Drug target relationship(DTR)prediction is a rapidly evolving area of research in com-putational drug discovery.Despite recent advances in computational solutions that have overcome the challenges of in vitro and in v...Drug target relationship(DTR)prediction is a rapidly evolving area of research in com-putational drug discovery.Despite recent advances in computational solutions that have overcome the challenges of in vitro and in vivo experiments,most computational methods still focus on binary classification.They ignore the importance of binding affinity,which correctly distinguishes between on-targets and off-targets.In this study,we propose a deep learning model based on the microstruc-ture of compounds and proteins to predict drug-target binding affinity(DTA),which utilizes topo-logical structure information of drug molecules and sequence semantic information of proteins.In this model,graph attention network(GAT)is used to capture the deep features of the compound molecular graph,and bidirectional long short-term memory(BiLSTM)network is used to extract the protein sequence features,and the pharmacological context of DTA is obtained by combining the two.The results show that the proposed model has achieved superior performance in both cor-rectly predicting the value of interaction strength and correctly discriminating the ranking of bind-ing strength compared to the state-of-the-art baselines.A case study experiment on COVID-19 con-firms that the proposed DTA model can be used as an effective pre-screening tool in drug discovery.展开更多
Information on co-adherence of different oral bacterial species is important for understanding interspecies interactions within oral microbial community. Current knowledge on this topic is heavily based on pariwise co...Information on co-adherence of different oral bacterial species is important for understanding interspecies interactions within oral microbial community. Current knowledge on this topic is heavily based on pariwise coaggregation of known, cultivable species. In this study, we employed a membrane binding assay coupled with polymerase chain reaction-denaturing gradient gel electrophoresis （PCR-DGGE） to systematically analyze the co-adherence profiles of oral bacterial species, and achieved a more profound knowledge beyond pairwise coaggregation. Two oral bacterial species were selected to serve as ＂bait＂： Fusobacterium nucleatum （F. nucleatum） whose ability to adhere to a multitude of oral bacterial species has been extensively studied for pairwise interactions and Streptococcus mutans （S. mutans） whose interacting partners are largely unknown. To enable screening of interacting partner species within bacterial mixtures, cells of the ＂bait＂ oral bacterium were immobilized on nitrocellulose membranes which were washed and blocked to prevent unspecific binding. The ＂prey＂ bacterial mixtures （including known species or natural saliva samples） were added, unbound ceils were washed off after the incubation period and the remaining cells were eluted using 0.2 mol.L1 glycine. Genomic DNA was extraeted, subjeeted to 16S rRNA PCR amplification and separation of the resulting PCR produets by DGGE. Selected bands were recovered from the gel, sequenced and identified via Nucleotide BLAST searches against different databases. While few bacterial species bound to S. mutans, consistent with previous findings F.. nucleatum adhered to a variety of bacterial species including uncultivable and uneharacterized onesl This new approach can more effectively analyze the co-adherence profiles of oral bacteria, and could facilitate the systematic study of interbacterial binding of oral microbial species.展开更多
Objective: To study the correlation of serum epithelial fatty acid binding protein (E-FABP) with glucose and lipid metabolism and micro inflammatory reaction in obese children. Methods: children diagnosed as simple ob...Objective: To study the correlation of serum epithelial fatty acid binding protein (E-FABP) with glucose and lipid metabolism and micro inflammatory reaction in obese children. Methods: children diagnosed as simple obesity in endocrinology department of my hospital during June 2014 – August 2017 were selected as the obese group, and the health examination children were selected as the control group. The serum was collected and the levels of E-FABP, glucose and lipid metabolism and inflammatory cytokines were determined, peripheral blood was collected and the expression level of insulin signal molecules were measured. Results:serum E-FABP content of obese group was significantly higher than that in the control group;serum total cholesterol (TC), triglyceride (TG), low density lipoprotein cholesterol (LDL-C), Leptin, Chemerin, F-INS, tumor necrosis factor - α (TNF-α), interleukin -1β (IL-β), interleukin-6 (IL-6), soluble intercellular adhesion molecule -1 (sICAM-1) and monocyte chemoattractant protein 1 (MCP1) of obese group were significantly higher than thosein the control group and positively correlated with serum E-FABP content;serum high density lipoprotein cholesterol (HDL-C), lipoprotein (APN), and C1q/tumor necrosis factor-related proteins 12 (CTRP12), Omentin-1 and the expression intensity of insulin receptor substrate 1 (IRS1), IRS2, glucose transporter -4 (GLUT-4) in peripheral blood were significantly lower than those of the control group and negatively correlated with serum E-FABP content. Conclusion: the excessive secretion of E-FABP in obese children is closely related to the disorder of glucose and lipid metabolism and the activation of micro inflammatory reaction.展开更多
