Lipid-mediated phase separation of AGO proteins on the ER controls nascent-peptide ubiquitination.

AGO/miRNA-mediated gene silencing and ubiquitin-mediated protein quality control represent two fundamental mechanisms that control proper gene expression. Here, we unexpectedly discover that fly and human AGO proteins, which are key components in the miRNA pathway, undergo lipid-mediated phase separation and condense into RNP granules on the endoplasmic reticulum (ER) membrane to control protein production. Phase separation on the ER is mediated by electrostatic interactions between a conserved lipid-binding motif within the AGOs and the lipid PI(4,5)P2. The ER-localized AGO condensates recruit the E3 ubiquitin ligase Ltn1 to catalyze nascent-peptide ubiquitination and coordinate with the VCP-Ufd1-Npl4 complex to process unwanted protein products for proteasomal degradation. Collectively, our study provides insight into the understanding of post-transcription-translation coupling controlled by AGOs via lipid-mediated phase separation.

Targeting protein condensation in cGAS-STING signaling pathway.

The cGAS-STING signaling pathway plays a pivotal role in sensing cytosolic DNA and initiating innate immune responses against various threats, with disruptions in this pathway being associated with numerous immune-related disorders. Therefore, precise regulation of the cGAS-STING signaling is crucial to ensure appropriate immune responses. Recent research, including ours, underscores the importance of protein condensation in driving the activation and maintenance of innate immune signaling within the cGAS-STING pathway. Consequently, targeting condensation processes in this pathway presents a promising approach for modulating the cGAS-STING signaling and potentially managing associated disorders. In this review, we provide an overview of recent studies elucidating the role and regulatory mechanism of protein condensation in the cGAS-STING signaling pathway while emphasizing its pathological implications. Additionally, we explore the potential of understanding and manipulating condensation dynamics to develop novel strategies for mitigating cGAS-STING-related disorders in the future.

Some Recent Advances in Density-Based Reactivity Theory.

Establishing a chemical reactivity theory in density functional theory (DFT) language has been our intense research interest in the past two decades, exemplified by the determination of steric effect and stereoselectivity, evaluation of electrophilicity and nucleophilicity, identification of strong and weak interactions, and formulation of cooperativity, frustration, and principle of chirality hierarchy. In this Featured Article, we first overview the four density-based frameworks in DFT to appreciate chemical understanding, including conceptual DFT, use of density associated quantities, information-theoretic approach, and orbital-free DFT, and then present a few recent advances of these frameworks as well as new applications from our studies. To that end, we will introduce the relationship among these frameworks, determining the entire spectrum of interactions with Pauli energy derivatives, performing topological analyses with information-theoretic quantities, and extending the density-based frameworks to excited states. Applications to examine physiochemical properties in external electric fields and to evaluate polarizability for proteins and crystals are discussed. A few possible directions for future development are followed, with the special emphasis on its merger with machine learning.

Chiral Jahn-Teller Distortion in Quasi-Planar Boron Clusters.

In this work, we have observed that some chiral boron clusters (B16-, B20-, B24-, and B28-) can simultaneously have helical molecular orbitals and helical spin densities; these seem to be the first compounds discovered to have this intriguing property. We show that chiral Jahn-Teller distortion of quasi-planar boron clusters drives the formation of the helical molecular spin densities in these clusters and show that elongation/enhancement in helical molecular orbitals can be achieved by simply adding more building blocks via a linker. Aromaticity of these boron clusters is discussed. Chiral boron clusters may find potential applications in spintronics, such as molecular magnets.

Efficient and accurate density-based prediction of macromolecular polarizabilities.

