Anatholy Dimoglo

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 Kohonens 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 requirements 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.

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 Kohonens 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.

Electronic-Topological Study of Structurally Diverse Cyclooxygenase-2 Inhibitors

A large series of cyclooxygenase-2 (COX-2) inhibitors with diverse skeletons were investigated by means of the Electronic-Topological Method. A system for the COX-2 inhibitor activity prognostication was built with 6 pharmacophores and 6 anti-pharmacophores. The forecasting ability of the system was also tested on different structures, which differ from those that characterize the series studied.

First-Principles Study of Thermoelectric Properties of Covalent Organic Frameworks

Covalent organic frameworks (COFs) are new emerging functional porous materials. Strong covalent bonds result in molecular building blocks that can be arranged in layered two-dimensional (2D) or three-dimensional (3D) periodic networks. However, to the best of our knowledge, there have been no reports on experimental and theoretical studies of thermoelectrical properties of COFs to date. Therefore, density functional theory (DFT) and the Boltzmann transport equation have been applied in this work to calculate the semiclassical transport coefficients for phthalocyanine (Pc)-based NiPc, NiPc-benzothiadiazole (BTDA), and Pc COFs. Owing to the well-ordered stacking of the phthalocyanine units and linkers in these compounds, charge-carrier transport is facilitated in the stacking direction. In all studied compounds, the highly directional character of π-orbitals provides band-structure engineering and produces a type of low-dimensional hole transport along the stacking direction. All studied compounds are indirect semiconductors. The low-dimensional transport of holes and the localized states in both valence and conduction bands prevent the electron–hole compensation effect in the Seebeck coefficients, correlating with the large Seebeck coefficients of the studied compounds. Insertion of the electron-deficient building block benzothiadiazole in the NiPc-BTDA COF leads to positive Seebeck coefficients along the a-, b-, and c-directions. The relaxation time was estimated in our investigations from DFT band-structure calculations and the experimentally defined mobility, leading to determination of the electrical conductivity and electronic contribution to the thermal conductivity, as well as figure of merit (ZT) estimation. Ni atom provided greater electrical conductivity along the c-direction in comparison with metal-free Pc COF, and NiPc COF showed the highest thermoelectric performance among the studied COFs.

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.

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.