Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is...Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors.展开更多
The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carb...The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carbon dioxide(CO_2) and store methane(CH4), where the latter is a kind of clean energy source with abundant reserves and lower CO_2 emission. Hundreds of thousands of porous materials can be enrolled on the candidate list, but how to quickly identify the really promising ones, or even evolve materials(namely, rational design high-performing candidates) based on the large database of present porous materials? In this context, high-throughput computational techniques, which have emerged in the past few years as powerful tools, make the targets of fast evaluation of adsorbents and evolving materials for CO_2 capture and CH_4 storage feasible. This review provides an overview of the recent computational efforts on such related topics and discusses the further development in this field.展开更多
Gastric cancers are caused primarily due to the activation and amplification of the EGFR or HER2 kinases resulting in cell proliferation,adhesion,angiogenesis,and metastasis.Conventional therapies are ineffective due ...Gastric cancers are caused primarily due to the activation and amplification of the EGFR or HER2 kinases resulting in cell proliferation,adhesion,angiogenesis,and metastasis.Conventional therapies are ineffective due to the intra-tumoral heterogeneity and concomitant genetic mutations.Hence,dual inhibition strategies are recommended to increase potency and reduce cytotoxicity.In this study,we have conducted computational high-throughput screening of the ChemBridge library followed by in vitro assays and identified novel selective inhibitors that have a dual impediment of EGFR/HER2 kinase activities.Diversity-based High-throughput Virtual Screening(D-HTVS)was used to screen the whole ChemBridge small molecular library against EGFR and HER2.The atomistic molecular dynamic simulation was conducted to understand the dynamics and stability of the protein-ligand complexes.EGFR/HER2 kinase enzymes,KATOIII,and Snu-5 cells were used for in vitro validations.The atomistic Molecular Dynamics simulations followed by solvent-based Gibbs binding free energy calculation of top molecules,identified compound C3(5-(4-oxo-4H-3,1-benzoxazin-2-yl)-2-[3-(4-oxo-4H-3,1-benzoxazin-2-yl)phenyl]-1H-isoindole-1,3(2H)-dione)to have a good affinity for both EGFR and HER2.The predicted compound,C3,was promising with better binding energy,good binding pose,and optimum interactions with the EGFR and HER2 residues.C3 inhibited EGFR and HER2 kinases with IC50 values of 37.24 and 45.83 nM,respectively.The GI50 values of C3 to inhibit KATOIII and Snu-5 cells were 84.76 and 48.26 nM,respectively.Based on these findings,we conclude that the identified compound C3 showed a conceivable dual inhibitory activity on EGFR/HER2 kinase,and therefore can be considered as a plausible lead-like molecule for treating gastric cancers with minimal side effects,though testing in higher models with pharmacokinetic approach is required.展开更多
For the advancement of fast-charging sodium-ion batteries(SIBs),the synthesis of cutting-edge cathode materials with superior structural stability and enhanced Na+diffusion kinetics is imperative.Multiphase layered tr...For the advancement of fast-charging sodium-ion batteries(SIBs),the synthesis of cutting-edge cathode materials with superior structural stability and enhanced Na+diffusion kinetics is imperative.Multiphase layered transition metal oxides(LTMOs),which leverage the synergistic properties of two distinct monophasic LTMOs,have garnered significant attention;however,their efficacy under fast-charging conditions remains underexplored.In this study,we developed a high-throughput computational screening framework to identify optimal dopants that maximize the electrochemical performance of LTMOs.Specifically,we evaluated the efficacy of 32 dopants based on P2/O3-type Mn/Fe-based Na_(x)Mn_(0.5)Fe_(0.5)O_(2)(NMFO)cathode material.Multiphase LTMOs satisfying criteria for thermodynamic and structural stability,minimized phase transitions,and enhanced Na^(+)diffusion were systematically screened for their suitability in fast-charging applications.The analysis identified two dopants,Ti and Zr,which met all predefined screening criteria.Furthermore,we ranked and scored dopants based on their alignment with these criteria,establishing a comprehensive dopant performance database.These findings provide a robust foundation for experimental exploration and offer detailed guidelines for tailoring dopants to optimize fast-charging SIBs.展开更多
Additives are widely employed to regulate the morphology,size,and agglomeration degree of crystalline materials during crystallization to enhance their functional,physical,and powder properties.However,the existing me...Additives are widely employed to regulate the morphology,size,and agglomeration degree of crystalline materials during crystallization to enhance their functional,physical,and powder properties.However,the existing methods for screening and validating target additives require a large quantity of materials and involve tedious molecular simulation/crystallization experiments,making them time-consuming,resource-intensive,and reliant on the operator’s experience level.To overcome these challenges,we proposed a computer vision-assisted high-throughput additive screening system(CV-HTPASS)which comprises a high-throughput additive screening device,in situ imaging equipment,and an artificial intelligence(AI)-assisted image-analysis algorithm.Using the CV-HTPASS,we performed high-throughput screening experiments on additives to regulate the succinic acid crystal properties,generating thousands of crystal images with diverse crystal morphologies.To extract valuable crystal information from the massive data and improve the analysis accuracy and efficiency,the AI-based image-analysis algorithm was implemented innovatively for the segmentation,classification,and data mining of crystals with four morphologies to further screen the target additive.Subsequently,scale-up crystallization experiments conducted under optimized conditions demonstrated that succinic acid products exhibited a preferred cubic morphology,reduced agglomeration degree,narrowed crystal size distribution,and improved powder properties.The proposed CV-HTPASS offers a highly efficient approach for scale-up experiments.Further,it provides a platform for the screening of additives and the optimization of the powder properties of crystal products in industrial-scale crystallization processes.展开更多
