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Proteomic analysis of cellular soluble proteins from human bronchial smooth muscle cells by combining nondenaturing micro 2DE and quantitative LC‐MS/MS. 2. Similarity search between protein maps for the analysis of protein complexes
Human bronchial smooth muscle cell soluble proteins were analyzed by a combined method of nondenaturing micro 2DE, grid gel‐cutting, and quantitative LC‐MS/MS and a native protein map was prepared for each of the identified 4323 proteins [1]. A method to evaluate the degree of similarity between the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5157777/ https://www.ncbi.nlm.nih.gov/pubmed/26031785 http://dx.doi.org/10.1002/elps.201400574 |
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author | Jin, Ya Yuan, Qi Zhang, Jun Manabe, Takashi Tan, Wen |
author_facet | Jin, Ya Yuan, Qi Zhang, Jun Manabe, Takashi Tan, Wen |
author_sort | Jin, Ya |
collection | PubMed |
description | Human bronchial smooth muscle cell soluble proteins were analyzed by a combined method of nondenaturing micro 2DE, grid gel‐cutting, and quantitative LC‐MS/MS and a native protein map was prepared for each of the identified 4323 proteins [1]. A method to evaluate the degree of similarity between the protein maps was developed since we expected the proteins comprising a protein complex would be separated together under nondenaturing conditions. The following procedure was employed using Excel macros; (i) maps that have three or more squares with protein quantity data were selected (2328 maps), (ii) within each map, the quantity values of the squares were normalized setting the highest value to be 1.0, (iii) in comparing a map with another map, the smaller normalized quantity in two corresponding squares was taken and summed throughout the map to give an “overlap score,” (iv) each map was compared against all the 2328 maps and the largest overlap score, obtained when a map was compared with itself, was set to be 1.0 thus providing 2328 “overlap factors,” (v) step (iv) was repeated for all maps providing 2328 × 2328 matrix of overlap factors. From the matrix, protein pairs that showed overlap factors above 0.65 from both protein sides were selected (431 protein pairs). Each protein pair was searched in a database (UniProtKB) on complex formation and 301 protein pairs, which comprise 35 protein complexes, were found to be documented. These results demonstrated that native protein maps and their similarity search would enable simultaneous analysis of multiple protein complexes in cells. |
format | Online Article Text |
id | pubmed-5157777 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-51577772016-12-30 Proteomic analysis of cellular soluble proteins from human bronchial smooth muscle cells by combining nondenaturing micro 2DE and quantitative LC‐MS/MS. 2. Similarity search between protein maps for the analysis of protein complexes Jin, Ya Yuan, Qi Zhang, Jun Manabe, Takashi Tan, Wen Electrophoresis Part I: Proteomics and Proteins Human bronchial smooth muscle cell soluble proteins were analyzed by a combined method of nondenaturing micro 2DE, grid gel‐cutting, and quantitative LC‐MS/MS and a native protein map was prepared for each of the identified 4323 proteins [1]. A method to evaluate the degree of similarity between the protein maps was developed since we expected the proteins comprising a protein complex would be separated together under nondenaturing conditions. The following procedure was employed using Excel macros; (i) maps that have three or more squares with protein quantity data were selected (2328 maps), (ii) within each map, the quantity values of the squares were normalized setting the highest value to be 1.0, (iii) in comparing a map with another map, the smaller normalized quantity in two corresponding squares was taken and summed throughout the map to give an “overlap score,” (iv) each map was compared against all the 2328 maps and the largest overlap score, obtained when a map was compared with itself, was set to be 1.0 thus providing 2328 “overlap factors,” (v) step (iv) was repeated for all maps providing 2328 × 2328 matrix of overlap factors. From the matrix, protein pairs that showed overlap factors above 0.65 from both protein sides were selected (431 protein pairs). Each protein pair was searched in a database (UniProtKB) on complex formation and 301 protein pairs, which comprise 35 protein complexes, were found to be documented. These results demonstrated that native protein maps and their similarity search would enable simultaneous analysis of multiple protein complexes in cells. John Wiley and Sons Inc. 2015-07-20 2015-09 /pmc/articles/PMC5157777/ /pubmed/26031785 http://dx.doi.org/10.1002/elps.201400574 Text en © 2015 The Authors ELECTROPHORESIS Published by Wiley‐VCH Verlag GmbH & Co. KGaA This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs (http://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Part I: Proteomics and Proteins Jin, Ya Yuan, Qi Zhang, Jun Manabe, Takashi Tan, Wen Proteomic analysis of cellular soluble proteins from human bronchial smooth muscle cells by combining nondenaturing micro 2DE and quantitative LC‐MS/MS. 2. Similarity search between protein maps for the analysis of protein complexes |
title | Proteomic analysis of cellular soluble proteins from human bronchial smooth muscle cells by combining nondenaturing micro 2DE and quantitative LC‐MS/MS. 2. Similarity search between protein maps for the analysis of protein complexes |
title_full | Proteomic analysis of cellular soluble proteins from human bronchial smooth muscle cells by combining nondenaturing micro 2DE and quantitative LC‐MS/MS. 2. Similarity search between protein maps for the analysis of protein complexes |
title_fullStr | Proteomic analysis of cellular soluble proteins from human bronchial smooth muscle cells by combining nondenaturing micro 2DE and quantitative LC‐MS/MS. 2. Similarity search between protein maps for the analysis of protein complexes |
title_full_unstemmed | Proteomic analysis of cellular soluble proteins from human bronchial smooth muscle cells by combining nondenaturing micro 2DE and quantitative LC‐MS/MS. 2. Similarity search between protein maps for the analysis of protein complexes |
title_short | Proteomic analysis of cellular soluble proteins from human bronchial smooth muscle cells by combining nondenaturing micro 2DE and quantitative LC‐MS/MS. 2. Similarity search between protein maps for the analysis of protein complexes |
title_sort | proteomic analysis of cellular soluble proteins from human bronchial smooth muscle cells by combining nondenaturing micro 2de and quantitative lc‐ms/ms. 2. similarity search between protein maps for the analysis of protein complexes |
topic | Part I: Proteomics and Proteins |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5157777/ https://www.ncbi.nlm.nih.gov/pubmed/26031785 http://dx.doi.org/10.1002/elps.201400574 |
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