Slavica Filipic

Multitarget compounds bearing tacrine- and donepezil-like structural and functional motifs for the potential treatment of Alzheimer's disease.

Alzheimers disease is a multifactorial and fatal neurodegenerative disorder characterized by decline of cholinergic function, deregulation of other neurotransmitter systems, β-amyloid fibril deposition, and β-amyloid oligomers formation. Based on the involvement of a relevant number of biological systems in Alzheimers disease progression, multitarget compounds may enable therapeutic efficacy. Accordingly, compounds possessing, besides anticholinergic activity and β-amyloid aggregation inhibition properties, metal chelating and/or nitric oxide releasing properties with additional antioxidant capacity were developed. Other targets relevant to Alzheimers disease have also been considered in the last years for producing multitarget compounds such as β-secretase, monoamino oxidases, serotonin receptors and sigma 1 receptors. The purpose of this review will be to highlight recent reports on the development of multitarget compounds for Alzheimers disease published within the last years focusing on multifunctional ligands characterized by tacrine-like and donepezil-like structures.

Investigation of surfactant/cosurfactant synergism impact on ibuprofen solubilization capacity and drug release characteristics of nonionic microemulsions

The current study investigates the performances of the multicomponent mixtures of nonionic surfactants regarding the microemulsion stabilisation, drug solubilization and in vitro drug release kinetic. The primary surfactant was PEG-8 caprylic/capric glycerides (Labrasol). The cosurfactants were commercially available mixtures of octoxynol-12 and polysorbate 20 without or with the addition of PEG-40 hydrogenated castor oil (Solubilisant gamma 2421 and Solubilisant gamma 2429, respectively). The oil phase of microemulsions was isopropyl myristate. Phase behaviour study of the pseudo-ternary systems Labrasol/cosurfactant/oil/water at surfactant-to-cosurfactant weight ratios (K(m)) 40:60, 50:50 and 60:40, revealed a strong synergism in the investigated tensides mixtures for stabilisation of microemulsions containing up to 80% (w/w) of water phase at surfactant +cosurfactant-to-oil weight ratio (SCoS/O) 90:10. Solubilization of a model drug ibuprofen in concentration common for topical application (5%, w/w) was achieved at the water contents below 50% (w/w). Drug free and ibuprofen-loaded microemulsions M1-M6, containing 45% (w/w) of water phase, were prepared and characterized by polarized light microscopy, conductivity, pH, rheological and droplet size measurements. In vitro ibuprofen release kinetics from the microemulsions was investigated using paddle-over-enhancer cell method and compared with the commercial 5% (w/w) ibuprofen hydrogel product (Deep Relief, Mentholatum Company Ltd., USA). The investigated microemulsions were isotropic, low viscous Bingham-type liquids with the pH value (4.70-6.61) suitable for topical application. The different efficiency of the tensides mixtures for microemulsion stabilisation was observed, depending on the cosurfactant type and K(m) value. Solubilisant gamma 2429 as well as higher K(m) (i.e., lower relative content of the cosurfactant) provided higher surfactant/cosurfactant synergism. The drug molecules were predominantly solubilized within the interface film. The amount of drug released from the formulations M3 (10.75%, w/w) and M6 (13.45%, w/w) (K(m) 60:40) was limited in comparison with the reference (22.22%, w/w) and follows the Higuchi model. Microemulsions M2 and M5 (K(m) 50:50) gave zero order drug release pattern and ∼15% (w/w) ibuprofen released. The release profiles from microemulsions M1 and M4 (K(m) 40:60) did not fit well with the models used for analysis, although the amounts of ibuprofen released (24.47%, w/w) and 17.99% (w/w), respectively) were comparable to that of the reference hydrogel. The drug release mechanism was related with the surfactant/cosurfactant synergism, thus the lower efficiency of the tensides corresponded to the faster drug release.

N-methyl-N-((1-methyl-5-(3-(1-(2-methylbenzyl)piperidin-4-yl)propoxy)-1H-indol-2-yl)methyl)prop-2-yn-1-amine, a new cholinesterase and monoamine oxidase dual inhibitor

On the basis of N-((5-(3-(1-benzylpiperidin-4-yl)propoxy)-1-methyl-1H-indol-2-yl)methyl)-N-methylprop-2-yn-1-amine (II, ASS234) and QSAR predictions, in this work we have designed, synthesized, and evaluated a number of new indole derivatives from which we have identified N-methyl-N-((1-methyl-5-(3-(1-(2-methylbenzyl)piperidin-4-yl)propoxy)-1H-indol-2-yl)methyl)prop-2-yn-1-amine (2, MBA236) as a new cholinesterase and monoamine oxidase dual inhibitor.

QSAR study of imidazoline antihypertensive drugs.

