3-D-QSAR analysis of N-(3-acyloxy-2-benzylpropyl)-N'-dihydroxytetrahydrobenzazepine and tetrahydroisoquinoline and N-(3-acyloxy-2-benzylpropyl)-N'-(4-hydroxy-3-methoxybenzyl) thioureas analogues as potent vanilloid receptor ligands

3-D-Quantitative structure--activity relationships of N-(3-acyloxy-2-benzylpropyl)-N'-dihydroxytetrahydro-benzazepine and tetrahydroisoquinoline and N-(3-acyloxy-2-benzylpropyl)-N'-(4-hydroxy-3-methoxybenzyl) thiourea analogues as potent vanilloid receptor ligands were investigated using the CoMFA and the COMSIA methods. The best CoMFA model obtained in this study from 29 substituted thiourea analogues is a two-component model with the following statistics. R(2)((cv))=0.407 and RMSE((cv))=0.532 for the cross-validation, and R(2)=0.705 and RMSE=0.375 for the fitted. The best COMSIA model obtained from the same 29 compounds is a two-component model with the following statistics: R(2)((cv))=0.336 and RMSE((cv))=0.563 for the cross-validation, and R(2)=0.693 and RMSE=0.382 for the fitted.     

3-D-QSAR CoMFA and CoMSIA studies on tetrahydrofuroyl-L-phenylalanine derivatives as VLA-4 antagonists

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on tetrahydrofuroyl-L-phenylalanine derivatives as VLA-4 antagonists. The best CoMFA and CoMSIA models that were generated using atom based alignment from a training set of twenty five tetrahydrofuroyl-L-phenylalanine derivatives, are six-component models with good statistics; CoMFA: r(2)(cv)=0.366, r(2)=0.983, s=0.099, F=172.661 and PRESS=4.435; CoMSIA: r(2)(cv)=0.528, r(2)=0.995, s=0.054, F=577.87 and PRESS=3.563. Both of these 3-D-QSAR models were validated using a test set of eleven compounds, whose predicted pIC(50) values fall within one log unit of the actual pIC(50). The contour diagrams obtained for the various CoMFA and CoMSIA field contributions can be mapped back onto structural features to explain the activity trends of the molecules analysed. Based on the spatial arrangement of the various field contributions, novel molecules with improved activity can be designed.     

3D-QSAR of N-myristoyltransferase inhibiting antifungal agents by CoMFA and CoMSIA methods

A series of benzofuran antifungals was examined to determine the structural requirements of N-myristoyltransferase (Nmt) enzyme inhibition by three-dimensional quantitative structure-activity relationship (3D-QSAR) using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. Evaluation of 20 compounds (training set) served to establish the model, which was validated by evaluation of a set of 6 compounds (test set). The lowest energy conformer of the most active molecule obtained from systematic search was used as the template structure for the alignment. The best predictions were obtained with the CoMFA model from RMS fit, with r(2)(cv)=0.828, r(2)(conv)=0.989, r(2)(pred)=0.754 and with the CoMSIA model combining hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields with r(2)(cv)=0.821, r(2)(conv)=0.978 and r(2)(pred)=0.747. The models obtained from the present study can be useful for the development of new Nmt inhibitors as potential antifungals. The docking studies were also carried out wherein the active and inactive molecules were docked into the active site of the recently reported Candida albicans Nmt (CaNmt) crystal structure to analyze enzyme-inhibitor interactions. The results obtained from the present 3D-QSAR and docking studies were found complimentary.     

Comparative molecular field analysis and comparative molecular similarity indices analysis of human thymidine kinase 1 substrates

Thymidine kinase 1 (TK1) is a key target for antiviral and anticancer chemotherapy. Three-dimensional quantitative structure-activity relationship (3D-QSAR) using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques was applied to analyze the phosphorylation capacity of a series of 31 TK1 substrates. The optimal predictive CoMFA model with 26 molecules provided the following values: cross-validated r(2) (q(2))=0.651, non-cross-validated r(2)=0.980, standard error of estimate (s)=0.207, F=129.3. For the optimal CoMSIA model the following values were found: q(2)=0.619, r(2)=0.994, s=0.104, F=372.2. The CoMSIA model includes steric, electrostatic, and hydrogen bond donor fields. The predictive capacity of both models was successfully validated by calculating known phosphorylation rates of five TK1 substrates that were not included in the training set. Contour maps obtained from CoMFA and CoMSIA models correlated with the experimentally developed SAR.     

