Jovana B. Veselinović

QSAR as a random event: a case of NOAEL

Quantitative structure–activity relationships (QSAR) for no observed adverse effect levels (NOAEL, mmol/kg/day, in logarithmic units) are suggested. Simplified molecular input line entry systems (SMILES) were used for molecular structure representation. Monte Carlo method was used for one-variable models building up for three different splits into the “visible” training set and “invisible” validation. The statistical quality of the models for three random splits are the following: split 1 n = 180, r2 = 0.718, q2 = 0.712, s = 0.403, F = 454 (training set); n = 17, r2 = 0.544, s = 0.367 (calibration set); n = 21, r2 = 0.61, s = 0.44, rm2 = 0.61 (validation set); split 2 n = 169, r2 = 0.711, q2 = 0.705, s = 0.409, F = 411 (training set); n = 27, r2 = 0.512, s = 0.461 (calibration set); n = 22, r2 = 0.669, s = 0.360, rm2 = 0.63 (validation set); split 3 n = 172, r2 = 0.679, q2 = 0.672, s = 0.420, F = 360 (training set); n = 19, r2 = 0.617, s = 0.582 (calibration set); n = 21, r2 = 0.627, s = 0.367, rm2 = 0.54 (validation set). All models are built according to OCED principles.

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.

Monte Carlo QSAR models for predicting organophosphate inhibition of acetycholinesterase

A series of 278 organophosphate compounds acting as acetylcholinesterase inhibitors has been studied. The Monte Carlo method was used as a tool for building up one-variable quantitative structure–activity relationship (QSAR) models for acetylcholinesterase inhibition activity based on the principle that the target endpoint is treated as a random event. As an activity, bimolecular rate constants were used. The QSAR models were based on optimal descriptors obtained from Simplified Molecular Input-Line Entry System (SMILES) used for the representation of molecular structure. Two modelling approaches were examined: (1) ‘classic’ training-test system where the QSAR model was built with one random split into a training, test and validation set; and (2) the correlation balance based QSAR models were built with two random splits into a sub-training, calibration, test and validation set. The DModX method was used for defining the applicability domain. The obtained results suggest that studied activity can be determined with the application of QSAR models calculated with the Monte Carlo method since the statistical quality of all build models was very good. Finally, structural indicators for the increase and the decrease of the bimolecular rate constant are defined. The possibility of using these results for the computer-aided design of new organophosphate compounds is presented.

QSAR modeling of the antimicrobial activity of peptides as a mathematical function of a sequence of amino acids

Antimicrobial peptides have emerged as new therapeutic agents for fighting multi-drug-resistant bacteria. However, the process of optimizing peptide antimicrobial activity and specificity using large peptide libraries is both tedious and expensive. Therefore, computational techniques had to be applied for process optimization. In this work, the representation of the molecular structure of peptides (mastoparan analogs) by a sequence of amino acids has been used to establish quantitative structure-activity relationships (QSARs) for their antibacterial activity. The data for the studied peptides were split three times into the training, calibration and test sets. The Monte Carlo method was used as a computational technique for QSAR models calculation. The statistical quality of QSAR for the antibacterial activity of peptides for the external validation set was: n=7, r(2)=0.8067, s=0.248 (split 1); n=6, r(2)=0.8319, s=0.169 (split 2); and n=6, r(2)=0.6996, s=0.297 (split 3). The stated statistical parameters favor the presented QSAR models in comparison to 2D and 3D descriptor based ones. The Monte Carlo method gave a reasonably good prediction for the antibacterial activity of peptides. The statistical quality of the prediction is different for three random splits. However, the predictive potential is reasonably well for all cases. The presented QSAR modeling approach can be an attractive alternative of 3D QSAR at least for the described peptides.

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: r2 = 0.8760, q2 = 0.8665, s = 8.94 for the training set and r2 = 0.9812, q2 = 0.9753, s = 7.31 for the test set. For the validation set, the statistical parameters were r2 = 0.727 and s = 12.52, but after removing the three worst outliers, the statistical parameters improved to r2 = 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.

A comparative antimicrobial and toxicological study of gold(III) and silver(I) complexes with aromatic nitrogen-containing heterocycles: synergistic activity and improved selectivity index of Au(III)/Ag(I) complexes mixture

Five aromatic nitrogen-containing heterocycles, pyridazine (pydz, 1), pyrimidine (pm, 2), pyrazine (pz, 3), quinoxaline (qx, 4) and phenazine (phz, 5) have been used for the synthesis of gold(III) and silver(I) complexes. In contrast to the mononuclear Au1–5 complexes all having square-planar geometry, the corresponding Ag1–5 complexes have been found to be polynuclear and of different geometries. Complexes Au1–5 and Ag1–5, along with K[AuCl4], AgNO3 and N-heterocyclic ligands used for their synthesis, were evaluated by in vitro antimicrobial studies against a panel of microbial strains that lead to many skin and soft tissue, respiratory, wound and nosocomial infections. All tested complexes exhibited excellent to good antibacterial activity with minimal inhibitory (MIC) values in the range of 2.5 to 100 μg mL−1 against the investigated strains. The complexes were particularly efficient against pathogenic Pseudomonas aeruginosa (MIC = 2.5–30 μg mL−1) and had a marked ability to disrupt clinically relevant biofilms of strains with high inherent resistance to antibiotics. Moreover, the Au1–4 and Ag1–5 complexes exhibited pronounced ability to competitively intercalate double stranded genomic DNA of P. aeruginosa, which was demonstrated by gel electrophoresis techniques and supported by molecular docking into the DNA major groove. Antiproliferative effect on the normal human lung fibroblast cell line MRC5 has also been evaluated in order to determine therapeutic potential of Au1–5 and Ag1–5 complexes. Since the investigated gold(III) complexes showed much lower negative effects on the viability of the MRC5 cell line than their silver(I) analogues and slightly lower antimicrobial activity against the investigated strains, the combination approach to improve their pharmacological profiles was applied. Synergistic antimicrobial effect and the selectivity index of 10 were achieved for the selected gold(III)/silver(I) complexes mixtures, as well as higher P. aeruginosa PAO1 biofilm disruption activity, and improved toxicity profile towards zebrafish embryos, in comparison to the single complexes. To the best of our knowledge, this is the first report on synergistic activity of gold(III)/silver(I) complexes mixtures and it could have an impact on development of new combination therapy methods for the treatment of multi-resistant bacterial infections.

