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QSPR Prediction of Lipophilicity for Organic Compounds Using Random Forest Technique on the Basis of Simplex Representation of Molecular Structure
Author(s) -
Ognichenko Liudmyla N.,
Kuz'min Victor E.,
Gorb Leonid,
Hill Frances C.,
Artemenko Anatoly G.,
Polischuk Pavel G.,
Leszczynski Jerzy
Publication year - 2012
Publication title -
molecular informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 68
eISSN - 1868-1751
pISSN - 1868-1743
DOI - 10.1002/minf.201100102
Subject(s) - quantitative structure–activity relationship , lipophilicity , partition coefficient , simplex , molecular descriptor , random forest , representation (politics) , octanol , cheminformatics , biological system , chemistry , virtual screening , computational chemistry , computer science , mathematics , artificial intelligence , molecular dynamics , stereochemistry , organic chemistry , combinatorics , politics , political science , law , biology
The relationship between the octanol‐water partition coefficient for more than twelve thousand organic compounds and their structures was investigated using a QSPR approach based on Simplex Representation of Molecular Structure (SiRMS). The dataset used in our study included 10973 compounds with experimental values of lipophilicity (Log K ow ) for different chemical compounds. Random Forest (RF) method was used for statistical modeling at the 2D level of representation of molecular structure. Developed models are adequate and successfully validated with external test sets. Proposed models have clear interpretation due to the use of simplex representation of molecular structure and predict the Log K ow values with the accuracy of the best modern models. Thus QSPR models proposed in this study represent powerful and easy‐to use virtual screening tool that can be recommended for prediction of octanol‐water partition coefficient.