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At least 793 records · Page 44

Molecular dissection of the glutamine synthetase-GlnR nitrogen regulatory circuitry in Gram-positive bacteria

How bacteria sense and respond to nitrogen levels are central questions in microbial physiology. In Gram-positive bacteria, nitrogen homeostasis is controlled by an operon encoding glutamine synthetase (GS), a dodecameric machine that assimilates ammonium into glutamine, and the GlnR repressor. GlnR detects nitrogen excess indirectly by binding glutamine-feedback-inhibited-GS (FBI-GS), which activates its transcription-repression function. The molecular mechanisms behind this regulatory circuitry, however, are unknown. Here we describe biochemical and structural analyses of GS and FBI-GS-GlnR complexes from pathogenic and non-pathogenic Gram-positive bacteria. The structures show FBI-GS binds the GlnR C-terminal domain within its active-site cavity, juxtaposing two GlnR monomers to form a DNA-binding-competent GlnR dimer. The FBI-GS-GlnR interaction stabilizes the inactive GS conformation. Strikingly, this interaction also favors a remarkable dodecamer to tetradecamer transition in some GS, breaking the paradigm that all bacterial GS are dodecamers. These data thus unveil unique structural mechanisms of transcription and enzymatic regulation.

59 BASIC BIOLOGICAL SCIENCES↗

Generative $β$-hairpin design using a residue-based physicochemical property landscape

De novo peptide design is a new frontier that has broad application potential in the biological and biomedical fields. Most existing models for de novo peptide design are largely based on sequence homology that can be restricted based on evolutionarily derived protein sequences and lack the physicochemical context essential in protein folding. Generative machine learning for de novo peptide design is a promising way to synthesize theoretical data that are based on, but unique from, the observable universe. In this study, we created and tested a custom peptide generative adversarial network intended to design peptide sequences that can fold into the -hairpin secondary structure. This deep neural network model is designed to establish a preliminary foundation of the generative approach based on physicochemical and conformational properties of 20 canonical amino acids, for example, hydrophobicity and residue volume, using extant structure-specific sequence data from the PDB. The beta generative adversarial network model robustly distinguishes secondary structures of hairpin from α helix and intrinsically disordered peptides with an accuracy of up to 96% and generates artificial -hairpin peptide sequences with minimum sequence identities around 31% and 50% when compared against the current NCBI PDB and nonredundant databases, respectively. These results highlight the potential of generative models specifically anchored by physicochemical and conformational property features of amino acids to expand the sequence-to-structure landscape of proteins beyond evolutionary limits.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Damage to Polystyrene Polymer Film by Shock Wave Induced Bubble Collapse

Metallic surfaces that are in contact with solutions are commonly used in numerous applications where these surfaces can be damaged by shock wave induced bubble collapse. Use of polymer films that coat such surfaces to prevent them from damage requires a better understanding of how much harm collapsing bubbles produce in the films. In this study, we report the results from coarse-grained molecular dynamics simulations to study the damage to polystyrene (PS) films coating a hard surface. The damage was caused by a collapsing nanobubble located in the proximity of the film and interacting with an impinging shock wave. This collapse produces a high-speed water jet that impacts the PS film with a greater force than the shock front and creates cavities/pits in the PS film. We observed that polymer molecules located in the jet vicinity undergo conformational extension in the direction perpendicular to the jet motion, while chain molecules in the rest of the film undergo compression. Furthermore, we also observed that damage to the film is sensitive to the strength of the shock wave.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Polymer Crosslinked 3-D Assemblies of Nanoparticles: Mechanically Strong Lightweight Porous Materials

