Addiction to nicotine, and possibly other tobacco constituents, is a major factor that contributes to the difficulties smokers face when attempting to quit smoking. Amongst the various subtypes of nicotinic acetylchol...Addiction to nicotine, and possibly other tobacco constituents, is a major factor that contributes to the difficulties smokers face when attempting to quit smoking. Amongst the various subtypes of nicotinic acetylcholine receptors (nAChRs), the α4β2 subtype plays an important role in mediating the addiction process. The characterization of human α4β2-ligand binding interactions provides a molecular framework for understanding ligand-receptor interactions, rendering insights into mechanisms of nicotine addiction and may furnish a tool for efficiently identifying ligands that can bind the nicotine receptor. Therefore, we constructed a homology model of human α4β2 nAChR and performed molecular docking and molecular dynamics (MD) simulations to elucidate the potential human α4β2-ligand binding modes for eleven compounds known to bind to this receptor. Residues V96, L97 and F151 of the α4 subunit and L111, F119 and F121 of the β2 subunit were found to be involved in hydrophobic interactions while residues S153 and W154 of the α4 subunit were involved in the formation of hydrogen bonds between the receptor and respective ligands. The homology model and its eleven ligand-bound structures will be used to develop a virtual screening program for identifying tobacco constituents that are potentially addictive.展开更多
Alkaline phosphatases(APs) include the placental AP(PLAP), germ cell AP(GCAP), intestinal AP(IAP) and tissue nonspecific AP(TNAP). Over expression of TNAP in smooth muscle cells of kidney and vessels provokes the prog...Alkaline phosphatases(APs) include the placental AP(PLAP), germ cell AP(GCAP), intestinal AP(IAP) and tissue nonspecific AP(TNAP). Over expression of TNAP in smooth muscle cells of kidney and vessels provokes the progress of such serious diseases as end-stage renal disease, idiopathic infantile arterial calcification, ankylosis, osteoarthritis and diabetes. In order to design and optimize the potent TNAP inhibitors, comparative molecular field analysis(CoMFA) and comparative molecular similarity indices analysis(CoMSIA) were used to analyze 3D structure-activity relationships(3D-QSAR) of TNAP inhibitors. The 3D-QSAR model(CoMFA with q^2 = 0.521, r^2 = 0.930; CoMSIA with q^2 = 0.529, r^2 = 0.933) had a good predictability. Surflex-dock was used to reveal the binding mode between the inhibitors and TNAP protein. CoMFA, CoMSIA and docking results provide guidance for the discovery of TNAP inhibitors. Finally, eight new compounds as potential TNAP inhibitors were designed.展开更多
A new descriptor, called vector of topological and structural information for coded and noncoded amino acids (VTSA), was derived by principal component analysis (PCA) from a matrix of 66 topological and structural var...A new descriptor, called vector of topological and structural information for coded and noncoded amino acids (VTSA), was derived by principal component analysis (PCA) from a matrix of 66 topological and structural variables of 134 amino acids. The VTSA vector was then applied into two sets of peptide quantitative structure-activity relationships or quantitative sequence-activity modelings (QSARs/QSAMs). Molded by genetic partial least squares (GPLS), support vector machine (SVM), and immune neural network (INN), good results were obtained. For the datasets of 58 angiotensin converting enzyme inhibitors (ACEI) and 89 elastase substrate catalyzed kinetics (ESCK), the R 2, cross-validation R 2, and root mean square error of estimation (RMSEE) were as follows: ACEI, R cu 2 ?0.82, Q cu 2 ?0.77, E rmse?0.44 (GPLS+SVM); ESCK, R cu 2 ?0.84, Q cu 2 ?0.82, E rmse?0.20 (GPLS+INN), respectively.展开更多
