QSAR of caffeines by similarity cluster prediction

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 w...

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Veröffentlicht in:	Central European journal of chemistry 2014-03, Vol.12 (3), p.365-376
Hauptverfasser:	Harsa, Teodora E., Harsa, Alexandra M., Szefler, Beata
Format:	Artikel
Sprache:	eng
Schlagworte:	Biochemistry Biological and Medical Physics Biophysics Caffeine Chemistry Chemistry and Materials Science Chemistry/Food Science Clusters Correlation Derivatives Geochemistry Hypermolecule LD50 log P Mathematical models QSAR Research Article Similarity Weighting Xanthine
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Beschreibung
Zusammenfassung:	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.
ISSN:	1895-1066 2391-5420 1644-3624 2391-5420
DOI:	10.2478/s11532-013-0389-y