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Matched molecular pair analysis on large melting point datasets: A big data perspective.
ChemMedChem 13, 599-606 (2017)
Postprint
Forschungsdaten
DOI
PMC
A matched molecular pair (MMP) analysis was used to examine the change in melting point (MP) between pairs of similar molecules in a set of approximate to 275k compounds. We found many cases in which the change in MP (MP) of compounds correlates with changes in functional groups. In line with the results of a previous study, correlations between MP and simple molecular descriptors, such as the number of hydrogen bond donors, were identified. In using a larger dataset, covering a wider chemical space and range of melting points, we observed that this method remains stable and scales well with larger datasets. This MMP-based method could find use as a simple privacy-preserving technique to analyze large proprietary databases and share findings between participating research groups.
Impact Factor
Scopus SNIP
Web of Science
Times Cited
Times Cited
Scopus
Cited By
Cited By
Altmetric
3.225
0.906
7
8
Anmerkungen
Besondere Publikation
Auf Hompepage verbergern
Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Schlagwörter
General Solubility Equation ; Matched Molecular Pairs ; Melting Points ; Ochem; Artificial Neural-networks; Drug-like Compounds; E-state Indexes; Aqueous Solubility; Partition-coefficients; Water Solubility; Vapor-pressure; Prediction; Nonelectrolytes; Descriptors
Sprache
englisch
Veröffentlichungsjahr
2017
HGF-Berichtsjahr
2017
ISSN (print) / ISBN
1860-7179
e-ISSN
1860-7187
Zeitschrift
ChemMedChem
Quellenangaben
Band: 13,
Heft: 6,
Seiten: 599-606
Verlag
Wiley
Verlagsort
Weinheim
Begutachtungsstatus
Peer reviewed
Institut(e)
Institute of Structural Biology (STB)
POF Topic(s)
30203 - Molecular Targets and Therapies
Forschungsfeld(er)
Enabling and Novel Technologies
PSP-Element(e)
G-503000-003
WOS ID
WOS:000428380000017
Scopus ID
85027849449
PubMed ID
28650584
Erfassungsdatum
2017-07-20