Three-dimensional QSAR Studies Research Articles

6-amide-2-aryl benzoxazole/benzimidazole derivatives as VEFGR-2 inhibitors in two-and three-dimensional QSAR studies: topomer CoMFA and HQSAR

The vascular endothelial growth factor (VEGF) is the main target of tumor treatment. VEGFR-2 is the main functional receptor of VEGF, which is involved in the regulation of angiogenesis. Based on hologram quantitative structure activity relationships (HQSAR) and topomer comparative molecular field analysis (topomer CoMFA), the contribution of 6-amide-2-aryl benzoxazole/benzimidazole derivatives (VEGFR-2 kinase inhibitors) to these structures was discussed and the corresponding modification strategies were proposed. The most effective HQSAR and topomer CoMFA models are generated by using a training set of 33 compounds. In order to ensure the robustness of the model, the randomization test was used, and 11 compounds were selected as the test set. The results show that the q2 of cross-validation is 0.646/0.659, and the r2 of non-cross-validation is 0.871/0.867, respectively. The data show that both models are reliable. Topomer CoMFA’s steric/electrostatic contour and HQSAR’s atomic contribution map show the structural characteristics controlling its inhibition ability. In addition, molecular docking is also used to study the interaction between these drugs and large proteins, and the ligand pair is connected to the active site of VEGFR-2 kinase, revealing the possible biological active conformation. This study showed that there was a wide interaction between 6-amide-2-aryl benzoxazole/benzimidazole derivatives and Hrg136 and Tyr356 residues of VEGFR-2 kinase active site. Finally, we used ADMET properties and drug-like properties to predict the newly designed molecules, and the results showed that they meet the conditions for becoming drugs and are expected to become potential anti-VEGFR-2 inhibitors. This study can provide a theoretical reference for the synthesis of target products of VEGFR-2 inhibitors.

Two- and three-dimensional QSAR studies on hURAT1 inhibitors with flexible linkers: topomer CoMFA and HQSAR.

hURAT1 (human urate transporter 1) is a successful target for hyperuricemia. Recently, the modification work on hURAT1 inhibitors showed that the flexible linkers would benefit biological activity. The study aimed to investigate the contribution of the linkers and give modification strategies on this kind of structures based on QSAR models (HQSAR and topomer CoMFA). The most effective HQSAR and topomer CoMFA models were generated by applying the training set containing 63 compounds, with the cross-validated q2 values of 0.869/0.818 and the non-cross-validated correlation coefficients r2 of 0.951/0.978, respectively. The Y-randomization test was applied to ensure the robustness of the models. The external predictive correlation coefficient (rpred2) grounded on the external test set (21 compounds) of two models was 0.910 and 0.907, respectively. In addition, the models were validated by Golbraikh-Tropsha and Roy methods, as well as other statistical metrics. The results showed that both models were reliable. Topomer CoMFA steric/electrostatic contours and HQSAR atomic contribution maps illustrated the structural features which governed their inhibitory potency. The dependable results could provide important insights to guide the designing of more potential hURAT1 inhibitors.

Comprehensive two and three-dimensional QSAR studies of 3-substituted 6-butyl-1,2dihydropyridin-2-ones derivatives as angiotensin II receptor antagonists