In analogy to supramolecular assemblies, which are pursued because of properties above and beyond those of the individual molecules, self-standing monolithic three-dimensional assemblies of nanoparticles also have unique properties attributed to their structure. For example, ultra low-density 3-D assemblies of silica nanoparticles, known as silica aerogels, are characterized by large internal void space, high surface area and very low thermal conductivity. Aerogels, however, are also extremely fragile materials, limiting their application to a few specialized environments, e.g., in nuclear reactors as Cerenkov radiation detectors, in space (refer to NASA's Stardust Program) and aboard certain planetary vehicles (thermal insulators on Mars Rovers in 1997 and 2004). The fragility problem is traced to well-defined weak points in the aerogel skeletal framework, the interparticle necks. Using the surface functionality of the nanoparticle building blocks as a focal point, we have directed attachment of a conformal polymer coating over the entire framework, rendering all necks wider. Thus, although the bulk density may increase only by 3x, the mesoporosity (pores in the range 2-50 nm) remains unchanged, while the strength of the material increases by up to 300... Having addressed the fragility problem, aerogels are now robust materials, and a variety of applications, ranging from thermal/acoustic insulators to catalyst supports, to platform for sensors, and dielectrics are all within reach. Our approach employs molecular science to manipulate nanoscopic matter for achieving useful macroscopic properties, and in our view it resides at the core of what defines nanotechnology. In that spirit, this technology is expandable in three directions. Thus, we have already crosslinked successfully amine-modified silica, and we anticipate that more rich chemistry will be realized by been creative with the nanoparticle surface modifiers. On the other hand, although we do not expect orders-of-magnitude increase in strength, nevertheless, by varying the polymer we expect to impart other properties such as hydrophobicity, thermal stability and perhaps electrical conductivity. Besides polymers, crosslinkers will include metals and ceramics (e.g., through POSS precursors). Finally, network morphology directs load dissipation, and of approximately 30 different crosslinked oxide aerogels, vanadia, whose structure is fibrous rather than particulate, yields a much stronger (by 4..) material than silica of the same density. It seems imperative to implement control of network morphology, even through templating.

Leventis, Nicholas↗

The confluence of machine learning and multiscale simulations

Multiscale modeling has a long history of use in structural biology, as computational biologists strive to overcome the time- and length-scale limits of atomistic molecular dynamics. Contemporary machine learning techniques, such as deep learning, have promoted advances in virtually every field of science and engineering and are revitalizing the traditional notions of multiscale modeling. Deep learning has found success in various approaches for distilling information from fine-scale models, such as building surrogate models and guiding the development of coarse-grained potentials. However, perhaps its most powerful use in multiscale modeling is in defining latent spaces that enable efficient exploration of conformational space. In conclusion, this confluence of machine learning and multiscale simulation with modern high-performance computing promises a new era of discovery and innovation in structural biology.

59 BASIC BIOLOGICAL SCIENCES↗

A simple technique to classify diffraction data from dynamic proteins according to individual polymorphs

One often observes small but measurable differences in the diffraction data measured from different crystals of a single protein. These differences might reflect structural differences in the protein and may reveal the natural dynamism of the molecule in solution. Partitioning these mixed-state data into single-state clusters is a critical step that could extract information about the dynamic behavior of proteins from hundreds or thousands of single-crystal data sets. Mixed-state data can be obtained deliberately (through intentional perturbation) or inadvertently (while attempting to measure highly redundant single-crystal data). To the extent that different states adopt different molecular structures, one expects to observe differences in the crystals; each of the polystates will create a polymorph of the crystals. After mixed-state diffraction data have been measured, deliberately or inadvertently, the challenge is to sort the data into clusters that may represent relevant biological polystates. Here, this problem is addressed using a simple multi-factor clustering approach that classifies each data set using independent observables, thereby assigning each data set to the correct location in conformational space. This procedure is illustrated using two independent observables, unit-cell parameters and intensities, to cluster mixed-state data from chymotrypsinogen (ChTg) crystals. It is observed that the data populate an arc of the reaction trajectory as ChTg is converted into chymotrypsin.

36 MATERIALS SCIENCE↗

Ethanol-Induced Condensation and Decondensation in DNA-Linked Nanoparticles: A Nucleosome-like Model for the Condensed State

Inspired by the conventional use of ethanol to induce DNA precipitation, ethanol condensation has been applied as a routine method to dynamically tune “bond” lengths (i.e., the surface-to-surface distances between adjacent nanoparticles that are linked by DNA) and thermal stabilities of colloidal crystals involving DNA-linked nanoparticles. However, the underlying mechanism of how the DNA bond that links gold nanoparticles changes in this class of colloidal crystals in response to ethanol remains unclear. Here, we conducted a series of all-atom molecular dynamic (MD) simulations to explore the free energy landscape for DNA condensation and decondensation. Our simulations confirm that DNA condensation is energetically much more favorable under 80% ethanol conditions than in pure water, as a result of ethanol’s role in enhancing electrostatic interactions between oppositely charged species. Moreover, the condensed DNA adopts B-form in pure water and A-form in 80% ethanol, which indicates that the higher-order transition does not affect DNA’s conformational preferences. We further propose a nucleosome-like supercoiled model for the DNA condensed state, and we show that the DNA end-to-end distance derived from this model matches the experimentally measured DNA bond length of about 3 nm in the fully condensed state for DNA where the measured length is 16 nm in water. Altogether, this study provides an atomistic understanding of the mechanism underlying ethanol-induced condensation and water-induced decondensation, while our proposed nucleosome-like model allows the design of new strategies for interpreting experimental studies of DNA condensation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational design of mechanically coupled axle-rotor protein assemblies

Natural molecular machines contain protein components that undergo motion relative to each other. Designing such mechanically constrained nanoscale protein architectures with internal degrees of freedom is an outstanding challenge for computational protein design. Here we explore the de novo construction of protein machinery from designed axle and rotor components with internal cyclic or dihedral symmetry. We find that the axle-rotor systems assemble in vitro and in vivo as designed. Using cryo–electron microscopy, we find that these systems populate conformationally variable relative orientations reflecting the symmetry of the coupled components and the computationally designed interface energy landscape. These mechanical systems with internal degrees of freedom are a step toward the design of genetically encodable nanomachines.

