Development of Novel Therapeutics for Schizophrenia Treatment Based on a Selective Positive Allosteric Modulation of α1-Containing GABAARs-In Silico Approach.

For the development of atypical antipsychotics, the selective positive allosteric modulation of the ionotropic GABAA receptor (GABAAR) has emerged as a promising approach. In the presented research, two unrelated methods were used for the development of QSAR models for selective positive allosteric modulation of 1-containing GABAARs with derivatives of imidazo [1,2-a]-pyridine. The development of conformation-independent QSAR models, based on descriptors derived from local molecular graph invariants and SMILES notation, was achieved with the Monte Carlo optimization method. From the vast pool of 0D, 1D, and 2D molecule descriptors, the GA-MLR method developed additional QSAR models. Various statistical methods were utilised for the determination of the developed models' robustness, predictability, and overall quality, and according to the obtained results, all QSAR models are considered good. The molecular fragments that have a positive or negative impact on the studied activity were obtained from the studied molecules' SMILES notations, and according to the obtained results, nine novel compounds were designed. The binding affinities to GABAAR of designed compounds were assessed with the application of molecular docking studies and the obtained results showed a high correlation with results obtained from QSAR modeling. To assess all designed molecules' "drug-likeness", their physicochemical descriptors were computed and utilised for the prediction of medicinal chemistry friendliness, pharmacokinetic properties, ADME parameters, and druglike nature.

Synthesis, spectroscopic and structural characterization of Co(II)-pullulan complexes by UV-Vis, ATR-FTIR, MALDI-TOF/TOF MS and XRD.

Complexes of Co(II) ion with reduced low-molar pullulan (RLMP) (Mw 6000 g/mol) were synthesized in aqueous solutions at boiling temperature in the pH range from 7.5 to 13.5. Obtained Co(II)-RLMP complexes, with cobalt content ∼2-8% (AAS), were characterized by UV-Vis spectrophotometry, FTIR spectroscopy (ATR-FTIR, FT-IRIS), MALDI-TOF/TOF MS, and XRD. Tetragonally distorted Oh coordination of Co(II) ions with O ligand atoms in synthesized complexes is suggested based on the spectrophotometric data. No influence of complexation process on the 4C1 chair conformation of the d-glucopyranose units of pullulan was detected by ATR-FTIR measurements and FT-IRIS showed high homogeneity of synthesized complexes. Some additional depolymerization of pullulan during complex synthesis was indicated by MALDI-TOF/TOF MS but it also revealed good stability of complexes with much weaker binding of Co(II) ion in low molar mass fragments. Even in complexes with highest Co(II) ion content a low degree of crystallinity was detected by XRD analysis.

In silico prediction of the ß-cyclodextrin complexation based on Monte Carlo method.

In this study QSPR models were developed to predict the complexation of structurally diverse compounds with ß-cyclodextrin based on SMILES notation optimal descriptors using Monte Carlo method. The predictive potential of the applied approach was tested with three random splits into the sub-training, calibration, test and validation sets and with different statistical methods. Obtained results demonstrate that Monte Carlo method based modeling is a very promising computational method in the QSPR studies for predicting the complexation of structurally diverse compounds with ß-cyclodextrin. The SMILES attributes (structural features both local and global), defined as molecular fragments, which are promoters of the increase/decrease of molecular binding constants were identified. These structural features were correlated to the complexation process and their identification helped to improve the understanding for the complexation mechanisms of the host molecules.

Monte Carlo method based QSAR modeling of maleimide derivatives as glycogen synthase kinase-3ß inhibitors.