Accurately and efficiently predicting macromolecules' polarizabilities is an open problem. In this work, we employ a few simple density-based quantities from the information-theoretic approach (ITA) to predict polarizability of proteins. We first build quantitative structure/property relationships between molecular polarizabilities and ITA quantities. We then verify the broad applicability of ITA quantities for polarizability prediction for inorganic, organic, and biological systems with both localized and delocalized electronic structure. As a proof-of-concept application, we predict the molecular polarizabilities of complex proteins. Based on the linear regression equations for 20 natural amino acid residues, 400 dipeptides, and 8000 tripeptides, one then predicts the molecular polarizability of a larger peptide or even a protein once the molecular wavefunction is obtained. Because it is extremely costly to determine the wavefunction for a macromolecule like a protein, we propose to combine the ITA with the linear-scaling generalized energy-based fragmentation (GEBF) method to predict the macromolecular polarizability. In GEBF, the total molecular polarizability is obtained as a linear combination of the corresponding quantities from a series of small subsystems. We can predict them based on the subsystem wavefunction and linear regression equations rather than compute them from the nearly-intractable coupled-perturbed Hartree-Fock or Kohn-Sham equations for the whole macromolecule. Computational results showcase that the GEBF-ITA protocol should be an inexpensive yet accurate theoretical tool for predicting macromolecular polarizabilities.

Directionality and additivity effects of molecular acidity and aromaticity for substituted benzoic acids under external electric fields.

Our recent study [M. Li et al.Phys. Chem. Chem. Phys., 2023, 25, 2595-2605] unveiled that the impact of an external electric field on molecular acidity and aromaticity for benzoic acid is directional, which can be understood using changes in frontier orbitals and partial charges. However, it is unclear if the effect will disappear when substituting groups are present and whether new patterns of changes will show up. In this work, as a continuation of our efforts to appreciate the impact of external electric fields on physiochemical properties, we find that the directionality effect is still in place for substituted benzoic acid derivatives and that there exists the additivity effect with respect to the number of substituent groups, regardless of the direction of the applied field and the type of substituting groups. We confirm the findings using electron-donating and electron-accepting groups with the electric field applied either parallelly or perpendicularly to the carboxyl group along the benzene ring. The directionality and additivity effects uncovered from this work should enrich the body of our knowledge about the impact of external electric fields on physiochemical properties and could be applicable to other systems and properties as well.

Simultaneous identification of strong and weak interactions with Pauli energy, Pauli potential, Pauli force, and Pauli charge.

Strong and weak interatomic interactions in chemical and biological systems are ubiquitous, yet how to identify them on a unified theoretical foundation is still not well established. Recently, we proposed employing Pauli energy-based indexes, such as strong covalent interaction and bonding and noncovalent interaction indexes, in the framework of density functional theory for the purpose. In this work, we extend our previous theoretical work by directly employing Pauli energy, Pauli potential, Pauli force, and Pauli charge to simultaneously identify both strong covalent bonding and weak noncovalent interactions. Our results from this work elucidate that using their signature isosurfaces, we can identify different types of interactions, either strong or weak, including single, double, triple, and quadruple covalent bonds, ionic bond, metallic bond, hydrogen bonding, and van der Waals interaction. We also discovered strong linear correlations between Pauli energy derived quantities and different covalent bond orders. These qualitative and quantitative results from our present study solidify the viewpoint that a unified approach to simultaneously identify both strong and weak interactions is possible. In our view, this work signifies one step forward towards the goal of establishing a density-based theory of chemical reactivity in density functional theory.

EVLncRNAs 2.0: an updated database of manually curated functional long non-coding RNAs validated by low-throughput experiments.

Long non-coding RNAs (lncRNAs) play important functional roles in many diverse biological processes. However, not all expressed lncRNAs are functional. Thus, it is necessary to manually collect all experimentally validated functional lncRNAs (EVlncRNA) with their sequences, structures, and functions annotated in a central database. The first release of such a database (EVLncRNAs) was made using the literature prior to 1 May 2016. Since then (till 15 May 2020), 19 245 articles related to lncRNAs have been published. In EVLncRNAs 2.0, these articles were manually examined for a major expansion of the data collected. Specifically, the number of annotated EVlncRNAs, associated diseases, lncRNA-disease associations, and interaction records were increased by 260%, 320%, 484% and 537%, respectively. Moreover, the database has added several new categories: 8 lncRNA structures, 33 exosomal lncRNAs, 188 circular RNAs, and 1079 drug-resistant, chemoresistant, and stress-resistant lncRNAs. All records have checked against known retraction and fake articles. This release also comes with a highly interactive visual interaction network that facilitates users to track the underlying relations among lncRNAs, miRNAs, proteins, genes and other functional elements. Furthermore, it provides links to four new bioinformatics tools with improved data browsing and searching functionality. EVLncRNAs 2.0 is freely available at https://www.sdklab-biophysics-dzu.net/EVLncRNAs2/.

