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An updated geometric build-up algorithm for solving the molecular distance geometry problems with sparse distance data

机译:一种更新的几何构造算法,可解决稀疏距离数据中的分子距离几何问题

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摘要

An updated geometric build-up algorithm is developed for solving the molecular distance geometry problem with a sparse set of inter-atomic distances. Different from the general geometric build-up algorithm, the updated algorithm recomputes the coordinates of the base atoms whenever necessary and possible. In this way, the errors introduced in solving the algebraic equations for the determination of the coordinates of the atoms are controlled in the intermediate computational steps. The method for re-computing the coordinates of the base atoms based on the estimation on the root-mean-square deviation (RMSD) is described. The results of applying the updated algorithm to a set of protein structure problems are presented. In many cases, the updated algorithm solves the problems with high accuracy when the results of the general algorithm are inadequate.
机译:开发了一种更新的几何构造算法,用于解决稀疏的原子间距离集的分子距离几何问题。与一般的几何构造算法不同,更新的算法会在必要和可能的情况下重新计算基本原子的坐标。这样,在中间计算步骤中控制了在求解代数方程式以确定原子坐标时引入的误差。描述了基于对均方根偏差(RMSD)的估计重新计算基础原子坐标的方法。提出了将更新的算法应用于一组蛋白质结构问题的结果。在许多情况下,当通用算法的结果不足时,更新后的算法可以高精度地解决问题。

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