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An Improved Harmony Search Algorithm for Protein Structure Prediction Using 3D Off-Lattice Model

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 514))

Abstract

Protein structure prediction (PSP) is an important research area in bio-informatics for its immense scope of application in drug design, disease prediction, name a few. Structure prediction of protein based on sequence of amino acids is a NP-hard and multi-modal optimization problem. This paper presents an improved harmony search (ImHS) algorithm to solve the PSP problem based on 3D off lattice model. In the proposed method, the basic harmony search (HS) algorithm combined with dimensional mean based perturbation strategy to avoid premature convergence and enhance the capability of jumping out from the local optima. The experiments are carried out on a set of real protein sequences with different length collected from the Protein Data Bank (PDB) to validate the efficiency of the proposed method. Numerical results show that the ImHS algorithm significantly outperforms compared to other algorithms on protein energy minimization.

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Correspondence to Nanda Dulal Jana .

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Jana, N.D., Sil, J., Das, S. (2017). An Improved Harmony Search Algorithm for Protein Structure Prediction Using 3D Off-Lattice Model. In: Del Ser, J. (eds) Harmony Search Algorithm. ICHSA 2017. Advances in Intelligent Systems and Computing, vol 514. Springer, Singapore. https://doi.org/10.1007/978-981-10-3728-3_30

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  • DOI: https://doi.org/10.1007/978-981-10-3728-3_30

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3727-6

  • Online ISBN: 978-981-10-3728-3

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