Exploring QSAR for CYP11B2 binding affinity and CYP11B2/CYP11B1 selectivity of diverse functional compounds using GFA and G/PLS techniques

A data set of a series of 132 structurally diverse compounds with cytochrome 11B2 and 11B1 (CYP11B2 and CYP11B1) enzyme inhibitory activities was subjected to molecular shape analysis to explore contributions of shape features as well as electronic, structural, and physicochemical parameters toward enzyme inhibitory activities, in search of appropriate molecular scaffolds with optimum substitutions for highly potent CYP11B2 inhibitors. Genetic function approximation (GFA) and genetic partial least squares (G/PLS) were used as chemometric tools for modeling, and the derived equations were of acceptable statistical quality considering both internal and external validation parameters (Q²: 0.514–0.659, R²_pred: 0.510–0.734). The G/PLS models with spline option for CYP11B2 and CYP11B1 inhibition and selectivity modeling appeared to be the best models based on r_m²_(overall) criterion. The study indicates the importance of the pyridinylnaphthalene and pyridylmethylene-indane scaffolds with less polar and electrophilic substituents for optimum CYP11B2 inhibitory activity and CYP11B2/CYP11B1 selectivity.     

Pharmacophore mapping,molecular docking and QSAR studies of structurally diverse compounds as CYP2B6 inhibitors

Pharmacophore mapping, molecular docking and quantitative structure–activity relationship (QSAR) studies were carried out for a structurally diverse set of 48 compounds as CYP2B6 inhibitors. The generated best pharmacophore hypotheses from the three methods of conformer generation (FAST, BEST and conformer algorithm based on energy screening and recursive buildup) indicate the importance of two features, namely, hydrogen bond acceptor [electron-rich centre] and ring aromaticity. The distance between the two centres of the important features for ideal inhibitors varied from 5.82 to 6.03 Å. The chemometric tools used for the QSAR analysis were genetic function approximation (GFA) and genetic partial least squares. The developed QSAR models indicate the importance of an electron-rich centre, size of molecule, impact of branching and ring system and distribution of charges in the molecular surface. The docking study confirms the importance of an electron-rich centre for binding with the iron atom of the cytochrome enzyme. A GFA model with spline option was found to be the best model based on internal validation as well as the r ² _{m (overall)} criterion (Q ² = 0.772, r ² _{m (overall)} = 0.774). According to the external prediction statistics (R ² _pred = 0.876), another GFA-derived model with spline option outperforms the remaining models.     

Predicting genotoxicity of aromatic and heteroaromatic amines using electrotopological state indices

A quantitative structure-activity relationship (QSAR) model relating electrotopological state (E-state) indices and mutagenic potency was previously described by Cash [Mutat. Res. 491 (2001) 31-37] using a data set of 95 aromatic amines published by Debnath et al. [Environ. Mol. Mutagen. 19 (1992) 37-52]. Mutagenic potency was expressed as the number of Salmonella typhimurium TA98 revertants per nmol (LogR). Earlier work on the development of QSARs for the prediction of genotoxicity indicated that numerous methods could be effectively employed to model the same aromatic amines data set, namely, Debnath et al.; Maran et al. [Quant. Struct.-Act. Relat. 18 (1999) 3-10]; Basak et al. [J. Chem. Inf. Comput. Sci. 41 (2001) 671-678]; Gramatica et al. [SAR QSAR Environ. Res. 14 (2003) 237-250]. However, results obtained from external validations of those models revealed that the effective predictivity of the QSARs was well below the potential indicated by internal validation statistics (Debnath et al., Gramatica et al.). The purpose of the current research is to externally validate the model published by Cash using a data set of 29 aromatic amines reported by Glende et al. [Mutat. Res. 498 (2001) 19-37; Mutat. Res. 515 (2002) 15-38] and to further explore the potential utility of using E-state sums for the prediction of mutagenic potency of aromatic amines.     