The hypotensive effect of imidazoline ligands was attributed to both alpha(2)-adrenergic receptors and nonadrenergic imidazoline-1 receptors (I(1)-R). Selective I(1)-R ligands, devoid of the typical side effects of other centrally acting antihypertensive drugs, could be widely used in antihypertensive therapy. Thus, there is significant interest in developing new imidazoline analogs with higher selectivity and affinity for I(1) receptors. The quantitative structure-activity relationship (QSAR) study of 12 ligands was carried out using multilinear regression method on I(1)-R and alpha(2)-adrenergic receptors binding affinities on human platelets. The compounds have been studied using Becke3LYP/3-21G (d,p) and Becke3LYP/6-31G(d,p) DFT methods. Among 42 descriptors that were considered in generating the QSAR model, three descriptors such as partial atomic charges of nitrogen in the heterocyclic moiety, distribution coefficient, and molar refractivity of the ligands resulted in a statistically significant model with R(2)=0.935 and cross-validation parameter q(2)(pre) =0.803. The validation of the QSAR models was done by cross-validation and external test set prediction. The developed multiple linear regression models for the I(1)-R ligands were aimed to link the structures to their reported I(1)-R binding affinity log(1/K(i)). The theoretical approach indicates that an increase in distribution coefficient and molar refractivity value, together with a decrease in average N-charge in the heterocyclic moiety of the ligands, causes better binding affinity for active site of the I(1) receptors. The developed QSAR model is intended to predict I(1)-R binding affinity of related compounds and to define possible physicochemical, electrical, and structural requirements for selective I(1)-receptor ligands.

Procognitive Properties of Drugs with Single and Multitargeting H3 Receptor Antagonist Activities

The histamine H3 receptor (H3R) is an important modulator of numerous central control mechanisms. Novel lead optimizations for H3R antagonists/inverse agonists involved studies of structure–activity relationships, cross‐affinities, and pharmacokinetic properties of promising ligands. Blockade of inhibitory histamine H3 autoreceptors reinforces histaminergic transmission, while antagonism of H3 heteroreceptors accelerates the corticolimbic liberation of acetylcholine, norepinephrine, glutamate, dopamine, serotonin and gamma‐aminobutyric acid (GABA). The H3R positioned at numerous neurotransmission crossroads indicates therapeutic applications of small‐molecule H3R modulators in a number of psychiatric and neurodegenerative diseases with various clinical candidates available. Dual target drugs displaying H3R antagonism/inverse agonism with inhibition of acetylcholine esterase (AChE), histamine N‐methyltransferase (HMT), or serotonin transporter (SERT) are novel class of procognitive agents. Main chemical diversities, pharmacophores, and pharmacological profiles of procognitive agents acting as H3R antagonists/inverse agonists and dual H3R antagonists/inverse agonists with inhibiting activity on AChE, HMT, or SERT are highlighted here.

Quantitative structure-mobility relationship analysis of imidazoline receptor ligands in CDs-mediated CE

The performed quantitative structure‐mobility relationship (QSMR) study has investigated relative migration times of 11 guanidine/imidazoline derivatives, imidazoline receptor ligands, in CE system containing one of CDs, α‐, β‐, or γ‐CD, using linear and nonlinear modeling methods. The analyzed ligands and their inclusion complexes with CDs were fully examined and optimized at semiempirical parametrized model 3 level. The density functional theory, such as B3LYP/6–31G+(d,p)/3–21G(d)/STO‐3G(d,p)/STO‐3G(d), and ab initio theory, such as HF/3–21G(d)/STO‐3G(d), were applied for molecular descriptors computation of the optimized ligands and their complexes. Predictive performances of the developed QSMR models were tested by use of the cross‐validation and external test set prediction. Obtained results for Q2 values (0.869, 0.911, and 0.966 for CE system containing α‐, β‐, and γ‐CD, respectively) and root mean squared error of prediction (0.239, 0.242, and 0.288 for α‐, β‐, and γ‐CD, respectively) were proved high predictive power of the proposed models. Finally, multitarget QSMR model, using the ligands descriptors (X) and the relative migration time in presence of α‐CD (Y1), β‐CD (Y2), and γ‐CD (Y3), has been created. The multitarget QSMR model can be used as initial screening predictive tool for CE migration behavior of other related guanidine/imidazoline derivatives in presence of α‐, β‐, and γ‐CD.

Polypharmacology of dopamine receptor ligands

Most neurological diseases have a multifactorial nature and the number of molecular mechanisms discovered as underpinning these diseases is continuously evolving. The old concept of developing selective agents for a single target does not fit with the medical need of most neurological diseases. The development of designed multiple ligands holds great promises and appears as the next step in drug development for the treatment of these multifactorial diseases. Dopamine and its five receptor subtypes are intimately involved in numerous neurological disorders. Dopamine receptor ligands display a high degree of cross interactions with many other targets including G-protein coupled receptors, transporters, enzymes and ion channels. For brain disorders like Parkinsońs disease, schizophrenia and depression the dopaminergic system, being intertwined with many other signaling systems, plays a key role in pathogenesis and therapy. The concept of designed multiple ligands and polypharmacology, which perfectly meets the therapeutic needs for these brain disorders, is herein discussed as a general ligand-based concept while focusing on dopaminergic agents and receptor subtypes in particular.

