Slavica Erić

Role of complexes formation between drugs and penetration enhancers in transdermal delivery

The use of chemical penetration enhancers (CPE) is growing due to their ability to improve drug delivery through the skin. A possible mechanism of penetration enhancement could involve the complex formation between drug and components in the pharmaceutical formulation, thus altering the physicochemical properties of the active substance. Here, modelling studies indicate that hydrocarbon and oxygen-containing terpenes (penetration enhancers) could form complexes with drugs. Satisfactory correlations have been obtained between the predicted molecular properties of enhancers and their enhancement effects.

Target fishing and docking studies of the novel derivatives of aryl-aminopyridines with potential anticancer activity

A set of 16 previously synthesized aryl-aminopyridine and aryl-aminoquinoline derivatives have been evaluated for cytotoxic activity against three cancer cell lines (human cervical cancer-HeLa; human chronic myeloid leukemia-K562; human melanoma-Fem-x) and two types of normal peripheral blood mononuclear cells, with and without phytohemaglutinin (PBMC-PHA; PBMC+PHA). Twelve of the studied compounds showed moderate cytotoxicity, with selectivity against K562 but not the remaining two cancer cell lines. Four compounds were not active in cytotoxicity assays, presumably due to high predicted lipophilicity and low solubility. To rationalize the observed cytotoxic effects, structure-based virtual screening was carried out against a pool of potential targets constructed using the inverse docking program Tarfisdock and bibliographical references. The putative targets were identified on the basis of the best correlation between docking scores and in vitro cytotoxicity. It is proposed that the mechanism of action of the studied aminopyridines involves the disruption of signaling pathways and cancer cell cycle through the inhibition of cyclin-dependent kinases and several tyrosine kinases, namely Bcr-Abl kinase and KIT receptor kinase. The obtained results can guide further structural modifications of the studied compounds aimed at developing selective agents targeting proteins involved in cancer cell survival and proliferation.

Prediction of toxicity and data exploratory analysis of estrogen-active endocrine disruptors using counter-propagation artificial neural networks

In this work, a novel algorithm for optimization of counter-propagation artificial neural networks has been used for development of quantitative structure-activity relationships model for prediction of the estrogenic activity of endocrine-disrupting chemicals. The search for the best model was performed using genetic algorithms. Genetic algorithms were used not only for selection of the most suitable descriptors for modeling, but also for automatic adjustment of their relative importance. Using our recently developed algorithm for automatic adjustment of the relative importance of the input variables, we have developed simple models with very good generalization performances using only few interpretable descriptors. One of the developed models is in details discussed in this article. The simplicity of the chosen descriptors and their relative importance for this model helped us in performing a detailed data exploratory analysis which gave us an insight in the structural features required for the activity of the estrogenic endocrine-disrupting chemicals.

High-performance liquid chromatographic method for the assay of dexamethasone and xylometazoline in nasal drops containing methyl p-hydroxybenzoate

A rapid and sensitive high-performance liquid chromatographic method has been developed for the determination of dexamethasone sodium phosphate (DSP), xylometazoline hydrochloride (XMC) and methyl p-hydroxybenzoate (MHB). An assay of the compounds has been performed on a HPLC system GBC 1210, at controlled room temperature, on a Nucleosil C8 column (250x3 mm, 5 microm). The mobile phase was acetonitrile-water (35:65, v/v), at a flow-rate of 1 ml min(-1). The parameters for validation such as linearity (r>0.9996), precision (RSD: 0.51-(1.93%), limit of detection and quantification (2.032 x 10(-4) and 4.063 x 10(-4) mg ml(-1) for DSP, 9.7 x 10(-5) and 1.953 x 10(-4) mg ml(-1) for XMC, 1.953 x 10(-4) and 3.096 x 10(-4) mg ml(-1) for MHB) have also been reported. The method was applied to the determination of DSP, XMC and MHB in nasal drops. The statistical parameters were found to be satisfactory, with recovery values ranging from 98.69 to 101.60% (RSD: 0.32-1.03%). The method is simple and accurate and therefore suitable for the simultaneous determination of these compounds in dosage form.

Antiproliferative activity and QSAR studies of a series of new 4-aminomethylidene derivatives of some pyrazol-5-ones.

Twenty five 4-aminomethylidene derivatives obtained from 3-phenyl-2-pyrazolin-5-one and 1,3-diphenyl-2-pyrazolin-5-one were synthesized and tested for their antiproliferative activity against human breast cancer MDA-MB-361 and MDA-MB-453 cell lines. The compounds derived from 1,3-diphenyl-2-pyrazolin-5-one exhibited the most remarkable activity in the treatment of both cell lines. In vitro antiproliferative activities were accompanied by an important apoptotic fraction of both cell lines; also, compounds inhibited key endothelial cell functions implicated in invasion and angiogenesis. QSAR methods were performed in order to analyze the influence of structural features of the compounds investigated on the antiproliferative potential on MDA-MB-361 and MDA-MB-453 cancer cells. One-parameter heuristic analysis was performed and different whole molecule and fragmental descriptors were considered for rationalization of mechanism of interaction of these compounds with active place of hypothetical target included in tumorigenesis.

