氨基酸残基环境及残基类型预测

Won Kim, W.John Wilbur
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引用次数: 3

摘要

从其线性链的知识来确定蛋白质的结构是解释快速增加的基因序列数据库的重要问题之一,仍然是一个瓶颈。解决这个问题的一种方法已经显示出希望,并给出了一个成功的衡量标准,那就是线程。在这种方法中,不同氨基酸之间的接触能首先由应用于已知结构的统计方法确定。然后将这些接触能量应用于序列,该序列的结构将通过将其穿过各种已知结构并确定每个候选结构的总穿线能量来确定。在所有测试的结构中,产生最低总能量的结构被认为是主要的候选结构。为了支持穿线研究的结果,通常需要额外的资料,因为在这个领域众所周知,所使用的接触电位不够敏感,无法得出明确的结论。在这里,我们研究了这样一个假设,即氨基酸残基的环境被实现为所有这些残基在链上不是局部的,但在空间上足够接近,可以提供预测该残基类型的信息,而这些信息没有充分反映在单个接触能中。我们提出的证据证实了这一假设,并提出了一个高阶的协同性之间的残基,围绕一个给定的残基和他们如何与它相互作用。我们建议将其应用于线程。
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Amino acid residue environments and predictions of residue type

The determination of a protein's structure from the knowledge of its linear chain is one of the important problems that remains as a bottleneck in interpreting the rapidly increasing repository of genetic sequence data. One approach to this problem that has shown promise and given a measure of success is threading. In this approach contact energies between different amino acids are first determined by statistical methods applied to known structures. These contact energies are then applied to a sequence whose structure is to be determined by threading it through various known structures and determining the total threading energy for each candidate structure. That structure that yields the lowest total energy is then considered the leading candidate among all the structures tested. Additional information is often needed in order to support the results of threading studies, as it is well known in the field that the contact potentials used are not sufficiently sensitive to allow definitive conclusions. Here, we investigate the hypothesis that the environment of an amino acid residue realized as all those residues not local to it on the chain but sufficiently close spatially can supply information predictive of the type of that residue that is not adequately reflected in the individual contact energies. We present evidence that confirms this hypothesis and suggests a high order cooperativity between the residues that surround a given residue and how they interact with it. We suggest a possible application to threading.

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Instructions to authors Author Index Keyword Index Volume contents New molecular surface-based 3D-QSAR method using Kohonen neural network and 3-way PLS
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