Marjana Novič | Karolinska Institutet (original) (raw)
Papers by Marjana Novič
Additional file 11. Training set input file used for the modelling of bio-concentration factor.
Additional file 9. The file containing smiles of compounds used for modelling acute toxicity.
Background: CPANNatNIC is software for development of counter-propagation artificial neural netwo... more Background: CPANNatNIC is software for development of counter-propagation artificial neural network models.
Besides the interface for training of a new neural network it also provides an interface for visualisation of the results
which was developed to aid in interpretation of the results and to use the program as a tool for read-across.
Results: The work presents the details of the program’s interface. Parts of the interface are presented and how they
can be used. The examples provided show how the user can build a new model and view the results of predictions
using the interface. Examples are given to show how the software may be used in read-across.
Conclusions: CPANNatNIC provides a simple user interface for model development and visualisation. The interface
implements options which may simplify read-across procedure. Statistical results show better prediction accuracy of
read-across predictions than model predictions where similar compounds could be identified, which indicates the
importance of using read-across and usefulness of the program.
Additional file 10. File with read-across results for acute toxicity validation set.
F1000Research, 2013
Figure 4b: NMR structure of TM3 Conclusions BTL shows no sequence homology Contains two motif... more Figure 4b: NMR structure of TM3 Conclusions BTL shows no sequence homology Contains two motifs conserved in alpha-phycocyanins Four transmembrane domains are predicted for BTL Stable alpha-helical structures are maintained by all the four transmembrane domains Most favored transmembrane domain arrangement type is ABDC Transmembrane regions TM2 and TM3 are found to play significant role in formation of transport channel, ligand interaction and mediation (Ab studies and sequence analysis) Solvent accessible Ser and Cys are present at both ends of the probable transport channel, providing H-bond formnig residues for substrate binding (experimental and theoretical) TM2 forms helix-loop-helix motif , with an angle of ~80° NMR structures further provide evidence for possible allosteric mechanism Presence of two conserved motifs at both ends of the probable transport channel suggest substrate transport in both directions
Computational and Structural Biotechnology Journal, 2017
The structural and functional details of transmembrane proteins are vastly underexplored, mostly ... more The structural and functional details of transmembrane proteins are vastly underexplored, mostly due to experimental difficulties regarding their solubility and stability. Currently, the majority of transmembrane protein structures are still unknown and this present a huge experimental and computational challenge. Nowadays, thanks to X-ray crystallography or NMR spectroscopy over 3000 structures of membrane proteins have been solved, among them only a few hundred unique ones. Due to the vast biological and pharmaceutical interest in the elucidation of the structure and the functional mechanisms of transmembrane proteins, several computational methods have been developed to overcome the experimental gap. If combined with experimental data the computational information enables rapid, low cost and successful predictions of the molecular structure of unsolved proteins. The reliability of the predictions depends on the availability and accuracy of experimental data associated with structural information. In this review, the following methods are proposed for in silico structure elucidation: sequence-dependent predictions of transmembrane regions, predictions of transmembrane helixhelix interactions, helix arrangements in membrane models, and testing their stability with molecular dynamics simulations. We also demonstrate the usage of the computational methods listed above by proposing a model for the molecular structure of the transmembrane protein bilitranslocase. Bilitranslocase is bilirubin membrane transporter, which shares similar tissue distribution and functional properties with some of the members of the Organic Anion Transporter family and is the only member classified in the Bilirubin Transporter Family. Regarding its unique properties, bilitranslocase is a potentially interesting drug target.