The Monte Carlo method was used for QSAR modeling of maleimide derivatives as glycogen synthase kinase-3ß inhibitors. The first QSAR model was developed for a series of 74 3-anilino-4-arylmaleimide derivatives. The second QSAR model was developed for a series of 177 maleimide derivatives. QSAR models were calculated with the representation of the molecular structure by the simplified molecular input-line entry system. Two splits have been examined: one split into the training and test set for the first QSAR model, and one split into the training, test and validation set for the second. The statistical quality of the developed model is very good. The calculated model for 3-anilino-4-arylmaleimide derivatives had following statistical parameters: r(2)=0.8617 for the training set; r(2)=0.8659, and r(m)(2)=0.7361 for the test set. The calculated model for maleimide derivatives had following statistical parameters: r(2)=0.9435, for the training, r(2)=0.9262 and r(m)(2)=0.8199 for the test and r(2)=0.8418, r(av)(m)(2)=0.7469 and ∆r(m)(2)=0.1476 for the validation set. Structural indicators considered as molecular fragments responsible for the increase and decrease in the inhibition activity have been defined. The computer-aided design of new potential glycogen synthase kinase-3ß inhibitors has been presented by using defined structural alerts.

Application of SMILES Notation Based Optimal Descriptors in Drug Discovery and Design.

SMILES notation based optimal descriptors as a universal tool for the QSAR analysis with further application in drug discovery and design is presented. The basis of this QSAR modeling is Monte Carlo method which has important advantages over other methods, like the possibility of analysis of a QSAR as a random event, is discussed. The advantages of SMILES notation based optimal descriptors in comparison to commonly used descriptors are defined. The published results of QSAR modeling with SMILES notation based optimal descriptors applied for various pharmacologically important endpoints are listed. The presented QSAR modeling approach obeys OECD principles and has mechanistic interpretation with possibility to identify molecular fragments that contribute in positive and negative way to studied biological activity, what is of big importance in computer aided drug design of new compounds with desired activity.

Selected 4-phenyl hydroxycoumarins: in vitro cytotoxicity, teratogenic effect on zebrafish (Danio rerio) embryos and molecular docking study.

A study of structure cytotoxic-activity relationship of three hydroxy 4-phenyl-coumarins and basic coumarin molecule against two human cell lines (MRC5 fibroblasts and A375 melanoma cells) is presented. Of all investigated compounds the highest cytotoxic activity in both cell lines was determined for 7,8-dihydroxy-4-phenyl coumarin. SAR studies revealed the influence of phenyl group and hydroxyl group's number and position on cytotoxic activity. In addition, to get an insight about their binding preferences at the active site of the receptor (catalytic subunit of cAMP-dependent protein kinase) molecular docking studies were performed. Docking studies suggest that 4-phenyl hydroxycoumarins are potent cAMP-dependent protein kinase inhibitors, better than their analogs without phenyl group. The teratogenic potential was assessed in zebrafish embryo toxicity test and results showed that 4-phenyl dihydroxycoumarins were more while 7-hydroxy-4-phenyl coumarin was less embryo toxic in comparison to coumarin. In order to examine selected 4-phenyl hydroxycoumarins as a new lead compounds the druglikeness of selected 4-phenyl hydroxycoumarins was estimated by using Lipinski's "rule of five". All selected 4-phenyl hydroxycoumarins proved to have satisfying pharmacokinetic profile.

Monte carlo method-based QSAR modeling of penicillins binding to human serum proteins.

The binding of penicillins to human serum proteins was modeled with optimal descriptors based on the Simplified Molecular Input-Line Entry System (SMILES). The concentrations of protein-bound drug for 87 penicillins expressed as percentage of the total plasma concentration were used as experimental data. The Monte Carlo method was used as a computational tool to build up the quantitative structure-activity relationship (QSAR) model for penicillins binding to plasma proteins. One random data split into training, test and validation set was examined. The calculated QSAR model had the following statistical parameters: r(2) = 0.8760, q(2) = 0.8665, s = 8.94 for the training set and r(2) = 0.9812, q(2) = 0.9753, s = 7.31 for the test set. For the validation set, the statistical parameters were r(2) = 0.727 and s = 12.52, but after removing the three worst outliers, the statistical parameters improved to r(2) = 0.921 and s = 7.18. SMILES-based molecular fragments (structural indicators) responsible for the increase and decrease of penicillins binding to plasma proteins were identified. The possibility of using these results for the computer-aided design of new penicillins with desired binding properties is presented.

