BACKGROUNDS: The CORAL software has been developed as a tool to build up quantitative structure- activity relationships (QSAR) for various endpoints. OBJECTIVE: The task of the present work was to estimate and to compare QSAR models for biochemical activity of various therapeutic agents, which are built up by the CORAL software. METHOD: The Monte Carlo technique gives possibility to build up predictive model of an endpoint by means of selection of so-called correlation weights of various molecular features extracted from simplified molecular input-line entry system (SMILES). Descriptors calculated with these weights are basis for building up correlations "structure - endpoint". RESULTS: Optimal descriptors, which are aimed to predict values of endpoints with apparent influence upon metabolism are crytically compared in aspect of their robustness and heuristic potential. Arguments which are confirming the necessity of reformulation of basics of QSARs are listed: (i) each QSAR model is stochastic experiment. The result of this experiment is defined by distribution into the training set and validation set; (ii) predictive potential of a model should be checked up with a group of different splits; and (iii) only model stochastically stable for a group of splits can be estimated as a reliable tool for the prediction. Examples of the improvement of the models previously suggested are demonstrated. CONCLUSION: The current version of the CORAL software remains a convenient tool to build up predictive models. The Monte Carlo technique involved for the software confirms the principle "QSAR is a random event" is important paradigm for the QSPR/QSAR analyses.

• Klíčová slova
• CORAL, Metabolism, OECD principle, QSAR, pharmacology, toxicology, validation,
• MeSH
• kvantitativní vztahy mezi strukturou a aktivitou * MeSH
• léčivé přípravky metabolismus   MeSH
• lidé MeSH
• metoda Monte Carlo MeSH
• molekulární modely * MeSH
• software * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• léčivé přípravky MeSH

Quantitative structure - activity relationships (QSARs) for the pIC50 (binding affinity) of gamma-secretase inhibitors can be constructed with the Monte Carlo method using CORAL software (http://www.insilico.eu/coral). The considerable influence of the presence of rings of various types with respect to the above endpoint has been detected. The mechanistic interpretation and the domain of applicability of the QSARs are discussed. Methods to select new potential gamma-secretase inhibitors are suggested.

• Klíčová slova
• CORAL software, Gamma-secretase inhibitor, Monte Carlo method, OECD principles, QSAR,
• MeSH
• Alzheimerova nemoc farmakoterapie   MeSH
• kvantitativní vztahy mezi strukturou a aktivitou MeSH
• lidé MeSH
• metoda Monte Carlo MeSH
• objevování léků metody   MeSH
• sekretasy * antagonisté a inhibitory   chemie   metabolismus   MeSH
• software MeSH
• výpočetní biologie metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• sekretasy * MeSH

Robust quantitative structure-activity relationships (QSARs) for hBACE-1 inhibitors (pIC50) for a large database (n = 1706) are established. New statistical criteria of the predictive potential of models are suggested and tested. These criteria are the index of ideality of correlation (IIC) and the correlation intensity index (CII). The system of self-consistent models is a new approach to validate the predictive potential of QSAR-models. The statistical quality of models obtained using the CORAL software (http://www.insilico.eu/coral) for the validation sets is characterized by the average determination coefficient R2v= 0.923, and RMSE = 0.345. Three new promising molecular structures which can become inhibitors hBACE-1 are suggested.

• Klíčová slova
• Alzheimer's disease, CORAL software, QSAR, correlation intensity index, hBACE-1, index of ideality of correlation,
• MeSH
• Alzheimerova nemoc * farmakoterapie   MeSH
• kvantitativní vztahy mezi strukturou a aktivitou MeSH
• lidé MeSH
• metoda Monte Carlo MeSH
• molekulární struktura MeSH
• software MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

BACKGROUND: Staphylococcus aureus bacterial infections are still a serious health care problem. Therefore, the development of new drugs for these infections is a constant requirement. Quantitative structure-activity relationship (QSAR) methods can assist this development. METHODS: The study included 151 structurally diverse compounds with antibacterial activity against S. aureus ATCC 25923 (Endpoint 1) or the drug-resistant clinical isolate of S. aureus (Endpoint 2). QSARs based on hybrid optimal descriptors were used. RESULTS: The predictive potential of developed models has been checked with three random splits into training, passive training, calibration, and validation sets. The proposed models give satisfactory predictive models for both endpoints examined. CONCLUSIONS: The results of the study show the possibility of SMILES-based QSAR in the evaluation of the antibacterial activity of structurally diverse compounds for both endpoints. Although the developed models give satisfactory predictive models for both endpoints examined, splitting has an apparent influence on the statistical quality of the models.

