Svava Ósk Jónsdóttir

Prediction methods and databases within chemoinformatics: emphasis on drugs and drug candidates

MOTIVATION To gather information about available databases and chemoinformatics methods for prediction of properties relevant to the drug discovery and optimization process. RESULTS We present an overview of the most important databases with 2-dimensional and 3-dimensional structural information about drugs and drug candidates, and of databases with relevant properties. Access to experimental data and numerical methods for selecting and utilizing these data is crucial for developing accurate predictive in silico models. Many interesting predictive methods for classifying the suitability of chemical compounds as potential drugs, as well as for predicting their physico-chemical and ADMET properties have been proposed in recent years. These methods are discussed, and some possible future directions in this rapidly developing field are described.

Prediction of pH-dependent aqueous solubility of druglike molecules

In the present work, the Henderson-Hasselbalch (HH) equation has been employed for the development of a tool for the prediction of pH-dependent aqueous solubility of drugs and drug candidates. A new prediction method for the intrinsic solubility was developed, based on artificial neural networks that have been trained on a druglike PHYSPROP subset of 4548 compounds. For the prediction of acid/base dissociation coefficients, the commercial tool Marvin has been used, following validation on a data set of 467 molecules from the PHYSPROP database. The best performing network for intrinsic solubility predictions has a cross-validated root mean square error (RMSE) of 0.70 log S-units, while the Marvin pKa plug-in has an RMSE of 0.71 pH-units. A data set of 27 drugs with experimentally determined pH-solubility curves was assembled from the literature for the validation of the combined pH-dependent model, giving a mean RMSE of 0.79 log S-units. Finally, the combined model has been applied on profiling the solubility space at low pH of five large vendor libraries.

Modeling and measurements of solid-liquid and vapor-liquid equilibria of polyols and carbohydrates in aqueous solution

The solubilities of five saccharides in water have been measured at various temperatures. This includes the monosaccharides xylose and galactose, and the disaccharides maltose monohydrate, cellobiose and trehalose dihydrate. A method that uses interaction energies and interaction parameters calculated with molecular mechanics methods has shown to give good predictions of the phase behavior of a variety of mixtures, including glycols and small saccharides in aqueous solution. The method is completely predictive, as the strength of the molecular interactions is determined with a theoretical method in the absence of any phase equilibrium data. For calculating solubilities, experimental values for the melting points and the heats of fusion of the compounds under study are, however, necessary. The solubilities of the five saccharides listed above, raffinose and meso-erythritol in water were calculated with this method. The calculated solubilities are in reasonably good agreement with experiment, and in the case of meso-erythritol, which is a polyalcohol (polyol), and galactose, the agreement between prediction and experiment is excellent. Also the vapor pressures of water over several polyols and saccharides in aqueous solution have been predicted with this method, giving results in excellent agreement with the experimental values.

Identification of biomarkers for genotyping Aspergilli using non-linear methods for clustering and classification

BackgroundIn the present investigation, we have used an exhaustive metabolite profiling approach to search for biomarkers in recombinant Aspergillus nidulans (mutants that produce the 6- methyl salicylic acid polyketide molecule) for application in metabolic engineering.ResultsMore than 450 metabolites were detected and subsequently used in the analysis. Our approach consists of two analytical steps of the metabolic profiling data, an initial non-linear unsupervised analysis with Self-Organizing Maps (SOM) to identify similarities and differences among the metabolic profiles of the studied strains, followed by a second, supervised analysis for training a classifier based on the selected biomarkers. Our analysis identified seven putative biomarkers that were able to cluster the samples according to their genotype. A Support Vector Machine was subsequently employed to construct a predictive model based on the seven biomarkers, capable of distinguishing correctly 14 out of the 16 samples of the different A. nidulans strains.ConclusionOur study demonstrates that it is possible to use metabolite profiling for the classification of filamentous fungi as well as for the identification of metabolic engineering targets and draws the attention towards the development of a common database for storage of metabolomics data.

QSAR model for human pregnane X receptor (PXR) binding: screening of environmental chemicals and correlations with genotoxicity, endocrine disruption and teratogenicity.

The pregnane X receptor (PXR) has a key role in regulating the metabolism and transport of structurally diverse endogenous and exogenous compounds. Activation of PXR has the potential to initiate adverse effects, causing drug-drug interactions, and perturbing normal physiological functions. Therefore, identification of PXR ligands would be valuable information for pharmaceutical and toxicological research. In the present study, we developed a quantitative structure-activity relationship (QSAR) model for the identification of PXR ligands using data based on a human PXR binding assay. A total of 631 molecules, representing a variety of chemical structures, constituted the training set of the model. Cross-validation of the model showed a sensitivity of 82%, a specificity of 85%, and a concordance of 84%. The developed model provided knowledge about molecular descriptors that may influence the binding of molecules to PXR. The model was used to screen a large inventory of environmental chemicals, of which 47% was found to be within domain of the model. Approximately 35% of the chemicals within domain were predicted to be PXR ligands. The predicted PXR ligands were found to be overrepresented among chemicals predicted to cause adverse effects, such as genotoxicity, teratogenicity, estrogen receptor activation and androgen receptor antagonism compared to chemicals not causing these effects. The developed model may be useful as a tool for predicting potential PXR ligands and for providing mechanistic information of toxic effects of chemicals.

