How ATP and dATP Act as Molecular Switches to Regulate Enzymatic Activity in the Prototypical Bacterial Class Ia Ribonucleotide Reductase
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Results for “biological physics”
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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VPS26 Moonlights as a β-Arrestin-like Adapter for a 7-Transmembrane RGS Protein in Arabidopsis thaliana
Extracellular signals perceived by 7-transmembrane (7TM)-spanning receptors initiate desensitization that involves the removal of these receptors from the plasma membrane. Agonist binding often evokes phosphorylation in the flexible C-terminal region and/or intracellular loop 3 of many 7TM G-protein-coupled receptors in animal cells, which consequently recruits a cytoplasmic intermediate adaptor, β-arrestin, resulting in clathrin-mediated endocytosis (CME) and downstream signaling such as transcriptional changes. Some 7TM receptors undergo CME without recruiting β-arrestin, but it is not clear how. Arrestins are not encoded in the Arabidopsis thaliana genome, yet Arabidopsis cells have a well-characterized signal-induced CME of a 7TM protein, designated Regulator of G Signaling 1 (AtRGS1). Here we show that a component of the retromer complex, Vacuolar Protein Sorting-Associated 26 (VPS26), binds the phosphorylated C-terminal region of AtRGS1 as a VPS26A/B heterodimer to form a complex that is required for downstream signaling. We propose that VPS26 moonlights as an arrestin-like adaptor in the CME of AtRGS1.
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DNA Replication across α- l -(3′-2′)-Threofuranosyl Nucleotides Mediated by Human DNA Polymerase η
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Native Chemical Ligation of Peptoid Oligomers
Bioorganic chemists are inspired by natural biopolymers to design peptidomimetic oligomers that can exhibit sequence-structure-function relationships. Biomimetic polymers can be synthesized to incorporate a specific sequence of nonbiological monomer units using a variety of iterative solution-phase or solid-phase reaction schemes. These protocols generally provide access to a vast diversity of oligomeric compounds but are limited with respect to their ability to attain protein-like chain lengths. This constraint can preclude access to sequence-defined synthetic macromolecules with sufficient sizes required to exhibit tertiary structure and other protein-mimetic attributes. In contrast, peptide chemists have overcome this limitation by developing convergent synthetic methods, such as native chemical ligation, to join individual, smaller peptide chains together to make larger peptides or full proteins. A similar convergent approach is needed to establish efficient synthetic routes to non-natural sequence-defined macromolecules. Herein, we adapt the peptide native chemical ligation method to peptoid oligomers, demonstrating how short chains can be conjoined to create sequence-defined peptoid macromolecules. Nanosheet-forming peptoid polymers with distinct surface loop display domains were generated by sequential ligation of several discrete fragments. This method provides a reliable convergent ligation route for sequence-defined polypeptoids that results in a native amide bond joining the fragments. We envision that this strategy will be useful in synthesizing peptoid-based proteomimetics that incorporate diverse chemical features.
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Interconnection of the Antenna Pigment 8-HDF and Flavin Facilitates Red-Light Reception in a Bifunctional Animal-like Cryptochrome
Cryptochromes are ubiquitous flavin-binding light sensors closely related to DNA-repairing photolyases. The animal-like cryptochrome CraCRY from the green alga Chlamydomonas reinhardtii challenges the paradigm of cryptochromes as pure blue-light receptors by acting as a (6-4) photolyase, using 8-hydroxy-5-deazaflavin (8-HDF) as a light-harvesting antenna with a 17.4 Å distance to flavin and showing spectral sensitivity up to 680 nm. The expanded action spectrum is attributed to the presence of the flavin neutral radical (FADH•) in the dark, despite a rapid FADH• decay observed in vitro in samples exclusively carrying flavin. Herein, the red-light response of CraCRY carrying flavin and 8-HDF was studied, revealing a 3-fold prolongation of the FADH• lifetime in the presence of 8-HDF. Millisecond time-resolved ultraviolet-visible spectroscopy showed the red-light-induced formation and decay of an absorbance band at 458 nm concomitant with flavin reduction. Time-resolved Fourier transform infrared (FTIR) spectroscopy and density functional theory attributed these changes to the deprotonation of 8-HDF, challenging the paradigm of 8-HDF being permanently deprotonated in photolyases. FTIR spectra showed changes in the hydrogen bonding network of asparagine 395, a residue suggested to indirectly control flavin protonation, indicating the involvement of N395 in the stabilization of FADH•. Fluorescence spectroscopy revealed a decrease in the energy transfer efficiency of 8-HDF upon flavin reduction, possibly linked to 8-HDF deprotonation. Finally, the discovery of the interdependence of flavin and 8-HDF beyond energy transfer processes highlights the essential role of the antenna, introducing a new concept enabling CraCRY and possibly other bifunctional cryptochromes to fulfill their dual function.
