A 3D-QSAR study was conducted to analyze the anti-excitatory activity(p E)of benzodiazepinooxazole derivatives to mice by the comparative molecular field analysis(CoMFA)method.Among the 54 active molecules,a training set of 46 compounds was randomly selected to construct the CoMFA model;the remaining compounds,together with template molecule(No.54)and two newly designed molecules constitute a test set of 17 compounds to validate the model.The obtained cross-validation coefficient(R_(cv)^(2)),the non-cross validation coefficient(R^(2)),and the test value F of the CoMFA model for training set are 0.516,0.899,and 57.57,respectively.The model was used to predict the activities of all compounds in the training and testing sets,and the results indicated that the model had good correlation,strong stability and good predictability.Based on the 3D contour maps,eight novel benzodiazepinooxazole derivatives with higher anti-excitatory activity were designed.However,the effectiveness of these novel benzodiazepinooxazole derivatives is still needed to be verified by the experimental results.
Comparative molecular field analysis(CoMFA)techniques were used to perform three-dimensional quantitative structure-activity relationship(3D-QSAR)studies on the anti-tumor activity(pIH and pIC)of 28 fluoroquinolon-3-yl s-triazole sulfide-ketone derivatives(FQTSDs)against two cancer cell lines,including human hepatoma Hep-3B cells and human pancreatic cancer Capan-1 cells.23 compounds were randomly selected as the training set to establish the prediction models,which were verified by the test set of 6 compounds containing template molecule.The obtained cross-validation(Rcv2)and non-cross-validation correlation coefficients(R2)of the CoMFA models were 0.477 and 0.850 for pIH,and 0.421 and 0.836 for pIC,respectively.The contributions of steric and electrostatic fields to pIH were determined to be 48.1%and 51.9%,and those to pIC were 49.4%and 50.6%,respectively.The CoMFA models were then used to predict the activities of the compounds in the training and testing sets,and the models had a strong stability and good predictability.Based on the 3D contour maps,four novel FQTSDs with a higher anti-tumor activity were designed.However,the effectiveness of these novel FQTSDs is still needed to be verified by experimental results.
A three-dimensional quantitative structure-activity relationship(3 D-QSAR) study was conducted to analyze the A1 AR density(Bmax) of 56 3-aroyl-5-substituted thiophene derivatives(ASTDs) in human A1 Chinese hamster ovary(hA1 CHO) membranes by the comparative molecular field analysis(CoMFA) method. A training set of 45 compounds was used to establish the predictive model, which was verified by the test set of 17 compounds containing template molecule and 5 newly designed molecules. The cross-validation(R2 cv) and non-cross-validation(R2) coefficients of the training set were 0.655 and 0.959, respectively. The model was used to predict the activities of the compounds of the training and test sets, and the results indicated that the models had strong stability and good prediction ability. According to model analysis, the contribution of steric and electrostatic fields was 51.4% and 48.6%, respectively. Based on the 3 D contour maps, five excellent ASTDs agonists were designed, which need to be further verified by biomedical experiments.
A molecular electronegativity distance vector(M_t)based on 13 atomic types has been used to describe the structures of 19 conjugates(LHCc)of levofloxacin-thiadiazole HDAC inhibitor(HDACi)and related inhibitory activities(pH_i,i=1,2,6)of LHCc against histone deacetylases(HDACs,such as HDAC1,HDAC2 and HDAC6).The quantitative structure-activity relationships(QSAR)were established by using leaps-and-bounds regression analysis for the inhibitory activities(pH_i)of 19 above compounds to HDAC1,HDAC2 and HDAC6 along with M_t.The correlation coefficients(R^2)and the leave-one-out(LOO)cross validation R_(cv)^(2 )for the pH_1,pH_(2 )and pH_(6 )models were 0.976 and 0.949;0.985 and 0.977;0.976 and 0.932,respectively.The QSAR models had favorable correlations,as well as robustness and good prediction capability by R^2,F,R^2_(cv),A_(IC),F_(IT )and V_(IF )tests.Validated by using 3876 training sets,the models have good external prediction ability.The results indicate that the molecular structural units:–CH_g–(g=1,2),–NH_2,–OH,=O,–O–and–S–are the main factors which can affect the inhibitory activity of pH_1,pH_(2 )as well as pH_(6 )bioactivities of these compounds directly.Accordingly,the main interactions between HDACs inhibitor and HDACs are hydrophobic interaction,hydrogen bond,and coordination with Zn^(2+)to form compounds,which is consistent with the results in reports.
Density functional theory(DFT)-B3LYP level with the 6-311G**(d,p) basis set was used to calculate a set of molecular quantum chemical descriptors of 12 chloroanilines. Quantitative structure-activity relationship(QSAR) models of the bioconcentration factors(BCF) of the anilines in fish were established using some of the following calculated descriptors: EHOMO, ENHOMO, ELUMO, ENLUMO, ΔE1(= ELUMO- EHOMO), ΔE2(= ENLUMO- ENHOMO), dipole moment(μ), molecular volume(V), vibrational energy of 0 K(Ev), thermodynamic energy(E), heat capacity(Cv), entropy(Sm) and the charge of benzene ring(Qph). Using the variable selection and leaps-and-bounds regression, the quantum chemical descriptors derived directly from the molecular structures were employed to develop a linear QSAR model between the bioconcentration factors(BCF) and two descriptors(Sm, ENHOMO) of 12 chloroanilines. Statistically, the most significant one is a two-parameter linear equation with the correlation coefficient(R2) of 0.981 and cross-validated correlation coefficient(Rcv2) of 0.967. The established QSAR model has good stability and predictability based on the results from Rcv2 of leave-one-out cross-validation, AIC, FIT and tα/2. The quantum chemical analyses were performed from two aspects of frontier molecular orbital and entropy. The results show that two structural describers are crucial to the bioconcentration activity of chloroanilines.
