Accurate prediction of molecular properties is crucial for selecting compounds with ideal properties and reducing the costs and risks of trials.Traditional methods based on manually crafted features and graph-based me...Accurate prediction of molecular properties is crucial for selecting compounds with ideal properties and reducing the costs and risks of trials.Traditional methods based on manually crafted features and graph-based methods have shown promising results in molecular property prediction.However,traditional methods rely on expert knowledge and often fail to capture the complex structures and interactions within molecules.Similarly,graph-based methods typically overlook the chemical structure and function hidden in molecular motifs and struggle to effectively integrate global and local molecular information.To address these limitations,we propose a novel fingerprint-enhanced hierarchical graph neural network(FH-GNN)for molecular property prediction that simultaneously learns information from hierarchical molecular graphs and fingerprints.The FH-GNN captures diverse hierarchical chemical information by applying directed message-passing neural networks(D-MPNN)on a hierarchical molecular graph that integrates atomic-level,motif-level,and graph-level information along with their relationships.Addi-tionally,we used an adaptive attention mechanism to balance the importance of hierarchical graphs and fingerprint features,creating a comprehensive molecular embedding that integrated hierarchical mo-lecular structures with domain knowledge.Experiments on eight benchmark datasets from MoleculeNet showed that FH-GNN outperformed the baseline models in both classification and regression tasks for molecular property prediction,validating its capability to comprehensively capture molecular informa-tion.By integrating molecular structure and chemical knowledge,FH-GNN provides a powerful tool for the accurate prediction of molecular properties and aids in the discovery of potential drug candidates.展开更多
Molecular recognition of bioreceptors and enzymes relies on orthogonal interactions with small molecules within their cavity. To date, Chinese scientists have developed three types of strategies for introducing active...Molecular recognition of bioreceptors and enzymes relies on orthogonal interactions with small molecules within their cavity. To date, Chinese scientists have developed three types of strategies for introducing active sites inside the cavity of macrocyclic arenes to better mimic molecular recognition of bioreceptors and enzymes.The editorial aims to enlighten scientists in this field when they develop novel macrocycles for molecular recognition, supramolecular assembly, and applications.展开更多
Due to its synergistic effects and reduced side effects,combination therapy has become an important strategy for treating complex diseases.In traditional Chinese medicine(TCM),the“monarch,minister,assistant,envoy”co...Due to its synergistic effects and reduced side effects,combination therapy has become an important strategy for treating complex diseases.In traditional Chinese medicine(TCM),the“monarch,minister,assistant,envoy”compatibilities theory provides a systematic framework for drug compatibility and has guided the formation of a large number of classic formulas.However,due to the complex compositions and diverse mechanisms of action of TCM,it is difficult to comprehensively reveal its potential synergistic patterns using traditional methods.Synergistic prediction based on molecular compatibility theory provides new ideas for identifying combinations of active compounds in TCM.Compared to resource-intensive traditional experimental methods,artificial intelligence possesses the ability to mine synergistic patterns from multi-omics and structural data,providing an efficient means for modeling and optimizing TCM combinations.This paper systematically reviews the application progress of AI in the synergistic prediction of TCM active compounds and explores the challenges and prospects of its application in modeling combination relationships,thereby contributing to the modernization of TCM theory and methodological innovation.展开更多
Background:In this present study,we have screened major phytoconstituents of Nilavembu Kudineer against critical COVID-19 target proteins that cause severe pneumonia globally.In addition,a human receptor protein that ...Background:In this present study,we have screened major phytoconstituents of Nilavembu Kudineer against critical COVID-19 target proteins that cause severe pneumonia globally.In addition,a human receptor protein that facilitates viral entry into the host cell was also targeted.Methods:Phytoconstituents derived from Nilavembu Kudineer formulation were docked against 12 major proteins,which help viral entry,viral proliferation,and a human receptor facilitate the viral entry into the host cells.The major metabolites of Nilavembu Kudineer were retrieved based on literature from the PubChem database.The docked complex was subjected to MD simulation studies to verify its binding mode and the stability of the interactions.The binding energy analysis was performed to estimate the binding affinity between the compounds and their respective receptors using MM/GBSA.Results:Docking studies have shown that three major plants in the polyherbal formulation,Andrographis paniculata,Mollugo cerviana,and Zingiber officinale,have 14 potential compounds that have better binding affinity against COVID-19 proteins and their host receptor protein.MD studies and binding energy calculations also confirmed that these compounds possess better stability and strong binding energy with these proteins.Conclusion:In silico analyses suggest that phytoconstituents from Nilavembu Kudineer possess promising multi-target antiviral activity against COVID-19.These findings provide a rationale for further experimental studies to validate their therapeutic potential for the treatment of COVID-19.展开更多
Glaucoma,a degenerative optic neuropathy,causes retinal ganglion cell(RGC)apoptosis and irreversible vision loss.Current therapies often fail to stop disease progression despite lowering intraocular pressure,the main ...Glaucoma,a degenerative optic neuropathy,causes retinal ganglion cell(RGC)apoptosis and irreversible vision loss.Current therapies often fail to stop disease progression despite lowering intraocular pressure,the main risk factor.Thus,neuroprotective strategies have gained interest.We performed a bibliometric analysis to determine global publishing trends and relationships among prolific authors,publications,institutions,funding agencies,and journals.We also analyzed author keywords to identify research hotspots in glaucoma neuroprotection.Further,based on keyword analysis,we reviewed most recent literature to understand mechanistic pathways underlying glaucomarelated pathophysiological responses leading to RGC loss.Bibliographic data were sourced from Scopus.Basic bibliographic features were characterized using Scopus’s functions.VOSviewer was used for mapping and visualizing bibliometric networks.The analysis included trends in publications since 2000,the most prolific countries,institutions,authors,and the strength of their linkages.A significant increase in publication output over the past two decades was noted.The United States leads in funding support,research output,and citation links,followed by China and the UK.Among the top 10 most cited authors,three are from Japanese institutions.Keyword analysis shows a focus on molecular targets related to ischemia,excitotoxicity,inflammation,and oxidative stress,with fewer emerging drug candidates and limited clinical trials.Based on the most recent literature,emerging molecular targets underlying these key pathophysiological mechanisms are summarized.In conclusion,while pathophysiology and molecular mechanisms are the current focus,there is not much progress in developing new drug candidates and conducting clinical trials.展开更多