QSAR Models for the Reactivation of Sarin Inhibited AChE by Quaternary Pyridinium Oximes Based on Monte Carlo Method.

For three random splits, one-variable models of oximes reactivation of sarin inhibited acetylcholinesterase (logarithm of the AChE reactivation percentage by oximes with concentration of 0.001 M) have been calculated with CORAL software. The total number of considered oximes was 42. Simplified molecular input line entry system (SMILES) and hydrogen-suppressed graph (HSG) are used to represent the molecular structure. Using CORAL software by means of the calculation with Monte Carlo optimization of the so called correlation weights for the molecular fragments, optimal SMILES-based descriptors were defined, which are correlated with an endpoint for the training set. The predictability of these descriptors for an external test are estimated. In this study hybrid representation HSG together with SMILES was used. The "classic" scheme (i.e. split data into the training set and test set) of building up quantitative structure-activity relationships was employed. Computational experiments indicated that this approach can satisfactorily predict the desired endpoint. Best model had following statistical characteristics n=32, r2= 0.6012, s= 0.279, F= 45 for training and n=10, r2= 0.9301, s= 0.076, Rm2=0.9206 for test set.

Antioxidant properties of selected 4-phenyl hydroxycoumarins: Integrated in vitro and computational studies.

A study on the structure-activity relationship of three hydroxy 4-phenyl coumarins, carried out by employing a series of different chemical cell-free tests is presented. Different assays involving one redox reaction with the oxidant (DPPH, ABTS, FRAP and CUPRAC) were employed. Further, the measurement of inhibition of oxidative degradation, such as lipid peroxidation, was used to define compound antioxidant activity. Our results confirm the good antioxidant activity of the 7,8-dihydroxy-4-phenyl coumarin and moderate antioxidant activity of 5,7-dihydroxy-4-phenyl coumarin. In this work, quantum chemical calculations based on density functional theory have been employed at B3LYP/6-311++G(d,p) level of theory to study the influence of number and position of hydroxyl groups in coumarin molecules on antioxidant activity. Calculated values for HOMO and LUMO energies, energy gap, stabilization energies and spin density distribution confirmed experimental results and were used for SAR definition. For determination of reaction mechanism in gas phase and selected solvents bond dissociation enthalpy, adiabatic ionization potential, proton dissociation enthalpy, proton affinity, electron transfer enthalpy and gas phase acidity have been calculated. Hydrogen Atom Transfer mechanism in vacuum and Single-Electron Transfer followed by the Proton Transfer mechanism in other studied systems are most probable free radical scavenging pathways. On the basis of these findings, these hydroxy 4-phenyl coumarins may be considered as potential therapeutic candidates for pathological conditions characterized by free radical overproduction.

QSAR models for the reactivation of sarin inhibited acetylcholinesterase by quaternary pyridinium oximes based on Monte Carlo method.

Monte Carlo method has been used as a computational tool for building QSAR models for the reactivation of sarin inhibited acetylcholinesterase (AChE) by quaternary pyridinium oximes. Simplified molecular input line entry system (SMILES) together with hydrogen-suppressed graph (HSG) was used to represent molecular structure. Total number of considered oximes was 46 and activity was defined as logarithm of the AChE reactivation percentage by oximes with concentration of 0.001 M. One-variable models have been calculated with CORAL software for one data split into training, calibration and test set. Computational experiments indicated that this approach can satisfactorily predict the desired endpoint. Best QSAR model had the following statistical parameters: for training set r2=0.7096, s=0.177, MAE=0.148; calibration set: r2=0.6759, s=0.330, MAE=0.271 and test set: r2=0.8620, s=0.182, MAE=0.150. Structural indicators (SMILES based molecular fragments) for the increase and the decrease of the stated activity are defined. Using defined structural alerts computer aided design of new oxime derivatives with desired activity is presented.

