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SimCAL: a flexible tool to compute biochemical reaction similarity
BACKGROUND: Computation of reaction similarity is a pre-requisite for several bioinformatics applications including enzyme identification for specific biochemical reactions, enzyme classification and mining for specific inhibitors. Reaction similarity is often assessed at either two levels: (i) comp...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029250/ https://www.ncbi.nlm.nih.gov/pubmed/29969981 http://dx.doi.org/10.1186/s12859-018-2248-5 |
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author | Sivakumar, Tadi Venkata Bhaduri, Anirban Duvvuru Muni, Rajasekhara Reddy Park, Jin Hwan Kim, Tae Yong |
author_facet | Sivakumar, Tadi Venkata Bhaduri, Anirban Duvvuru Muni, Rajasekhara Reddy Park, Jin Hwan Kim, Tae Yong |
author_sort | Sivakumar, Tadi Venkata |
collection | PubMed |
description | BACKGROUND: Computation of reaction similarity is a pre-requisite for several bioinformatics applications including enzyme identification for specific biochemical reactions, enzyme classification and mining for specific inhibitors. Reaction similarity is often assessed at either two levels: (i) comparison across all the constituent substrates and products of a reaction, reaction level similarity, (ii) comparison at the transformation center with various degrees of neighborhood, transformation level similarity. Existing reaction similarity computation tools are designed for specific applications and use different features and similarity measures. A single system integrating these diverse features enables comparison of the impact of different molecular properties on similarity score computation. RESULTS: To address these requirements, we present SimCAL, an integrated system to calculate reaction similarity with novel features and capability to perform comparative assessment. SimCAL provides reaction similarity computation at both whole reaction level and transformation level. Novel physicochemical features such as stereochemistry, mass, volume and charge are included in computing reaction fingerprint. Users can choose from four different fingerprint types and nine molecular similarity measures. Further, a comparative assessment of these features is also enabled. The performance of SimCAL is assessed on 3,688,122 reaction pairs with Enzyme Commission (EC) number from MetaCyc and achieved an area under the curve (AUC) of > 0.9. In addition, SimCAL results showed strong correlation with state-of-the-art EC-BLAST and molecular signature based reaction similarity methods. CONCLUSIONS: SimCAL is developed in java and is available as a standalone tool, with intuitive, user-friendly graphical interface and also as a console application. With its customizable feature selection and similarity calculations, it is expected to cater a wide audience interested in studying and analyzing biochemical reactions and metabolic networks. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2248-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6029250 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-60292502018-07-09 SimCAL: a flexible tool to compute biochemical reaction similarity Sivakumar, Tadi Venkata Bhaduri, Anirban Duvvuru Muni, Rajasekhara Reddy Park, Jin Hwan Kim, Tae Yong BMC Bioinformatics Software BACKGROUND: Computation of reaction similarity is a pre-requisite for several bioinformatics applications including enzyme identification for specific biochemical reactions, enzyme classification and mining for specific inhibitors. Reaction similarity is often assessed at either two levels: (i) comparison across all the constituent substrates and products of a reaction, reaction level similarity, (ii) comparison at the transformation center with various degrees of neighborhood, transformation level similarity. Existing reaction similarity computation tools are designed for specific applications and use different features and similarity measures. A single system integrating these diverse features enables comparison of the impact of different molecular properties on similarity score computation. RESULTS: To address these requirements, we present SimCAL, an integrated system to calculate reaction similarity with novel features and capability to perform comparative assessment. SimCAL provides reaction similarity computation at both whole reaction level and transformation level. Novel physicochemical features such as stereochemistry, mass, volume and charge are included in computing reaction fingerprint. Users can choose from four different fingerprint types and nine molecular similarity measures. Further, a comparative assessment of these features is also enabled. The performance of SimCAL is assessed on 3,688,122 reaction pairs with Enzyme Commission (EC) number from MetaCyc and achieved an area under the curve (AUC) of > 0.9. In addition, SimCAL results showed strong correlation with state-of-the-art EC-BLAST and molecular signature based reaction similarity methods. CONCLUSIONS: SimCAL is developed in java and is available as a standalone tool, with intuitive, user-friendly graphical interface and also as a console application. With its customizable feature selection and similarity calculations, it is expected to cater a wide audience interested in studying and analyzing biochemical reactions and metabolic networks. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2248-5) contains supplementary material, which is available to authorized users. BioMed Central 2018-07-03 /pmc/articles/PMC6029250/ /pubmed/29969981 http://dx.doi.org/10.1186/s12859-018-2248-5 Text en © The Author(s). 2018 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 | Software Sivakumar, Tadi Venkata Bhaduri, Anirban Duvvuru Muni, Rajasekhara Reddy Park, Jin Hwan Kim, Tae Yong SimCAL: a flexible tool to compute biochemical reaction similarity |
title | SimCAL: a flexible tool to compute biochemical reaction similarity |
title_full | SimCAL: a flexible tool to compute biochemical reaction similarity |
title_fullStr | SimCAL: a flexible tool to compute biochemical reaction similarity |
title_full_unstemmed | SimCAL: a flexible tool to compute biochemical reaction similarity |
title_short | SimCAL: a flexible tool to compute biochemical reaction similarity |
title_sort | simcal: a flexible tool to compute biochemical reaction similarity |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029250/ https://www.ncbi.nlm.nih.gov/pubmed/29969981 http://dx.doi.org/10.1186/s12859-018-2248-5 |
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