Background:Atherosclerosis(AS),the primary pathological foundation of cardiovascular diseases,is characterized by intricate processes including inflammation,lipid metabolism disorders,and pyroptosis.While the traditio...Background:Atherosclerosis(AS),the primary pathological foundation of cardiovascular diseases,is characterized by intricate processes including inflammation,lipid metabolism disorders,and pyroptosis.While the traditional Chinese medicine compound Dingxin Recipe(DXR)has demonstrated definitive clinical efficacy in treating AS,its therapeutic mechanisms remain unclear.This study employed an integrated approach combining network pharmacology,molecular docking,and molecular dynamics simulations(MDS)to investigate DXR’s anti-AS mechanisms.Methods:Active ingredients and targets of DXR were identified and screened using databases such as GeneCards,OMIM,and TCMSP.An“ingredient-target-disease”network was constructed to visualize these interactions.Molecular docking was utilized to assess the binding affinity between key ingredients and their respective targets.Additionally,MDS were conducted to analyze the stability of these complexes,providing robust evidence for further clinical applications and in-depth research.Results:Through network pharmacology analysis,we identified 99 active drug components,934 gene targets,and 1463 disease targets associated with DXR.Protein-protein interaction analysis revealed central regulatory nodes.Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that these components primarily modulate processes such as inflammatory response and transcription factor activation,and are closely linked to the AGERAGE signaling pathway,lipid metabolism,and atherosclerosis pathways.Molecular docking confirmed strong binding potential between the components and their targets,while MDS further validated the stability of these interactions.Conclusion:This study elucidates that the active ingredients in DXR alleviate AS by mitigating inflammatory responses and inhibiting pyroptosis through the suppression of inflammatory factor release.These findings provide a scientific foundation for the clinical application of DXR in AS treatment.展开更多
Euphorbia helioscopia,a natural plant recognized for its anti-tumor properties,has been extensively investigated in various cancers.However,its therapeutic potential in gastric cancer with positive lymph node metastas...Euphorbia helioscopia,a natural plant recognized for its anti-tumor properties,has been extensively investigated in various cancers.However,its therapeutic potential in gastric cancer with positive lymph node metastasis remains underexplored.This study aimed to elucidate the role of E.helioscopia in treating gastric cancer with lymph node metastasis using an integrative approach that combined network pharmacology,molecular docking,and molecular dynamics simulations.Initially,shared target data between E.helioscopia and gastric cancer with positive lymph node metastasis were identified and systematically analyzed.Subsequently,molecular docking was conducted to validate the interactions between key components and targets.Finally,molecular dynamics simulations were employed,with binding free energy calculations performed using the MM-PBSA algorithm.The findings revealed that the primary bioactive compounds of E.helioscopia in this context included quercetin and luteolin,targeting core molecules such as EGFR and MMP9.Key pathways implicated in its mechanism of action included resistance to EGFR tyrosine kinase inhibitors,among others.Molecular docking demonstrated robust binding affinity between the active compounds and critical targets,with molecular dynamics and binding free energy analyses highlighting a particularly stable interaction between luteolin and MMP9.In conclusion,E.helioscopia exhibited a multi-component,multi-target,and multi-pathway therapeutic profile in treating gastric cancer with positive lymph node metastasis.These findings offered valuable theoretical insights supporting its potential clinical application in oncology.展开更多
Objective To evaluate the antibacterial potential of bioactive compounds from Persicaria hydropiper(L.)(P.hydropiper)against bacterial virulence proteins through molecular docking(MD)and experimental validation.Method...Objective To evaluate the antibacterial potential of bioactive compounds from Persicaria hydropiper(L.)(P.hydropiper)against bacterial virulence proteins through molecular docking(MD)and experimental validation.Methods Six bioactive compounds from P.hydropiper were investigated:catechin(CAT1),hyperin(HYP1),ombuin(OMB1),pinosylvin(PSV1),quercetin 3-sulfate(QSF1),and scutellarein(SCR1).Their binding affinities and potential binding pockets were assessed through MD against four bacterial target proteins with Protein Data Bank identifiers(PDB IDs):topoisomerase IV from Escherichia coli(E.coli)(PDB ID:3FV5),Staphylococcus aureus(S.aureus)gyrase ATPase binding domain(PDB ID:3U2K),CviR from Chromobacterium violaceum(C.violaceum)(PDB ID:3QP1),and glycosyl hydrolase from Pseudomonas aeruginosa(P.aeruginosa)(PDB ID:5BX9).Molecular dynamics simulations(MDS)were performed on the most promising compound-protein complexes for 50 nanoseconds(ns).Drug-likeness was evaluated using Lipinski's Rule of Five(RO5),followed by absorption,distribution,metabolism,excretion,and toxicity(ADMET)analysis using SwissADME and pkCSM web servers.Antibacterial activity was evaluated through disc diffusion assays,testing both individual compounds and combinations with conventional antibiotics[cefotaxime(CTX1,30μg/disc),ceftazidime(CAZ1,30μg/disc),and piperacillin(PIP1,100μg/disc)].Results MD revealed strong binding affinity(ranging from-9.3 to-5.9 kcal/mol)for all compounds,with CAT1 showing exceptional binding to 3QP1(-9.3 kcal/mol)and 5BX9(-8.4 kcal/mol).MDS confirmed the stability of CAT1-protein complexes with binding free energies of-84.71 kJ/mol(5BX9-CAT1)and-95.59 kJ/mol(3QP1-CAT1).Five compounds(CAT1,SCR1,PSV1,OMB1,and QSF1)complied with Lipinski's RO5 and showed favorable ADMET profiles.All compounds were non-carcinogenic,with CAT1 classified in the lowest toxicity class(VI).In antibacterial assays,CAT1 demonstrated significant activity against both gram-positive bacteria[Streptococcus pneumoniae(S.pneumoniae),S.aureus,and Bacillus cereus(B.cereus)][zone diameter of inhibition(ZDI):10-22 mm]and gram-negative bacteria[Acinetobacter baumannii(A.baumannii),E.coli,and P.aeruginosa](ZDI:14-27 mm).Synergistic effects were observed when CAT1 was combined with antibiotics and the growth inhibitory indices(GII)was 0.69-1.00.Conclusion P.hydropiper bioactive compounds,particularly CAT1,show promising antibacterial potential through multiple mechanisms,including direct inhibition of bacterial virulence proteins and synergistic activity with conventional antibiotics.The favorable pharmacological properties and low toxicity profiles support their potential development as therapeutic agents against bacterial infections.展开更多
Porous molecular sieve catalysts,including aluminosilicate zeolites and silicoaluminophosphate(SAPO)molecular sieves,have found widespread use in heterogeneous catalysis and are expected to play a key role in advancin...Porous molecular sieve catalysts,including aluminosilicate zeolites and silicoaluminophosphate(SAPO)molecular sieves,have found widespread use in heterogeneous catalysis and are expected to play a key role in advancing carbon neutrality and sustainable development.Given the ubiquitous presence of water during catalyst synthesis,storage,and application,the interactions between water and molecular sieves as well as their consequent effects on frameworks and catalytic reactions have attracted considerable attention.These effects are inherently complex and highly dependent on various factors such as temperature,water phase,and partial pressure.In this review,we provide a comprehensive overview of the current understanding of water-molecular sieve interactions and their roles in catalysis,based on both experimental and theoretical calculation results.Special attention is paid to water-induced reversible and irreversible structural changes in aluminosilicate and SAPO frameworks at the atomic level,underscoring the dynamic and labile nature of these frameworks in water environments.The influence of water on catalytic performance and reaction kinetics in molecular sieve-catalyzed reactions is discussed from two perspectives:(1)its participation in reaction through hydrogen bonding interactions,such as competitive adsorption at active sites,stabilization of ground and transition states,and proton transfer bridge;(2)its role as a direct reactant forming new species via reactions with other vip molecules.Recent advancements in this area provide valuable insights for the rational design and optimization of catalysts for water-involved reactions.展开更多
