Synthesis, Biological Activity Evaluation and Molecular Docking of Imidazole Derivatives Possessing Hydrazone Moiety.

In an attempt to identify potential active anticancer agents with low cytotoxic properties and CA inhibitors, a new series of hybrid compounds incorporating imidazole ring and hydrazone moiety as part of their structure were synthesized by aza-Michael addition reaction followed by intramolecular cyclization. The structure of synthesized compounds was elucidated using various spectral techniques. Synthesized compounds were evaluated for their in vitro anticancer (prostate cell lines; PC3) and CA inhibitory (hCA I and hCA II) activity. Among them, some compound displayed remarkable anticancer activity and CA inhibitory activity with Ki values in range of 17.53±7.19-150.50±68.87 nM against cytosolic hCA I isoform associated with epilepsy, and 28.82±14.26-153.27±55.80 nM against dominant cytosolic hCA II isoforms associated with glaucoma. Furthermore, the theoretical parameters of the bioactive molecules were calculated to establish their drug-likeness qualities. The proteins used for the calculations are prostate cancer protein (PDB ID: 3RUK and 6XXP). ADME/T analysis was carried out to examine the drug properties of the studied molecules.

A novel hybrid method named electron conformational genetic algorithm as a 4D QSAR investigation to calculate the biological activity of the tetrahydrodibenzazosines.

To understand the structure-activity correlation of a group of tetrahydrodibenzazocines as inhibitors of 17ß-hydroxysteroid dehydrogenase type 3, we have performed a combined genetic algorithm (GA) and four-dimensional quantitative structure-activity relationship (4D-QSAR) modeling study. The computed electronic and geometry structure descriptors were regulated as a matrix and named as electron-conformational matrix of contiguity (ECMC). A chemical property-based pharmacophore model was developed for series of tetrahydrodibenzazocines by EMRE software package. GA was employed to choose an optimal combination of parameters. A model has been developed for estimating anticancer activity quantitatively. All QSAR models were established with 40 compounds (training set), then they were considered for selective capability with additional nine compounds (test set). A statistically valid 4D-QSAR ( Rtraining2=0.856 , Rtest2=0.851 and q2 = 0.650) with good external set prediction was obtained.

Conformation depends on 4D-QSAR analysis using EC-GA method: pharmacophore identification and bioactivity prediction of TIBOs as non-nucleoside reverse transcriptase inhibitors.

The electron conformational and genetic algorithm methods (EC-GA) were integrated for the identification of the pharmacophore group and predicting the anti HIV-1 activity of tetrahydroimidazo[4,5,1-jk][1,4]benzodiazepinone (TIBO) derivatives. To reveal the pharmacophore group, each conformation of all compounds was arranged by electron conformational matrices of congruity. Multiple comparisons of these matrices, within given tolerances for high active and low active TIBO derivatives, allow the identification of the pharmacophore group that refers to the electron conformational submatrix of activity. The effects of conformations, internal and external validation were investigated by four different models based on an ensemble of conformers and a single conformer, both with and without a test set. Model 1 using an ensemble of conformers for the training (39 compounds) and test sets (13 compounds), obtained by the optimum seven parameters, gave satisfactory results (R²(training) = 0.878, R²(test)= 0.910, q² = 0.840, q²(ext1) = 0.926 and q²(ext2) = 0.900).

4D-QSAR analysis and pharmacophore modeling: electron conformational-genetic algorithm approach for penicillins.

4D-QSAR studies were performed on a series of 87 penicillin analogues using the electron conformational-genetic algorithm (EC-GA) method. In this EC-based method, each conformation of the molecular system is described by a matrix (ECMC) with both electron structural parameters and interatomic distances as matrix elements. Multiple comparisons of these matrices within given tolerances for high active and low active penicillin compounds allow one to separate a smaller number of matrix elements (ECSA) which represent the pharmacophore groups. The effect of conformations was investigated building model 1 and 2 based on ensemble of conformers and single conformer, respectively. GA was used to select the most important descriptors and to predict the theoretical activity of the training (74 compounds) and test (13 compounds, commercial penicillins) sets. The model 1 for training and test sets obtained by optimum 12 parameters gave more satisfactory results (R(training)(2)=0.861, SE(training)=0.044, R(test)(2)=0.892, SE(test)=0.099, q(2)=0.702, q(ext1)(2)=0.777 and q(ext2)(2)=0.733) than model 2 (R(training)(2)=0.774, SE(training)=0.056, R(test)(2)=0.840, SE(test)=0.121, q(2)=0.514, q(ext1)(2)=0.641 and q(ext2)(2)=0.570). To estimate the individual influence of each of the molecular descriptors on biological activity, the E statistics technique was applied to the derived EC-GA model.

The effect of stereoisomerism on the 4D-QSAR study of some dipeptidyl boron derivatives.