Quantitative Structure-Activity Relationships in Drug Design, Predictive Toxicology, and Risk Assessment
Although almost fully automated, the discovery of novel, effective, and safe drugs is still a lon... more Although almost fully automated, the discovery of novel, effective, and safe drugs is still a long-term and highly expensive process. Consequently, the need for fleet, rational, and cost-efficient development of novel drugs is crucial, and nowadays the advanced in silico drug design methodologies seem to effectively meet these issues. The aim of this chapter is to provide a comprehensive overview of some of the current trends and advances in the in silico design of novel drug candidates with a special emphasis on 6-fluoroquinolone (6-FQ) antibacterials as potential novel Mycobacterium tuberculosis DNA gyrase inhibitors. In particular, the chapter covers some of the recent aspects of a wide range of in silico drug discovery approaches including multidimensional machine-learning methods, ligand-based and structurebased methodologies, as well as their proficient combination and integration into an intelligent virtual screening protocol for design and optimization of novel 6-FQ analogs.
Analytica Chimica Acta, 2013
h i g h l i g h t s The concept of applicability domain (AD) in QSAR modeling is discussed. The A... more h i g h l i g h t s The concept of applicability domain (AD) in QSAR modeling is discussed. The AD assessment method for nonlinear neural network predictive models is proposed. The counter-propagation artificial neural network (CP-ANN) was applied for modeling. Minimal Euclidean distance space (MEDS) of CP-ANN model was defined and analyzed. The resulting outliers coincide with those from linear models (leverage based AD).
PloS one, 2015
We present a 3D model of the four transmembrane (TM) helical regions of bilitranslocase (BTL), a ... more We present a 3D model of the four transmembrane (TM) helical regions of bilitranslocase (BTL), a structurally uncharacterized protein that transports organic anions across the cell membrane. The model was computed by considering helix-helix interactions as primary constraints, using Monte Carlo simulations. The interactions between the TM2 and TM3 segments have been confirmed by Förster resonance energy transfer (FRET) spectroscopy and nuclear magnetic resonance (NMR) spectroscopy, increasing our confidence in the model. Several insights into the BTL transport mechanism were obtained by analyzing the model. For example, the observed cis-trans Leu-Pro peptide bond isomerization in the TM3 fragment may indicate a key conformational change during anion transport by BTL. Our structural model of BTL may facilitate further studies, including drug discovery.
SAR and QSAR in Environmental Research, 2012
Extensive use of pharmaceuticals as human and veterinary medication raises concerns for their adv... more Extensive use of pharmaceuticals as human and veterinary medication raises concerns for their adverse effects on non-target organisms. The purpose of this study was to employ multiple linear regression (MLR) to predict the toxicities of a diverse set of pharmaceuticals to fish. The descriptor pool consisted of about 1500 descriptors calculated using Dragon 5.4, Spartan 06 and Codessa 2.2 software. Descriptor selection was made by the heuristic method available in Codessa 2.2. The data set was divided into training and test sets using Kohonen networks. The training set contained approximately 65% of the compounds of the full data set (99 compounds). The training set model contained eight descriptors from all dimensions, all of which were obtained from Dragon 5.4. The statistical parameters of the model for the training set are R(2 )= 0.664, F = 13.588, and R(cv)(2) (LOO) = 0.542 while it achieves R(2 )= 0.605 for the test set. The training, test and external sets have no response outliers considering the standardized residual greater than three. The external validation of the model was made with a set of pharmaceuticals obtained from several databases. The R(pred)(2) is 0.777, reflecting a relatively good predictive power for the external set.
Additional file 15. The file containing smiles of compounds used for modelling bio-concentration ... more Additional file 15. The file containing smiles of compounds used for modelling bio-concentration factor.
Additional file 14. The resulting model for bio-concentration factor.
Molecules, 2019
P-glycoprotein (P-gp) is a transmembrane protein that actively transports a wide variety of chemi... more P-glycoprotein (P-gp) is a transmembrane protein that actively transports a wide variety of chemically diverse compounds out of the cell. It is highly associated with the ADMET (absorption, distribution, metabolism, excretion and toxicity) properties of drugs/drug candidates and contributes to decreasing toxicity by eliminating compounds from cells, thereby preventing intracellular accumulation. Therefore, in the drug discovery and toxicological assessment process it is advisable to pay attention to whether a compound under development could be transported by P-gp or not. In this study, an in silico multiclass classification model capable of predicting the probability of a compound to interact with P-gp was developed using a counter-propagation artificial neural network (CP ANN) based on a set of 2D molecular descriptors, as well as an extensive dataset of 2512 compounds (1178 P-gp inhibitors, 477 P-gp substrates and 857 P-gp non-active compounds). The model provided a good classifi...
