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QSPR for LogP using molecules without oxygen and nitrogen and quantum mechanics descriptors

Content Provider	Springer Nature Link
Author	Tarko, Laszlo
Copyright Year	2014
Abstract	We report a quantitative structure–property relationship (QSPR) study regarding LogP. The text includes some comments regarding the influence of diversity of molecules on results of QSPR computation. The calibration (training) set was selected, according to specific molecular diversity/similarity criteria, from certain group of 621 molecules, without oxygen and nitrogen atoms. The calibration set includes 211 molecules (hydrocarbons, halo-derivatives, thioethers, phosphines etc.) having much higher diversity from the point of view of chemical structure, size, shape and lipophilicity. The validation set includes the non-selected 410 molecules. The observed value of LogP is within (0.20, 9.14) range in calibration set and within (1.08, 9.36) range in prediction/validation set. The best QSPR multilinear formula includes three quantum mechanics descriptors and does not include molecular fragments’ descriptors. For calibration set, the predictive power of QSPR is high (r $^{2}$ = 0.9489; SEE = 0.4117), close to KOWWIN (r $^{2}$ = 0.9545; SEE = 0.3961) and miLogP (r $^{2}$ = 0.9477; SEE = 0.4736) results. The predictor ‘conductor-like screening model area’ has largest influence on the value of LogP. The quality of prediction for validation set is good (r $^{2}$ = 0.9517; SEE = 0.4334), close to result obtained by KOWWIN (r $^{2}$ = 0.9676, SEE = 0.3286) and miLogP (r $^{2}$ = 0.9612; SEE = 0.4776).
Starting Page	359
Ending Page	365
Page Count	7
File Format	PDF
ISSN	1735207X
Journal	Journal of the Iranian Chemical Society
Volume Number	12
Issue Number	2
e-ISSN	17352428
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2014-06-28
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	QSPR MOPAC Analytical Chemistry Physical Chemistry LogP PRECLAV Biochemistry Inorganic Chemistry Organic Chemistry
Content Type	Text
Resource Type	Article
Subject	Chemistry

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