A new paradigm for applying deep learning to protein-ligand interaction prediction.

Protein-ligand interaction prediction presents a significant challenge in drug design. Numerous machine learning and deep learning (DL) models have been developed to accurately identify docking poses of ligands and active compounds against specific targets. However, current models often suffer from inadequate accuracy or lack practical physical significance in their scoring systems. In this research paper, we introduce IGModel, a novel approach that utilizes the geometric information of protein-ligand complexes as input for predicting the root mean square deviation of docking poses and the binding strength (pKd, the negative value of the logarithm of binding affinity) within the same prediction framework. This ensures that the output scores carry intuitive meaning. We extensively evaluate the performance of IGModel on various docking power test sets, including the CASF-2016 benchmark, PDBbind-CrossDocked-Core and DISCO set, consistently achieving state-of-the-art accuracies. Furthermore, we assess IGModel's generalizability and robustness by evaluating it on unbiased test sets and sets containing target structures generated by AlphaFold2. The exceptional performance of IGModel on these sets demonstrates its efficacy. Additionally, we visualize the latent space of protein-ligand interactions encoded by IGModel and conduct interpretability analysis, providing valuable insights. This study presents a novel framework for DL-based prediction of protein-ligand interactions, contributing to the advancement of this field. The IGModel is available at GitHub repository https://github.com/zchwang/IGModel.

StemDriver: a knowledgebase of gene functions for hematopoietic stem cell fate determination.

StemDriver is a comprehensive knowledgebase dedicated to the functional annotation of genes participating in the determination of hematopoietic stem cell fate, available at http://biomedbdc.wchscu.cn/StemDriver/. By utilizing single-cell RNA sequencing data, StemDriver has successfully assembled a comprehensive lineage map of hematopoiesis, capturing the entire continuum from the initial formation of hematopoietic stem cells to the fully developed mature cells. Extensive exploration and characterization were conducted on gene expression features corresponding to each lineage commitment. At the current version, StemDriver integrates data from 42 studies, encompassing a diverse range of 14 tissue types spanning from the embryonic phase to adulthood. In order to ensure uniformity and reliability, all data undergo a standardized pipeline, which includes quality data pre-processing, cell type annotation, differential gene expression analysis, identification of gene categories correlated with differentiation, analysis of highly variable genes along pseudo-time, and exploration of gene expression regulatory networks. In total, StemDriver assessed the function of 23 839 genes for human samples and 29 533 genes for mouse samples. Simultaneously, StemDriver also provided users with reference datasets and models for cell annotation. We believe that StemDriver will offer valuable assistance to research focused on cellular development and hematopoiesis.

Integrated mRNA sequence optimization using deep learning.

The coronavirus disease of 2019 pandemic has catalyzed the rapid development of mRNA vaccines, whereas, how to optimize the mRNA sequence of exogenous gene such as severe acute respiratory syndrome coronavirus 2 spike to fit human cells remains a critical challenge. A new algorithm, iDRO (integrated deep-learning-based mRNA optimization), is developed to optimize multiple components of mRNA sequences based on given amino acid sequences of target protein. Considering the biological constraints, we divided iDRO into two steps: open reading frame (ORF) optimization and 5' untranslated region (UTR) and 3'UTR generation. In ORF optimization, BiLSTM-CRF (bidirectional long-short-term memory with conditional random field) is employed to determine the codon for each amino acid. In UTR generation, RNA-Bart (bidirectional auto-regressive transformer) is proposed to output the corresponding UTR. The results show that the optimized sequences of exogenous genes acquired the pattern of human endogenous gene sequence. In experimental validation, the mRNA sequence optimized by our method, compared with conventional method, shows higher protein expression. To the best of our knowledge, this is the first study by introducing deep-learning methods to integrated mRNA sequence optimization, and these results may contribute to the development of mRNA therapeutics.

PharmaRedefine: A database server for repurposing drugs against pathogenic bacteria.