The electron conformational genetic algorithm (EC-GA) method had been employed by distinguishing between enantiomers for the first time as a 4D-QSAR approach to reveal the pharmacophore (Pha) and to predict the bioactivity of the dipeptidyl boron compounds. The Electron Conformational Matrices of Congruity (ECMCs) were prepared for all conformers of compounds in the data set based on the quantum chemical calculations at HF/3-21 G level in an aqueous medium. The comparison of the ECMCs within the certain tolerances by the EMRE program revealed the pharmacophore for some dipeptidyl boron derivatives. For the selection of the most influential parameters on the activity and the calculation of theoretical activities, the genetic algorithm with the non-linear least square method was used. The final model was validated by the cross-validation method with the division of the data set into training and test items. The 12-parameter model gave excellent statistical results (R2training = 0.850, R2test = 0.809, q2 = 0.755, q2ext1 = 0.776, q2ext2 = 0.759, q2ext3 = 0.735, CCCtr = 0.922, CCCtest = 0.846, CCCall = 0.905). Because of the inexistence of 4D-QSAR studies on the dipeptidyl boron derivatives and the stereoisomerism effect on the biological activity was examined for the first time for these compounds, this study plays an important role in the development of new boron-containing compounds.

Discovery of hydrazone containing thiadiazoles as Mycobacterium tuberculosis growth and enoyl acyl carrier protein reductase (InhA) inhibitors.

Tuberculosis, caused by Mycobacterium tuberculosis, is a serious infectious disease and remains a global health problem. There is an increasing need for the discovery of novel therapeutic agents for its treatment due to the emerging multi-drug resistance. Herein, we present the rational design and the synthesis of eighteen new thiadiazolylhidrazones (TDHs) which were synthesized by intramolecular oxidative N-S bond formation reaction of 2-benzylidene-N-(phenylcarbamothioyl)hydrazine-1-carboximidamide derivatives by phenyliodine(III) bis(trifluoroacetate) (PIFA) under mild conditions. The compounds were characterized by various spectral techniques including FTIR, 1H NMR, 13C NMR and HRMS. Furthermore, the proposed structure of TDH12 was resolved by single-crystal X-ray analysis. The compounds were evaluated for their in vitro antitubercular activity against M. tuberculosis H37Rv. Among them, some compounds exhibited remarkable antimycobacterial activity, MIC = 0.78-6.25 µg/mL, with low cytotoxicity. Additionally, the most active compounds were screened for their biological activities against M. tuberculosis in the nutrient starvation model. Enzyme inhibition assays and molecular docking studies revealed enoyl acyl carrier protein reductase (InhA) as the possible target enzyme of the compounds to show their antitubercular activities.

Pharmacophore Modelling and 4D-QSAR Study of Ruthenium(II) Arene Complexes as Anticancer Agents (Inhibitors) by Electron Conformational- Genetic Algorithm Method.

OBJECTIVE: The EC-GA method was employed in this study as a 4D-QSAR method, for the identification of the pharmacophore (Pha) of ruthenium(II) arene complex derivatives and quantitative prediction of activity. METHODS: The arrangement of the computed geometric and electronic parameters for atoms and bonds of each compound occurring in a matrix is known as the electron-conformational matrix of congruity (ECMC). It contains the data from HF/3-21G level calculations. Compounds were represented by a group of conformers for each compound rather than a single conformation, known as fourth dimension to generate the model. ECMCs were compared within a certain range of tolerance values by using the EMRE program and the responsible pharmacophore group for ruthenium(II) arene complex derivatives was found. For selecting the sub-parameter which had the most effect on activity in the series and the calculation of theoretical activity values, the non-linear least square method and genetic algorithm which are included in the EMRE program were used. In addition, compounds were classified as the training and test set and the accuracy of the models was tested by cross-validation statistically. RESULTS: The model for training and test sets attained by the optimum 10 parameters gave highly satisfactory results with R2 training= 0.817, q 2=0.718 and SEtraining=0.066, q2 ext1 = 0.867, q2 ext2 = 0.849, q2 ext3 =0.895, ccctr = 0.895, ccctest = 0.930 and cccall = 0.905. CONCLUSION: Since there is no 4D-QSAR research on metal based organic complexes in the literature, this study is original and gives a powerful tool to the design of novel and selective ruthenium(II) arene complexes.

4D-QSAR Study of Some Pyrazole Pyridine Carboxylic Acid Derivatives By Electron Conformational-Genetic Algorithm Method.

