Studies of H4R antagonists using 3D-QSAR,molecular docking and molecular dynamics

Three-dimensional quantitative structure–activity relationship studies were performed on a series of 88 histamine receptor 4 (H4R) antagonists in an attempt to elucidate the 3D structural features required for activity. Several in silico modeling approaches, including comparative molecular field analysis (CoMFA), comparative similarity indices analysis (CoMSIA), molecular docking, and molecular dynamics (MD), were carried out. The results show that both the ligand-based CoMFA model (Q ² = 0.548, R _ncv² = 0.870, R _pre² = 0.879, SEE = 0.410, SEP = 0.386) and the CoMSIA model (Q ² = 0.526, R _ncv² =0.866, R _pre² = 0.848, SEE = 0.416, SEP = 0.413) are acceptable, as they show good predictive capabilities. Furthermore, a combined analysis incorporating CoMFA, CoMSIA contour maps and MD results shows that (1) compounds with bulky or hydrophobic substituents at positions 4–6 in ring A (R2 substituent), positively charged or hydrogen-bonding (HB) donor groups in the R1 substituent, and hydrophilic or HB acceptor groups in ring C show enhanced biological activities, and (2) the key amino acids in the binding pocket are TRP67, LEU71, ASP94, TYR95, PHE263 and GLN266. To our best knowledge, this work is the first to report the 3D-QSAR modeling of these H4R antagonists. The conclusions of this work may lead to a better understanding of the mechanism of antagonism and aid in the design of new, more potent H4R antagonists.     

In silico QSAR studies of anilinoquinolines as EGFR inhibitors

Members of the epidermal growth factor receptor (EGFR) family of proteins are frequently overactive in solid tumors. A relatively new therapeutic approach to inhibit the kinase activity is the use of ATP-competitive small molecules. In silico techniques were employed to identify the key interactions between inhibitors and their protein receptors. A series of EGFR inhibitory anilinoquinolines was studied within the framework of hologram quantitative structure activity relationship (HQSAR), density functional theory (DFT)-based QSAR, and three-dimensional (3D) QSAR (CoMFA/CoMSIA). The HQSAR analysis implied that substitutions at certain sites on the inhibitors play an important role in EGFR inhibition. DFT-based QSAR results suggested that steric and electronic interactions contributed significantly to the activity. Ligand-based 3D-QSAR and receptor-guided 3D-QSAR analyses such as CoMFA and CoMSIA techniques were carried out, and the results corroborated the previous two approaches. The 3D QSAR models indicated that steric and hydrophobic interactions are dominant, and that substitution patterns are an important factor in determining activity. Molecular docking was helpful in identifying a bioactive conformer as well as a plausible binding mode. The docked geometry-based CoMFA model with steric and electrostatic fields effect gave q ² = 0.66, r ² = = 0.94 with r ² _predictive = 0.72. Similarly, CoMSIA with hydrophobic field gave q ² = 0.59, r ² = 0.85 with r ² _predictive = 0.63. Bulky groups around site 3 of ring “C”, and hydrophilic and bulky groups at position 6 of ring “A” are desirable, with a hydrophobic and electron-donating group at site 7 of ring “A” being helpful. Accordingly, potential EGFR inhibitors may be designed by modification of known inhibitors.     

Identification of novel 5-hydroxy-1<Emphasis Type="Italic">H</Emphasis>-indole-3-carboxylates with anti-HBV activities based on 3D QSAR studies

Infection with hepatitis B virus (HBV) is a major cause of liver diseases such as cirrhosis and hepatocellular carcinoma. In our previous studies, we identified indole derivatives that have anti-HBV activities. In this study, we optimize a series of 5-hydroxy-1H-indole-3-carboxylates, which exhibited potent anti-HBV activities, using three-dimensional quantitative structure-activity relationship (3D QSAR) studies with comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The lowest energy conformation of compound 3, which exhibited the most potent anti-HBV activity, obtained from systematic search was used as the template for alignment. The best predictions were obtained with the CoMFA standard model (q ² = 0.689, r ² = 0.965, SEE = 0.082, F = 148.751) and with CoMSIA combined steric, electrostatic, hydrophobic and H-bond acceptor fields (q ² = 0.578, r ² = 0.973, SEE = 0.078, F = 100.342). Both models were validated by an external test set of six compounds giving satisfactory prediction. Based on the clues derived from CoMFA and CoMSIA models and their contour maps, another three compounds were designed and synthesized. Pharmacological assay demonstrated that the newly synthesized compounds possessed more potent anti-HBV activities than before (IC₅₀: compound 35a is 3.1 μmol/l, compound 3 is 4.1 μmol/l). Combining the clues derived from the 3D QSAR studies and from further validation of the 3D QSAR models, the activities of the newly synthesized indole derivatives were well accounted for. Furthermore, this showed that the CoMFA and CoMSIA models proved to have good predictive ability.     