Science & Technology - Other Topics↗

Tailoring Molecular-Scale Contact at Perovskite/Polymeric Hole Transporting Material Interface for Efficient Solar Cells

Perovskite solar cells (PSCs) have delivered more than 25% of power conversion efficiency (PCE) and incorporating polymers as hole transporting layers (HTLs) can further enhance the stability of devices towards the goal of commercialization. Among various polymeric hole transporting materials, poly(triaryl amine) (PTAA) is one of the promising HTL candidates with good stability; however, the hydrophobicity of PTAA causes problematic interfacial contact with perovskite, limiting the device performance. Using molecular side-chain engineering, we successfully constructed a uniform two-dimensional (2D) perovskite interlayer with conjugated ligands, between three-dimensional (3D) perovskites and PTAA. Further, employing conjugated ligands as cohesive elements, perovskite/PTAA interfacial adhesion was significantly improved. As a result, the thin and lateral extended 2D/3D heterostructure enabled the as-fabricated PTAA-based PSCs to achieve a PCE of 23.7%, improved from the 18% of reference devices. Owing to the increased ion migration energy barrier and conformal 2D coating, unencapsulated devices with the new ligands exhibited both superior thermal stability under 60°C heating and moisture stability in ambient conditions.

14 SOLAR ENERGY↗

Reversible domain closure modulates GlnBP ligand binding affinity

Glutamine binding protein (GlnBP) is an Escherichia Coli periplasmic binding protein, which binds and carries glutamine to the inner membrane ATP-binding cassette (ABC) transporter. GlnBP binds the ligand with affinity around 0.1μM measured by isothermal titration calorimetry (ITC) and ligand binding stabilizes protein structure shown by its increase in thermodynamic stability. However, the molecular determinant of GlnBP ligand binding is not known. Electrostatic and hydrophobic interaction between GlnBP and glutamine are critical factors. We propose that the freedome of closure movement is also vital for ligand binding. In order to approve this hypothesis, we generate a series of mutants with different linker length that has different magnitude of domain closure. Mutants show different ligand binding affinity, which indicates that the propensity of domain closure determines the ligand binding affinity. Ligand binding triggers gradual ensemble conformational change. Structural changes upon ligand binding are monitored by combination of small angle x-ray scattering (SAXS) and NMR spectroscopy. Detailed structure characterization of GlnBP contributes to a better understanding of ligand binding and provides the structural basis for biosensor design.

59 BASIC BIOLOGICAL SCIENCES↗

Inhibition of the proton-activated chloride channel PAC by PIP 2

Proton-activated chloride (PAC) channel is a ubiquitously expressed pH-sensing ion channel, encoded by PACC1 (TMEM206). PAC regulates endosomal acidification and macropinosome shrinkage by releasing chloride from the organelle lumens. It is also found at the cell surface, where it is activated under pathological conditions related to acidosis and contributes to acid-induced cell death. However, the pharmacology of the PAC channel is poorly understood. Here, we report that phosphatidylinositol (4,5)-bisphosphate (PIP 2 ) potently inhibits PAC channel activity. We solved the cryo-electron microscopy structure of PAC with PIP 2 at pH 4.0 and identified its putative binding site, which, surprisingly, locates on the extracellular side of the transmembrane domain (TMD). While the overall conformation resembles the previously resolved PAC structure in the desensitized state, the TMD undergoes remodeling upon PIP 2 -binding. Structural and electrophysiological analyses suggest that PIP 2 inhibits the PAC channel by stabilizing the channel in a desensitized-like conformation. Our findings identify PIP 2 as a new pharmacological tool for the PAC channel and lay the foundation for future drug discovery targeting this channel.

