Fragment-based drug discovery supports drugging 'undruggable' protein-protein interactions.

Protein-protein interactions (PPIs) have important roles in various cellular processes, but are commonly described as 'undruggable' therapeutic targets due to their large, flat, featureless interfaces. Fragment-based drug discovery (FBDD) has achieved great success in modulating PPIs, with more than ten compounds in clinical trials. Here, we highlight the progress of FBDD in modulating PPIs for therapeutic development. Targeting hot spots that have essential roles in both fragment binding and PPIs provides a shortcut for the development of PPI modulators via FBDD. We highlight successful cases of cracking the 'undruggable' problems of PPIs using fragment-based approaches. We also introduce new technologies and future trends. Thus, we hope that this review will provide useful guidance for drug discovery targeting PPIs.

ACFIS 2.0: an improved web-server for fragment-based drug discovery via a dynamic screening strategy.

Drug discovery, which plays a vital role in maintaining human health, is a persistent challenge. Fragment-based drug discovery (FBDD) is one of the strategies for the discovery of novel candidate compounds. Computational tools in FBDD could help to identify potential drug leads in a cost-efficient and time-saving manner. The Auto Core Fragment in silico Screening (ACFIS) server is a well-established and effective online tool for FBDD. However, the accurate prediction of protein-fragment binding mode and affinity is still a major challenge for FBDD due to weak binding affinity. Here, we present an updated version (ACFIS 2.0), that incorporates a dynamic fragment growing strategy to consider protein flexibility. The major improvements of ACFIS 2.0 include (i) increased accuracy of hit compound identification (from 75.4% to 88.5% using the same test set), (ii) improved rationality of the protein-fragment binding mode, (iii) increased structural diversity due to expanded fragment libraries and (iv) inclusion of more comprehensive functionality for predicting molecular properties. Three successful cases of drug lead discovery using ACFIS 2.0 are described, including drugs leads to treat Parkinson's disease, cancer, and major depressive disorder. These cases demonstrate the utility of this web-based server. ACFIS 2.0 is freely available at http://chemyang.ccnu.edu.cn/ccb/server/ACFIS2/.

Exploring the kinase-inhibitor fragment interaction space facilitates the discovery of kinase inhibitor overcoming resistance by mutations.

Protein kinases play crucial roles in many cellular signaling processes, making them become important targets for drug discovery. But drug resistance mediated by mutation puts a barrier to the therapeutic effect of kinase inhibitors. Fragment-based drug discovery has been successfully applied to overcome such resistance. However, the complicate kinase-inhibitor fragment interaction and fragment-to-lead process seriously limit the efficiency of kinase inhibitor discovery against resistance caused by mutation. Here, we constructed a comprehensive web platform KinaFrag for the fragment-based kinase inhibitor discovery to overcome resistance. The kinase-inhibitor fragment space was investigated from 7783 crystal kinase-inhibitor fragment complexes, and the structural requirements of kinase subpockets were analyzed. The core fragment-based virtual screening workflow towards specific subpockets was developed to generate new kinase inhibitors. A series of tropomyosin receptor kinase (TRK) inhibitors were designed, and the most potent compound YT9 exhibits up to 70-fold activity improvement than marketed drugs larotrectinib and selitrectinib against G595R, G667C and F589L mutations of TRKA. YT9 shows promising antiproliferative against tumor cells in vitro and effectively inhibits tumor growth in vivo for wild type TRK and TRK mutants. Our results illustrate the great potential of KinaFrag in the kinase inhibitor discovery to combat resistance mediated by mutation. KinaFrag is freely available at http://chemyang.ccnu.edu.cn/ccb/database/KinaFrag/.

PTMdyna: exploring the influence of post-translation modifications on protein conformational dynamics.