• Klíčová slova
• CORAL software, Monte Carlo method, QSAR, SMILES, antibacterial activity, hybrid optimal descriptors,
• MeSH
• antibakteriální látky farmakologie   MeSH
• kvantitativní vztahy mezi strukturou a aktivitou * MeSH
• metoda Monte Carlo MeSH
• molekulární modely MeSH
• software MeSH
• Staphylococcus aureus * MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• antibakteriální látky MeSH

The CORAL software ( http://www.insilico.eu/coral ) was used to build up quantitative structure-property relationships (QSPRs) for the retention characteristics of 93 derivatives of three groups of heterocyclic compounds: 2-phenyl-1,3-benzoxazoles, 4-benzylsulfanylpyridines, and benzoxazines. The QSPRs are one-variable models based on the optimal descriptors calculated from the molecular structure represented by simplified molecular input-line entry systems (SMILES). Each symbol (or two undivided symbols) of SMILES is characterized by correlation weight. The optimal descriptor is the sum of the correlation weights. The numerical data on the correlation weights were calculated with the Monte Carlo method by the manner which provides best correlation between endpoint and optimal descriptor for the calibration set. The predictive ability of the model is checked with the validation set (compounds invisible during building up of the model). The approach has been checked with three random splits into the training, calibration, and validation sets: all models have apparent predictive potential. The mechanistic interpretation of the molecular features extracted from SMILES as the promoters of increase or decrease of examined endpoints is suggested.

• Klíčová slova
• CORAL software, Monte Carlo method, QSPR, Retention factor, SMILES,
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Optimal descriptors calculated with Simplified Molecular Input Line Entry System (SMILES) notation have been used in quantitative structure-property relationships (QSPR) of half-wave potential of N-benzylsalicylthioamides. The QSPR developed is one-variable model based on the optimal descriptors calculated with the Monte Carlo method. The approach has been checked up with three random splits into the training and test sets. Mechanistic interpretations (structural alerts related to the half-wave potential) of the model are discussed.

• Klíčová slova
• CORAL software, Half-wave potential, N-benzylsalicylthioamide, QSPR, SMILES,
• MeSH
• kvantitativní vztahy mezi strukturou a aktivitou * MeSH
• metoda Monte Carlo MeSH
• molekulární struktura MeSH
• thioamidy chemická syntéza   chemie   farmakologie   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• thioamidy MeSH

By optimization of so-called correlation weights of attributes of simplified molecular input-line entry system (SMILES) quantitative structure - activity relationships (QSAR) for toxicity towards Pimephales promelas are established. A new SMILES attribute has been utilized in this work. This attribute is a molecular descriptor, which reflects (i) presence of different kinds of bonds (double, triple, and stereo chemical bonds); (ii) presence of nitrogen, oxygen, sulphur, and phosphorus atoms; and (iii) presence of fluorine, chlorine, bromine, and iodine atoms. The statistical characteristics of the best model are the following: n=226, r2=0.7630, RMSE=0.654 (training set); n=114, r2=0.7024, RMSE=0.766 (calibration set); n=226, r2=0.6292, RMSE=0.870 (validation set). A new criterion to select a preferable split into the training and validation sets are suggested and discussed.

• Klíčová slova
• CORAL software, Monte carlo method, Pimephales promelas, QSAR, Toxicity,
• MeSH
• biologické modely * MeSH
• chemické látky znečišťující vodu chemie   toxicita   MeSH
• Cyprinidae růst a vývoj   metabolismus   MeSH
• kvantitativní vztahy mezi strukturou a aktivitou * MeSH
• LD50 MeSH
• metoda Monte Carlo * MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• chemické látky znečišťující vodu MeSH

Acetylcholinesterase (AChE) inhibitors, dihydrofolate reductase inhibitors (DHFR), Toxicity in Tetrahymena pyriformis (TP), Acute Toxicity in fathead minnow (TFat), Water solubility (WS), and Acute Aquatic Toxicity in Daphnia magna (DM) are examined as endpoints to establish quantitative structure - property/activity relationships (QSPRs/QSARs). The Index of Ideality of Correlation (IIC) is a measure of predictive potential. The IIC has been studied in a few recent works. The comparison of models for the six endpoints above confirms that the index can be a useful tool for building up and validation of QSPR/QSAR models. All examined endpoints are important from an ecologic point of view. The diversity of examined endpoints confirms that the IIC is real criterion of the predictive potential of a model.

• Klíčová slova
• CORAL software, Environmental risk, Index of ideality of correlation, OECD principles, QSPR/QSAR, Toxicity,
• MeSH
• chemické látky znečišťující vodu toxicita   MeSH
• chemické modely * MeSH
• kvantitativní vztahy mezi strukturou a aktivitou * MeSH
• metoda Monte Carlo MeSH
• monitorování životního prostředí metody   MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• chemické látky znečišťující vodu MeSH

The algorithm of building up a model for the biological activity of peptides as a mathematical function of a sequence of amino acids is suggested. The general scheme is the following: The total set of available data is distributed into the active training set, passive training set, calibration set, and validation set. The training (both active and passive) and calibration sets are a system of generation of a model of biological activity where each amino acid obtains special correlation weight. The numerical data on the correlation weights calculated by the Monte Carlo method using the CORAL software (http://www.insilico.eu/coral). The target function aimed to give the best result for the calibration set (not for the training set). The final checkup of the model is carried out with data on the validation set (peptides, which are not visible during the creation of the model). Described computational experiments confirm the ability of the approach to be a tool for the design of predictive models for the biological activity of peptides (expressed by pIC50).

• Klíčová slova
• Amino acid, Index of ideality of correlation, Monte Carlo method, Peptide, QSAR,
• Publikační typ
• časopisecké články MeSH