INTRODUCTION: In the present work, pharmacophore identification and biological activity prediction for 86 pyrazole pyridine carboxylic acid derivatives were made using the electron conformational genetic algorithm approach which was introduced as a 4D-QSAR analysis by us in recent years. In the light of the data obtained from quantum chemical calculations at HF/6-311 G** level, the Electron Conformational Matrices of Congruity (ECMC) were constructed by EMRE software. Comparing the matrices, electron conformational submatrix of activity (ECSA, Pha) was revealed that are common for these compounds within a minimum tolerance. A parameter pool was generated considering the obtained pharmacophore. METHODS: To determine the theoretical biological activity of molecules and identify the best subset of variables affecting bioactivities, we used the nonlinear least square regression method and genetic algorithm. RESULTS: The results obtained in this study are in good agreement with the experimental data presented in the literature. The model for training and test sets attained by the optimum 12 parameters gave highly satisfactory results with R2 training= 0.889, q2=0.839 and SEtraining=0.066, q2 ext1 = 0.770, q2 ext2 = 0.750, q2 ext3=0.824, ccctr = 0.941, ccctest = 0.869 and cccall = 0.927.

Synthesis, spectroscopic (FT-IR/NMR) characterization, X-ray structure and DFT studies on (E)-2-(1-phenylethylidene) hydrazinecarboximidamide nitrate hemimethanol.

The title molecular salt, (E)-2-(1-phenylethylidene) hydrazinecarboximidamide nitrate hemimethanol C9H13N4(+)·NO3(-)·0.5CH4O, was synthesized and characterized by elemental analysis, FT-IR and NMT spectroscopies, and single-crystal X-ray diffraction technique. Quantum chemical calculations were performed to study the molecular and spectroscopic properties of the title compound, and the results were compared with the experimental findings. The calculated results show that the optimized geometry can well reproduce the crystal structure parameters, and the theoretical vibrational frequencies and GIAO (1)H and (13)CNMR chemical shifts show good agreement with experimental values. The dipole moment, linear polarizability and first hyperpolarizability values were also computed. The linear polarizabilities and first hyper polarizabilities of the studied molecule indicate that the compound is a good candidate of nonlinear optical materials. On the basis of the thermodynamic properties of the title compound at different temperatures have been calculated, revealing the correlations between standard heat capacities (C) standard entropies (S), and standard enthalpy changes (H) and temperatures.

Application of electron conformational-genetic algorithm approach to 1,4-dihydropyridines as calcium channel antagonists: pharmacophore identification and bioactivity prediction.

Two different approaches, namely the electron conformational and genetic algorithm methods (EC-GA), were combined to identify a pharmacophore group and to predict the antagonist activity of 1,4-dihydropyridines (known calcium channel antagonists) from molecular structure descriptors. To identify the pharmacophore, electron conformational matrices of congruity (ECMC)-which include atomic charges as diagonal elements and bond orders and interatomic distances as off-diagonal elements-were arranged for all compounds. The ECMC of the compound with the highest activity was chosen as a template and compared with the ECMCs of other compounds within given tolerances to reveal the electron conformational submatrix of activity (ECSA) that refers to the pharmacophore. The genetic algorithm was employed to search for the best subset of parameter combinations that contributes the most to activity. Applying the model with the optimum 10 parameters to training (50 compounds) and test (22 compounds) sets gave satisfactory results (R(2)(training)= 0.848, R(2)(test))= 0.904, with a cross-validated q(2) = 0.780).

Pharmacophore identification and bioactivity prediction for triaminotriazine derivatives by electron conformational-genetic algorithm QSAR method.

The electron conformational-genetic algorithm (EC-GA) method has been employed as a 4D-QSAR approach to reveal the pharmacophore (Pha) and to predict anticancer activity in the N-morpholino triaminotriazine derivatives. The electron conformational matrices of congruity (ECMCs) identified by electronic and structural parameters are constructed from data of conformational analysis and electronic structure calculation of molecules. Comparing the matrices, electron conformational submatrix of activity (ECSA, Pha) are revealed that are common for these compounds within a minimum tolerance. To predict the theoretical activity of training and test set and to select important variables for describing the activities, genetic algorithm and non-linear least square regression methods were applied. Regression coefficients were found 0.9708 for training and 0.9520 for test set.

N-(2,4-Dimethoxybenzylideneamino)guanidinium dihydrogenphosphate.

In the asymmetric unit of the title compound, C10H15N4O2+.H2PO4-, there are two protonated aminoguanidinium cations and two dihydrogenphosphate anions. The positive charge on the protonated amidine group is delocalized over the three C-N bonds in a manner similar to that found in guanidinium salts. The aminoguanidinium cations are found to be the E-isomer structures. Intramolecular interactions of the N-H...N type are observed, leading to the formation of five-membered rings. Extensive networks of O-H...O, N-H...O and C-H...O hydrogen bonds stabilize the three-dimensional network. In the crystal structure, pi-pi interactions between the benzene rings, with a distance of 3.778 (2) angstroms between the ring centroids, also affect the packing of the molecules.