Molecules, 2019
Phenols are the most abundant naturally accessible antioxidants present in a human normal diet. S... more Phenols are the most abundant naturally accessible antioxidants present in a human normal diet. Since numerous beneficial applications of phenols as preventive agents in various diseases were revealed, the evaluation of phenols bioavailability is of high interest of researchers, consumers and drug manufacturers. The hydrophilic nature of phenols makes a cell membrane penetration difficult, which imply an alternative way of uptake via membrane transporters. However, the structural and functional data of membrane transporters are limited, thus the in silico modelling is really challenging and urgent tool in elucidation of transporter ligands. Focus of this research was a particular transporter bilitranslocase (BTL). BTL has a broad tissue expression (vascular endothelium, absorptive and excretory epithelia) and can transport wide variety of poly-aromatic compounds. With available BTL data (pKi [mmol/L] for 120 organic compounds) a robust and reliable QSAR models for BTL transport acti...
Tekstilec, 2015
Innovate textile materials for special clothing are intended for providing trauma protection for ... more Innovate textile materials for special clothing are intended for providing trauma protection for the wearer. Fabrics made from high performance aramid fi bres are widely used nowadays for manufacturing athletic sportswear for extreme sports due to their high specifi c tensile modulus and strength. The aim of our study was to illustrate a new approach when searching for optimal settings for impregnating individual batches of textile materials on the basis of para aramid fi bres. We demonstrate a feed-forward bottleneck (FFBN) neural network mapping technique that makes it possible to see all optima (optimal settings for best quality) in the studied process. The selections of optimal settings are based on making decisions allowing us to choose optimal settings for processes in relation to the best quality and smallest (minimal) expense. This new approach can be applied for searching optimal settings regarding different chemical treatments. If a standard statistical regression model (in the cases of non-linear relationships) experiences lack of fi t, it can be successfully substituted with the FFBN neural network mapping technique. This method can also be recommended as a double check of a studied process when we use other approaches.
Analytica Chimica Acta, 2015
Engineering optimization is an actual goal in manufacturing and service industries. In the tutori... more Engineering optimization is an actual goal in manufacturing and service industries. In the tutorial we represented the concept of traditional parametric estimation models (Factorial Design (FD) and Central Composite Design (CCD)) for searching optimal setting parameters of technological processes. Then the 2D mapping method based on Auto Associative Neural Networks (ANN) (particularly, the Feed Forward Bottle Neck Neural Network (FFBN NN)) was described in comparison with traditional methods. The FFBN NN mapping technique enables visualization of all optimal solutions in considered processes due to the projection of input as well as output parameters in the same coordinates of 2D map. This phenomenon supports the more efficient way of improving the performance of existing systems. Comparison of two methods was performed on the bases of optimization of solder paste printing processes as well as optimization of properties of cheese. Application of both methods enables the double check. This increases the reliability of selected optima or specification limits.
PloS one, 2015
A pigment from the edible mushroom Xerocomus badius norbadione A, which is a natural derivative o... more A pigment from the edible mushroom Xerocomus badius norbadione A, which is a natural derivative of pulvinic acid, was found to possess antioxidant properties. Since the pulvinic acid represents a novel antioxidant scaffold, several other derivatives were recently synthetized and evaluated experimentally, along with some structurally related coumarine derivatives. The obtained data formed the basis for the construction of several quantitative structure-activity and pharmacophore models, which were employed in the virtual screening experiments of compound libraries and for the prediction of their antioxidant activity, with the goal of discovering novel compounds possessing antioxidant properties. A final prioritization list of 21 novel compounds alongside 8 established antioxidant compounds was created for their experimental evaluation, consisting of the DPPH assay, 2-deoxyribose assay, β-carotene bleaching assay and the cellular antioxidant activity assay. Ten novel compounds from th...