Separating He from CH_(4)or N_(2)is crucial for natural gas He extraction,a prevailing industrial approach.Herein,molecular simulation and machine learning(ML)were combined to screen 801 experimentally synthesized COF...Separating He from CH_(4)or N_(2)is crucial for natural gas He extraction,a prevailing industrial approach.Herein,molecular simulation and machine learning(ML)were combined to screen 801 experimentally synthesized COFs for He/CH_(4)and He/N_(2)separation,either by means of adsorption or membrane separation.Top 10 COFs for 4 different gas separation purposes(CH_(4)/He or N_(2)/He separation with either adsorption or membrane)were identified respectively.The highest adsorption performance score(APSmix,defined as the product of working capacity and adsorption selectivity for mixture gas)reached 447.88 mol/kg and 49.45 mol/kg for CH_(4)/He and N_(2)/He,with corresponding adsorption selectivity of 115.56 and 30.33.He permeabilities of 1.5×10^(6)or 1.2×10^(6)Barrer were achieved for equimolar He/CH_(4)or He/N_(2)mixture gas separations,accompanied by permselectivity of 5.47 and 11.80 well surpassing 2008 Robeson's upper bound.Best performing COFs for adsorption separation are 3D COFs with pore diameter below 0.8 nm while those for membrane separation are 2D COFs with large pores.Additionally,ML models were developed to predict separation performance,with key descriptors identified.The mechanism for how COFs'structure affects their separation performance was also revealed.展开更多
Malignant melanoma is characterized by both genetic and molecular alterations that activate phosphoinositide 3-kinase(PI3K),and RAS/BRAF pathways.In this work,through diversity-based high-throughput virtual screening ...Malignant melanoma is characterized by both genetic and molecular alterations that activate phosphoinositide 3-kinase(PI3K),and RAS/BRAF pathways.In this work,through diversity-based high-throughput virtual screening we identified a lead molecule that selectively targets PI3K and BRAF^(V600E) kinases.Computational screening,Molecular dynamics simulation and MMPBSA calculations were performed.PI3K and BRAF^(V600E) kinase inhibition was done.A375 and G-361 cells were used for in vitro cellular analysis to determine antiproliferative effects,annexin V binding,nuclear fragmentation and cell cycle analysis.Computational screening of small molecules indicates compound CB-006-3 selectively targets PI3KCG(gamma subunit),PI3KCD(delta subunit)and BRAF^(V600E).Molecular dynamics simulation and MMPBSA bases binding free energy calculations predict a stable binding of CB-006-3 to the active sites of PI3K and BRAF^(V600E).The compound effectively inhibited PI3KCG,PI3KCD and BRAF^(V600E)kinases with respective IC50 values of 75.80,160.10 and 70.84 nM.CB-006-3 controlled the proliferation of A375 and G-361 cells with GI50 values of 223.3 and 143.6 nM,respectively.A dose dependent increase in apoptotic cell population and sub G0/G1 phase of cell cycle were also observed with the compound treatment in addition to observed nuclear fragmentation in these cells.Furthermore,CB-006-3 inhibited BRAF^(V600E),PI3KCD and PI3KCG in both melanoma cells.Collectively,based on the computational modeling and in vitro validations,we propose CB-006-3 as a lead candidate for selectively targeting PI3K and mutant BRAF^(V600E) to inhibit melanoma cell proliferation.Further experimental validations,including pharmacokinetic evaluations in mouse models will identify the druggability of the proposed lead candidate for further development as a therapeutic agent for treating melanoma.展开更多
The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF str...The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF structure database is available.In this study,we report a machine learning model for high-throughput screening of MOF catalysts for the CO_(2) cycloaddition reaction.The descriptors for model training were judiciously chosen according to the reaction mechanism,which leads to high accuracy up to 97%for the 75%quantile of the training set as the classification criterion.The feature contribution was further evaluated with SHAP and PDP analysis to provide a certain physical understanding.12,415 hypothetical MOF structures and 100 reported MOFs were evaluated under 100℃ and 1 bar within one day using the model,and 239 potentially efficient catalysts were discovered.Among them,MOF-76(Y)achieved the top performance experimentally among reported MOFs,in good agreement with the prediction.展开更多
Lithium-ion batteries(LiBs)with high energy density have gained significant popularity in smart grids and portable electronics.LiMn_(1-x)Fe_(x)PO_(4)(LMFP)is considered a leading candidate for the cathode,with the pot...Lithium-ion batteries(LiBs)with high energy density have gained significant popularity in smart grids and portable electronics.LiMn_(1-x)Fe_(x)PO_(4)(LMFP)is considered a leading candidate for the cathode,with the potential to combine the low cost of Li Fe PO_(4)(LFP)with the high theoretical energy density of LiMnPO_(4)(LMP).However,quantitative investigation of the intricate coupling between the Fe/Mn ratio and the resulting energy density is challenging due to the parametric complexity.It is crucial to develop a universal approach for the rapid construction of multi-parameter mapping.In this work,we propose an active learning-guided high-throughput workflow for quantitatively predicting the Fe/Mn ratio and the energy density mapping of LMFP.An optimal composition(LiMn_(0.66)Fe_(0.34)PO_(4))was effectively screened from 81 cathode materials via only 5 samples.Model-guided electrochemical analysis revealed a nonlinear relationship between the Fe/Mn ratio and electrochemical properties,including ion mobility and impedance,elucidating the quantitative chemical composition-energy density map of LMFP.The results demonstrated the efficacy of the method in high-throughput screening of LiBs cathode materials.展开更多
The capture of CO_(2)from CO_(2)/H_(2)gas mixtures in syngas is a crucial issue for hydrogen production from steam methane reforming in industry,as the presence of CO_(2)directly affects the purity of H_(2).A combinat...The capture of CO_(2)from CO_(2)/H_(2)gas mixtures in syngas is a crucial issue for hydrogen production from steam methane reforming in industry,as the presence of CO_(2)directly affects the purity of H_(2).A combination of a high-throughput screening method and grand canonical Monte Carlo simulation was utilized to evaluate and screen 1725 metal–organic frameworks(MOFs)in detail as a means of determining their adsorption performance for CO_(2)/H_(2)gas mixtures.The adsorption and separation performance of double-linker MOFs was comprehensively evaluated using eight evaluation indicators,namely,the largest cavity diameter,accessible surface area,pore occupied accessible volume,porosity,adsorption selectivity,working capacity,adsorbent performance score and percent regeneration.Six optimal performance frameworks were screened to further study their single-component adsorption and binary competitive adsorption of CO_(2)/H_(2)respectively.The CO_(2)adsorption selectivity at different CO_(2)/H_(2)feed ratios was also evaluated,which indicated their excellent adsorption and separation performance.The microscopic adsorption mechanisms for CO_(2)and H_(2)at the molecular level were investigated by analyzing the radial distribution function and density distribution.This study may provide directional guidance and reference for subsequent experiments on the adsorption and separation of CO_(2)/H_(2).展开更多