Protein post-translational modifications (PTM) play vital roles in cellular regulation, modulating functions by driving changes in protein structure and dynamics. Exploring comprehensively the influence of PTM on conformational dynamics can facilitate the understanding of the related biological function and molecular mechanism. Currently, a series of excellent computation tools have been designed to analyze the time-dependent structural properties of proteins. However, the protocol aimed to explore conformational dynamics of post-translational modified protein is still a blank. To fill this gap, we present PTMdyna to visually predict the conformational dynamics differences between unmodified and modified proteins, thus indicating the influence of specific PTM. PTMdyna exhibits an AUC of 0.884 tested on 220 protein-protein complex structures. The case of heterochromatin protein 1α complexed with lysine 9-methylated histone H3, which is critical for genomic stability and cell differentiation, was used to demonstrate its applicability. PTMdyna provides a reliable platform to predict the influence of PTM on protein dynamics, making it easier to interpret PTM functionality at the structure level. The web server is freely available at http://ccbportal.com/PTMdyna.

Single-cell analysis reveals alterations in cellular composition and cell-cell communication associated with airway inflammation and remodeling in asthma.

BACKGROUND: Asthma is a heterogeneous disease characterized by airway inflammation and remodeling, whose pathogenetic complexity was associated with abnormal responses of various cell types in the lung. The specific interactions between immune and stromal cells, crucial for asthma pathogenesis, remain unclear. This study aims to determine the key cell types and their pathological mechanisms in asthma through single-cell RNA sequencing (scRNA-seq). METHODS: A 16-week mouse model of house dust mite (HDM) induced asthma (n = 3) and controls (n = 3) were profiled with scRNA-seq. The cellular composition and gene expression profiles were assessed by bioinformatic analyses, including cell enrichment analysis, trajectory analysis, and Gene Set Enrichment Analysis. Cell-cell communication analysis was employed to investigate the ligand-receptor interactions. RESULTS: The asthma model results in airway inflammation coupled with airway remodeling and hyperresponsiveness. Single-cell analysis revealed notable changes in cell compositions and heterogeneities associated with airway inflammation and remodeling. GdT17 cells were identified to be a primary cellular source of IL-17, related to inflammatory exacerbation, while a subpopulation of alveolar macrophages exhibited numerous significantly up-regulated genes involved in multiple pathways related to neutrophil activities in asthma. A distinct fibroblast subpopulation, marked by elevated expression levels of numerous contractile genes and their regulators, was observed in increased airway smooth muscle layer by immunofluorescence analysis. Asthmatic stromal-immune cell communication significantly strengthened, particularly involving GdT17 cells, and macrophages interacting with fibroblasts. CXCL12/CXCR4 signaling was remarkedly up-regulated in asthma, predominantly bridging the interaction between fibroblasts and immune cell populations. Fibroblasts and macrophages could jointly interact with various immune cell subpopulations via the CCL8/CCR2 signaling. In particular, fibroblast-macrophage cell circuits played a crucial role in the development of airway inflammation and remodeling through IL1B paracrine signaling. CONCLUSIONS: Our study established a mouse model of asthma that recapitulated key pathological features of asthma. ScRNA-seq analysis revealed the cellular landscape, highlighting key pathological cell populations associated with asthma pathogenesis. Cell-cell communication analysis identified the crucial ligand-receptor interactions contributing to airway inflammation and remodeling. Our findings emphasized the significance of cell-cell communication in bridging the possible causality between airway inflammation and remodeling, providing valuable hints for therapeutic strategies for asthma.

Lemneolemnanes A-D, Four Uncommon Sesquiterpenoids from the Soft Coral Lemnalia sp.

Four undescribed sesquiterpenoids, lemneolemnanes A-D (1-4), have been isolated from the marine soft coral Lemnalia sp. The absolute configurations of the stereogenic carbons of 1-4 were determined by single-crystal X-ray crystallographic analysis. Compounds 1 and 2 are epimers at C-3 and have an unusual skeleton with a formyl group on C-6. Compound 3 possesses an uncommonly rearranged carbon skeleton, while 4 has a 6/5/5 tricyclic system. Compound 1 showed significant anti-Alzheimer's disease (AD) activity in a humanized Caenorhabditis elegans AD pathological model.

