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Refinement of F-Actin Model against Fiber Diffraction Data by Long-Range Normal Modes

机译:远距离法向模对光纤衍射数据的F-Actin模型的改进

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摘要

The atomic model of F-actin was refined against fiber diffraction data using long-range normal modes as adjustable parameters to account for the collective long-range filamentous deformations. To determine the effect of long-range deformations on the refinement, each of the four domains of G-actin was treated as a rigid body. It was found that among all modes, the bending modes make the most significant contributions to the improvement of the refinement. Inclusion of only 7–9 bending modes as adjustable parameters yielded a lowest R-factor of 6.3%. These results demonstrate that employing normal modes as refinement parameters has the advantage of using a small number of adjustable parameters to achieve a good fitting efficiency. Such a refinement procedure may therefore prevent the refinement from overfitting the structural model. More importantly, the results of this study demonstrate that, for any fiber diffraction data, a substantial amount of refinement error is due to long-range deformations, especially the bending, of the filaments. The effects of these intrinsic deformations cannot be easily compensated for by adjusting local structural parameters, and must be properly accounted for in the refinement to achieve improved fit of refined models with experimental diffraction data.
机译:F-肌动蛋白的原子模型针对纤维衍射数据使用远程正常模式作为可调节参数进行细化,以说明集体的远程丝状变形。为了确定远距离变形对细化的影响,将G-肌动蛋白的四个结构域中的每一个均视为刚体。已经发现,在所有模式中,弯曲模式对改进细化做出了最重要的贡献。仅包含7–9个弯曲模式作为可调整参数可产生6.3%的最低R系数。这些结果表明,采用正常模式作为细化参数具有使用少量可调参数来实现良好拟合效率的优势。因此,这种细化过程可以防止细化过度拟合结构模型。更重要的是,这项研究的结果表明,对于任何纤维衍射数据,大量的细化误差归因于长丝的长期变形,尤其是弯曲。这些固有变形的影响无法通过调整局部结构参数轻松补偿,必须在优化中适当考虑,以提高改进的模型与实验衍射数据的拟合度。

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