首页> 外文会议>2016 23rd Iranian Conference on Biomedical Engineering and 2016 1st International Iranian Conference on Biomedical Engineering >On the contribution of normal modes of elastic network models in prediction of conformational changes
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On the contribution of normal modes of elastic network models in prediction of conformational changes

机译:关于弹性网络模型的正常模式对构象变化预测的贡献

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Conformational changes of proteins during binding to other biomolecules play a vital role in many biological processes in a living body. There have been a lot of efforts to predict the conformational changes using normal modes of various elastic network models. In all the studies, usually a single or a few lowest modes are considered. In this study, we consider the contribution of all normal modes on the unbound structure of protein to predict the bound form. The results show that low frequency normal modes are not sufficient for describing these motions and there are contributing normal modes even in the high frequency range. The results also indicate that high decaying and low cutoff radii network models show similar behavior in their prediction of the conformational changes.
机译:在与其他生物分子结合期间,蛋白质的构象变化在生物体内的许多生物过程中起着至关重要的作用。已经进行了许多努力来使用各种弹性网络模型的正常模式来预测构象变化。在所有研究中,通常考虑一个或几个最低模式。在这项研究中,我们考虑所有正常模式对蛋白质的未结合结构的贡献,以预测结合形式。结果表明,低频正常模式不足以描述这些运动,即使在高频范围内,也有贡献的正常模式。结果还表明,高衰减和低截止半径网络模型在其构象变化的预测中显示出相似的行为。

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