Protein structure prediction using diversity controlled self-adaptive differential evolution with local search
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| 024 | 7 | 0 | |a 10.1007/s00500-014-1353-2 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00500-014-1353-2 | ||
| 245 | 0 | 0 | |a Protein structure prediction using diversity controlled self-adaptive differential evolution with local search |h [Elektronische Daten] |c [S. Sudha, S. Baskar, S. Amali, S. Krishnaswamy] |
| 520 | 3 | |a In this paper, Protein Structure Prediction problem is solved using Diversity Controlled Self-Adaptive Differential Evolution with Local search (DCSaDE-LS). DCSaDE-LS, an improved version of Self-Adaptive Differential Evolution (SaDE), use simple fuzzy system to control the diversity of individuals and local search to maintain a balance between exploration and exploitation. DCSaDE-LS with four different local search replacement strategies are used. SaDE is also implemented for comparison purposes. Algorithms are tested on a peptide Met-enkephalin for force fields ECEPP/2, ECEPP/3 and CHARMM22. Results show that both DCSaDE-LS and SaDE produce the best energy for both force fields. Among the four replacement strategies, DCSaDE-LS1 strategy reports better results than other strategies and SaDE in terms of number of function evaluations, mean energy and success rate. Best conformations obtained using DCSaDE-LS is compared with native structure 1PLW and GEM structure Scheraga. Nonparametric statistical tests for multiple comparisons ( $$1\times N$$ 1 × N ) with control method are implemented for CHARMM22 observations. A set of unique 100 best conformations obtained from DCSaDE-LS are clustered into 3 independent clusters suggesting the robustness of this methodology and the ability to explore the conformational space available and to populate the near native conformations. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2014 | ||
| 690 | 7 | |a Protein structure prediction |2 nationallicence | |
| 690 | 7 | |a Self-adaptive differential evolution |2 nationallicence | |
| 690 | 7 | |a Diversity control |2 nationallicence | |
| 690 | 7 | |a Local search |2 nationallicence | |
| 690 | 7 | |a Met-enkephalin |2 nationallicence | |
| 690 | 7 | |a Energy function |2 nationallicence | |
| 700 | 1 | |a Sudha |D S. |u Thiagarajar College of Engineering, 625015, Madurai, India |4 aut | |
| 700 | 1 | |a Baskar |D S. |u Thiagarajar College of Engineering, 625015, Madurai, India |4 aut | |
| 700 | 1 | |a Amali |D S. |u Thiagarajar College of Engineering, 625015, Madurai, India |4 aut | |
| 700 | 1 | |a Krishnaswamy |D S. |u Centre of Excellence in Bioinformatics, Madurai Kamaraj University, 625021, Madurai, India |4 aut | |
| 773 | 0 | |t Soft Computing |d Springer Berlin Heidelberg |g 19/6(2015-06-01), 1635-1646 |x 1432-7643 |q 19:6<1635 |1 2015 |2 19 |o 500 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00500-014-1353-2 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00500-014-1353-2 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Sudha |D S. |u Thiagarajar College of Engineering, 625015, Madurai, India |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Baskar |D S. |u Thiagarajar College of Engineering, 625015, Madurai, India |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Amali |D S. |u Thiagarajar College of Engineering, 625015, Madurai, India |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Krishnaswamy |D S. |u Centre of Excellence in Bioinformatics, Madurai Kamaraj University, 625021, Madurai, India |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Soft Computing |d Springer Berlin Heidelberg |g 19/6(2015-06-01), 1635-1646 |x 1432-7643 |q 19:6<1635 |1 2015 |2 19 |o 500 | ||