Excited-State Polarizabilities: A Combined Density Functional Theory and Information-Theoretic Approach Study.

Accurate and efficient determination of excited-state polarizabilities (α) is an open problem both experimentally and computationally. Following our previous work, (Phys. Chem. Chem. Phys. 2023, 25, 2131-2141), in which we employed simple ground-state (S0) density-related functions from the information-theoretic approach (ITA) to accurately and efficiently evaluate the macromolecular polarizabilities, in this work we aimed to predict the lowest excited-state (S1) polarizabilities. The philosophy is to use density-based functions to depict excited-state polarizabilities. As a proof-of-principle application, employing 2-(2'-hydroxyphenyl)benzimidazole (HBI), its substituents, and some other commonly used ESIPT (excited-state intramolecular proton transfer) fluorophores as model systems, we verified that either with S0 or S1 densities as an input, ITA quantities can be strongly correlated with the excited-state polarizabilities. When transition densities are considered, both S0 and S1 polarizabilities are in good relationships with some ITA quantities. The transferability of the linear regression model is further verified for a series of molecules with little or no similarity to those molecules in the training set. Furthermore, the excitation energies can be predicted based on multivariant linear regression equations of ITA quantities. This study also found that the nature of both the ground-state and excited-state polarizabilities of these species are due to the spatial delocalization of the electron density.

Bone marrow-derived mesenchymal stem cells ameliorate severe acute pancreatitis by inhibiting oxidative stress in rats.

To investigate whether bone marrow mesenchymal stem cells (BMSCs) attenuate pancreatic injury via mediating oxidative stress in severe acute pancreatitis (SAP). The SAP model was established in rats. Phosphate buffered saline (PBS) or BMSCs were injected into the rats by tail veins. ML385 was used to down-regulate Nrf2 expression in rats. Pancreatic pathological score was used to evaluated pancreatic injury. Inflammatory-associated cytokines, serum lipase and amylase, levels of myeloperoxidase, malondialdehyde, reactive oxygen species and superoxide dismutase, as well as catalase activity were measured for injury severity evaluation. ML385 aggravates oxidative stress in SAP + ML385 group, compared with SAP + PBS group. BMSCs transplantation alleviated pancreatic injury and enhance antioxidant tolerance in SAP + BMSCs group, while ML385 administration weakened this efficacy in SAP + BMSCs + ML385 group. In addition, BMSCs promoted Nrf2 nuclear translocation via PI3K/AKT signaling pathway. Besides, BMSCs reduced inflammatory response by inhibiting NF-κB signaling pathway in SAP. BMSCs can inhibit oxidative stress and reduce pancreatic injury via inducing Nrf2 nuclear translocation in SAP.

Sputum-Based Tumor Fluid Biopsy: Isolation and High-Throughput Single-Cell Analysis of Exfoliated Tumor Cells for Lung Cancer Diagnosis.

Timely and effective diagnosis is of great significance for improving the survival rate of lung cancer patients. Although histopathology is the main diagnostic tool among the existing methods for lung cancer diagnosis, it is not suitable for high-risk groups, early lung cancer patients, patients with advanced-stage disease, and other situations wherein tumor tissues cannot be obtained. In view of this, we proposed an innovative lung cancer diagnosis method employing for the first time a microfluidic technology for high-efficiency isolation and high-throughput single-cell analysis of exfoliated tumor cells (ETCs) in sputum. This method fully combines the advantages of traditional sputum cytology and microfluidic technology and realizes the diagnosis of lung cancer by using a small amount of repeatable ETCs instead of the tumor tissue. This method is expected to provide a practical strategy for the non-invasive detection of lung cancer patients and lung cancer screening for high-risk groups.

