In this article, generalized torsion angles of derivatives of 1 [(2 hydroxyethoxy)methyl] 6 (phenylthio)thymine(HEPT) were calculated, which include abundant three dimensional information of molecules. Molecular simil...In this article, generalized torsion angles of derivatives of 1 [(2 hydroxyethoxy)methyl] 6 (phenylthio)thymine(HEPT) were calculated, which include abundant three dimensional information of molecules. Molecular similarity matrix was built based on the calculated generalized torsion angles. These similarities were taken as the new variables, and the new variables were selected by using Leaps and Bounds regression analysis. Multiple regression analysis and neural networks were performed, and the satisfactory results were achieved by using the neural networks.展开更多
Cancer is one of the most serious issues in human life.Blocking programmed cell death protein 1 and programmed death ligand-1(PD-L1)pathway is one of the great innovations in the last few years,a few numbers of inhibi...Cancer is one of the most serious issues in human life.Blocking programmed cell death protein 1 and programmed death ligand-1(PD-L1)pathway is one of the great innovations in the last few years,a few numbers of inhibitors can be able to block it.(2-Methyl-3-biphenylyl)methanol derivative is one of them.Here,the quantitative structure-activity relationship(QSAR)established twenty(2-methyl-3-biphenylyl)methanol derivatives as the programmed death ligand-1 inhibitors.Density functional theory at the B3LPY/6-31+G(d,p)level was employed to study the chemical structure and properties of the chosen compounds.Highest occupied molecular orbital energy EHOMO,lowest unoccupied molecular orbital energy ELUMO,total energy ET,dipole moment DM,absolute hardnessη,absolute electronegativityχ,softness S,electrophilicityω,energy gap?E,etc.,were observed and determined.Principal component analysis(PCA),multiple linear regression(MLR)and multiple nonlinear regression(MNLR)analysis were carried out to establish the QSAR.The proposed quantitative models and interpreted outcomes of the compounds were based on statistical analysis.Statistical results of MLR and MNLR exhibited the coefficient R^2 was 0.661 and 0.758,respectively.Leave-one-out cross-validation,r_m^2 metric,r_m^2 test,and"Golbraikh&Tropsha’s criteria"analyses were applied for the validation of MLR and MNLR,which indicate two models are statistically significant and well stable with data variation in the external validation towards PD-L1.The obtained results showed that the MNLR model predicts the bioactivity more accurately than MLR,and it may be helpful and supporting for evaluation of the biological activity of PD-L1 inhibitors.展开更多
A quantitative structure–activity relationship(QSAR) was performed to analyze antimalarial activities against the D10 strains of Plasmodium falciparum of triazole-linked chalcone and dienone hybrid derivatives using ...A quantitative structure–activity relationship(QSAR) was performed to analyze antimalarial activities against the D10 strains of Plasmodium falciparum of triazole-linked chalcone and dienone hybrid derivatives using partial least squares regression coupled with stepwise forward–backward variable selection method. QSAR analyses were performed on the available IC50 D10 strains of Plasmodium falciparum data based on theoretical molecular descriptors. The QSAR model developed gave good predictive correlation coefficient(r2) of 0.8994, significant cross validated correlation coefficient(q2) of 0.7689, r2 for external test set)(2predr of 0.8256, coefficient of correlation of predicted data set)(2sepred,r of 0.3276. The model shows that antimalarial activity is greatly affected by donor and electron-withdrawing substituents. The study implicates that chalcone and dienone rings should have strong donor and electron-withdrawing substituents as they increase the activity of chalcone. Results show that the predictive ability of the model is satisfactory, and it can be used for designing similar group of antimalarial compounds. The findings derived from this analysis along with other molecular modeling studies will be helpful in designing of the new potent antimalarial activity of clinical utility.展开更多
The quantitative structure-activity relationship(QSAR) of 2-alkyl-4-(biphenylylmethoxy) pyridine derivatives was studied.Three different alignment methods were used to get the models of the comparative molecular field...The quantitative structure-activity relationship(QSAR) of 2-alkyl-4-(biphenylylmethoxy) pyridine derivatives was studied.Three different alignment methods were used to get the models of the comparative molecular field analysis(CoMFA),the comparative molecular similarity indices analysis(CoMSIA),and the hologram quantitative structure?activity relationship(HQSAR).The statistical results from the established models show believable predictivity based on the cross-validated value(q2>0.5) and the non-validated value(r2>0.9),The analysis on contour maps of CoMFA and CoMSIA models suggests that hydrophobic and hydrogen-bond acceptor fields are important factors that affect the AT1 antagonistic activity of 2-alkyl-4-(biphenylylmethoxy) pyridine derivatives besides the steric and electrostatic fields,The structural modification information from different atom contributions in the HQSAR model is in agreement with that in the 3D-QSAR models.展开更多
