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On suitable orders for discretizing Molecular Distance Geometry problems related to protein side chains

机译:在适当的顺序上离散化与蛋白质侧链有关的分子距离几何问题

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Proteins are important molecules that are widely studied in biology. Their three-dimensional conformations can give clues about their function, however an optimal methodology for the identification of such conformations has not been found yet. Experiments of Nuclear Magnetic Resonance (NMR) are able to estimate distances between some pairs of atoms forming the protein, and the problem of identifying the possible conformations satisfying the available distance constraints is known in the scientific literature as the Molecular Distance Geometry Problem (MDGP). Since some years, some of us have been working on a suitable discretization for the MDGP and on an efficient Branch & Prune (BP) algorithm which is based on a tree search. In order to perform this discretization, however, some assumptions need to be satisfied. We recently hand-crafted a special order for protein backbone atoms which allows us to discretize all MDGPs concerning backbones. In this paper, we do the same for the side chains of some amino acids. Our computational experiments show that the inclusion of the side chain information allows to improve the performances of the BP algorithm.
机译:蛋白质是生物学上广泛研究的重要分子。它们的三维构象可以提供有关其功能的线索,但是尚未找到用于鉴定此类构象的最佳方法。核磁共振(NMR)实验能够估算形成蛋白质的几对原子之间的距离,而确定满足可用距离限制的可能构象的问题在科学文献中称为分子距离几何问题(MDGP) 。几年以来,我们中的一些人一直在为MDGP进行合适的离散化,以及基于树搜索的高效Branch&Prune(BP)算法。但是,为了执行这种离散化,需要满足一些假设。最近,我们为蛋白质骨架原子手工制作了一个特殊订单,使我们能够离散化所有与骨架有关的MDGP。在本文中,我们对某些氨基酸的侧链进行了相同的处理。我们的计算实验表明,包含侧链信息可以改善BP算法的性能。

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