Pathogenic bacteria represent a formidable threat to human health, necessitating substantial resources for prevention and treatment. With the escalating concern regarding antibiotic resistance, there is a pressing need for innovative approaches to combat these pathogens. Repurposing existing drugs offers a promising solution. Our present work hypothesizes that proteins harboring ligand-binding pockets with similar chemical environments may be able to bind the same drug. To facilitate this drug-repurposing strategy against pathogenic bacteria, we introduce an online server, PharmaRedefine. Leveraging a combination of sequence and structure alignment and protein pocket similarity analysis, this platform enables the prediction of potential targets in representative bacteria for specific FDA-approved drugs. This novel approach holds tremendous potential for drug repositioning that effectively combat infections caused by pathogenic bacteria. PharmaRedefine is freely available at http://guolab.mpu.edu.mo/pharmredefine.

ALKHB5-demethylated lncRNA SNHG15 promotes myeloma tumorigenicity by increasing chromatin accessibility and recruiting H3K36me3 modifier SETD2.

Chromatin instability plays a crucial role in multiple myeloma (MM) relapse and progression, but its mechanism remains obscure. Here, we uncovered that m6A-demethylase ALKBH5 upregulated and stabilized long noncoding RNA (lncRNA) small nucleolar RNA host gene 15 (SNHG15), which was elevated in MM and positively correlated with unfavorable clinical prognosis factors. ALKBH5-SNHG15 axis participated in viability and migration/invasion of myeloma cell lines and MM-xenografted SCID/NOD mice. Mechanically, ALKBH5 promoted the expression of trimethylated histone H3 at lysine 36 (H3K36me3) methyltransferase SETD2 through lncRNA SNHG15-mediated protein stability. ALKBH5-SNHG15 axis increased chromatin accessibility and altered the H3K36me3 enrichment at the gene body, which is responsible for transcription elongation. Our study suggested a novel epigenetically interaction of N6-methyladenosine (m6A) methylation, lncRNA SNHG15, and histone SETD2/H3K36me3 modifications in myeloma progression, indicating that ALKBH5 and lncRNA SNHG15 could serve as potential novel therapeutic targets for MM treatment.NEW & NOTEWORTHY To our knowledge, this study first demonstrated the prognostic significance and biological function of long noncoding RNA (lncRNA) small nucleolar RNA host gene 15 (SNHG15) in multiple myeloma (MM), and indicated a novel revelation on the effect of N6-methyladenosine (m6A)-regulated lncRNA on MM tumorigenicity. Moreover, the novel chromatin-regulatory mechanism of lncRNA by interacting with epigenetic modifiers including m6A demethylase ALKBH5 and H3K36me3 methyltransferase SETD2 in myeloma progression elucidated intricate mechanism of tumor pathogenesis.

Exogenous melatonin alleviates sodium chloride stress and increases vegetative growth in Lonicera japonica seedlings via gene regulation.

Melatonin (Mt) functions as a growth regulator and multifunctional signaling molecule in plants, thereby playing a crucial role in promoting growth and orchestrating protective responses to various abiotic stresses. However, the mechanism whereby exogenous Mt protects Lonicera japonica Thunb. (L. japonica) against salt stress has not been fully elucidated. Therefore, this study aimed to elucidate how exogenous Mt alleviates sodium chloride (NaCl) stress in L. japonica seedlings. Salt-sensitive L. japonica seedlings were treated with an aqueous solution containing 150 mM of NaCl and aqueous solutions containing various concentrations of Mt. The results revealed that treatment of NaCl-stressed L. japonica seedlings with a 60 µM aqueous solution of Mt significantly enhanced vegetative plant growth by scavenging reactive oxygen species and thus reducing oxidative stress. The latter was evidenced by decreases in electrical conductivity and malondialdehyde (MDA) concentrations. Moreover, Mt treatment led to increases in the NaCl-stressed L. japonica seedlings' total chlorophyll content, soluble sugar content, and flavonoid content, demonstrating that Mt treatment improved the seedlings' tolerance of NaCl stress. This was also indicated by the NaCl-stressed L. japonica seedlings exhibiting marked increases in the activities of antioxidant enzymes (superoxide dismutase, peroxidase, catalase, and ascorbate peroxidase) and in photosynthetic functions. Furthermore, Mt treatment of NaCl-stressed L. japonica seedlings increased their expression of phenylalanine ammonia-lyase 1 (PAL1), phenylalanine ammonia-lyase 2 (PAL2), calcium-dependent protein kinase (CPK), cinnamyl alcohol dehydrogenase (CAD), flavanol synthase (FLS), and chalcone synthase (CHS). In conclusion, our results demonstrate that treatment of L. japonica seedlings with a 60 µM aqueous solution of Mt significantly ameliorated the detrimental effects of NaCl stress in the seedlings. Therefore, such treatment has substantial potential for use in safeguarding medicinal plant crops against severe salinity.

