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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...

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Detalles Bibliográficos
Autores principales: Withnall, Michael, Chen, Hongming, Tetko, Igor V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
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.
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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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