Density functional theory studies of boron clusters with exotic properties in bonding, aromaticity and reactivity.

Atomic clusters are unique in many perspectives because of their size and structure features and are continuously being applied for different purposes. To unveil their unconventional properties, in this work, using neutral tetraboron clusters as illustrative examples, we study their exotic behaviors in bonding, aromaticity, and reactivity. We show that both double and triple bonds can be formed, ring current patterns can be totally different, and both electrophilic and nucleophilic reactivities can coexist simultaneously. These features are often in contrast with our conventional chemical wisdom and could enrich the possibility for their potential applications. The methodologies employed in this work can be readily applied to other systems. Our studies should help us better appreciate atomic clusters with many atypical properties and henceforth yield novel applications.

Quantifications and Applications of Relative Fisher Information in Density Functional Theory.

Though density functional theory is widely accepted as one of the most successful developments in theoretical chemistry in the past few decades, the knowledge of how to apply this new electronic structure theory, to help us better understand chemical processes and transformations, is still an unaccomplished task. The information-theoretic approach is emerging as a viable option for that purpose in the recent literature, providing new insights about steric effect, cooperativity, electrophilicity, nucleophilicity, stereoselectivity, homochirality, etc. In this work, based on the result from a recent paper by one of us [ J. Chem. Phys, 2019, 151, 141103], we present two quantifications of the relative Fisher information and discuss their physiochemical properties and possible applications. To that end, their analytical properties have been elucidated. They have also been applied to six categories of systems to illustrate their applicability. A better descriptor to quantify the single bond rotation barrier has been obtained. The relative Fisher information can also simultaneously determine electrophilicity and nucleophilicity, and effectively describe helical structures with different homochiral and heterochiral propensities. As integral parts of the information-theoretic approach, these newly introduced quantities will provide us with more analytical tools toward the long-term goal of crafting a chemical reactivity theory in the density-based language.

Rosiglitazone attenuates high glucose-induced proliferation, inflammation, oxidative stress and extracellular matrix accumulation in mouse mesangial cells through the Gm26917/miR-185-5p pathway.

Rosiglitazone (RSG) is widely used to reduce the amount of sugar in the blood of patients with diabetes mellitus. Diabetic nephropathy is the most common microvascular complication of diabetes. The role of RSG in diabetic nephropathy is not fully understood. Diabetic nephropathy model was constructed in high glucose (HG)-treated mouse mesangial cells. The effects of RSG on cell viability and cell cycle were investigated using cell counting kit-8 (CCK-8) assay and flow cytometry assay. Oxidative stress was assessed according to ROS production and SOD activity in cells. Inflammatory responses were assessed according to the releases of inflammatory cytokines. Extracellular matrix (ECM) accumulation was determined by the levels of fibronectin and collagen IV using western blot. The expression of Gm26917 and microRNA-185-5p (miR-185-5p) was detected by quantitative real-time polymerase chain reaction (qPCR). The interaction between Gm26917 and miR-185-5p was validated by dual-luciferase reporter assay, RNA immunoprecipitation (RIP) assay and pull-down assay. RSG significantly inhibited HG-induced proliferation, oxidative stress, inflammatory responses and ECM accumulation in mouse mesangial cells. The expression of Gm26917 was induced by HG but weakened by RSG. Gm26917 knockdown alleviated HG-induced proliferation, oxidative stress, inflammatory responses and ECM accumulation in mouse mesangial cells, and Gm26917 overexpression partly abolished the effects of RSG. Moreover, miR-185-5p was a target of Gm26917, and miR-185-5p inhibition recovered proliferation, oxidative stress, inflammatory responses and ECM accumulation in mouse mesangial cells that were alleviated by Gm26917 knockdown. RSG ameliorated HG-induced mouse mesangial cell proliferation, oxidative stress, inflammation and ECM accumulation partially by governing the Gm26917/miR-185-5p pathway.