Molecular medicine,which delves into the intricacies of biomolecular structure,function,and role,is pivotal for advancing precise diagnostics and personalized treatment.Nucleic acids,a class of star functional molecul...Molecular medicine,which delves into the intricacies of biomolecular structure,function,and role,is pivotal for advancing precise diagnostics and personalized treatment.Nucleic acids,a class of star functional molecules,are notable for their versatile applications in molecular diagnostics,gene therapy,and drug development.Therefore,in this study,we review the extensive use of nucleic acid aptamers in medicinal practice.Furthermore,the expanding field of molecular medicine has catalyzed advancements in traditional Chinese medicine(TCM),as evidenced by scientific endeavors to integrate modern technologies.Therefore,TCM has experienced rapid modernization by leveraging artificial intelligence,nucleic acid molecular medicine,and bioelectronic medicine.展开更多
Silicon-based materials are considered as the next generation anode to replace graphite due to their low cost and ultra-high theoretical capacity.However,significant volume expansion and contraction occur during charg...Silicon-based materials are considered as the next generation anode to replace graphite due to their low cost and ultra-high theoretical capacity.However,significant volume expansion and contraction occur during charging and discharging processes,leading to the instability of electrode structure and susceptibility to peeling and damage,limiting its application.Constructing controllable molecular artificial solid electrolyte interphase(CMASEI)is an effective approach to address the commercialization of silicon-based anode materials[1].Improving the performance of silicon-based anodes through CMASEI is a multifaceted outcome.展开更多
Bulk modulus is a constant that measures the incompressibility of materials, which can be obtained in high pressure experiment by fitting the equations of state(EOS), like third-order Birch–Murnaghan EOS(BM EOS) and ...Bulk modulus is a constant that measures the incompressibility of materials, which can be obtained in high pressure experiment by fitting the equations of state(EOS), like third-order Birch–Murnaghan EOS(BM EOS) and Vinet EOS. Bulk modulus reflects the intermolecular interaction inside molecular crystals, making it useful for researchers to design novel high pressure materials. This review systematically examines bulk moduli of various molecular crystals, including rare-gas solids, di-atom and triplet-atom molecules, saturated organic molecules, and aromatic organic crystals. Comparisons with ionic crystals are presented, along with an analysis of connections between bulk modulus and crystal structures.展开更多
Colorectal cancer(CRC)ranks among the top causes of cancer-related fatalities globally.Recent progress in genomics,proteomics,and bioinformatics has greatly improved our comprehension of the molecular underpinnings of...Colorectal cancer(CRC)ranks among the top causes of cancer-related fatalities globally.Recent progress in genomics,proteomics,and bioinformatics has greatly improved our comprehension of the molecular underpinnings of CRC,paving the way for targeted therapies and immunotherapies.Nonetheless,obstacles such as tumor heterogeneity and drug resistance persist,hindering advancements in treatment efficacy.In this context,the integration of artificial intelligence(AI)and organoid technology presents promising new avenues.AI can analyze genetic and clinical data to forecast disease risk,prognosis,and treatment responses,thereby expediting drug development and tailoring treatment plans.Organoids replicate the genetic traits and biological behaviors of tumors,acting as platforms for drug testing and the formulation of personalized treatment approaches.Despite notable strides in CRC research and treatment-from genetic insights to therapeutic innovations-numerous challenges endure,including the intricate tumor microen-vironment,tumor heterogeneity,adverse effects of immunotherapies,issues related to AI data quality and privacy,and the need for standardization in organoid culture.Future initiatives should concentrate on clarifying the pathogenesis of CRC,refining AI algorithms and organoid models,and creating more effective therapeutic strategies to alleviate the global impact of CRC.展开更多
Pancreatic cancer, particularly pancreatic ductal adenocarcinoma(PDAC), is one of the most lethal malignancies,which is characterized by a complex tumor microenvironment(TME) that fosters immune evasion and treatment ...Pancreatic cancer, particularly pancreatic ductal adenocarcinoma(PDAC), is one of the most lethal malignancies,which is characterized by a complex tumor microenvironment(TME) that fosters immune evasion and treatment resistance. Recent genomic advancements have unveiled diverse molecular subtypes of PDAC, providing insights into targeted therapies and precision medicine. This review synthesizes the current understanding of PDAC's molecular characterization and immunosuppressive TME, as well as emerging therapeutic strategies, including innovative approaches targeting key molecular pathways such as kirsten rat sarcoma viral oncogene homolog(KRAS), epidermal growth factor receptor(EGFR), and immune checkpoints. Despite advances, challenges remain in overcoming treatment resistance and inherent heterogeneity of pancreatic cancer subtypes. We highlight the need for multidisciplinary collaboration to enhance early diagnosis and develop individualized therapeutic protocols, paving the way for improving the outcomes of this aggressive cancer. This integrated perspective underscores the urgency of transforming the innovative research into pancreatic cancer management.展开更多
Advancements in molecular approaches have been utilized to breed crops with a wide range of economically valuable traits to develop superior cultivars.This review provides a concise overview of modern breakthroughs in...Advancements in molecular approaches have been utilized to breed crops with a wide range of economically valuable traits to develop superior cultivars.This review provides a concise overview of modern breakthroughs in molecular plant production.Genotyping and high-throughput phenotyping methods for predictive plant breeding are briefly discussed.In this study,we explore contemporary molecular breeding techniques for producing desirable crop varieties.These techniques include cisgenesis,clustered regularly interspaced short palindromic repeat(CRISPR/Cas9)gene editing,haploid induction,and de novo domestication.We examine the speed breeding approach-a strategy for cultivating plants under controlled conditions.We further highlight the significance of modern breeding technologies in efficiently utilizing agricultural resources for crop production in urban areas.The deciphering of crop genomes has led to the development of extensive DNA markers,quantitative trait loci(QTLs),and pangenomes associated with various desirable crop traits.This shift to the genotypic selection of crops considerably expedites the plant breeding process.Based on the plant population used,the connection between genotypic and phenotypic data provides several genetic elements,including genes,markers,and alleles that can be used in genomic breeding and gene editing.The integration of speed breeding with genomic-assisted breeding and cutting-edge genome editing tools has made it feasible to rapidly manipulate and generate multiple crop cycles and accelerate the plant breeding process.Breakthroughs in molecular techniques have led to substantial improvements in modern breeding methods.展开更多
