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Comparative Analysis of Different Evaluation Functions for Protein Structure Prediction Under the HP Model

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Abstract

The HP model for protein structure prediction abstracts the fact that hydrophobicity is a dominant force in the protein folding process. This challenging combinatorial optimization problem has been widely addressed through metaheuristics. The evaluation function is a key component for the success of metaheuristics; the poor discrimination of the conventional evaluation function of the HP model has motivated the proposal of alternative formulations for this component. This comparative analysis inquires into the effectiveness of seven different evaluation functions for the HP model. The degree of discrimination provided by each of the studied functions, their capability to preserve a rank ordering among potential solutions which is consistent with the original objective of the HP model, as well as their effect on the performance of local search methods are analyzed. The obtained results indicate that studying alternative evaluation schemes for the HP model represents a highly valuable direction which merits more attention.

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Authors and Affiliations

  1. Information Technology Laboratory, CINVESTAV-Tamaulipas, Km. 5.5 Carretera Ciudad Victoria-Soto La Marina, 87130, Ciudad Victoria, Tamaulipas, México

    Mario Garza-Fabre, Eduardo Rodriguez-Tello & Gregorio Toscano-Pulido

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  1. Mario Garza-Fabre
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  2. Eduardo Rodriguez-Tello
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  3. Gregorio Toscano-Pulido
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Additional information

This research was partially supported by the National Council of Science and Technology of Mexico (CONACyT) under Grant Nos. 105060 and 99276.

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Garza-Fabre, M., Rodriguez-Tello, E. & Toscano-Pulido, G. Comparative Analysis of Different Evaluation Functions for Protein Structure Prediction Under the HP Model. J. Comput. Sci. Technol. 28, 868–889 (2013). https://doi.org/10.1007/s11390-013-1384-7

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