QSAR MODELING OF ANTIBACTERIAL ACTIVITY OF SOME BENZIMIDAZOLE DERIVATIVES

A quantitative structure-activity relationship (QSAR) study has been carried out for a training set of 12 benzimidazole derivatives to correlate and predict the antibacterial activity of studied compounds against Gram-negative bacteria Pseudomonas aeruginosa. Multiple linear regression was used to select the descriptors and to generate the best prediction model that relates the structural features to inhibitory activity. The predictivity of the model was estimated by cross-validation with the leave-one-out method. Our results suggest a QSAR model based on the following descriptors: parameter of lipophilicity (logP) and hydration energy (HE). Good agreement between experimental and predicted inhibitory values, obtained in the validation procedure, indicated the good quality of the generated QSAR model

Physico-chemical characterization and anti- microbial activity of copper(II) complexes with 2-amino and 2-methylbenzimidazole derivatives

Copper(II) chloride, in warm ethanolic solution, reacted with 2-amino and 2-methylbenzimidazole derivatives to give complexes of the formula CuL2Cl2·nH2O, where L=1-benzyl-2-aminobenzimidazole 1-(4-methylbenzyl)-2-aminobenzimidazole, 1-benzyl-2-methylbenzimidazole and 1-(4-methylbenzyl)-2-methylbenzimidazole( n=1 or 2). The complexes were characterized by elemental analysis of the metal, molar conductivity magnetic susceptibility measurements and IR spectra. The molar conductivities of copper(II)complexes in dimethyl formamide (DMF) corresponding to a 1:1 type of electrolyte indicate that in all the complexes one of the coordinated chloride ions has been replaced by DMF molecule. The room temperature effective magnetic moments and IR data of the complexes suggest that all Cu(II) complexes have a tetrahedral configuration, which is realized by participation of the pyridine nitrogen of two organic ligand molecules and two chloride anions. The antimicrobial activity of the ligands and their complexes against Pseudomonas aeruginosa, Bacillus sp. Staphylococcus aureus, Sarcina lutea and Saccharomyces cerevisiae was investigated. The effect of copper complexation on the ligand antimicrobial activity is discussed

Quantitative structure-activity relationship of some 1-benzylbenzimidazole derivatives as antifungal agents

In the present study, the antifungal activity of some 1-benzylbenzimidazole derivatives against yeast Saccharomyces cerevisiae was investigated. The tested benzimidazoles displayed in vitro antifungal activity and minimum inhibitory concentration (MIC) was determined for all the compounds. Quantitative structure-activity relationship (QSAR) has been used to study the relationships between the antifungal activity and lipophilicity parameter, logP, calculated by using CS Chem-Office Software version 7.0. The results are discussed on the basis of statistical data. The best QSAR model for prediction of antifungal activity of the investigated series of benzimidazoles was developed. High agreement between experimental and predicted inhibitory values was obtained. The results of this study indicate that the lipophilicity parameter has a significant effect on antifungal activity of this class of compounds, which simplify design of new biologically active molecules

Synthesis, physico-chemical characterization and biological activity of 2-aminobenzimidazole complexes with different metal ions

Complexes of 2-aminobenzimidazole (L) with nitrates of cobalt(II) nickel(II), copper (II), zinc(II) and silver(I) were synthesized. The molar ratio metal:ligand in the reaction of the complex formation was 1:2. It should be noticed, that the reaction of all the metal salts yielded bis(ligand) complexes of the general formula M(L)2(NO3)2 × nH2O (M=Co, Ni Cu, Zn or Ag; n=0, 1, 2 or 6). The complexes were characterized by elemental analysis of the metal, molar conductivity, magnetic susceptibility measurements and IR spectra. Co(II), Ni(II) and Cu(II) complexes behave as non-electrolytes, whilst Zn(II) and Ag(I) are 1:1 electrolytes. Cu(II) complex has a square-planar stereochemistry, Ag(I) complex is linear, whilst the Co(II), Ni(II) and Zn(II) complexes have a tetrahedral configuration. In all the complexes ligand is coordinated by participation of the pyridine nitrogen of the benzimidazole ring. The antimicrobial activity of the ligand and its complexes against Pseudomonas aeruginosa, Bacillus sp. Staphylococcus aureus and Saccharomyces cerevisiae was investigated. The effect of metal on the ligand antimicrobial activity is discussed

C18-UHPLC analysis of retention behavior of newly designed o-alkylated and rostane derivatives in ternary mixture methanol/acetonitrile/water

Different new groups of steroid compounds are the center of attention in a grate number of scientific publications since the majority of compounds are being researched as anticancer drugs. One of the most important feature of potential drug is its lipophilicity. Nowadays, ultra high-performance liquid chromatography (UHPLC) is used as one of the most sophisticated techniques for determination of the retention behavior determination of different biologically active compounds. The series of 18 newly designed O-alkylated androstane derivatives was investigated in reversed phase (RP)-UHPLC system using ternary mixture methanol/acetonitrile/water. A good agreement between experimentally observed and in silico lipophilicity was noticed given that coefficient of determination of 0.8406 was achieved

Electrostatic and Topological Features as Predictors of Antifungal Potential of Oxazolo Derivatives as Promising Compounds in Treatment of Infections Caused by Candida albicans

The results presented in this study include the prediction of the antifungal activity of 24 oxazolo derivatives based on their topological and electrostatic molecular descriptors, derived from the 2D molecular structures. The artificial neural network (ANN) method was applied as a regression tool. The input data for ANN modeling were selected by stepwise selection (SS) procedure. The ANN modeling resulted in three networks with the outstanding statistical characteristics. High predictivity of the established networks was confirmed by comparisons of the predicted and experimental data and by the residuals analysis. The obtained results indicate the usefulness of the formed ANNs in precise prediction of minimum inhibitory concentrations of the analyzed compounds towards Candida albicans. The Sum of Ranking Differences (SRD) method was used in this study to reveal possible grouping of the compounds in the space of the variables used in ANN modeling. The obtained results can be considered to be a contribution to development of new antifungal drugs structurally based on oxazole core, particularly nowadays when there is a lack of highly efficient antimycotics

Neural network modelling of antifungal activity of a series of oxazole derivatives based on in silico pharmacokinetic parameters

In the present paper, the antifungal activity of a series of benzoxazole and oxazolo[ 4,5-b]pyridine derivatives was evaluated against Candida albicans by using quantitative structure-activity relationships chemometric methodology with artificial neural network (ANN) regression approach. In vitro antifungal activity of the tested compounds was presented by minimum inhibitory concentration expressed as log(1/cMIC). In silico pharmacokinetic parameters related to absorption, distribution, metabolism and excretion (ADME) were calculated for all studied compounds by using PreADMET software. A feedforward back-propagation ANN with gradient descent learning algorithm was applied for modelling of the relationship between ADME descriptors (blood-brain barrier penetration, plasma protein binding, Madin-Darby cell permeability and Caco-2 cell permeability) and experimental log(1/cMIC) values. A 4-6-1 ANN was developed with the optimum momentum and learning rates of 0.3 and 0.05, respectively. An excellent correlation between experimental antifungal activity and values predicted by the ANN was obtained with a correlation coefficient of 0.9536. [Projekat Ministarstva nauke Republike Srbije, br. 172012 i br. 172014