Epimedium Linn: A Comprehensive Review of Phytochemistry, Pharmacology, Clinical Applications and Quality Control.

Epimedium genus is a traditional Chinese medicine, which has functions of tonifying kidney and yang, strengthening tendons and bones, dispelling wind and emoving dampness. It is mainly used for the treatment of impotence and spermatorrhea, osteoporosis, Parkinson's, Alzheimer's, and cardiovascular diseases. The aim of this review is to provide a systematic summary of the phytochemistry, pharmacology, and clinical applications of the Epimedium Linn. In this paper, the relevant literature on Epimedium Linn. was collected from 1987 to the present day, and more than 274 chemical constituents, including flavonoids, phenylpropanoids, lignans, phenanthrenes, and others, were isolated from this genus. Modern pharmacological studies have shown that Epimedium Linn. has osteoprotective, neuroprotective, cardiovascular protective, and immune enhancing pharmacological effects. In addition, Epimedium Linn. has been commonly used to treat osteoporosis, erectile dysfunction, hypertension and cardiovascular disease. In this paper, the distribution of resources, chemical compositions, pharmacological effects, clinical applications and quality control of Epimedium Linn. are progressed to provide a reference for further research and development of the resources of this genus.

Mapping of major QTL and candidate gene analysis for hull colour in foxtail millet (Setaria italica (L.) P. Beauv.).

BACKGROUND: Hull colour is an important morphological marker for selection in seed production of foxtail millet. However, the molecular mechanisms underlying hull colour variation remain unknown. RESULTS: An F7 recombinant inbred line (RIL) population containing 215 lines derived from Hongjiugu × Yugu18 was used to analyze inheritance and detect the quantitative trait loci (QTL) for four hull colour traits using major gene plus polygene mixed inheritance analysis and composite interval mapping (CIM) in four environments. Genetic analysis revealed that the hull colour L* value (HCL*) was controlled by two major genes plus additive polygenes, the hull colour a* value (HCa*) was controlled by three major genes, the hull colour b* value (HCb*) was controlled by two major genes plus polygenes, and the hull colour C* value (HCC*) was controlled by four major genes. A high-density genetic linkage map covering 1227.383 cM of the foxtail millet genome, with an average interval of 0.879 cM between adjacent bin markers, was constructed using 1420 bin markers. Based on the genetic linkage map and the phenotypic data, a total of 39 QTL were detected for these four hull colour traits across four environments, each explaining 1.50%-49.20% of the phenotypic variation. Of these, six environmentally stable major QTL were co-localized to regions on chromosomes 1 and 9, playing a major role in hull colour. There were 556 annotated genes within the two QTL regions. Based on the functions of homologous genes in Arabidopsis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) gene annotations, five genes were predicted as candidate genes for further studies. CONCLUSIONS: This is the first study to use an inheritance model and QTL mapping to determine the genetic mechanisms of hull colour trait in foxtail millet. We identified six major environmentally stable QTL and predicted five potential candidate genes to be associated with hull colour. These results advance the current understanding of the genetic mechanisms underlying hull colour traits in foxtail millet and provide additional resources for application in genomics-assisted breeding and potential isolation and functional characterization of the candidate genes.

Bioinformatics toolbox for exploring protein phosphorylation network.

A clear systematic delineation of the interactions between phosphorylation sites on substrates and their effector kinases plays a fundamental role in revealing cellular activities, understanding signaling modulation mechanisms and proposing novel hypotheses. The emergence of bioinformatics tools contributes to studying phosphorylation network. Some of them feature the visualization of network, enabling more effective trace of the underlying biological problems in a clear and succinct way. In this review, we aimed to provide a toolbox for exploring phosphorylation network. We first systematically surveyed 19 tools that are available for exploring phosphorylation networks, and subsequently comparatively analyzed and summarized these tools to guide tool selection in terms of functionality, data sources, performance, network visualization and implementation, and finally briefly discussed the application cases of these tools. In different scenarios, the conclusion on the suitability of a tool for a specific user may vary. Nevertheless, easily accessible bioinformatics tools are proved to facilitate biological findings. Hopefully, this work might also assist non-specialists, students, as well as computational scientists who aim at developing novel tools in the field of phosphorylation modification.