Coupled hydraulics and carbon economy underlie age-related growth decline and revitalisation of sand-fixing shrubs after crown removal.

Crown removal revitalises sand-fixing shrubs that show declining vigour with age in drought-prone environments; however, the underlying mechanisms are poorly understood. Here, we addressed this knowledge gap by comparing the growth performance, xylem hydraulics and plant carbon economy across different plant ages (10, 21 and 33 years) and treatments (control and crown removal) using a representative sand-fixing shrub (Caragana microphylla Lam.) in northern China. We found that growth decline with plant age was accompanied by simultaneous decreases in soil moisture, plant hydraulic efficiency and photosynthetic capacity, suggesting that these interconnected changes in plant water relations and carbon economy were responsible for this decline. Following crown removal, quick resprouting, involving remobilisation of root nonstructural carbohydrate reserves, contributed to the reconstruction of an efficient hydraulic system and improved plant carbon status, but this became less effective in older shrubs. These age-dependent effects of carbon economy and hydraulics on plant growth vigour provide a mechanistic explanation for the age-related decline and revitalisation of sand-fixing shrubs. This understanding is crucial for the development of suitable management strategies for shrub plantations constructed with species having the resprouting ability and contributes to the sustainability of ecological restoration projects in water-limited sandy lands.

Identification of Increased Grain Length 1 (IGL1), a novel gene encoded by a major QTL for modulating grain length in rice.

KEY MESSAGE: A novel quantitative trait locus qIGL1, which performed a positive function in regulating grain length in rice, was cloned by the map-based cloning approach; further studies revealed that it corresponded to LOC_Os03g30530, and the IGL1 appeared to contribute to lengthening and widening of the cells on the surface of grain hulls. Grain length is a prominent determinant for grain weight and appearance quality of rice. In this study, we conducted quantitative trait locus mapping to determine a genomic interval responsible for a long-grain phenotype observed in a japonica cultivar HD385. This led to the identification of a novel QTL for grain length on chromosome 3, named qIGL1 (for Increased Grain Length 1); the HD385 (Handao 385)-derived allele showed enhancement effects on grain length, and such an allele as well as NIP (Nipponbare)-derived allele was designated qigl1 HD385 and qIGL1NIP, respectively. Genetic analysis revealed that the qigl1HD385 allele displayed semidominant effects on grain length. Fine mapping further narrowed down the qIGL1 to an ~ 70.8-kb region containing 9 open reading frames (ORFs). A comprehensive analysis indicated that LOC_Os03g30530, which corresponded to ORF6 and carried base substitutions and deletions in HD385 relative to NIP, thereby causing changes or losses of amino-acid residues, was the true gene for qIGL1. Comparison of grain traits between a pair of near-isogenic lines (NILs), termed NIL-igl1HD385 and NIL-IGL1NIP, discovered that introduction of the igl1HD385 into the NIP background significantly resulted in the elevations of grain length and 1000-grain weight. Closer inspection of grain surfaces revealed that the cell length and width in the longitudinal direction were significantly longer and greater, respectively, in NIL-igl1HD385 line compared with in NIL-IGL1NIP line. Hence, our studies identified a new semidominant natural allele contributing to the increase of grain length and further shed light on the regulatory mechanisms of grain length.

Effects of PGE1 on the ERS pathway in neonatal rats with hyperoxic lung injury.

