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Insights into Active Sites and Mechanisms of Benzyl Alcohol Oxidation on Nickel–Iron Oxyhydroxide Electrodes
The electrochemical oxidation of bio-derived molecules has recently garnered interest for its potential in opening electrified synthetic pathways toward value-added products. Herein, we investigate the electrochemical conversion of benzyl alcohol (BA) to benzaldehyde and benzoate on nickel–iron (Fe ~ 7–18%) electrodes as a model system to understand reaction mechanisms and environmental conditions that can transform these molecules. Our results indicate a strong correlation between benzyl alcohol oxidation (BAO) onset potentials and Ni(II/III) redox peak positions, highlighting the potential role that lower oxidation states of nickel, i.e., Ni 3+ , can play in BAO catalysis. Our work on the Ni 2+/3+ system complements mechanisms that involve higher oxidation states of Ni as reported by others. We note that the Ni redox position and thus BAO onset is impacted by Fe incorporation during electrochemistry from unpurified electrolytes, which can resemble standard reactor operating conditions. We perform a systematic computational investigation into BAO and provide density functional theory (DFT) insights into how the redox mechanism has been such a prominent focus of alcohol oxidations. This includes the mode of BA adsorption and the nature of the adsorption site; upon conversion of the Ni 2+ surface to active Ni 3+ via hydroxyl deprotonation, BAO is thermodynamically downhill. Our DFT study also introduces the possibility of a vacancy-driven mechanism, though expected to be less prevalent during catalysis than the redox mechanism for a Ni 3+ surface. Through the systematic investigation of experimental reaction conditions and computational free energy thermodynamics, we have gained valuable insights into BAO reaction mechanisms that inform catalytic activity. Our study opens avenues for further design and development of catalyst active sites for the oxidation of related organic molecules.
NELL2-Robo3 complex structure reveals mechanisms of receptor activation for axon guidance
Axon pathfinding is critical for nervous system development, and it is orchestrated by molecular cues that activate receptors on the axonal growth cone. Robo family receptors bind Slit guidance cues to mediate axon repulsion. In mammals, the divergent family member Robo3 does not bind Slits, but instead signals axon repulsion from its own ligand, NELL2. Conversely, canonical Robos do not mediate NELL2 signaling. Here, we present the structures of NELL-Robo3 complexes, identifying a mode of ligand engagement for Robos that is orthogonal to Slit binding. We elucidate the structural basis for differential binding between NELL and Robo family members and show that NELL2 repulsive activity is a function of its Robo3 affinity and is enhanced by ligand trimerization. Our results reveal a mechanism of oligomerization-induced Robo activation for axon guidance and shed light on Robo family member ligand binding specificity, conformational variability, divergent modes of signaling, and evolution.
Polyhydroxybutyrate laminated trilayer films with enhanced barrier and mechanical properties for active food packaging
Polysaccharides such as starch and chitosan have been explored for sustainable food packaging films. However, their inherent hydrophilicity and brittleness cause poor water vapor barrier performance and limited mechanical properties. To address these issues, starch was first functionalized with acetoacetate groups and subsequently blended with chitosan. Dynamic cross-linking occurred between the acetoacetate groups and the primary amine groups of chitosan, forming vinylogous urethane linkages that reduced the water solubility of the films while preserving high mechanical strength. With 30 wt% of glycerol as a plasticizer, the resulting films showed a tensile strength of up to 24.68 MPa and an elongation at break of up to 83.96%. To improve the barrier properties, poly(3-hydroxybutyrate) (PHB), plasticized with 5-15 wt% epoxidized vegetable oil, was laminated on top of the chitosan/modified starch films, resulting in a significantly reduced water vapor transmission rate (WVTR) of 66%. Additional components, such as food colors like β-carotene were incorporated into this layer to make UV-protective films. A third layer of PHB without active additives was then coated to further reduce WVTR by 99%. Therefore, this multilayer lamination strategy effectively enhanced the barrier and mechanical properties of the polysaccharide-based packaging films.