Cloud 3D-QSAR: a web tool for the development of quantitative structure-activity relationship models in drug discovery.

Effective drug discovery contributes to the treatment of numerous diseases but is limited by high costs and long cycles. The Quantitative Structure-Activity Relationship (QSAR) method was introduced to evaluate the activity of a large number of compounds virtually, reducing the time and labor costs required for chemical synthesis and experimental determination. Hence, this method increases the efficiency of drug discovery. To meet the needs of researchers to utilize this technology, numerous QSAR-related web servers, such as Web-4D-QSAR and DPubChem, have been developed in recent years. However, none of the servers mentioned above can perform a complete QSAR modeling and supply activity prediction functions. We introduce Cloud 3D-QSAR by integrating the functions of molecular structure generation, alignment, molecular interaction field (MIF) computing and results analysis to provide a one-stop solution. We rigidly validated this server, and the activity prediction correlation was R2 = 0.934 in 834 test molecules. The sensitivity, specificity and accuracy were 86.9%, 94.5% and 91.5%, respectively, with AUC = 0.981, AUCPR = 0.971. The Cloud 3D-QSAR server may facilitate the development of good QSAR models in drug discovery. Our server is free and now available at http://chemyang.ccnu.edu.cn/ccb/server/cloud3dQSAR/ and http://agroda.gzu.edu.cn:9999/ccb/server/cloud3dQSAR/.

A fine-scale map of genome-wide recombination in divergent Escherichia coli population.

Recombination is one of the most important molecular mechanisms of prokaryotic genome evolution, but its exact roles are still in debate. Here we try to infer genome-wide recombination within a species, utilizing a dataset of 149 complete genomes of Escherichia coli from diverse animal hosts and geographic origins, including 45 in-house sequenced with the single-molecular real-time platform. Two major clades identified based on physiological, clinical and ecological characteristics form distinct genetic lineages based on scarcity of interclade gene exchanges. By defining gene-based syntenies for genomic segments within and between the two clades, we build a fine-scale recombination map for this representative global E. coli population. The map suggests extensive within-clade recombination that often breaks physical linkages among individual genes but seldom interrupts the structure of genome organizational frameworks as well as primary metabolic portfolios supported by the framework integrity, possibly due to strong natural selection for both physiological compatibility and ecological fitness. In contrast, the between-clade recombination declines drastically when phylogenetic distance increases to the extent where a 10-fold reduction can be observed, establishing a firm genetic barrier between clades. Our empirical data suggest a critical role for such recombination events in the early stage of speciation where recombination rate is associated with phylogenetic distance in addition to sequence and gene variations. The extensive intraclade recombination binds sister strains into a quasisexual group and optimizes genes or alleles to streamline physiological activities, whereas the sharply declined interclade recombination split the population into clades adaptive to divergent ecological niches.

Rotundic acid improves nonalcoholic steatohepatitis in mice by regulating glycolysis and the TLR4/AP1 signaling pathway.