In this paper, an attempt was made to develop a two and three-dimensional QSAR models on a series of 3-substituted 6-butyl-1,2 dihydropyridin-2-ones derivatives acting as angiotensin II receptor antagonists using partial least squares regression method. Various 2D descriptors were calculated and used in the present analysis. For model validation, the dataset was divided into various training and test sets using random selection procedures. The whole dataset was divided into training set (24 compounds) and test set (5 compounds). The statistically significant best 2D-QSAR model having correlation coefficient (r 2 = 0.9062) was selected for further study. The model was further validated by means of crossed squared correlation coefficient (q 2 = 0.7314 and pred_r 2 = 0.8133) which shows model has good predictive ability. The optimum QSAR model showed that the parameters SdsCHE-index, T_N_N_3, fluorines count, and SaaNHE-index contributed highly positive, while SsCH3count contributed negatively for antihypertensive activity. Using kNNMFA approach, various 3D-QSAR models were generated and selected on the basis of q 2 and predictive r 2 values. 3D-QSAR study was performed using k-nearest neighbor molecular field analysis approach for steric, electrostatic, and hydrophobic fields. Molecular field analysis was used to construct the best 3D-QSAR model using simulated annealing method. The significant best 3D-QSAR model-6 having model with good external and internal predictivity for the training and test sets has shown cross-validation (q 2) and external validation (pred_r2) values of 0.8534 and 0.8020, respectively. The steric, electrostatic, and hydrophobic descriptors at the grid points S_415, S_1059, E_1523, E_1045, E_1308, and H_153 play an important role in the design of new molecule. This model was found to yield reliable clues for further optimization of 3-substituted 6-butyl-1,2dihydropyridin-2-ones in the data set. The information rendered by 2D- and 3D-QSAR models may lead to a better understanding of structural requirements of 3-substituted 6-butyl-1,2dihydropyridin-2-ones derivatives and also aid in designing novel potent antihypertensive molecules.

Two- and three-dimensional QSAR studies on benzyl amide-ketoacid inhibitors of HIV integrase and their reduced analogues

The discovery of clinically relevant inhibitors of HIV-integrase for antiviral therapy has proven to be a challenging task. Ketoacid-derived inhibitors selectively inhibit the strand transfer reaction of HIV-integrase. To elucidate the structural properties required for HIV-integrase inhibitory activity, we present here the results of two- and three-dimensional (2D and 3D) QSAR studies of a series of 24 benzyl amide derivatives. The 2D-QSAR studies were performed using three methods: the multiple linear regression method (MLR), giving r 2 = 0.9340 and q 2 = 0.8471; the partial least squares method, with r 2 = 0.9291 and q 2 = 0.7896; and principle component analysis, giving r 2 = 0.6496 and q 2 = 0.3893. The 3D-QSAR studies were performed using the stepwise variable selection k-nearest-neighbor molecular field analysis approach; a leave-one-out cross-validated correlation coefficient (q 2) of 0.4577 and a non-cross-validated correlation coefficient (r 2) of 0.5836 were obtained. Contour maps using this approach showed that steric effects dominantly determine binding affinities. The information rendered by 2D and 3D QSAR models may lead to a better understanding of structural requirements of HIV-integrase inhibitors and can help in the design of novel potent molecules.

3D QSAR analysis of oxazolidinone antibacterials: can we predict?

Three-dimensional QSAR studies for substituted aryloxazolidinones 3–9 were conducted using TSAR 3.3. The in vitro activities (MICs) of the compounds against Staphylococcus aureus and Enterococcus faecalis exhibited a good correlation with the prediction made by the model using heat of formation and LUMO energies.

3D QSAR studies of N-4-arylacryloylpiperazin-1-yl-phenyl-oxazolidinones: A novel class of antibacterial agents

Three-dimensional QSAR studies for N-4-arylacryloylpiperazin-1-yl-phenyl-oxazolidinones were conducted using TSAR 3.3. The in vitro activities (MICs) of the compounds against Staphylococcus aureus ATCC 25923 exhibited a strong correlation with the prediction made by the model developed in the present study.

Cluster analysis and three-dimensional QSAR studies of HIV-1 integrase inhibitors

Three-dimensional quantitative structure-activity relationship (3D QSAR) and cluster analysis were applied to a variety of HIV-1 integrase inhibitors. One structure was chosen from each of 11 classes of inhibitors to represent the whole class in descriptor-based cluster analysis. The 11 classes of inhibitors were classified into two groups. The molecular field analysis (MFA) models for these two clusters had r 2 values of 0.90 and 0.95 and q 2 values of 0.85 and 0.91 that were noticeably enhanced from those of conventional QSAR models. The five test compounds, which were proposed to have a common binding site near the metal in HIV-1 integrase based on docking studies by Sotriffer et al., were utilized to compare the predictive capability of MFA and conventional QSAR models. Among these five compounds, only l-chicoric acid belongs to cluster 1 and the other four belong to cluster 2. MFA models give better overall predictions and more importantly the activity of these test compounds is better predicted by the MFA model derived from the cluster each test compound belongs to. The necessity of dividing the inhibitors into two groups to obtain predictive QSAR models supports the likelihood of two separate binding sites.

