DLS), and size exclusion chromatography (SEC) were used to monitor the stability and aggregation. Thermal stress alone did not influence the stability. However, 24 hr exposure to vigorous mechanical stress shifted the DLS size peaks of Novolog and Humalog from 5 ± 1 nm to > 50.9 ± 25.6 nm, and the SEC native protein peak areas decreased 52% for Novolog and 18.4% for Humalog. Combined stress accelerated protein aggregation more drastically. Novolog and Humalog size shifted (>75 nm) after 3 hr and the peak area decreased > 97.9% after 6 hr exposure, indicating that high temperature accelerated the aggregation triggered by agitation. Soluble aggregates were captured by DLS early on compared to SEC. Apidra was comparably stable indicating DP formulation plays a critical role in stability. Here this study provides a greater understanding of potential failure modes patients and care givers may encounter while handling insulin DPs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Energetic and structural control of polyspecificity in a multidrug transporter

Multidrug efflux pumps are dynamic molecular machines that drive antibiotic resistance by harnessing ion gradients to export chemically diverse substrates. Despite their clinical importance, the molecular principles underlying multidrug promiscuity and energy efficiency remain poorly understood. Using multiparametric deep mutational scanning across eight substrates and two energy conditions, we deconvolute the contributions of substrate recognition, energetic coupling, and protein stability, providing an integrated, high-resolution view of multidrug transport. We find that substrate specificity arises from a distributed network of residues extending beyond the binding site, with mutations that reshape binding, coupling, conformational flexibility, and membrane interactions. Further, we apply a pH-based selection scheme to measure the effect of mutation on pH-dependent transport efficiency. By integrating these data, we reveal a fundamental relationship between efficiency and promiscuity: Highly efficient variants exhibit broad substrate profiles, while inefficient variants are narrower. In conclusion, these findings establish a direct link between energy coupling and polyspecificity, uncovering the biochemical logic underlying multidrug transport.

Biological Sciences↗
DOE OSTI2023

Small molecule biosensors

Biosensors for small molecules can be used in applications that range from metabolic engineering to orthogonal control of transcription. Biosensors are produced based on a ligand-binding domain (LBD) using a method that, in principle, can be applied for any target molecule. The LBD is fused to either a fluorescent protein or a transcriptional activator and is destabilized by mutation such that the fusion accumulates only in cells containing the target ligand. The power of this method is illustrated by developing biosensors for digoxin and progesterone. Addition of ligand to cells expressing a biosensor activates transcription in yeast, mammalian cells and plants, with a dynamic range of up to about 100-fold or more. The biosensors are used to improve the biotransformation of pregnenolone to progesterone in yeast and to regulate CRISPR activity in mammalian cells. This work provides a general methodology to develop biosensors for a broad range of molecules.

Mandell, Daniel J.↗
DOE OSTI2024

ezAlign: A Tool for Converting Coarse-Grained Molecular Dynamics Structures to Atomistic Resolution for Multiscale Modeling

Soft condensed matter is challenging to study due to the vast time and length scales that are necessary to accurately represent complex systems and capture their underlying physics. Multiscale simulations are necessary to study processes that have disparate time and/or length scales, which abound throughout biology and other complex systems. Herein we present ezAlign, an open-source software for converting coarse-grained molecular dynamics structures to atomistic representation, allowing multiscale modeling of biomolecular systems. The ezAlign v1.1 software package is publicly available for download at github.com/LLNL/ezAlign. Its underlying methodology is based on a simple alignment of an atomistic template molecule, followed by position-restraint energy minimization, which forces the atomistic molecule to adopt a conformation consistent with the coarse-grained molecule. The molecules are then combined, solvated, minimized, and equilibrated with position restraints. Validation of the process was conducted on a pure POPC membrane and compared with other popular methods to construct atomistic membranes. Additional examples, including surfactant self-assembly, membrane proteins, and more complex bacterial and human plasma membrane models, are also presented. By providing these examples, parameter files, code, and an easy-to-follow recipe to add new molecules, this work will aid future multiscale modeling efforts.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Room-temperature structural studies of SARS-CoV-2 protein NendoU with an X-ray free-electron laser

NendoU from SARS-CoV-2 is responsible for the virus’s ability to evade the innate immune system by cleaving the polyuridine leader sequence of antisense viral RNA. Here we report the room-temperature structure of NendoU, solved by serial femtosecond crystallography at an X-ray free-electron laser to 2.6 Å resolution. The room-temperature structure provides insight into the flexibility, dynamics, and other intrinsic properties of NendoU, with indications that the enzyme functions as an allosteric switch. Functional studies examining cleavage specificity in solution and in crystals support the uridine-purine cleavage preference, and we demonstrate that enzyme activity is fully maintained in crystal form. Optimizing the purification of NendoU and identifying suitable crystallization conditions set the benchmark for future time-resolved serial femtosecond crystallography studies. This could advance the design of antivirals with higher efficacy in treating coronaviral infections, since drugs that block allosteric conformational changes are less prone to drug resistance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Mapping microhabitats of lignocellulose decomposition by a microbial consortium

The leaf-cutter ant fungal garden ecosystem is a naturally evolved model system for efficient plant biomass degradation. Degradation processes mediated by the symbiotic fungus Leucoagaricus gongylophorus are difficult to characterize due to dynamic metabolisms and spatial complexity of the system. Herein, we performed microscale imaging across 12-µm-thick adjacent sections of Atta cephalotes fungal gardens and applied a metabolome-informed proteome imaging approach to map lignin degradation. This approach combines two spatial multiomics mass spectrometry modalities that enabled us to visualize colocalized metabolites and proteins across and through the fungal garden. Spatially profiled metabolites revealed an accumulation of lignin-related products, outlining morphologically unique lignin microhabitats. Metaproteomic analyses of these microhabitats revealed carbohydrate-degrading enzymes, indicating a prominent fungal role in lignocellulose decomposition. Integration of metabolome-informed proteome imaging data provides a comprehensive view of underlying biological pathways to inform our understanding of metabolic fungal pathways in plant matter degradation within the micrometer-scale environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