A new set of descriptors,namely score vectors of the zero dimension,one dimension,two dimensions and three dimensions(SZOTT),was derived from principle component analysis of a matrix of 1369 structural variables inclu...A new set of descriptors,namely score vectors of the zero dimension,one dimension,two dimensions and three dimensions(SZOTT),was derived from principle component analysis of a matrix of 1369 structural variables including 0D,1D,2D and 3D information for the 20 coded amino acids. SZOTT scales were then used in cleavage site prediction of human immunodeficiency virus type 1 protease. Linear discriminant analysis(LDA) and support vector machines(SVM) were applied to developing models to predict the cleavage sites. The results obtained by linear discriminant analysis(LDA) and support vector machines(SVM) are as follows. The Matthews correlation coefficients(MCC) by the resubstitution test,leave-one-out cross validation(LOOCV) and external validation are 0.879 and 0.911,0.849 and 0.901,0.822 and 0.846,respectively. The receiver operating characteristic(ROC) analysis showed that the SVM model possesses better simulative and predictive ability in comparison with the LDA model. Satisfactory results show that SZOTT descriptors can be further used to predict cleavage sites of human immunodeficiency virus type 1 protease.展开更多
Cyclin D dependent kinases 4/6 regulate the entry of cells into S phase and are effective target for the discovery of anticancer drugs.In this article,3D-QSAR modeling including comparative molecular field analy-sis(C...Cyclin D dependent kinases 4/6 regulate the entry of cells into S phase and are effective target for the discovery of anticancer drugs.In this article,3D-QSAR modeling including comparative molecular field analy-sis(CoMFA)and comparative molecular similarity indices analysis fields(CoMSIA)was implemented on 52 dual CDK4/6 inhibitors.As a result,we obtained a pretty good 3D-QSAR model,which is CoMFACDK4 with q2 to be 0.543 and r^(2) to be 0.967;CoMSIACDK4 with q2 being 0.518 and r^(2) being 0.937;CoMFACDK6 with q2 to be 0.624 and r^(2) to be 0.984;CoMSIACDK6 with q2 being 0.584 and r^(2) being 0.975.Molecular docking confirmed the important residues for interactions.Molecular dynamics simulation further confirmed binding affinity with key residues of protein,such as Lys22,Lys35,Val96 for CDK4 and Lys43,His100,Val101 for CDK6 at the active sites.Then these results offered new directions to explore new inhibitors of CDK4/6.Finally,we designed 10 novel compounds with promising expected activity and ADME/T properties,and provided referable synthetic routes.展开更多
Acetaldehyde dehydrogenase 1A1 is a hopeful therapeutic target to ovarian cancer. In this present work, 3D-QSAR, molecular docking and molecular dynamics(MD) simulations were implemented on a series of quinoline-based...Acetaldehyde dehydrogenase 1A1 is a hopeful therapeutic target to ovarian cancer. In this present work, 3D-QSAR, molecular docking and molecular dynamics(MD) simulations were implemented on a series of quinoline-based ALDH1A1 inhibitors to investigate novel acetaldehyde dehydrogenase 1A1 inhibitors as anticancer adjuvant drugs for ovarian cancer. Two reliable CoMFA(Q^(2) = 0.583, R^(2) = 0.967) and CoMSIA(Q^(2) = 0.640, R^(2) = 0.977) models of ALDH1A1 inhibitors were established. Novel ALDH1A1 inhibitors were predicted by the 3D-QSAR models. Molecular docking reveals important residues for protein-compound interactions, and the results revealed ALDH1A1 inhibitors had stronger electrostatic interaction and binding affinity with key residues of protein, such as Phe171, Val174 and Cys303. Molecular dynamics simulations further verified the results of molecular docking. The above information provided significant guidance for the design of novel ALDH1A1 inhibitors.展开更多
Total 200 properties related to structural characteristics were employed to represent structures of 400 HA coded proteins of influenza virus as training samples. Some recognition models for HA proteins of avian influe...Total 200 properties related to structural characteristics were employed to represent structures of 400 HA coded proteins of influenza virus as training samples. Some recognition models for HA proteins of avian influenza virus (AIV) were developed using support vector machine (SVM) and linear discriminant analysis (LDA). The results obtained from LDA are as follows: the identification accuracy (Ria) for training samples is 99.8% and Ria by leave one out cross validation is 99.5%. Both Ria of 99.8% for training samples and Ria of 99.3% by leave one out cross validation are obtained using SVM model, respectively. External 200 HA proteins of influenza virus were used to validate the external predictive power of the resulting model. The external Ria for them is 95.5% by LDA and 96.5% by SVM, respectively, which shows that HA proteins of AIVs are preferably recognized by SVM and LDA, and the performances by SVM are superior to those by LDA.展开更多
