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IDPM: an online database for ion distribution in protein molecules
BACKGROUND: Interactions between ions and proteins have been extensively studied, yet most of the studies focus on the ion binding site. The binding mechanism for many ion binding sites can be clearly described from high resolution structures. Although knowledge accumulated on a case-by-case basis i...
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/PMC5857119/ https://www.ncbi.nlm.nih.gov/pubmed/29548284 http://dx.doi.org/10.1186/s12859-018-2110-9 |
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author | Xiang, Xilun Liu, Haiguang |
author_facet | Xiang, Xilun Liu, Haiguang |
author_sort | Xiang, Xilun |
collection | PubMed |
description | BACKGROUND: Interactions between ions and proteins have been extensively studied, yet most of the studies focus on the ion binding site. The binding mechanism for many ion binding sites can be clearly described from high resolution structures. Although knowledge accumulated on a case-by-case basis is valuable, it is also important to study the ion-protein interaction statistically. From experimentally determined structures, it is possible to examine the ion distribution around each amino acid. Such distributions can reveal relation between ions and amino acids, so it is desirable to carry out a systematic survey of ‘ion-amino acid’ pairing interaction and share the information with a publicly available database. RESULTS: The survey in the Protein Data Bank (PDB) revealed that approximately 40% of molecules records contain at least one ion. To reduce the bias resulted from protein redundancy, the statistics were extracted from a non-redundant dataset by excluding the proteins with similar sequences. Based on the structures of protein molecules and the location of ions, the statistical distributions of ions around each proteinogenic amino acid type were investigated and further summarized in a database. To systematically quantify the interactions between ions and each amino acid, the positions of ions were mapped to the coordinate system centered at each neighboring amino acid. It was found that the distribution of ions follows the expected rules governed by the physicochemical interactions in general. Large variations were observed, reflecting the preference in ‘ion-amino acid’ interactions. The analysis program is written in the Python programming language. The statistical results and program are available from the online database: ion distribution in protein molecules (IDPM) at http://liulab.csrc.ac.cn/idpm/. CONCLUSION: The spatial distribution of ions around amino acids is documented and analyzed. The statistics can be useful for identifying ion types for a given site in biomolecules, and can be potentially used in ion position prediction for given structures. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2110-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5857119 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-58571192018-03-22 IDPM: an online database for ion distribution in protein molecules Xiang, Xilun Liu, Haiguang BMC Bioinformatics Research Article BACKGROUND: Interactions between ions and proteins have been extensively studied, yet most of the studies focus on the ion binding site. The binding mechanism for many ion binding sites can be clearly described from high resolution structures. Although knowledge accumulated on a case-by-case basis is valuable, it is also important to study the ion-protein interaction statistically. From experimentally determined structures, it is possible to examine the ion distribution around each amino acid. Such distributions can reveal relation between ions and amino acids, so it is desirable to carry out a systematic survey of ‘ion-amino acid’ pairing interaction and share the information with a publicly available database. RESULTS: The survey in the Protein Data Bank (PDB) revealed that approximately 40% of molecules records contain at least one ion. To reduce the bias resulted from protein redundancy, the statistics were extracted from a non-redundant dataset by excluding the proteins with similar sequences. Based on the structures of protein molecules and the location of ions, the statistical distributions of ions around each proteinogenic amino acid type were investigated and further summarized in a database. To systematically quantify the interactions between ions and each amino acid, the positions of ions were mapped to the coordinate system centered at each neighboring amino acid. It was found that the distribution of ions follows the expected rules governed by the physicochemical interactions in general. Large variations were observed, reflecting the preference in ‘ion-amino acid’ interactions. The analysis program is written in the Python programming language. The statistical results and program are available from the online database: ion distribution in protein molecules (IDPM) at http://liulab.csrc.ac.cn/idpm/. CONCLUSION: The spatial distribution of ions around amino acids is documented and analyzed. The statistics can be useful for identifying ion types for a given site in biomolecules, and can be potentially used in ion position prediction for given structures. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2110-9) contains supplementary material, which is available to authorized users. BioMed Central 2018-03-16 /pmc/articles/PMC5857119/ /pubmed/29548284 http://dx.doi.org/10.1186/s12859-018-2110-9 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 | Research Article Xiang, Xilun Liu, Haiguang IDPM: an online database for ion distribution in protein molecules |
title | IDPM: an online database for ion distribution in protein molecules |
title_full | IDPM: an online database for ion distribution in protein molecules |
title_fullStr | IDPM: an online database for ion distribution in protein molecules |
title_full_unstemmed | IDPM: an online database for ion distribution in protein molecules |
title_short | IDPM: an online database for ion distribution in protein molecules |
title_sort | idpm: an online database for ion distribution in protein molecules |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5857119/ https://www.ncbi.nlm.nih.gov/pubmed/29548284 http://dx.doi.org/10.1186/s12859-018-2110-9 |
work_keys_str_mv | AT xiangxilun idpmanonlinedatabaseforiondistributioninproteinmolecules AT liuhaiguang idpmanonlinedatabaseforiondistributioninproteinmolecules |