Structural and Electronic Factors Influencing the Selective Inhibition of COX-2.

Structural and electronic factors influencing the inhibition of cyclooxygenase-1 and -2 (COX-1/COX-2) were studied by means of Electronic-Topological Method combined with Neural Networks (ETM-NN), molecular docking and Density Functional Theory (DFT). A series of structurally diverse compounds containing 209 molecules were classified in accordance with their inhibiting properties, as selectively inhibiting and non-selectively inhibiting COX-2 receptor agents (110 and 99 molecules, correspondingly). The results obtained from the ETM-NN calculations gave us possibility of selecting those pharmacophoric molecular fragments, which allow for the search of new selective inhibitors of COX-2 with high probability of realization. The final selection of pharmacophores and anti-pharmacophores found was taken as a basis for a system designed for the COX-2 inhibitory activity prediction. Analysis of the electron density distribution showed that more effective binding with COX-2 receptor was observed for selective inhibitors. To make an assessment of these interactions, calculations of stabilization energies were carried out for the ligand-receptor complexes. From the results of the docking and from the analysis of electronic structures of active sites of enzymes, some peculiarities of ligand-receptor binding and its influence on the selectivity of the COX-2 relative to COX-1 inhibition were elucidated. 95% of compounds were recognized correctly, as the most active ones, by the system of prediction designed. Thus, the system being the result of the study is capable of predicting the selective inhibitory activity of COX-2 successfully. As a consequence, it can be used both for computer screening and synthesis of potent inhibitors of COX-2 with molecular skeletons that may vary considerably.

The study of dual COX-2/5-LOX inhibitors by using electronic-topological approach based on data on the ligand-receptor interactions.

Structural and electronic factors influencing selective inhibition of cyclooxygenase-2 and 5-lipoxygenase (COX-2/5-LOX) were studied by using Electronic-Topological Method combined with Neural Networks (ETM-NN), molecular docking, and Density Functional Theory (DFT) in a large set of molecules. The results of the ETM-NN calculations allowed for the selection of pharmacophoric molecular fragments, which could be taken as a basis for a system capable of predicting the COX-2/5-LOX inhibitory activity. For the more effective extraction of the pharmacophoric molecular fragments, docking of molecules into the active sites of the two enzymes was carried out to get data on the ligand-receptor interaction. To make an assessment of these interactions, stabilization energies were calculated by using Natural Bond Orbital (NBO) analysis. Docking and data on the electronic structures of active sites of enzymes helped to reveal effectively the peculiarities of the ligand-receptor binding. The system for the selective COX-2/5-LOX inhibitory activity prediction that has been developed as the result of the ETM-NN study recognized correctly 93% of compounds as highly active ones. Thus, this system can be successfully used for carrying out computer screening and synthesis of potent inhibitors of COX-2/5-LOX with diverse molecular skeletons.

Electronic-topological and neural network approaches to the structure- antimycobacterial activity relationships study on hydrazones derivatives.

That the implementation of Electronic-Topological Method and a variant of Feed Forward Neural Network (FFNN) called as the Associative Neural Network are applied to the compounds of Hydrazones derivatives have been employed in order to construct model which can be used in the prediction of antituberculosis activity. The supervised learning has been performed using (ASNN) and categorized correctly 84.4% of them, namely, 38 out of 45. Ph1 pharmacophore and Ph2 pharmacophore consisting of 6 and 7 atoms, respectively were found. Anti-pharmacophore features socalled "break of activity" have also been revealed, which means that APh1 is found in 22 inactive molecules. Statistical analyses have been carried out by using the descriptors, such as EHOMO, ELUMO, ΔE, hardness, softness, chemical potential, electrophilicity index, exact polarizibility, total of electronic and zero point energies, dipole moment as independent variables in order to account for the dependent variable called inhibition efficiency. Observing several complexities, namely, linearity, nonlinearity and multi-co linearity at the same time leads data to be modeled using two different techniques called multiple regression and Artificial Neural Networks (ANNs) after computing correlations among descriptors in order to compute QSAR. Computations resulting in determining some compounds with relatively high values of inhibition are presented.