Recently,diffusion models have emerged as a promising paradigm for molecular design and optimization.However,most diffusion-based molecular generative models focus on modeling 2D graphs or 3D geom-etries,with limited ...Recently,diffusion models have emerged as a promising paradigm for molecular design and optimization.However,most diffusion-based molecular generative models focus on modeling 2D graphs or 3D geom-etries,with limited research on molecular sequence diffusion models.The International Union of Pure and Applied Chemistry(IUPAC)names are more akin to chemical natural language than the simplified molecular input line entry system(SMILES)for organic compounds.In this work,we apply an IUPAC-guided conditional diffusion model to facilitate molecular editing from chemical natural language to chemical language(SMILES)and explore whether the pre-trained generative performance of diffusion models can be transferred to chemical natural language.We propose DiffIUPAC,a controllable molecular editing diffusion model that converts IUPAC names to SMILES strings.Evaluation results demonstrate that our model out-performs existing methods and successfully captures the semantic rules of both chemical languages.Chemical space and scaffold analysis show that the model can generate similar compounds with diverse scaffolds within the specified constraints.Additionally,to illustrate the model’s applicability in drug design,we conducted case studies in functional group editing,analogue design and linker design.展开更多
Aqueous zinc-ion batteries(AZIBs)have regained interest due to their inherent safety and costeffectiveness.However,the zinc anode is notorious for side reactions and dendrite growth,which plague the practical applicat...Aqueous zinc-ion batteries(AZIBs)have regained interest due to their inherent safety and costeffectiveness.However,the zinc anode is notorious for side reactions and dendrite growth,which plague the practical application of AZIBs.Adjusting the interfacial pH to reduce the by-products has been proven to be effective in protecting the zinc anode.Nevertheless,the dynamic regulation of the inherently unstable zinc interface during prolonged cycling remains a significant challenge.Herein,zwitterionic N-tris(hydroxymethyl)methylglycine(TMG)integrated with negative-COO^(-)and positive NH_(2)^(+)groups is proposed to stabilize the Zn anode and extend the lifespan as a self-regulating interfacial additive.The anionic portion serves as a trapping site to balance the interfacial pH and thus mitigate the unintended side reactions.Simultaneously,the NH_(2)^(+)cations are anchored on the zinc surface,forming a water-shielding,zincophilic molecular layer that guides three-dimensional diffusion and promotes uniform electro-deposition.Thus,an average plating efficiency of 99.74%over 3300 cycles at a current density of2 mA cm^(-2)is achieved.Notably,the TMG additive actualizes ultralong life in Zn‖Zn symmetrical cells(5500 h,exceeding 229 days,1 mA cm^(-2)/1 mA h cm^(-2)),and enables the Zn‖I_(2)cells to reach capacity retention rate of 89.4%after 1000 cycles at 1 A g^(-1).展开更多
Traditional Chinese medicine formula(TCMF)represents a fundamental component of Chinese medical practice,incorporating medical knowledge and practices from both Han Chinese and various ethnic minorities,while providin...Traditional Chinese medicine formula(TCMF)represents a fundamental component of Chinese medical practice,incorporating medical knowledge and practices from both Han Chinese and various ethnic minorities,while providing comprehensive insights into health and disease.The foundation of TCMF lies in its holistic approach,manifested through herbal compatibility theory,which has emerged from extensive clinical experience and evolved into a highly refined knowledge system.Within this framework,Chinese herbal medicines exhibit intricated characteristics,including multi-component interactions,diverse target sites,and varied biological pathways.These complexities pose significant challenges for understanding their molecular mechanisms.Contemporary advances in artificial intelligence(AI)are reshaping research in traditional Chinese medicine(TCM),offering immense potential to transform our understanding of the molecular mechanisms underlying TCMFs.This review explores the application of AI in uncovering these mechanisms,highlighting its role in compound absorption,distribution,metabolism,and excretion(ADME)prediction,molecular target identification,compound and target synergy recognition,pharmacological mechanisms exploration,and herbal formula optimization.Furthermore,the review discusses the challenges and opportunities in AI-assisted research on TCMF molecular mechanisms,promoting the modernization and globalization of TCM.展开更多
Guided by molecular networking,nine novel curvularin derivatives(1-9)and 16 known analogs(10-25)were isolated from the hydrothermal vent sediment fungus Penicillium sp.HL-50.Notably,compounds 5-7 represented a hybrid ...Guided by molecular networking,nine novel curvularin derivatives(1-9)and 16 known analogs(10-25)were isolated from the hydrothermal vent sediment fungus Penicillium sp.HL-50.Notably,compounds 5-7 represented a hybrid of curvularin and purine.The structures and absolute configurations of compounds 1-9 were elucidated via nuclear magnetic resonance(NMR)spectroscopy,X-ray diffraction,electronic circular dichroism(ECD)calculations,^(13)C NMR calculation,modified Mosher's method,and chemical derivatization.Investigation of anti-inflammatory activities revealed that compounds 7-9,11,12,14,15,and 18 exhibited significant suppressive effects against lipopolysaccharide(LPS)-induced nitric oxide(NO)production in murine macrophage RAW264.7 cells,with IC_(50)values ranging from 0.44 to 4.40μmol·L^(-1).Furthermore,these bioactive compounds were found to suppress the expression of inflammation-related proteins,including inducible NO synthase(i NOS),cyclooxygenase-2(COX-2),NLR family pyrin domain-containing protein 3(NLRP3),and nuclear factor kappa-B(NF-κB).Additional studies demonstrated that the novel compound 7 possessed potent antiinflammatory activity by inhibiting the transcription of inflammation-related genes,downregulating the expression of inflammation-related proteins,and inhibiting the release of inflammatory cytokines,indicating its potential application in the treatment of inflammatory diseases.展开更多
The global energy demand is increasing rapidly,and it is imperative to develop shale hydrocarbon re-sources vigorously.The prerequisite for enhancing the exploitation efficiency of shale reservoirs is the systematic e...The global energy demand is increasing rapidly,and it is imperative to develop shale hydrocarbon re-sources vigorously.The prerequisite for enhancing the exploitation efficiency of shale reservoirs is the systematic elucidation of the occurrence characteristics,flow behavior,and enhanced oil recovery(EOR)mechanisms of shale oil within commonly developed nanopores.Molecular dynamics(MD)technique can simulate the occurrence,flow,and extraction processes of shale oil at the nanoscale,and then quantitatively characterize various fluid properties,flow characteristics,and action mechanisms under different reservoir conditions by calculating and analyzing a series of MD parameters.However,the existing review on the application of MD simulation in shale oil reservoirs is not systematic enough and lacks a summary of technical challenges and solutions.Therefore,recent MD studies on shale oil res-ervoirs were summarized and analyzed.Firstly,the applicability of force fields and ensembles of MD in shale reservoirs with different reservoir conditions and fluid properties was discussed.Subsequently,the calculation methods and application examples of MD parameters characterizing various properties of fluids at the microscale were summarized.Then,the application of MD simulation in the study of shale oil occurrence characteristics,flow behavior,and EOR mechanisms was reviewed,along with the elucidation of corresponding micro-mechanisms.Moreover,influencing factors of pore structure,wall properties,reservoir conditions,fluid components,injection/production parameters,formation water,and inorganic salt ions were analyzed,and some new conclusions were obtained.Finally,the main challenges associated with the application of MD simulations to shale oil reservoirs were discussed,and reasonable prospects for future MD research directions were proposed.The purpose of this review is to provide theoretical basis and methodological support for applying MD simulation to study shale oil reservoirs.展开更多
基金supported by Macao Science and Technology Development Fund,Macao SAR,China(Grant No.:0043/2023/AFJ)the National Natural Science Foundation of China(Grant No.:22173038)Macao Polytechnic University,Macao SAR,China(Grant No.:RP/FCA-01/2022).