Binding kinetics enhancement of a microfluidic biosensor into a micro-channel through the application of a supplementary mechanism has received tremendous attention because of the obtained significant enhancement fact...Binding kinetics enhancement of a microfluidic biosensor into a micro-channel through the application of a supplementary mechanism has received tremendous attention because of the obtained significant enhancement factor. However, biosensor’s performance enhancement using only simple channel engineering is still rarely realized. Herein, we present a novel design of a complex reactive protein (CRP) biosensor into a U-shaped channel with a sensitive membrane located in the middle of the bent zone. Various critical factors affecting the equilibrium binding time are numerically investigated. The turn geometry is then optimized when the arc length along the inner and outer radii is almost the same, which leads to locally minimizing the channel height overhead the reaction surface and improves the analyte transport towards the sensing area. The numerical studies reveal that applying a local narrowing above the reaction surface can notably enhance the trapping and the surface formation of complex antibody-antigen, thus upgrading the biosensor performance. This work puts a significant advance towards microfluidic channel engineering and the exploration of micro-flow injection experimental studies.展开更多
The kinetics of hydrogen oxidation reaction(HOR)declines with orders of magnitude when the electrolyte varies from acid to base.Therefore,unveiling the mechanism of pH-dependent HOR and narrowing the acid-base kinetic...The kinetics of hydrogen oxidation reaction(HOR)declines with orders of magnitude when the electrolyte varies from acid to base.Therefore,unveiling the mechanism of pH-dependent HOR and narrowing the acid-base kinetic gap are indispensable and challenging.Here,the HOR behaviors of palladium phosphides and their counterpart(PdP_2/C,Pd_5P_2/C,Pd_3P/C,and Pd/C)in the whole pH region(from pH 1 to 13)are explored.Unexpectedly,there are non-monotonous relationships between their HOR kinetics and varied pHs,showing distinct inflection-point behaviors(inflection points and acid-base kinetic gaps).We find the inflection-point behaviors can be explained by the discrepant role of pH-dependent hydroxyl binding energy(OHBE)and hydrogen binding energy(HBE)induced HOR kinetics under the entire pH range.We further reveal that the strengthened OHBE is responsible for the earlier appearance of the inflection point and much narrower acid-base kinetic gap.These findings are conducive to understanding the mechanism of the pH-targeted HOR process,and provide a new strategy for rational designing advanced HOR electrocatalysts under alkaline electrolyte.展开更多
Many efforts have been exerted toward screening potential drugs for targets,and conducting wet experiments remains a laborious and time-consuming approach.Artificial intelligence methods,such as Convolutional Neural N...Many efforts have been exerted toward screening potential drugs for targets,and conducting wet experiments remains a laborious and time-consuming approach.Artificial intelligence methods,such as Convolutional Neural Network(CNN),are widely used to facilitate new drug discovery.Owing to the structural limitations of CNN,features extracted from this method are local patterns that lack global information.However,global information extracted from the whole sequence and local patterns extracted from the special domain can influence the drugtarget affinity.A fusion of global information and local patterns can construct neural network calculations closer to actual biological processes.This paper proposes a Fingerprint-embedding framework for Drug-Target binding Affinity prediction(FingerDTA),which uses CNN to extract local patterns and utilize fingerprints to characterize global information.These fingerprints are generated on the basis of the whole sequence of drugs or targets.Furthermore,FingerDTA achieves comparable performance on Davis and KIBA data sets.In the case study of screening potential drugs for the spike protein of the coronavirus disease 2019(COVID-19),7 of the top 10 drugs have been confirmed potential by literature.Ultimately,the docking experiment demonstrates that FingerDTA can find novel drug candidates for targets.All codes are available at http://lanproxy.biodwhu.cn:9099/mszjaas/FingerDTA.git.展开更多
