PuSH - Publication Server of Helmholtz Zentrum München

Withnall, M.D. ; Chen, H.* ; Tetko, I.V.

Matched molecular pair analysis on large melting point datasets: A big data perspective.

ChemMedChem 13, 599-606 (2017)
Postprint Research data DOI PMC
Open Access Green
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
Scopus
Cited By
Altmetric
3.225
0.906
7
8
Tags
Annotations
Special Publikation
Hide on homepage

Edit extra information
Edit own tags
Private
Edit own annotation
Private
Hide on publication lists
on hompage
Mark as special
publikation
Publication type Article: Journal article
Document type Scientific Article
Keywords 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
Language english
Publication Year 2017
HGF-reported in Year 2017
ISSN (print) / ISBN 1860-7179
e-ISSN 1860-7187
Journal ChemMedChem
Quellenangaben Volume: 13, Issue: 6, Pages: 599-606 Article Number: , Supplement: ,
Publisher Wiley
Publishing Place Weinheim
Reviewing status Peer reviewed
POF-Topic(s) 30203 - Molecular Targets and Therapies
Research field(s) Enabling and Novel Technologies
PSP Element(s) G-503000-003
Scopus ID 85027849449
PubMed ID 28650584
Erfassungsdatum 2017-07-20