https://scholars.lib.ntu.edu.tw/handle/123456789/65225
標題: | Bioinformatics Approaches for Disulfide Connectivity Prediction | 作者: | Tsai, Chi-Hung Chan, Chen-Hsiung Chen, Bo-Juen Kao, Cheng-Yan Liu, Hsuan-Liang Hsu, Jyh-Ping |
關鍵字: | Bioinformatics; Conformational space; Disulfide connectivity; Molecular simulation; Protein engineering; Protein folding | 公開日期: | 2007 | 卷: | 8 | 期: | 3 | 起(迄)頁: | 243-260 | 來源出版物: | Current Protein and Peptide Science | 摘要: | Protein structure prediction with computational methods has gained much attention in the research fields of protein engineering and protein folding studies. Due to the vastness of conformational space, one of the major tasks is to restrain the flexibility of protein structure and reduce the search space. Many studies have revealed that, with the information of disulfide connectivity available, the search in conformational space can be dramatically reduced and lead to significant improvements in the prediction accuracy. As a result, predicting disulfide connectivity using bioinformatics approaches is of great interest nowadays. In this mini-review, the prediction of disulfide connectivity in proteins will be discussed in four aspects: (1) how the problem formulated and the computational techniques used in the literatures; (2) the effects of the features adopted to encode the information and the biological meanings implied; (3) the problems encountered and limitations of disulfide connectivity prediction; and (4) the practical usages of predicted disulfide bond information in molecular simulation and the prospects in the future. © 2007 Bentham Science Publishers Ltd. |
URI: | http://ntur.lib.ntu.edu.tw//handle/246246/89995 https://www.scopus.com/inward/record.uri?eid=2-s2.0-34250811981&doi=10.2174%2f138920307780831848&partnerID=40&md5=5f294ea50eafc4860791a57cd3c9e818 |
ISSN: | 13892037 | DOI: | 10.2174/138920307780831848 | SDG/關鍵字: | amylase; bacterial toxin; cysteine; cytoglobin; disulfide; glutaredoxin; glutathione reductase; neuroglobin; peroxidase; ribonuclease A; superoxide dismutase; urokinase; accuracy; amino acid sequence; artificial neural network; Bacillus; bacterial virulence; bioinformatics; classification algorithm; computer prediction; computer program; disulfide bond; human; information processing; molecular model; nonhuman; oxidation reduction state; oxidative stress; protein conformation; protein engineering; protein expression; protein folding; protein function; protein secondary structure; protein stability; protein structure; Pseudoalteromonas; review; sequence alignment; support vector machine; Amino Acid Sequence; Computational Biology; Computer Simulation; Cysteine; Disulfides; Drug Stability; Humans; Hydrogen Bonding; Models, Molecular; Molecular Conformation; Protein Folding; Proteins; Urinary Plasminogen Activator |
顯示於: | 化學工程學系 |
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