3D-QSAR and molecular docking studies of 2-pyrimidinecarbonitrile derivatives as inhibitors against falcipain-3

The three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on a series of falcipain-3 inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. A training set containing 42 molecules served to establish the QSAR models. The optimum CoMFA and CoMSIA models obtained for the training set were statistically significant with cross-validated correlation coefficients r(cv)(2) (q(2)) of 0.549 and 0.608, and conventional correlation coefficients (r(2)) of 0.976 and 0.932, respectively. An independent test set of 12 molecules validated the external predictive power of both models with predicted correlation coefficients (r(pred)(2)) for CoMFA and CoMSIA as 0.697 and 0.509, respectively. The docking of inhibitors into falcipain-3 active site using GOLD software revealed the vital interactions and binding conformation of the inhibitors. The CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of falcipain-3 active site, which suggests that the information rendered by 3D-QSAR models and the docking interactions can provide guidelines for the development of improved falcipain-3 inhibitors.     

QSARs on human carbonic anhydrase VA and VB inhibitors of some new not yet synthesized, substituted aromatic/heterocyclic sulphonamides as anti-obesity agent

This paper presents result of quantitative structure-activity relationships (QSAR) study realized with the PRECLAV, omega, brood and MOPAC software. The dependent property is the inhibitory activity against human carbonic anhydrase mitochondrial isoforms VA and VB. The calibration set includes 17 aromatic/heterocyclic sulphonamides incorporating phenacetyl, pyridylacetyl and thienylacetyl tails with three clinically used CA inhibitors namely AZA, TPM and ZNS molecules. The prediction set contains 24 others not yet synthesized substituted aromatic/heterocyclic sulphonamides having unknown observed values of activity. In the presence of prediction set, the predictive quality of QSAR of hCA VA (r(2) = 0.9789, F = 418.115, r(2)(CV) = 0.9689) and hCA VB (r(2) = 0.9768; F = 379.717; r(2)(CV) = 0.9637) is large. The obtained models suggest a slightly different inhibition mechanism for the two isoforms. Large percentage, in weight, of CONH molecular fragments seems to be favourable to inhibitory activity of both VA and VB.     

QSAR studies on CCR2 antagonists with chiral sensitive hologram descriptors

Chemokines are small molecular weight water-soluble proteins playing a key role in immunomodulation and host-defense mechanisms. CCR2 receptor is targeted for diseases like arthritis, multiple sclerosis, vascular disease, obesity, and type 2 diabetes. Reported, herein are the QSAR studies performed on a diverse set of enantiopure analogues reported as CCR2 antagonists by hologram analysis. The best model highlights the importance of chirality feature in comparison with the other models developed without the chirality. The validated model showed high internal and external predictive power. The robustness of the model was achieved with good statistical r(2) of 0.945 and cross-validated r(cv)(2) of 0.837. The challenging test predictivity of the model was confirmed with r(pred)(2) of 0.807. The fragment fingerprints help in understanding essential pharmacophoric features for CCR2 antagonism and provide basis for SAR of the molecules. The 2D contribution maps with fragment information will be useful for the design of novel CCR2 antagonists having improved efficacy.     

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.     

Correlation weighting of valence shells in QSAR analysis of toxicity

In the rainbow trout (Oncorhynchus mykiss), we studied the acute toxicity LC(50)-96 h of 274 organic pesticides with a wide variety of molecular structures. Optimization of correlation weights of local and global graph invariants (OCWLGI) gave quantitative structure-activity relationships (QSARs) for predicting toxicity. We used a labeled hydrogen-filled graph (LHFG) to elucidate the molecular structure. We also used the extended connectivity of zero ((0)EC(k)), first ((1)EC(k)), and second ((2)EC(k)) order, numbers of path lengths 2 (P2(k)) and 3 (P3(k)) starting from a given vertex in the LHFG, and valence shells of second order (S2(k)). S2(k) is the sum of the degree of vertices at distance 2 from a given vertex k. The presence of three-, five-, and six-member cycles and hydrogen bond indices suggested they might be used as global LHFG invariants. We applied this method to a broad set of pesticides, to predict toxicity for the trout. The best model used weighted S2(k) and global LHFG invariants. Statistical characteristics of this model are as follows: n=233, r(2)=0.7689, r(2)(pred)=0.7688, s=0.75, F=769 (training set); n=41, r(2)=0.6421, r(2)(pred)=0.4241, s=1.14, F=70 (test set).     

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.     

New potent 5-substituted benzofuroxans as inhibitors of Trypanosoma cruzi growth: quantitative structure-activity relationship studies

Benzofuroxan derivatives have been shown to inhibit the growth of Trypanosoma cruzi, the etiological agent of Chagas' disease. Therefore, 2D- and 3D-QSAR models of their in vitro antichagasic activity were developed. Six new derivatives were synthesized to complete a final set of 26 structurally diverse benzofuroxans. The 2D-QSAR model (r = 0.939, r(adj)(2) = 0.849) was generated using multiple regression analysis of tabulated substituents' physicochemical properties and indicator variables. In addition, a 3D-QSAR model (r(2) = 0.997, q(2) = 0.802) was obtained using a comparative molecular field analysis (CoMFA). Due to the well-known benzofuroxan tautomerism, in both approaches (2D- and 3D-QSAR) it was necessary to include an indicator variable to consider the N-oxide position (I(6)). This parameter was established using low-temperature NMR experiments. Both QSAR models identified the electrophilic character of the substituent alpha-atom as a requirement for activity. Further support was found using a density functional theory (DFT) approach.     

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.     

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.