Discovery of a novel selective PPARγ ligand with partial agonist binding properties by integrated in silico/in vitro work flow.

Full agonists to the peroxisome proliferator-activated receptor (PPAR)γ, such as Rosiglitazone, have been associated with a series of undesired side effects, such as weight gain, fluid retention, cardiac hypertrophy, and hepatotoxicity. Nevertheless, PPARγ is involved in the expression of genes that control glucose and lipid metabolism and is an important target for drugs against type 2 diabetes, dyslipidemia, atherosclerosis, and cardiovascular disease. In an effort to identify novel PPARγ ligands with an improved pharmacological profile, emphasis has shifted to selective ligands with partial agonist binding properties. Toward this end we applied an integrated in silico/in vitro workflow, based on pharmacophore- and structure-based virtual screening of the ZINC library, coupled with competitive binding and transactivation assays, and adipocyte differentiation and gene expression studies. Hit compound 9 was identified as the most potent ligand (IC50 = 0.3 μM) and a relatively poor inducer of adipocyte differentiation. The binding mode of compound 9 was confirmed by molecular dynamics simulation, and the calculated free energy of binding was -8.4 kcal/mol. A novel functional group, the carbonitrile group, was identified to be a key substituent in the ligand-protein interactions. Further studies on the transcriptional regulation properties of compound 9 revealed a gene regulatory profile that was to a large extent unique, however functionally closer to that of a partial agonist.

Structural insight into the UNC-45–myosin complex

The UNC‐45 chaperone protein interacts with and affects the folding, stability, and the ATPase activity of myosins. It plays a critical role in the cardiomyopathy development and in the breast cancer tumor growth. Here we propose the first structural model of the UNC‐45–myosin complex using various in silico methods. Initially, the human UNC‐45B binding epitope was identified and the protein was docked to the cardiac myosin (MYH7) motor domain. The final UNC45B–MYH7 structure was obtained by performing of total 630 ns molecular dynamics simulations. The results indicate a complex formation, which is mainly stabilized by electrostatic interactions. Remarkably, the contact surface area is similar to that of the myosin‐actin complex. A significant interspecies difference in the myosin binding epitope is observed. Our results reveal the structural basis of MYH7 exons 15–16 hypertrophic cardiomyopathy mutations and provide directions for drug targeting. Proteins 2013; 81:1212–1221.

UNIQUAC interaction parameters for alkane/amine systems determined by Molecular Mechanics

Abstract UNIQUAC interaction parameters have been successfully determined for three alkane/primary amine systems using a Molecular Mechanics method calledthe Consistent Force Field. Interaction parameters for alkane/alkane and alkane/ketone systems had been determined previously using this method and in this contribution the method has been extended to polar systems with extensive hydrogen bonding. It is thus possible to predict reliable vapor liquid equilibrium data using pure component data only. A method for finding the global minimum on the potential energy surface of a pair of molecules was developed. Good results were obtained in most cases but for a pair of cyclic molecules and a pair of ethylamine molecules this simple procedure was not satisfactory. A more objective method is desirable and the Boltzmann Jump search procedure seems to be such a method. Promising results have been obtained using the Boltzmann Jump search procedure for investigating the conformational space of a pair of molecules.

Phase equilibria of carbohydrates in polar solvents

Abstract A method for calculating interaction energies and interaction parameters with molecular mechanics methods is extended to predict solid–liquid equilibria (SLE) for saccharides in aqueous solution, giving results in excellent agreement with experimental values. Previously, the method has been shown to be suitable for predicting vapor–liquid equilibria (VLE) for a variety of mixtures.

An in silico study of the molecular basis of B-RAF activation and conformational stability.

BackgroundB-RAF kinase plays an important role both in tumour induction and maintenance in several cancers and it is an attractive new drug target. However, the structural basis of the B-RAF activation is still not well understood.ResultsIn this study we suggest a novel molecular basis of B-RAF activation based on molecular dynamics (MD) simulations of B-RAFWT and the B-RAFV600E, B-RAFK601E and B-RAFD594V mutants. A strong hydrogen bond network was identified in B-RAFWT in which the interactions between Lys601 and the well known catalytic residues Lys483, Glu501 and Asp594 play an important role. It was found that several mutations, which directly or indirectly destabilized the interactions between these residues within this network, contributed to the changes in B-RAF activity.ConclusionOur results showed that the above mechanisms lead to the disruption of the electrostatic interactions between the A-loop and the αC-helix in the activating mutants, which presumably contribute to the flipping of the activation segment to an active form. Conversely, in the B-RAFD594V mutant that has impaired kinase activity, and in B-RAFWT these interactions were strong and stabilized the kinase inactive form.