Harmony Search Algorithms For Ab Initio Protein Tertiary Structure Prediction
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Date
2011-02
Authors
Abual-Rub, Mohammed Said Saleh
Journal Title
Journal ISSN
Volume Title
Publisher
Universiti Sains Malaysia
Abstract
Predicting the tertiary structure of proteins from their linear sequence is really a big challenge
in biology. This thesis considers the ab initio protein tertiary structure prediction. The
Harmony Search Algorithm (HSA) has been adapted for the protein structure prediction by
modeling the problem as an optimization problem. HSA has obtained feasible solutions but not
as magnificent as those reported in the literature. However, some shortcomings were identified
and addressed by proposing an Adaptive Harmony Search Algorithm (AHSA) and a Hybrid
Harmony Search Algorithm (HHSA). The AHSA introduces a new scheme for controlling
the two main parameters of HSA, i.e. Pitch Adjustment Rate (PAR) and Harmony Memory
Consideration Rate (HMCR), suitable for the Protein Structure Prediction Problem (PSPP).
Experiments on two popular benchmarks namely ‘Met-enkephalin’ and ‘1CRN’ has been performed.
The experimental results have proved that both AHSA and HHSA have improved the
overall performance of ab initio protein tertiary structure prediction. Both AHSA and HHSA
have converged the lowest energy of the given proteins, and their results have outperformed
some of the lowest energies recorded by some state-of-the-art algorithms. Moreover, two new
global optimal energy values of the the ‘Met-enkephalin’ protein has been recorded by both
AHSA and HHSA based on ECEPP/3 and ECEPP/2 force fields with w = 180 .
Description
Keywords
Harmony Search Algorithms , Ab Initio Protein