CoMFA and HQSAR studies on 6,7-dimethoxy-4-pyrrolidylquinazoline derivatives as phosphodiesterase10A inhibitors

Phosphodiesterase10A (PDE10A) is an important enzyme with diverse biological actions in intracellular signaling systems, making it an emerging target for diseases such as schizophrenia, Huntington's disease, and diabetes mellitus. The objective of the current 3D QSAR study is to uncover some of the structural parameters which govern PDE10A inhibitory activity over PDE3A/B. Thus, comparative molecular field analysis (CoMFA) and hologram quantitative structure-activity relationship (HQSAR) studies were carried out on recently reported 6,7-dimethoxy-4-pyrrolidylquinazoline derivatives as PDE10A inhibitors. The best CoMFA model using atom-fit alignment approach with the bound conformation of compound 21 as the template yielded the steric parameter as a major contributor (nearly 70%) to the observed variations in biological activity. The best CoMFA model produced statistically significant results, with the cross-validated (r(cv)(2)) and conventional correlation (r(ncv)(2)) coefficients being 0.557 and 0.991, respectively, for the 21 training set compounds. Validation of the model by external set of six compounds yielded a high (0.919) predictive value. The CoMFA models of PDE10A and PDE3A/B activity were compared in order to address the selectivity issue of these inhibitors. The best HQSAR model for PDE10A was obtained with an r(cv)(2) of 0.704 and r(ncv)(2) of 0.902 using atoms, bonds, connections, chirality, donor, and acceptor as fragment distinction and default fragment size of 4-7 with three components for the 21 compounds. The HQSAR model predicted the external test-set of compounds well since a good agreement between the experimental and predicted values was verified. Taken together, the present QSAR models were found to accurately predict the PDE10A inhibitory activity of the test-set compounds and to yield reliable clues for further optimization of the quinazoline derivatives in the dataset.     

Particular interaction between pyrimethamine derivatives and quadruple mutant type dihydrofolate reductase of Plasmodium falciparum: CoMFA and quantum chemical calculations studies

Comparative molecular field analysis (CoMFA) was performed on twenty-three pyrimethamine (pyr) derivatives active against quadruple mutant type (Asn51Ile, Cys59Arg, Ser108Asn, Ile164Leu) dihydrofolate reductase of Plasmodium falcipaarum (PfDHFR). The represented CoMFA models were evaluated based on the various three different probe atoms, C(sp3) (+1), O(sp3) (-1) and H (+1), resulting in the best model with combined three types of probe atoms. The statistical results were r(2)(cv) = 0.702, S(press) = 0.608, r(2)(nv) = 0.980, s = 0.156, and r(2)(test-set) = 0.698 which can explain steric contribution of about 50%. In addition, an understanding of particular interaction energy between inhibitor and surrounding residues in the binding pocket was performed by using MP2/6-31G(d,p) quantum chemical calculations. The obtained results clearly demonstrate that Asn108 is the cause of pyr resistance with the highest repulsive interaction energy. Therefore, CoMFA and particular interaction energy analyses can be useful for identifying the structural features of potent pyr derivatives active against quadruple mutant type PfDHFR.     

Three-dimensional quantitative structure-activity relationship studies on novel series of benzotriazine based compounds acting as Src inhibitors using CoMFA and CoMSIA

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of benzotriazine derivatives, as Src inhibitors. Ligand molecular superimposition on the template structure was performed by database alignment method. The statistically significant model was established of 72 molecules, which were validated by a test set of six compounds. The CoMFA model yielded a q(2)=0.526, non cross-validated R(2) of 0.781, F value of 88.132, bootstrapped R(2) of 0.831, standard error of prediction=0.587, and standard error of estimate=0.351 while the CoMSIA model yielded the best predictive model with a q(2)=0.647, non cross-validated R(2) of 0.895, F value of 115.906, bootstrapped R(2) of 0.953, standard error of prediction=0.519, and standard error of estimate=0.178. The contour maps obtained from 3D-QSAR studies were appraised for activity trends for the molecules analyzed. Results indicate that small steric volumes in the hydrophobic region, electron-withdrawing groups next to the aryl linker region, and atoms close to the solvent accessible region increase the Src inhibitory activity of the compounds. In fact, adding substituents at positions 5, 6, and 8 of the benzotriazine nucleus were generated new compounds having a higher predicted activity. The data generated from the present study will further help to design novel, potent, and selective Src inhibitors as anticancer therapeutic agents.     

Comparative molecular field analysis (CoMFA) of phthalazine derivatives as phosphodiesterase IV inhibitors

A comparative molecular field analysis (CoMFA) of phthalazine class of phosphodiesterase IV (PDE IV) inhibitors has been performed to correlate their chemical structures with their observed biological activity. A statistically valid model with good correlative and predictive power is reported. The leave one out cross-validation study gave cross-validation r(2)(cv) of value 0.507 at six optimum components and conventional r(2) of value 0.98. The predictive ability of the model was tested by predicting the seven molecules belonging to the test set giving predictive correlation coefficient of 0.59. This model is potentially helpful in the design of novel and more potent PDE IV inhibitors.     

