A Firefly-Inspired Method for Protein Structure Prediction in Lattice Models
We introduce a Firefly-inspired algorithmic approach for protein structure prediction over two different lattice models in three-dimensional space. In particular, we consider three-dimensional cubic and three-dimensional face-centred-cubic (FCC) lattices. The underlying energy models are the Hydroph...
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| Format: | Article |
| Language: | English |
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MDPI AG
2014-01-01
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| Series: | Biomolecules |
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| Online Access: | http://www.mdpi.com/2218-273X/4/1/56 |
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| author | Brian Maher Andreas A. Albrecht Martin Loomes Xin-She Yang Kathleen Steinhöfel |
| author_facet | Brian Maher Andreas A. Albrecht Martin Loomes Xin-She Yang Kathleen Steinhöfel |
| author_sort | Brian Maher |
| collection | DOAJ |
| description | We introduce a Firefly-inspired algorithmic approach for protein structure prediction over two different lattice models in three-dimensional space. In particular, we consider three-dimensional cubic and three-dimensional face-centred-cubic (FCC) lattices. The underlying energy models are the Hydrophobic-Polar (H-P) model, the Miyazawa–Jernigan (M-J) model and a related matrix model. The implementation of our approach is tested on ten H-P benchmark problems of a length of 48 and ten M-J benchmark problems of a length ranging from 48 until 61. The key complexity parameter we investigate is the total number of objective function evaluations required to achieve the optimum energy values for the H-P model or competitive results in comparison to published values for the M-J model. For H-P instances and cubic lattices, where data for comparison are available, we obtain an average speed-up over eight instances of 2.1, leaving out two extreme values (otherwise, 8.8). For six M-J instances, data for comparison are available for cubic lattices and runs with a population size of 100, where, a priori, the minimum free energy is a termination criterion. The average speed-up over four instances is 1.2 (leaving out two extreme values, otherwise 1.1), which is achieved for a population size of only eight instances. The present study is a test case with initial results for ad hoc parameter settings, with the aim of justifying future research on larger instances within lattice model settings, eventually leading to the ultimate goal of implementations for off-lattice models. |
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| issn | 2218-273X |
| language | English |
| last_indexed | 2024-12-23T11:05:23Z |
| publishDate | 2014-01-01 |
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| series | Biomolecules |
| spelling | doaj.art-dbe338f3e44742d4bd3c84933fc5a5ec2022-12-21T17:49:30ZengMDPI AGBiomolecules2218-273X2014-01-0141567510.3390/biom4010056biom4010056A Firefly-Inspired Method for Protein Structure Prediction in Lattice ModelsBrian Maher0Andreas A. Albrecht1Martin Loomes2Xin-She Yang3Kathleen Steinhöfel4Department of Informatics, King's College London, Strand, London WC2R 2LS, UKSchool of Science and Technology, Middlesex University, The Burroughs, London, NW4 4BT, UKSchool of Science and Technology, Middlesex University, The Burroughs, London, NW4 4BT, UKSchool of Science and Technology, Middlesex University, The Burroughs, London, NW4 4BT, UKDepartment of Informatics, King's College London, Strand, London WC2R 2LS, UKWe introduce a Firefly-inspired algorithmic approach for protein structure prediction over two different lattice models in three-dimensional space. In particular, we consider three-dimensional cubic and three-dimensional face-centred-cubic (FCC) lattices. The underlying energy models are the Hydrophobic-Polar (H-P) model, the Miyazawa–Jernigan (M-J) model and a related matrix model. The implementation of our approach is tested on ten H-P benchmark problems of a length of 48 and ten M-J benchmark problems of a length ranging from 48 until 61. The key complexity parameter we investigate is the total number of objective function evaluations required to achieve the optimum energy values for the H-P model or competitive results in comparison to published values for the M-J model. For H-P instances and cubic lattices, where data for comparison are available, we obtain an average speed-up over eight instances of 2.1, leaving out two extreme values (otherwise, 8.8). For six M-J instances, data for comparison are available for cubic lattices and runs with a population size of 100, where, a priori, the minimum free energy is a termination criterion. The average speed-up over four instances is 1.2 (leaving out two extreme values, otherwise 1.1), which is achieved for a population size of only eight instances. The present study is a test case with initial results for ad hoc parameter settings, with the aim of justifying future research on larger instances within lattice model settings, eventually leading to the ultimate goal of implementations for off-lattice models.http://www.mdpi.com/2218-273X/4/1/56protein foldinglattice modelsH-P and M-J energy functionsFirefly Algorithm |
| spellingShingle | Brian Maher Andreas A. Albrecht Martin Loomes Xin-She Yang Kathleen Steinhöfel A Firefly-Inspired Method for Protein Structure Prediction in Lattice Models Biomolecules protein folding lattice models H-P and M-J energy functions Firefly Algorithm |
| title | A Firefly-Inspired Method for Protein Structure Prediction in Lattice Models |
| title_full | A Firefly-Inspired Method for Protein Structure Prediction in Lattice Models |
| title_fullStr | A Firefly-Inspired Method for Protein Structure Prediction in Lattice Models |
| title_full_unstemmed | A Firefly-Inspired Method for Protein Structure Prediction in Lattice Models |
| title_short | A Firefly-Inspired Method for Protein Structure Prediction in Lattice Models |
| title_sort | firefly inspired method for protein structure prediction in lattice models |
| topic | protein folding lattice models H-P and M-J energy functions Firefly Algorithm |
| url | http://www.mdpi.com/2218-273X/4/1/56 |
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