Involvement of autophagy in mesaconitine-induced neurotoxicity in HT22 cells revealed through integrated transcriptomic, proteomic, and m6A epitranscriptomic profiling.

Background: Mesaconitine (MA), a diester-diterpenoid alkaloid extracted from the medicinal herb Aconitum carmichaelii, is commonly used to treat various diseases. Previous studies have indicated the potent toxicity of aconitum despite its pharmacological activities, with limited understanding of its effects on the nervous system and the underlying mechanisms. Methods: HT22 cells and zebrafish were used to investigate the neurotoxic effects of MA both in vitro and in vivo, employing multi-omics techniques to explore the potential mechanisms of toxicity. Results: Our results demonstrated that treatment with MA induces neurotoxicity in zebrafish and HT22 cells. Subsequent analysis revealed that MA induced oxidative stress, as well as structural and functional damage to mitochondria in HT22 cells, accompanied by an upregulation of mRNA and protein expression related to autophagic and lysosomal pathways. Furthermore, methylated RNA immunoprecipitation sequencing (MeRIP-seq) showed a correlation between the expression of autophagy-related genes and N6-methyladenosine (m6A) modification following MA treatment. In addition, we identified METTL14 as a potential regulator of m6A methylation in HT22 cells after exposure to MA. Conclusion: Our study has contributed to a thorough mechanistic elucidation of the neurotoxic effects caused by MA, and has provided valuable insights for optimizing the rational utilization of traditional Chinese medicine formulations containing aconitum in clinical practice.

Gelsenicine disrupted the intestinal barrier of Caenorhabditis elegans.

Gelsemium elegans Benth. (G. elegans) is a traditional medicinal herb that has anti-inflammatory, analgesic, sedative, and detumescence effects. However, it can also cause intestinal side effects such as abdominal pain and diarrhea. The toxicological mechanisms of gelsenicine are still unclear. The objective of this study was to assess enterotoxicity induced by gelsenicine in the nematodes Caenorhabditis elegans (C. elegans). The nematodes were treated with gelsenicine, and subsequently their growth, development, and locomotion behavior were evaluated. The targets of gelsenicine were predicted using PharmMapper. mRNA-seq was performed to verify the predicted targets. Intestinal permeability, ROS generation, and lipofuscin accumulation were measured. Additionally, the fluorescence intensities of GFP-labeled proteins involved in oxidative stress and unfolded protein response in endoplasmic reticulum (UPRER) were quantified. As a result, the treatment of gelsenicine resulted in the inhibition of nematode lifespan, as well as reductions in body length, width, and locomotion behavior. A total of 221 targets were predicted by PharmMapper, and 731 differentially expressed genes were screened out by mRNA-seq. GO and KEGG enrichment analysis revealed involvement in redox process and transmembrane transport. The permeability assay showed leakage of blue dye from the intestinal lumen into the body cavity. Abnormal mRNAs expression of gem-4, hmp-1, fil-2, and pho-1, which regulated intestinal development, absorption and catabolism, transmembrane transport, and apical junctions, was observed. Intestinal lipofuscin and ROS were increased, while sod-2 and isp-1 expressions were decreased. Multiple proteins in SKN-1/DAF-16 pathway were found to bind stably with gelsenicine in a predictive model. There was an up-regulation in the expression of SKN-1:GFP, while the nuclear translocation of DAF-16:GFP exhibited abnormality. The UPRER biomarker HSP-4:GFP was down-regulated. In conclusion, the treatment of gelsenicine resulted in the increase of nematode intestinal permeability. The toxicological mechanisms underlying this effect involved the disruption of intestinal barrier integrity, an imbalance between oxidative and antioxidant processes mediated by the SKN-1/DAF-16 pathway, and abnormal unfolded protein reaction.

Phase Transition between Crystalline Variants of Ordinary Ice.

Water is one of the most abundant molecules on Earth. However, this common and "simple" material has more than 18 different phases, which poses a great challenge to theoretically study the nature of water and ice. We designed two reaction coordinates that can distinguish between water and various ice states and used them to efficiently sample all possible states of the system in all-atom molecular dynamics simulation at ambient temperature and pressure. Various structural and thermodynamics properties, including the water-ice phase diagrams, can thus be calculated. We also present a simple model that successfully explains the thermodynamic stability of different ice states. Our work provides effective methods and data for theoretical studies of different phases of water and ice.

