Background:In-feed antibiotics are being phased out in livestock production worldwide.Alternatives to antibiotics are urgently needed to maintain animal health and production performance.Host defense peptides(HDPs)are...Background:In-feed antibiotics are being phased out in livestock production worldwide.Alternatives to antibiotics are urgently needed to maintain animal health and production performance.Host defense peptides(HDPs)are known for their broad-spectrum antimicrobial and immunomodulatory capabilities.Enhancing the synthesis of endogenous HDPs represents a promising antibiotic alternative strategy to disease control and prevention.Methods:To identify natural products with an ability to stimulate the synthesis of endogenous HDPs,we performed a high-throughput screening of 1261 natural products using a newly-established stable luciferase reporter cell line known as IPEC-J2/pBD3-luc.The ability of the hit compounds to induce HDP genes in porcine IPEC-J2 intestinal epithelial cells,3D4/31 macrophages,and jejunal explants were verified using RT-qPCR.Augmentation of the antibacterial activity of porcine 3D4/31 macrophages against a Gram-negative bacterium(enterotoxigenic E.coli)and a Gram-positive bacterium(Staphylococcus aureus)were further confirmed with four selected HDP-inducing compounds.Results:A total of 48 natural products with a minimum Z-score of 2.0 were identified after high-throughput screening,with 21 compounds giving at least 2-fold increase in luciferase activity in a follow-up dose-response experiment.Xanthohumol and deoxyshikonin were further found to be the most potent in inducing pBD3 mRNA expression,showing a minimum 10-fold increase in IPEC-J2,3D4/31 cells,and jejunal explants.Other compounds such as isorhapontigenin and calycosin also enhanced pBD3 mRNA expression by at least 10-fold in both IPEC-J2 cells and jejunal explants,but not 3D4/31 cells.In addition to pBD3,other porcine HDP genes such as pBD2,PG1-5,and pEP2C were induced to different magnitudes by xanthohumol,deoxyshikonin,isorhapontigenin,and calycosin,although clear gene-and cell type-specific patterns of regulation were observed.Desirably,these four compounds had a minimum effect on the expression of several representative inflammatory cytokine genes.Furthermore,when used at HDP-inducing concentrations,these compounds showed no obvious direct antibacterial activity,but significantly augmented the antibacterial activity of 3D4/31 macrophages(P<0.05)against both Gram-negative and Gram-positive bacteria.Conclusions:Our results indicate that these newly-identified natural HDP-inducing compounds have the potential to be developed as novel alternatives to antibiotics for prophylactic and therapeutic treatment of infectious diseases in livestock production.展开更多
Single atomic catalysts(SACs),especially metal-nitrogen doped carbon(M-NC)catalysts,have been extensively explored for the electrochemical oxygen reduction reaction(ORR),owing to their high activity and atomic utiliza...Single atomic catalysts(SACs),especially metal-nitrogen doped carbon(M-NC)catalysts,have been extensively explored for the electrochemical oxygen reduction reaction(ORR),owing to their high activity and atomic utilization efficiency.However,there is still a lack of systematic screening and optimization of local structures surrounding active centers of SACs for ORR as the local coordination has an essential impact on their electronic structures and catalytic performance.Herein,we systematic study the ORR catalytic performance of M-NC SACs with different central metals and environmental atoms in the first and second coordination sphere by using density functional theory(DFT)calculation and machine learning(ML).The geometric and electronic informed overpotential model(GEIOM)based on random forest algorithm showed the highest accuracy,and its R^(2) and root mean square errors(RMSE)were 0.96 and 0.21,respectively.30 potential high-performance catalysts were screened out by GEIOM,and the RMSE of the predicted result was only 0.12 V.This work not only helps us fast screen high-performance catalysts,but also provides a low-cost way to improve the accuracy of ML models.展开更多
A stably transfected CHO cell line coexpressing G551D-CFTR and iodide-sensitive yellow fluorescent protein mutant EYFP-H148Q-I152L was successfully established and used as assay model to identify small-molecule activa...A stably transfected CHO cell line coexpressing G551D-CFTR and iodide-sensitive yellow fluorescent protein mutant EYFP-H148Q-I152L was successfully established and used as assay model to identify small-molecule activators of G551D-CFTR chloride channel from 100000 diverse combinatorial compounds by high throughput screening on a customized Beckman robotic system. A bicyclooctane compound was identified to activate G551D-CFTR chloride channel with high-affinity(K d=1.8 μmol/L). The activity of the bicyclooctane compound is G551D-CFTR-specific, reversible and non-toxic. The G551D-CFTR activator may be useful as a tool to study the mutant G551D-CFTR chloride channel structure and transport properties and as a candidate drug to cure cystic fibrosis caused by G551D-CFTR mutation.展开更多
A novel solid phase organic synthesis resin was synthesized for combinatorial high-throughput screening,which based on FTIR spectra self-encoding functional resin technology. A new deconvolution strategy termed positi...A novel solid phase organic synthesis resin was synthesized for combinatorial high-throughput screening,which based on FTIR spectra self-encoding functional resin technology. A new deconvolution strategy termed position encoding deconvolution had illustrated and was compared with some popular combinatorial deconvolution strategies in efficiency and information content. The mimic high throughput screening of hexapeptide library successfully proved the applying of the self-encoding functional resin technology and the position encoding deconvolution strategy.展开更多
The glycine-to-aspartic acid missense mutation at the codon 551(G551D) of the cystic fibrosis transmembrane conductance regulator(CFTR) is one of the five most frequent cystic fibrosis(CF) mutations associated with a ...The glycine-to-aspartic acid missense mutation at the codon 551(G551D) of the cystic fibrosis transmembrane conductance regulator(CFTR) is one of the five most frequent cystic fibrosis(CF) mutations associated with a severe CF phenotype. To explore the feasibility of pharmacological correction of disrupted activation of CFTR chloride channel caused by G551D mutation, we developed a halide-sensitive fluorescence miniassay for G551D-CFTR in Fisher rat thyroid(FRT) epithelial cells for the discovery of novel activators of G551D-CFTR. A class of bicyclooctane small molecule compounds that efficiently stimulate G551D-CFTR chloride channel activity was identified by high throughput screening via the FRT cell-based assay. This class of compounds selectively activates G551D-CFTR with a high affinity, whereas little effect of the compounds on wildtype CFTR can be seen. The discovery of a class of bicyclooctane G551D-CFTR activators will permit the analysis of structure-activity relationship of the compounds to identify ideal leads for in vivo therapeutic studies.展开更多
In this article, we introduce the system of high throughput screening (HTS). Its role in new drug study and current development is described. The relationship between research achievements of genome study and new type...In this article, we introduce the system of high throughput screening (HTS). Its role in new drug study and current development is described. The relationship between research achievements of genome study and new type screening model of new drugs is emphasized. The personal opinions of current problems about HTS study in China are raised.展开更多
