New protic ionic liquids for fungi and bacteria removal from paper heritage artefacts.

In this work, new protic ionic liquids (PILs) with 1-ammonium-2-propanol cation and nine different anions: formate (For), acetate (Ac), lactate (Lac), trifluoroacetate (TFA), chloroacetate (ClA), trichloroacetate (TClA), 3-chloropropionate (3-ClP), 4-chlorobutyrate (4-ClB) and mandelate (Man) were prepared in order to study their antimicrobial activity and possible application for fungi and bacteria removal from deteriorated paper heritage. Ten filamentous fungal strains isolated from specific pigmented area of the damaged books: Trichoderma sp., Cladosporium sp., Penicillium sp.(1-3), Penicillium citrinum, Aspergillus sp.(1,2), Aspergillus flavus, Fusarium graminearum, eight Gram positive and Gram negative ATCC bacterial strains: B. subtilis (6633), S. aureus (6538), E. faecalis (19433), K. rhizophila (9341), E. coli (11229), S. enteritidis (13076), P. mirabilis (12453), P. aeruginosa (15692) and two yeast Candida strains: Candida albicans (ATCC 10231) and Candida albicans (L) were used in this study. The results indicated that antimicrobial activity of selected ionic liquids is significantly affected by the size and specific functional groups in the anion structure. These facts opened the possibility for molecular design of new ionic liquids with strong inhibition properties against the specific bacterial, mould and yeast strains. The significant antimicrobial properties observed in this research suggest that studied PILs may have potential applications in the paper art and artefact cleaning and conservation replacing thus, conventional solvents and organic substances that are toxic for humans and environment.

Off-Pump Plicating Ascending Aortoplasty With External Wrapping: Magnum in Parvo.

BACKGROUND: Isolated, fusiform aneurysms, exclusively affecting the tubular portion of the ascending aorta, are rare. Surgical treatment aims to change their natural course, reducing individual and cumulative risks of rupture, dissection and death. Open tubular graft replacement still remains the procedure of choice, despite significant risks. In permanent pursuit for optimal, alternative surgical strategy in high-risk patients, less invasive and off-pump plicating ascending aortoplasty with modified external Dacron graft wrapping seems to be a reliable choice. METHODS: Two (2) consecutive patients were operated on. The same preoperative calculations and slightly different operative techniques were applied regarding surgical exposure and wrapping graft orientation. Immediate and late follow-up (5 years) results were compared. RESULTS: Absolute and indexed target ascending aortic diameters remained acceptable (<2.1cm/m2 considered the upper normal range for adults). There were no significant changes in proximal and distal aortic diameters. Ascending aortic silhouette on contrast enhanced multi-detector CT was better with Dacron wrapping graft tailored to have its grooves in the longitudinal direction. Upper mini-sternotomy was quite appropriate for this procedure, from a surgical point of view, and was safe for the patient. CONCLUSIONS: Careful patient selection and using the current model of preoperative calculations and surgical technique resulted in acceptable and stable ascending aortoplasty in high-risk patients 5 years after surgery.

Toward steroidal anticancer drugs: Non-parametric and 3D-QSAR modeling of 17-picolyl and 17-picolinylidene androstanes with antiproliferative activity on breast adenocarcinoma cells.

The present study is aimed to analyze lipophilicity and ADMET profiles, and to develop field based 3D-QSAR and ligand-based pharmacophore hypothesis for a series of 17α-picolyl and 17(E)-picolinylidene androstane derivatives in order to give detailed structural insights and to highlight important binding features of novel androstane derivatives, as compounds with antiproliferative activity toward breast adenocarcinoma cells. This study can provide guidelines for the rational design of novel potent compounds. Sum of ranking differences (SRD), as a non-parametric method, was applied for compounds ranking. 3D-QSAR methods, including comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), were applied to predict the antiproliferative effect on breast adenocarcinoma cells and provide the regions in space where interactive fields may influence the activity. The compounds are ranked so the compounds with the most favorable ADME and lipophilicity features together with significant anticancer activity can be distinguished. The established 3D-QSAR model could be used for design of new compounds with antiproliferative activity on the human ER- breast adenocarcinoma cells. The pharmacophore model is able to accurately predict antiproliferative activity. Generally, the present study provides significant guidelines for further selection, synthesis and rational design of new highly potential androstane derivatives as anticancer drugs.

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.

Binding affinity toward human prion protein of some anti-prion compounds - Assessment based on QSAR modeling, molecular docking and non-parametric ranking.