文摘Accurate prediction of molecular properties is crucial for selecting compounds with ideal properties and reducing the costs and risks of trials.Traditional methods based on manually crafted features and graph-based methods have shown promising results in molecular property prediction.However,traditional methods rely on expert knowledge and often fail to capture the complex structures and interactions within molecules.Similarly,graph-based methods typically overlook the chemical structure and function hidden in molecular motifs and struggle to effectively integrate global and local molecular information.To address these limitations,we propose a novel fingerprint-enhanced hierarchical graph neural network(FH-GNN)for molecular property prediction that simultaneously learns information from hierarchical molecular graphs and fingerprints.The FH-GNN captures diverse hierarchical chemical information by applying directed message-passing neural networks(D-MPNN)on a hierarchical molecular graph that integrates atomic-level,motif-level,and graph-level information along with their relationships.Addi-tionally,we used an adaptive attention mechanism to balance the importance of hierarchical graphs and fingerprint features,creating a comprehensive molecular embedding that integrated hierarchical mo-lecular structures with domain knowledge.Experiments on eight benchmark datasets from MoleculeNet showed that FH-GNN outperformed the baseline models in both classification and regression tasks for molecular property prediction,validating its capability to comprehensively capture molecular informa-tion.By integrating molecular structure and chemical knowledge,FH-GNN provides a powerful tool for the accurate prediction of molecular properties and aids in the discovery of potential drug candidates.
文摘Molecular recognition of bioreceptors and enzymes relies on orthogonal interactions with small molecules within their cavity. To date, Chinese scientists have developed three types of strategies for introducing active sites inside the cavity of macrocyclic arenes to better mimic molecular recognition of bioreceptors and enzymes.The editorial aims to enlighten scientists in this field when they develop novel macrocycles for molecular recognition, supramolecular assembly, and applications.
基金supported by the National Key Research and Development Program of China(No.2024YFC3506900)Science and Technology Program of Tianjin(No.24ZXZSSS00460)Special Project for Technological Innovation in New Productive Forces of Modern Chinese Medicines(No.24ZXZKSY00010)。
文摘Due to its synergistic effects and reduced side effects,combination therapy has become an important strategy for treating complex diseases.In traditional Chinese medicine(TCM),the“monarch,minister,assistant,envoy”compatibilities theory provides a systematic framework for drug compatibility and has guided the formation of a large number of classic formulas.However,due to the complex compositions and diverse mechanisms of action of TCM,it is difficult to comprehensively reveal its potential synergistic patterns using traditional methods.Synergistic prediction based on molecular compatibility theory provides new ideas for identifying combinations of active compounds in TCM.Compared to resource-intensive traditional experimental methods,artificial intelligence possesses the ability to mine synergistic patterns from multi-omics and structural data,providing an efficient means for modeling and optimizing TCM combinations.This paper systematically reviews the application progress of AI in the synergistic prediction of TCM active compounds and explores the challenges and prospects of its application in modeling combination relationships,thereby contributing to the modernization of TCM theory and methodological innovation.
文摘Background:In this present study,we have screened major phytoconstituents of Nilavembu Kudineer against critical COVID-19 target proteins that cause severe pneumonia globally.In addition,a human receptor protein that facilitates viral entry into the host cell was also targeted.Methods:Phytoconstituents derived from Nilavembu Kudineer formulation were docked against 12 major proteins,which help viral entry,viral proliferation,and a human receptor facilitate the viral entry into the host cells.The major metabolites of Nilavembu Kudineer were retrieved based on literature from the PubChem database.The docked complex was subjected to MD simulation studies to verify its binding mode and the stability of the interactions.The binding energy analysis was performed to estimate the binding affinity between the compounds and their respective receptors using MM/GBSA.Results:Docking studies have shown that three major plants in the polyherbal formulation,Andrographis paniculata,Mollugo cerviana,and Zingiber officinale,have 14 potential compounds that have better binding affinity against COVID-19 proteins and their host receptor protein.MD studies and binding energy calculations also confirmed that these compounds possess better stability and strong binding energy with these proteins.Conclusion:In silico analyses suggest that phytoconstituents from Nilavembu Kudineer possess promising multi-target antiviral activity against COVID-19.These findings provide a rationale for further experimental studies to validate their therapeutic potential for the treatment of COVID-19.
基金Supported by the Ministry of Higher Education(Malaysia)(No.FRGS/1/2023/SKK15/IMU/01/1)International Medical University[No.PHMS I-2023(01)].
文摘Glaucoma,a degenerative optic neuropathy,causes retinal ganglion cell(RGC)apoptosis and irreversible vision loss.Current therapies often fail to stop disease progression despite lowering intraocular pressure,the main risk factor.Thus,neuroprotective strategies have gained interest.We performed a bibliometric analysis to determine global publishing trends and relationships among prolific authors,publications,institutions,funding agencies,and journals.We also analyzed author keywords to identify research hotspots in glaucoma neuroprotection.Further,based on keyword analysis,we reviewed most recent literature to understand mechanistic pathways underlying glaucomarelated pathophysiological responses leading to RGC loss.Bibliographic data were sourced from Scopus.Basic bibliographic features were characterized using Scopus’s functions.VOSviewer was used for mapping and visualizing bibliometric networks.The analysis included trends in publications since 2000,the most prolific countries,institutions,authors,and the strength of their linkages.A significant increase in publication output over the past two decades was noted.The United States leads in funding support,research output,and citation links,followed by China and the UK.Among the top 10 most cited authors,three are from Japanese institutions.Keyword analysis shows a focus on molecular targets related to ischemia,excitotoxicity,inflammation,and oxidative stress,with fewer emerging drug candidates and limited clinical trials.Based on the most recent literature,emerging molecular targets underlying these key pathophysiological mechanisms are summarized.In conclusion,while pathophysiology and molecular mechanisms are the current focus,there is not much progress in developing new drug candidates and conducting clinical trials.
基金supported by the National Natural Science Foundation of China(82374367)Jiangxi Provincial Natural Science Foundation(20242BAB26163,20232BAB206144)+4 种基金Jiangxi Province Key Laboratory of Traditional Chinese Medicine for Cardiovascular Diseases(20242BCC32096)NATCM’s Project of High-level Construction of Key TCM Disciplines(zyyzdxk-2023113)Project of Key Discipline Construction Fund of Jiangxi University of Chinese Medicine(2023jzzdxk032)Science and Technology Innovation Team Development Program of Jiangxi University of Chinese Medicine(CXTD22011)National Traditional Chinese Medicine Inheritance and Innovation Center Construction Project.
