A new computational approach for real protein folding prediction.

Ben Zhuo Lu, Bao Han Wang, Wei Zu Chen, Cun Xin Wang
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引用次数: 7

Abstract

An effective and fast minimization approach is proposed for the prediction of protein folding, in which the 'relative entropy' is used as a minimization function and the off-lattice model is used. In this approach, we only use the information of distances between the consecutive Calpha atoms along the peptide chain and a generalized form of the contact potential for 20 types of amino acids. Tests of the algorithm are performed on the real proteins. The root mean square deviations of the structures of eight folded target proteins versus the native structures are in a reasonable range. In principle, this method is an improvement on the energy minimization approach.

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一种新的蛋白质折叠预测计算方法。
提出了一种有效、快速的蛋白质折叠预测最小化方法,该方法将“相对熵”作为最小化函数,并采用离晶格模型。在这种方法中,我们只使用沿肽链连续的α原子之间的距离信息和20种氨基酸的一般形式的接触势。该算法在实际蛋白质上进行了测试。8种折叠靶蛋白的结构与天然结构的均方根偏差均在合理范围内。原则上,该方法是对能量最小化方法的改进。
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