Molecular Diversity, 2009
The new European chemicals regulation Registration, Evaluation, Authorization and Restriction of ... more The new European chemicals regulation Registration, Evaluation, Authorization and Restriction of Chemicals entered into force in June 2007 and accelerated the development of quantitative structure-activity relationship (QSAR) models for a variety of endpoints, including carcinogenicity. Here, we would like to present quantitative (continuous) and qualitative (categorical) models for non-congeneric chemicals for prediction of carcinogenic potency. A dataset of 805 substances was obtained after a preliminary screening of findings of rodent carcinogenicity for 1,481 chemicals accessible via Distributed Structure-Searchable Toxicity (DSSTox) Public Database Network originated from the Lois Gold Carcinogenic Potency Database (CPDB). Twenty seven two-dimensional MDL descriptors were selected using Kohonen mapping and principal component analysis. The counter propagation artificial neural network (CP ANN) technique was applied. Quantitative models were developed exploring the relationship between the experimental and predicted carcinogenic potency expressed as a tumorgenic dose TD(50) for rats. The obtained models showed low prediction power with correlation coefficient less than 0.5 for the test set. In the next step, qualitative models were developed. We found that the qualitative models exhibit good accuracy for the training set (92%). The model demonstrated good predicted performance for the test set. It was obtained accuracy (68%), sensitivity (73%), and specificity (63%). We believe that CP ANN method is a good in silico approach for modeling and predicting rodent carcinogenicity for non-congeneric chemicals and may find application for other toxicological endpoints.
The aim of this work is to detect the presence of refined hazelnut oil in refined olive oil, usin... more The aim of this work is to detect the presence of refined hazelnut oil in refined olive oil, using the Counter-propagation Artificial Neural Networks (CP-ANN) model. The oil samples were analyzed by FT-MIR spectroscopy. They were clas- sified as pure olive oil (Class 1), pure hazelnut oil (Class 2), and two type of adulterated olive oil samples, one with mo-
Additional file 11. Training set input file used for the modelling of bio-concentration factor.
Additional file 9. The file containing smiles of compounds used for modelling acute toxicity.
Background: CPANNatNIC is software for development of counter-propagation artificial neural netwo... more Background: CPANNatNIC is software for development of counter-propagation artificial neural network models.
Besides the interface for training of a new neural network it also provides an interface for visualisation of the results
which was developed to aid in interpretation of the results and to use the program as a tool for read-across.
Results: The work presents the details of the program’s interface. Parts of the interface are presented and how they
can be used. The examples provided show how the user can build a new model and view the results of predictions
using the interface. Examples are given to show how the software may be used in read-across.
Conclusions: CPANNatNIC provides a simple user interface for model development and visualisation. The interface
implements options which may simplify read-across procedure. Statistical results show better prediction accuracy of
read-across predictions than model predictions where similar compounds could be identified, which indicates the
importance of using read-across and usefulness of the program.
Additional file 10. File with read-across results for acute toxicity validation set.