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Cofactor Complexes of DesD, a Model Enzyme in the Virulence-related NIS Synthetase Family
The understudied nonribosomal-peptide-synthetase-independent siderophore (NIS) synthetase family has been increasingly associated with virulence in bacterial species due to its key role in the synthesis of hydroxamate and carboxylate "stealth" siderophores. We have identified a model family member, DesD, from Streptomyces coelicolor , to structurally characterize using a combination of a wild-type and a Arg306Gln variant in apo , cofactor product AMP-bound, and cofactor reactant ATP-bound complexes. The kinetics in the family has been limited by solubility and reporter assays, so we have developed a label-free kinetics assay utilizing a single-injection isothermal-titration-calorimetry-based method. We report second-order rate constants that are 50 times higher than the previous estimations for DesD. Our Arg306Gln DesD variant was also tested under identical buffer and substrate conditions, and its undetectable activity was confirmed. These are the first reported structures for DesD, and they describe the critical cofactor coordination. This is also the first label-free assay to unambiguously determine the kinetics for an NIS synthetase.
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Structure, Hydration, and Interactions of Native and Hydrophobically Modified Phytoglycogen Nanoparticles
Phytoglycogen is a highly branched polymer of glucose produced as soft, compact nanoparticles by sweet corn. Properties such as softness, porosity, and mechanical integrity, combined with nontoxicity and biodegradability, make phytoglycogen nanoparticles ideal for applications involving the human body, ranging from skin moisturizing and rejuvenation agents in personal care formulations to functional therapeutics in biomedicine. To further broaden the range of applications, phytoglycogen nanoparticles can be chemically modified with hydrophobic species such as octenyl succinic anhydride (OSA). In this study, we present a self-consistent model of the particle structure, water content, and degree of chemical modification of the particles, as well as the emergence of well-defined interparticle spacings in concentrated dispersions, based on small-angle neutron scattering (SANS) measurements of aqueous dispersions of native phytoglycogen nanoparticles and particles that were hydrophobically modified using octenyl succinic anhydride (OSA) in both its protiated (pOSA) and deuterated (dOSA) forms. Measurements on native particles with reduced polydispersity have allowed us to refine the particle morphology, which is well described by a hairy particle (core-chain) geometry with short chains decorating the surface of the particles. The isotopic variants of OSA-modified particles enhanced the scattering contrast for neutrons, revealing lightly modified hairy chains for small degrees of substitution (DS) of OSA, and a raspberry particle geometry for the largest DS value, where the OSA-modified hairy chains collapse to form small seeds on the surface of the particles. This refined model of native and OSA-modified phytoglycogen nanoparticles establishes a quantitative basis for the development of new applications of this promising sustainable nanotechnology.
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Effects of Charge Sequence Pattern and Lysine-to-Arginine Substitution on the Structural Stability of Bioinspired Polyampholytes
A comprehensive study focusing on the combined influence of the charge sequence pattern and the type of positively charged amino acids on the formation of secondary structures in sequence-specific polyampholytes is presented. The sequences of interest consisting exclusively of ionizable amino acids (lysine, K; arginine, R; and glutamic acid, E) are (EKEK) 5 , (EKKE) 5 , (ERER) 5 , (ERRE) 5 , and (EKER) 5 . The stability of the secondary structure was examined at three pH values in the presence of urea and NaCl. The results presented here underscore the combined prominent effects of the charge sequence pattern and the type of positively charged monomers on secondary structure formation. Additionally, (ERRE) 5 readily aggregated across a wide range of pH. In contrast, sequences with the same charge pattern, (EKKE) 5 , as well as the sequences with the equivalent amino acid content, (ERER) 5 , exhibited no aggregate formation under equivalent pH and concentration conditions.
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Soft Nanoconfinement Nucleates and Stabilizes Ultrasmall Amorphous Calcium Carbonate from Aggregation
Organisms use soft confinement structures, such as vesicles and compartments, to direct the nucleation of calcium carbonate (CaCO 3 ) and its subsequent processes during biomineralization. Despite recent efforts elucidating confinement’s effects on CaCO 3 polymorph selection, we still poorly understand how the size and distribution of CaCO 3 are controlled within soft confinement. Here, using a size-controlled nanoemulsions system made from isooctane, Span 80, Tween 80, and aqueous solutions, we studied CaCO 3 formation in soft confinement. Small angle X-ray scattering (SAXS) confirmed that a 72 nm aqueous core in nanoemulsions served as the confined space for CaCO 3 formation. Unlike the ~ 50 nm CaCO 3 particles that formed in the unconfined solution, small angle neutron scattering (SANS) and transmission electron microscope (TEM) showed that ultrasmall and amorphous calcium carbonate precipitated within soft confinement and did not exhibit any aggregation/coalescence of nanoparticles even after 24 hrs of reaction.