An On-the-Fly Approach to Construct Generalized Energy-Based Fragmentation Machine Learning Force Fields of Complex Systems.

An on-the-fly fragment-based machine learning (ML) approach was developed to construct machine learning force fields for large complex systems. In this approach, the energy, forces, and molecular properties of the target system are obtained by combining machine learning force fields of various subsystems with the generalized energy-based fragmentation (GEBF) approach. Using a nonparametric Gaussian process (GP) model, all the force fields of subsystems are automatically generated online without data selection and parameter optimization. With the GEBF-ML force field constructed for a normal alkane, C60H122, long-time molecular dynamics (MD) simulations are performed on different sizes of alkanes, and the predicted energy, forces, and molecular properties (dipole moment) are favorably comparable with full quantum mechanics (QM) calculations. The predicted IR spectra also show excellent agreement with the direct ab initio MD results. Our results demonstrate that the GEBF-ML method provides an automatic and efficient way to build force fields for a broad range of complex systems such as biomolecules and supramolecular systems.

In Situ Imaging Facet-Induced Spatial Heterogeneity of Electrocatalytic Reaction Activity at the Subparticle Level via Electrochemiluminescence Microscopy.

Investigating catalytic behavior of heterogeneous catalysts, especially at the crystal facets level, is crucial for rational catalyst design in the energy and environmental fields. Here we demonstrate an efficient approach to in situ visualize and analyze the heterogeneity of electrocatalytic activity on different facets at the subparticle level via electrochemiluminescence (ECL) microscopy. ZnO crystals with various exposed facet proportions were synthesized, and the correlation between their electrocatalytic performance toward luminol analogue degradation and the exposed facets is established. It is clearly imaged that the ZnO (002) facet has superior catalytic performance compared to the ZnO (100) facet, which is supported by theoretical computation and electrochemical experiments as the facet-induced heterogeneity of the catalytic effect on oxygen reduction into the key reactant for ECL. Accordingly, the spatial heterogeneity of electrocatalytic activity at different facets on one particle is visualized for the first time. The realization of subparticle ECL imaging and kinetic analysis could provide a special approach to visualize facet-induced spatial heterogeneity of catalytic behavior and valuable information for the catalysis study and analysis.

Bone marrow-derived mesenchymal stromal cells ameliorate severe acute pancreatitis in rats via hemeoxygenase-1-mediated anti-oxidant and anti-inflammatory effects.

BACKGROUND AND AIMS: It has been previously verified that mesenchymal stromal cells (MSCs) have a good therapeutic effect on severe acute pancreatitis (SAP) and the potential for regeneration of damaged pancreatic tissue, but the exact molecular mechanism remains unclear. In this study, we demonstrated the therapeutic effect of bone morrow MSCs (BMSCs) on SAP, probably by targeting heme oxygenase-1 (HO-1). METHODS: Six hours after SAP induction, either phosphate-buffered saline (PBS) or BMSCs were transfused into the caudal vein of rats, zinc protoporphyrin (ZnPP) was administered intraperitoneally. Pancreatic pathological scoring, serum levels of amylase and inflammatory factors, as well as levels of reactive oxygen species (ROS), malondialdehyde (MDA) and myeloperoxidase (MPO), superoxide dismutase (SOD) and catalase (CAT) activity in the pancreas were evaluated. RESULTS: Our data showed that BMSCs significantly reduce inflammation and oxidative stress, reduce apoptosis and promote angiogenesis of damaged pancreas. Moreover, BMSCs increased the level of HO-1 in the serum and pancreatic tissue in rats with SAP. In addition, the protective effect of BMSCs was partially neutralized by the HO-1 activity inhibitor ZnPP, suggesting a key role of HO-1 in the therapeutic effect of BMSCs on SAP. CONCLUSIONS: BMSCs ameliorated SAP, probably by inducing expression of HO-1, which can exert anti-inflammatory and anti-oxidant effects, reduce apoptosis and promote angiogenesis.