Strain Rate-Dependent Hyperbolic Constitutive Model for Tensile Behavior of PE100 Pipe Material.

It is not conservative to directly use the strength tested under the laboratory loading rates to evaluate the long-term creep strength of polymers. A suitable strain rate-dependent constitutive model is crucial for accurately predicting the long-term strength and mechanical behavior of polymer pressure pipes. In this study, the Kondner hyperbolic constitutive model is considered the base model in deriving the rate-dependent constitutive model for PE100 pipe material, and the yield stress and initial tangent modulus are the two rate-dependent parameters of the model. Uniaxial tension tests are carried out under five specified strain rates ranging from 10-5 s-1 to 5 × 10-2 s-1 to obtain these two parameters. It is demonstrated that the strain rate dependence of the yield stress and the initial tangent modulus can be described by either a power or a logarithm law. The predictions from the two models are in good agreement with the experiments. In contrast, the power-law rate-dependent Kondner model is more suitable for describing the rate-dependent tensile behavior of PE100 pipe material than the logarithm-law rate-dependent Kondner model, especially for the cases of very low strain rates which relate to the polymer pressure pipe applications.

Ionic surfactants as assembly crosslinkers triggered supramolecular membrane with 2D↔3D conversion under multiple stimulus.

HYPOTHESIS: General strategies leading to 2D assemblies promise a significant step forward in the development of supramolecular materials with diversity and superiority. Considering molecular packing parameter indicates a connection between molecular geometry and aggregate morphology, we predict the introduction of ionic surfactants as assembly crosslinker would be endowed to develop a methodology of 2D supramolecular assembles. EXPERIMENTS: In this work, by introducing ionic surfactants such as sodium dodecylsulfate (SDS), the molecular packing parameter P in bolaamphiphile (A2G) system was increased, which successfully manipulated the transformation of the 3D vesicles into 2D membranes. This 2D membranes further showed excellent light and enzyme response, and thus 2D to 3D morphological conversion can be rationally controlled via UV/Vis light irradiation and alternate addition of ß-CD and α-amylase. Significantly, the 2D feature revealed not only a remarkable fluorescence enhancement to luminescent molecules but also the ability to effectively remove pollutants from water through filtration. FINDINGS: We report a general and facile strategy for the construction of 2D supramolecular membranes, initiated by introducing ionic surfactants as assembly crosslinker to increase P. In the existence of stimulus response factors, 2D↔3D morphological conversion can be further controlled in a flexible manner, which opens up a new paradigm leading to interconvertible supramolecular materials.

Deep reinforcement learning of transition states.

Combining reinforcement learning (RL) and molecular dynamics (MD) simulations, we propose a machine-learning approach, called RL‡, to automatically unravel chemical reaction mechanisms. In RL‡, locating the transition state of a chemical reaction is formulated as a game, and two functions are optimized, one for value estimation and the other for policy making, to iteratively improve our chance of winning this game. Both functions can be approximated by deep neural networks. By virtue of RL‡, one can directly interpret the reaction mechanism according to the value function. Meanwhile, the policy function allows efficient sampling of the transition path ensemble, which can be further used to analyze reaction dynamics and kinetics. Through multiple experiments, we show that RL‡ can be trained tabula rasa hence allowing us to reveal chemical reaction mechanisms with minimal subjective biases.

A Perspective on Deep Learning for Molecular Modeling and Simulations.

Deep learning is transforming many areas in science, and it has great potential in modeling molecular systems. However, unlike the mature deployment of deep learning in computer vision and natural language processing, its development in molecular modeling and simulations is still at an early stage, largely because the inductive biases of molecules are completely different from those of images or texts. Footed on these differences, we first reviewed the limitations of traditional deep learning models from the perspective of molecular physics and wrapped up some relevant technical advancement at the interface between molecular modeling and deep learning. We do not focus merely on the ever more complex neural network models; instead, we introduce various useful concepts and ideas brought by modern deep learning. We hope that transacting these ideas into molecular modeling will create new opportunities. For this purpose, we summarized several representative applications, ranging from supervised to unsupervised and reinforcement learning, and discussed their connections with the emerging trends in deep learning. Finally, we give an outlook for promising directions which may help address the existing issues in the current framework of deep molecular modeling.

Allostery of multidomain proteins with disordered linkers.