ESTIMATION OF LIPOPHILICITY AND RETENTION BEHAVIOR OF SOME ALPHA ADRENERGIC AND IMIDAZOLINE RECEPTOR LIGANDS USING RP-TLC

The chromatographic behavior of 16 alpha adrenergic and imidazoline receptor ligands has been studied by reversed-phase thin-layer chromatography (RP-TLC) on RP-18 and CN stationary phases. Retention constant was determined for all tested compounds in three different chromatographic systems: methanol–water/RP-18, tetrahydrofuran–ammonia-water/RP-18, and tetrahydrofuran–ammonia–water/CN. Good correlations between determined hydrophobic parameters and calculated log P values were obtained for the system tetrahydrofuran–ammonia–water on both RP-18 and CN stationary phases. Experimentally obtained values and computed molecular parameters of the examined compounds were further used for the quantitative structure–retention relationship (QSRR) study, in order to determine the most important properties governing retention. The QSRR modeling was performed with use of the partial least squares regression, and predictive performances of the developed QSRR models were tested by use of the cross-validation and external test set prediction. The created models revealed that apart from lipophilicity, constitutional descriptors, the amount of van der Waals surface area having a property P (P_VSA-like descriptors), and hydrogen bonding properties of the tested compounds were important for the retention behavior in the RP-TLC systems.

Quantitative structure-retention relationship of selected imidazoline derivatives on α1-acid glycoprotein column

The retention behaviour of 22 selected imidazoline drugs and derivatives was investigated on α1-acid glycoprotein (AGP) column using Sørensen phosphate buffer (pH 7.0) and 2-propanol as organic modifier. Quantitative Structure-Retention Relationships (QSRR) models were built using extrapolated logkw values as well as isocratic retention factors (logk5, logk8, logk10, logk12, logk15 obtained for 5%, 8%, 10%, 12%, and 15%, of 2-propanol in mobile phase, respectively) as dependant variables and calculated physicochemical parameters as independant variables. The established QSRR models were built by stepwise multiple linear regression (MLR) and partial least squares regression (PLS). The performance of the stepwise and PLS models was tested by cross-validation and the external test set prediction. The validated QSRR models were compared and the optimal PLS-QSRR model for logkw and each isocratic retention factors (PLS-QSRR(logk5), PLS-QSRR(logk8), PLS-QSRR(logk10), MLR-QSRR(logk12), MLR-QSRR(logk15)) were selected. The QSRR results were further confirmed by Linear Solvation Energy Relationships (LSER). LSER analysis indicated on hydrogen bond basicity, McGowan volume and excess molar refraction as the most significant parameters for all AGP chromatographic retention factors and logkw values of 22 selected imidazoline drugs and derivatives.

Multi-target QSAR and docking study of steroids binding to corticosteroid-binding globulin and sex hormone-binding globulin.

The QSAR and docking studies were performed on fifty seven steroids with binding affinities for corticosteroid-binding globulin (CBG) and eighty four steroids with binding affinities for sex hormone-binding globulin (SHBG). Since the steroidal compounds have binding affinity for both CBG and SHBG, multi-target QSAR approach was employed to establish a unique QSAR method for simultaneous evaluation of the CBG and SHBG binding affinities. The constitutional, geometrical, physico-chemical and electronic descriptors were computed for the examined structures by use of the Chem3D Ultra 7.0.0, the Dragon 6.0, the MOPAC2009, and the Chemical Descriptors Library (CDL) program. Partial least squares regression (PLSR) has been applied for selection of the most relevant molecular descriptors and QSAR models building. The QSAR (SHGB) model, QSAR model (CBG), and multi-target QSAR model (CBG, SHBG) were created. The multi-target QSAR model (CBG and SHBG) was found to be more effective in describing the CBG and SHBG affinity of steroids in comparison to the one target models (QSAR (SHGB) model, QSAR model (CBG)). The multi-target QSAR study indicated the importance of the electronic descriptor (Mor16v), steric/symmetry descriptors (Eig06_EA(ed)), 2D autocorrelation descriptor (GATS4m), distance distribution descriptor (RDF045m), and atom type fingerprint descriptor (CDL-ATFP 253) in describing the CBG and SHBG affinity of steroidal compounds. Results of the created multi-target QSAR model were in accordance with the performed docking studies. The theoretical study defined physicochemical, electronic and structural requirements for selective and effective binding of steroids to the CBG and SHBG active sites.