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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.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

minervachem

Minervachem is a tool for cheminformatics and machine learning in chemistry. It includes both algorithms from existing literature and algorithms which we have developed. Its features center around two main themes: molecular representations and algorithms, both for molecular machine learning. It provides a scikit-learn transformer interface for molecular featurization and an estimator interface for machine learning algorithms. It also provides visualization tools for explaining machine learning predictions. We aim to continue developing this software to improve its performance and usability and expand its capabilities within the realm of molecular machine learning, cheminformatics, and visualization.

Lubbers, Nicholas↗
DOE OSTI2026

A tunable autonomous RNA-fueled micro-engine

Autonomous molecular machines capable of converting chemical energy into mechanical motion are foundational components for synthetic nanoscale systems. Inspired by biological motors, we report the construction of a tunable, RNA-fueled DNA origami engine that drives the cyclic movement of a 500 nm-diameter particle at the microscale. The engine operates via sequential RNA–DNA hybridization and enzymatic cleavage by RNase H, enabling reversible switching between folded and unfolded conformations without external intervention. By modulating RNA and enzyme concentrations and controlling temperature, we achieve tunable switching kinetics, with transition periods as short as ~10 s. Kinetic modeling reveals that the folding pathway is governed by both productive RNA binding and the enzymatic clearance of misfolded intermediates, while unfolding is primarily controlled by RNase H activity. Since the RNA fuel binds specifically to the DNA strands, each engine is addressable simply by changing the sequences. This work demonstrates a programmable, self-resetting molecular actuator and offers a blueprint for building more complex nanomechanical systems with forces and energies comparable to molecular motors.

DNA nanomachines↗
DOE OSTI2023

Probing Accuracy-Speedup Tradeoff in Machine Learning Surrogates for Molecular Dynamics Simulations

The performance promise of machine learning surrogates of molecular dynamics simulations of soft materials is significant but generally comes at the cost of acquiring large training datasets to learn the complex relationships between input soft material attributes and output properties. Under the constraint of limited high-performance computing resources, optimizing the size of the training datasets becomes paramount. Using an artificial neural network based surrogate for molecular dynamics simulations of confined electrolytes, we explore the tradeoff between surrogate accuracy and computational gains. Accuracy is assessed by computing the root-mean-square errors between the surrogate predictions and the ground truth results obtained via molecular dynamics simulations. The computational performance is judged by evaluating the speedup which incorporates the training dataset creation time. Improvement in accuracy occurs with a loss of speedup, which scales as the inverse of the training dataset size. Furthermore, the link between surrogate generalizability and the accuracy-speedup tradeoff is assessed by examining the errors incurred in surrogate predictions on unseen, interpolated input variables and developing a net speedup metric to capture the associated gains.

Anions↗
DOE OSTI2023

Entropic control of the free-energy landscape of an archetypal biomolecular machine

Biomolecular machines are complex macromolecular assemblies that utilize thermal and chemical energy to perform essential, multistep, cellular processes. Despite possessing different architectures and functions, an essential feature of the mechanisms of action of all such machines is that they require dynamic rearrangements of structural components. Surprisingly, biomolecular machines generally possess only a limited set of such motions, suggesting that these dynamics must be repurposed to drive different mechanistic steps. Although ligands that interact with these machines are known to drive such repurposing, the physical and structural mechanisms through which ligands achieve this remain unknown. Using temperature-dependent, single-molecule measurements analyzed with a time-resolution-enhancing algorithm, here, we dissect the free-energy landscape of an archetypal biomolecular machine, the bacterial ribosome, to reveal how its dynamics are repurposed to drive distinct steps during ribosome-catalyzed protein synthesis. Specifically, we show that the free-energy landscape of the ribosome encompasses a network of allosterically coupled structural elements that coordinates the motions of these elements. Moreover, we reveal that ribosomal ligands which participate in disparate steps of the protein synthesis pathway repurpose this network by differentially modulating the structural flexibility of the ribosomal complex (i.e., the entropic component of the free-energy landscape). Here, we propose that such ligand-dependent entropic control of free-energy landscapes has evolved as a general strategy through which ligands may regulate the functions of all biomolecular machines. Such entropic control is therefore an important driver in the evolution of naturally occurring biomolecular machines and a critical consideration for the design of synthetic molecular machines.