Intrinsically disordered regions are often involved in allosteric regulation of multidomain proteins. They can act as disordered linkers to connect and interact with domains, resulting in rather complex allosteric mechanism and novel protein behavior. Therefore, it is necessary to analyze the diverse functions of disordered linkers in order to better understand allostery and relevant regulation process. Here we summarize recent advances in understanding the function of linkers and the advantages of adopting mutlidomain architecture with disorder linkers. It was shown that linkers between domains enhance the local domain concentration and make the allosteric regulation of weakly interacting partners possible, while linkers with only one tethered end cause an entropy effect to reduce binding affinity and prevent aggregation.

Tunable High-Performance Microwave Absorption and Shielding by Three Constituent Phases Between rGO and Fe3O4@SiO2 Nanochains.

With the aim of achieving high microwave absorption and electromagnetic shielding performance, reduced graphene oxide (rGO) and Fe3O4@SiO2 nanochains are successfully combined at various mass ratios. By selecting the right mass ratio, an rGO/Fe3O4@SiO2 composite with excellent microwave absorption properties is obtained, and, due to the addition of highly conductive rGO, the desired shielding effectiveness is also achieved. The reflection loss (RL) value of the composite can reach -48.34 dB with a mass ratio of 1:1, and the effective bandwidth (<-10 dB) can cover 4.88 GHz at a thickness of 2.0 mm. Moreover, the composite with a mass ratio of 4:1 exhibits outstanding electromagnetic shielding performance, which also broadens its fields of application. This outstanding microwave absorption and electromagnetic shielding performance indicate that the composite can potentially be employed as a multi-functional material.

Critical fracture properties of puckered and buckled arsenenes by molecular dynamics simulations.

The pioneering prediction and successful synthesis of monolayer arsenene in recent years have promoted intensive studies on this novel two-dimensional (2D) material. Strain-engineered arsenene monolayer can change its geometric structures with tuned charge distribution, which paves the way for achieving novel electronic properties. The practical applications of the strain-driven topological state in arsenene strongly depend on its critical strain value. In this work, mechanical properties such as fracture strain, fracture strength and Young's modulus of two arsenene structures, i.e. buckled arsenene (b-arsenene) and puckered arsenene (p-arsenene), are comprehensively investigated under different modulators such as system dimension, chirality, temperature, strain rate and random surface defect. A maximum fracture strain reduction of 41.7% from 0.24 to 0.14 is observed in armchair b-arsenene when the temperature increases from 100 to 500 K. The most significant impact factor on the mechanical properties of arseneneis found to be surface defects. A maximum fracture strength reduction of 85.7% is predicted in the armchair b-arsenene when the defect ratio increases from 0 to 5%. On the other hand, the strain rate has a negligible effect on the mechanical properties. Our results provide fundamental knowledge on the critical fracture properties of arsenene.

A comprehensive ensemble model for comparing the allosteric effect of ordered and disordered proteins.

Intrinsically disordered proteins/regions (IDPs/IDRs) are prevalent in allosteric regulation. It was previously thought that intrinsic disorder is favorable for maximizing the allosteric coupling. Here, we propose a comprehensive ensemble model to compare the roles of both order-order transition and disorder-order transition in allosteric effect. It is revealed that the MWC pathway (order-order transition) has a higher probability than the EAM pathway (disorder-order transition) in allostery, suggesting a complicated role of IDPs/IDRs in regulatory proteins. In addition, an analytic formula for the maximal allosteric coupling response is obtained, which shows that too stable or too unstable state is unfavorable to endow allostery, and is thus helpful for rational design of allosteric drugs.

Reversible Manipulation of Supramolecular Chirality using Host-Guest Dynamics between ß-Cyclodextrin and Alkyl Amines.

Host-guest interactions are widely employed in constructing responsive materials, although less is known to manipulate the chiral property of materials using such host-guest dynamics. With the supramolecular self-assembly based on ß-cyclodextrin (ß-CD) and alkyl amines (CH3(CH2)n-1NH2), we report that faster host-guest dynamics induces a dipole located above the cavity of ß-CD, whereas slower dynamics create in-cavity dipole. These two scenarios correspond to negative and positive chiral signals, respectively. Considering that a larger fraction of amines facilitates faster exchange between the threaded and unthreaded amines, the chiral signal for the right-handed helical ribbons can be manipulated simply by alternatively increasing the fraction of amines and ß-CD. Excitingly, enzyme responsive supramolecular chirality is obtained as a result of shifting the molar ratio by enzyme triggered hydrolysis of ß-CD. We expect that this strategy may open up an area of rationally designed chiral supramolecular materials based on host-guest chemistry.