Background Early embryo development plays a pivotal role in determining pregnancy outcomes,postnatal development,and lifelong health.Therefore,the strategic selection of functional nutrients to enhance embryo developm...Background Early embryo development plays a pivotal role in determining pregnancy outcomes,postnatal development,and lifelong health.Therefore,the strategic selection of functional nutrients to enhance embryo development is of paramount importance.In this study,we established a stable porcine trophectoderm cell line expressing dual fluorescent reporter genes driven by the CDX2 and TEAD4 gene promoter segments using lentiviral transfection.Results Three amino acid metabolites—kynurenic acid,taurine,and tryptamine—met the minimum z-score criteria of 2.0 for both luciferase and Renilla luciferase activities and were initially identified as potential metabolites for embryo development,with their beneficial effects validated by qPCR.Given that the identified metabolites are closely related to methionine,arginine,and tryptophan,we selected these three amino acids,using lysine as a standard,and employed response surface methodology combined with our high-throughput screening cell model to efficiently screen and optimize amino acid combination conducive to early embryo development.The optimized candidate amino acid system included lysine(1.87 mmol/L),methionine(0.82 mmol/L),tryptophan(0.23 mmol/L),and arginine(3 mmol/L),with the ratio of 1:0.43:0.12:1.60.In vitro experiments confirmed that this amino acid system enhances the expression of key genes involved in early embryonic development and improves in vitro embryo adhesion.Transcriptomic analysis of blastocysts suggested that candidate amino acid system enhances early embryo development by regulating early embryonic cell cycle and differentiation,as well as improving nutrient absorption.Furthermore,based on response surface methodology,400 sows were used to verify this amino acid system,substituting arginine with the more cost-effective N-carbamoyl glutamate(NCG),a precursor of arginine.The optimal dietary amino acid requirement was predicted to be 0.71%lysine,0.32%methionine,0.22%tryptophan,and 0.10%NCG for sows during early gestation.The optimized amino acid system ratio of the feed,derived from the peripheral release of essential amino acids,was found to be 1:0.45:0.13,which is largely consistent with the results obtained from the cell model optimization.Subsequently,we furtherly verified that this optimal dietary amino acid system significantly increased total litter size,live litter size and litter weight in sows.Conclusions In summary,we successfully established a dual-fluorescent high-throughput screening cell model for the efficient identification of potential nutrients that would promote embryo development and implantation.This innovative approach overcomes the limitations of traditional amino acid nutrition studies in sows,providing a more effective model for enhancing reproductive outcomes.展开更多
While the human genome is pervasively transcribed,<2%of the human genome is transcribed into protein-coding mRNAs,leaving most of the transcripts as noncoding RNAs,such as microRNAs and long-noncoding RNAs(lncRNAs)...While the human genome is pervasively transcribed,<2%of the human genome is transcribed into protein-coding mRNAs,leaving most of the transcripts as noncoding RNAs,such as microRNAs and long-noncoding RNAs(lncRNAs),which are critical components of epigenetic regulation.lncRNAs are emerging as critical regulators of gene expression and genomic stability.However,it remains largely unknown about how lncRNAs are regulated.Here,we develop a highly sensitive and dynamic reporter that allows us to identify and/or monitor negative modulators of lncRNA transcript levels in a high throughput fashion.Specifically,we engineer a fluorescent fusion protein by fusing three copies of the PEST destruction domain of mouse ornithine decarboxylase(MODC)to the C-terminal end of the codon-optimized bilirubin-inducible fluorescent protein,designated as dBiFP,and show that the dBiFP protein is highly destabilized,compared with the commonly-used eGFP protein.We further demonstrate that the dBiFP signal is effectively down-regulated when the dBiFP and mouse lncRNA H19 chimeric transcript is silenced by mouse H19-specific siRNAs.Therefore,our results strongly suggest that the dBiFP fusion protein may serve as a sensitive and dynamic transcript reporter to monitor the inhibition of lncRNAs by microRNAs,synthetic regulatory RNA molecules,RNA binding proteins,and/or small molecule inhibitors so that novel and efficacious inhibitors targeting the epigenetic circuit can be discovered to treat human diseases such as cancer and other chronic disorders.展开更多
Due to their immunomodulatory function,mesenchymal stromal cells(MSCs)are a promising therapeutic with the potential to treat neuroinflammation associated with neurodegenerative diseases.This function is mediated by s...Due to their immunomodulatory function,mesenchymal stromal cells(MSCs)are a promising therapeutic with the potential to treat neuroinflammation associated with neurodegenerative diseases.This function is mediated by secreted extracellular vesicles(MSC-EVs).Despite established safety,MSC clinical translation has been unsuccessful due to inconsistent clinical outcomes resulting from functional heterogeneity.Current approaches to mitigate functional heterogeneity include‘priming’MSCs with inflammatory signals to enhance function.However,comprehensive evaluation of priming and its effects on MSC-EV function has not been performed.Furthermore,clinical translation of MSC-EV therapies requires significant manufacturing scale-up,yet few studies have investigated the effects of priming in bioreactors.As MSC morphology has been shown to predict their immunomodulatory function,we screened MSC morphological response to an array of priming signals and evaluated MSC-EV identity and potency in response to priming in flasks and bioreactors.We identified unique priming conditions corresponding to distinct morphologies.These conditions demonstrated a range of MSC-EV preparation quality and lipidome,allowing us to discover a novel MSC-EV manufacturing condition,as well as gain insight into potential mechanisms of MSC-EV microglia modulation.Our novel screening approach and application of priming to MSC-EV bioreactor manufacturing informs refinement of larger-scale manufacturing and enhancement of MSC-EV function.展开更多
Alphaviruses,which contain a variety of mosquito-borne pathogens,are important pathogens of emerging/reemerging infectious diseases and potential biological weapons.Currently,no specific antiviral drugs are available ...Alphaviruses,which contain a variety of mosquito-borne pathogens,are important pathogens of emerging/reemerging infectious diseases and potential biological weapons.Currently,no specific antiviral drugs are available for the treatment of alphaviruses infection.For most highly pathogenic alphaviruses are classified as risk group-3 agents,the requirement of biosafety level 3(BSL-3)facilities limits the live virus-based antiviral study.To facilitate the antiviral development of alphaviruses,we developed a high throughput screening(HTS)platform based on a recombinant Semliki Forest virus(SFV)which can be manipulated in BSL-2 laboratory.Using the reverse genetics approach,the recombinant SFV and SFV reporter virus expressing eGFP(SFV-eGFP)were successfully rescued.The SFV-eGFP reporter virus exhibited robust eGFP expression and remained relatively stable after four passages in BHK-21 cells.Using a broad-spectrum alphavirus inhibitor ribavirin,we demonstrated that the SFV-eGFP can be used as an effective tool for antiviral study.The SFV-eGFP reporter virus-based HTS assay in a 96-well format was then established and optimized with a robust Z0 score.A section of reference compounds that inhibit highly pathogenic alphaviruses were used to validate that the SFV-eGFP reporter virus-based HTS assay enables rapid screening of potent broad-spectrum inhibitors of alphaviruses.This assay provides a safe and convenient platform for antiviral study of alphaviruses.展开更多