Aldosterone synthase inhibitors can lessen the production of aldosterone in organisms,which effec-tively affecting the treatment of hypertension.A series of computational approaches like QSAR,docking,DFT and molecular...Aldosterone synthase inhibitors can lessen the production of aldosterone in organisms,which effec-tively affecting the treatment of hypertension.A series of computational approaches like QSAR,docking,DFT and molecular dynamics simulation are applied on 40 benzimidazole derivatives of aldosterone synthase(CYP11B2)in-hibitors.Statistical parameters:Q^(2)=0.877,R^(2)=0.983(CoMFA)and Q^(2)=0.848,R^(2)=0.994(CoMSIA)indicate on good predictive power of both models and DFT’s result illustrates the stability of both models.Besides,Y-randomization test is also performed to ensure the robustness of the obtained 3D-QSAR models.Docking studies show inhibitors rely onπ-πinteraction with residues,such as Phe130,Ala313 and Phe481.Molecular dynamics simulation results further confirm that the hydrophobic interaction with proteins enhances the inhibitor’s inhibitory effect.Based on QSAR studies and molecular docking,we designed novel compounds with enhanced activity against aldosterone synthase.Furthermore,the newly designed compounds are analyzed for their ADMET proper-ties and drug likeness and the results show that they all have excellent bioavailability.展开更多
文摘Addiction to nicotine, and possibly other tobacco constituents, is a major factor that contributes to the difficulties smokers face when attempting to quit smoking. Amongst the various subtypes of nicotinic acetylcholine receptors (nAChRs), the α4β2 subtype plays an important role in mediating the addiction process. The characterization of human α4β2-ligand binding interactions provides a molecular framework for understanding ligand-receptor interactions, rendering insights into mechanisms of nicotine addiction and may furnish a tool for efficiently identifying ligands that can bind the nicotine receptor. Therefore, we constructed a homology model of human α4β2 nAChR and performed molecular docking and molecular dynamics (MD) simulations to elucidate the potential human α4β2-ligand binding modes for eleven compounds known to bind to this receptor. Residues V96, L97 and F151 of the α4 subunit and L111, F119 and F121 of the β2 subunit were found to be involved in hydrophobic interactions while residues S153 and W154 of the α4 subunit were involved in the formation of hydrogen bonds between the receptor and respective ligands. The homology model and its eleven ligand-bound structures will be used to develop a virtual screening program for identifying tobacco constituents that are potentially addictive.
基金supported by the Key Project of Natural Science Foundation of Chongqing(No.cstc2015jcyjBX0080)Science and Technology project of Chongqing Education Commission(KJ1600907)
文摘Alkaline phosphatases(APs) include the placental AP(PLAP), germ cell AP(GCAP), intestinal AP(IAP) and tissue nonspecific AP(TNAP). Over expression of TNAP in smooth muscle cells of kidney and vessels provokes the progress of such serious diseases as end-stage renal disease, idiopathic infantile arterial calcification, ankylosis, osteoarthritis and diabetes. In order to design and optimize the potent TNAP inhibitors, comparative molecular field analysis(CoMFA) and comparative molecular similarity indices analysis(CoMSIA) were used to analyze 3D structure-activity relationships(3D-QSAR) of TNAP inhibitors. The 3D-QSAR model(CoMFA with q^2 = 0.521, r^2 = 0.930; CoMSIA with q^2 = 0.529, r^2 = 0.933) had a good predictability. Surflex-dock was used to reveal the binding mode between the inhibitors and TNAP protein. CoMFA, CoMSIA and docking results provide guidance for the discovery of TNAP inhibitors. Finally, eight new compounds as potential TNAP inhibitors were designed.