Polychlorinated biphenyls(PCBs) can antagonize human pregnane X receptor(hPXR) activation.Such chemicals could pose a serious threat to the reproductive and developmental ability of humans.The quantitative structure a...Polychlorinated biphenyls(PCBs) can antagonize human pregnane X receptor(hPXR) activation.Such chemicals could pose a serious threat to the reproductive and developmental ability of humans.The quantitative structure activity relationship(QSAR) provides a promising method for the estimation of PCBs' antagonistic activity.In this investigation,a QSAR model was developed by using heuristic method and best subset modeling(r2 = 0.873,q2LOO=0.742).The built model was validated externally by splitting the original data set into training and prediction sets.The results of the model derived are as follows:r2 = 0.907,q2LOO=0.709,r2pred=0.676,suggesting developed QSAR model had good robustness and predictive ability.The applicability domain(AD) of the model was assessed by Williams plot.The antagonistic activity(?logKi) of 108 PCBs,which are unavailable by experiment at present,was predicted within the applicability domain of the model.The critical structural features related to the activity of PCBs were identified.展开更多
Abstract The rapid development and production of nanomaterials has created some concerns about their potential hazard on the environment, human health and safety. However, since the list of materials that may gen- era...Abstract The rapid development and production of nanomaterials has created some concerns about their potential hazard on the environment, human health and safety. However, since the list of materials that may gen- erate such concerns is very long, it is impossible to test them all. It is therefore usually recommended to use some small compositional nanomaterial libraries to perform ini- tial toxicity screening, based on which combinatorial libraries are then introduced for more in-depth studies. All nanomaterials in the compositional and combinatorial libraries must be rigorously characterized before any bio- logical studies. In this review, several major categories of physicochemical properties that must be characterized are discussed, along with different analytical techniques that are commonly used. Some case studies from the University of California Center for Environmental Implications of Nanotechnology are also chosen to demonstrate the effec- tive use of compositional and combinatorial nanomaterials libraries to identify the role of some key physicochemical properties and to establish true quantitative structure-ac- tivity relationships. Examples on how to use the knowledge generated from those studies to design safer nanomaterials for improved biological applications are also presented.展开更多
文摘In this article, generalized torsion angles of derivatives of 1 [(2 hydroxyethoxy)methyl] 6 (phenylthio)thymine(HEPT) were calculated, which include abundant three dimensional information of molecules. Molecular similarity matrix was built based on the calculated generalized torsion angles. These similarities were taken as the new variables, and the new variables were selected by using Leaps and Bounds regression analysis. Multiple regression analysis and neural networks were performed, and the satisfactory results were achieved by using the neural networks.
基金the Natural Science Foundation of Jiangsu Province(BK20181128)333 Project of Jiangsu Province(BRA2016518)Jiangsu Provincial Medical Youth Talent(QNRC2016626)。
文摘Cancer is one of the most serious issues in human life.Blocking programmed cell death protein 1 and programmed death ligand-1(PD-L1)pathway is one of the great innovations in the last few years,a few numbers of inhibitors can be able to block it.(2-Methyl-3-biphenylyl)methanol derivative is one of them.Here,the quantitative structure-activity relationship(QSAR)established twenty(2-methyl-3-biphenylyl)methanol derivatives as the programmed death ligand-1 inhibitors.Density functional theory at the B3LPY/6-31+G(d,p)level was employed to study the chemical structure and properties of the chosen compounds.Highest occupied molecular orbital energy EHOMO,lowest unoccupied molecular orbital energy ELUMO,total energy ET,dipole moment DM,absolute hardnessη,absolute electronegativityχ,softness S,electrophilicityω,energy gap?E,etc.,were observed and determined.Principal component analysis(PCA),multiple linear regression(MLR)and multiple nonlinear regression(MNLR)analysis were carried out to establish the QSAR.The proposed quantitative models and interpreted outcomes of the compounds were based on statistical analysis.Statistical results of MLR and MNLR exhibited the coefficient R^2 was 0.661 and 0.758,respectively.Leave-one-out cross-validation,r_m^2 metric,r_m^2 test,and"Golbraikh&Tropsha’s criteria"analyses were applied for the validation of MLR and MNLR,which indicate two models are statistically significant and well stable with data variation in the external validation towards PD-L1.The obtained results showed that the MNLR model predicts the bioactivity more accurately than MLR,and it may be helpful and supporting for evaluation of the biological activity of PD-L1 inhibitors.
