caa a22 4500 605468516 CHVBK 20210128100317.0 cr unu---uuuuu 210128e20150601xx s 000 0 eng 10.1007/s00500-014-1353-2 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1353-2 Protein structure prediction using diversity controlled self-adaptive differential evolution with local search [Elektronische Daten] [S. Sudha, S. Baskar, S. Amali, S. Krishnaswamy] 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. Springer-Verlag Berlin Heidelberg, 2014 Protein structure prediction nationallicence Self-adaptive differential evolution nationallicence Diversity control nationallicence Local search nationallicence Met-enkephalin nationallicence Energy function nationallicence Sudha S. Thiagarajar College of Engineering, 625015, Madurai, India aut Baskar S. Thiagarajar College of Engineering, 625015, Madurai, India aut Amali S. Thiagarajar College of Engineering, 625015, Madurai, India aut Krishnaswamy S. Centre of Excellence in Bioinformatics, Madurai Kamaraj University, 625021, Madurai, India aut Soft Computing Springer Berlin Heidelberg 19/6(2015-06-01), 1635-1646 1432-7643 19:6<1635 2015 19 500 https://doi.org/10.1007/s00500-014-1353-2 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1353-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Sudha S. Thiagarajar College of Engineering, 625015, Madurai, India aut NATIONALLICENCE 700 1- Baskar S. Thiagarajar College of Engineering, 625015, Madurai, India aut NATIONALLICENCE 700 1- Amali S. Thiagarajar College of Engineering, 625015, Madurai, India aut NATIONALLICENCE 700 1- Krishnaswamy S. Centre of Excellence in Bioinformatics, Madurai Kamaraj University, 625021, Madurai, India aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/6(2015-06-01), 1635-1646 1432-7643 19:6<1635 2015 19 500