Deuterium(D_(2)) is one of the important fuel sources that power nuclear fusion reactors. The existing D_(2)/H_(2) separation technologies that obtain high-purity D_(2) are cost-intensive. Recent research has shown th...Deuterium(D_(2)) is one of the important fuel sources that power nuclear fusion reactors. The existing D_(2)/H_(2) separation technologies that obtain high-purity D_(2) are cost-intensive. Recent research has shown that metal-organic frameworks(MOFs) are of good potential for D_(2)/H_(2) separation application. In this work, a high-throughput computational screening of 12020 computation-ready experimental MOFs is carried out to determine the best MOFs for hydrogen isotope separation application. Meanwhile, the detailed structure-performance correlation is systematically investigated with the aid of machine learning. The results indicate that the ideal D_(2)/H_(2) adsorption selectivity calculated based on Henry coefficient is strongly correlated with the 1/ΔAD feature descriptor;that is, inverse of the adsorbility difference of the two adsorbates. Meanwhile, the machine learning(ML) results show that the prediction accuracy of all the four ML methods is significantly improved after the addition of this feature descriptor. In addition, the ML results based on extreme gradient boosting model also revealed that the 1/ΔAD descriptor has the highest relative importance compared to other commonly-used descriptors. To further explore the effect of hydrogen isotope separation in binary mixture, 1548 MOFs with ideal adsorption selectivity greater than 1.5 are simulated at equimolar conditions. The structure-performance relationship shows that high adsorption selectivity MOFs generally have smaller pore size(0.3-0.5 nm) and lower surface area. Among the top 200 performers, the materials mainly have the sql, pcu, cds, hxl, and ins topologies.Finally, three MOFs with high D_(2)/H_(2) selectivity and good D_(2) uptake are identified as the best candidates,of all which had one-dimensional channel pore. The findings obtained in this work may be helpful for the identification of potentially promising candidates for hydrogen isotope separation.展开更多
In all-solid-state lithium batteries,the impedance at the cathode/electrolyte interface shows close relationship with the cycle performance.Cathode coatings are helpful to reduce the impedance and increase the stabili...In all-solid-state lithium batteries,the impedance at the cathode/electrolyte interface shows close relationship with the cycle performance.Cathode coatings are helpful to reduce the impedance and increase the stability at the interface effectively.LiTi_(2)(PO_(4))_(3),a fast ion conductor with high ionic conductivity approaching 10^(-3)S·cm^(-1),is adopted as the coating materials in this study.The crystal and electronic structures,as well as the Li^+ion migration properties are evaluated for LTP and its doped derivatives based on density functional theory(DFT)and bond valence(BV)method.Substituting part of Ti sites with element Mn,Fe,or Mg in LTP can improve the electronic conductivity of LTP while does not decrease its high ionic conductivity.In this way,the coating materials with both high ionic conductivities and electronic conductivities can be prepared for all-solid-state lithium batteries to improve the ion and electron transport properties at the interface.展开更多
The mitogen-activated protein kinase （MAPK） cell signal transduction pathways play a key role in determining the survival of cells. If these pathways can be controlled, they will prohibit the proliferation of cancer...The mitogen-activated protein kinase （MAPK） cell signal transduction pathways play a key role in determining the survival of cells. If these pathways can be controlled, they will prohibit the proliferation of cancer cells. To attain this goal, the authors utilize many drugs to interact with mitogen-activated protein kinase kinase-1 （MEK1） in MAPK, and use computer aided drug design （CADD） to analyze the ligand activities of proteins in MEKL The results show that in these drugs, the aromatic group in the terminal of the protein and the PHE209 will induce the stacking force, which is highly related to the actual activities of these drugs.展开更多
Background:Risk substances in cosmetics have long been associated with adverse reactions.However,as risk substances become more concealed and diversified,conventional targeted analysis methods are no longer sufficient...Background:Risk substances in cosmetics have long been associated with adverse reactions.However,as risk substances become more concealed and diversified,conventional targeted analysis methods are no longer sufficient to meet regulatory requirements.Objective:To construct a rapid and effective non-targeted screening method for the identification of risk substances,and to provide a high-throughput method for toxicity assessment.Methods:Molecular networking was utilized for the non-targeted screening of risk substances in facial skincare products,and the toxicity of these risk substances was evaluated through molecular docking and quantitative structure-activity relationship(QSAR)models.Results:Through molecular networking,we identified seven known prohibited ingredients,six of which were confirmed using standard substances.In addition,17 potential risk substances were discovered within molecular clusters containing prohibited ingredients,including antibiotics,antihistamines,and phthalates,etc.Notably,chloramphenicol base and N-desmethyl chlorpheniramine exhibited stronger binding affinity to keratin 5/14 than chloramphenicol and chlorpheniramine through molecular docking,respectively.Additionally,toxicity prediction results indicated that the carcinogenicity of antibiotics presented gender differences in mice and rats,and two chlorpheniramine derivatives also showed carcinogenicity in mice.Moreover,of the 24 compounds,11 showed skin sensitization,while 14 caused skin irritation.Furthermore,half of these compounds demonstrated potential developmental toxicity,and only 4-nitrobenzenethiol was found to be mutagenic.Conclusion:In this study,we developed a visualization strategy for non-targeted screening of risk substances and a high-throughput method for initial toxicity assessment of risk substances.展开更多
Objective: European lung cancer screening studies using computed tomography(CT) have shown that a management protocol based on measuring lung nodule volume and volume doubling time(VDT) is more specific for early lung...Objective: European lung cancer screening studies using computed tomography(CT) have shown that a management protocol based on measuring lung nodule volume and volume doubling time(VDT) is more specific for early lung cancer detection than a diameter-based protocol. However, whether this also applies to a Chinese population is unclear. The aim of this study is to compare the diagnostic performance of a volume-based protocol with a diameter-based protocol for lung cancer detection and optimize the nodule management criteria for a Chinese population.Methods: This study has a population-based, prospective cohort design and includes 4000 participants from the Hexi district of Tianjin, China. Participants will undergo low-dose chest CT at baseline and after 1 year. Initially, detected lung nodules will be evaluated for diameter and managed according to a routine diameter-based protocol(Clinical Practice Guideline in Oncology for Lung Cancer Screening, Version 2.2018). Subsequently, lung nodules will be evaluated for volume and management will be simulated according to a volume-based protocol and VDT(a European lung nodule management protocol). Participants will be followed up for 4 years to evaluate lung cancer incidence and mortality. The primary outcome is the diagnostic performance of the European volume-based protocol compared to diameter-based management regarding lung nodules detected using low-dose CT.Results: The diagnostic performance of volume-and diameter-based management for lung nodules in a Chinese population will be estimated and compared.Conclusions: Through the study, we expect to improve the management of lung nodules and early detection of lung cancer in Chinese populations.展开更多
