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An efficient computer-aided structural elucidation strategy for mixtures using an iterative dynamic programming algorithm

The identification of chemical structures in natural product mixtures is an important task in drug discovery but is still a challenging problem, as structural elucidation is a time-consuming process and is limited by the available mass spectra of known natural products. Computer-aided structure eluc...

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Autores principales: Su, Bo-Han, Shen, Meng-Yu, Harn, Yeu-Chern, Wang, San-Yuan, Schurz, Alioune, Lin, Chieh, Lin, Olivia A., Tseng, Yufeng J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5688056/
https://www.ncbi.nlm.nih.gov/pubmed/29143270
http://dx.doi.org/10.1186/s13321-017-0244-9
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author Su, Bo-Han
Shen, Meng-Yu
Harn, Yeu-Chern
Wang, San-Yuan
Schurz, Alioune
Lin, Chieh
Lin, Olivia A.
Tseng, Yufeng J.
author_facet Su, Bo-Han
Shen, Meng-Yu
Harn, Yeu-Chern
Wang, San-Yuan
Schurz, Alioune
Lin, Chieh
Lin, Olivia A.
Tseng, Yufeng J.
author_sort Su, Bo-Han
collection PubMed
description The identification of chemical structures in natural product mixtures is an important task in drug discovery but is still a challenging problem, as structural elucidation is a time-consuming process and is limited by the available mass spectra of known natural products. Computer-aided structure elucidation (CASE) strategies seek to automatically propose a list of possible chemical structures in mixtures by utilizing chromatographic and spectroscopic methods. However, current CASE tools still cannot automatically solve structures for experienced natural product chemists. Here, we formulated the structural elucidation of natural products in a mixture as a computational problem by extending a list of scaffolds using a weighted side chain list after analyzing a collection of 243,130 natural products and designed an efficient algorithm to precisely identify the chemical structures. The complexity of such a problem is NP-complete. A dynamic programming (DP) algorithm can solve this NP-complete problem in pseudo-polynomial time after converting floating point molecular weights into integers. However, the running time of the DP algorithm degrades exponentially as the precision of the mass spectrometry experiment grows. To ideally solve in polynomial time, we proposed a novel iterative DP algorithm that can quickly recognize the chemical structures of natural products. By utilizing this algorithm to elucidate the structures of four natural products that were experimentally and structurally determined, the algorithm can search the exact solutions, and the time performance was shown to be in polynomial time for average cases. The proposed method improved the speed of the structural elucidation of natural products and helped broaden the spectrum of available compounds that could be applied as new drug candidates. A web service built for structural elucidation studies is freely accessible via the following link (http://csccp.cmdm.tw/). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13321-017-0244-9) contains supplementary material, which is available to authorized users.
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spelling pubmed-56880562017-12-01 An efficient computer-aided structural elucidation strategy for mixtures using an iterative dynamic programming algorithm Su, Bo-Han Shen, Meng-Yu Harn, Yeu-Chern Wang, San-Yuan Schurz, Alioune Lin, Chieh Lin, Olivia A. Tseng, Yufeng J. J Cheminform Research Article The identification of chemical structures in natural product mixtures is an important task in drug discovery but is still a challenging problem, as structural elucidation is a time-consuming process and is limited by the available mass spectra of known natural products. Computer-aided structure elucidation (CASE) strategies seek to automatically propose a list of possible chemical structures in mixtures by utilizing chromatographic and spectroscopic methods. However, current CASE tools still cannot automatically solve structures for experienced natural product chemists. Here, we formulated the structural elucidation of natural products in a mixture as a computational problem by extending a list of scaffolds using a weighted side chain list after analyzing a collection of 243,130 natural products and designed an efficient algorithm to precisely identify the chemical structures. The complexity of such a problem is NP-complete. A dynamic programming (DP) algorithm can solve this NP-complete problem in pseudo-polynomial time after converting floating point molecular weights into integers. However, the running time of the DP algorithm degrades exponentially as the precision of the mass spectrometry experiment grows. To ideally solve in polynomial time, we proposed a novel iterative DP algorithm that can quickly recognize the chemical structures of natural products. By utilizing this algorithm to elucidate the structures of four natural products that were experimentally and structurally determined, the algorithm can search the exact solutions, and the time performance was shown to be in polynomial time for average cases. The proposed method improved the speed of the structural elucidation of natural products and helped broaden the spectrum of available compounds that could be applied as new drug candidates. A web service built for structural elucidation studies is freely accessible via the following link (http://csccp.cmdm.tw/). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13321-017-0244-9) contains supplementary material, which is available to authorized users. Springer International Publishing 2017-11-15 /pmc/articles/PMC5688056/ /pubmed/29143270 http://dx.doi.org/10.1186/s13321-017-0244-9 Text en © The Author(s) 2017 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 Research Article
Su, Bo-Han
Shen, Meng-Yu
Harn, Yeu-Chern
Wang, San-Yuan
Schurz, Alioune
Lin, Chieh
Lin, Olivia A.
Tseng, Yufeng J.
An efficient computer-aided structural elucidation strategy for mixtures using an iterative dynamic programming algorithm
title An efficient computer-aided structural elucidation strategy for mixtures using an iterative dynamic programming algorithm
title_full An efficient computer-aided structural elucidation strategy for mixtures using an iterative dynamic programming algorithm
title_fullStr An efficient computer-aided structural elucidation strategy for mixtures using an iterative dynamic programming algorithm
title_full_unstemmed An efficient computer-aided structural elucidation strategy for mixtures using an iterative dynamic programming algorithm
title_short An efficient computer-aided structural elucidation strategy for mixtures using an iterative dynamic programming algorithm
title_sort efficient computer-aided structural elucidation strategy for mixtures using an iterative dynamic programming algorithm
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5688056/
https://www.ncbi.nlm.nih.gov/pubmed/29143270
http://dx.doi.org/10.1186/s13321-017-0244-9
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