Recognizing ion ligand binding sites by SMO algorithm
Background In many important life activities, the execution of protein function depends on the interaction between proteins and ligands. As an important protein binding ligand, the identification of the binding site of the ion ligands plays an important role in the study of the protein function. Res...
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Gespeichert in:
| Autor*in: |
Wang, Shan [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s). 2019 |
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| Übergeordnetes Werk: |
Enthalten in: BMC cell biology - London : BioMed Central, 2000, 20(2019), Suppl 3 vom: 11. Dez. |
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| Übergeordnetes Werk: |
volume:20 ; year:2019 ; number:Suppl 3 ; day:11 ; month:12 |
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| DOI / URN: |
10.1186/s12860-019-0237-9 |
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SPR026940892 |
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| 520 | |a Background In many important life activities, the execution of protein function depends on the interaction between proteins and ligands. As an important protein binding ligand, the identification of the binding site of the ion ligands plays an important role in the study of the protein function. Results In this study, four acid radical ion ligands ($ NO_{2} $−,$ CO_{3} $2−,$ SO_{4} $2−,$ PO_{4} $3−) and ten metal ion ligands ($ Zn^{2+} $,$ Cu^{2+} $,$ Fe^{2+} $,$ Fe^{3+} $,$ Ca^{2+} $,$ Mg^{2+} $,$ Mn^{2+} $,$ Na^{+} $,$ K^{+} $,$ Co^{2+} $) are selected as the research object, and the Sequential minimal optimization (SMO) algorithm based on sequence information was proposed, better prediction results were obtained by 5-fold cross validation. Conclusions An efficient method for predicting ion ligand binding sites was presented. | ||
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| 650 | 4 | |a SMO algorithm |7 (dpeaa)DE-He213 | |
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| 650 | 4 | |a Sequence information |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Hu, Xiuzhen |4 aut | |
| 700 | 1 | |a Feng, Zhenxing |4 aut | |
| 700 | 1 | |a Zhang, Xiaojin |4 aut | |
| 700 | 1 | |a Liu, Liu |4 aut | |
| 700 | 1 | |a Sun, Kai |4 aut | |
| 700 | 1 | |a Xu, Shuang |4 aut | |
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10.1186/s12860-019-0237-9 doi (DE-627)SPR026940892 (SPR)s12860-019-0237-9-e DE-627 ger DE-627 rakwb eng Wang, Shan verfasserin aut Recognizing ion ligand binding sites by SMO algorithm 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background In many important life activities, the execution of protein function depends on the interaction between proteins and ligands. As an important protein binding ligand, the identification of the binding site of the ion ligands plays an important role in the study of the protein function. Results In this study, four acid radical ion ligands ($ NO_{2} $−,$ CO_{3} $2−,$ SO_{4} $2−,$ PO_{4} $3−) and ten metal ion ligands ($ Zn^{2+} $,$ Cu^{2+} $,$ Fe^{2+} $,$ Fe^{3+} $,$ Ca^{2+} $,$ Mg^{2+} $,$ Mn^{2+} $,$ Na^{+} $,$ K^{+} $,$ Co^{2+} $) are selected as the research object, and the Sequential minimal optimization (SMO) algorithm based on sequence information was proposed, better prediction results were obtained by 5-fold cross validation. Conclusions An efficient method for predicting ion ligand binding sites was presented. Ion ligand (dpeaa)DE-He213 SMO algorithm (dpeaa)DE-He213 Binding site (dpeaa)DE-He213 Sequence information (dpeaa)DE-He213 Hu, Xiuzhen aut Feng, Zhenxing aut Zhang, Xiaojin aut Liu, Liu aut Sun, Kai aut Xu, Shuang aut Enthalten in BMC cell biology London : BioMed Central, 2000 20(2019), Suppl 3 vom: 11. Dez. (DE-627)326644830 (DE-600)2041486-9 1471-2121 nnns volume:20 year:2019 number:Suppl 3 day:11 month:12 https://dx.doi.org/10.1186/s12860-019-0237-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_22 GBV_ILN_2003 GBV_ILN_2008 GBV_ILN_2021 GBV_ILN_4305 AR 20 2019 Suppl 3 11 12 |
