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Protein structure prediction based on particle swarm optimization and tabu search strategy
BACKGROUND: The stability of protein sequence structure plays an important role in the prevention and treatment of diseases. RESULTS: In this paper, particle swarm optimization and tabu search are combined to propose a new method for protein structure prediction. The experimental results show that:...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9396775/ https://www.ncbi.nlm.nih.gov/pubmed/35999491 http://dx.doi.org/10.1186/s12859-022-04888-4 |
Sumario: | BACKGROUND: The stability of protein sequence structure plays an important role in the prevention and treatment of diseases. RESULTS: In this paper, particle swarm optimization and tabu search are combined to propose a new method for protein structure prediction. The experimental results show that: for four groups of artificial protein sequences with different lengths, this method obtains the lowest potential energy value and stable structure prediction results, and the effect is obviously better than the other two comparison methods. Taking the first group of protein sequences as an example, our method improves the prediction of minimum potential energy by 127% and 7% respectively. CONCLUSIONS: Therefore, the method proposed in this paper is more suitable for the prediction of protein structural stability. |
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