A Multi-Objective Approach for Protein Structure Prediction Based on an Energy Model and Backbone Angle Preferences
Protein structure prediction (PSP) is concerned with the prediction of protein tertiary structure from primary structure and is a challenging calculation problem. After decades of research effort, numerous solutions have been proposed for optimisation methods based on energy models. However, further...
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-07-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | http://www.mdpi.com/1422-0067/16/7/15136 |
| _version_ | 1811280058274283520 |
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| author | Jyh-Jong Tsay Shih-Chieh Su Chin-Sheng Yu |
| author_facet | Jyh-Jong Tsay Shih-Chieh Su Chin-Sheng Yu |
| author_sort | Jyh-Jong Tsay |
| collection | DOAJ |
| description | Protein structure prediction (PSP) is concerned with the prediction of protein tertiary structure from primary structure and is a challenging calculation problem. After decades of research effort, numerous solutions have been proposed for optimisation methods based on energy models. However, further investigation and improvement is still needed to increase the accuracy and similarity of structures. This study presents a novel backbone angle preference factor, which is one of the factors inducing protein folding. The proposed multiobjective optimisation approach simultaneously considers energy models and backbone angle preferences to solve the ab initio PSP. To prove the effectiveness of the multiobjective optimisation approach based on the energy models and backbone angle preferences, 75 amino acid sequences with lengths ranging from 22 to 88 amino acids were selected from the CB513 data set to be the benchmarks. The data sets were highly dissimilar, therefore indicating that they are meaningful. The experimental results showed that the root-mean-square deviation (RMSD) of the multiobjective optimization approach based on energy model and backbone angle preferences was superior to those of typical energy models, indicating that the proposed approach can facilitate the ab initio PSP. |
| first_indexed | 2024-04-13T01:07:42Z |
| format | Article |
| id | doaj.art-79906ff708d24654b3f493698150f3e8 |
| institution | Directory Open Access Journal |
| issn | 1422-0067 |
| language | English |
| last_indexed | 2024-04-13T01:07:42Z |
| publishDate | 2015-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-79906ff708d24654b3f493698150f3e82022-12-22T03:09:17ZengMDPI AGInternational Journal of Molecular Sciences1422-00672015-07-01167151361514910.3390/ijms160715136ijms160715136A Multi-Objective Approach for Protein Structure Prediction Based on an Energy Model and Backbone Angle PreferencesJyh-Jong Tsay0Shih-Chieh Su1Chin-Sheng Yu2Department of Computer Science and Information Engineering, National Chung Cheng University, Min-Hsiung Township, Chia-yi County 62102, TaiwanDepartment of Computer Science and Information Engineering, National Chung Cheng University, Min-Hsiung Township, Chia-yi County 62102, TaiwanDepartment of Information Engineering and Computer Science, Feng Chia University, Taichung 40724, TaiwanProtein structure prediction (PSP) is concerned with the prediction of protein tertiary structure from primary structure and is a challenging calculation problem. After decades of research effort, numerous solutions have been proposed for optimisation methods based on energy models. However, further investigation and improvement is still needed to increase the accuracy and similarity of structures. This study presents a novel backbone angle preference factor, which is one of the factors inducing protein folding. The proposed multiobjective optimisation approach simultaneously considers energy models and backbone angle preferences to solve the ab initio PSP. To prove the effectiveness of the multiobjective optimisation approach based on the energy models and backbone angle preferences, 75 amino acid sequences with lengths ranging from 22 to 88 amino acids were selected from the CB513 data set to be the benchmarks. The data sets were highly dissimilar, therefore indicating that they are meaningful. The experimental results showed that the root-mean-square deviation (RMSD) of the multiobjective optimization approach based on energy model and backbone angle preferences was superior to those of typical energy models, indicating that the proposed approach can facilitate the ab initio PSP.http://www.mdpi.com/1422-0067/16/7/15136backbone angle preferencesprotein structuremultiobjective optimizationface-centered cubic |
| spellingShingle | Jyh-Jong Tsay Shih-Chieh Su Chin-Sheng Yu A Multi-Objective Approach for Protein Structure Prediction Based on an Energy Model and Backbone Angle Preferences International Journal of Molecular Sciences backbone angle preferences protein structure multiobjective optimization face-centered cubic |
| title | A Multi-Objective Approach for Protein Structure Prediction Based on an Energy Model and Backbone Angle Preferences |
| title_full | A Multi-Objective Approach for Protein Structure Prediction Based on an Energy Model and Backbone Angle Preferences |
| title_fullStr | A Multi-Objective Approach for Protein Structure Prediction Based on an Energy Model and Backbone Angle Preferences |
| title_full_unstemmed | A Multi-Objective Approach for Protein Structure Prediction Based on an Energy Model and Backbone Angle Preferences |
| title_short | A Multi-Objective Approach for Protein Structure Prediction Based on an Energy Model and Backbone Angle Preferences |
| title_sort | multi objective approach for protein structure prediction based on an energy model and backbone angle preferences |
| topic | backbone angle preferences protein structure multiobjective optimization face-centered cubic |
| url | http://www.mdpi.com/1422-0067/16/7/15136 |
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