Nano-QSAR: Model of mutagenicity of fullerene as a mathematical function of different conditions

The experimental data on the bacterial reverse mutation test (under various conditions) on C60 nanoparticles for the cases (i) TA100, and (ii) WP2uvrA/pkM101 are examined as endpoints. By means of the optimal descriptors calculated with the Monte Carlo method a mathematical model of these endpoints has been built up. The models are a mathematical function of eclectic data such as (i) dose (g/plate); (ii) metabolic activation (i.e. with mix S9 or without mix S9); and (iii) illumination (i.e. darkness or irradiation). The eclectic data on different conditions were represented by so-called quasi-SMILES. In contrast to the traditional SMILES which are representation of molecular structure, the quasi-SMILES are representation of conditions by sequence of symbols. The calculations were carried out with the CORAL software, available on the Internet at http://www.insilico.eu/coral. The main idea of the suggested descriptors is the accumulation of all available eclectic information in the role of logical and digital basis for building up a model. The computational experiments have shown that the described approach can be a tool to build up models of mutagenicity of fullerene under different conditions.

Biological activity of Pinus nigra terpenes-Evaluation of FtsZ inhibition by selected compounds as contribution to their antimicrobial activity

In the current work, in vitro antioxidant, antibacterial, and antifungal activites of the needle terpenes of three taxa of Pinus nigra from Serbia (ssp. nigra, ssp. pallasiana, and var. banatica) were analyzed. The black pine essential oils showed generally weak antioxidative properties tested by two methods (DPPH and ABTS scavenging assays), where the highest activity was identified in P. nigra var. banatica (IC50=25.08 mg/mL and VitC=0.67 mg (vitamin C)/g when tested with the DPPH and ABTS reagents, respectively). In the antimicrobial assays, one fungal (Aspergilus niger) and two bacterial strains (Staphylococcus aureus and Bacillus cereus) showed sensitivity against essential oils of all three P. nigra taxa. The tested oils have been shown to possess inhibitory action in the range from 20.00 to 0.62 mg/mL, where var. banatica exhibited the highest and ssp. nigra the lowest antimicrobial action. In order to determine potential compounds that are responsible for alternative mode of action, molecular docking simulations inside FtsZ (a prokaryotic homolog of tubulin) were performed. Tested compounds were the most abundant terpenoid (germacrene D-4-ol) and its structurally similar terpene (germacrene D), both present in all three essential oils. It was determined that the oxygenated form of the molecule creates stable bonds with investigated enzyme FtsZ, and that this compound, through this mechanism of action participates in the antimicrobial activity.

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

In this study QSPR models were developed to predict the complexation of structurally diverse compounds with β-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 β-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 Coumarin Derivates as Potent HIV‐1 Integrase Inhibitors and Molecular Docking Studies of Selected 4‐phenyl Hydroxycoumarins

Summary In search for new and promising coumarin compounds as HIV-1 integrase inhibitors, chemoinformatic methods like quantitative structure-activity relationships (QSAR) modeling and molecular docking have an important role since they can predict desired activity and propose molecule binding to enzyme. The aim of this study was building of QSAR models for coumarin derivatives as HIV-1 integrase inhibitors with the application of Monte Carlo method. SMILES notation was used to represent the molecular structure and for defining optimal SMILES-based descriptors. Molecular docking into rigid enzyme active site with flexible molecule was performed. Computational results indicated that this approach can satisfactorily predict the desired activity with very good statistical significance. For best built model statistical parameters were: a) 3’ Processing activity: R2=0.9980 and Q2=0.9977 for training set and R2=0.9788 for test set and b) Integration activity: R2=0.9999 and Q2=0.9998 for training set and R2= 0.9213 for test set. Built QSAR models were applied to selected 4-phenyl hydroxycoumarins for calculating desired activity and for HIV-1 integrase inhibition estimation. Additionally, molecular docking study was performed to a newly identified pocket in the HIV-1 integrase enzyme structure for determination of selected 4-phenyl hydroxycoumarins binding mode. Monte Carlo method proved to be an efficient approach to build up a robust model for estimating HIV-1 integrase inhibition of coumarin compounds. Based on QSAR and molecular docking studies, 4-phenyl hydroxycoumarins can be considered as promising model compounds for developing new HIV-1 integrase inhibitors.