文摘Background:Atherosclerosis(AS),the primary pathological foundation of cardiovascular diseases,is characterized by intricate processes including inflammation,lipid metabolism disorders,and pyroptosis.While the traditional Chinese medicine compound Dingxin Recipe(DXR)has demonstrated definitive clinical efficacy in treating AS,its therapeutic mechanisms remain unclear.This study employed an integrated approach combining network pharmacology,molecular docking,and molecular dynamics simulations(MDS)to investigate DXR’s anti-AS mechanisms.Methods:Active ingredients and targets of DXR were identified and screened using databases such as GeneCards,OMIM,and TCMSP.An“ingredient-target-disease”network was constructed to visualize these interactions.Molecular docking was utilized to assess the binding affinity between key ingredients and their respective targets.Additionally,MDS were conducted to analyze the stability of these complexes,providing robust evidence for further clinical applications and in-depth research.Results:Through network pharmacology analysis,we identified 99 active drug components,934 gene targets,and 1463 disease targets associated with DXR.Protein-protein interaction analysis revealed central regulatory nodes.Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that these components primarily modulate processes such as inflammatory response and transcription factor activation,and are closely linked to the AGERAGE signaling pathway,lipid metabolism,and atherosclerosis pathways.Molecular docking confirmed strong binding potential between the components and their targets,while MDS further validated the stability of these interactions.Conclusion:This study elucidates that the active ingredients in DXR alleviate AS by mitigating inflammatory responses and inhibiting pyroptosis through the suppression of inflammatory factor release.These findings provide a scientific foundation for the clinical application of DXR in AS treatment.
基金The Gansu Province University Industrial Support Plan(Grant No.2023CYZC-05)the Cuiying Technology Innovation Project of Lanzhou University Second Hospital(Grant No.CY2022-MS-B04)+1 种基金the Doctoral Students Training Research Fund of Lanzhou University Second Hospital(Grant No.YJS-BD-32)the Gansu Province Drug Regulatory Science Research Project in 2024(Grant No.2024GSMPA032).
文摘Euphorbia helioscopia,a natural plant recognized for its anti-tumor properties,has been extensively investigated in various cancers.However,its therapeutic potential in gastric cancer with positive lymph node metastasis remains underexplored.This study aimed to elucidate the role of E.helioscopia in treating gastric cancer with lymph node metastasis using an integrative approach that combined network pharmacology,molecular docking,and molecular dynamics simulations.Initially,shared target data between E.helioscopia and gastric cancer with positive lymph node metastasis were identified and systematically analyzed.Subsequently,molecular docking was conducted to validate the interactions between key components and targets.Finally,molecular dynamics simulations were employed,with binding free energy calculations performed using the MM-PBSA algorithm.The findings revealed that the primary bioactive compounds of E.helioscopia in this context included quercetin and luteolin,targeting core molecules such as EGFR and MMP9.Key pathways implicated in its mechanism of action included resistance to EGFR tyrosine kinase inhibitors,among others.Molecular docking demonstrated robust binding affinity between the active compounds and critical targets,with molecular dynamics and binding free energy analyses highlighting a particularly stable interaction between luteolin and MMP9.In conclusion,E.helioscopia exhibited a multi-component,multi-target,and multi-pathway therapeutic profile in treating gastric cancer with positive lymph node metastasis.These findings offered valuable theoretical insights supporting its potential clinical application in oncology.
基金Research Grants of Senior Research Fellowship in favor of first author(Gloak Majumdar)from Council of Scientific and Industrial Research(CSIR,New Delhi,Government of India)(CSIR-SRF)with Award No.09/1151/(0008)2020-EMR-I.
文摘Objective To evaluate the antibacterial potential of bioactive compounds from Persicaria hydropiper(L.)(P.hydropiper)against bacterial virulence proteins through molecular docking(MD)and experimental validation.Methods Six bioactive compounds from P.hydropiper were investigated:catechin(CAT1),hyperin(HYP1),ombuin(OMB1),pinosylvin(PSV1),quercetin 3-sulfate(QSF1),and scutellarein(SCR1).Their binding affinities and potential binding pockets were assessed through MD against four bacterial target proteins with Protein Data Bank identifiers(PDB IDs):topoisomerase IV from Escherichia coli(E.coli)(PDB ID:3FV5),Staphylococcus aureus(S.aureus)gyrase ATPase binding domain(PDB ID:3U2K),CviR from Chromobacterium violaceum(C.violaceum)(PDB ID:3QP1),and glycosyl hydrolase from Pseudomonas aeruginosa(P.aeruginosa)(PDB ID:5BX9).Molecular dynamics simulations(MDS)were performed on the most promising compound-protein complexes for 50 nanoseconds(ns).Drug-likeness was evaluated using Lipinski's Rule of Five(RO5),followed by absorption,distribution,metabolism,excretion,and toxicity(ADMET)analysis using SwissADME and pkCSM web servers.Antibacterial activity was evaluated through disc diffusion assays,testing both individual compounds and combinations with conventional antibiotics[cefotaxime(CTX1,30μg/disc),ceftazidime(CAZ1,30μg/disc),and piperacillin(PIP1,100μg/disc)].Results MD revealed strong binding affinity(ranging from-9.3 to-5.9 kcal/mol)for all compounds,with CAT1 showing exceptional binding to 3QP1(-9.3 kcal/mol)and 5BX9(-8.4 kcal/mol).MDS confirmed the stability of CAT1-protein complexes with binding free energies of-84.71 kJ/mol(5BX9-CAT1)and-95.59 kJ/mol(3QP1-CAT1).Five compounds(CAT1,SCR1,PSV1,OMB1,and QSF1)complied with Lipinski's RO5 and showed favorable ADMET profiles.All compounds were non-carcinogenic,with CAT1 classified in the lowest toxicity class(VI).In antibacterial assays,CAT1 demonstrated significant activity against both gram-positive bacteria[Streptococcus pneumoniae(S.pneumoniae),S.aureus,and Bacillus cereus(B.cereus)][zone diameter of inhibition(ZDI):10-22 mm]and gram-negative bacteria[Acinetobacter baumannii(A.baumannii),E.coli,and P.aeruginosa](ZDI:14-27 mm).Synergistic effects were observed when CAT1 was combined with antibiotics and the growth inhibitory indices(GII)was 0.69-1.00.Conclusion P.hydropiper bioactive compounds,particularly CAT1,show promising antibacterial potential through multiple mechanisms,including direct inhibition of bacterial virulence proteins and synergistic activity with conventional antibiotics.The favorable pharmacological properties and low toxicity profiles support their potential development as therapeutic agents against bacterial infections.
文摘Porous molecular sieve catalysts,including aluminosilicate zeolites and silicoaluminophosphate(SAPO)molecular sieves,have found widespread use in heterogeneous catalysis and are expected to play a key role in advancing carbon neutrality and sustainable development.Given the ubiquitous presence of water during catalyst synthesis,storage,and application,the interactions between water and molecular sieves as well as their consequent effects on frameworks and catalytic reactions have attracted considerable attention.These effects are inherently complex and highly dependent on various factors such as temperature,water phase,and partial pressure.In this review,we provide a comprehensive overview of the current understanding of water-molecular sieve interactions and their roles in catalysis,based on both experimental and theoretical calculation results.Special attention is paid to water-induced reversible and irreversible structural changes in aluminosilicate and SAPO frameworks at the atomic level,underscoring the dynamic and labile nature of these frameworks in water environments.The influence of water on catalytic performance and reaction kinetics in molecular sieve-catalyzed reactions is discussed from two perspectives:(1)its participation in reaction through hydrogen bonding interactions,such as competitive adsorption at active sites,stabilization of ground and transition states,and proton transfer bridge;(2)its role as a direct reactant forming new species via reactions with other vip molecules.Recent advancements in this area provide valuable insights for the rational design and optimization of catalysts for water-involved reactions.