Binding conformations and QSAR of CA-4 analogs as tubulin inhibitors

A theoretical study on the binding conformations and the quantitative structure–activity relationship (QSAR) of combretastatin A4 (CA-4) analogs as inhibitors toward tubulin has been carried out using docking analysis and comparative molecular field analysis (CoMFA). The appropriate binding orientations and conformations of these compounds interacting with tubulin were revealed by the docking study; and a 3D-QSAR model showing significant statistical quality and satisfactory predictive ability was established, in which the correlation coefficient (R²) and cross-validation coefficient (q²) were 0.955 and 0.66, respectively. The same model was further applied to predict the pIC₅₀ values for 16 congeneric compounds as external test set, and the predictive correlation coefficient R²_pred reached 0.883. Other tests on additional validations further confirmed the satisfactory predictive power of the model. In this work, it was very interesting to find that the 3D topology structure of the active site of tubulin from the docking analysis was in good agreement with the 3D-QSAR model from CoMFA for this series of compounds. Some key structural factors of the compounds responsible for cytotoxicity were reasonably presented. These theoretical results can offer useful references for understanding the action mechanism and directing the molecular design of this kind of inhibitor with improved activity.     

Synthesis,crystal structure and biological evaluation of new phosphoramide derivatives as urease inhibitors using docking,QSAR and kinetic studies

In an attempt to achieve a new class of phosphoramide inhibitors with high potency and resistance to the hydrolysis process against urease enzyme, we synthesized a series of bisphosphoramide derivatives (01–43) and characterized them by various spectroscopic techniques. The crystal structures of compounds 22 and 26 were investigated using X-ray crystallography. The inhibitory activities of the compounds were evaluated against the jack bean urease and were compared to monophosphoramide derivatives and other known standard inhibitors. The compounds containing aromatic amines and their substituted derivatives exhibited very high inhibitory activity in the range of IC₅₀ = 3.4–1.91 × 10⁻¹⁰ nM compared with monophosphoramides, thiourea, and acetohydroxamic acid. It was also found that derivatives with PO functional groups have higher anti-urease activity than those with PS functional groups. Kinetics and docking studies were carried out to explore the binding mechanism that showed these compounds follow a mixed-type mechanism and, due to their extended structures, can cover the entire binding pocket of the enzyme, reducing the formation of the enzyme-substrate complex. The quantitative structure-activity relationship (QSAR) analysis also revealed that the interaction between the enzyme and inhibitor is significantly influenced by aromatic rings and PO functional groups. Collectively, the data obtained from experimental and theoretical studies indicated that these compounds can be developed as appropriate candidates for urease inhibitors in this field.     

QSAR studies on 4-anilino-3-quinolinecarbonitriles as Src kinase inhibitors using robust PCA and both linear and nonlinear models

Quantitative structure-activity relationship (QSAR) studies have been carried out on 4-anilino-3-quinolinecarbonitriles, a set of novel Src kinase inhibitors, with the aim of dissecting the structural requirements for Src inhibitory activities. After outlier identification using robust principal component analysis (robust PCA), linear models based on forward selection combined with multiple linear regression, (FS-MLR), enhanced replacement method followed by multiple linear regression (ERM) and a nonlinear model using support vector regression (SVR) were constructed and compared. All models were rigorously validated using leave-one-out cross-validation (LOOCV), 5-fold cross-validations (5-CV) and shuffling external validation (SEVs). ERM seems to outperform both FS-MLR and SVR evidenced by better prediction performance (n?=?35, R²_training?=?0.918, R²_pred?=?0.928). Robustness and predictive ability of ERM model were also evaluated. The generated QASR model revealed that the Src inhibitory activity of 4-anilino-3-quinolinecarbonitriles could be associated with the size of substituents in the C7 position and the steric hindrance effect. The results of the present study may be of great help in designing novel 4-anilino-3-quinolinecarbonitriles with more potent Src kinase inhibitory activity.