Finding energetic materials with tailored properties is always a significant challenge due to low research efficiency in trial and error.Herein,a methodology combining domain knowledge,a machine learning algorithm,and...Finding energetic materials with tailored properties is always a significant challenge due to low research efficiency in trial and error.Herein,a methodology combining domain knowledge,a machine learning algorithm,and experiments is presented for accelerating the discovery of novel energetic materials.A high-throughput virtual screening(HTVS)system integrating on-demand molecular generation and machine learning models covering the prediction of molecular properties and crystal packing mode scoring is established.With the proposed HTVS system,candidate molecules with promising properties and a desirable crystal packing mode are rapidly targeted from the generated molecular space containing 25112 molecules.Furthermore,a study of the crystal structure and properties shows that the good comprehensive performances of the target molecule are in agreement with the predicted results,thus verifying the effectiveness of the proposed methodology.This work demonstrates a new research paradigm for discovering novel energetic materials and can be extended to other organic materials without manifest obstacles.展开更多
Natural antimicrobial peptides(AMPs)are promising candidates for the development of a new generation of antimicrobials to combat antibiotic-resistant pathogens.They have found extensive applications in the fields of m...Natural antimicrobial peptides(AMPs)are promising candidates for the development of a new generation of antimicrobials to combat antibiotic-resistant pathogens.They have found extensive applications in the fields of medicine,food,and agriculture.However,efficiently screening AMPs from natural sources poses several challenges,including low efficiency and high antibiotic resistance.This review focuses on the action mechanisms of AMPs,both through membrane and non-membrane routes.We thoroughly examine various highly efficient AMP screening methods,including whole-bacterial adsorption binding,cell membrane chromatography(CMC),phospholipid membrane chromatography binding,membranemediated capillary electrophoresis(CE),colorimetric assays,thin layer chromatography(TLC),fluorescence-based screening,genetic sequencing-based analysis,computational mining of AMP databases,and virtual screening methods.Additionally,we discuss potential developmental applications for enhancing the efficiency of AMP discovery.This review provides a comprehensive framework for identifying AMPs within complex natural product systems.展开更多
Screening gene function in vivo is a powerful approach to discover novel drug targets. We present high-throughput screening （HTS） data for 3 762 distinct global gene knockout （KO） mouse lines with viable adult hom...Screening gene function in vivo is a powerful approach to discover novel drug targets. We present high-throughput screening （HTS） data for 3 762 distinct global gene knockout （KO） mouse lines with viable adult homozygous mice generated using either gene-trap or homologous recombination technologies. Bone mass was determined from DEXA scans of male and female mice at 14 weeks of age and by microCT analyses of bones from male mice at 16 weeks of age. Wild-type （WT） cagemates/littermates were examined for each gene KO. Lethality was observed in an additional 850 KO lines. Since primary HTS are susceptible to false positive findings, additional cohorts of mice from KO lines with intriguing HTS bone data were examined. Aging, ovariectomy, histomorphometry and bone strength studies were performed and possible non-skeletal phenotypes were explored. Together, these screens identified multiple genes affecting bone mass： 23 previously reported genes （Calcr, Cebpb, Crtap, Dcstamp, Dkkl, Duoxa2, Enppl, Fgf23, Kissl/Kisslr, Kl （Klotho）, Lrp5, Mstn, Neol, Npr2, Ostml, Postn, Sfrp4, S1c30a5, Sic39a13, Sost, Sumf1, Src, Wnt10b）, five novel genes extensively characterized （Cldn18, Fam20c, Lrrkl, Sgpll, Wnt16）, five novel genes with preliminary characterization （Agpat2, RassfS, Slc10a7, Stc26a7, Slc30a10） and three novel undisclosed genes coding for potential osteoporosis drug targets.展开更多
Objective To develop a high-throughput screening assay for Farnesoid X receptor （FXR） agonists based on mammalian one-hybrid system （a chimera receptor gene system） for the purpose of identifying new lead compound...Objective To develop a high-throughput screening assay for Farnesoid X receptor （FXR） agonists based on mammalian one-hybrid system （a chimera receptor gene system） for the purpose of identifying new lead compounds for dyslipidaemia drug from the chemical library. Methods cDNA encoding the human FXR ligand binding domain （LBD） was amplified by RT-PCR from a human liver total mRNA and fused to the DNA binding domain （DBD） of yeast GAL4 of pBIND to construct a GAL4-FXR （LBD） chimera expression plasmid. Five copies of the GAL4 DNA binding site were synthesized and inserted into upstream of the SV40 promoter of pGL3-promoter vector to construct a reporter plasmid pG5-SV40 Luc. The assay was developed by transient co-transfection with pG5-SV40 Luc reporter plasmid and pBIND-FXR-LBD （189-472） chimera expression plasmid. Results After optimization, CDCA, a FXR natural agonist, could induce expression of the luciferase gene in a dose-dependent manner, and had a signal/noise ratio of 10 and Z＇ factor value of 0.65, Conclusion A stable and sensitive cell-based high-throughput screening model can be used in high-throughput screening for FXR agonists from the synthetic and natural compound library.展开更多
Ion channels are attractive targets for drug discovery as an increasing number of new ion channel targets have been uncovered in diseases, such as pain, cardiovascular disease, and neurological disorders. Despite thei...Ion channels are attractive targets for drug discovery as an increasing number of new ion channel targets have been uncovered in diseases, such as pain, cardiovascular disease, and neurological disorders. Despite their relevance in diseases and the variety of physiological functions they are involved in, ion channels still remain underexploited as drug targets. This, to a large extent, is attributed to the absence of screening technologies that ensure both the quality and the throughput of data. However, an increasing number of assays and technologies have evolved rapidly in the past decades. In this review, we summarized the currently available high-throughput screening technologies in ion channel drug discovery.展开更多
基金The authors are grateful for financial support from the National Key Projects for Fundamental Research and Development of China(2021YFA1500803)the National Natural Science Foundation of China(51825205,52120105002,22102202,22088102,U22A20391)+1 种基金the DNL Cooperation Fund,CAS(DNL202016)the CAS Project for Young Scientists in Basic Research(YSBR-004).
文摘Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors.