Science & Technology - Other Topics↗
DOE OSTI2022

Molecular dipole moment learning via rotationally equivariant derivative kernels in molecular-orbital-based machine learning

This study extends the accurate and transferable molecular-orbital-based machine learning (MOB-ML) approach to modeling the contribution of electron correlation to dipole moments at the cost of Hartree–Fock computations. A MOB pairwise decomposition of the correlation part of the dipole moment is applied, and these pair dipole moments could be further regressed as a universal function of MOs. The dipole MOB features consist of the energy MOB features and their responses to electric fields. An interpretable and rotationally equivariant derivative kernel for Gaussian process regression (GPR) is introduced to learn the dipole moment more efficiently. The proposed problem setup, feature design, and ML algorithm are shown to provide highly accurate models for both dipole moments and energies on water and 14 small molecules. To demonstrate the ability of MOB-ML to function as generalized density-matrix functionals for molecular dipole moments and energies of organic molecules, we further apply the proposed MOB-ML approach to train and test the molecules from the QM9 dataset. The application of local scalable GPR with Gaussian mixture model unsupervised clustering GPR scales up MOB-ML to a large-data regime while retaining the prediction accuracy. In addition, compared with the literature results, MOB-ML provides the best test mean absolute errors of 4.21 mD and 0.045 kcal/mol for dipole moment and energy models, respectively, when training on 110 000 QM9 molecules. The excellent transferability of the resulting QM9 models is also illustrated by the accurate predictions for four different series of peptides.

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 OSTI2024

Dashboard for Visualizing Molecular Property Prediction Machine Learning Results

This is a dashboard for exploring the results of machine learning models for predicting molecular properties from molecular structure. It includes tools for: 1. Modifying molecules to observe the change in predicted properties 2. Exploring the relationship between molecular structure and predicted properties 3. Recommending structurally similar molecules with improved properties 4. Exploring the impact of data subsampling on model performance metrics

Xu, Audrey↗
DOE OSTI2022

Ratchet, swivel, tilt and roll: a complete description of subunit rotation in the ribosome

Protein synthesis by the ribosome requires large-scale rearrangements of the ‘small’ subunit (SSU; ~1 MDa), including inter- and intra-subunit rotational motions. However, with nearly 2000 structures of ribosomes and ribosomal subunits now publicly available, it is exceedingly difficult to design experiments based on analysis of all known rotation states. To overcome this, we developed an approach where the orientation of each SSU head and body is described in terms of three angular coordinates (rotation, tilt and tilt direction) and a single translation. By considering the entire RCSB PDB database, we describe 1208 fully-assembled ribosome complexes and 334 isolated small subunits, which span >50 species. This reveals aspects of subunit rearrangements that are universal, and others that are organism/domain-specific. For example, we show that tilt-like rearrangements of the SSU body (i.e. ‘rolling’) are pervasive in both prokaryotic and eukaryotic (cytosolic and mitochondrial) ribosomes. As another example, domain orientations associated with frameshifting in bacteria are similar to those found in eukaryotic ribosomes. Together, this study establishes a common foundation with which structural, simulation, single-molecule and biochemical efforts can more precisely interrogate the dynamics of this prototypical molecular machine.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Structural basis for the inability of chloramphenicol to inhibit peptide bond formation in the presence of A-site glycine

Ribosome serves as a universal molecular machine capable of synthesis of all the proteins in a cell. Small-molecule inhibitors, such as ribosome-targeting antibiotics, can compromise the catalytic versatility of the ribosome in a context-dependent fashion, preventing transpeptidation only between particular combinations of substrates. Classic peptidyl transferase center inhibitor chloramphenicol (CHL) fails to inhibit transpeptidation reaction when the incoming A site acceptor substrate is glycine, and the molecular basis for this phenomenon is unknown. Here, we present a set of high-resolution X-ray crystal structures that explain why CHL is unable to inhibit peptide bond formation between the incoming glycyl-tRNA and a nascent peptide that otherwise is conducive to the drug action. Our structures reveal that fully accommodated glycine residue can co-exist in the A site with the ribosome-bound CHL. Moreover, binding of CHL to a ribosome complex carrying glycyl-tRNA does not affect the positions of the reacting substrates, leaving the peptide bond formation reaction unperturbed. These data exemplify how small-molecule inhibitors can reshape the A-site amino acid binding pocket rendering it permissive only for specific amino acid residues and rejective for the other substrates extending our detailed understanding of the modes of action of ribosomal antibiotics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Combining Molecular Simulations and Machine Learning to Comprehensively Explore Adsorption Space (Final Report)

This is the final report for the project "Combining Molecular Simulations and Machine Learning to Comprehensively Explore Adsorption Space". The central aim of this project was to develop modeling tools that vastly increase the diversity of molecules for which reliable adsorption isotherms in nanoporous materials are available. Within the project, molecular simulation data for a diverse set of examples was combined with machine-learning (ML) methods to rapidly predict adsorption equilibria in crystalline nanoporous materials (primarily MOFs).