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The Intermetallic Reactivity Database: Compiling Chemical Pressure and Electronic Metrics toward Materials Design and Discovery
Here, the advent of high-throughput Density Functional Theory (DFT) calculations has supported the creation of large databases containing the quantitative output necessary for constructing theoretical phase diagrams and predicting physical properties. In this Article, we present a complementary resource, the Intermetallic Reactivity Database (IRD), focused on the chemical bonding features of solid-state structures and indicators of potential structural transformations. Each IRD entry augments common features, such as band structures and density of states (DOS) distributions, with chemically motivated information including DFT-Chemical Pressure (CP) schemes and visualizable representations of the atomic charges. Together, these data types enable the rationalization and prediction of potential structural phenomena encountered in intermetallic chemistry, as we illustrate with four examples: the origins of the Y 2 Ni 2 Mg structure in terms of CP features of its parent structures, the anticipation of intergrowth phases from the net atomic CPs collected in Al-containing binary phases, the correlation between trends in the CP schemes of CaCu 5 -type phases and experimentally observed structural variations, and finally, the development of theoretical methodology with the testing of a streamlined method generating DFT-CP schemes. Altogether, these examples highlight how the IRD supports the creation of models of structural chemistry that extend beyond the bounds of its entries.
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Computational Construction of Toxicant Signaling Networks
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Elucidation of Structure and Physical Properties of Pyrolytic Sugar Oligomers Derived from Cellulose Depolymerization/Dehydration Reactions: A Density Functional Theory Study
Fast pyrolysis of lignocellulosic materials is a promising research area to produce renewable fuels and chemicals. Dehydration is known to be among the most important reaction families during cellulose pyrolysis; water is the most important product. Together with water, dehydration reactions also form a range of poorly known oligomer species of varying molecular sizes, often collected as part of bio-oil water-soluble (WS) fraction. In this work, we used electronic structure calculations to evaluate the relative thermodynamic stabilities of several oligomer species resulting from up to three consecutive dehydration events from cellulose depolymerization intermediates. A library of the thermodynamically favored candidate molecular structures was compiled. Results revealed that most of the water molecules are eliminated from the non-reducing end, forming thermodynamically more stable conjugated compounds. This is consistent with results reported by other researchers in literature where dehydration reactions occur preferably at the non-reducing ends of oligomers. The physical-chemical properties of the proposed structures were estimated using quantitative structure-property relationships (QSPRs) and quantitative property-property relationships (QPPRs). The anhydro-sugars derived from cellulose are often blamed for coke formation during bio-oil hydrotreatment. Understanding their chemical structure could help to develop rational strategies to mitigate coke formation. Furthermore, the thermo-physical properties reported (boiling point, melting point, Gibb’s free energy of formation, enthalpy of formation, and solubility parameters among others) are also fundamental to conducting first principle engineering calculations to design and analyze new pyrolysis reactors and bio-oil up-grading units.
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Multiobjective Optimal Controlled Variable Selection for a Gas Turbine–Solid Oxide Fuel Cell System Using a Multiagent Optimization Platform
Hybrid gas turbine–fuel cell systems have immense potential for high efficiency in electrical power generation with cleaner emissions compared with fossil-fueled power generation. We report a systematic controlled variable (CV) selection method is deployed for a hybrid gas turbine–fuel cell system in the HyPer (hybrid performance) facility at the U.S. Department of Energy’s National Energy Technology Laboratory (NETL) for maximizing its economic and control performance. A three-stage approach is used for the CV selection comprising a priori analysis, multiobjective optimization, and a posteriori analysis. The a priori analysis helps to screen off several candidate CVs, thus reducing the size of the combinatorial optimization problem for multiobjective CV selection. For optimal CV selection, a transfer function model of the HyPer facility is identified. By considering several candidate models, the final transfer function model is selected using Akaike’s Final Prediction Error criterion. Experimental data from the HyPer facility are used to estimate the noise in the measurement data. For solving the combinatorial multiobjective optimization problem for CV selection, a multiagent optimization platform comprising simulated annealing, genetic algorithm, and efficient ant colony optimization algorithms is used. Pareto-optimal CV sets exhibit a high trade-off between the economic and control objective. The a posteriori analysis is undertaken for several top Pareto-optimal CV sets. An optimal CV set is selected that shows the best compromise between process economics and controllability under both nominal and off-design conditions.