The structure-antituberculosis activity relationships study in a series of 5-aryl-2-thio-1,3,4-oxadiazole derivatives.

A series of 82 5-aryl-2-thio-1,3,4-oxadiazole derivatives were screened for their anti-mycobacterial activities against Mycobacterium tuberculosis H37Rv. The synthesized compounds 30-37 appeared to be the most active derivatives exhibiting more than 90% inhibition of mycobacterial growth at 12.5 µg/mL. Structure-activity relationships study was performed for the given series by using the electronic-topological method combined with neural networks (ETM-NN). A system for the anti-mycobacterial activity prediction was developed as the result of training associative neural network (ASNN) with weights calculated from projections of a compound and each pharmacophoric fragment found on the elements of the Kohonen's self-organizing maps (SOMs). From the detailed analysis of all compounds under study, the necessary requirements for a compound to possess antituberculosis activity have been formulated. The analysis has shown that any requirement's violation for a molecule implies a considerable decrease or even complete loss of its activity. Molecular docking studies of the compounds allowed shedding light on the binding mode of these novel anti-mycobacterial inhibitors.

Synthesis and structure-antituberculosis activity relationship of 1H-indole-2,3-dione derivatives.

New series of 5-fluoro-1H-indole-2,3-dione-3-thiosemicarbazones 2a-k and 5-fluoro-1-morpholino/piperidinomethyl-1H-indole-2,3-dione-3-thiosemicarbazones 3a-r were synthesized. The structures of the synthesized compounds were confirmed by spectral data, elemental and single crystal X-ray diffraction analysis. The new 5-fluoro-1H-indole-2,3-dione derivatives, along with previously reported 5-nitro-1H-indole-2,3-dione-3-thiosemicarbazones 2l-v, 1-morpholino/piperidinomethyl-5-nitro-1H-indole-2,3-dione-3-thiosemicarbazones 4a-l, and 5-nitro-1H-indole-2,3-dione-3-[(4-oxo-1,3-thiazolidin-2-ylidene)hydrazones] 5a-s, were evaluated for in vitro antituberculosis activity against Mycobacterium tuberculosis H37Rv. Among the tested compounds, 5-nitro-1H-indole-2,3-dione-3-thiosemicarbazones (2p, 2r, and 2s) and its 1-morpholinomethyl derivatives (4a, 4e, 4g, and 4i) exhibited significant inhibitory activity in the primary screen. The antituberculosis activity of molecules with diverse skeletons was investigated by means of the Electronic-Topological Method (ETM). Ten pharmacophores and ten anti-pharmacophores that have been found by this form the basis of the system capable of predicting the structures of potentially active compounds. The forecasting ability of the system has been tested on structures that differ from those synthesized. The probability of correct identification for active compounds was found as equal to 93% in average. To obtain the algorithmic base for the activity prediction, Artificial Neural Networks were used after the ETM (the so-called combined ETM-ANN method). As the result, only 9 pharmacophores and anti-pharmacophores were chosen as the most important ones for the activity. By this, ANNs classified correctly 94.4%, or 67 compounds from 71.

Synthesis and structure-antibacterial activity relationship investigation of isomeric 2,3,5-substituted perhydropyrrolo[3,4-d]isoxazole-4,6-diones.

The synthesis of 2,3,5-substituted perhydropyrrolo[3,4-d]isoxazole-4,6-diones (44 compounds) has been accomplished by the cycloaddition reaction of N-methyl-C-arylnitrones with N-substituted maleimides. The compounds were screened for their antibacterial activities and most of them exhibited activity against Enterococcus faecalis (ATCC 29212) and Staphylococcus aureus (ATCC 25923). cis-3a and cis-3d were found fairly effective against E. faecalis (ATCC 29212) and S. aureus (ATCC 25923) with MIC values of 25 and 50microg/ml. With the changes of cis isomers of the compounds to trans, their antibacterial activities also changed against the bacteria studied. First, pharmacophoric fragments had been calculated in accordance with the rules of the electronic-topological method (ETM). Next, both active compounds and pharmacophores had been projected to the nodes of Kohonen's self-organizing maps (SOM) to obtain the weights of pharmacophore fragments as numerical descriptors, that were used after this for the associative neural networks (ASNN) training. A model for the activity prediction was developed as the result of training the ASNNs.

