Performance comparison of ab initio protein structure prediction methods
Wet Lab methods used to resolve the native structure of a given protein such as X-ray Diffraction and NMR spectroscopy are time-consuming, expensive, and could be done multiple times due to failure. Those pitfalls led to the development of computationally automated prediction methods. Predicting the...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2019-12-01
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| Series: | Ain Shams Engineering Journal |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2090447919300565 |
| _version_ | 1818863804710125568 |
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| author | Mohamad Yousef Tamer Abdelkader Khaled El-Bahnasy |
| author_facet | Mohamad Yousef Tamer Abdelkader Khaled El-Bahnasy |
| author_sort | Mohamad Yousef |
| collection | DOAJ |
| description | Wet Lab methods used to resolve the native structure of a given protein such as X-ray Diffraction and NMR spectroscopy are time-consuming, expensive, and could be done multiple times due to failure. Those pitfalls led to the development of computationally automated prediction methods. Predicting the structure of a protein using its peptide sequence only — also known as ab initio Protein Structure Prediction “PSP”— is computationally challenging because of the large conformational space to be searched and the complexity of energy functions. Some successful predictive methods have been developed to solve PSP problem. In this paper, by using a set of peptide sequences, we compare a collection of PSP ab initio-based methods. Experiments show that using a metaheuristic-based search method that utilizes genetic algorithm can achieve same or better results than time consuming methods. Keywords: Genetic algorithm, Combinatorial optimization, Protein tertiary structure, Evolutionary algorithms, Ab initio prediction, De novo prediction, Free modeling |
| first_indexed | 2024-12-19T10:21:35Z |
| format | Article |
| id | doaj.art-ddcb8bf6fc1f47ffa041419f68bce4cc |
| institution | Directory Open Access Journal |
| issn | 2090-4479 |
| language | English |
| last_indexed | 2024-12-19T10:21:35Z |
| publishDate | 2019-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ain Shams Engineering Journal |
| spelling | doaj.art-ddcb8bf6fc1f47ffa041419f68bce4cc2022-12-21T20:26:03ZengElsevierAin Shams Engineering Journal2090-44792019-12-01104713719Performance comparison of ab initio protein structure prediction methodsMohamad Yousef0Tamer Abdelkader1Khaled El-Bahnasy2Department of Information Systems, Faculty of Computer and Information Sciences, Ain Shams University, Abbassia 11566, Cairo, Egypt; Corresponding author.Department of Information Systems, Faculty of Computer and Information Sciences, Ain Shams University, Abbassia 11566, Cairo, EgyptDepartment of Information Systems, Faculty of Computer and Information Sciences, Ain Shams University, Abbassia 11566, Cairo, EgyptWet Lab methods used to resolve the native structure of a given protein such as X-ray Diffraction and NMR spectroscopy are time-consuming, expensive, and could be done multiple times due to failure. Those pitfalls led to the development of computationally automated prediction methods. Predicting the structure of a protein using its peptide sequence only — also known as ab initio Protein Structure Prediction “PSP”— is computationally challenging because of the large conformational space to be searched and the complexity of energy functions. Some successful predictive methods have been developed to solve PSP problem. In this paper, by using a set of peptide sequences, we compare a collection of PSP ab initio-based methods. Experiments show that using a metaheuristic-based search method that utilizes genetic algorithm can achieve same or better results than time consuming methods. Keywords: Genetic algorithm, Combinatorial optimization, Protein tertiary structure, Evolutionary algorithms, Ab initio prediction, De novo prediction, Free modelinghttp://www.sciencedirect.com/science/article/pii/S2090447919300565 |
| spellingShingle | Mohamad Yousef Tamer Abdelkader Khaled El-Bahnasy Performance comparison of ab initio protein structure prediction methods Ain Shams Engineering Journal |
| title | Performance comparison of ab initio protein structure prediction methods |
| title_full | Performance comparison of ab initio protein structure prediction methods |
| title_fullStr | Performance comparison of ab initio protein structure prediction methods |
| title_full_unstemmed | Performance comparison of ab initio protein structure prediction methods |
| title_short | Performance comparison of ab initio protein structure prediction methods |
| title_sort | performance comparison of ab initio protein structure prediction methods |
| url | http://www.sciencedirect.com/science/article/pii/S2090447919300565 |
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