基金supported by the National Natural Science Foundation of China(T2188102)Hangzhou Institute of Medicine(2024ZZBS02,Hangzhou,China).
文摘Molecular medicine,which delves into the intricacies of biomolecular structure,function,and role,is pivotal for advancing precise diagnostics and personalized treatment.Nucleic acids,a class of star functional molecules,are notable for their versatile applications in molecular diagnostics,gene therapy,and drug development.Therefore,in this study,we review the extensive use of nucleic acid aptamers in medicinal practice.Furthermore,the expanding field of molecular medicine has catalyzed advancements in traditional Chinese medicine(TCM),as evidenced by scientific endeavors to integrate modern technologies.Therefore,TCM has experienced rapid modernization by leveraging artificial intelligence,nucleic acid molecular medicine,and bioelectronic medicine.
基金supported by the Nanxun Scholars Program for Young Scholars of ZJWEU(No.RC2023021315)the start-up funding for Scientific Research for High-level Talents(No.88106324004)the National Natural Science Foundation of China(No.62304070).
文摘Silicon-based materials are considered as the next generation anode to replace graphite due to their low cost and ultra-high theoretical capacity.However,significant volume expansion and contraction occur during charging and discharging processes,leading to the instability of electrode structure and susceptibility to peeling and damage,limiting its application.Constructing controllable molecular artificial solid electrolyte interphase(CMASEI)is an effective approach to address the commercialization of silicon-based anode materials[1].Improving the performance of silicon-based anodes through CMASEI is a multifaceted outcome.
基金Project supported by the National Key Research and Development Program of China (Grant Nos. 2019YFA0708502 and 2023YFA1406200)the National Natural Science Foundation of China (Grant No. 22022101)。
文摘Bulk modulus is a constant that measures the incompressibility of materials, which can be obtained in high pressure experiment by fitting the equations of state(EOS), like third-order Birch–Murnaghan EOS(BM EOS) and Vinet EOS. Bulk modulus reflects the intermolecular interaction inside molecular crystals, making it useful for researchers to design novel high pressure materials. This review systematically examines bulk moduli of various molecular crystals, including rare-gas solids, di-atom and triplet-atom molecules, saturated organic molecules, and aromatic organic crystals. Comparisons with ionic crystals are presented, along with an analysis of connections between bulk modulus and crystal structures.
基金Supported by the National Human Genetic Resources Sharing Service Platform,No.PT-2024-0303Qingdao Medical and Health Research Guidance Project,No.2023-WJZD202.
文摘Colorectal cancer(CRC)ranks among the top causes of cancer-related fatalities globally.Recent progress in genomics,proteomics,and bioinformatics has greatly improved our comprehension of the molecular underpinnings of CRC,paving the way for targeted therapies and immunotherapies.Nonetheless,obstacles such as tumor heterogeneity and drug resistance persist,hindering advancements in treatment efficacy.In this context,the integration of artificial intelligence(AI)and organoid technology presents promising new avenues.AI can analyze genetic and clinical data to forecast disease risk,prognosis,and treatment responses,thereby expediting drug development and tailoring treatment plans.Organoids replicate the genetic traits and biological behaviors of tumors,acting as platforms for drug testing and the formulation of personalized treatment approaches.Despite notable strides in CRC research and treatment-from genetic insights to therapeutic innovations-numerous challenges endure,including the intricate tumor microen-vironment,tumor heterogeneity,adverse effects of immunotherapies,issues related to AI data quality and privacy,and the need for standardization in organoid culture.Future initiatives should concentrate on clarifying the pathogenesis of CRC,refining AI algorithms and organoid models,and creating more effective therapeutic strategies to alleviate the global impact of CRC.
文摘Pancreatic cancer, particularly pancreatic ductal adenocarcinoma(PDAC), is one of the most lethal malignancies,which is characterized by a complex tumor microenvironment(TME) that fosters immune evasion and treatment resistance. Recent genomic advancements have unveiled diverse molecular subtypes of PDAC, providing insights into targeted therapies and precision medicine. This review synthesizes the current understanding of PDAC's molecular characterization and immunosuppressive TME, as well as emerging therapeutic strategies, including innovative approaches targeting key molecular pathways such as kirsten rat sarcoma viral oncogene homolog(KRAS), epidermal growth factor receptor(EGFR), and immune checkpoints. Despite advances, challenges remain in overcoming treatment resistance and inherent heterogeneity of pancreatic cancer subtypes. We highlight the need for multidisciplinary collaboration to enhance early diagnosis and develop individualized therapeutic protocols, paving the way for improving the outcomes of this aggressive cancer. This integrated perspective underscores the urgency of transforming the innovative research into pancreatic cancer management.
基金funded by the United Arab Emirates UniversityResearch Officegrant number 12F041 to KM。
文摘Advancements in molecular approaches have been utilized to breed crops with a wide range of economically valuable traits to develop superior cultivars.This review provides a concise overview of modern breakthroughs in molecular plant production.Genotyping and high-throughput phenotyping methods for predictive plant breeding are briefly discussed.In this study,we explore contemporary molecular breeding techniques for producing desirable crop varieties.These techniques include cisgenesis,clustered regularly interspaced short palindromic repeat(CRISPR/Cas9)gene editing,haploid induction,and de novo domestication.We examine the speed breeding approach-a strategy for cultivating plants under controlled conditions.We further highlight the significance of modern breeding technologies in efficiently utilizing agricultural resources for crop production in urban areas.The deciphering of crop genomes has led to the development of extensive DNA markers,quantitative trait loci(QTLs),and pangenomes associated with various desirable crop traits.This shift to the genotypic selection of crops considerably expedites the plant breeding process.Based on the plant population used,the connection between genotypic and phenotypic data provides several genetic elements,including genes,markers,and alleles that can be used in genomic breeding and gene editing.The integration of speed breeding with genomic-assisted breeding and cutting-edge genome editing tools has made it feasible to rapidly manipulate and generate multiple crop cycles and accelerate the plant breeding process.Breakthroughs in molecular techniques have led to substantial improvements in modern breeding methods.
基金supported by the Yonsei University graduate school Department of Integrative Biotechnology.
文摘Recently,diffusion models have emerged as a promising paradigm for molecular design and optimization.However,most diffusion-based molecular generative models focus on modeling 2D graphs or 3D geom-etries,with limited research on molecular sequence diffusion models.The International Union of Pure and Applied Chemistry(IUPAC)names are more akin to chemical natural language than the simplified molecular input line entry system(SMILES)for organic compounds.In this work,we apply an IUPAC-guided conditional diffusion model to facilitate molecular editing from chemical natural language to chemical language(SMILES)and explore whether the pre-trained generative performance of diffusion models can be transferred to chemical natural language.We propose DiffIUPAC,a controllable molecular editing diffusion model that converts IUPAC names to SMILES strings.Evaluation results demonstrate that our model out-performs existing methods and successfully captures the semantic rules of both chemical languages.Chemical space and scaffold analysis show that the model can generate similar compounds with diverse scaffolds within the specified constraints.Additionally,to illustrate the model’s applicability in drug design,we conducted case studies in functional group editing,analogue design and linker design.
