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Consensus Diversity Plots: a global diversity analysis of chemical libraries
BACKGROUND: Measuring the structural diversity of compound databases is relevant in drug discovery and many other areas of chemistry. Since molecular diversity depends on molecular representation, comprehensive chemoinformatic analysis of the diversity of libraries uses multiple criteria. For instan...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5105260/ https://www.ncbi.nlm.nih.gov/pubmed/27895718 http://dx.doi.org/10.1186/s13321-016-0176-9 |
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author | González-Medina, Mariana Prieto-Martínez, Fernando D. Owen, John R. Medina-Franco, José L. |
author_facet | González-Medina, Mariana Prieto-Martínez, Fernando D. Owen, John R. Medina-Franco, José L. |
author_sort | González-Medina, Mariana |
collection | PubMed |
description | BACKGROUND: Measuring the structural diversity of compound databases is relevant in drug discovery and many other areas of chemistry. Since molecular diversity depends on molecular representation, comprehensive chemoinformatic analysis of the diversity of libraries uses multiple criteria. For instance, the diversity of the molecular libraries is typically evaluated employing molecular scaffolds, structural fingerprints, and physicochemical properties. However, the assessment with each criterion is analyzed independently and it is not straightforward to provide an evaluation of the “global diversity”. RESULTS: Herein the Consensus Diversity Plot (CDP) is proposed as a novel method to represent in low dimensions the diversity of chemical libraries considering simultaneously multiple molecular representations. We illustrate the application of CDPs to classify eight compound data sets and two subsets with different sizes and compositions using molecular scaffolds, structural fingerprints, and physicochemical properties. CONCLUSIONS: CDPs are general data mining tools that represent in two-dimensions the global diversity of compound data sets using multiple metrics. These plots can be constructed using single or combined measures of diversity. An online version of the CDPs is freely available at: https://consensusdiversityplots-difacquim-unam.shinyapps.io/RscriptsCDPlots/. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13321-016-0176-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5105260 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-51052602016-11-28 Consensus Diversity Plots: a global diversity analysis of chemical libraries González-Medina, Mariana Prieto-Martínez, Fernando D. Owen, John R. Medina-Franco, José L. J Cheminform Methodology BACKGROUND: Measuring the structural diversity of compound databases is relevant in drug discovery and many other areas of chemistry. Since molecular diversity depends on molecular representation, comprehensive chemoinformatic analysis of the diversity of libraries uses multiple criteria. For instance, the diversity of the molecular libraries is typically evaluated employing molecular scaffolds, structural fingerprints, and physicochemical properties. However, the assessment with each criterion is analyzed independently and it is not straightforward to provide an evaluation of the “global diversity”. RESULTS: Herein the Consensus Diversity Plot (CDP) is proposed as a novel method to represent in low dimensions the diversity of chemical libraries considering simultaneously multiple molecular representations. We illustrate the application of CDPs to classify eight compound data sets and two subsets with different sizes and compositions using molecular scaffolds, structural fingerprints, and physicochemical properties. CONCLUSIONS: CDPs are general data mining tools that represent in two-dimensions the global diversity of compound data sets using multiple metrics. These plots can be constructed using single or combined measures of diversity. An online version of the CDPs is freely available at: https://consensusdiversityplots-difacquim-unam.shinyapps.io/RscriptsCDPlots/. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13321-016-0176-9) contains supplementary material, which is available to authorized users. Springer International Publishing 2016-11-10 /pmc/articles/PMC5105260/ /pubmed/27895718 http://dx.doi.org/10.1186/s13321-016-0176-9 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology González-Medina, Mariana Prieto-Martínez, Fernando D. Owen, John R. Medina-Franco, José L. Consensus Diversity Plots: a global diversity analysis of chemical libraries |
title | Consensus Diversity Plots: a global diversity analysis of chemical libraries |
title_full | Consensus Diversity Plots: a global diversity analysis of chemical libraries |
title_fullStr | Consensus Diversity Plots: a global diversity analysis of chemical libraries |
title_full_unstemmed | Consensus Diversity Plots: a global diversity analysis of chemical libraries |
title_short | Consensus Diversity Plots: a global diversity analysis of chemical libraries |
title_sort | consensus diversity plots: a global diversity analysis of chemical libraries |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5105260/ https://www.ncbi.nlm.nih.gov/pubmed/27895718 http://dx.doi.org/10.1186/s13321-016-0176-9 |
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