Three-dimensional quantitative structure activity relationships (3-D-QSAR) of antihyperglycemic agents.

A three-dimensional quantitative structure activity relationship study (3-D-QSAR) was performed on a set of thiazolidinedione antihyperglycemic agents using the comparative molecular field analysis (CoMFA) method. The CoMFA models were derived from a training set of 53 compounds. Fifteen compounds, which were not used in model generation were used to validate the CoMFA models. All the compounds were superimposed to the template structure by atom-based and shape-based strategies. The SYBYL QSAR rigid body field fit was also used for aligning the ligands. A total of twelve different alignments were generated. The resulting models exhibited a good cross-validated r2cv values (0.624-0.764) and the conventional r2 values (0.689-0.921). A more robust cross-validation test using cross-validation by 2 groups (leave half out method) was performed 100 times to ascertain the predictiveness of the CoMFA models. The mean of r2cv values from 100 runs ranged from 0.611-0.690. Few models exhibited good external predictivity. These models were then used to define a hypothetical receptor model for antihyperglycemic agents.     

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.     

Synthesis,biological activity and receptor-based 3-D QSAR study of 3'-N-substituted-3'-N-debenzoylpaclitaxel analogues

3'-N-Substituted-3'-N-debenzoylpaclitaxel analogues were synthesized and investigated for their 3-D QSAR by using comparative molecular field analysis (CoMFA). The CoMFA model obtained from receptor(microtubule)-paclitaxel binding structure displays an excellent predictive power to forecast the biological activity of new 3'-N-substituted-3'-N-debenzoylpaclitaxel analogues as well as the ability to explain the activity of the known paclitaxel analogues. The cross-validated r(2)(cv) values of the selected models are 0.835 and 0.616 for A549 and SK-OV-3, respectively, and the non-cross-validated r(2)(ncv) values of them are 0.992 and 0.974.     

CoMFA and CoMSIA 3D-QSAR analysis of diaryloxy-methano-phenanthrene derivatives as anti-tubercular agents

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were conducted on a series (44 compounds) of diaryloxy-methano-phenanthrene derivatives as potent antitubercular agents. The best predictions were obtained with a CoMFA standard model (q (2)=0.625, r (2)=0.994) and with CoMSIA combined steric, electrostatic, and hydrophobic fields (q (2)=0.486, r (2)=0.986). Both models were validated by a test set of seven compounds and gave satisfactory predictive r (2) values of 0.999 and 0.745, respectively. CoMFA and CoMSIA contour maps were used to analyze the structural features of the ligands to account for the activity in terms of positively contributing physicochemical properties: steric, electrostatic, and hydrophobic fields. The information obtained from CoMFA and CoMSIA 3-D contour maps can be used for further design of phenanthrene-based analogs as anti-TB agents. The resulting contour maps, produced by the best CoMFA and CoMSIA models, were used to identify the structural features relevant to the biological activity in this series of analogs. Further analysis of these interaction-field contour maps also showed a high level of internal consistency. This study suggests that introduction of bulky and highly electronegative groups on the basic amino side chain along with decreasing steric bulk and electronegativity on the phenanthrene ring might be suitable for designing better antitubercular agents.     

CoMFA and HQSAR of acylhydrazide cruzain inhibitors

An approach combining CoMFA and HQSAR methods was used to describe QSAR models for a series of cruzain inhibitors having the acylhydrazide framework. A CoMFA study using two alignment orientations (I and II), three different probe atoms and changes of the lattice spacing (1 and 2 A) was performed. Alignment II and an sp3 probe carbon atom yielded good cross-validation (q2=0.688) employing lattice spacing of 1 A. The best HQSAR model was generated using atoms, bond, and connectivity as fragment distinction and fragment size default (4-5) showing similar cross-validated value of CoMFA (q2=0.689). Based upon the information derived from CoMFA and HQSAR, we have identified some key features that may be used to design new acylhydrazide derivatives that may be more potent cruzain inhibitors.     

CoMFA of artemisinin derivatives: effect of location and size of lattice.

A CoMFA study of artemisinin derivatives with changes of the location and the number of lattice points was performed. The location of probe atoms in a large lattice has practically no effect on the cross-validated r(2) value (r(2)(cv)). The selection of only 18 probe atoms around the peroxide bond, considering the action mechanism of artemisinin, provided a less time-demanding and more reliable CoMFA model, which forecasts better than the large lattice model despite the lower r(2)(cv) value. Only 1 A displacement of the small lattice caused a reduction of cross-validated r(2) value of more than 50%, which indicates the lattice location played an important role in this small lattice model.