The development of highly efficient electrocatalysts toward hydrogen oxidation reaction(HOR)under alkaline media is essential for the commercialization of alkaline exchange membrane fuel cells(AEMFCs).However,the HOR ...The development of highly efficient electrocatalysts toward hydrogen oxidation reaction(HOR)under alkaline media is essential for the commercialization of alkaline exchange membrane fuel cells(AEMFCs).However,the HOR kinetics in alkaline is two to three orders of magnitude slower than that in acid.More critically,fundamental understanding of the sluggish kinetics derived from the p H effect is still debatable.In this review,the recent development of understanding HOR mechanism and rational design of advanced HOR electrocatalysts are summarized.First,recent advances in the theories focusing on fundamental understandings of HOR under alkaline electrolyte are comprehensively discussed.Then,from the aspect of intermediates binding energy,optimizing hydrogen binding energy(HBE)and increasing hydroxyl binding energy(OHBE),the strategies for designing efficient alkaline HOR catalysts are summarized.At last,perspectives for the future research on alkaline HOR are pointed out.展开更多
Anion exchange membrane(AEM)fuel cells have gained great attention partially due to the advantage of using non-precious metal as catalysts.However,the reaction kinetics of hydrogen oxidation reaction(HOR)is two orders...Anion exchange membrane(AEM)fuel cells have gained great attention partially due to the advantage of using non-precious metal as catalysts.However,the reaction kinetics of hydrogen oxidation reaction(HOR)is two orders of magnitude slower in alkaline systems than in acid.To understand the slower kinetics of HOR in base,two major theories have been proposed,such as(1)pH dependent hydrogen binding energy as a major descriptor for HOR;and(2)bifunctional theory based on the contributions of both hydrogen and hydroxide adsorption for HOR in alkaline electrolyte.Here,we discuss the possible HOR mechanisms in alkaline electrolytes with the corresponding change in their Tafel behavior.Apart from the traditional Tafel-Volmer and Heyrovsky-Volmer HOR mechanisms,the recently proposed hydroxide adsorption step is also discussed to illustrate the difference in HOR mechanisms in acid and base.We further summarize the representative works of alkaline HOR catalyst design(e.g.,precious metals,alloy,intermetallic materials,Ni-based alloys,carbides,nitrides,etc.),and briefly describe their fundamental HOR reaction mechanism to emphasize the difference in elementary reaction steps in alkaline medium.The strategy of strengthening local interaction that facilitates both H2 desorption and Hads+OHads recombination is finally proposed for future HOR catalyst design in alkaline environment.展开更多
To achieve the goals of the peak carbon dioxide emissions and carbon neutral,the development and utilization of sustainable clean energy are extremely important.Hydrogen fuel cells are an important system for converti...To achieve the goals of the peak carbon dioxide emissions and carbon neutral,the development and utilization of sustainable clean energy are extremely important.Hydrogen fuel cells are an important system for converting hydrogen energy into electrical energy.However,the slow hydrogen oxidation reaction(HOR)kinetics under alkaline conditions has limited its development.Therefore,elucidating the catalytic mechanism of HOR in acidic and alkaline media is of great significance for the construction of highly active and stable catalysts.In terms of practicality,Pt is still the primary choice for commercialization of fuel cells.On the above basis,we first introduced the hydrogen binding energy theory and bifunctional theory used to describe the HOR activity,as well as the pH dependence.After that,the rational design strategies of Pt-based HOR catalysts were systematically classified and summarized from the perspective of activity descriptors.In addition,we further emphasized the importance of theoretical simulations and in situ characterization in revealing the HOR mechanism,which is crucial for the rational design of catalysts.Moreover,the practical application of Pt-based HOR catalysts in fuel cells was also presented.In closing,the current challenges and future development directions of HOR catalysts were discussed.This review will provide a deep understanding for exploring the mechanism of highly efficient HOR catalysts and the development of fuel cells.展开更多
Mitochondria are essential for eukaryotic life as powerhouses for energy metabolism. Excessive mitochondrial hyperthermia and reactive oxygen species(ROS) production have been associated with aging, cancer,neurodegene...Mitochondria are essential for eukaryotic life as powerhouses for energy metabolism. Excessive mitochondrial hyperthermia and reactive oxygen species(ROS) production have been associated with aging, cancer,neurodegenerative diseases, and other disorders. Uncoupling protein 2(UCP2) is the effector responsible for regulating cellular thermogenesis and ROS production via dissipating protons in an electrochemical gradient. A UCP2 inhibitor named genipin(GNP) is being researched for its effect on mitochondrial temperature, but little is known about its mechanisms. This study developed several molecular probes to explore the interactions between GNP and UCP2. The result indicated that the hemiacetal structure in GNP could selectively react with the ?-amine of lysine on the UCP2 proton leakage channel through ringopening condensation at the mitochondrial, cellular, and animal levels. A notable feature of the reaction is its temperature sensitivity and ability to conjugate with UCP2 at high fever as lysine-specific covalent inhibitors that prevent mitochondrial thermogenesis. The result not only clarifies the existence of an antipyretic properties of GNP via its irreversible coupling to UCP2, but also reveals a bioorthogonal reaction of hemiacetal iridoid aglycone for selectively binding with the ?-amine of lysine on proteins.展开更多