High throughput screening(HTS)is a widely used effective approach in genome-wide association and large scale protein expression studies,drug discovery,and biomedical imaging research.How to accurately identify candid...High throughput screening(HTS)is a widely used effective approach in genome-wide association and large scale protein expression studies,drug discovery,and biomedical imaging research.How to accurately identify candidate‘targets’or biologically meaningful features with a high degree of confidence has led to extensive statistical research in an effort to minimize both false-positive and false-negative rates.A large body of literature on this topic with in-depth statistical contents is available.We examine currently available statistical methods on HTS and aim to summarize some selected methods into a concise,easy-tofollow introduction for experimental biologists.展开更多
Since the mid-to-late 20th century,the scientific community has increasingly recognized that the rapid rise in atmospheric greenhouse gases,particularly CO_(2)from human activities,is the primary driver of global warm...Since the mid-to-late 20th century,the scientific community has increasingly recognized that the rapid rise in atmospheric greenhouse gases,particularly CO_(2)from human activities,is the primary driver of global warming.This escalation has led to pressing climate challenges,including sea-level rise and more frequent extreme weather events[1,2].Among the limited strategies available to mitigate CO_(2)emissions,carbon capture and storage have emerged as a key approach.To this end,various adsorbents—such as metalorganic frameworks(MOFs),zeolites,and carbon materials—have been developed for CO_(2)capture[3-6].展开更多
The mechanical properties of biological fluids serve as early indicators of disease,offering valuable insights into complex physiological and pathological processes.However,the existing technologies struggle to achiev...The mechanical properties of biological fluids serve as early indicators of disease,offering valuable insights into complex physiological and pathological processes.However,the existing technologies struggle to achieve high-throughput measurement,limiting their widespread applications in disease diagnosis.Here,we propose laser-emission vibrational microscopy of microdroplets for high-throughput measurement of the intrinsic mechanical properties of fluids.The microdroplet array supporting high Q-factor(104)whispering gallery modes(WGM)lasing was massively fabricated on a superhydrophobic surface with inkjet printing.Ultrasound was employed to actuate the mechanical vibrations of the microdroplets,and the vibration amplitude was quantified using time-resolved laser spectra.We found that the stimulus-response of the laser emission is strongly dependent on the liquid viscosity.Fast mapping of the microdroplets’viscosities was achieved by stage scanning.High-throughput screening of hyperlipidemia disease was also demonstrated by performing over 2000 measurements within 25 min.Thanks to the small volume of the microdroplets,a single drop of blood can support over seven million measurements.The high-throughput ability and small sample consumption make it a promising tool for clinical diagnoses based on mechanical properties.展开更多
The Lieb lattice is fundamental in condensed matter physics for hosting exotic electronic and topological states.Through high-throughput computational screening of 1470 binary metal-inorganic frameworks(MIFs),we ident...The Lieb lattice is fundamental in condensed matter physics for hosting exotic electronic and topological states.Through high-throughput computational screening of 1470 binary metal-inorganic frameworks(MIFs),we identified 24 stable Lieb lattice structures,including 22 new materials.These comprise 15 nonmagnetic,2 ferromagnetic(FM)half-metals,and 7 antiferromagnetic semiconductors,with critical temperatures reaching 877 K.Key electronic features include flat bands,Dirac cones,and van Hove singularities.HfCl_(2)and WO_(2)are FM half-metals with large spin gaps(5.37 eV and 3.57 eV),enabling full spin polarization.Be_(2)C and ReF_(2)exhibit nodal loops and quasi-flat bands,respectively,hosting nontrivial topology confirmed by edge-state analysis.NineMIFs are zerodimensional electrides with work functions as low as 2.64 eV.Thirteen structures are ground-state phases,ensuring stability.These Lieb lattices offer promising platforms for high-temperature electronic,spintronic,and topological applications.展开更多
Rising atmospheric CO_(2)levels threaten climate stability,demanding transformative solutions in carbon capture,utilization,and storage.Porous activated carbons(ACs)derived from sustainable waste sources offer a promi...Rising atmospheric CO_(2)levels threaten climate stability,demanding transformative solutions in carbon capture,utilization,and storage.Porous activated carbons(ACs)derived from sustainable waste sources offer a promising route for cost-effective and eco-friendly carbon capture,thanks to their tunable surface chemistry and high surface areas.However,optimizing ACs for peak CO_(2)uptake is often hindered by complex,resource-intensive experimental workflows and the scarcity of highquality data.This study presents a machine learning-driven framework that combines a multi-headed one-dimensional convolutional neural network(MH1DCNN)with multi-fidelity Bayesian optimization(MFBO)to efficiently navigate large design spaces by balancing exploration of uncertain regions with exploitation of known high-performing candidates.The MH1DCNN captures nonlinear relationships between physicochemical properties and CO_(2)uptake,serving as a deployable low-fidelity model.Using 841 literature-reported samples as high-cost,high-fidelity data and MH1DCNN-generated predictions as low-cost,low-fidelity evaluations,MFBO fuses these information sources through a probabilistic surrogate model,enabling rapid and cost-effective optimization.This approach reduces high-fidelity evaluation requirements by over75%and identifies top-performing candidates using only 13 high-fidelity acquisitions.This scalable,data-driven strategy supports the development of closedloop experiment-analysis-planning systems for future autonomous laboratories and accelerates sustainable materials discovery.展开更多
Traditional Chinese medicine(TCM) has been widely used in China and other Asia countries for thousands of years to treat or prevent human diseases. Chinese herbal medicine, one of the most important components of TCM,...Traditional Chinese medicine(TCM) has been widely used in China and other Asia countries for thousands of years to treat or prevent human diseases. Chinese herbal medicine, one of the most important components of TCM, has unique diversities in chemical components, and thus results in a wide range of biological activities. However, pharmaceutical industry is facing a major challenge to develop a large population of novel natural products and drugs, and considerable efforts have not resulted in highvolume of novel drug discovery and productivity. At present, increasing attention has been paid to Chinese herb medicine modernization in combination with the cutting-age technologies of drug discovery, especially the high throughput selection. High content imaging is an image-based high throughput screening method by using automated microscopy and image analysis software to capture and analyze phenotypes at a large scale to investigate multiple biological features simultaneously in the biological complex. Here, we described the pipeline of the state-of-the-art high content imaging technology, summarized the applications of the high content imaging technology in drug discovery from traditional Chinese herbal medicine, and finally discussed the current challenges and future perspectives for development of high throughput image-based screening technology in novel drug research and discovery.展开更多