基金supported by the Natural Science Foundation of China (Nos.21706106,21536001 and 21322603)the National Key Basic Research Program of China ("973") (No.2013CB733503)+1 种基金the Natural Science Foundation of Jiangsu Normal University(16XLR011)Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carbon dioxide(CO_2) and store methane(CH4), where the latter is a kind of clean energy source with abundant reserves and lower CO_2 emission. Hundreds of thousands of porous materials can be enrolled on the candidate list, but how to quickly identify the really promising ones, or even evolve materials(namely, rational design high-performing candidates) based on the large database of present porous materials? In this context, high-throughput computational techniques, which have emerged in the past few years as powerful tools, make the targets of fast evaluation of adsorbents and evolving materials for CO_2 capture and CH_4 storage feasible. This review provides an overview of the recent computational efforts on such related topics and discusses the further development in this field.
文摘Gastric cancers are caused primarily due to the activation and amplification of the EGFR or HER2 kinases resulting in cell proliferation,adhesion,angiogenesis,and metastasis.Conventional therapies are ineffective due to the intra-tumoral heterogeneity and concomitant genetic mutations.Hence,dual inhibition strategies are recommended to increase potency and reduce cytotoxicity.In this study,we have conducted computational high-throughput screening of the ChemBridge library followed by in vitro assays and identified novel selective inhibitors that have a dual impediment of EGFR/HER2 kinase activities.Diversity-based High-throughput Virtual Screening(D-HTVS)was used to screen the whole ChemBridge small molecular library against EGFR and HER2.The atomistic molecular dynamic simulation was conducted to understand the dynamics and stability of the protein-ligand complexes.EGFR/HER2 kinase enzymes,KATOIII,and Snu-5 cells were used for in vitro validations.The atomistic Molecular Dynamics simulations followed by solvent-based Gibbs binding free energy calculation of top molecules,identified compound C3(5-(4-oxo-4H-3,1-benzoxazin-2-yl)-2-[3-(4-oxo-4H-3,1-benzoxazin-2-yl)phenyl]-1H-isoindole-1,3(2H)-dione)to have a good affinity for both EGFR and HER2.The predicted compound,C3,was promising with better binding energy,good binding pose,and optimum interactions with the EGFR and HER2 residues.C3 inhibited EGFR and HER2 kinases with IC50 values of 37.24 and 45.83 nM,respectively.The GI50 values of C3 to inhibit KATOIII and Snu-5 cells were 84.76 and 48.26 nM,respectively.Based on these findings,we conclude that the identified compound C3 showed a conceivable dual inhibitory activity on EGFR/HER2 kinase,and therefore can be considered as a plausible lead-like molecule for treating gastric cancers with minimal side effects,though testing in higher models with pharmacokinetic approach is required.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(No.2022R1F1A1074339)。
文摘For the advancement of fast-charging sodium-ion batteries(SIBs),the synthesis of cutting-edge cathode materials with superior structural stability and enhanced Na+diffusion kinetics is imperative.Multiphase layered transition metal oxides(LTMOs),which leverage the synergistic properties of two distinct monophasic LTMOs,have garnered significant attention;however,their efficacy under fast-charging conditions remains underexplored.In this study,we developed a high-throughput computational screening framework to identify optimal dopants that maximize the electrochemical performance of LTMOs.Specifically,we evaluated the efficacy of 32 dopants based on P2/O3-type Mn/Fe-based Na_(x)Mn_(0.5)Fe_(0.5)O_(2)(NMFO)cathode material.Multiphase LTMOs satisfying criteria for thermodynamic and structural stability,minimized phase transitions,and enhanced Na^(+)diffusion were systematically screened for their suitability in fast-charging applications.The analysis identified two dopants,Ti and Zr,which met all predefined screening criteria.Furthermore,we ranked and scored dopants based on their alignment with these criteria,establishing a comprehensive dopant performance database.These findings provide a robust foundation for experimental exploration and offer detailed guidelines for tailoring dopants to optimize fast-charging SIBs.
基金supported by the Shandong Provincial Key Research and Development Program(Major Key Technology Project)(2021CXGC010514)the National Natural Science Foundation of China(22008173).
文摘Additives are widely employed to regulate the morphology,size,and agglomeration degree of crystalline materials during crystallization to enhance their functional,physical,and powder properties.However,the existing methods for screening and validating target additives require a large quantity of materials and involve tedious molecular simulation/crystallization experiments,making them time-consuming,resource-intensive,and reliant on the operator’s experience level.To overcome these challenges,we proposed a computer vision-assisted high-throughput additive screening system(CV-HTPASS)which comprises a high-throughput additive screening device,in situ imaging equipment,and an artificial intelligence(AI)-assisted image-analysis algorithm.Using the CV-HTPASS,we performed high-throughput screening experiments on additives to regulate the succinic acid crystal properties,generating thousands of crystal images with diverse crystal morphologies.To extract valuable crystal information from the massive data and improve the analysis accuracy and efficiency,the AI-based image-analysis algorithm was implemented innovatively for the segmentation,classification,and data mining of crystals with four morphologies to further screen the target additive.Subsequently,scale-up crystallization experiments conducted under optimized conditions demonstrated that succinic acid products exhibited a preferred cubic morphology,reduced agglomeration degree,narrowed crystal size distribution,and improved powder properties.The proposed CV-HTPASS offers a highly efficient approach for scale-up experiments.Further,it provides a platform for the screening of additives and the optimization of the powder properties of crystal products in industrial-scale crystallization processes.
基金the support from the Natural Science Foundation of China(U23A20115)the Natural Science Foundation of China(22368027,22078104)+4 种基金Science and Technology Key Project of Guangdong Province(2025B0101060003)the Natural Science Foundation of Guangdong Province(2024A1515012725,2024A1515012724)Guangzhou Municipal Science and Technology Project(2024A04J6251)State Key Laboratory of Pulp and Paper Engineering 2024ZD03Fundamental Research Funds for the Central Universities(2025ZYGXZR023)。
文摘Separating He from CH_(4)or N_(2)is crucial for natural gas He extraction,a prevailing industrial approach.Herein,molecular simulation and machine learning(ML)were combined to screen 801 experimentally synthesized COFs for He/CH_(4)and He/N_(2)separation,either by means of adsorption or membrane separation.Top 10 COFs for 4 different gas separation purposes(CH_(4)/He or N_(2)/He separation with either adsorption or membrane)were identified respectively.The highest adsorption performance score(APSmix,defined as the product of working capacity and adsorption selectivity for mixture gas)reached 447.88 mol/kg and 49.45 mol/kg for CH_(4)/He and N_(2)/He,with corresponding adsorption selectivity of 115.56 and 30.33.He permeabilities of 1.5×10^(6)or 1.2×10^(6)Barrer were achieved for equimolar He/CH_(4)or He/N_(2)mixture gas separations,accompanied by permselectivity of 5.47 and 11.80 well surpassing 2008 Robeson's upper bound.Best performing COFs for adsorption separation are 3D COFs with pore diameter below 0.8 nm while those for membrane separation are 2D COFs with large pores.Additionally,ML models were developed to predict separation performance,with key descriptors identified.The mechanism for how COFs'structure affects their separation performance was also revealed.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Small Groups Project under Grant No.R.G.P.1/191/43.
