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Bioorg Med Chem Lett. 2004 Feb 23;14(4):851-3.

A neural network based prediction of octanol-water partition coefficients using atomic5 fragmental descriptors.

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  • 1Department of Chemical Information Technology, Budapest University of Technology and Economics, Szent Gellért tér 4., H-1111 Budapest, Hungary.

Abstract

An artificial neural network based approach using Atomic5 fragmental descriptors has been developed to predict the octanol-water partition coefficient (logP). We used a pre-selected set of organic molecules from PHYSPROP database as training and test sets for a feedforward neural network. Results demonstrate the superiority of our non-linear model over the traditional linear method.

PMID:
15012980
[PubMed - indexed for MEDLINE]
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