OBJECTIVE Dopamine receptors(DRs) are involved in the development and treatment of many neuropsychiatric disorders.Currently available dopaminergic drugs modulate both DRD2 and DRD3,leading to side effects and uncerta...OBJECTIVE Dopamine receptors(DRs) are involved in the development and treatment of many neuropsychiatric disorders.Currently available dopaminergic drugs modulate both DRD2 and DRD3,leading to side effects and uncertainty as to the roles each DR subtype plays physiologically.Our lab employed high throughput screening paradigms to discover highly selective modulators for the DRD3.METHODS The NIH Molecular Libraries Program 400,000 + small molecule library was screened using the Discove Rx Path Hunter?β-arrestin assay for compounds that activate the DRD3 without effects on the DRD2.Confirmation and counter-screens assessed selectivity and mechanisms of action.We identified 62 potential agonists,and chose the most promising to perform a structure-activity relationship(SAR) study to increase potency while maintaining selectivity.The lead compound identified through this process,ML417,was also characterized using bioluminescence resonance energy transfer(BRET)-based β-arrestin recruitment and G-protein activation assays as well as p-ERK assays.Potential neuroprotective properties of this compound were assessed using a SHSY5 Y neuronal cell model.RESULTS ML417 displays potent,DRD3-selective agonist activity in multiple functional assays.Binding and functional GPCR screens(>165 receptors) show ML417 has limited cross-reactivity with other GPCRs.ML417 also displays superior(compared to the reference compound pramipexole),dose-dependent protection against a decrease in neurite length induced by 10 μmol·L^(-1) of the neurotoxin,6-hydroxydopamine,in the SHSY5 Y cell model.CONCLUSION We have discovered and characterized ML417,a potent and highly selective DRD3 agonist.This compound will be useful as a research tool,and may prove useful as a therapeutic drug lead.展开更多
The removal of leaked radioactive iodine isotopes in humid air environments holds significant importance in nuclear waste management and nuclear accident mitigation.In this study,highthroughput computational screening...The removal of leaked radioactive iodine isotopes in humid air environments holds significant importance in nuclear waste management and nuclear accident mitigation.In this study,highthroughput computational screening and machine learning were combined to reveal the iodine capture performance of 1816 metal-organic framework(MOF)materials under humid air conditions.Initially,the relationship between the structural characteristics of MOF materials(including density,surface area and pore features)and their adsorption properties was explored,with the aim of identifying the optimal structural parameters for iodine capture.Subsequently,two machine learning regression algorithms—Random Forest and CatBoost,were employed to predict the iodine adsorption capabilities of MOF materials.In addition to 6 structural features,25 molecular features(encompassing the types of metal and ligand atoms as well as bonding modes)and 8 chemical features(including heat of adsorption and Henry’s coefficient)were incorporated to enhance the prediction accuracy of the machine learning algorithms.Feature importance was assessed to determine the relative influence of various features on iodine adsorption performance,in which the Henry’s coefficient and heat of adsorption to iodine were found the two most crucial chemical factors.Furthermore,four types of molecular fingerprints were introduced for providing comprehensive and detailed structural information of MOF materials.The 20 most significant Molecular ACCess Systems(MACCS)bits were picked out,revealing that the presence of six-membered ring structures and nitrogen atomsin theMOFframeworkwere the key structural factors that enhanced iodine adsorption,followed by the presence of oxygen atoms.This work combined high-throughput computation,machine learning,and molecular fingerprints to comprehensively and systematically elucidate the multifaceted factors governing the iodine adsorption performance of MOFs in humid environments,establishing a robust and profound guideline framework for accelerating the screening and targeted design of high-performance MOF materials.展开更多
The utilization of phosphorescent metal complexes as emissive dopants for organic light-emitting diodes(OLEDs)has been the subject of intense research.Cyclometalated Pt(Ⅱ)complexes are particularly popular triplet em...The utilization of phosphorescent metal complexes as emissive dopants for organic light-emitting diodes(OLEDs)has been the subject of intense research.Cyclometalated Pt(Ⅱ)complexes are particularly popular triplet emitters due to their color-tunable emissions.To make them viable for practical applications as OLED emitters,it is essential to develop Pt(Ⅱ)complexes with high radiative decay rate constants(k_(r))and photoluminescence quantum yields(PLQY).To this end,an efficient and accurate prediction tool is highly desirable.In this work,we propose a general yet powerful protocol achieving metal complex generation,high throughput virtual screening(HTVS),and fast predictions with high accuracy.More than 3600 potential structures are generated in a synthesis-friendly manner.Moreover,three HTVS-machine learning(ML)models are established using different algorithms with carefully designed features that are suitable for metal complexes.Specifically,30 potential candidates are filtered out by HTVS-ML models with a three-tier screening rule and put into accurate predictions with experimental calibrationΔ-learning method.The highly accurate prediction approach further reduces the stress of experiments and inspires greater confidence in identifying the most promising complexes as excellent emitters.As a result,12 promising complexes(k_(r)>10^(5) s^(−1) and PLQY>0.6)with the same superior core structures are confirmed from over 3600 Pt-complexes.Experiments revealed that two very close complexes have excellent emission properties and are consistent with the prediction results,providing strong evidence for the efficacy of the proposed protocol.We expect this protocol will become a valuable tool,expediting the rational design and rapid development of novel OLED materials with desired properties.展开更多
The discovery of fluorescence materials with an inverted singlet-triplet(IST)energy gap,where the singlet excited state(S_(1))lies below the triplet excited state(T_(1)),mark a transformative advancement in organic li...The discovery of fluorescence materials with an inverted singlet-triplet(IST)energy gap,where the singlet excited state(S_(1))lies below the triplet excited state(T_(1)),mark a transformative advancement in organic light-emitting diodes(OLEDs)technology.However,designing the potential IST emitters are greatly challenging,and their IST energy gap,arising from double electron excitation,can only be accurately described by time-consuming post-Hartree-Fock(HF)methods,which blocks large-scale high-throughput screening speed.Here,we develop a four-orbital model to elucidate detailly the roles of double excitations in the IST formation,and establish two molecular descriptors(K_(S)and O_(D))based on exchange integral and molecular orbital energy.By these descriptors,we rapidly identify 41 IST candidates out of 3,486 molecules.The descriptors-aided approach achieves a screening success rate of 90%and reduces computational costs by 13 times compared to full post-HF calculations.Importantly,wepredicted a series of excellent non-traditional near-infrared IST emitters from a dataset of 1028 compounds with emission wavelengths ranging from 852.2 to 1002.3 nm,which open new avenues for designing highly efficient near-infrared OLED materials.展开更多