F1000Research, 2013
Figure 4b: NMR structure of TM3 Conclusions BTL shows no sequence homology Contains two motif... more Figure 4b: NMR structure of TM3 Conclusions BTL shows no sequence homology Contains two motifs conserved in alpha-phycocyanins Four transmembrane domains are predicted for BTL Stable alpha-helical structures are maintained by all the four transmembrane domains Most favored transmembrane domain arrangement type is ABDC Transmembrane regions TM2 and TM3 are found to play significant role in formation of transport channel, ligand interaction and mediation (Ab studies and sequence analysis) Solvent accessible Ser and Cys are present at both ends of the probable transport channel, providing H-bond formnig residues for substrate binding (experimental and theoretical) TM2 forms helix-loop-helix motif , with an angle of ~80° NMR structures further provide evidence for possible allosteric mechanism Presence of two conserved motifs at both ends of the probable transport channel suggest substrate transport in both directions
Computational and Structural Biotechnology Journal, 2017
The structural and functional details of transmembrane proteins are vastly underexplored, mostly ... more The structural and functional details of transmembrane proteins are vastly underexplored, mostly due to experimental difficulties regarding their solubility and stability. Currently, the majority of transmembrane protein structures are still unknown and this present a huge experimental and computational challenge. Nowadays, thanks to X-ray crystallography or NMR spectroscopy over 3000 structures of membrane proteins have been solved, among them only a few hundred unique ones. Due to the vast biological and pharmaceutical interest in the elucidation of the structure and the functional mechanisms of transmembrane proteins, several computational methods have been developed to overcome the experimental gap. If combined with experimental data the computational information enables rapid, low cost and successful predictions of the molecular structure of unsolved proteins. The reliability of the predictions depends on the availability and accuracy of experimental data associated with structural information. In this review, the following methods are proposed for in silico structure elucidation: sequence-dependent predictions of transmembrane regions, predictions of transmembrane helixhelix interactions, helix arrangements in membrane models, and testing their stability with molecular dynamics simulations. We also demonstrate the usage of the computational methods listed above by proposing a model for the molecular structure of the transmembrane protein bilitranslocase. Bilitranslocase is bilirubin membrane transporter, which shares similar tissue distribution and functional properties with some of the members of the Organic Anion Transporter family and is the only member classified in the Bilirubin Transporter Family. Regarding its unique properties, bilitranslocase is a potentially interesting drug target.
Quantitative Structure-Activity Relationships in Drug Design, Predictive Toxicology, and Risk Assessment
Although almost fully automated, the discovery of novel, effective, and safe drugs is still a lon... more Although almost fully automated, the discovery of novel, effective, and safe drugs is still a long-term and highly expensive process. Consequently, the need for fleet, rational, and cost-efficient development of novel drugs is crucial, and nowadays the advanced in silico drug design methodologies seem to effectively meet these issues. The aim of this chapter is to provide a comprehensive overview of some of the current trends and advances in the in silico design of novel drug candidates with a special emphasis on 6-fluoroquinolone (6-FQ) antibacterials as potential novel Mycobacterium tuberculosis DNA gyrase inhibitors. In particular, the chapter covers some of the recent aspects of a wide range of in silico drug discovery approaches including multidimensional machine-learning methods, ligand-based and structurebased methodologies, as well as their proficient combination and integration into an intelligent virtual screening protocol for design and optimization of novel 6-FQ analogs.
Analytica Chimica Acta, 2013
h i g h l i g h t s The concept of applicability domain (AD) in QSAR modeling is discussed. The A... more h i g h l i g h t s The concept of applicability domain (AD) in QSAR modeling is discussed. The AD assessment method for nonlinear neural network predictive models is proposed. The counter-propagation artificial neural network (CP-ANN) was applied for modeling. Minimal Euclidean distance space (MEDS) of CP-ANN model was defined and analyzed. The resulting outliers coincide with those from linear models (leverage based AD).
PloS one, 2015
We present a 3D model of the four transmembrane (TM) helical regions of bilitranslocase (BTL), a ... more We present a 3D model of the four transmembrane (TM) helical regions of bilitranslocase (BTL), a structurally uncharacterized protein that transports organic anions across the cell membrane. The model was computed by considering helix-helix interactions as primary constraints, using Monte Carlo simulations. The interactions between the TM2 and TM3 segments have been confirmed by Förster resonance energy transfer (FRET) spectroscopy and nuclear magnetic resonance (NMR) spectroscopy, increasing our confidence in the model. Several insights into the BTL transport mechanism were obtained by analyzing the model. For example, the observed cis-trans Leu-Pro peptide bond isomerization in the TM3 fragment may indicate a key conformational change during anion transport by BTL. Our structural model of BTL may facilitate further studies, including drug discovery.