Properties and reaction mechanism of phosphoric acid activated metakaolin geopolymer at varied curing temperatures
Reaction mechanism of phosphoric activated metakaolin is studied by techniques of calorimetry, ICP-OES, FTIR and NMR taking curing temperature and [H{sub 3}PO{sub 4}] as variables. A two-stage curing method including pre-curing at 40 °C for 24 h and second curing at 60/80 °C for another 24 h effectively mitigates thermal-cracking of the obtained silico-aluminate phosphate (SAP) samples, whose maximum compressive strength reaches 120 MPa. Dealumination of metakaolin in H{sub 3}PO{sub 4} solution produces low aluminate-containing silicate units and subsequently condensation of silicate tetrahedrons occurs. Higher temperature and H{sub 3}PO{sub 4} concentration accelerate the two processes. After complete reaction, A{sub VI} structure from metakaolin disappears and the dissolved Al preferably forms Al{sub VI}-O-P units. During reaction, metastable P-O-P intermediate appears in SAPs with higher P/Al ratio and finally transforms into Al-O-P structure upon PO{sub 4}{sup 3−} consumption. Phosphate units as P(OAl){sub x}(H{sub 2}O){sub 4-x} are connected with Si or Al structure units. Major structural units of the SAPs include Al-O-P, Si-O-P, Si-O-Si, and Si-O-Al.
Decoupling the catalytic and degradation mechanisms of cobalt active sites during acidic water oxidation
Advancement of iridium-free catalysts for the low-pH oxygen evolution reaction (OER) is required to enable multi-gigawatt-scale proton-exchange water electrolysis. Cobalt-based materials might address this requirement, but little is known about the mechanism of operation of these OER catalysts at low pH. Here we investigate the nature and evolution of the active cobalt sites along with charge- and mass-transfer processes that support their catalytic function within a cobalt–iron–lead oxide material using in situ spectroscopic, gravimetric and electrochemical techniques. We demonstrate that corrosion of the cobalt sites and their reformation through electrooxidation of dissolved Co 2+ do not affect the catalytic mechanism and are decoupled from the OER. The OER-coupled charge transfer is supported by Co (3+δ)+ -oxo-species, which are structurally different from those reported for alkaline/near-neutral conditions and are formed on a relatively slow timescale of minutes. These mechanistic insights might assist in developing genuinely practical catalysts for this vital technology.
Structural insights into the mechanism of oxidative activation of heme-free H-NOX from Vibrio cholerae
Bacterial heme nitric oxide/oxygen (H-NOX) domains are nitric oxide (NO) or oxygen sensors. This activity is mediated through binding of the ligand to a heme cofactor. However, H-NOX from Vibrio cholerae (Vc H-NOX) can be easily purified in a heme-free state that is capable of reversibly responding to oxidation, suggesting a heme-independent function as a redox sensor. This occurs by oxidation of Cys residues at a zinc-binding site conserved in a subset of H-NOX homologs. Remarkably, zinc is not lost from the protein upon oxidation, although its ligation environment is significantly altered. Using a combination of computational and experimental approaches, we have characterized localized structural changes that accompany the formation of specific disulfide bonds between Cys residues upon oxidation. Furthermore, the larger-scale structural changes accompanying oxidation appear to mimic those changes observed upon NO binding to the heme-bound form. Thus, Vc H-NOX and its homologs may act as both redox and NO sensors by completely separate mechanisms.