Estimation of the Hydrophobicity of Antimycotic Compounds by Planar Chromatography

The retention behavior of bifonazole, clotrimazole, fenticonazole, fluconazole, ketoconazole, miconazole, metronidazole, and itraconazole, widely used antimycotic drugs have been determined by TLC by use of the binary mobile phases acetone-n-hexane, methanol-toluene, and methyl ethyl ketone-toluene containing different amounts of organic modifier. Hydrophobicity was established from the linear relationships between the solute RM values and the concentration of organic modifier. Calculated values of RM0 and C0 were considered for application in QSAR studies of the antimycotics.

Synthesis, antitumor activity and QSAR studies of some 4-aminomethylidene derivatives of edaravone.

A series of aminomethylidene derivatives obtained from 4-formyledaravone were synthesized and characterized by IR, NMR and elemental analysis. All the compounds were screened for their antitumor activity. The compound containing 5-phenylpyrazole moiety (3q) exhibited remarkable antitumor activity in in vitro assays, especially against human breast cancer MDA-MB-361 and MDA-MB-453 cell lines. The most important whole-molecule descriptors for antitumor activity on MDA-MB-453 cells belong to the group of quantum-chemical descriptors.

Computational classification models for predicting the interaction of drugs with P-glycoprotein and breast cancer resistance protein

P-glycoprotein (P-gp/ABCB1) and breast cancer resistance protein (BCRP/ABCG2) are two members of the adenosine triphosphate (ATP) binding cassette (ABC) family of transporters which function as membrane efflux transporters and display considerable substrate promiscuity. Both are known to significantly influence the absorption, distribution and elimination of drugs, mediate drug–drug interactions and contribute to multiple drug resistance (MDR) of cancer cells. Correspondingly, timely characterization of the interaction of novel leads and drug candidates with these two transporters is of great importance. In this study, several computational classification models for prediction of transport and inhibition of P-gp and BCRP, respectively, were developed based on newly compiled and critically evaluated experimental data. Artificial neural network (ANN) and support vector machine (SVM) ensemble based models were explored, as well as knowledge-based approaches to descriptor selection. The average overall classification accuracy of best performing models was 82% for P-gp transport, 88% for BCRP transport, 89% for P-gp inhibition and 87% for BCRP inhibition, determined across an array of different test sets. An analysis of substrate overlap between P-gp and BCRP was also performed. The accuracy, simplicity and interpretability of the proposed models suggest that they could be of significant utility in the drug discovery and development settings.

Computational study and peptide inhibitors design for the CDK9 – cyclin T1 complex

Cyclin dependent kinase 9 (CDK9) is a protein that belongs to the cyclin-dependent kinases family, and its main role is in the regulation of the cell transcription processes. Since the increased activity of CDK9 is connected with the development of pathological processes such as tumor growth and survival and HIV-1 replication, inhibition of the CDK9 could be of particular interest for treating such diseases. The activation of CDK9 is initiated by the formation of CDK9/cyclin T1 complex, therefore disruption of its formation could be a promising strategy for the design of CDK9 inhibitors. In order to assist in the design of potential inhibitors of CDK9/cyclin T1 complex formation, a computational study of the CDK9/cyclin T1 interface was conducted. Ten peptides were designed using the information from the analysis of the complex, hot spot residues and fragment based design. The designed peptides were docked to CDK9 structures obtained by molecular dynamics simulations of CDK9/cyclin T1 complex and the CDK9 alone and their binding affinities were evaluated using molecular mechanics Poisson Boltzman surface area (MM-PBSA) method and steered molecular dynamics (SMD). Designed peptide sequences LQTLGF and ESIILQ, both derived from the surface of cyclin T1, as well as the peptide sequence PRWPE, derived from fragment based design, showed the most favorable binding properties and were selected for our further studies.

Structural insights into binding of small molecule inhibitors to Enhancer of Zeste Homolog 2

Enhancer of Zeste Homolog 2 (EZH2) is a SET domain protein lysine methyltransferase (PKMT) which has recently emerged as a chemically tractable and therapeutically promising epigenetic target, evidenced by the discovery and characterization of potent and highly selective EZH2 inhibitors. However, no experimental structures of the inhibitors co-crystallized to EZH2 have been resolved, and the structural basis for their activity and selectivity remains unknown. Considering the need to minimize cross-reactivity between prospective PKMT inhibitors, much can be learned from understanding the molecular basis for selective inhibition of EZH2. Thus, to elucidate the binding of small-molecule inhibitors to EZH2, we have developed a model of its fully-formed cofactor binding site and used it to carry out molecular dynamics simulations of protein–ligand complexes, followed by molecular mechanics/generalized born surface area calculations. The obtained results are in good agreement with biochemical inhibition data and reflect the structure–activity relationships of known ligands. Our findings suggest that the variable and flexible post-SET domain plays an important role in inhibitor binding, allowing possibly distinct binding modes of inhibitors with only small variations in their structure. Insights from this study present a good basis for design of novel and optimization of existing compounds targeting the cofactor binding site of EZH2.