基金supported by the National Natural Science Foundation of China(31972576)the Beijing Natural Science Foundation(6202004)+2 种基金the Special Program on Science and Technology Innovation Capacity Building of BAAFS(KJCX20180414 and KJCX201914)the USDA National Institute of Food and Agriculture(2018-68003-27462 and 2018-33610-28252)the Oklahoma Center for the Advancement of Science and Technology(AR19-27)。
文摘Background:In-feed antibiotics are being phased out in livestock production worldwide.Alternatives to antibiotics are urgently needed to maintain animal health and production performance.Host defense peptides(HDPs)are known for their broad-spectrum antimicrobial and immunomodulatory capabilities.Enhancing the synthesis of endogenous HDPs represents a promising antibiotic alternative strategy to disease control and prevention.Methods:To identify natural products with an ability to stimulate the synthesis of endogenous HDPs,we performed a high-throughput screening of 1261 natural products using a newly-established stable luciferase reporter cell line known as IPEC-J2/pBD3-luc.The ability of the hit compounds to induce HDP genes in porcine IPEC-J2 intestinal epithelial cells,3D4/31 macrophages,and jejunal explants were verified using RT-qPCR.Augmentation of the antibacterial activity of porcine 3D4/31 macrophages against a Gram-negative bacterium(enterotoxigenic E.coli)and a Gram-positive bacterium(Staphylococcus aureus)were further confirmed with four selected HDP-inducing compounds.Results:A total of 48 natural products with a minimum Z-score of 2.0 were identified after high-throughput screening,with 21 compounds giving at least 2-fold increase in luciferase activity in a follow-up dose-response experiment.Xanthohumol and deoxyshikonin were further found to be the most potent in inducing pBD3 mRNA expression,showing a minimum 10-fold increase in IPEC-J2,3D4/31 cells,and jejunal explants.Other compounds such as isorhapontigenin and calycosin also enhanced pBD3 mRNA expression by at least 10-fold in both IPEC-J2 cells and jejunal explants,but not 3D4/31 cells.In addition to pBD3,other porcine HDP genes such as pBD2,PG1-5,and pEP2C were induced to different magnitudes by xanthohumol,deoxyshikonin,isorhapontigenin,and calycosin,although clear gene-and cell type-specific patterns of regulation were observed.Desirably,these four compounds had a minimum effect on the expression of several representative inflammatory cytokine genes.Furthermore,when used at HDP-inducing concentrations,these compounds showed no obvious direct antibacterial activity,but significantly augmented the antibacterial activity of 3D4/31 macrophages(P<0.05)against both Gram-negative and Gram-positive bacteria.Conclusions:Our results indicate that these newly-identified natural HDP-inducing compounds have the potential to be developed as novel alternatives to antibiotics for prophylactic and therapeutic treatment of infectious diseases in livestock production.
基金financially supported by the National Key Research and Development Program of China (2018YFA0702002)the Beijing Natural Science Foundation (Z210016)the National Natural Science Foundation of China (21935001)。
文摘Single atomic catalysts(SACs),especially metal-nitrogen doped carbon(M-NC)catalysts,have been extensively explored for the electrochemical oxygen reduction reaction(ORR),owing to their high activity and atomic utilization efficiency.However,there is still a lack of systematic screening and optimization of local structures surrounding active centers of SACs for ORR as the local coordination has an essential impact on their electronic structures and catalytic performance.Herein,we systematic study the ORR catalytic performance of M-NC SACs with different central metals and environmental atoms in the first and second coordination sphere by using density functional theory(DFT)calculation and machine learning(ML).The geometric and electronic informed overpotential model(GEIOM)based on random forest algorithm showed the highest accuracy,and its R^(2) and root mean square errors(RMSE)were 0.96 and 0.21,respectively.30 potential high-performance catalysts were screened out by GEIOM,and the RMSE of the predicted result was only 0.12 V.This work not only helps us fast screen high-performance catalysts,but also provides a low-cost way to improve the accuracy of ML models.
基金the Start- up Fund for Returned Overseas Scholars from Northeast Normal U niversity,National ScienceFund for Distinguished Young Scholars (No. 30 32 5 0 11) ,Distinguished Young Scholars Fund of Jilin Province(No.2 0 0 30 112 ) ,Excellent Young Teachers
文摘A stably transfected CHO cell line coexpressing G551D-CFTR and iodide-sensitive yellow fluorescent protein mutant EYFP-H148Q-I152L was successfully established and used as assay model to identify small-molecule activators of G551D-CFTR chloride channel from 100000 diverse combinatorial compounds by high throughput screening on a customized Beckman robotic system. A bicyclooctane compound was identified to activate G551D-CFTR chloride channel with high-affinity(K d=1.8 μmol/L). The activity of the bicyclooctane compound is G551D-CFTR-specific, reversible and non-toxic. The G551D-CFTR activator may be useful as a tool to study the mutant G551D-CFTR chloride channel structure and transport properties and as a candidate drug to cure cystic fibrosis caused by G551D-CFTR mutation.
文摘A novel solid phase organic synthesis resin was synthesized for combinatorial high-throughput screening,which based on FTIR spectra self-encoding functional resin technology. A new deconvolution strategy termed position encoding deconvolution had illustrated and was compared with some popular combinatorial deconvolution strategies in efficiency and information content. The mimic high throughput screening of hexapeptide library successfully proved the applying of the self-encoding functional resin technology and the position encoding deconvolution strategy.
基金the Start- up Fund for Returned Overseas Scholars from Northeast Normal U niversity,National ScienceFund for Distinguished Young Scholars(No.30 32 5 0 11) ,Distinguished Young Scholars Fund of Jilin Province(No.2 0 0 30 112 ) ,Excellent Young Teachers Pr
文摘The glycine-to-aspartic acid missense mutation at the codon 551(G551D) of the cystic fibrosis transmembrane conductance regulator(CFTR) is one of the five most frequent cystic fibrosis(CF) mutations associated with a severe CF phenotype. To explore the feasibility of pharmacological correction of disrupted activation of CFTR chloride channel caused by G551D mutation, we developed a halide-sensitive fluorescence miniassay for G551D-CFTR in Fisher rat thyroid(FRT) epithelial cells for the discovery of novel activators of G551D-CFTR. A class of bicyclooctane small molecule compounds that efficiently stimulate G551D-CFTR chloride channel activity was identified by high throughput screening via the FRT cell-based assay. This class of compounds selectively activates G551D-CFTR with a high affinity, whereas little effect of the compounds on wildtype CFTR can be seen. The discovery of a class of bicyclooctane G551D-CFTR activators will permit the analysis of structure-activity relationship of the compounds to identify ideal leads for in vivo therapeutic studies.
文摘In this article, we introduce the system of high throughput screening (HTS). Its role in new drug study and current development is described. The relationship between research achievements of genome study and new type screening model of new drugs is emphasized. The personal opinions of current problems about HTS study in China are raised.