3D-QSAR studies of substituted 1-(3, 3-diphenylpropyl)-piperidinyl amides and ureas as CCR5 receptor antagonists

3D-QSAR studies on the derivatives of 1-(3,3-diphenylpropyl)-piperidinyl amide and urea as CCR5 receptor antagonists were performed by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) methods to rationalize the structural requirements responsible for the inhibitory activity of these compounds. The global minimum energy conformer of the template molecule, the most active and pharmacokinetically stable molecule of the series, was obtained by systematic search and used to build structures of the molecules in the dataset. The best predictions for the CCR5-receptor were obtained with the CoMFA standard model (q ² = 0.787, r ² = 0.962) and CoMSIA model combined steric, electrostatic and hydrophobic fields (q ² = 0.809, r ² = 0.951). The predictive ability of CoMFA and CoMSIA were determined using a test set of 12 compounds giving predictive correlation coefficients of 0.855 and 0.83, respectively, indicating good predictive power. Further, the robustness of the model was verified by bootstrapping analysis. The contour maps produced by the CoMFA and CoMSIA models were used to identify the structural features relevant to the biological activity in this series. Based on the CoMFA and CoMSIA analysis, we have identified some key features in the series that are responsible for CCR5 antagonistic activity which may be used to design more potent 1-(3,3-diphenylpropyl)-piperidinyl derivatives and predict their activity prior to synthesis. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Use of molecular modeling, docking, and 3D-QSAR studies for the determination of the binding mode of benzofuran-3-yl-(indol-3-yl)maleimides as GSK-3β inhibitors

Molecular modeling and docking studies along with three-dimensional quantitative structure relationships (3D-QSAR) studies have been used to determine the correct binding mode of glycogen synthase kinase 3β (GSK-3β) inhibitors. The approaches of comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) are used for the 3D-QSAR of 51 substituted benzofuran-3-yl-(indol-3-yl)maleimides as GSK-3β inhibitors. Two binding modes of the inhibitors to the binding site of GSK-3β are investigated. The binding mode 1 yielded better 3D-QSAR correlations using both CoMFA and CoMSIA methodologies. The three-component CoMFA model from the steric and electrostatic fields for the experimentally determined pIC₅₀ values has the following statistics: R²(cv) = 0.386 nd SE(cv) = 0.854 for the cross-validation, and R² = 0.811 and SE = 0.474 for the fitted correlation. F (3,47) = 67.034, and probability of R² = 0 (3,47) = 0.000. The binding mode suggested by the results of this study is consistent with the preliminary results of X-ray crystal structures of inhibitor-bound GSK-3β. The 3D-QSAR models were used for the estimation of the inhibitory potency of two additional compounds.     

Insights into ET<Subscript>A</Subscript> subtype selectivity of benzodiazepine endothelin receptor antagonists by 3D-QSAR approaches

ET_A subtype selective antagonists constitute a novel and potentially important class of agents for the treatment of pulmonary hypertension, heart failure, and other pathological conditions. In this paper, 60 benzodiazepine derivatives displaying potent activities against ET_A and ET_B subtypes of endothelin receptor were selected to establish the 3D-QSAR models using CoMFA and CoMSIA approaches. These models show excellent internal predictability and consistency, external validation using test-set 19 compounds yields a good predictive power for antagonistic potency. Statistical parameters of models were obtained with CoMFA-ET_A (q ² = 0.787, r ² = 0.935, r ² _pred  = 0.901), CoMFA-ET_B (q ² = 0.842, r ² = 0.984, r ² _pred  = 0.941), CoMSIA-ET_A (q ² = 0.762, r ² = 0.971, r ² _pred  = 0.958) and CoMSIA-ET_B (q ² = 0.771, r ² = 0.974, r ² _pred  = 0.953) respectively. Field contour maps (CoMFA and CoMSIA) corresponding to the ET_A and ET_B subtypes reflects the characteristic similarities and differences between these types. The results of this paper provide valuable information to facilitate structural modifications of the title compounds to increase the inhibitory potency and subtype selectivity of endothelin receptor.