Using Pauli energy to appraise the quality of approximate semilocal non-interacting kinetic energy density functionals.

It is well-known that the kinetic energy density (KED) functional is the most difficult to approximate in density functional theory (DFT), yet to take full advantage of DFT with its density-based descriptive capability of molecular properties, an accurate account of KED is a must. To have a better idea of how an approximate KED formula behaves and where we should focus in the future development of better approximate KEDs, in this work we propose to employ the Pauli energy to assess their quality. We tested the performance of a total of 22 approximate semilocal noninteracting KED functionals from the literature for 18 neutral atoms and 20 small molecules. We found that generalized gradient approximation formulas of the KED functional can often reasonably accurately predict the total kinetic energy value for atoms and molecules but failed miserably to forecast the integrated values for Pauli energy related properties. The reason behind this is that presently available approximate KED functionals are unable to accurately account for the kinetic energy distribution in the medium range away from nuclei, where the Pauli energy plays a crucial role. Our results strongly suggest that the key information missing in approximate KED functionals comes from the medium regions, not nuclear cusps nor asymptotic areas, and the Pauli energy is a reliable measure of the quality of approximate KED functionals. Future efforts in developing better KED approximations should be invested in the regions of molecules where chemical bonds are formed in order to accurately account for the Pauli energy.

Long Noncoding RNA (lncRNA) FOXD2-AS1 Promotes Cell Proliferation and Metastasis in Hepatocellular Carcinoma by Regulating MiR-185/AKT Axis.

BACKGROUND The aim of this study was to investigate the effects and mechanisms of long noncoding (lnc) RNA FOXD2-AS1 in hepatocellular carcinoma development. MATERIAL AND METHODS Collecting the 3 pairs of adjacent and hepatocellular carcinoma tissue and analysis by gene chip. Evaluating the FOXD2-AS1 expression by in situ hybridization assay. Evaluating the FOXD2-AS1 to Bel-7402 biological activity in vitro study by Cell Counting Kit-8, flow cytometry, Transwell and wound healing assay and correlation between miR-185 by dual-luciferase reporter assay. The relative proteins expressions were evaluated by western blot assay. RESULTS FOXD2-AS1 was significantly upregulation in hepatocellular carcinoma tissues. FOXD2-AS1 knockdown suppressed Bel-7401 cell biological activities (proliferation, invasion, and migration) with miR-185 overexpression and AKT depressing in cell expression. CONCLUSIONS LncRNA FOXD2-AS1 promoted hepatocellular carcinoma development by regulation miR-185/AKT axis.

Quantification and origin of cooperativity: insights from density functional reactivity theory.

Cooperativity is a widely used chemical concept whose existence is ubiquitous in chemical and biological systems but whose quantification is still controversial and origin much less appreciated. In this work, using the interaction energy of a molecular system, which is composed of multiple copies of a building block, we propose a quantitative measurement to evaluate the cooperativity effect. This quantification approach is then applied to six molecular systems, i.e., water cluster, argon cluster, protonated water cluster, zinc atom cluster, water cluster on top of a graphene sheet, and alpha helix of glycine amino acids, each with up to 20 copies of the building block. Cooperativity is seen in all these systems. Both positive and negative cooperativity effects are observed. Employing the two energy partition schemes in density functional theory and the information-theoretic quantities such as Shannon entropy, Fisher information, information gain, etc., we then examine the origin of the cooperativity effect for these systems. Strong linear correlations between the cooperativity measure and some of these theoretical quantities have been unveiled. With these correlations, we are able to quantitatively account for their origin of cooperativity. Our results show that the interactions governing the existence and validity of the cooperativity effect are complicated. An opposite mechanism in enthalpy-entropy compensation for positive and negative cooperativity has been unveiled. These results should provide new insights and understandings from a different viewpoint about the nature and origin of cooperativity to appreciate this vastly important chemical concept.