基金supported by National Natural Science Foundation of China (32172747 and 32425052)
文摘Background Early embryo development plays a pivotal role in determining pregnancy outcomes,postnatal development,and lifelong health.Therefore,the strategic selection of functional nutrients to enhance embryo development is of paramount importance.In this study,we established a stable porcine trophectoderm cell line expressing dual fluorescent reporter genes driven by the CDX2 and TEAD4 gene promoter segments using lentiviral transfection.Results Three amino acid metabolites—kynurenic acid,taurine,and tryptamine—met the minimum z-score criteria of 2.0 for both luciferase and Renilla luciferase activities and were initially identified as potential metabolites for embryo development,with their beneficial effects validated by qPCR.Given that the identified metabolites are closely related to methionine,arginine,and tryptophan,we selected these three amino acids,using lysine as a standard,and employed response surface methodology combined with our high-throughput screening cell model to efficiently screen and optimize amino acid combination conducive to early embryo development.The optimized candidate amino acid system included lysine(1.87 mmol/L),methionine(0.82 mmol/L),tryptophan(0.23 mmol/L),and arginine(3 mmol/L),with the ratio of 1:0.43:0.12:1.60.In vitro experiments confirmed that this amino acid system enhances the expression of key genes involved in early embryonic development and improves in vitro embryo adhesion.Transcriptomic analysis of blastocysts suggested that candidate amino acid system enhances early embryo development by regulating early embryonic cell cycle and differentiation,as well as improving nutrient absorption.Furthermore,based on response surface methodology,400 sows were used to verify this amino acid system,substituting arginine with the more cost-effective N-carbamoyl glutamate(NCG),a precursor of arginine.The optimal dietary amino acid requirement was predicted to be 0.71%lysine,0.32%methionine,0.22%tryptophan,and 0.10%NCG for sows during early gestation.The optimized amino acid system ratio of the feed,derived from the peripheral release of essential amino acids,was found to be 1:0.45:0.13,which is largely consistent with the results obtained from the cell model optimization.Subsequently,we furtherly verified that this optimal dietary amino acid system significantly increased total litter size,live litter size and litter weight in sows.Conclusions In summary,we successfully established a dual-fluorescent high-throughput screening cell model for the efficient identification of potential nutrients that would promote embryo development and implantation.This innovative approach overcomes the limitations of traditional amino acid nutrition studies in sows,providing a more effective model for enhancing reproductive outcomes.
基金The reported work was supported in part by research grants from the National Institutes of Health(AT004418,DE020140 to TCH and RRR)the US Department of Defense(OR130096 to JMW)+5 种基金the Scoliosis Research Society(TCH and MJL)the National Key Research and Development Program of China(2016YFC1000803 and 2011CB707906 to TCH)the National Natural Science Foundation of China(#81201916 to XW)ZZ was a recipient of protectorate fellowship from China Scholarship CouncilThis project was also supported in part by The University of Chicago Cancer Center Support Grant(P30CA014599)the National Center for Advancing Translational Sciences of the National Institutes of Health through Grant Number UL1 TR000430.
文摘While the human genome is pervasively transcribed,<2%of the human genome is transcribed into protein-coding mRNAs,leaving most of the transcripts as noncoding RNAs,such as microRNAs and long-noncoding RNAs(lncRNAs),which are critical components of epigenetic regulation.lncRNAs are emerging as critical regulators of gene expression and genomic stability.However,it remains largely unknown about how lncRNAs are regulated.Here,we develop a highly sensitive and dynamic reporter that allows us to identify and/or monitor negative modulators of lncRNA transcript levels in a high throughput fashion.Specifically,we engineer a fluorescent fusion protein by fusing three copies of the PEST destruction domain of mouse ornithine decarboxylase(MODC)to the C-terminal end of the codon-optimized bilirubin-inducible fluorescent protein,designated as dBiFP,and show that the dBiFP protein is highly destabilized,compared with the commonly-used eGFP protein.We further demonstrate that the dBiFP signal is effectively down-regulated when the dBiFP and mouse lncRNA H19 chimeric transcript is silenced by mouse H19-specific siRNAs.Therefore,our results strongly suggest that the dBiFP fusion protein may serve as a sensitive and dynamic transcript reporter to monitor the inhibition of lncRNAs by microRNAs,synthetic regulatory RNA molecules,RNA binding proteins,and/or small molecule inhibitors so that novel and efficacious inhibitors targeting the epigenetic circuit can be discovered to treat human diseases such as cancer and other chronic disorders.
基金supported by the National Science Foundation under BIO-2036968,cooperative agreement EEC-1648035(RAM),and UGA Research Foundation startup funds(KMH)supported in part by the Glycosciences Training Grant Program(NIH T32 GM145467)。
文摘Due to their immunomodulatory function,mesenchymal stromal cells(MSCs)are a promising therapeutic with the potential to treat neuroinflammation associated with neurodegenerative diseases.This function is mediated by secreted extracellular vesicles(MSC-EVs).Despite established safety,MSC clinical translation has been unsuccessful due to inconsistent clinical outcomes resulting from functional heterogeneity.Current approaches to mitigate functional heterogeneity include‘priming’MSCs with inflammatory signals to enhance function.However,comprehensive evaluation of priming and its effects on MSC-EV function has not been performed.Furthermore,clinical translation of MSC-EV therapies requires significant manufacturing scale-up,yet few studies have investigated the effects of priming in bioreactors.As MSC morphology has been shown to predict their immunomodulatory function,we screened MSC morphological response to an array of priming signals and evaluated MSC-EV identity and potency in response to priming in flasks and bioreactors.We identified unique priming conditions corresponding to distinct morphologies.These conditions demonstrated a range of MSC-EV preparation quality and lipidome,allowing us to discover a novel MSC-EV manufacturing condition,as well as gain insight into potential mechanisms of MSC-EV microglia modulation.Our novel screening approach and application of priming to MSC-EV bioreactor manufacturing informs refinement of larger-scale manufacturing and enhancement of MSC-EV function.
基金supported by the Creative Research Group Program of Natural Science Foundation of Hubei Province (2022CFA021)National Natural Science Foundation of China (81702005).
文摘Alphaviruses,which contain a variety of mosquito-borne pathogens,are important pathogens of emerging/reemerging infectious diseases and potential biological weapons.Currently,no specific antiviral drugs are available for the treatment of alphaviruses infection.For most highly pathogenic alphaviruses are classified as risk group-3 agents,the requirement of biosafety level 3(BSL-3)facilities limits the live virus-based antiviral study.To facilitate the antiviral development of alphaviruses,we developed a high throughput screening(HTS)platform based on a recombinant Semliki Forest virus(SFV)which can be manipulated in BSL-2 laboratory.Using the reverse genetics approach,the recombinant SFV and SFV reporter virus expressing eGFP(SFV-eGFP)were successfully rescued.The SFV-eGFP reporter virus exhibited robust eGFP expression and remained relatively stable after four passages in BHK-21 cells.Using a broad-spectrum alphavirus inhibitor ribavirin,we demonstrated that the SFV-eGFP can be used as an effective tool for antiviral study.The SFV-eGFP reporter virus-based HTS assay in a 96-well format was then established and optimized with a robust Z0 score.A section of reference compounds that inhibit highly pathogenic alphaviruses were used to validate that the SFV-eGFP reporter virus-based HTS assay enables rapid screening of potent broad-spectrum inhibitors of alphaviruses.This assay provides a safe and convenient platform for antiviral study of alphaviruses.