BACKGROUND: Steatosis and inflammation are the hallmarks of nonalcoholic steatohepatitis (NASH). Rotundic acid (RA) is among the key triterpenes of Ilicis Rotundae Cortex and has exhibited multipronged effects in terms of lowering the lipid content and alleviating inflammation. The study objective is to systematically evaluate the potential mechanisms through which RA affects the development and progression of NASH. METHODS: Transcriptomic and proteomic analyses of primary hepatocytes isolated from the control, high-fat diet-induced NASH, and RA treatment groups were performed through Gene Ontology analysis and pathway enrichment. Hub genes were identified through network analysis. Integrative analysis revealed key RA-regulated pathways, which were verified by gene and protein expression studies and cell assays. RESULTS: Hub genes were identified and enriched in the Toll-like receptor 4 (TLR4)/activator protein-1 (AP1) signaling pathway and glycolysis pathway. RA reversed glycolysis and attenuated the TLR4/AP1 pathway, thereby reducing lipid accumulation and inflammation. Additionally, lactate release in L-02 cells increased with NaAsO2-treated and significantly decreased with RA treatment, thus revealing that RA had a major impact on glycolysis. CONCLUSIONS: RA is effective in lowering the lipid content and reducing inflammation in mice with NASH by ameliorating glycolysis and TLR4/AP1 pathways, which contributes to the existing knowledge and potentially sheds light on the development of therapeutic interventions for patients with NASH.

Synthesis and Cytotoxicity Evaluation of Dehydroepiandrosterone Derivatives by Iron-Catalyzed Stereoselective Hydroamination.

The direct modification of structurally complex natural product dehydroepiandrosterone (DHEA) through iron-catalyzed direct hydroamination of DHEA with various nitro(hetero)arenes was carried out to afford 5α-arylamino-DHEAs (1-25) in good yields (53-72%). Though as a radical reaction, it features high stereoselectivity, and only the 5α-substituted derivatives were produced. The in vitro antiproliferative activity of these synthesized compounds against the human breast cancer MCF-7 cell was evaluated, showing that most of DHEA analogues possessed the moderate cytotoxic activity. The preliminary structure-activity relationship analysis revealed that the electron-withdrawing groups installed at the para-position of arylamine ring had a great contribution to the improvement of the DHEA's cytotoxic potency. Among them, (4-trifluoromethylaniline)-DHEA (4) displayed the most potent cytotoxicity, with an IC50 value of 19.3 µM, which was 2.3-fold more active than DHEA.

Palladium-catalyzed synthesis and acetylcholinesterase inhibitory activity evaluation of 1-arylhuperzine A derivatives.

A series of arylated huperzine A (HPA) derivatives (1-24) were efficiently synthesized in good yields (45-88% yields) through the late-stage modification of structurally complex natural anti-Alzheimer's disease (AD) drug huperzine A (HPA), using the palladium-catalyzed Suzuki-Miyaura cross-coupling reaction. The acetylcholinesterase (AChE) inhibitory activity of all synthesized compounds was evaluated to screen the potential anti-AD bioactive molecules. The results showed that introducing the aryl groups to C-1 position of HPA resulted in the unsatisfactory AChE inhibitory activity. The present study demonstrably verifies pyridone carbonyl group could be the necessary and unchangeable pharmacophore for maintaining HPA's anti-AChE potency, and provides the helpful information on the further research for developing anti-AD HPA analogues.

Concentrations, seasonal trends, sources, health risk and subchronic toxicity to the respiratory and immune system of PAHs in PM2.5 in Xi'an.

PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) have been proved to be hazardous to health. Previous studies have focused on the distribution and sources of PAHs, whereas there is little knowledge of the damage to organs. Here we sought to investigate the pollution level and seasonal variation characteristics of PAHs in PM2.5 in Xi'an and assess the health risk, to establish a PAHs exposure model, and investigate the toxicological effects of PAHs on the respiratory and immune functions. A sub-chronic exposure model of PAHs was established by inhalation. The pathological changes of lung tissues were observed with a light microscope. Inflammatory reactions in alveolar lavage fluid were determined using the corresponding kit. The levels of interleukin-6 (IL-6) and interleukin-8 (IL-8) were detected with enzyme linked immunosorbent assay (ELISA) kit; the proliferation of lymphocytes in spleen was detected with methyl tetrazolium (MTT); DNA immune damage was determined with DNA gel electrophoresis. The results showed that (1) the total concentration of 16 PAHs ranged from 41.1 to 387 ng/m3, with a mean value of 170 ng/m3, and the concentration of PAHs in PM2.5 was higher in winter than in other seasons. (2) The sources of PAHs in the atmosphere of Xi'an urban area were mainly coal combustion, and the equivalent carcinogenic concentration of PAHs in PM2.5 was 3.9 ng/m3. (3) Foreign body granuloma formation and inflammatory cell damage were observed in the lungs of rats infected with toxin; the levels of reactive oxygen species (ROS) and mobile device assistant (MDA) increased while nitric oxide synthase (NOS) decreased with the increase of dose; the expression levels of IL-6 and IL-8 elevated with the increase of toxin dose, showing an obvious dose-effect relationship; the level of PAHs damage to cells showed a dose-effect relationship. Sub-chronic exposure to PAHs could cause sustained inflammatory injury to the organism. Measures should be taken to counter the problems of PAHs in PM2.5 in Xi'an and relevant health promotion strategies should be developed.

