Abstract

Hydrophobic-Polar model is a simplified representation of Protein Structure Prediction (PSP) problem. However, even with the HP model, the PSP problem remains NP-complete. This work proposes a systematic and problem specific design for operators of the evolutionary program which hybrids with local search hill climbing, to efficiently explore the search space of PSP and thereby obtain an optimum conformation. The proposed algorithm achieves this by incorporating the following novel features: (i) new initialization method which generates only valid individuals with (rather than random) better fitness values; (ii) use of probability-based selection operators that limit the local convergence; (iii) use of secondary structure based mutation operator that makes the structure more closely to the laboratory determined structure; and (iv) incorporating all the above-mentioned features developed a complete two-tier framework. The developed framework builds the protein conformation on the square and triangular lattice. The test has been performed using benchmark sequences, and a comparative evaluation is done with various state-of-the-art algorithms. Moreover, in addition to hypothetical test sequences, we have tested protein sequences deposited in protein database repository. It has been observed that the proposed framework has shown superior performance regarding accuracy (fitness value) and speed (number of generations needed to attain the final conformation). The concepts used to enhance the performance are generic and can be used with any other population-based search algorithm such as genetic algorithm, ant colony optimization, and immune algorithm.

Highlights

  • The Protein Structure Prediction (PSP) problem is one of the major problems in the field of computational biology

  • Due to complexities and limitations of experimental methods, there is a huge gap in the number of reported protein sequences and their structure, and yet only 1% of structures are known for the reported protein sequences [7]

  • Besides exploitation and exploration of search space, we have considered the hybrid of local search with the evolutionary programming (MA(EP+HC))

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Summary

Introduction

The Protein Structure Prediction (PSP) problem is one of the major problems in the field of computational biology. The prediction of the native conformation of protein structure from its amino acid sequence is called PSP problem [1,2,3,4]. Due to complexities and limitations of experimental methods, there is a huge gap in the number of reported protein sequences and their structure, and yet only 1% of structures are known for the reported protein sequences [7]. This calls for a computational solution to the PSP problem

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