文摘Malignant melanoma is characterized by both genetic and molecular alterations that activate phosphoinositide 3-kinase(PI3K),and RAS/BRAF pathways.In this work,through diversity-based high-throughput virtual screening we identified a lead molecule that selectively targets PI3K and BRAF^(V600E) kinases.Computational screening,Molecular dynamics simulation and MMPBSA calculations were performed.PI3K and BRAF^(V600E) kinase inhibition was done.A375 and G-361 cells were used for in vitro cellular analysis to determine antiproliferative effects,annexin V binding,nuclear fragmentation and cell cycle analysis.Computational screening of small molecules indicates compound CB-006-3 selectively targets PI3KCG(gamma subunit),PI3KCD(delta subunit)and BRAF^(V600E).Molecular dynamics simulation and MMPBSA bases binding free energy calculations predict a stable binding of CB-006-3 to the active sites of PI3K and BRAF^(V600E).The compound effectively inhibited PI3KCG,PI3KCD and BRAF^(V600E)kinases with respective IC50 values of 75.80,160.10 and 70.84 nM.CB-006-3 controlled the proliferation of A375 and G-361 cells with GI50 values of 223.3 and 143.6 nM,respectively.A dose dependent increase in apoptotic cell population and sub G0/G1 phase of cell cycle were also observed with the compound treatment in addition to observed nuclear fragmentation in these cells.Furthermore,CB-006-3 inhibited BRAF^(V600E),PI3KCD and PI3KCG in both melanoma cells.Collectively,based on the computational modeling and in vitro validations,we propose CB-006-3 as a lead candidate for selectively targeting PI3K and mutant BRAF^(V600E) to inhibit melanoma cell proliferation.Further experimental validations,including pharmacokinetic evaluations in mouse models will identify the druggability of the proposed lead candidate for further development as a therapeutic agent for treating melanoma.
基金financial support from the National Key Research and Development Program of China(2021YFB 3501501)the National Natural Science Foundation of China(No.22225803,22038001,22108007 and 22278011)+1 种基金Beijing Natural Science Foundation(No.Z230023)Beijing Science and Technology Commission(No.Z211100004321001).
文摘The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF structure database is available.In this study,we report a machine learning model for high-throughput screening of MOF catalysts for the CO_(2) cycloaddition reaction.The descriptors for model training were judiciously chosen according to the reaction mechanism,which leads to high accuracy up to 97%for the 75%quantile of the training set as the classification criterion.The feature contribution was further evaluated with SHAP and PDP analysis to provide a certain physical understanding.12,415 hypothetical MOF structures and 100 reported MOFs were evaluated under 100℃ and 1 bar within one day using the model,and 239 potentially efficient catalysts were discovered.Among them,MOF-76(Y)achieved the top performance experimentally among reported MOFs,in good agreement with the prediction.
基金supported by the National Key Research and Development Program of China(No.2021YFB3702102)support from the“Initiation Program for New Teachers”(No.AF0500207)+1 种基金Shanghai Jiao Tong Universitysupport from the Changsha Science and Technology Plan International and Regional Cooperation Project(No.kh2304002)。
文摘Lithium-ion batteries(LiBs)with high energy density have gained significant popularity in smart grids and portable electronics.LiMn_(1-x)Fe_(x)PO_(4)(LMFP)is considered a leading candidate for the cathode,with the potential to combine the low cost of Li Fe PO_(4)(LFP)with the high theoretical energy density of LiMnPO_(4)(LMP).However,quantitative investigation of the intricate coupling between the Fe/Mn ratio and the resulting energy density is challenging due to the parametric complexity.It is crucial to develop a universal approach for the rapid construction of multi-parameter mapping.In this work,we propose an active learning-guided high-throughput workflow for quantitatively predicting the Fe/Mn ratio and the energy density mapping of LMFP.An optimal composition(LiMn_(0.66)Fe_(0.34)PO_(4))was effectively screened from 81 cathode materials via only 5 samples.Model-guided electrochemical analysis revealed a nonlinear relationship between the Fe/Mn ratio and electrochemical properties,including ion mobility and impedance,elucidating the quantitative chemical composition-energy density map of LMFP.The results demonstrated the efficacy of the method in high-throughput screening of LiBs cathode materials.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11304079,11404094,and 11504088)Science and Technology Research Project of Henan Science and Technology Department(Grant No.182102410076)。
文摘The capture of CO_(2)from CO_(2)/H_(2)gas mixtures in syngas is a crucial issue for hydrogen production from steam methane reforming in industry,as the presence of CO_(2)directly affects the purity of H_(2).A combination of a high-throughput screening method and grand canonical Monte Carlo simulation was utilized to evaluate and screen 1725 metal–organic frameworks(MOFs)in detail as a means of determining their adsorption performance for CO_(2)/H_(2)gas mixtures.The adsorption and separation performance of double-linker MOFs was comprehensively evaluated using eight evaluation indicators,namely,the largest cavity diameter,accessible surface area,pore occupied accessible volume,porosity,adsorption selectivity,working capacity,adsorbent performance score and percent regeneration.Six optimal performance frameworks were screened to further study their single-component adsorption and binary competitive adsorption of CO_(2)/H_(2)respectively.The CO_(2)adsorption selectivity at different CO_(2)/H_(2)feed ratios was also evaluated,which indicated their excellent adsorption and separation performance.The microscopic adsorption mechanisms for CO_(2)and H_(2)at the molecular level were investigated by analyzing the radial distribution function and density distribution.This study may provide directional guidance and reference for subsequent experiments on the adsorption and separation of CO_(2)/H_(2).
