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Determining molecular properties with differential mobility spectrometry and machine learning

Authors :
Stephen W. C. Walker
Ahdia Anwar
Jarrod M. Psutka
Jeff Crouse
Chang Liu
J. C. Yves Le Blanc
Justin Montgomery
Gilles H. Goetz
John S. Janiszewski
J. Larry Campbell
W. Scott Hopkins
Source :
Nature Communications, Vol 9, Iss 1, Pp 1-7 (2018)
Publication Year :
2018
Publisher :
Nature Portfolio, 2018.

Abstract

The fast and accurate determination of molecular properties is particularly crucial in drug discovery. Here, the authors employ supervised machine learning to treat differential mobility spectrometry – mass spectrometry data for ten classes of drug candidates and predict several condensed-phase properties.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20411723
Volume :
9
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
edsdoj.5545143641641f8afbe1987126bcf2f
Document Type :
article
Full Text :
https://doi.org/10.1038/s41467-018-07616-w