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首页> 外文期刊>Journal of Bioinformatics and Computational Biology >CHARACTERIZING THE SPACE OF INTERATOMIC DISTANCE DISTRIBUTION FUNCTIONS CONSISTENT WITH SOLUTION SCATTERING DATA
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CHARACTERIZING THE SPACE OF INTERATOMIC DISTANCE DISTRIBUTION FUNCTIONS CONSISTENT WITH SOLUTION SCATTERING DATA

机译：表征与溶液散射数据一致的原子间距分布函数的空间

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Scattering of neutrons and X-rays from molecules in solution offers alternativenapproaches to the study of a wide range of macromolecular structures in their solutionnstate without crystallization. We study one part of the problem of elucidatingnthree-dimensional structure from solution scattering data, determining the distributionnof interatomic distances, P(r), where r is the distance between two atoms in the proteinnmolecule. This problem is known to be ill-conditioned: for a single observed diffractionnpattern, there may be many consistent distance distribution functions, and there is a risknof overfitting the observed scattering data. We propose a new approach to avoiding thisnproblem: accepting the validity of multiple alternative P(r) curves rather than seekingna single “best.”nWe place linear constraints to ensure that a computed P(r) is consistent withnthe experimental data. The constraints enforce smoothness in the P(r) curve, ensurenthat the P(r) curve is a probability distribution, and allow for experimental error. Wenuse these constraints to precisely describe the space of all consistent P(r) curves as anpolytope of histogram values or Fourier coefficients. We develop a linear programmingn∗Corresponding author.n315n316 P. A. Kavathekar et al.napproach to sampling the space of consistent, realistic P(r) curves. On both experimentalnand simulated scattering data, our approach efficiently generates ensembles of suchncurves that display substantial diversity
机译：溶液中分子对中子和X射线的散射为研究大分子结构处于溶液状态而不发生结晶提供了替代方法。我们从溶液散射数据研究三维结构问题的一部分，确定原子间距离的分布n P（r），其中r是蛋白分子中两个原子之间的距离。已知该问题是病态的：对于单个观察到的衍射图样，可能存在许多一致的距离分布函数，并且存在过拟合观察到的散射数据的风险。我们提出了一种避免此问题的新方法：接受多个替代P（r）曲线的有效性，而不是寻求单个“最佳”。n我们放置线性约束以确保计算的P（r）与实验数据一致。约束条件强制P（r）曲线保持平滑，确保P（r）曲线是概率分布，并考虑到实验误差。利用这些约束条件，可以将所有一致的P（r）曲线的空间精确地描述为直方图值或傅立叶系数的对角线。我们开发了线性规划程序n *通讯作者。n315n316 P. A. Kavathekar等人napproach用来采样一致，逼真的P（r）曲线的空间。在实验和模拟散射数据上，我们的方法都可以有效地生成这样的曲线集合，从而显示出很大的多样性

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