基金supported by the National Natural Science Foundation of China (22078004)the Research Development Fund from Xi’an Jiaotong-Liverpool University (RDF-16-02-03 and RDF15-01-23)key program special fund (KSF-E-03)。
文摘Deuterium(D_(2)) is one of the important fuel sources that power nuclear fusion reactors. The existing D_(2)/H_(2) separation technologies that obtain high-purity D_(2) are cost-intensive. Recent research has shown that metal-organic frameworks(MOFs) are of good potential for D_(2)/H_(2) separation application. In this work, a high-throughput computational screening of 12020 computation-ready experimental MOFs is carried out to determine the best MOFs for hydrogen isotope separation application. Meanwhile, the detailed structure-performance correlation is systematically investigated with the aid of machine learning. The results indicate that the ideal D_(2)/H_(2) adsorption selectivity calculated based on Henry coefficient is strongly correlated with the 1/ΔAD feature descriptor;that is, inverse of the adsorbility difference of the two adsorbates. Meanwhile, the machine learning(ML) results show that the prediction accuracy of all the four ML methods is significantly improved after the addition of this feature descriptor. In addition, the ML results based on extreme gradient boosting model also revealed that the 1/ΔAD descriptor has the highest relative importance compared to other commonly-used descriptors. To further explore the effect of hydrogen isotope separation in binary mixture, 1548 MOFs with ideal adsorption selectivity greater than 1.5 are simulated at equimolar conditions. The structure-performance relationship shows that high adsorption selectivity MOFs generally have smaller pore size(0.3-0.5 nm) and lower surface area. Among the top 200 performers, the materials mainly have the sql, pcu, cds, hxl, and ins topologies.Finally, three MOFs with high D_(2)/H_(2) selectivity and good D_(2) uptake are identified as the best candidates,of all which had one-dimensional channel pore. The findings obtained in this work may be helpful for the identification of potentially promising candidates for hydrogen isotope separation.
基金Project supported by the National Natural Science Foundation of China(Grant No.51772321)the National Key R&D Program of China(Grant No.2017YFB0701602)the Youth Innovation Promotion Association,China(Grant No.2016005)。
文摘In all-solid-state lithium batteries,the impedance at the cathode/electrolyte interface shows close relationship with the cycle performance.Cathode coatings are helpful to reduce the impedance and increase the stability at the interface effectively.LiTi_(2)(PO_(4))_(3),a fast ion conductor with high ionic conductivity approaching 10^(-3)S·cm^(-1),is adopted as the coating materials in this study.The crystal and electronic structures,as well as the Li^+ion migration properties are evaluated for LTP and its doped derivatives based on density functional theory(DFT)and bond valence(BV)method.Substituting part of Ti sites with element Mn,Fe,or Mg in LTP can improve the electronic conductivity of LTP while does not decrease its high ionic conductivity.In this way,the coating materials with both high ionic conductivities and electronic conductivities can be prepared for all-solid-state lithium batteries to improve the ion and electron transport properties at the interface.
文摘The mitogen-activated protein kinase （MAPK） cell signal transduction pathways play a key role in determining the survival of cells. If these pathways can be controlled, they will prohibit the proliferation of cancer cells. To attain this goal, the authors utilize many drugs to interact with mitogen-activated protein kinase kinase-1 （MEK1） in MAPK, and use computer aided drug design （CADD） to analyze the ligand activities of proteins in MEKL The results show that in these drugs, the aromatic group in the terminal of the protein and the PHE209 will induce the stacking force, which is highly related to the actual activities of these drugs.
基金supported by the Scientific and technological innovation project of Guangdong Provincial Drug Administration(ZA20230069,2024ZDZ04)the Science and Technology Plan Project of Guangdong Provincial(2023A1111120025).
文摘Background:Risk substances in cosmetics have long been associated with adverse reactions.However,as risk substances become more concealed and diversified,conventional targeted analysis methods are no longer sufficient to meet regulatory requirements.Objective:To construct a rapid and effective non-targeted screening method for the identification of risk substances,and to provide a high-throughput method for toxicity assessment.Methods:Molecular networking was utilized for the non-targeted screening of risk substances in facial skincare products,and the toxicity of these risk substances was evaluated through molecular docking and quantitative structure-activity relationship(QSAR)models.Results:Through molecular networking,we identified seven known prohibited ingredients,six of which were confirmed using standard substances.In addition,17 potential risk substances were discovered within molecular clusters containing prohibited ingredients,including antibiotics,antihistamines,and phthalates,etc.Notably,chloramphenicol base and N-desmethyl chlorpheniramine exhibited stronger binding affinity to keratin 5/14 than chloramphenicol and chlorpheniramine through molecular docking,respectively.Additionally,toxicity prediction results indicated that the carcinogenicity of antibiotics presented gender differences in mice and rats,and two chlorpheniramine derivatives also showed carcinogenicity in mice.Moreover,of the 24 compounds,11 showed skin sensitization,while 14 caused skin irritation.Furthermore,half of these compounds demonstrated potential developmental toxicity,and only 4-nitrobenzenethiol was found to be mutagenic.Conclusion:In this study,we developed a visualization strategy for non-targeted screening of risk substances and a high-throughput method for initial toxicity assessment of risk substances.
基金a part of NELCIN-B3 project. The NELCIN-B3 project is funded by The Royal Netherlands Academy of Arts and Sciences (Grant No. PSA_SA_BD_01)Ministry of Science and Technology of the People’s Republic of China+1 种基金National Key R & D Program of China (Grant No. 2016YFE0103000)the financial support from China Scholarship Council (CSC file No. 201708340072)
文摘Objective: European lung cancer screening studies using computed tomography(CT) have shown that a management protocol based on measuring lung nodule volume and volume doubling time(VDT) is more specific for early lung cancer detection than a diameter-based protocol. However, whether this also applies to a Chinese population is unclear. The aim of this study is to compare the diagnostic performance of a volume-based protocol with a diameter-based protocol for lung cancer detection and optimize the nodule management criteria for a Chinese population.Methods: This study has a population-based, prospective cohort design and includes 4000 participants from the Hexi district of Tianjin, China. Participants will undergo low-dose chest CT at baseline and after 1 year. Initially, detected lung nodules will be evaluated for diameter and managed according to a routine diameter-based protocol(Clinical Practice Guideline in Oncology for Lung Cancer Screening, Version 2.2018). Subsequently, lung nodules will be evaluated for volume and management will be simulated according to a volume-based protocol and VDT(a European lung nodule management protocol). Participants will be followed up for 4 years to evaluate lung cancer incidence and mortality. The primary outcome is the diagnostic performance of the European volume-based protocol compared to diameter-based management regarding lung nodules detected using low-dose CT.Results: The diagnostic performance of volume-and diameter-based management for lung nodules in a Chinese population will be estimated and compared.Conclusions: Through the study, we expect to improve the management of lung nodules and early detection of lung cancer in Chinese populations.