Identification of crystal plasticity model parameters by multi-objective optimization integrating microstructural evolution and mechanical data
Crystal plasticity models evolve a polycrystalline yield surface using meso-scale descriptions of deformation mechanisms. The activation of deformation mechanisms is governed by crystallography and a set of model parameters, which are typically calibrated through the fitting of mechanical data such as stress–strain curves and elastic lattice strains. Microstructural data such as phase fractions and texture evolution are used for verifying crystal plasticity parameters. In this study, we use a multi-objective genetic algorithm to identify hardening parameters from flow stress curves with an option to incorporate texture into the optimization approach. Robust, generalized objective functions are developed and used to identify sets of parameters pertaining to dislocation density-based hardening laws in visco-plastic and elasto-plastic self-consistent (VPSC and EPSC) homogenization models. First, the parameters are identified for pure Nb directly from texture using an objective function based on generalized spherical harmonics. Since texture evolution is driven by the relative contribution of active slip systems, the parameters governing the evolution of slip resistance ratios can be recovered from fitting discrete textures at a series of strains. Next, a comprehensive set of load reversal data for dual phase (DP) 780 steel is used to fit a hardening law and a back-stress law in EPSC. Finally, parameters pertaining to a complex hardening law for the evolution of slip and twinning in pure α-Ti are identified. Remarkably, using texture as an objective in combination with stress–strain objectives constrains the model of Ti to fully reproduce not only stress–strain and texture evolution but also hierarchical twinning measurements as a function of initial grain size and texture. Furthermore, given an appropriate model fit to representative experimental texture evolution, underlying twin volume fractions contributing to texture evolution can be predicted.
Exploiting activation and inactivation mechanisms in type I-C CRISPR-Cas3 for genome-editing applications
Not provided.
Mechanism for the activation of the anaplastic lymphoma kinase receptor
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Structural mechanism of allosteric activation of TRPML1 by PI(3,5)P 2 and rapamycin
Transient receptor potential mucolipin 1 (TRPML1) is a Ca 2+ -permeable, nonselective cation channel ubiquitously expressed in the endolysosomes of mammalian cells and its loss-of-function mutations are the direct cause of type IV mucolipidosis (MLIV), an autosomal recessive lysosomal storage disease. TRPML1 is a ligand-gated channel that can be activated by phosphatidylinositol 3,5-bisphosphate [PI(3,5)P 2 ] as well as some synthetic small-molecule agonists. Recently, rapamycin has also been shown to directly bind and activate TRPML1. Interestingly, both PI(3,5)P 2 and rapamycin have low efficacy in channel activation individually but together they work cooperatively and activate the channel with high potency. To reveal the structural basis underlying the synergistic activation of TRPML1 by PI(3,5)P 2 and rapamycin, we determined the high-resolution cryoelectron microscopy (cryo-EM) structures of the mouse TRPML1 channel in various states, including apo closed, PI(3,5)P 2 -bound closed, and PI(3,5)P 2 /temsirolimus (a rapamycin analog)-bound open states. These structures, combined with electrophysiology, elucidate the molecular details of ligand binding and provide structural insight into how the TRPML1 channel integrates two distantly bound ligand stimuli and facilitates channel opening.
Structure of the phosphoinositide 3-kinase (PI3K) p110γ-p101 complex reveals molecular mechanism of GPCR activation
The class IB phosphoinositide 3-kinase (PI3K), PI3Kγ, is a master regulator of immune cell function and a promising drug target for both cancer and inflammatory diseases. Critical to PI3Kγ function is the association of the p110γ catalytic subunit to either a p101 or p84 regulatory subunit, which mediates activation by G protein–coupled receptors. Here, we report the cryo–electron microscopy structure of a heterodimeric PI3Kγ complex, p110γ-p101. This structure reveals a unique assembly of catalytic and regulatory subunits that is distinct from other class I PI3K complexes. p101 mediates activation through its Gβγ-binding domain, recruiting the heterodimer to the membrane and allowing for engagement of a secondary Gβγ-binding site in p110γ. Mutations at the p110γ-p101 and p110γ–adaptor binding domain interfaces enhanced Gβγ activation. A nanobody that specifically binds to the p101-Gβγ interface blocks activation, providing a novel tool to study and target p110γ-p101–specific signaling events in vivo.
New Insights on Plasmin Long Term Stability and the Mechanism of Its Activity Inhibition Analyzed by Quartz Crystal Microbalance
We used the research quartz crystal microbalance (RQCM) to monitor regulatory effects of plasmin and trypsin in the presence of their inhibitor α2-antiplasmin. The gold surface of quartz crystals was modified with a β-casein layer that served as a substrate for protease digestion. The addition of plasmin or trypsin as well as their mixtures with α2-antiplasmin resulted in an increase of resonant frequency, f, and in a decrease of motional resistance, Rm, depending on the molar ratio of protease: antiplasmin. At equimolar concentrations of protease and α2-antiplasmin (5 nM:5 nM) full inhibition of protease activity took place. Monitoring of plasmin activity on an hourly and daily basis revealed a prominent effect of autolysis and decrease of plasmin activity in freshly activated samples. The degree of inhibition as well as plasmin half-life (t1/2 = 2.48 ± 0.28 days) connected with its degradation was determined.