36 MATERIALS SCIENCE↗
DOE OSTI2024

The 1.3 Å resolution structure of the truncated group Ia type IV pilin from Pseudomonas aeruginosa strain P1

The type IV pilus is a diverse molecular machine capable of conferring a variety of functions and is produced by a wide range of bacterial species. The ability of the pilus to perform host-cell adherence makes it a viable target for the development of vaccines against infection by human pathogens such as Pseudomonas aeruginosa . Here, the 1.3 Å resolution crystal structure of the N-terminally truncated type IV pilin from P. aeruginosa strain P1 (ΔP1) is reported, the first structure of its phylogenetically linked group (group I) to be discussed in the literature. The structure was solved from X-ray diffraction data that were collected 20 years ago with a molecular-replacement search model generated using AlphaFold ; the effectiveness of other search models was analyzed. Examination of the high-resolution ΔP1 structure revealed a solvent network that aids in maintaining the fold of the protein. On comparing the sequence and structure of P1 with a variety of type IV pilins, it was observed that there are cases of higher structural similarities between the phylogenetic groups of P. aeruginosa than there are between the same phylogenetic group, indicating that a structural grouping of pilins may be necessary in developing antivirulence drugs and vaccines. These analyses also identified the α–β loop as the most structurally diverse domain of the pilins, which could allow it to serve a role in pilus recognition. Studies of ΔP1 in vitro polymerization demonstrate that the optimal hydrophobic catalyst for the oligomerization of the pilus from strain K122 is not conducive for pilus formation of ΔP1; a model of a three-start helical assembly using the ΔP1 structure indicates that the α–β loop and the D-loop prevent in vitro polymerization.

Bragagnolo, Nicholas↗
DOE OSTI2026

Human NLRP3 inflammasome activation leads to formation of condensate at the microtubule organizing center

The NLRP3 inflammasome is a multiprotein molecular machine that drives inflammatory responses in innate immunity. Although its dysregulation is implicated in numerous human diseases, its structural organization in cells remains poorly understood. Here, we used precise fluorescence-guided cryo–focused ion beam (cryo-FIB) milling and cryo–electron tomography (cryo-ET) to visualize NLRP3 inflammasomes in situ within human macrophages at various stages of activation. After priming and activation, we observed expansion and dispersion of Golgi cisternae, along with the emergence of 50-nanometer NLRP3-associated vesicles, which likely transport NLRP3 to the MTOC. Dense NLRP3-containing condensates then formed in and around the MTOC. In later stages, the condensates solidified, coincident with widespread mitochondrial damage, autophagy, and pyroptotic cell death.

Wang, Jue [Division of Chemistry and Chemical Engi↗
DOE OSTI2022

Neutron scattering maps the higher-order assembly of NADPH-dependent assimilatory sulfite reductase

Precursor molecules for biomass incorporation must be imported into cells and made available to the molecular machines that build the cell. Sulfur-containing macromolecules require that sulfur be in its S2- oxidation state before assimilation into amino acids, cofactors, and vitamins that are essential to organisms throughout the biosphere. In α-proteobacteria, NADPH-dependent assimilatory sulfite reductase (SiR) performs the final six-electron reduction of sulfur. SiR is a dodecameric oxidoreductase composed of an octameric flavoprotein reductase (SiRFP) and four hemoprotein metalloenzyme oxidases (SiRHPs). SiR performs the electron transfer reduction reaction to produce sulfide from sulfite through coordinated domain movements and subunit interactions without release of partially reduced intermediates. Efforts to understand the electron transfer mechanism responsible for SiR’s efficiency are confounded by structural heterogeneity arising from intrinsically disordered regions throughout its complex, including the flexible linker joining SiRFP’s flavin-binding domains. As a result, high-resolution structures of SiR dodecamer and its subcomplexes are unknown, leaving a gap in the fundamental understanding of how SiR performs this uniquely large-volume electron transfer reaction. In this work, we use deuterium labeling, in vitro reconstitution, analytical ultracentrifugation (AUC), small-angle neutron scattering (SANS), and neutron contrast variation (NCV) to observe the relative subunit positions within SiR’s higher-order assembly. AUC and SANS reveal SiR to be a flexible dodecamer and confirm the mismatched SiRFP and SiRHP subunit stoichiometry. NCV shows that the complex is asymmetric, with SiRHP on the periphery of the complex and the centers of mass between SiRFP and SiRHP components over 100 Å apart. SiRFP undergoes compaction upon assembly into SiR’s dodecamer and SiRHP adopts multiple positions in the complex. The resulting map of SiR’s higher-order structure supports a cis/trans mechanism for electron transfer between domains of reductase subunits as well as between tightly bound or transiently interacting reductase and oxidase subunits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Design of light- and chemically responsive protein assemblies through host-guest interactions