LECT2: A pleiotropic and promising hepatokine, from bench to bedside.

LECT2 (leucocyte cell-derived chemotaxin 2) is a 16-kDa protein mainly produced by hepatocytes. It was first isolated in PHA-activated human T-cell leukaemia SKW-3 cells and originally identified as a novel neutrophil chemotactic factor. However, many lines of studies suggested that LECT2 was a pleiotropic protein, it not only functioned as a cytokine to exhibit chemotactic property, but also played multifunctional roles in some physiological conditions and pathological abnormalities, involving liver regeneration, neuronal development, HSC(haematopoietic stem cells) homeostasis, liver injury, liver fibrosis, hepatocellular carcinoma, metabolic disorders, inflammatory arthritides, systemic sepsis and systemic amyloidosis. Among the above studies, it was discovered that LECT2 could be a promising molecular biomarker and therapeutic target. This review summarizes LECT2-related receptors and pathways, basic and clinical researches, primarily in mice and human, for a better comprehension and management of these diseases in the future.

Enhanced intestinal protein fermentation in schizophrenia.

BACKGROUND: Emerging findings highlighted the associations of mental illness to nutrition and dysbiosis in the intestinal microbiota, but the underlying mechanisms, especially in schizophrenia (SZ), remain unclarified. METHODS: We conducted a case-control study of SZ patients (case to control=100:52) by performing sequencing of the gut metagenome; measurement of fecal and plasma non-targeted metabolome; including short-, medium-, and long-chain fatty acids; and targeted metabolites, along with recorded details of daily intakes of food. RESULTS: The metagenome analysis uncovered enrichment of asaccharolytic species and reduced abundance of carbohydrate catabolism pathways and enzymes in the gut of SZ patients, but increased abundance of peptidases in contrast to their significantly reduced protein intake. Fecal metabolome analysis identified increased concentrations of many protein catabolism products, including amino acids (AAs), urea, branched short-chain fatty acids, and various nitrogenous derivates of aromatic AAs in SZ patients. Protein synthesis, represented by the abundance of AA-biosynthesis pathways and aminoacyl-tRNA transferases in metagenome, was significantly decreased. The AUCs (area under the curve) of the diagnostic random forest models based on their abundance achieved 85% and 91%, respectively. The fecal levels of AA-fermentative enzymes and products uniformly showed positive correlations with the severity of psychiatric symptoms. CONCLUSIONS: Our findings revealed apparent dysbiosis in the intestinal microbiome of SZ patients, where microbial metabolism is dominated by protein fermentation and shift from carbohydrate fermentation and protein synthesis in healthy conditions. The aberrant macronutrient metabolism by gut microbes highlights the importance of nutrition care and the potential for developing microbiota-targeted therapeutics in SZ.

Enhanced DNA and RNA pathogen detection via metagenomic sequencing in patients with pneumonia.