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EPR and 31 P ENDOR Characterization of Pseudo-Jahn–Teller Dynamics and N 2 Activation in Functional Nitrogenase Models, P 3 E M(N 2 ) (M = Fe, Co; E = Si, B, C)
Here, the nominally trigonal, pseudo-Jahn-Teller (PJT)-active, S = ½ N 2 -bound transition-metal complexes, P 3 E M(N 2 ), M = Fe, Co, with three in-plane phosphine-ligands and axial donors, E = Si, B, C, include functional nitrogenase models that catalyze reduction of N 2 to NH 3 . We applied EPR, 31 P ENDOR spectroscopy and DFT computations to characterize the PJT-induced distortions of four selected P 3 E M(N 2 ), revealing how the metal-ion and axial ligand E together tune both PJT dynamics and N 2 activation for reduction. Comparisons reveal an unrecognized correlation between PJT distortion, M-E bond elasticity, and N 2 activation, providing guidelines for designing bioinspired N 2 -reduction catalysts.
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Machine Learning Algorithm Identifies an Antibiotic Vocabulary for Permeating Gram-Negative Bacteria
Drug discovery faces a crisis. The industry has used up the “obvious” space in which to find novel drugs for biomedical applications, and productivity is declining. One strategy to combat this is rational approaches to expand the search space without relying on chemical intuition, to avoid rediscovery of similar spaces. Here, we present proof of concept of an approach to rationally identify a “chemical vocabulary” related to a specific drug activity of interest without employing known rules. We focus on the pressing concern of multidrug resistance in Pseudomonas aeruginosa by searching for submolecules that promote compound entry into this bacterium. By synergizing theory, computation, and experiment, we validate our approach, explain the molecular mechanism behind identified fragments promoting compound entry, and select candidate compounds from an external library that display good permeation ability.
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Improving Enzyme Optimum Temperature Prediction with Resampling Strategies and Ensemble Learning
Accurate prediction of the optimal catalytic temperature ( T opt ) of enzymes is vital in biotechnology, as enzymes with high T opt values are desired for enhanced reaction rates. Recently, a machine learning method (temperature optima for microorganisms and enzymes, TOME) for predicting T opt was developed. TOME was trained on a normally distributed data set with a median T opt of 37 °C and less than 5% of T opt values above 85 °C, limiting the method’s predictive capabilities for thermostable enzymes. Due to the distribution of the training data, the mean squared error on T opt values greater than 85 °C is nearly an order of magnitude higher than the error on values between 30 and 50 °C. Here, we apply ensemble learning and resampling strategies that tackle the data imbalance to significantly decrease the error on high T opt values (>85 °C) by 60% and increase the overall R 2 value from 0.527 to 0.632. The revised method, temperature optima for enzymes with resampling (TOMER), and the resampling strategies applied in this work are freely available to other researchers as Python packages on GitHub.
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Ligand-Binding-Site Refinement to Generate Reliable Holo Protein Structure Conformations from Apo Structures
The first important step in a structure-based virtual screening is the judicious selection of a receptor protein. In cases where the holo protein receptor structure is unavailable, significant reduction in virtual screening performance has been reported. In this work, we present a robust method to generate reliable holo protein structure conformations from apo structures using molecular dynamics (MD) simulation with restraints derived from holo structure binding-site templates. We perform benchmark tests on two different datasets: 40 structures from a directory of useful decoy-enhanced (DUD-E) and 84 structures from the Gunasekaran dataset. Our results show successful refinement of apo binding-site structures toward holo conformations in 82% of the test cases. In addition, virtual screening performance of 40 DUD-E structures is significantly improved using our MD-refined structures as receptors with an average enrichment factor (EF), an EF1% value of 6.2 compared to apo structures with 3.5. Docking of native ligands to the refined structures shows an average ligand root mean square deviation (RMSD) of 1.97 Å (DUD-E dataset and Gunasekaran dataset) relative to ligands in the holo crystal structures, which is comparable to the self-docking (i.e., docking of the native ligand back to its crystal structure receptor) average, 1.34 Å (DUD-E dataset) and 1.36 Å (Gunasekaran dataset). On the other hand, docking to the apo structures yields an average ligand RMSD of 3.65 Å (DUD-E) and 2.90 Å (Gunasekaran). These results indicate that our method is robust and can be useful to improve virtual screening performance of apo structures.
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