BACKGROUND: With the increase in the number of low birth weight infants, oxygen therapy is more widely used. However, chronic high-concentration oxygen environments lead to hyperoxic lung injury in children, which in turn leads to bronchopulmonary dysplasia (BPD). PGE1 is widely used in the clinic for its ability to inhibit inflammation and improve circulation. Therefore, we further investigated whether PGE-1 has a therapeutic effect on hyperoxic lung injury. METHODS: Hyperoxic lung injury model was adopted for investigating the interventional effects and underlying mechanisms of intraperitoneal injection of prostaglandin E1 (PGE-1) on hyperoxic lung injury in newborn rats via relevant experimental techniques, such as Diff-Quick staining, lung wet dry specific gravity measurements, HE staining, TUNEL staining, ELISA, and the Western blot method. RESULTS: Inflammatory and apoptotic cells in the PGE1-treated group were significantly lower than those in the hyperoxic lung injury group (p < 0.05); and the contents of IL-1ß, IL-6 and TNF-α in the treated group were significantly lower than those in the model group (p < 0.05). Caspase-3, CHOP, GRP78 and Bcl-2/Bax protein expression in the treatment group was significantly lower than that in the model group (p < 0.05). CONCLUSION: PGE-1 has a therapeutic effect on hyperoxic lung injury in neonatal rats. IMPACT: PGE1 treatment reduces levels of inflammatory cells and pro-inflammatory cytokines and decreases apoptosis. PGE1 has a therapeutic effect on BPD through the endoplasmic reticulum stress pathway. This study offers the possibility of PGE1 for the treatment of BPD.

The spatial-temporal distribution of hepatitis B virus infection in China,2006-2018.

OBJECTIVES: Hepatitis B is a liver disease caused by Hepatitis B virus (HBV) infection and is highly prevalent in China. To better understand the epidemiological characteristics of hepatitis B in China and develop effective disease control strategies, we employed temporal and spatial statistical methods. METHODS: We obtained HBV incidence data from the Public Health Science Data Center of the Chinese Center for Disease Control and Prevention for the years 2006 to 2018. Using Geographic Information System (GIS) and SaTScan scanning technology, we conducted spatial autocorrelation analysis and spatiotemporal scan analysis to create a map and visualize the distribution of hepatitis B incidence. RESULTS: While hepatitis B incidence rebounded in 2011 and 2017, the overall incidence in China decreased.In the trend analysis by item, the incidence varies from high to low. The global spatial autocorrelation analysis revealed a clustered distribution, and the Moran index analysis of spatial autocorrelation within local regions identified five provinces as H-H clusters (hot spots), while one province was an L-L cluster (cold spot). Spatial scan analysis identified 11 significant spatial clusters. CONCLUSIONS: We found significant clustering in the spatial distribution of hepatitis B incidence and positive spatial correlation of hepatitis B incidence in China. We also identified high-risk times and regional clusters of hepatitis B incidence.

Experimental recognition of vortex beams in oceanic turbulence combining the Gerchberg-Saxton algorithm and convolutional neural network.

In underwater wireless optical communication (UWOC), vortex beams carrying orbital angular momentum (OAM) can improve channel capacity but are vulnerable to oceanic turbulence (OT), leading to recognition errors. To mitigate this issue, we propose what we believe to be a novel method that combines the Gerchberg-Saxton (GS) algorithm-based recovery with convolutional neural network (CNN)-based recognition (GS-CNN). Our experimental results demonstrate that superposed Laguerre-Gaussian (LG) beams with small topological charge are ideal information carriers, and the GS-CNN remains effective even when OT strength C n2 is high up to 10-11 K 2 m -2/3. Furthermore, we use 16 kinds of LG beams to transmit a 256-grayscale digital image, giving rise to an increase in recognition accuracy from 0.75 to 0.93 and a decrease in bit error ratio from 3.98×10-2 to 6.52×10-3 compared to using the CNN alone.

Posttraumatic growth of medical staff during COVID-19 pandemic: A scoping review.