基金the Foundations of National High Technology (863) Programme (Grant No. 2006AA02Z312)State New Drug Project (Grant No. 1996ND1035A01)+4 种基金Fok- Yingtung Educational Foundation (Grant No. 980706)State Key Laboratory of Chemo/Biosensing and Chemometrics Foundation (Grant No. KLCB005-0012)Chongqing University Innovation Fund (Grant No. CUIF030506)Chongqing Mu-nicipality Applied Science Fund (Grant No. CASF01-3-6)Momentous Juche Innovation Fund for Tackle Key Problem Items (Grant No. MJIF 06-9-9)
文摘A new descriptor, called vector of topological and structural information for coded and noncoded amino acids (VTSA), was derived by principal component analysis (PCA) from a matrix of 66 topological and structural variables of 134 amino acids. The VTSA vector was then applied into two sets of peptide quantitative structure-activity relationships or quantitative sequence-activity modelings (QSARs/QSAMs). Molded by genetic partial least squares (GPLS), support vector machine (SVM), and immune neural network (INN), good results were obtained. For the datasets of 58 angiotensin converting enzyme inhibitors (ACEI) and 89 elastase substrate catalyzed kinetics (ESCK), the R 2, cross-validation R 2, and root mean square error of estimation (RMSEE) were as follows: ACEI, R cu 2 ?0.82, Q cu 2 ?0.77, E rmse?0.44 (GPLS+SVM); ESCK, R cu 2 ?0.84, Q cu 2 ?0.82, E rmse?0.20 (GPLS+INN), respectively.
基金Supported by the Research on National High-tech R&D Program (the 863 program) (Grant No. 2006AA02Z312)Innovative Group Program for Graduates of Chong- qing University, Science and Innovation Fund (Grant No. 200711C1A0010260)
文摘A new set of descriptors,namely score vectors of the zero dimension,one dimension,two dimensions and three dimensions(SZOTT),was derived from principle component analysis of a matrix of 1369 structural variables including 0D,1D,2D and 3D information for the 20 coded amino acids. SZOTT scales were then used in cleavage site prediction of human immunodeficiency virus type 1 protease. Linear discriminant analysis(LDA) and support vector machines(SVM) were applied to developing models to predict the cleavage sites. The results obtained by linear discriminant analysis(LDA) and support vector machines(SVM) are as follows. The Matthews correlation coefficients(MCC) by the resubstitution test,leave-one-out cross validation(LOOCV) and external validation are 0.879 and 0.911,0.849 and 0.901,0.822 and 0.846,respectively. The receiver operating characteristic(ROC) analysis showed that the SVM model possesses better simulative and predictive ability in comparison with the LDA model. Satisfactory results show that SZOTT descriptors can be further used to predict cleavage sites of human immunodeficiency virus type 1 protease.
基金supported by the key project of Chongqing Natural Science Foundation (cstc2015jcyj BX0080)
文摘Cyclin D dependent kinases 4/6 regulate the entry of cells into S phase and are effective target for the discovery of anticancer drugs.In this article,3D-QSAR modeling including comparative molecular field analy-sis(CoMFA)and comparative molecular similarity indices analysis fields(CoMSIA)was implemented on 52 dual CDK4/6 inhibitors.As a result,we obtained a pretty good 3D-QSAR model,which is CoMFACDK4 with q2 to be 0.543 and r^(2) to be 0.967;CoMSIACDK4 with q2 being 0.518 and r^(2) being 0.937;CoMFACDK6 with q2 to be 0.624 and r^(2) to be 0.984;CoMSIACDK6 with q2 being 0.584 and r^(2) being 0.975.Molecular docking confirmed the important residues for interactions.Molecular dynamics simulation further confirmed binding affinity with key residues of protein,such as Lys22,Lys35,Val96 for CDK4 and Lys43,His100,Val101 for CDK6 at the active sites.Then these results offered new directions to explore new inhibitors of CDK4/6.Finally,we designed 10 novel compounds with promising expected activity and ADME/T properties,and provided referable synthetic routes.