Two 6-(propan-2-yl)-4-methyl-morpholine-2,5-diones as new non-purine xanthine oxidase inhibitors and anti-inflammatory agents.

Two cyclodidepsipeptides, 3-(2-methylpropyl)-6-(propan-2-yl)-4-methyl-morpholine-2,5-dione (1) and 3,6-di(propan-2-yl)-4-methyl-morpholine-2,5-dione (2), were evaluated for inhibitory activity against commercial enzyme xanthine oxidase (XO) in vitro and XO in rat liver homogenate as well as for anti-inflammatory response on human peripheral blood mononuclear cells (PBMCs). Both of cyclodidepsipeptides were excellent inhibitors of XO and significantly suppressed the nuclear factor of κB (NF-κB) activation. Allopurinol, a widely used XO inhibitor and drug to treat gout, relevated stronger inhibitory effect on rat liver XO activity than those of compounds 1 and 2. Molecular docking studies were performed to gain an insight into their binding modes with XO. The studied morpholine-diones derivatives exerting XO inhibition and anti-inflammatory effect may give a promise to be used in the treatment of gout and other excessive uric acid production or inflammatory conditions.

SMILES-based QSAR model for arylpiperazines as high-affinity 5-HT(1A) receptor ligands using CORAL.

A predictive quantitative structure - activity relationships model of arylpiperazines as high-affinity 5-HT(1A) receptor ligands was developed using CORAL software (http://www.insilico.eu/CORAL). Simplified molecular input-line entry system (SMILES) was used as representation of the molecular structure of the arylpiperazines. The balance of correlations was used in the Monte Carlo optimization aimed to build up optimal descriptors for one-variable models. The robustness of this model has been tested in four random splits into the sub-training, calibration, and test set. The obtained results reveal good predictive potential of the applied approach: correlation coefficients (r²) for the test sets of the four random splits are 0.9459, 0.9249, 0.9473 and 0.9362.

SMILES-based QSAR models for the calcium channel-antagonistic effect of 1,4-dihydropyridines.

The activity of 72 1,4-dihydropyridines as calcium channel antagonists was examined. The simplified molecular input-line entry system (SMILES) was used as representation of the molecular structure of the calcium channel antagonists. Quantitative structure-activity relationships (QSARs) were developed using CORAL software (http://www.insilico.eu/CORAL) for four random splits of the data into the training and test sets. Using the Monte Carlo method, the CORAL software generated the optimal descriptors for one-variable models. The reproducibility of each model was tested performing three runs of the Monte Carlo optimization. The obtained results reveal good predictive potential of the applied approach: The correlation coefficients (r(2) ) for the test sets of the four random splits are 0.9571, 0.9644, 0.9836, and 0.9444.

Synthesis, physicochemical and spectroscopic characterization of copper(II)-polysaccharide pullulan complexes by UV-vis, ATR-FTIR, and EPR.

Bioactive copper(II) complexes with polysaccharides, like pullulan and dextran, are important in both veterinary and human medicine for the treatment of hypochromic microcitary anemia and hypocupremia. In aqueous alkaline solutions, Cu(II) ion forms complexes with the exopolysaccharide pullulan and its reduced low-molecular derivative. The metal content and the solution composition depend on pH, temperature, and time of the reaction. The complexing process begins in a weak alkali solution (pH >7) and involves OH groups of pullulan monomer (glucopyranose) units. Complexes of Cu(II) ion with reduced low-molecular pullulan (RLMP, M(w) 6000 g mol(-1)) were synthesized in water solutions, at the boiling temperature and at different pH values ranging from 7.5 to 12. The Cu(II) complex formation with RLMP was analyzed by UV-vis spectrophotometry and other physicochemical methods. Spectroscopic characterizations (ATR-FTIR, FT-IRIS, and EPR) and spectra-structure correlation of Cu(II)-RLMP complexes were also carried out.