BACKGROUND: Metagenomic next-generation sequencing (mNGS) is an important supplement to conventional tests for pathogen detections of pneumonia. However, mNGS pipelines were limited by irregularities, high proportion of host nucleic acids, and lack of RNA virus detection. Thus, a regulated pipeline based on mNGS for DNA and RNA pathogen detection of pneumonia is essential. METHODS: We performed a retrospective study of 151 patients with pneumonia. Three conventional tests, culture, loop-mediated isothermal amplification (LAMP) and viral quantitative real-time polymerase chain reaction (qPCR) were conducted according to clinical needs, and all samples were detected using our optimized pipeline based on the mNGS (DNA and RNA) method. The performances of mNGS and three other tests were compared. Human DNA depletion was achieved respectively by MolYsis kit and pre-treatment using saponin and Turbo DNase. Three RNA library preparation methods were used to compare the detection performance of RNA viruses. RESULTS: An optimized mNGS workflow was built, which had only 1-working-day turnaround time. The proportion of host DNA in the pre-treated samples decreased from 99 to 90% and microbiome reads achieved an approximately 20-fold enrichment compared with those without host removal. Meanwhile, saponin and Turbo DNase pre-treatment exhibited an advantage for DNA virus detection compared with MolYsis. Besides, our in-house RNA library preparation procedure showed a more robust RNA virus detection ability. Combining three conventional methods, 76 (76/151, 50.3%) cases had no clear causative pathogen, but 24 probable pathogens were successfully detected in 31 (31/76 = 40.8%) unclear cases using mNGS. The agreement of the mNGS with the culture, LAMP, and viral qPCR was 60%, 82%, and 80%, respectively. Compared with all conventional tests, mNGS had a sensitivity of 70.4%, a specificity of 72.7%, and an overall agreement of 71.5%. CONCLUSIONS: A complete and effective mNGS workflow was built to provide timely DNA and RNA pathogen detection for pneumonia, which could effectively remove the host sequence, had a higher microbial detection rate and a broader spectrum of pathogens (especially for viruses and some pathogens that are difficult to culture). Despite the advantages, there are many challenges in the clinical application of mNGS, and the mNGS report should be interpreted with caution.

Intervalley Excitonic Hybridization, Optical Selection Rules, and Imperfect Circular Dichroism in Monolayer h-BN.

We perform first-principles GW plus Bethe-Salpeter equation calculations to investigate the photophysics of monolayer hexagonal boron nitride (h-BN), revealing excitons with novel k-space characteristics. The excitonic states forming the first and third peaks in its absorption spectrum are s-like, but those of the second peak are notably p-like, a first finding of strong co-occurrence of bright s-like and bright p-like states in an intrinsic 2D material. Moreover, even though the k-space wave function of these excitonic states are centered at the K and K^{'} valleys as in monolayer transition metal dichalcogenides, the k-space envelope functions of the basis excitons at one valley have significant extents to the basin of the other valley. As a consequence, the optical response of monolayer h-BN exhibits a lack of circular dichroism, as well as a coupling that induces an intervalley mixing between s- and p-like states.

Unveiling toxicity profile for food risk components: A manually curated toxicological databank of food-relevant chemicals.

Rigorous risk assessment of chemicals in food and feed is essential to address the growing worldwide concerns about food safety. High-quality toxicological data on food-relevant chemicals are fundamental for risk modeling and assessment in the food safety area. The organization and analysis of substantial toxicity information can positively support decision-making by providing insight into toxicity trends. However, it remains challenging to systematically obtain fragmented toxicity data, and related toxicological resources are required to meet the current demands. In this study, we collected 221,439 experimental toxicity records for 5,657 food-relevant chemicals identified from extensive databases and literature, along with their information on chemical identification, physicochemical properties, environmental fates, and biological targets. Based on the aggregated data, a freely available web-based databank, Food-Relevant Available Chemicals Toxicology Databank (FRAC-TD) is presented, which supports multiple browsing ways and search criterions. Applying FRAC-TD for data-driven analysis, we revealed the underlying toxicity profiles of food-relevant chemicals in humans, mammals, and other species in the food chain. Expectantly, FRAC-TD could positively facilitate toxicological studies, toxicity prediction, and risk assessments in the food industry.