Evidence map›Paper›PMID 30116298›Full record

ArticleBioData mining2018

Protein folding prediction in the HP model using ions motion optimization with a greedy algorithm.

Cheng-Hong Yang, Kuo-Chuan Wu, Yu-Shiun Lin, Li-Yeh Chuang, Hsueh-Wei Chang

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Article in BioData mining, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Cheng-Hong Yang1Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan.
Kuo-Chuan Wu1Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan.
Yu-Shiun Lin1Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan.
Li-Yeh Chuang4Department of Chemical Engineering & Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung, Taiwan.
Hsueh-Wei Chang5Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, Taiwan.ORCID 0000-0003-0068-2366

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe function of a protein is determined by its native protein structure. Among many protein prediction methods, the Hydrophobic-Polar (HP) model, an ab initio method, simplifies the protein folding prediction process in order to reduce the prediction complexity.

resultsIn this study, the ions motion optimization (IMO) algorithm was combined with the greedy algorithm (namely IMOG) and implemented to the HP model for the protein folding prediction based on the 2D-triangular-lattice model. Prediction results showed that the integration method IMOG provided a better prediction efficiency in a HP model. Compared to others, our proposed method turned out as superior in its prediction ability and resilience for most of the test sequences. The efficiency of the proposed method was verified by the prediction results. The global search capability and the ability to escape from the local best solution of IMO combined with a local search (greedy algorithm) to the new algorithm IMOG greatly improve the search for the best solution with reliable protein folding prediction.

conclusionOverall, the HP model integrated with IMO and a greedy algorithm as IMOG provides an improved way of protein structure prediction of high stability, high efficiency, and outstanding performance.

Indexed as

Global searchHydrophobic-polar (HP) modelIMOGIon motion optimizationLocal searchProtein folding

Identifiers

PMID30116298
PMCPMC6083565

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