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10.1186/s12860-019-0237-9 doi (DE-627)SPR026940892 (SPR)s12860-019-0237-9-e DE-627 ger DE-627 rakwb eng Wang, Shan verfasserin aut Recognizing ion ligand binding sites by SMO algorithm 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background In many important life activities, the execution of protein function depends on the interaction between proteins and ligands. As an important protein binding ligand, the identification of the binding site of the ion ligands plays an important role in the study of the protein function. Results In this study, four acid radical ion ligands ($ NO_{2} $−,$ CO_{3} $2−,$ SO_{4} $2−,$ PO_{4} $3−) and ten metal ion ligands ($ Zn^{2+} $,$ Cu^{2+} $,$ Fe^{2+} $,$ Fe^{3+} $,$ Ca^{2+} $,$ Mg^{2+} $,$ Mn^{2+} $,$ Na^{+} $,$ K^{+} $,$ Co^{2+} $) are selected as the research object, and the Sequential minimal optimization (SMO) algorithm based on sequence information was proposed, better prediction results were obtained by 5-fold cross validation. Conclusions An efficient method for predicting ion ligand binding sites was presented. Ion ligand (dpeaa)DE-He213 SMO algorithm (dpeaa)DE-He213 Binding site (dpeaa)DE-He213 Sequence information (dpeaa)DE-He213 Hu, Xiuzhen aut Feng, Zhenxing aut Zhang, Xiaojin aut Liu, Liu aut Sun, Kai aut Xu, Shuang aut Enthalten in BMC cell biology London : BioMed Central, 2000 20(2019), Suppl 3 vom: 11. Dez. (DE-627)326644830 (DE-600)2041486-9 1471-2121 nnns volume:20 year:2019 number:Suppl 3 day:11 month:12 https://dx.doi.org/10.1186/s12860-019-0237-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_22 GBV_ILN_2003 GBV_ILN_2008 GBV_ILN_2021 GBV_ILN_4305 AR 20 2019 Suppl 3 11 12 |
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10.1186/s12860-019-0237-9 doi (DE-627)SPR026940892 (SPR)s12860-019-0237-9-e DE-627 ger DE-627 rakwb eng Wang, Shan verfasserin aut Recognizing ion ligand binding sites by SMO algorithm 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background In many important life activities, the execution of protein function depends on the interaction between proteins and ligands. As an important protein binding ligand, the identification of the binding site of the ion ligands plays an important role in the study of the protein function. Results In this study, four acid radical ion ligands ($ NO_{2} $−,$ CO_{3} $2−,$ SO_{4} $2−,$ PO_{4} $3−) and ten metal ion ligands ($ Zn^{2+} $,$ Cu^{2+} $,$ Fe^{2+} $,$ Fe^{3+} $,$ Ca^{2+} $,$ Mg^{2+} $,$ Mn^{2+} $,$ Na^{+} $,$ K^{+} $,$ Co^{2+} $) are selected as the research object, and the Sequential minimal optimization (SMO) algorithm based on sequence information was proposed, better prediction results were obtained by 5-fold cross validation. Conclusions An efficient method for predicting ion ligand binding sites was presented. Ion ligand (dpeaa)DE-He213 SMO algorithm (dpeaa)DE-He213 Binding site (dpeaa)DE-He213 Sequence information (dpeaa)DE-He213 Hu, Xiuzhen aut Feng, Zhenxing aut Zhang, Xiaojin aut Liu, Liu aut Sun, Kai aut Xu, Shuang aut Enthalten in BMC cell biology London : BioMed Central, 2000 20(2019), Suppl 3 vom: 11. Dez. (DE-627)326644830 (DE-600)2041486-9 1471-2121 nnns volume:20 year:2019 number:Suppl 3 day:11 month:12 https://dx.doi.org/10.1186/s12860-019-0237-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_22 GBV_ILN_2003 GBV_ILN_2008 GBV_ILN_2021 GBV_ILN_4305 AR 20 2019 Suppl 3 11 12 |
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10.1186/s12860-019-0237-9 doi (DE-627)SPR026940892 (SPR)s12860-019-0237-9-e DE-627 ger DE-627 rakwb eng Wang, Shan verfasserin aut Recognizing ion ligand binding sites by SMO algorithm 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background In many important life activities, the execution of protein function depends on the interaction between proteins and ligands. As an important protein binding ligand, the identification of the binding site of the ion ligands plays an important role in the study of the protein function. Results In this study, four acid radical ion ligands ($ NO_{2} $−,$ CO_{3} $2−,$ SO_{4} $2−,$ PO_{4} $3−) and ten metal ion ligands ($ Zn^{2+} $,$ Cu^{2+} $,$ Fe^{2+} $,$ Fe^{3+} $,$ Ca^{2+} $,$ Mg^{2+} $,$ Mn^{2+} $,$ Na^{+} $,$ K^{+} $,$ Co^{2+} $) are selected as the research object, and the Sequential minimal optimization (SMO) algorithm based on sequence information was proposed, better prediction results were obtained by 5-fold cross validation. Conclusions An efficient method for predicting ion ligand binding sites was presented. Ion ligand (dpeaa)DE-He213 SMO algorithm (dpeaa)DE-He213 Binding site (dpeaa)DE-He213 Sequence information (dpeaa)DE-He213 Hu, Xiuzhen aut Feng, Zhenxing aut Zhang, Xiaojin aut Liu, Liu aut Sun, Kai aut Xu, Shuang aut Enthalten in BMC cell biology London : BioMed Central, 2000 20(2019), Suppl 3 vom: 11. Dez. (DE-627)326644830 (DE-600)2041486-9 1471-2121 nnns volume:20 year:2019 number:Suppl 3 day:11 month:12 https://dx.doi.org/10.1186/s12860-019-0237-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_22 GBV_ILN_2003 GBV_ILN_2008 GBV_ILN_2021 GBV_ILN_4305 AR 20 2019 Suppl 3 11 12 |