文摘A quantitative structure–activity relationship(QSAR) was performed to analyze antimalarial activities against the D10 strains of Plasmodium falciparum of triazole-linked chalcone and dienone hybrid derivatives using partial least squares regression coupled with stepwise forward–backward variable selection method. QSAR analyses were performed on the available IC50 D10 strains of Plasmodium falciparum data based on theoretical molecular descriptors. The QSAR model developed gave good predictive correlation coefficient(r2) of 0.8994, significant cross validated correlation coefficient(q2) of 0.7689, r2 for external test set)(2predr of 0.8256, coefficient of correlation of predicted data set)(2sepred,r of 0.3276. The model shows that antimalarial activity is greatly affected by donor and electron-withdrawing substituents. The study implicates that chalcone and dienone rings should have strong donor and electron-withdrawing substituents as they increase the activity of chalcone. Results show that the predictive ability of the model is satisfactory, and it can be used for designing similar group of antimalarial compounds. The findings derived from this analysis along with other molecular modeling studies will be helpful in designing of the new potent antimalarial activity of clinical utility.
基金Project(20876180) supported by the National Natural Science Foundation of China
文摘The quantitative structure-activity relationship(QSAR) of 2-alkyl-4-(biphenylylmethoxy) pyridine derivatives was studied.Three different alignment methods were used to get the models of the comparative molecular field analysis(CoMFA),the comparative molecular similarity indices analysis(CoMSIA),and the hologram quantitative structure?activity relationship(HQSAR).The statistical results from the established models show believable predictivity based on the cross-validated value(q2>0.5) and the non-validated value(r2>0.9),The analysis on contour maps of CoMFA and CoMSIA models suggests that hydrophobic and hydrogen-bond acceptor fields are important factors that affect the AT1 antagonistic activity of 2-alkyl-4-(biphenylylmethoxy) pyridine derivatives besides the steric and electrostatic fields,The structural modification information from different atom contributions in the HQSAR model is in agreement with that in the 3D-QSAR models.
基金supported by the Science and Technology Development Foundation Key Project of Nanjing Medical University (09NJMUZ16)Natural Science Research Project of Institution of Higher Education of Jiangsu Province (11KJB180006)
文摘Polychlorinated biphenyls(PCBs) can antagonize human pregnane X receptor(hPXR) activation.Such chemicals could pose a serious threat to the reproductive and developmental ability of humans.The quantitative structure activity relationship(QSAR) provides a promising method for the estimation of PCBs' antagonistic activity.In this investigation,a QSAR model was developed by using heuristic method and best subset modeling(r2 = 0.873,q2LOO=0.742).The built model was validated externally by splitting the original data set into training and prediction sets.The results of the model derived are as follows:r2 = 0.907,q2LOO=0.709,r2pred=0.676,suggesting developed QSAR model had good robustness and predictive ability.The applicability domain(AD) of the model was assessed by Williams plot.The antagonistic activity(?logKi) of 108 PCBs,which are unavailable by experiment at present,was predicted within the applicability domain of the model.The critical structural features related to the activity of PCBs were identified.
基金supported by the National Science Foundation and the Environmental Protection Agency to UCCEIN under Cooperative Agreement No. DBI-1266377Partial support was also provided by U.S. Public Health Service Grants (R01 ES016746 and U19 ES019528)
文摘Abstract The rapid development and production of nanomaterials has created some concerns about their potential hazard on the environment, human health and safety. However, since the list of materials that may gen- erate such concerns is very long, it is impossible to test them all. It is therefore usually recommended to use some small compositional nanomaterial libraries to perform ini- tial toxicity screening, based on which combinatorial libraries are then introduced for more in-depth studies. All nanomaterials in the compositional and combinatorial libraries must be rigorously characterized before any bio- logical studies. In this review, several major categories of physicochemical properties that must be characterized are discussed, along with different analytical techniques that are commonly used. Some case studies from the University of California Center for Environmental Implications of Nanotechnology are also chosen to demonstrate the effec- tive use of compositional and combinatorial nanomaterials libraries to identify the role of some key physicochemical properties and to establish true quantitative structure-ac- tivity relationships. Examples on how to use the knowledge generated from those studies to design safer nanomaterials for improved biological applications are also presented.