基金supported by the open research fund of Songshan Lake Materials Laboratory(2023SLABFN18)the Anhui Provincial Natural Science Foundation(2308085QB46)+2 种基金the Scientific Research Foundation of Education Department of Anhui Province of China(2022AH010025,2023AH051109)the Key Research and Development Program of Anhui Province of China(2022l07020011)The open research fund of the Anhui Key Lab of Metal Material and Processing(RZ2200002901)。
文摘Aqueous zinc-ion batteries(AZIBs)have regained interest due to their inherent safety and costeffectiveness.However,the zinc anode is notorious for side reactions and dendrite growth,which plague the practical application of AZIBs.Adjusting the interfacial pH to reduce the by-products has been proven to be effective in protecting the zinc anode.Nevertheless,the dynamic regulation of the inherently unstable zinc interface during prolonged cycling remains a significant challenge.Herein,zwitterionic N-tris(hydroxymethyl)methylglycine(TMG)integrated with negative-COO^(-)and positive NH_(2)^(+)groups is proposed to stabilize the Zn anode and extend the lifespan as a self-regulating interfacial additive.The anionic portion serves as a trapping site to balance the interfacial pH and thus mitigate the unintended side reactions.Simultaneously,the NH_(2)^(+)cations are anchored on the zinc surface,forming a water-shielding,zincophilic molecular layer that guides three-dimensional diffusion and promotes uniform electro-deposition.Thus,an average plating efficiency of 99.74%over 3300 cycles at a current density of2 mA cm^(-2)is achieved.Notably,the TMG additive actualizes ultralong life in Zn‖Zn symmetrical cells(5500 h,exceeding 229 days,1 mA cm^(-2)/1 mA h cm^(-2)),and enables the Zn‖I_(2)cells to reach capacity retention rate of 89.4%after 1000 cycles at 1 A g^(-1).
基金supported by the National Key R&D Program of China(No.2022YFC3502005)the three-year Action Plan for Shanghai TCM Development and Inheritance Program[No.ZY(2021-2023)-0401]the National Natural Science Foundation of China(No.82104521)。
文摘Traditional Chinese medicine formula(TCMF)represents a fundamental component of Chinese medical practice,incorporating medical knowledge and practices from both Han Chinese and various ethnic minorities,while providing comprehensive insights into health and disease.The foundation of TCMF lies in its holistic approach,manifested through herbal compatibility theory,which has emerged from extensive clinical experience and evolved into a highly refined knowledge system.Within this framework,Chinese herbal medicines exhibit intricated characteristics,including multi-component interactions,diverse target sites,and varied biological pathways.These complexities pose significant challenges for understanding their molecular mechanisms.Contemporary advances in artificial intelligence(AI)are reshaping research in traditional Chinese medicine(TCM),offering immense potential to transform our understanding of the molecular mechanisms underlying TCMFs.This review explores the application of AI in uncovering these mechanisms,highlighting its role in compound absorption,distribution,metabolism,and excretion(ADME)prediction,molecular target identification,compound and target synergy recognition,pharmacological mechanisms exploration,and herbal formula optimization.Furthermore,the review discusses the challenges and opportunities in AI-assisted research on TCMF molecular mechanisms,promoting the modernization and globalization of TCM.
基金funded by the National Key Research and Development Program of China(No.2022YFC2804101)the Guangdong Provincial Key R&D Program(No.2023B1111050011)+2 种基金the Guangdong Basic and Applied Basic Research Foundation(No.2023A1515010432)the Guangzhou Basic and Applied Basic Research Foundation(No.202201010305)the High-Level Talents Special Program of Zhejiang(No.2022R52036)。
文摘Guided by molecular networking,nine novel curvularin derivatives(1-9)and 16 known analogs(10-25)were isolated from the hydrothermal vent sediment fungus Penicillium sp.HL-50.Notably,compounds 5-7 represented a hybrid of curvularin and purine.The structures and absolute configurations of compounds 1-9 were elucidated via nuclear magnetic resonance(NMR)spectroscopy,X-ray diffraction,electronic circular dichroism(ECD)calculations,^(13)C NMR calculation,modified Mosher's method,and chemical derivatization.Investigation of anti-inflammatory activities revealed that compounds 7-9,11,12,14,15,and 18 exhibited significant suppressive effects against lipopolysaccharide(LPS)-induced nitric oxide(NO)production in murine macrophage RAW264.7 cells,with IC_(50)values ranging from 0.44 to 4.40μmol·L^(-1).Furthermore,these bioactive compounds were found to suppress the expression of inflammation-related proteins,including inducible NO synthase(i NOS),cyclooxygenase-2(COX-2),NLR family pyrin domain-containing protein 3(NLRP3),and nuclear factor kappa-B(NF-κB).Additional studies demonstrated that the novel compound 7 possessed potent antiinflammatory activity by inhibiting the transcription of inflammation-related genes,downregulating the expression of inflammation-related proteins,and inhibiting the release of inflammatory cytokines,indicating its potential application in the treatment of inflammatory diseases.
基金supported by the National Natural Science Foundation of China(52304021,52104022,52204031)the Natural Science Foundation of Sichuan Province(2022NSFSC0205,2024NSFSC0201,2023NSFSC0947)the National Science and Technology Major Projects of China(2017ZX05049006-010).
文摘The global energy demand is increasing rapidly,and it is imperative to develop shale hydrocarbon re-sources vigorously.The prerequisite for enhancing the exploitation efficiency of shale reservoirs is the systematic elucidation of the occurrence characteristics,flow behavior,and enhanced oil recovery(EOR)mechanisms of shale oil within commonly developed nanopores.Molecular dynamics(MD)technique can simulate the occurrence,flow,and extraction processes of shale oil at the nanoscale,and then quantitatively characterize various fluid properties,flow characteristics,and action mechanisms under different reservoir conditions by calculating and analyzing a series of MD parameters.However,the existing review on the application of MD simulation in shale oil reservoirs is not systematic enough and lacks a summary of technical challenges and solutions.Therefore,recent MD studies on shale oil res-ervoirs were summarized and analyzed.Firstly,the applicability of force fields and ensembles of MD in shale reservoirs with different reservoir conditions and fluid properties was discussed.Subsequently,the calculation methods and application examples of MD parameters characterizing various properties of fluids at the microscale were summarized.Then,the application of MD simulation in the study of shale oil occurrence characteristics,flow behavior,and EOR mechanisms was reviewed,along with the elucidation of corresponding micro-mechanisms.Moreover,influencing factors of pore structure,wall properties,reservoir conditions,fluid components,injection/production parameters,formation water,and inorganic salt ions were analyzed,and some new conclusions were obtained.Finally,the main challenges associated with the application of MD simulations to shale oil reservoirs were discussed,and reasonable prospects for future MD research directions were proposed.The purpose of this review is to provide theoretical basis and methodological support for applying MD simulation to study shale oil reservoirs.
