QSAR of caffeines by similarity cluster prediction

• Authors: Teodora Harsa , Alexandra Harsa , Beata Szefler
• Languages of publication: EN

Abstracts

EN

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.

Keywords

EN

Xanthine; QSAR; log P; LD50; Hypermolecule

• Publisher: De Gruyter Open
• Journal: Open Chemistry
• Year: 2014
• Volume: 12
• Issue: 3
• Pages: 365-376

Dates

published

1 - 3 - 2014

online

21 - 12 - 2013

Contributors

author

Teodora Harsa

• Babes-Bolyai University

author

Alexandra Harsa

• Babes-Bolyai University

author

Beata Szefler

• Nicolaus Copernicus University

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Identifiers

DOI

10.2478/s11532-013-0389-y