基金This work is supported in part by NIH P50-CA70907,NIH U24CA126608,and NASA NNJ05HD36G.
文摘High throughput screening(HTS)is a widely used effective approach in genome-wide association and large scale protein expression studies,drug discovery,and biomedical imaging research.How to accurately identify candidate‘targets’or biologically meaningful features with a high degree of confidence has led to extensive statistical research in an effort to minimize both false-positive and false-negative rates.A large body of literature on this topic with in-depth statistical contents is available.We examine currently available statistical methods on HTS and aim to summarize some selected methods into a concise,easy-tofollow introduction for experimental biologists.
文摘Since the mid-to-late 20th century,the scientific community has increasingly recognized that the rapid rise in atmospheric greenhouse gases,particularly CO_(2)from human activities,is the primary driver of global warming.This escalation has led to pressing climate challenges,including sea-level rise and more frequent extreme weather events[1,2].Among the limited strategies available to mitigate CO_(2)emissions,carbon capture and storage have emerged as a key approach.To this end,various adsorbents—such as metalorganic frameworks(MOFs),zeolites,and carbon materials—have been developed for CO_(2)capture[3-6].
基金supported by the National Natural Science Foundation of China(Grant No.62375030,82241059,82125022)the Fundamental Research Funds for the Central Universities(Grant No.2024CDJYXTD-004)the Yunnan Province Major Science and Technology Special Project(Grant No.202302AA310039).
文摘The mechanical properties of biological fluids serve as early indicators of disease,offering valuable insights into complex physiological and pathological processes.However,the existing technologies struggle to achieve high-throughput measurement,limiting their widespread applications in disease diagnosis.Here,we propose laser-emission vibrational microscopy of microdroplets for high-throughput measurement of the intrinsic mechanical properties of fluids.The microdroplet array supporting high Q-factor(104)whispering gallery modes(WGM)lasing was massively fabricated on a superhydrophobic surface with inkjet printing.Ultrasound was employed to actuate the mechanical vibrations of the microdroplets,and the vibration amplitude was quantified using time-resolved laser spectra.We found that the stimulus-response of the laser emission is strongly dependent on the liquid viscosity.Fast mapping of the microdroplets’viscosities was achieved by stage scanning.High-throughput screening of hyperlipidemia disease was also demonstrated by performing over 2000 measurements within 25 min.Thanks to the small volume of the microdroplets,a single drop of blood can support over seven million measurements.The high-throughput ability and small sample consumption make it a promising tool for clinical diagnoses based on mechanical properties.
基金supported by the National Natural Science Foundation for Distinguished Young Scholars (22225301, 22503091)the Anhui Provincial Natural Science Foundation (2308085QB51)+2 种基金the CAS Project for Young Scientists in Basic Research (YSBR-004)the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB0450101)the Fundamental Research Funds for the Central Universities (WK9990000153). We thank the support from the Super Computer Centre of University of Science and Technology of China and Supercomputing Center of Chinese Academy of Sciences.
文摘The Lieb lattice is fundamental in condensed matter physics for hosting exotic electronic and topological states.Through high-throughput computational screening of 1470 binary metal-inorganic frameworks(MIFs),we identified 24 stable Lieb lattice structures,including 22 new materials.These comprise 15 nonmagnetic,2 ferromagnetic(FM)half-metals,and 7 antiferromagnetic semiconductors,with critical temperatures reaching 877 K.Key electronic features include flat bands,Dirac cones,and van Hove singularities.HfCl_(2)and WO_(2)are FM half-metals with large spin gaps(5.37 eV and 3.57 eV),enabling full spin polarization.Be_(2)C and ReF_(2)exhibit nodal loops and quasi-flat bands,respectively,hosting nontrivial topology confirmed by edge-state analysis.NineMIFs are zerodimensional electrides with work functions as low as 2.64 eV.Thirteen structures are ground-state phases,ensuring stability.These Lieb lattices offer promising platforms for high-temperature electronic,spintronic,and topological applications.
基金funded by Natural Resources Canada(NRCan)through the Energy Innovation Program under the project titled Using Renewables to Capture Carbon-RtoC2Additional financial support was generously provided by the Natural Sciences and Engineering Research Council of Canada(NSERC),which further contributed to the advancement of this work.
文摘Rising atmospheric CO_(2)levels threaten climate stability,demanding transformative solutions in carbon capture,utilization,and storage.Porous activated carbons(ACs)derived from sustainable waste sources offer a promising route for cost-effective and eco-friendly carbon capture,thanks to their tunable surface chemistry and high surface areas.However,optimizing ACs for peak CO_(2)uptake is often hindered by complex,resource-intensive experimental workflows and the scarcity of highquality data.This study presents a machine learning-driven framework that combines a multi-headed one-dimensional convolutional neural network(MH1DCNN)with multi-fidelity Bayesian optimization(MFBO)to efficiently navigate large design spaces by balancing exploration of uncertain regions with exploitation of known high-performing candidates.The MH1DCNN captures nonlinear relationships between physicochemical properties and CO_(2)uptake,serving as a deployable low-fidelity model.Using 841 literature-reported samples as high-cost,high-fidelity data and MH1DCNN-generated predictions as low-cost,low-fidelity evaluations,MFBO fuses these information sources through a probabilistic surrogate model,enabling rapid and cost-effective optimization.This approach reduces high-fidelity evaluation requirements by over75%and identifies top-performing candidates using only 13 high-fidelity acquisitions.This scalable,data-driven strategy supports the development of closedloop experiment-analysis-planning systems for future autonomous laboratories and accelerates sustainable materials discovery.
文摘Traditional Chinese medicine(TCM) has been widely used in China and other Asia countries for thousands of years to treat or prevent human diseases. Chinese herbal medicine, one of the most important components of TCM, has unique diversities in chemical components, and thus results in a wide range of biological activities. However, pharmaceutical industry is facing a major challenge to develop a large population of novel natural products and drugs, and considerable efforts have not resulted in highvolume of novel drug discovery and productivity. At present, increasing attention has been paid to Chinese herb medicine modernization in combination with the cutting-age technologies of drug discovery, especially the high throughput selection. High content imaging is an image-based high throughput screening method by using automated microscopy and image analysis software to capture and analyze phenotypes at a large scale to investigate multiple biological features simultaneously in the biological complex. Here, we described the pipeline of the state-of-the-art high content imaging technology, summarized the applications of the high content imaging technology in drug discovery from traditional Chinese herbal medicine, and finally discussed the current challenges and future perspectives for development of high throughput image-based screening technology in novel drug research and discovery.