BACKGROUND: The COVID-19 pandemic has imposed unprecedented stress and challenges upon medical staff, potentially resulting in posttraumatic growth (PTG). This scoping review aims to synthesize the existing knowledge on PTG among medical staff during the pandemic by identifying its current status and potential influencing factors. The findings may provide a foundation for future research and interventions to enhance the medical staff's psychological resilience and well-being. METHODS: Literature was systematically searched on PTG among medical staff during the COVID-19 pandemic from 01 January 2020 to 31 December 2022. The following databases were searched: PubMed, Web of Science, Embase, CINAHL, PsycINFO, Cochrane Library, China National Knowledge Infrastructure (CNKI), Chinese Biomedical Literature Service System (SinoMed), and Wanfang Data. Eligibility criteria included: (1) medical staff as research subjects; (2) a focus on "posttraumatic growth" or "alternative posttraumatic growth" related to the COVID-19 outbreak and pandemic; (3) discussion of the situation and influencing factors of PTG; and (4) study types, such as qualitative, quantitative, and mixed methods. Two researchers independently selected and extracted study characteristics (study design, study population, region, measurement instruments, and primary outcomes) from the included literature. The data were synthesized qualitatively and descriptively. RESULTS: Thirty-six papers from 12 countries met the inclusion criteria. Moderate PTG levels were observed among healthcare workers during the COVID-19 pandemic, with emphasis on "interpersonal relationships," "changes in life philosophy," and "growth in personal competence." Influencing factors included trauma exposure, sociodemographics, psychological characteristics (resilience and positive qualities), coping, and social support. CONCLUSIONS: This review discovered moderate PTG levels among medical staff during the COVID-19 pandemic, with critical areas in interpersonal relationships, life philosophy, and personal competence. The identified influencing factors can inform future research and interventions to enhance healthcare workers' psychological resilience and well-being.

Deep Learning-Based Segmentation and Risk Stratification for Gastrointestinal Stromal Tumors in Transabdominal Ultrasound Imaging.

PURPOSE: To develop a deep neural network system for the automatic segmentation and risk stratification prediction of gastrointestinal stromal tumors (GISTs). METHODS: A total of 980 ultrasound (US) images from 245 GIST patients were retrospectively collected. These images were randomly divided (6:2:2) into a training set, a validation set, and an internal test set. Additionally, 188 US images from 47 prospective GIST patients were collected to evaluate the segmentation and diagnostic performance of the model. Five deep learning-based segmentation networks, namely, UNet, FCN, DeepLabV3+, Swin Transformer, and SegNeXt, were employed, along with the ResNet 18 classification network, to select the most suitable network combination. The performance of the segmentation models was evaluated using metrics such as the intersection over union (IoU), Dice similarity coefficient (DSC), recall, and precision. The classification performance was assessed based on accuracy and the area under the receiver operating characteristic curve (AUROC). RESULTS: Among the compared models, SegNeXt-ResNet18 exhibited the best segmentation and classification performance. On the internal test set, the proposed model achieved IoU, DSC, precision, and recall values of 82.1, 90.2, 91.7, and 88.8%, respectively. The accuracy and AUC for GIST risk prediction were 87.4 and 92.0%, respectively. On the external test set, the segmentation models exhibited IoU, DSC, precision, and recall values of 81.0, 89.5, 92.8, and 86.4%, respectively. The accuracy and AUC for GIST risk prediction were 86.7 and 92.5%, respectively. CONCLUSION: This two-stage SegNeXt-ResNet18 model achieves automatic segmentation and risk stratification prediction for GISTs and demonstrates excellent segmentation and classification performance.

Cuproptosis-Related Gene FDX1 Suppresses the Growth and Progression of Colorectal Cancer by Retarding EMT Progress.