文摘Drug target relationship(DTR)prediction is a rapidly evolving area of research in com-putational drug discovery.Despite recent advances in computational solutions that have overcome the challenges of in vitro and in vivo experiments,most computational methods still focus on binary classification.They ignore the importance of binding affinity,which correctly distinguishes between on-targets and off-targets.In this study,we propose a deep learning model based on the microstruc-ture of compounds and proteins to predict drug-target binding affinity(DTA),which utilizes topo-logical structure information of drug molecules and sequence semantic information of proteins.In this model,graph attention network(GAT)is used to capture the deep features of the compound molecular graph,and bidirectional long short-term memory(BiLSTM)network is used to extract the protein sequence features,and the pharmacological context of DTA is obtained by combining the two.The results show that the proposed model has achieved superior performance in both cor-rectly predicting the value of interaction strength and correctly discriminating the ranking of bind-ing strength compared to the state-of-the-art baselines.A case study experiment on COVID-19 con-firms that the proposed DTA model can be used as an effective pre-screening tool in drug discovery.
基金supported by Chinese State Scholarship Fund to R. WangUS National Institutes of Health (NIH) Grants DE020102 and GM95373 to W. Shi
文摘Information on co-adherence of different oral bacterial species is important for understanding interspecies interactions within oral microbial community. Current knowledge on this topic is heavily based on pariwise coaggregation of known, cultivable species. In this study, we employed a membrane binding assay coupled with polymerase chain reaction-denaturing gradient gel electrophoresis （PCR-DGGE） to systematically analyze the co-adherence profiles of oral bacterial species, and achieved a more profound knowledge beyond pairwise coaggregation. Two oral bacterial species were selected to serve as ＂bait＂： Fusobacterium nucleatum （F. nucleatum） whose ability to adhere to a multitude of oral bacterial species has been extensively studied for pairwise interactions and Streptococcus mutans （S. mutans） whose interacting partners are largely unknown. To enable screening of interacting partner species within bacterial mixtures, cells of the ＂bait＂ oral bacterium were immobilized on nitrocellulose membranes which were washed and blocked to prevent unspecific binding. The ＂prey＂ bacterial mixtures （including known species or natural saliva samples） were added, unbound ceils were washed off after the incubation period and the remaining cells were eluted using 0.2 mol.L1 glycine. Genomic DNA was extraeted, subjeeted to 16S rRNA PCR amplification and separation of the resulting PCR produets by DGGE. Selected bands were recovered from the gel, sequenced and identified via Nucleotide BLAST searches against different databases. While few bacterial species bound to S. mutans, consistent with previous findings F.. nucleatum adhered to a variety of bacterial species including uncultivable and uneharacterized onesl This new approach can more effectively analyze the co-adherence profiles of oral bacteria, and could facilitate the systematic study of interbacterial binding of oral microbial species.
基金Natural Science Foundation of Hubei Province.Project No:2016CFB368.
文摘Objective: To study the correlation of serum epithelial fatty acid binding protein (E-FABP) with glucose and lipid metabolism and micro inflammatory reaction in obese children. Methods: children diagnosed as simple obesity in endocrinology department of my hospital during June 2014 – August 2017 were selected as the obese group, and the health examination children were selected as the control group. The serum was collected and the levels of E-FABP, glucose and lipid metabolism and inflammatory cytokines were determined, peripheral blood was collected and the expression level of insulin signal molecules were measured. Results:serum E-FABP content of obese group was significantly higher than that in the control group;serum total cholesterol (TC), triglyceride (TG), low density lipoprotein cholesterol (LDL-C), Leptin, Chemerin, F-INS, tumor necrosis factor - α (TNF-α), interleukin -1β (IL-β), interleukin-6 (IL-6), soluble intercellular adhesion molecule -1 (sICAM-1) and monocyte chemoattractant protein 1 (MCP1) of obese group were significantly higher than thosein the control group and positively correlated with serum E-FABP content;serum high density lipoprotein cholesterol (HDL-C), lipoprotein (APN), and C1q/tumor necrosis factor-related proteins 12 (CTRP12), Omentin-1 and the expression intensity of insulin receptor substrate 1 (IRS1), IRS2, glucose transporter -4 (GLUT-4) in peripheral blood were significantly lower than those of the control group and negatively correlated with serum E-FABP content. Conclusion: the excessive secretion of E-FABP in obese children is closely related to the disorder of glucose and lipid metabolism and the activation of micro inflammatory reaction.