Disordered linkers in multidomain allosteric proteins: Entropic effect to favor the open state or enhanced local concentration to favor the closed state?

There are many multidomain allosteric proteins where an allosteric signal at the allosteric domain modifies the activity of the functional domain. Intrinsically disordered regions (linkers) are widely involved in this kind of regulation process, but the essential role they play therein is not well understood. Here, we investigated the effect of linkers in stabilizing the open or the closed states of multidomain proteins using combined thermodynamic deduction and coarse-grained molecular dynamics simulations. We revealed that the influence of linker can be fully characterized by an effective local concentration [B]0 . When Kd is smaller than [B]0 , the closed state would be favored; while the open state would be preferred when Kd is larger than [B]0 . We used four protein systems with markedly different domain-domain binding affinity and structural order/disorder as model systems to understand the relationship between [B]0 and the linker length as well as its flexibility. The linker length is the main practical determinant of [B]0 . [B]0 of a flexible linker with 40-60 residues was determined to be in a narrow range of 0.2-0.6 mM, while a too short or too long length would dramatically decrease [B]0 . With the revealed [B]0 range, the introduction of a flexible linker makes the regulation of weakly interacting partners possible.

Quantum Chemical Examination of the Sequential Halogen Incorporation Scheme for the Modeling of Speciation of I/Br/Cl-Containing Trihalomethanes.

The recently developed three-step ternary halogenation model interprets the incorporation of chlorine, bromine, and iodine ions into natural organic matter (NOM) and formation of iodine-, bromine-, and chlorine-containing trihalomethanes (THMs) based on the competition of iodine, bromine, and chlorine species at each node of the halogenation sequence. This competition is accounted for using the dimensionless ratios (denoted as γ) of kinetic rates of reactions of the initial attack sites or halogenated intermediates with chlorine, bromine, and iodine ions. However, correlations between the model predictions made and mechanistic aspects of the incorporation of halogen species need to be ascertained in more detail. In this study, quantum chemistry calculations were first used to probe the formation mechanism of 10 species of Cl-/Br-/I- THMs. The HOMO energy (EHOMO) of each mono-, bi-, or trihalomethanes were calculated by B3LYP method in Gaussian 09 software. Linear correlations were found to exist between the logarithms of experimentally determined kinetic preference coefficients γ reported in prior research and, on the other hand, differences of EHOMO values between brominated/iodinated and chlorinated halomethanes. One notable exception from this trend was that observed for the incorporation of iodine into mono- and di-iodinated intermediates. These observations confirm the three-step halogen incorporation sequence and the factor γ in the statistical model. The combined use of quantum chemistry calculations and the ternary sequential halogenation model provides a new insight into the microscopic nature of NOM-halogen interactions and the trends seen in the behavior of γ factors incorporated in the THM speciation models.

Conservation of Potentially Druggable Cavities in Intrinsically Disordered Proteins.

Intrinsically disordered proteins (IDPs) exist in highly dynamic conformational ensembles, which pose a major obstacle for drug development targeting IDPs because traditional rational drug design relies on unique three-dimensional structures. Here, we analyzed the conservation (especially structural conservation) of potentially druggable cavities in 22 ensembles of IDPs. It was found that there is considerable conservation for potentially druggable cavities within each ensemble. The average common atom percentage of potentially druggable cavities is as high as 54%. The average root-mean-squared deviation of common atoms ranges between 1 and 8 Å for multichain IDPs, and a common pocket is kept after direct alignment of cavities. In addition, the conservation of potentially druggable cavities varies among different proteins. In the comparison of multi- and single-chain IDPs, some multichain IDPs have an extremely high conservation, whereas another multichain IDPs' conservation appears worse, and the single-chain IDPs have relatively moderate conservations. This study is a new attempt to generally assess the potentially druggable cavities in IDPs for taking IDPs as druggable targets, and this work also lends support to the opinion of IDPs tending to bind to "multiconformational affinity" compounds.

Carboxylate-Selective Chemical Cross-Linkers for Mass Spectrometric Analysis of Protein Structures.