Colorectal cancer (CRC) is a usual cancer and a kind of lethiferous cancer. Cuproptosis-related gene ferredoxin 1 (FDX1) has been discovered to act as a suppressor, thereby suppressing some cancers' progression. But, the regulatory functions of FDX1 in CRC progression keep vague. In this work, at first, through TCGA database, it was revealed that FDX1 exhibited lower expression in COAD (colon adenocarcinoma) tissues, and CRC patients with lower FDX1 expression had worse prognosis. Furthermore, FDX1 expression was verified to be down-regulated in CRC tissues (n = 30) and cells. It was further uncovered that FDX1 expression was positively correlated with CDH1 and TJP1 (epithelial marker), and negatively correlated with CDH2, TWIST1, and FN1 (stromal marker), suggesting that FDX1 was closely associated with the epithelial-mesenchymal transition (EMT) progress. Next, it was demonstrated that overexpression of FDX1 suppressed cell viability, invasion, and migration in CRC. Furthermore, it was verified that FDX1 retarded the EMT progress in CRC. Lastly, through rescue assays, the inhibited CRC progression mediated by FDX1 overexpression was rescued by EGF (EMT inducer) treatment. At last, it was uncovered that the tumor growth and metastasis were relieved after FDX1 overexpression, but these changes were reversed after EGF treatment. In conclusion, FDX1 inhibited the growth and progression of CRC by inhibiting EMT progress. This discovery hinted that FDX1 may act as an effective candidate for CRC treatment.

Development of Glycosylation-Modified DPPA-1 Compounds as Innovative PD-1/PD-L1 Blockers: Design, Synthesis, and Biological Evaluation.

In the context of peptide drug development, glycosylation plays a pivotal role. Accordingly, L-type peptides were synthesized predicated upon the PD-1/PD-L1 blocker DPPA-1. Subsequent glycosylation resulted in the production of two distinct glycopeptides, D-glu-LPPA-1 and D-gal-LPPA-1, by using D-glucose (D-glu) and D-galactose (D-gal), respectively, during glycosylation. Both glycopeptides significantly inhibited the interaction between PD-1 and PD-L1, and the measured half maximal inhibitory concentrations (IC50s) were 75.5 µM and 101.9 µM for D-glu-LPPA-1 and D-gal-LPPA-1, respectively. Furthermore, D-gal-LPPA-1 displayed a pronounced ability to restore T-cell functionality. In an MC38 tumor-bearing mouse model, D-gal-LPPA-1 demonstrated a significant inhibitory effect. Notably, D-gal-LPPA-1 substantially augmented the abundance and functionality of CD8+ T cells in the tumor microenvironment. Additionally, in the lymph nodes and spleens, D-gal-LPPA-1 significantly increased the proportion of CD8+ T cells secreting interferon-gamma (IFN-γ). These strong findings position D-gal-LPPA-1 as a potent enhancer of the antitumor immune response in MC38 tumor-bearing mice, underscoring its potential as a formidable PD-1/PD-L1 blocking agent.

Water quality assessment and its pollution source analysis from spatial and temporal perspectives in small watershed of Sichuan Province, China.

Rapid socio-economic development has led to many water environmental issues in small watersheds such as non-compliance with water quality standards, complex pollution sources, and difficulties in water environment management. To achieve a quantitative evaluation of water quality, identify pollution sources, and implement refined management in small watersheds, this study collected monthly seven water quality indexes of four monitoring points from 2010 to 2023, and ten water quality indexes of 23 sampling points in the Shiting River and Mianyuan River which are tributaries of the Tuojiang River Basin. Then, water quality evaluation and pollution source analysis were conducted from both temporal and spatial perspectives using the Water Quality Index (WQI) method, the Absolute Principal Component Scores/Multiple Linear Regression (APCS-MLR) method, and the Positive Matrix Factorization (PMF) receptor modeling technique. The results indicated that except for total nitrogen (TN), the concentrations of other water quality indexes exhibited a decreasing trend, and all were divided into two obvious stages before and after 2016. Furthermore, the proportion of water quality grade of Good and above increased from 73.96 to 84.94% from 2010-2015 to 2016-2023, and the water quality grade of Good and above from upstream to downstream dropped from 100 to 23.33%. From the temporal scale, four and five pollution sources were identified in the first and second stages, respectively. The distinct TN pollutant is mainly affected by agricultural non-point sources (NPS), whose impact is enhanced from 17.76 to 78.31%. Total phosphorus (TP) was affected by the phosphorus chemical industry, whose contribution gradually weakened from 50.8 to 24.9%. From a spatial perspective, four and five pollution sources were identified in the upstream and downstream, respectively. Therefore, even though there are some limitations due to the data availability of water monitory and hydrology data, the proposed research framework of this study can be applied to the water environmental management of other similar watersheds.