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10.1186/s12860-019-0237-9 doi (DE-627)SPR026940892 (SPR)s12860-019-0237-9-e DE-627 ger DE-627 rakwb eng Wang, Shan verfasserin aut Recognizing ion ligand binding sites by SMO algorithm 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background In many important life activities, the execution of protein function depends on the interaction between proteins and ligands. As an important protein binding ligand, the identification of the binding site of the ion ligands plays an important role in the study of the protein function. Results In this study, four acid radical ion ligands ($ NO_{2} $−,$ CO_{3} $2−,$ SO_{4} $2−,$ PO_{4} $3−) and ten metal ion ligands ($ Zn^{2+} $,$ Cu^{2+} $,$ Fe^{2+} $,$ Fe^{3+} $,$ Ca^{2+} $,$ Mg^{2+} $,$ Mn^{2+} $,$ Na^{+} $,$ K^{+} $,$ Co^{2+} $) are selected as the research object, and the Sequential minimal optimization (SMO) algorithm based on sequence information was proposed, better prediction results were obtained by 5-fold cross validation. Conclusions An efficient method for predicting ion ligand binding sites was presented. Ion ligand (dpeaa)DE-He213 SMO algorithm (dpeaa)DE-He213 Binding site (dpeaa)DE-He213 Sequence information (dpeaa)DE-He213 Hu, Xiuzhen aut Feng, Zhenxing aut Zhang, Xiaojin aut Liu, Liu aut Sun, Kai aut Xu, Shuang aut Enthalten in BMC cell biology London : BioMed Central, 2000 20(2019), Suppl 3 vom: 11. Dez. (DE-627)326644830 (DE-600)2041486-9 1471-2121 nnns volume:20 year:2019 number:Suppl 3 day:11 month:12 https://dx.doi.org/10.1186/s12860-019-0237-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_22 GBV_ILN_2003 GBV_ILN_2008 GBV_ILN_2021 GBV_ILN_4305 AR 20 2019 Suppl 3 11 12 |
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Background In many important life activities, the execution of protein function depends on the interaction between proteins and ligands. As an important protein binding ligand, the identification of the binding site of the ion ligands plays an important role in the study of the protein function. Results In this study, four acid radical ion ligands ($ NO_{2} $−,$ CO_{3} $2−,$ SO_{4} $2−,$ PO_{4} $3−) and ten metal ion ligands ($ Zn^{2+} $,$ Cu^{2+} $,$ Fe^{2+} $,$ Fe^{3+} $,$ Ca^{2+} $,$ Mg^{2+} $,$ Mn^{2+} $,$ Na^{+} $,$ K^{+} $,$ Co^{2+} $) are selected as the research object, and the Sequential minimal optimization (SMO) algorithm based on sequence information was proposed, better prediction results were obtained by 5-fold cross validation. Conclusions An efficient method for predicting ion ligand binding sites was presented. © The Author(s). 2019 |
| abstractGer |
Background In many important life activities, the execution of protein function depends on the interaction between proteins and ligands. As an important protein binding ligand, the identification of the binding site of the ion ligands plays an important role in the study of the protein function. Results In this study, four acid radical ion ligands ($ NO_{2} $−,$ CO_{3} $2−,$ SO_{4} $2−,$ PO_{4} $3−) and ten metal ion ligands ($ Zn^{2+} $,$ Cu^{2+} $,$ Fe^{2+} $,$ Fe^{3+} $,$ Ca^{2+} $,$ Mg^{2+} $,$ Mn^{2+} $,$ Na^{+} $,$ K^{+} $,$ Co^{2+} $) are selected as the research object, and the Sequential minimal optimization (SMO) algorithm based on sequence information was proposed, better prediction results were obtained by 5-fold cross validation. Conclusions An efficient method for predicting ion ligand binding sites was presented. © The Author(s). 2019 |
| abstract_unstemmed |
Background In many important life activities, the execution of protein function depends on the interaction between proteins and ligands. As an important protein binding ligand, the identification of the binding site of the ion ligands plays an important role in the study of the protein function. Results In this study, four acid radical ion ligands ($ NO_{2} $−,$ CO_{3} $2−,$ SO_{4} $2−,$ PO_{4} $3−) and ten metal ion ligands ($ Zn^{2+} $,$ Cu^{2+} $,$ Fe^{2+} $,$ Fe^{3+} $,$ Ca^{2+} $,$ Mg^{2+} $,$ Mn^{2+} $,$ Na^{+} $,$ K^{+} $,$ Co^{2+} $) are selected as the research object, and the Sequential minimal optimization (SMO) algorithm based on sequence information was proposed, better prediction results were obtained by 5-fold cross validation. Conclusions An efficient method for predicting ion ligand binding sites was presented. © The Author(s). 2019 |
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| title_short |
Recognizing ion ligand binding sites by SMO algorithm |
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Hu, Xiuzhen Feng, Zhenxing Zhang, Xiaojin Liu, Liu Sun, Kai Xu, Shuang |
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Hu, Xiuzhen Feng, Zhenxing Zhang, Xiaojin Liu, Liu Sun, Kai Xu, Shuang |
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2024-07-03T23:33:54.970Z |
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