SAR and QSAR in Environmental Research, 2012
Extensive use of pharmaceuticals as human and veterinary medication raises concerns for their adv... more Extensive use of pharmaceuticals as human and veterinary medication raises concerns for their adverse effects on non-target organisms. The purpose of this study was to employ multiple linear regression (MLR) to predict the toxicities of a diverse set of pharmaceuticals to fish. The descriptor pool consisted of about 1500 descriptors calculated using Dragon 5.4, Spartan 06 and Codessa 2.2 software. Descriptor selection was made by the heuristic method available in Codessa 2.2. The data set was divided into training and test sets using Kohonen networks. The training set contained approximately 65% of the compounds of the full data set (99 compounds). The training set model contained eight descriptors from all dimensions, all of which were obtained from Dragon 5.4. The statistical parameters of the model for the training set are R(2 )= 0.664, F = 13.588, and R(cv)(2) (LOO) = 0.542 while it achieves R(2 )= 0.605 for the test set. The training, test and external sets have no response outliers considering the standardized residual greater than three. The external validation of the model was made with a set of pharmaceuticals obtained from several databases. The R(pred)(2) is 0.777, reflecting a relatively good predictive power for the external set.
Additional file 15. The file containing smiles of compounds used for modelling bio-concentration ... more Additional file 15. The file containing smiles of compounds used for modelling bio-concentration factor.
Additional file 14. The resulting model for bio-concentration factor.
Molecules, 2019
P-glycoprotein (P-gp) is a transmembrane protein that actively transports a wide variety of chemi... more P-glycoprotein (P-gp) is a transmembrane protein that actively transports a wide variety of chemically diverse compounds out of the cell. It is highly associated with the ADMET (absorption, distribution, metabolism, excretion and toxicity) properties of drugs/drug candidates and contributes to decreasing toxicity by eliminating compounds from cells, thereby preventing intracellular accumulation. Therefore, in the drug discovery and toxicological assessment process it is advisable to pay attention to whether a compound under development could be transported by P-gp or not. In this study, an in silico multiclass classification model capable of predicting the probability of a compound to interact with P-gp was developed using a counter-propagation artificial neural network (CP ANN) based on a set of 2D molecular descriptors, as well as an extensive dataset of 2512 compounds (1178 P-gp inhibitors, 477 P-gp substrates and 857 P-gp non-active compounds). The model provided a good classifi...
Molecules, 2019
Phenols are the most abundant naturally accessible antioxidants present in a human normal diet. S... more Phenols are the most abundant naturally accessible antioxidants present in a human normal diet. Since numerous beneficial applications of phenols as preventive agents in various diseases were revealed, the evaluation of phenols bioavailability is of high interest of researchers, consumers and drug manufacturers. The hydrophilic nature of phenols makes a cell membrane penetration difficult, which imply an alternative way of uptake via membrane transporters. However, the structural and functional data of membrane transporters are limited, thus the in silico modelling is really challenging and urgent tool in elucidation of transporter ligands. Focus of this research was a particular transporter bilitranslocase (BTL). BTL has a broad tissue expression (vascular endothelium, absorptive and excretory epithelia) and can transport wide variety of poly-aromatic compounds. With available BTL data (pKi [mmol/L] for 120 organic compounds) a robust and reliable QSAR models for BTL transport acti...
Tekstilec, 2015
Innovate textile materials for special clothing are intended for providing trauma protection for ... more Innovate textile materials for special clothing are intended for providing trauma protection for the wearer. Fabrics made from high performance aramid fi bres are widely used nowadays for manufacturing athletic sportswear for extreme sports due to their high specifi c tensile modulus and strength. The aim of our study was to illustrate a new approach when searching for optimal settings for impregnating individual batches of textile materials on the basis of para aramid fi bres. We demonstrate a feed-forward bottleneck (FFBN) neural network mapping technique that makes it possible to see all optima (optimal settings for best quality) in the studied process. The selections of optimal settings are based on making decisions allowing us to choose optimal settings for processes in relation to the best quality and smallest (minimal) expense. This new approach can be applied for searching optimal settings regarding different chemical treatments. If a standard statistical regression model (in the cases of non-linear relationships) experiences lack of fi t, it can be successfully substituted with the FFBN neural network mapping technique. This method can also be recommended as a double check of a studied process when we use other approaches.
