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European Journal of Pharmaceutical Sciences
Article . 2014 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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CORAL software: Prediction of carcinogenicity of drugs by means of the Monte Carlo method

Authors: Alla P, Toropova; Andrey A, Toropov;

CORAL software: Prediction of carcinogenicity of drugs by means of the Monte Carlo method

Abstract

Methodology of building up and validation of models for carcinogenic potentials of drugs by means of the CORAL software is described. The QSAR analysis by the CORAL software includes three phases: (i) definition of preferable parameters for the optimization procedure that gives maximal correlation coefficient between endpoint and an optimal descriptor that is calculated with so-called correlation weights of various molecular features; (ii) detection of molecular features with stable positive correlation weights or vice versa stable negative correlation weights (molecular features which are characterized by solely positive or solely negative correlation weights obtained for several starts of the Monte Carlo optimization are a basis for mechanistic interpretations of the model); and (iii) building up the model that is satisfactory from point of view of reliable probabilistic criteria and OECD principles. The methodology is demonstrated for the case of carcinogenicity of a large set (n = 1464) of organic compounds which are potential or actual pharmaceutical agents.

Keywords

Neoplasms, Carcinogens, Quantitative Structure-Activity Relationship, Models, Theoretical, Monte Carlo Method, Software, Forecasting

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
78
Top 10%
Top 10%
Top 1%
gold