59 BASIC BIOLOGICAL SCIENCES↗

CryoEM structures of the human CLC-2 voltage-gated chloride channel reveal a ball-and-chain gating mechanism

CLC-2 is a voltage-gated chloride channel that contributes to electrical excitability and ion homeostasis in many different tissues. Among the nine mammalian CLC homologs, CLC-2 is uniquely activated by hyperpolarization, rather than depolarization, of the plasma membrane. The molecular basis for the divergence in polarity of voltage gating among closely related homologs has been a long-standing mystery, in part because few CLC channel structures are available. Here, we report cryoEM structures of human CLC-2 at 2.46 – 2.76 Å, in the presence and absence of the selective inhibitor AK-42. AK-42 binds within the extracellular entryway of the Cl – -permeation pathway, occupying a pocket previously proposed through computational docking studies. In the apo structure, we observed two distinct conformations involving rotation of one of the cytoplasmic C-terminal domains (CTDs). In the absence of CTD rotation, an intracellular N-terminal 15-residue hairpin peptide nestles against the TM domain to physically occlude the Cl – -permeation pathway. This peptide is highly conserved among species variants of CLC-2 but is not present in other CLC homologs. Previous studies suggested that the N-terminal domain of CLC-2 influences channel properties via a “ball-and-chain” gating mechanism, but conflicting data cast doubt on such a mechanism, and thus the structure of the N-terminal domain and its interaction with the channel has been uncertain. Through electrophysiological studies of an N-terminal deletion mutant lacking the 15-residue hairpin peptide, we support a model in which the N-terminal hairpin of CLC-2 stabilizes a closed state of the channel by blocking the cytoplasmic Cl – -permeation pathway.

59 BASIC BIOLOGICAL SCIENCES↗

Adsorption of Non-Ionic Surfactant and Monoclonal Antibody on Siliconized Surface Studied by Neutron Reflectometry

The adsorption of monoclonal antibodies (mAbs) on hydrophobic surfaces is known to cause protein aggregation and degradation. Therefore, surfactants, such as Poloxamer 188, are widely used in therapeutic formulations to stabilize mAbs and protect mAbs from interacting with liquid-solid interfaces. Here, the adsorption of Poloxamer 188, one mAb and their competitive adsorption on a model hydrophobic siliconized surface is investigated with neutron scattering coupled with contrast variation to determine the molecular structure of adsorbed layers for each case. Small angle neutron scattering measurements of the affinity of Poloxamer 188 to this mAb indicate that there is negligible binding at these solution conditions. Neutron reflectometry measurements of the mAb show irreversible adsorption on the siliconized surface, which cannot be washed off with neat buffer. Poloxamer 188 can be adsorbed on the surface already occupied by mAb, which enables partial removal of some adsorbed mAb by washing with buffer. The adsorption of the surfactant introduces significant conformational changes for mAb molecules that remain on the surface. In contrast, if the siliconized surface is first saturated with the surfactant, no adsorption of mAb is observed. Competitive adsorption of mAb and Poloxamer 188 from solution leads to a surface dominantly occupied with surfactant molecules, whereas only a minor amount of mAb absorbs. These findings clearly indicate that Poloxamer 188 can protect against mAb adsorption as well as modify the adsorbed conformation of previously adsorbed mAb.

36 MATERIALS SCIENCE↗

Integrated Quantum-Classical Protocol for the Realistic Description of Solvated Multinuclear Mixed-Valence Transition-Metal Complexes and Their Solvatochromic Properties

Linear cyanide-bridged polymetallic complexes, which undergo photoinduced metal-to-metal charge transfer, represent prototypical systems for studying long-range electron-transfer reactions and understanding the role played by specific solute–solvent interactions in modulating the excited-state dynamics. Here, to tackle this problem, while achieving a statistically meaningful description of the solvent and of its relaxation, one needs a computational approach capable of handling large polynuclear transition-metal complexes, both in their ground and excited states, as well as the ability to follow their dynamics in several environments up to nanosecond time scales. Here, we present a mixed quantum classical approach, which combines large-scale molecular dynamics (MD) simulations based on an accurate quantum mechanically derived force field (QMD-FF) and self-consistent QMD polarized point charges, with IR and UV–vis spectral calculations to model the solvation dynamics and optical properties of a cyano-bridged trinuclear mixed-valence compound (trans-[(NC) 5 Fe III (μ-CN)Ru II (pyridine) 4 (μ-NC)Fe III (CN) 5 ] 4– ). We demonstrate the reliability of the QMD-FF/MD approach in sampling the solute conformational space and capturing the local solute–solvent interactions by comparing the results with higher-level quantum mechanics/molecular mechanics (QM/MM) MD reference data. The IR spectra calculated along the classical MD trajectories in different solvents correctly predict the red shift of the CN stretching band in the aprotic medium (acetonitrile) and the subtle differences measured in water and methanol, respectively. By explicitly including the solvent molecules around the cyanide ligands and calculating the thermal averaged absorption spectra using time-dependent density functional theory calculations within the Tamm–Dancoff approximation, the experimental solvatochromic shift is quantitatively reproduced going from water to methanol, while it is overestimated for acetonitrile. This discrepancy can likely be traced back to the lack of important dispersion interactions between the solvent cyano groups and the pyridine substituents in our micro solvation model. The proposed protocol is applied to the ground state in water, methanol, and acetonitrile and can be flexibly generalized to study excited-state nonequilibrium solvation dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multidisciplinary studies with mutated HIV-1 capsid proteins reveal structural mechanisms of lattice stabilization