Host-guest (HG) interactions have been widely used to build responsive materials and molecular machines owing to their inherently dynamic nature, interaction specificity, and responsiveness to diverse stimuli. Here, in this work, we have set out to exploit these advantages of HG chemistry in the design of dynamic protein assemblies, using a C 4 symmetric protein, C98 RhuA, as a building block. We show that a C98 RhuA variant individually modified with β-cyclodextrin (βCD) (host) or azobenzene (guest) functionalities can specifically pair with each other to form highly ordered 1D and 2D assemblies. Association and dissociation of βCD RhuA- azo RhuA assemblies can be controlled by UV and visible light as well as by small-molecule modulators of βCD-azobenzene interactions. Kinetics analyses reveal that βCD RhuA- azo RhuA nanotubes assemble without a nucleation barrier, a highly unusual occurrence for helical supramolecular systems. Taken together, our findings provide a compelling example for achieving complex structural and dynamic outcomes in protein assembly through simple chemical design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Hydrodynamic spin-orbit coupling in asynchronous optically driven micro-rotors

Abstract Vortical flows of rotating particles describe interactions ranging from molecular machines to atmospheric dynamics. Yet to date, direct observation of the hydrodynamic coupling between artificial micro-rotors has been restricted by the details of the chosen drive, either through synchronization (using external magnetic fields) or confinement (using optical tweezers). Here we present a new active system that illuminates the interplay of rotation and translation in free rotors. We develop a non-tweezing circularly polarized beam that simultaneously rotates hundreds of silica-coated birefringent colloids. The particles rotate asynchronously in the optical torque field while freely diffusing in the plane. We observe that neighboring particles orbit each other with an angular velocity that depends on their spins. We derive an analytical model in the Stokes limit for pairs of spheres that quantitatively explains the observed dynamics. We then find that the geometrical nature of the low Reynolds fluid flow results in a universal hydrodynamic spin-orbit coupling. Our findings are of significance for the understanding and development of far-from-equilibrium materials.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

A generalized platform for artificial intelligence-powered autonomous enzyme engineering

Proteins are the molecular machines of life with numerous applications in energy, health, and sustainability. However, engineering proteins with desired functions for practical applications remains slow, expensive, and specialist-dependent. Here we report a generally applicable platform for autonomous enzyme engineering that integrates machine learning and large language models with biofoundry automation to eliminate the need for human intervention, judgement, and domain expertise. Requiring only an input protein sequence and a quantifiable way to measure fitness, this automated platform can be applied to engineer a wide array of proteins. As a proof of concept, we engineer Arabidopsis thaliana halide methyltransferase (AtHMT) for a 90-fold improvement in substrate preference and 16-fold improvement in ethyltransferase activity, along with developing a Yersinia mollaretii phytase (YmPhytase) variant with 26-fold improvement in activity at neutral pH. This is accomplished in four rounds over 4 weeks, while requiring construction and characterization of fewer than 500 variants for each enzyme. This platform for autonomous experimentation paves the way for rapid advancements across diverse industries, from medicine and biotechnology to renewable energy and sustainable chemistry.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Transforming an ATP-dependent enzyme into a dissipative, self-assembling system

Nucleoside triphosphate (NTP)-dependent protein assemblies such as microtubules and actin filaments have inspired the development of diverse chemically fueled molecular machines and active materials but their functional sophistication has yet to be matched by design. Given this challenge, we asked whether it is possible to transform a natural adenosine 5'-triphosphate (ATP)-dependent enzyme into a dissipative self-assembling system, thereby altering the structural and functional mode in which chemical energy is used. Furthermore we report that FtsH (filamentous temperature-sensitive protease H), a hexameric ATPase involved in membrane protein degradation, can be readily engineered to form one-dimensional helical nanotubes. FtsH nanotubes require constant energy input to maintain their integrity and degrade over time with the concomitant hydrolysis of ATP, analogous to natural NTP-dependent cytoskeletal assemblies. Yet, in contrast to natural dissipative systems, ATP hydrolysis is catalyzed by free FtsH protomers and FtsH nanotubes serve to conserve ATP, leading to transient assemblies whose lifetimes can be tuned from days to minutes through the inclusion of external ATPases in solution.

59 BASIC BIOLOGICAL SCIENCES↗