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Fluctuations of backbone torsion angles obtained from NMR-determined structures and their prediction.

机译:由NMR确定的结构获得的主链扭转角的波动及其预测。

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Protein molecules exhibit varying degrees of flexibility throughout their three-dimensional structures. Protein structural flexibility is often characterized by fluctuations in the Cartesian coordinate space. On the other hand, the protein backbone can be mostly defined by two torsion angles varphi and psi only. We introduce a new flexibility descriptor, backbone torsion-angle fluctuation derived from the variation of backbone torsion angles from different NMR models. The torsion-angle fluctuations correlate with mean-squared spatial fluctuations derived from the same collection of NMR models. We developed a neural-network based real-value predictor based on sequence information only. The predictor achieved ten-fold cross-validated correlation coefficients of 0.59 and 0.60, and mean absolute errors of 22.7 degrees and 24.3 degrees for the angle fluctuation of varphi and psi, respectively. This predictor is expected to be useful for function prediction and protein structure prediction when predicted torsion angles are used as restraints. Both sequence- and structure-based prediction of torsion-angle fluctuation will be available at http://sparks.informatics.iupui.edu within the SPINE-X package.
机译:蛋白质分子在其三维结构中表现出不同程度的柔韧性。蛋白质结构的灵活性通常以笛卡尔坐标空间的波动为特征。另一方面,蛋白质骨架主要只能由两个扭转角varphi和psi定义。我们引入了一种新的柔性描述符,即从不同N​​MR模型的主干扭转角的变化中得出的主干扭转角波动。扭转角波动与从相同的NMR模型集合得出的均方空间波动相关。我们仅基于序列信息开发了基于神经网络的实值预测器。该预测器获得了十倍的交叉验证相关系数,分别为0.59和0.60,并且对于varphi和psi的角度波动,平均绝对误差分别为22.7度和24.3度。当将预测的扭转角用作约束时,预计该预测器可用于功能预测和蛋白质结构预测。基于序列和基于结构的扭转角波动预测都可以在SPINE-X软件包中的http://sparks.informatics.iupui.edu上获得。

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