Synthesis and characterization of novel hydrazide-hydrazones and the study of their structure-antituberculosis activity.

A series of hydrazide-hydrazones, based on a series of 4-substituted benzoic acid, were synthesized, and their structures were elucidated and screened for the antituberculosis activity against Mycobacterium tuberculosis H37Rv with the help of the BACTEC 460 radiometric system. Compound 3, 4-fluorobenzoic acid [((5-nitro)thiophen-2yl) methylene]hydrazide showed the highest inhibitory activity in this series. The search of pharmacophores was done by means of the Electronic-Topological Method (ETM). The model developed in this study is supposed to be applied to the design, preparation and screening of new compounds of similar structure in order to further test and optimize the model with the eventual goal of preparing new anti-tubercular agents.

The structure--antituberculosis activity relationships study in a series of 5-(4-aminophenyl)-4-substituted-2,4-dihydro-3h-1,2,4-triazole-3-thione derivatives. A combined electronic-topological and neural networks approach.

Antituberculosis activity of several 5-(4-aminophenyl)-4-alkyl/aryl-2,4-dihydro-3H-1,2,4-triazole-3-thiones (1-9) and their thiourea derivatives (10-31) were screened for their antimycobacterial activities against Mycobacterium tuberculosis H37Rv using the BACTEC 460 radiometric system. Of the synthesized compounds, 10-12, 30 were the most active derivatives exhibiting more than 90 % inhibition of mycobacterial growth at 12.5 microg/mL. Structure-activity relationships study was performed for the given series by using the Electronic-Topological Method combined with Neural Networks (ETM-NN). A system of prognosis was developed as the result of training associative neural network (ASNN) using weights of pharmacophoric fragments as descriptors. Descriptors were calculated by the projection of ETM compound and pharmacophoric fragments on the elements of Kohonen's self-organizing maps (SOM). From the detailed analysis of all compounds under study, the necessary requirements for a compound to possess antituberculosis activity were formulated. The analysis have shown that any requirements violation for a molecule implies a considerable decrease or even complete loss of its activity.

Synthesis of novel 5-aryl-2-thio-1,3,4-oxadiazoles and the study of their structure-anti-mycobacterial activities.

The preparation of novel 5-aryl-2-thio-1,3,4-oxadiazoles 4a-41 and the computer-aided study of their in vitro anti-tubercular activity against Mycobacterium tuberculosis H37Rv (ATCC 27294) are reported. The average accuracy of the electronic-topological method and neural network methods applied to the activity prediction in leave-one-out cross validation is 80%.

1,3,4-thiadiazole derivatives. Synthesis, structure elucidation, and structure-antituberculosis activity relationship investigation.

A series of 2,5-disubstituted-1,3,4-thiadiazoles were synthesized, the compounds structures were elucidated and screened for the antituberculosis activity against Mycobacterium tuberculosis H37Rv using the BACTEC 460 radiometric system. Among the tested compounds, 2-phenylamino-5-(4-fluorophenyl)-1,3,4-thiadiazole 22 showed the highest inhibitory activity. The relationships between the structures of compounds and their antituberculosis activity were investigated by the Electronic-Topological Method (ETM) and feed forward neural networks (FFNNs) trained with the back-propagation algorithm. As a result of the approach, a system of pharmacophores and anti-pharmacophores has been found that effectively separates compounds of the examination set into groups of active and inactive compounds. The system can be applied to the screening and design of new active compounds possessing skeletons similar to those used in the present study.