基金the Science Challenge Project(TZ2018004)the National Natural Science Foundation of China(21875228 and 21702195)for financial support。
文摘Finding energetic materials with tailored properties is always a significant challenge due to low research efficiency in trial and error.Herein,a methodology combining domain knowledge,a machine learning algorithm,and experiments is presented for accelerating the discovery of novel energetic materials.A high-throughput virtual screening(HTVS)system integrating on-demand molecular generation and machine learning models covering the prediction of molecular properties and crystal packing mode scoring is established.With the proposed HTVS system,candidate molecules with promising properties and a desirable crystal packing mode are rapidly targeted from the generated molecular space containing 25112 molecules.Furthermore,a study of the crystal structure and properties shows that the good comprehensive performances of the target molecule are in agreement with the predicted results,thus verifying the effectiveness of the proposed methodology.This work demonstrates a new research paradigm for discovering novel energetic materials and can be extended to other organic materials without manifest obstacles.
基金supported by the National Natural Science Foundation of China(Grant Nos.:82373835,82304437,and 82173781)Regional Joint Fund Project of Guangdong Basic and Applied Basic Research Fund,China(Grant Nos.:2023A1515110417 and 2023A1515140131)+2 种基金Regional Joint Fund-Key Project of Guangdong Basic and Applied Basic Research Fund,China(Grant No.:2020B1515120033)the Key Field Projects of General Universities in Guangdong Province,China(Grant Nos.:2020ZDZX2057 and 2022ZDZX2056)Medical Scientific Research Foundation of Guangdong Province of China(Grant No.:A2022061).
文摘Natural antimicrobial peptides(AMPs)are promising candidates for the development of a new generation of antimicrobials to combat antibiotic-resistant pathogens.They have found extensive applications in the fields of medicine,food,and agriculture.However,efficiently screening AMPs from natural sources poses several challenges,including low efficiency and high antibiotic resistance.This review focuses on the action mechanisms of AMPs,both through membrane and non-membrane routes.We thoroughly examine various highly efficient AMP screening methods,including whole-bacterial adsorption binding,cell membrane chromatography(CMC),phospholipid membrane chromatography binding,membranemediated capillary electrophoresis(CE),colorimetric assays,thin layer chromatography(TLC),fluorescence-based screening,genetic sequencing-based analysis,computational mining of AMP databases,and virtual screening methods.Additionally,we discuss potential developmental applications for enhancing the efficiency of AMP discovery.This review provides a comprehensive framework for identifying AMPs within complex natural product systems.
文摘Screening gene function in vivo is a powerful approach to discover novel drug targets. We present high-throughput screening （HTS） data for 3 762 distinct global gene knockout （KO） mouse lines with viable adult homozygous mice generated using either gene-trap or homologous recombination technologies. Bone mass was determined from DEXA scans of male and female mice at 14 weeks of age and by microCT analyses of bones from male mice at 16 weeks of age. Wild-type （WT） cagemates/littermates were examined for each gene KO. Lethality was observed in an additional 850 KO lines. Since primary HTS are susceptible to false positive findings, additional cohorts of mice from KO lines with intriguing HTS bone data were examined. Aging, ovariectomy, histomorphometry and bone strength studies were performed and possible non-skeletal phenotypes were explored. Together, these screens identified multiple genes affecting bone mass： 23 previously reported genes （Calcr, Cebpb, Crtap, Dcstamp, Dkkl, Duoxa2, Enppl, Fgf23, Kissl/Kisslr, Kl （Klotho）, Lrp5, Mstn, Neol, Npr2, Ostml, Postn, Sfrp4, S1c30a5, Sic39a13, Sost, Sumf1, Src, Wnt10b）, five novel genes extensively characterized （Cldn18, Fam20c, Lrrkl, Sgpll, Wnt16）, five novel genes with preliminary characterization （Agpat2, RassfS, Slc10a7, Stc26a7, Slc30a10） and three novel undisclosed genes coding for potential osteoporosis drug targets.
基金supported by the Ministry of Science and Technology, PRC in Mega-projects of Science Research During the 10th Five-Year Plan Period (No. 2004AA2Z38784)National Natural Science Foundation of China (No. 30472026).
文摘Objective To develop a high-throughput screening assay for Farnesoid X receptor （FXR） agonists based on mammalian one-hybrid system （a chimera receptor gene system） for the purpose of identifying new lead compounds for dyslipidaemia drug from the chemical library. Methods cDNA encoding the human FXR ligand binding domain （LBD） was amplified by RT-PCR from a human liver total mRNA and fused to the DNA binding domain （DBD） of yeast GAL4 of pBIND to construct a GAL4-FXR （LBD） chimera expression plasmid. Five copies of the GAL4 DNA binding site were synthesized and inserted into upstream of the SV40 promoter of pGL3-promoter vector to construct a reporter plasmid pG5-SV40 Luc. The assay was developed by transient co-transfection with pG5-SV40 Luc reporter plasmid and pBIND-FXR-LBD （189-472） chimera expression plasmid. Results After optimization, CDCA, a FXR natural agonist, could induce expression of the luciferase gene in a dose-dependent manner, and had a signal/noise ratio of 10 and Z＇ factor value of 0.65, Conclusion A stable and sensitive cell-based high-throughput screening model can be used in high-throughput screening for FXR agonists from the synthetic and natural compound library.
基金supported by the State Key Laboratory of Natural and Biomimetic Drugs, Peking University。
文摘Ion channels are attractive targets for drug discovery as an increasing number of new ion channel targets have been uncovered in diseases, such as pain, cardiovascular disease, and neurological disorders. Despite their relevance in diseases and the variety of physiological functions they are involved in, ion channels still remain underexploited as drug targets. This, to a large extent, is attributed to the absence of screening technologies that ensure both the quality and the throughput of data. However, an increasing number of assays and technologies have evolved rapidly in the past decades. In this review, we summarized the currently available high-throughput screening technologies in ion channel drug discovery.