The present study is based on the quantitative structure-activity relationship (QSAR) analysis of binding affinity toward human prion protein (huPrPC) of quinacrine, pyridine dicarbonitrile, diphenylthiazole and diphenyloxazole analogs applying different linear and non-linear chemometric regression techniques, including univariate linear regression, multiple linear regression, partial least squares regression and artificial neural networks. The QSAR analysis distinguished molecular lipophilicity as an important factor that contributes to the binding affinity. Principal component analysis was used in order to reveal similarities or dissimilarities among the studied compounds. The analysis of in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) parameters was conducted. The ranking of the studied analogs on the basis of their ADMET parameters was done applying the sum of ranking differences, as a relatively new chemometric method. The main aim of the study was to reveal the most important molecular features whose changes lead to the changes in the binding affinities of the studied compounds. Another point of view on the binding affinity of the most promising analogs was established by application of molecular docking analysis. The results of the molecular docking were proven to be in agreement with the experimental outcome.

Chemometrics approach based on chromatographic behavior, in silico characterization and molecular docking study of steroid analogs with biomedical importance.

Physicochemical characterization of steroid analogs (triazole, tetrazole, toluenesulfonylhydrazide, nitrile, dinitrile and dione) is considered to be a very important step in further drug selection. This study applies to the determination of lipophilicity of previously synthesized steroid derivatives using reversed-phase high-performance liquid chromatography (RP HPLC). Chemometric aspect of chromatographic lipophilicity is given throughout multiple linear regression (MLR) quantitative structure-retention relationships (QSRR) approach. Minimal inhibitory concentration (MIC) is determined for two steroid derivatives possessing antimicrobial activity against Staphylococcus aureus. Molecular docking study was performed in order to identify the compound with the most promising potential as human cytochrome P450 CYP17A1inhibitor. Identified 3ß-hydroxyandrost-5-eno[16,17-d]-1,2,3-triazole (I.2.) could be recommended for further trials for anticancer drugs and subjected to the absorption, distribution, metabolism, excretion and toxicity (ADMET) evaluation.

A comparative study of chromatographic behavior and lipophilicity of selected natural styryl lactones, their derivatives and analogues.

This study is based on the analyses of the retention behavior of selected natural styryl lactones and their synthetic analogues in reversed-phase high-performance liquid chromatography. Chromatographic separations were achieved applying ZORBAX SB-C18 column and two different mobile phases: methanol-water and acetonitrile-water. Chromatographic lipophilicity of the analyzed compounds was defined by logk0 constant and correlated with in silico molecular descriptors. According to the statistical validation parameters, obtained results indicate that the presented linear and multiple quantitative structure-retention relationship models can successfully predict the chromatographic lipophilicity of structurally similar compounds. Hierarchical cluster analyses (HCA) was applied in order to group similar compounds according to their chromatographic and in silico lipophilicity. It can be concluded that chromatographic systems with methanol-water were better for modelling of logk0. Modelling was performed in order to characterize compounds regarding their lipophilicity profiles as future drug candidates.

Lipophilicity estimation and characterization of selected steroid derivatives of biomedical importance applying RP HPLC.

The present paper deals with chromatographic lipophilicity determination of twenty-nine selected steroid derivatives using reversed-phase high-performance liquid chromatography (RP HPLC) combined with two mobile phase, acetonitrile-water and methanol-water. Chromatographic behavior of four groups (triazole and tetrazole, toluenesulfonylhydrazide, nitrile and dinitrile and dione) of selected steroid derivatives was studied. Investigated compounds were grouped using principal component analysis (PCA) according to their logk values for both mobile phases. Grouping was in the very good accordance with the polarity and lipophilicity of the investigated compounds. QSRR (quantitative structure-retention relationship) approach was used to model chromatographic lipophilicity behavior using molecular descriptors. Modeling was performed using linear regression (LR) and multiple linear regression (MLR) methods. The most influential molecular descriptors were lipophilicity descriptors that are important for molecules ability to pass through biological membranes and geometrical descriptors. All established LR-QSRR and MLR-QSRR models were statistically validated by standards, cross- and external validation parameters as well as with two graphical methods. According to all these assessments, MLR models were better for chromatographic lipophilicity prediction. It was shown that chromatographic systems with methanol-water were better for modeling of logk than systems with acetonitrile-water, as well as the systems that contained lower volume fractions of organic component in mobile phase. Modeling was performed in order to obtain lipophilicity profiles of investigated compounds as future drug candidates of biomedical importance.

QSRR Analysis in Characterization of Some Benzimidazole Derivatives.

In this paper, quantitative structure-retention relationship study has been applied in order to correlate obtained retention parameter R(M)(0) and two groups of molecular descriptors, for eleven investigated benzimidazole derivatives. Principal component analysis (PCA), followed by hierarchical cluster analysis (HCA) and multiple linear regression (MLR), was applied in order to identify the most important molecular descriptors. Mathematical models were established and the best models were further validated by leave-on-out (LOO) technique as well as by the calculation of the statistical parameters. Statistically significant models were established.