DNA sequence-dependent activity and base flipping mechanisms of DNMT1 regulate genome-wide DNA methylation
DNA methylation maintenance by DNMT1 is an essential process in mammals but molecular mechanisms connecting DNA methylation patterns and enzyme activity remain elusive. Here, we systematically analyzed the specificity of DNMT1, revealing a pronounced influence of the DNA sequences flanking the target CpG site on DNMT1 activity. We determined DNMT1 structures in complex with preferred DNA substrates revealing that DNMT1 employs flanking sequence-dependent base flipping mechanisms, with large structural rearrangements of the DNA correlating with low catalytic activity. Moreover, flanking sequences influence the conformational dynamics of the active site and cofactor binding pocket. Importantly, we show that the flanking sequence preferences of DNMT1 highly correlate with genomic methylation in human and mouse cells, and 5-azacytidine triggered DNA demethylation is more pronounced at CpG sites with flanks disfavored by DNMT1. Overall, our findings uncover the intricate interplay between CpG-flanking sequence, DNMT1-mediated base flipping and the dynamic landscape of DNA methylation.
Deciphering enhancer sequence using thermodynamics-based models and convolutional neural networks
Abstract Deciphering the sequence-function relationship encoded in enhancers holds the key to interpreting non-coding variants and understanding mechanisms of transcriptomic variation. Several quantitative models exist for predicting enhancer function and underlying mechanisms; however, there has been no systematic comparison of these models characterizing their relative strengths and shortcomings. Here, we interrogated a rich data set of neuroectodermal enhancers in Drosophila, representing cis- and trans- sources of expression variation, with a suite of biophysical and machine learning models. We performed rigorous comparisons of thermodynamics-based models implementing different mechanisms of activation, repression and cooperativity. Moreover, we developed a convolutional neural network (CNN) model, called CoNSEPT, that learns enhancer ‘grammar’ in an unbiased manner. CoNSEPT is the first general-purpose CNN tool for predicting enhancer function in varying conditions, such as different cell types and experimental conditions, and we show that such complex models can suggest interpretable mechanisms. We found model-based evidence for mechanisms previously established for the studied system, including cooperative activation and short-range repression. The data also favored one hypothesized activation mechanism over another and suggested an intriguing role for a direct, distance-independent repression mechanism. Our modeling shows that while fundamentally different models can yield similar fits to data, they vary in their utility for mechanistic inference. CoNSEPT is freely available at: https://github.com/PayamDiba/CoNSEPT.
PayamDiba/CoNSEPT
Deciphering the sequence-function relationship encoded in enhancers holds the key to interpreting non-coding variants and understanding mechanisms of transcriptomic variation. Several quantitative models exist for predicting enhancer function and underlying mechanisms; however, there has been no systematic comparison of these models characterizing their relative strengths and shortcomings. Here, we interrogated a rich data set of neuroectodermal enhancers in Drosophila, representing cis- and trans- sources of expression variation, with a suite of biophysical and machine learning models. We performed rigorous comparisons of thermodynamics-based models implementing different mechanisms of activation, repression and cooperativity. Moreover, we developed a convolutional neural network (CNN) model, called CoNSEPT, that learns enhancer ‘grammar’ in an unbiased manner. CoNSEPT is the first general-purpose CNN tool for predicting enhancer function in varying conditions, such as different cell types and experimental conditions, and we show that such complex models can suggest interpretable mechanisms. We found model-based evidence for mechanisms previously established for the studied system, including cooperative activation and short-range repression. The data also favored one hypothesized activation mechanism over another and suggested an intriguing role for a direct, distance-independent repression mechanism. Our modeling shows that while fundamentally different models can yield similar fits to data, they vary in their utility for mechanistic inference.