基金supported by National Institute of Neurological Disorders and Stroke Intramural Research Program
文摘OBJECTIVE Dopamine receptors(DRs) are involved in the development and treatment of many neuropsychiatric disorders.Currently available dopaminergic drugs modulate both DRD2 and DRD3,leading to side effects and uncertainty as to the roles each DR subtype plays physiologically.Our lab employed high throughput screening paradigms to discover highly selective modulators for the DRD3.METHODS The NIH Molecular Libraries Program 400,000 + small molecule library was screened using the Discove Rx Path Hunter?β-arrestin assay for compounds that activate the DRD3 without effects on the DRD2.Confirmation and counter-screens assessed selectivity and mechanisms of action.We identified 62 potential agonists,and chose the most promising to perform a structure-activity relationship(SAR) study to increase potency while maintaining selectivity.The lead compound identified through this process,ML417,was also characterized using bioluminescence resonance energy transfer(BRET)-based β-arrestin recruitment and G-protein activation assays as well as p-ERK assays.Potential neuroprotective properties of this compound were assessed using a SHSY5 Y neuronal cell model.RESULTS ML417 displays potent,DRD3-selective agonist activity in multiple functional assays.Binding and functional GPCR screens(>165 receptors) show ML417 has limited cross-reactivity with other GPCRs.ML417 also displays superior(compared to the reference compound pramipexole),dose-dependent protection against a decrease in neurite length induced by 10 μmol·L^(-1) of the neurotoxin,6-hydroxydopamine,in the SHSY5 Y cell model.CONCLUSION We have discovered and characterized ML417,a potent and highly selective DRD3 agonist.This compound will be useful as a research tool,and may prove useful as a therapeutic drug lead.
基金supported by the National Key R&D Program of China(No.2022YFB4703403 and No.2016YFC1402504)Dr.G.C.Shan particularly acknowledges additional support from the College of Science Distinguished Alumni Award granted by the College of Science at the City University of Hong Kong(CityUHK).Finally,this groundbreaking study is dedicated to commemorating the 120th anniversary of Fudan University to be celebrated in May 2025.
文摘The removal of leaked radioactive iodine isotopes in humid air environments holds significant importance in nuclear waste management and nuclear accident mitigation.In this study,highthroughput computational screening and machine learning were combined to reveal the iodine capture performance of 1816 metal-organic framework(MOF)materials under humid air conditions.Initially,the relationship between the structural characteristics of MOF materials(including density,surface area and pore features)and their adsorption properties was explored,with the aim of identifying the optimal structural parameters for iodine capture.Subsequently,two machine learning regression algorithms—Random Forest and CatBoost,were employed to predict the iodine adsorption capabilities of MOF materials.In addition to 6 structural features,25 molecular features(encompassing the types of metal and ligand atoms as well as bonding modes)and 8 chemical features(including heat of adsorption and Henry’s coefficient)were incorporated to enhance the prediction accuracy of the machine learning algorithms.Feature importance was assessed to determine the relative influence of various features on iodine adsorption performance,in which the Henry’s coefficient and heat of adsorption to iodine were found the two most crucial chemical factors.Furthermore,four types of molecular fingerprints were introduced for providing comprehensive and detailed structural information of MOF materials.The 20 most significant Molecular ACCess Systems(MACCS)bits were picked out,revealing that the presence of six-membered ring structures and nitrogen atomsin theMOFframeworkwere the key structural factors that enhanced iodine adsorption,followed by the presence of oxygen atoms.This work combined high-throughput computation,machine learning,and molecular fingerprints to comprehensively and systematically elucidate the multifaceted factors governing the iodine adsorption performance of MOFs in humid environments,establishing a robust and profound guideline framework for accelerating the screening and targeted design of high-performance MOF materials.
基金supported by the RGC General Research Fund under Grant No.17309620Hong Kong Quantum AI Lab Limited and Air@InnoHK of Hong Kong Government+4 种基金the support from National Natural Science Foundation of China(Grant Nos.22073007 and 22473022)Shenzhen Basic Research Key Project Fund(Grant No.JCYJ20220818103200001)National Natural Science Foundation of China(No.22273010)Department of Science and Technology of Jilin Province(20210402075GH)C-M C and F-F H acknowledge Guangdong Major Project of Basic and Applied Basic Research(Grant No.2019B030302009).
文摘The utilization of phosphorescent metal complexes as emissive dopants for organic light-emitting diodes(OLEDs)has been the subject of intense research.Cyclometalated Pt(Ⅱ)complexes are particularly popular triplet emitters due to their color-tunable emissions.To make them viable for practical applications as OLED emitters,it is essential to develop Pt(Ⅱ)complexes with high radiative decay rate constants(k_(r))and photoluminescence quantum yields(PLQY).To this end,an efficient and accurate prediction tool is highly desirable.In this work,we propose a general yet powerful protocol achieving metal complex generation,high throughput virtual screening(HTVS),and fast predictions with high accuracy.More than 3600 potential structures are generated in a synthesis-friendly manner.Moreover,three HTVS-machine learning(ML)models are established using different algorithms with carefully designed features that are suitable for metal complexes.Specifically,30 potential candidates are filtered out by HTVS-ML models with a three-tier screening rule and put into accurate predictions with experimental calibrationΔ-learning method.The highly accurate prediction approach further reduces the stress of experiments and inspires greater confidence in identifying the most promising complexes as excellent emitters.As a result,12 promising complexes(k_(r)>10^(5) s^(−1) and PLQY>0.6)with the same superior core structures are confirmed from over 3600 Pt-complexes.Experiments revealed that two very close complexes have excellent emission properties and are consistent with the prediction results,providing strong evidence for the efficacy of the proposed protocol.We expect this protocol will become a valuable tool,expediting the rational design and rapid development of novel OLED materials with desired properties.
基金support from the National Natural Science Foundation of China(Grant Nos.22325305 and 22273105)the Strategic Priority Research Program of Sciences(XDB0520103)+1 种基金National Key R&D Program of China(2024YFB3614300)the Fundamental Research Funds for the Central Universities(Grant Nos.E2E40307X2 and E2ET0309X2).We gratefully acknowledge WQ&UCAS Research Academy Intelligent Computing Center(WRA-ICC)for providing computation facilities.
文摘The discovery of fluorescence materials with an inverted singlet-triplet(IST)energy gap,where the singlet excited state(S_(1))lies below the triplet excited state(T_(1)),mark a transformative advancement in organic light-emitting diodes(OLEDs)technology.However,designing the potential IST emitters are greatly challenging,and their IST energy gap,arising from double electron excitation,can only be accurately described by time-consuming post-Hartree-Fock(HF)methods,which blocks large-scale high-throughput screening speed.Here,we develop a four-orbital model to elucidate detailly the roles of double excitations in the IST formation,and establish two molecular descriptors(K_(S)and O_(D))based on exchange integral and molecular orbital energy.By these descriptors,we rapidly identify 41 IST candidates out of 3,486 molecules.The descriptors-aided approach achieves a screening success rate of 90%and reduces computational costs by 13 times compared to full post-HF calculations.Importantly,wepredicted a series of excellent non-traditional near-infrared IST emitters from a dataset of 1028 compounds with emission wavelengths ranging from 852.2 to 1002.3 nm,which open new avenues for designing highly efficient near-infrared OLED materials.