Analytica Chimica Acta, 2015
Engineering optimization is an actual goal in manufacturing and service industries. In the tutori... more Engineering optimization is an actual goal in manufacturing and service industries. In the tutorial we represented the concept of traditional parametric estimation models (Factorial Design (FD) and Central Composite Design (CCD)) for searching optimal setting parameters of technological processes. Then the 2D mapping method based on Auto Associative Neural Networks (ANN) (particularly, the Feed Forward Bottle Neck Neural Network (FFBN NN)) was described in comparison with traditional methods. The FFBN NN mapping technique enables visualization of all optimal solutions in considered processes due to the projection of input as well as output parameters in the same coordinates of 2D map. This phenomenon supports the more efficient way of improving the performance of existing systems. Comparison of two methods was performed on the bases of optimization of solder paste printing processes as well as optimization of properties of cheese. Application of both methods enables the double check. This increases the reliability of selected optima or specification limits.
PloS one, 2015
A pigment from the edible mushroom Xerocomus badius norbadione A, which is a natural derivative o... more A pigment from the edible mushroom Xerocomus badius norbadione A, which is a natural derivative of pulvinic acid, was found to possess antioxidant properties. Since the pulvinic acid represents a novel antioxidant scaffold, several other derivatives were recently synthetized and evaluated experimentally, along with some structurally related coumarine derivatives. The obtained data formed the basis for the construction of several quantitative structure-activity and pharmacophore models, which were employed in the virtual screening experiments of compound libraries and for the prediction of their antioxidant activity, with the goal of discovering novel compounds possessing antioxidant properties. A final prioritization list of 21 novel compounds alongside 8 established antioxidant compounds was created for their experimental evaluation, consisting of the DPPH assay, 2-deoxyribose assay, β-carotene bleaching assay and the cellular antioxidant activity assay. Ten novel compounds from th...
Molecular Diversity, 2009
The new European chemicals regulation Registration, Evaluation, Authorization and Restriction of ... more The new European chemicals regulation Registration, Evaluation, Authorization and Restriction of Chemicals entered into force in June 2007 and accelerated the development of quantitative structure-activity relationship (QSAR) models for a variety of endpoints, including carcinogenicity. Here, we would like to present quantitative (continuous) and qualitative (categorical) models for non-congeneric chemicals for prediction of carcinogenic potency. A dataset of 805 substances was obtained after a preliminary screening of findings of rodent carcinogenicity for 1,481 chemicals accessible via Distributed Structure-Searchable Toxicity (DSSTox) Public Database Network originated from the Lois Gold Carcinogenic Potency Database (CPDB). Twenty seven two-dimensional MDL descriptors were selected using Kohonen mapping and principal component analysis. The counter propagation artificial neural network (CP ANN) technique was applied. Quantitative models were developed exploring the relationship between the experimental and predicted carcinogenic potency expressed as a tumorgenic dose TD(50) for rats. The obtained models showed low prediction power with correlation coefficient less than 0.5 for the test set. In the next step, qualitative models were developed. We found that the qualitative models exhibit good accuracy for the training set (92%). The model demonstrated good predicted performance for the test set. It was obtained accuracy (68%), sensitivity (73%), and specificity (63%). We believe that CP ANN method is a good in silico approach for modeling and predicting rodent carcinogenicity for non-congeneric chemicals and may find application for other toxicological endpoints.
The aim of this work is to detect the presence of refined hazelnut oil in refined olive oil, usin... more The aim of this work is to detect the presence of refined hazelnut oil in refined olive oil, using the Counter-propagation Artificial Neural Networks (CP-ANN) model. The oil samples were analyzed by FT-MIR spectroscopy. They were clas- sified as pure olive oil (Class 1), pure hazelnut oil (Class 2), and two type of adulterated olive oil samples, one with mo-