title: CORAL Software: Analysis of Impacts of Pharmaceutical Agents Upon Metabolism via the Optimal Descriptors.
abstract: BACKGROUND
  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.
  
  
  METHODS
  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 &amp;quot;structure - endpoint&amp;quot;.
  
  
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Dipartimento di Scienze Farmaceutiche, Universita` degli Studi di Milano, Via L. Mangiagalli, 25, 20133 Milan, Italy.
authors.forename: Mariya A
authors.initials: MA
authors.lastname: Toropova
authors.affiliation: 3rd Department of Medicine-Department of Endocrinology and Metabolism, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, UNemocnice1, 12808 Prague 2, Czech Republic.
authors.forename: Ivan
authors.initials: I
authors.lastname: Raska
authors.affiliation: Laboratory of Environmental Chemistry and Toxicology, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milano, Italy.
authors.forename: Alla P
authors.initials: AP
authors.lastname: Toporova
authors.affiliation: 3rd Department of Medicine-Department of Endocrinology and Metabolism, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, UNemocnice1, 12808 Prague 2, Czech Republic.
authors.forename: Maria
authors.initials: M
authors.lastname: Raskova
mesh_terms: D006801:Humans; D008958:Models, Molecular; D009010:Monte Carlo Method; D004364:Pharmaceutical Preparations / Q000378:metabolism*; D021281:Quantitative Structure-Activity Relationship; D012984:Software
chemical_list: D004364:Pharmaceutical Preparations
keywords: CORAL; Metabolism; OECD principle; QSAR; pharmacology; toxicology; validation