Crystalline Olefin-Linked Chiral Covalent Organic Frameworks as a Platform for Asymmetric Catalysis.

The construction of olefin-linked chiral covalent organic frameworks (COFs) with high crystallinity is highly desirable while remains great challenge due to the poor reversibility of the formation reaction for the olefin linkages during the in situ structural self-healing process. Herein, we successfully synthesized two sets of enantiomeric olefin-linked COFs. The chiral catalytic groups are uniformly distributed on the pore walls of COFs, resulting in the full exposure of catalytic sites to the reactants in asymmetric catalysis. The as-prepared (R)/(S)-CCOF8 exhibits excellent catalytic performance with exceeding 99 % enantiomeric excess in the enantioselective electrophilic amination reaction. Moreover, the heterogeneous chiral catalysts are conveniently recycled and could maintain the performance after ten catalytic cycles. Our findings expand the scope to construct stable and crystalline chiral COFs for the asymmetric catalysis.

Redox-Regulated Synthetic Channels: Enabling Reversible Ion Transport by Modulating the Ion-Permeation Pathway.

Natural redox-regulated channel proteins often utilize disulfide bonds as redox sensors for adaptive regulation of channel conformations in response to diverse physiological environments. In this study, we developed novel synthetic ion channels capable of reversibly switching their ion-transport capabilities by incorporating multiple disulfide bonds into artificial systems. X-ray structural analysis and electrophysiological experiments demonstrated that these disulfide-bridged molecules possess well-defined tubular cavities and can be efficiently inserted into lipid bilayers to form artificial ion channels. More importantly, the disulfide bonds in these molecules serve as redox-tunable switches to regulate the formation and disruption of ion-permeation pathways, thereby achieving a transition in the transmembrane transport process between the ON and OFF states.

Bottom-Up Design of Photoactive Chiral Covalent Organic Frameworks for Visible-Light-Driven Asymmetric Catalysis.

The development of chiral covalentorganic framework catalysts (CCOFs) to synthesize enantiopure organic compounds is crucial and highly desirable in synthetic chemistry. Photocatalytic asymmetric reactions based on CCOFs are eco-friendly and sustainable while they are still elaborate. In this work, we report a general bottom-up strategy to successfully synthesize several photoactive CCOFX (X = 1-5 and 1-Boc). The photoactive porphyrin building blocks are selected as knots and various secondary-amine-based chiral catalytic centers are immobilized on the pore walls of CCOFX through a rational design of benzoimidazole linkers. The porphyrin units act as light-harvesting antennae to generate photo-induced charge carriers for the activation of bromide during the photocatalytic asymmetric alkylation of aldehydes. Meanwhile, various aldehydes are activated by the chiral secondary amine to form the target products with a high yield (up to 97%) and ee value (up to 93%). The results significantly expand the scope to predesign CCOF photocatalysts for visible-light-driven asymmetric catalysis.

Free Radical-Mediated Intramolecular Photocyclization of AIEgens Based on 2,3-Diphenylbenzo[b]thiophene S,S-Dioxide.

As an important category of photochemical reactions, photocyclization is regarded as an ideal entry point for building intelligent photoresponsive materials. Herein, a series of aggregation-induced emission luminogens (AIEgens) with sensitive photoresponsive behavior are developed based on 2,3-diphenylbenzo[b]thiophene S,S-dioxide (DP-BTO), and the impacts of substituents with different electronic structures are investigated. The comprehensive experimental and computational characterizations reveal that their photoresponsive activity is resulted from triplet diradical-mediated intramolecular photocyclization, followed by dehydrogenation to yield stable polycyclic photoproducts. This photocyclization process is active in solution but suppressed in the solid state, and thus can act as a supplementary nonradiative decay channel for the excited state to contribute to AIE effect. Moreover, the generated triplet diradical intermediates upon light irradiation can effectively inhibit the growth of S. aureus, indicative of their promising application as antibacterial agents. This work provides an in-depth mechanistic description about the photocyclization of DP-BTO derivatives and furnishes a perspective on the correlation of photochemical decay and photophysical property.