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Matched Molecular Pair Analysis on Large Melting Point Datasets: A Big Data Perspective
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 ∼275k compounds. We found many cases in which the change in MP (ΔMP) of compounds correlates with changes in functional groups. In line with the results of a pr...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5900986/ https://www.ncbi.nlm.nih.gov/pubmed/28650584 http://dx.doi.org/10.1002/cmdc.201700303 |
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author | Withnall, Michael Chen, Hongming Tetko, Igor V. |
author_facet | Withnall, Michael Chen, Hongming Tetko, Igor V. |
author_sort | Withnall, Michael |
collection | PubMed |
description | 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 ∼275k compounds. We found many cases in which the change in MP (ΔMP) of compounds correlates with changes in functional groups. In line with the results of a previous study, correlations between ΔMP 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. |
format | Online Article Text |
id | pubmed-5900986 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-59009862018-04-24 Matched Molecular Pair Analysis on Large Melting Point Datasets: A Big Data Perspective Withnall, Michael Chen, Hongming Tetko, Igor V. ChemMedChem Full Papers 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 ∼275k compounds. We found many cases in which the change in MP (ΔMP) of compounds correlates with changes in functional groups. In line with the results of a previous study, correlations between ΔMP 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. John Wiley and Sons Inc. 2017-08-23 2018-03-20 /pmc/articles/PMC5900986/ /pubmed/28650584 http://dx.doi.org/10.1002/cmdc.201700303 Text en © 2017 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Full Papers Withnall, Michael Chen, Hongming Tetko, Igor V. Matched Molecular Pair Analysis on Large Melting Point Datasets: A Big Data Perspective |
title | Matched Molecular Pair Analysis on Large Melting Point Datasets: A Big Data Perspective |
title_full | Matched Molecular Pair Analysis on Large Melting Point Datasets: A Big Data Perspective |
title_fullStr | Matched Molecular Pair Analysis on Large Melting Point Datasets: A Big Data Perspective |
title_full_unstemmed | Matched Molecular Pair Analysis on Large Melting Point Datasets: A Big Data Perspective |
title_short | Matched Molecular Pair Analysis on Large Melting Point Datasets: A Big Data Perspective |
title_sort | matched molecular pair analysis on large melting point datasets: a big data perspective |
topic | Full Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5900986/ https://www.ncbi.nlm.nih.gov/pubmed/28650584 http://dx.doi.org/10.1002/cmdc.201700303 |
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