Chemical cross-linking coupled with mass spectrometry (CXMS) facilitates structural analysis of proteins. As current CXMS applications are almost exclusively limited to lysine residues, they can only retrieve a small portion of the structural information theoretically accessible to CXMS. Chemical cross-linkers targeting the acidic residues Asp/Glu could greatly enhance the power of CXMS. However, it has been difficult to develop chemistries that offer selectivity and efficiency under physiological conditions. Here, we report a class of carboxylate-selective diazo-containing cross-linkers (Diazoker) of which Diazoker 1, with a spacer arm consisting of two ethan-1,2-diol units, is the best example. Unlike previously developed carboxylate-selective cross-linkers like pimelic acid dihydrazide (PDH), Diazoker 1 does not require a coupling reagent. We tested Diazoker 1 on nine model proteins and found that Diazoker 1 generated an average of 73 cross-linked peptide pairs per protein. Although this is 32% fewer than the number generated by PDH, the Diazoker 1 cross-links have a higher rate of compatibility with protein crystal structures. From a more complex protein mixture, Diazoker 1 and PDH identified 75 and 76 cross-linked peptide pairs, respectively. The Asp/Glu residues cross-linked by Diazoker 1 are not the same as those cross-linked by PDH. Diazoker 1 favors acidic residues that are less exposed to solvent. In conclusion, Diazoker 1 is complementary to existing cross-linkers and expands the toolkit of CXMS for structural analysis of proteins.

Dimension conversion and scaling of disordered protein chains.

To extract protein dimension and energetics information from single-molecule fluorescence resonance energy transfer spectroscopy (smFRET) data, it is essential to establish the relationship between the distributions of the radius of gyration (Rg) and the end-to-end (donor-to-acceptor) distance (Ree). Here, we performed a coarse-grained molecular dynamics simulation to obtain a conformational ensemble of denatured proteins and intrinsically disordered proteins. For any disordered chain with fixed length, there is an excellent linear correlation between the average values of Rg and Ree under various solvent conditions, but the relationship deviates from the prediction of a Gaussian chain. A modified conversion formula was proposed to analyze smFRET data. The formula reduces the discrepancy between the results obtained from FRET and small-angle X-ray scattering (SAXS). The scaling law in a coil-globule transition process was examined where a significant finite-size effect was revealed, i.e., the scaling exponent may exceed the theoretical critical boundary [1/3, 3/5] and the prefactor changes notably during the transition. The Sanchez chain model was also tested and it was shown that the mean-field approximation works well for expanded chains.

Dimensions, energetics, and denaturant effects of the protein unstructured state.

Determining the energetics of the unfolded state of a protein is essential for understanding the folding mechanics of ordered proteins and the structure-function relation of intrinsically disordered proteins. Here, we adopt a coil-globule transition theory to develop a general scheme to extract interaction and free energy information from single-molecule fluorescence resonance energy transfer spectroscopy. By combining protein stability data, we have determined the free energy difference between the native state and the maximally collapsed denatured state in a number of systems, providing insight on the specific/nonspecific interactions in protein folding. Both the transfer and binding models of the denaturant effects are demonstrated to account for the revealed linear dependence of inter-residue interactions on the denaturant concentration, and are thus compatible under the coil-globule transition theory to further determine the dimension and free energy of the conformational ensemble of the unfolded state. The scaling behaviors and the effective θ-state are also discussed.

Application of 1-hydroxyethylidene-1, 1-diphosphonic acid in boiler water for industrial boilers.

The primary method used for boiler water treatment is the addition of chemicals to industrial boilers to prevent corrosion and scaling. The static scale inhibition method was used to evaluate the scale inhibition performance of 1-hydroxyethylidene-1, 1-diphosphonic acid (HEDP). Autoclave static experiments were used to study the corrosion inhibition properties of the main material for industrial boilers (20# carbon steel) with an HEDP additive in the industrial boiler water medium. The electrochemical behavior of HEDP on carbon steel corrosion control was investigated using electrochemical impedance spectroscopy and Tafel polarization techniques. Experimental results indicate that HEDP can have a good scale inhibition effect when added at a quantity of 5 to 7 mg/L at a test temperature of not more than 100 °C. To achieve a high scale inhibition rate, the HEDP dosage must be increased when the test temperature exceeds 100 °C. Electrochemical and autoclave static experimental results suggest that HEDP has a good corrosion inhibition effect on 20# carbon steel at a concentration of 25 mg/L. HEDP is an excellent water treatment agent.