基金supported by the key project of Chongqing natural science foundation(cstc2015jcyjBX0080)。
文摘Acetaldehyde dehydrogenase 1A1 is a hopeful therapeutic target to ovarian cancer. In this present work, 3D-QSAR, molecular docking and molecular dynamics(MD) simulations were implemented on a series of quinoline-based ALDH1A1 inhibitors to investigate novel acetaldehyde dehydrogenase 1A1 inhibitors as anticancer adjuvant drugs for ovarian cancer. Two reliable CoMFA(Q^(2) = 0.583, R^(2) = 0.967) and CoMSIA(Q^(2) = 0.640, R^(2) = 0.977) models of ALDH1A1 inhibitors were established. Novel ALDH1A1 inhibitors were predicted by the 3D-QSAR models. Molecular docking reveals important residues for protein-compound interactions, and the results revealed ALDH1A1 inhibitors had stronger electrostatic interaction and binding affinity with key residues of protein, such as Phe171, Val174 and Cys303. Molecular dynamics simulations further verified the results of molecular docking. The above information provided significant guidance for the design of novel ALDH1A1 inhibitors.
基金Foundations of National High Technology (863) Programme (Grant No. 2006AA02Z312)Innovative Group Programme for Graduates of Chongqing Uni-versity, Science and Innovation Fund (Grant No. 200711C1A0010260)+4 种基金National 111 Programme Introducing Talents of Discipline to Universities (Grant No. 0507111106)Chongqing Municipality Basic and Applied Fundamental Science Fund (Grant No. 01-3-6)National Chunhui Project Foundation (Grant No. 99-4-4+3-7)State Key Laboratory of Chemo/Biosensing and Chemometrics Fund (Grant No.2005012)Fok-Yingtung Educational Foundation (Grant No. 98-7-6)
文摘Total 200 properties related to structural characteristics were employed to represent structures of 400 HA coded proteins of influenza virus as training samples. Some recognition models for HA proteins of avian influenza virus (AIV) were developed using support vector machine (SVM) and linear discriminant analysis (LDA). The results obtained from LDA are as follows: the identification accuracy (Ria) for training samples is 99.8% and Ria by leave one out cross validation is 99.5%. Both Ria of 99.8% for training samples and Ria of 99.3% by leave one out cross validation are obtained using SVM model, respectively. External 200 HA proteins of influenza virus were used to validate the external predictive power of the resulting model. The external Ria for them is 95.5% by LDA and 96.5% by SVM, respectively, which shows that HA proteins of AIVs are preferably recognized by SVM and LDA, and the performances by SVM are superior to those by LDA.
基金supported by the graduate student innovation project of Chongqing University of Technology (clgycx 20202129)
文摘Aldosterone synthase inhibitors can lessen the production of aldosterone in organisms,which effec-tively affecting the treatment of hypertension.A series of computational approaches like QSAR,docking,DFT and molecular dynamics simulation are applied on 40 benzimidazole derivatives of aldosterone synthase(CYP11B2)in-hibitors.Statistical parameters:Q^(2)=0.877,R^(2)=0.983(CoMFA)and Q^(2)=0.848,R^(2)=0.994(CoMSIA)indicate on good predictive power of both models and DFT’s result illustrates the stability of both models.Besides,Y-randomization test is also performed to ensure the robustness of the obtained 3D-QSAR models.Docking studies show inhibitors rely onπ-πinteraction with residues,such as Phe130,Ala313 and Phe481.Molecular dynamics simulation results further confirm that the hydrophobic interaction with proteins enhances the inhibitor’s inhibitory effect.Based on QSAR studies and molecular docking,we designed novel compounds with enhanced activity against aldosterone synthase.Furthermore,the newly designed compounds are analyzed for their ADMET proper-ties and drug likeness and the results show that they all have excellent bioavailability.