Mapping the Binding Site of a Large Set of Quinazoline Type EGF‐R Inhibitors Using Molecular Field Analyses and Molecular Docking Studies.

In the current work, three-dimensional QSAR studies for one large set of quinazoline type epidermal growth factor receptor (EGF-R) inhibitors were conducted using two types of molecular field analysis techniques: comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). These compounds belonging to six different structural classes were randomly divided into a training set of 122 compounds and a test set of 13 compounds. The statistical results showed that the 3D-QSAR models derived from CoMFA were superior to those generated from CoMSIA. The most optimal CoMFA model after region focusing bears significant cross-validated r2cv of 0.60 and conventional r2 of 0.92. The predictive power of the best CoMFA model was further validated by the accurate estimation to these compounds in the external test set, and the mean agreement of experimental and predicted log(IC50) values of the inhibitors is 0.6 log unit. Separate CoMFA models were conducted to evaluate the ...

Mapping the binding site of a large set of quinazoline type EGF-R inhibitors using molecular field analyses and molecular docking studies.

In the current work, three-dimensional QSAR studies for one large set of quinazoline type epidermal growth factor receptor (EGF-R) inhibitors were conducted using two types of molecular field analysis techniques: comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). These compounds belonging to six different structural classes were randomly divided into a training set of 122 compounds and a test set of 13 compounds. The statistical results showed that the 3D-QSAR models derived from CoMFA were superior to those generated from CoMSIA. The most optimal CoMFA model after region focusing bears significant cross-validated r(2)(cv) of 0.60 and conventional r(2) of 0.92. The predictive power of the best CoMFA model was further validated by the accurate estimation to these compounds in the external test set, and the mean agreement of experimental and predicted log(IC(50)) values of the inhibitors is 0.6 log unit. Separate CoMFA models were conducted to evaluate the influence of different partial charges (Gasteiger-Marsili, Gasteiger-Hückel, MMFF94, ESP-AM1, and MPA-AM1) on the statistical quality of the models. The resulting CoMFA field map provides information on the geometry of the binding site cavity and the relative weights of various properties in different site pockets for each of the substrates considered. Moreover, in the current work, we applied MD simulations combined with MM/PBSA (Molecular mechanics/Possion-Boltzmann Surface Area) to determine the correct binding mode of the best inhibitor for which no ligand-protein crystal structure was present. To proceed, we define the following procedure: three hundred picosecond molecular dynamics simulations were first performed for the four binding modes suggested by DOCK 4.0 and manual docking, and then MM/PBSA was carried out for the collected snapshots. The most favorable binding mode identified by MM/PBSA has a binding free energy about 10 kcal/mol more favorable than the second best one. The most favorable binding mode identified by MM/PBSA can give satisfactory explanation of the SAR data of the studied molecules and is in good agreement with the contour maps of CoMFA. The most favorable binding mode suggests that with the quinazoline-based inhibitor, the N3 atom is hydrogen-bonded to a water molecule which, in turn, interacts with Thr 766, not Thr 830 as proposed by Wissner et al. (J. Med. Chem. 2000, 43, 3244). The predicted complex structure of quinazoline type inhibitor with EGF-R as well as the pharmacophore mapping from CoMFA can interpret the structure activities of the inhibitors well and afford us important information for structure-based drug design.

3D QSAR studies on new oxazolidinone antibacterial agents by comparative molecular field analysis

Three-dimensional QSAR studies for two series of new oxazolidinone antibacterial agents were conducted using the comparative molecular field analysis (CoMFA). In vitro activities (MICs) of the compounds against methicillin-resistant Staphylococcus aureus 88 (MRSA 88) exhibited a strong correlation with their steric, electrostatic factors and lipophilicities.