文摘Binding kinetics enhancement of a microfluidic biosensor into a micro-channel through the application of a supplementary mechanism has received tremendous attention because of the obtained significant enhancement factor. However, biosensor’s performance enhancement using only simple channel engineering is still rarely realized. Herein, we present a novel design of a complex reactive protein (CRP) biosensor into a U-shaped channel with a sensitive membrane located in the middle of the bent zone. Various critical factors affecting the equilibrium binding time are numerically investigated. The turn geometry is then optimized when the arc length along the inner and outer radii is almost the same, which leads to locally minimizing the channel height overhead the reaction surface and improves the analyte transport towards the sensing area. The numerical studies reveal that applying a local narrowing above the reaction surface can notably enhance the trapping and the surface formation of complex antibody-antigen, thus upgrading the biosensor performance. This work puts a significant advance towards microfluidic channel engineering and the exploration of micro-flow injection experimental studies.
基金supported by the National Key Research and Development Program of China(2021YFB4001200)the National Natural Science Foundation of China(22272121,21972107)the Natural Science Foundation of Hubei Province(2020CFA095)。
文摘The kinetics of hydrogen oxidation reaction(HOR)declines with orders of magnitude when the electrolyte varies from acid to base.Therefore,unveiling the mechanism of pH-dependent HOR and narrowing the acid-base kinetic gap are indispensable and challenging.Here,the HOR behaviors of palladium phosphides and their counterpart(PdP_2/C,Pd_5P_2/C,Pd_3P/C,and Pd/C)in the whole pH region(from pH 1 to 13)are explored.Unexpectedly,there are non-monotonous relationships between their HOR kinetics and varied pHs,showing distinct inflection-point behaviors(inflection points and acid-base kinetic gaps).We find the inflection-point behaviors can be explained by the discrepant role of pH-dependent hydroxyl binding energy(OHBE)and hydrogen binding energy(HBE)induced HOR kinetics under the entire pH range.We further reveal that the strengthened OHBE is responsible for the earlier appearance of the inflection point and much narrower acid-base kinetic gap.These findings are conducive to understanding the mechanism of the pH-targeted HOR process,and provide a new strategy for rational designing advanced HOR electrocatalysts under alkaline electrolyte.
基金funded by the China National Key Research and Development Program(No.2019YFA0904300).
文摘Many efforts have been exerted toward screening potential drugs for targets,and conducting wet experiments remains a laborious and time-consuming approach.Artificial intelligence methods,such as Convolutional Neural Network(CNN),are widely used to facilitate new drug discovery.Owing to the structural limitations of CNN,features extracted from this method are local patterns that lack global information.However,global information extracted from the whole sequence and local patterns extracted from the special domain can influence the drugtarget affinity.A fusion of global information and local patterns can construct neural network calculations closer to actual biological processes.This paper proposes a Fingerprint-embedding framework for Drug-Target binding Affinity prediction(FingerDTA),which uses CNN to extract local patterns and utilize fingerprints to characterize global information.These fingerprints are generated on the basis of the whole sequence of drugs or targets.Furthermore,FingerDTA achieves comparable performance on Davis and KIBA data sets.In the case study of screening potential drugs for the spike protein of the coronavirus disease 2019(COVID-19),7 of the top 10 drugs have been confirmed potential by literature.Ultimately,the docking experiment demonstrates that FingerDTA can find novel drug candidates for targets.All codes are available at http://lanproxy.biodwhu.cn:9099/mszjaas/FingerDTA.git.
基金financially supported by the National Key Research and Development program of China(2018YFB1502302)the National Natural Science Foundation of China(21972107)+1 种基金the Natural Science Foundation of Hubei Province(2020CFA095)the Natural Science Foundation of Jiangsu Province(BK20191186)。
文摘The development of highly efficient electrocatalysts toward hydrogen oxidation reaction(HOR)under alkaline media is essential for the commercialization of alkaline exchange membrane fuel cells(AEMFCs).However,the HOR kinetics in alkaline is two to three orders of magnitude slower than that in acid.More critically,fundamental understanding of the sluggish kinetics derived from the p H effect is still debatable.In this review,the recent development of understanding HOR mechanism and rational design of advanced HOR electrocatalysts are summarized.First,recent advances in the theories focusing on fundamental understandings of HOR under alkaline electrolyte are comprehensively discussed.Then,from the aspect of intermediates binding energy,optimizing hydrogen binding energy(HBE)and increasing hydroxyl binding energy(OHBE),the strategies for designing efficient alkaline HOR catalysts are summarized.At last,perspectives for the future research on alkaline HOR are pointed out.
