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免疫球蛋白互补决定区(CDRs)的模式。

Patterns in the complementary determining regions of immunoglobulins (CDRs).

作者信息

Lara-Ochoa F, Vargas-Madrazo E, Jimenez-Montano M A, Almagro J C

机构信息

Instituto de Química, UNAM, Mexico.

出版信息

Biosystems. 1994;32(1):1-9. doi: 10.1016/0303-2647(94)90014-0.

Abstract

An analysis of the frequency of use of amino acids on the CDR-1 and CDR-2 of 1500 immunoglobulins showed that the frequencies of amino acids in different positions could be fitted by two types of distribution. For some positions the frequencies were fitted by an inverse power law and for other positions by an exponential distribution. In order to see whether the more frequently used amino acids for specific positions had physicochemical properties or attributes in common, they were clustered using an algorithm normally applied to artificial intelligence problems. It was found that the amino acids in those positions fitted by the inverse power law have similar hydrophobicity and volume, which are commonly attributes of amino acids in structural positions. Thus, if these positions are critical to maintaining the structural features of the CDR domains, the rest of the positions should be either properly involved in the recognition process or irrelevant. The frequencies of amino acids in these recognition positions were fitted by the exponential law, and it was found by the clustering analysis that these amino acids share properties of a more general type, such as capability of forming hydrogen bonds, polarity, etc. This suggests that at least part of the recognition mechanism requires general properties rather than specific amino acids. Amino acids sharing the required attributes for each one of these positions are then used with random frequency.

摘要

对1500种免疫球蛋白的互补决定区-1(CDR-1)和互补决定区-2(CDR-2)上氨基酸使用频率的分析表明,不同位置氨基酸的频率可以用两种分布类型来拟合。对于某些位置,频率用反幂律拟合,而对于其他位置,则用指数分布拟合。为了查看特定位置上更频繁使用的氨基酸是否具有共同的物理化学性质或属性,使用一种通常应用于人工智能问题的算法对它们进行聚类。结果发现,用反幂律拟合的那些位置上的氨基酸具有相似的疏水性和体积,这通常是结构位置上氨基酸的属性。因此,如果这些位置对于维持CDR结构域的结构特征至关重要,那么其余位置要么正确参与识别过程,要么与之无关。这些识别位置上氨基酸的频率用指数定律拟合,通过聚类分析发现这些氨基酸具有更一般类型的属性,如形成氢键的能力、极性等。这表明至少部分识别机制需要一般属性而非特定氨基酸。然后,具有这些位置各自所需属性的氨基酸以随机频率被使用。

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