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BY-NC-ND 3.0 license Open Access Published by De Gruyter Open Access December 21, 2013

QSAR of caffeines by similarity cluster prediction

Teodora Harsa, Alexandra Harsa and Beata Szefler
From the journal Open Chemistry

Abstract

A novel QSAR approach based on correlation weighting and alignment over a hypermolecule that mimics the investigated correlational space was performed on a set of 40 caffeines downloaded from the PubChem database. The best models describing log P and LD50 values of this set of caffeine derivatives were validated against the external test set and in a new predictive model by using clusters of similarity.

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Published Online: 2013-12-21
Published in Print: 2014-3-1

© 2014 Versita Warsaw

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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