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A Hybrid Evolutionary Algorithm for Protein Structure Prediction Using the Face-Centered Cubic Lattice Model

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Neural Information Processing (ICONIP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10634))

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Abstract

A hybrid combination between Differential Evolution (DE) and a local search procedure was used for the protein structure prediction problem. The Face-Centered Cubic lattice model was employed for the protein conformation representation. A Lamarckian combination between the global search of DE and the local search provides better results for obtaining protein conformations with minimal energy under the same number of fitness evaluations in comparison with DE alone. The results were validated with several benchmark protein sequences.

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Acknowledgments

This work was funded by the Ministry of Economy and Competitiveness of Spain (project TIN2013-40981-R), Xunta de Galicia (project GPC ED431B 2016/035), Xunta de Galicia (“Centro singular de investigación de Galicia” accreditation 2016-2019 ED431G/01) and the European Regional Development Fund (ERDF). D. Varela grant has received financial support from the Xunta de Galicia and the European Union (European Social Fund - ESF).

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Authors and Affiliations

  1. Computer Science Department, University of A Coruña, A Coruña, Spain

    Daniel Varela & José Santos

Authors
  1. Daniel Varela
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  2. José Santos
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Correspondence to José Santos .

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Editors and Affiliations

  1. Guangdong University of Technology, Guangzhou, China

    Derong Liu

  2. Guangdong University of Technology, Guangzhou, China

    Shengli Xie

  3. South China University of Technology, Guangzhou, China

    Yuanqing Li

  4. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Dongbin Zhao

  5. King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    El-Sayed M. El-Alfy

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Varela, D., Santos, J. (2017). A Hybrid Evolutionary Algorithm for Protein Structure Prediction Using the Face-Centered Cubic Lattice Model. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10634. Springer, Cham. https://doi.org/10.1007/978-3-319-70087-8_65

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  • DOI: https://doi.org/10.1007/978-3-319-70087-8_65

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70086-1

  • Online ISBN: 978-3-319-70087-8

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