Abstract HIV-1 capsid (CA) stability is important for viral replication. E45A and P38A mutations enhance and reduce core stability, thus impairing infectivity. Second-site mutations R132T and T216I rescue infectivity. Capsid lattice stability was studied by solving seven crystal structures (in native background), including P38A, P38A/T216I, E45A, E45A/R132T CA, using molecular dynamics simulations of lattices, cryo-electron microscopy of assemblies, time-resolved imaging of uncoating, biophysical and biochemical characterization of assembly and stability. We report pronounced and subtle, short- and long-range rearrangements: (1) A38 destabilized hexamers by loosening interactions between flanking CA protomers in P38A but not P38A/T216I structures. (2) Two E45A structures showed unexpected stabilizing CA NTD -CA NTD inter-hexamer interactions, variable R18-ring pore sizes, and flipped N-terminal β-hairpin. (3) Altered conformations of E45A a α9-helices compared to WT, E45A/R132T, WT PF74 , WT Nup153 , and WT CPSF6 decreased PF74, CPSF6, and Nup153 binding, and was reversed in E45A/R132T. (4) An environmentally sensitive electrostatic repulsion between E45 and D51 affected lattice stability, flexibility, ion and water permeabilities, electrostatics, and recognition of host factors.

60 APPLIED LIFE SCIENCES↗

Nonlinear Shear Rheology of Entangled Polymer Rings

Steady-state shear viscosity η($\bar{γ}$) of unconcatenated ring polymer melts as a function of the shear rate $\bar{γ}$ is studied by a combination of experiments, simulations, and theory. Experiments using polystyrenes with Z ≈ 5 and Z ≈ 11 entanglements indicate weaker shear thinning for rings compared to linear polymers exhibiting power law scaling of shear viscosity η ~ $\bar{γ}$ –0.56 ± 0.02 , independent of chain length, for Weissenberg numbers up to about 10 2 . Nonequilibrium molecular dynamics simulations using the bead-spring model reveal a similar behavior with η ~ $\bar{γ}$ -0.57 ± 0.08 for 4 ≤ Z ≤ 57. Viscosity decreases with chain length for high $\bar{γ}$. In our experiments, we see the onset of this regime, and in simulations, which we extended to Wi ~ 10 4 , the nonuniversality is fully developed. In addition to a naive scaling theory yielding for the universal regime η ~ $\bar{γ}$ –0.57 , we developed a novel shear slit model explaining many details of observed conformations and dynamics as well as the chain length-dependent behavior of viscosity at large $\bar{γ}$. The signature feature of the model is the presence of two distinct length scales: the size of tension blobs and much larger thickness of a shear slit in which rings are self-consistently confined in the velocity gradient direction and which is dictated by the size of a chain section with relaxation time 1/$\bar{γ}$. These two length scales control the two normal stress differences. In this model, the chain length-dependent onset of nonuniversal behavior is set by tension blobs becoming as small as about one Kuhn segment. This model explains the approximate applicability of the Cox–Merz rule for ring polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanism and inhibition of Streptococcus pneumoniae IgA1 protease

Opportunistic pathogens such as Streptococcus pneumoniae secrete a giant metalloprotease virulence factor responsible for cleaving host IgA1, yet the molecular mechanism has remained unknown since their discovery nearly 30 years ago despite the potential for developing vaccines that target these enzymes to block infection. Here we show through a series of cryo-electron microscopy single particle reconstructions how the Streptococcus pneumoniae IgA1 protease facilitates IgA1 substrate recognition and how this can be inhibited. Specifically, the Streptococcus pneumoniae IgA1 protease subscribes to an active-site-gated mechanism where a domain undergoes a 10.0 Å movement to facilitate cleavage. Monoclonal antibody binding inhibits this conformational change, providing a direct means to block infection at the host interface. These structural studies explain decades of biological and biochemical studies and provides a general strategy to block Streptococcus pneumoniae IgA1 protease activity to potentially prevent infection.

59 BASIC BIOLOGICAL SCIENCES↗