文摘Anion exchange membrane(AEM)fuel cells have gained great attention partially due to the advantage of using non-precious metal as catalysts.However,the reaction kinetics of hydrogen oxidation reaction(HOR)is two orders of magnitude slower in alkaline systems than in acid.To understand the slower kinetics of HOR in base,two major theories have been proposed,such as(1)pH dependent hydrogen binding energy as a major descriptor for HOR;and(2)bifunctional theory based on the contributions of both hydrogen and hydroxide adsorption for HOR in alkaline electrolyte.Here,we discuss the possible HOR mechanisms in alkaline electrolytes with the corresponding change in their Tafel behavior.Apart from the traditional Tafel-Volmer and Heyrovsky-Volmer HOR mechanisms,the recently proposed hydroxide adsorption step is also discussed to illustrate the difference in HOR mechanisms in acid and base.We further summarize the representative works of alkaline HOR catalyst design(e.g.,precious metals,alloy,intermetallic materials,Ni-based alloys,carbides,nitrides,etc.),and briefly describe their fundamental HOR reaction mechanism to emphasize the difference in elementary reaction steps in alkaline medium.The strategy of strengthening local interaction that facilitates both H2 desorption and Hads+OHads recombination is finally proposed for future HOR catalyst design in alkaline environment.
基金support of this research by the National Natural Science Foundation of China(Nos.22179034 and 22279030)the Natural Science Foundation of Heilongjiang Province(No.ZD2023B002).
文摘To achieve the goals of the peak carbon dioxide emissions and carbon neutral,the development and utilization of sustainable clean energy are extremely important.Hydrogen fuel cells are an important system for converting hydrogen energy into electrical energy.However,the slow hydrogen oxidation reaction(HOR)kinetics under alkaline conditions has limited its development.Therefore,elucidating the catalytic mechanism of HOR in acidic and alkaline media is of great significance for the construction of highly active and stable catalysts.In terms of practicality,Pt is still the primary choice for commercialization of fuel cells.On the above basis,we first introduced the hydrogen binding energy theory and bifunctional theory used to describe the HOR activity,as well as the pH dependence.After that,the rational design strategies of Pt-based HOR catalysts were systematically classified and summarized from the perspective of activity descriptors.In addition,we further emphasized the importance of theoretical simulations and in situ characterization in revealing the HOR mechanism,which is crucial for the rational design of catalysts.Moreover,the practical application of Pt-based HOR catalysts in fuel cells was also presented.In closing,the current challenges and future development directions of HOR catalysts were discussed.This review will provide a deep understanding for exploring the mechanism of highly efficient HOR catalysts and the development of fuel cells.
基金supported by the National Natural Science Foundation of China(No.81973449)the National Key Research and Development Program of China(Nos.2018YFC1704800 and 2018YFC1704805)。
文摘Mitochondria are essential for eukaryotic life as powerhouses for energy metabolism. Excessive mitochondrial hyperthermia and reactive oxygen species(ROS) production have been associated with aging, cancer,neurodegenerative diseases, and other disorders. Uncoupling protein 2(UCP2) is the effector responsible for regulating cellular thermogenesis and ROS production via dissipating protons in an electrochemical gradient. A UCP2 inhibitor named genipin(GNP) is being researched for its effect on mitochondrial temperature, but little is known about its mechanisms. This study developed several molecular probes to explore the interactions between GNP and UCP2. The result indicated that the hemiacetal structure in GNP could selectively react with the ?-amine of lysine on the UCP2 proton leakage channel through ringopening condensation at the mitochondrial, cellular, and animal levels. A notable feature of the reaction is its temperature sensitivity and ability to conjugate with UCP2 at high fever as lysine-specific covalent inhibitors that prevent mitochondrial thermogenesis. The result not only clarifies the existence of an antipyretic properties of GNP via its irreversible coupling to UCP2, but also reveals a bioorthogonal reaction of hemiacetal iridoid aglycone for selectively binding with the ?-amine of lysine on proteins.
