The resonant recognition model (RRM) predicts amino acid residues in highly conserved regions of the hormone prolactin (PRL)
The resonant recognition model (RRM) predicts amino acid residues in highly conserved regions of the hormone prolactin (PRL)
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DOI：
10.1016/s0301-4622(00)00109-5
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发表时间：
2000-04-14
影响因子：
3.8
通讯作者：
Cosic, I
中科院分区：
文献类型：
--
作者：
de Trad, CH;Fang, Q;Cosic, I
共振识别模型（RRM）是一种将蛋白质序列视为离散信号的模型。以前已经表明，这种信号中的某些周期性（频率）影响蛋白质的生物学功能。RRM被用来确定催乳素（PRL）激素的特征频率，并确定氨基酸（“热点”）主要有助于这些频率，从而提出主要有助于生物功能。预测的“热点”氨基酸Phe-19、Ser-26、Ser-33、Phe-37、Phe-40、Gly-47、Gly-49、Phe-50、Ser-61、Gly-129、Arg-176、Arg-177、Cys-191和Arg-192存在于PRL的高度保守的氨基末端和C末端区域。我们的预测同意与以前的实验测试的残基通过定点诱变和光亲和标记。(C)2000 Elsevier Science B. V.保留所有权利。
The resonant recognition model (RRM) is a model which treats the protein sequence as a discrete signal. It has been shown previously that certain periodicities (frequencies) in this signal characterise protein biological function. The RRM was employed to determine the characteristic frequencies of the hormone prolactin (PRL), and to identify amino acids ('hot spots') mostly contributing to these frequencies and thus proposed to mostly contribute to the biological function. The predicted 'hot spot' amino acids, Phe-19, Ser-26, Ser-33, Phe-37, Phe-40, Gly-47, Gly-49, Phe-50, Ser-61, Gly-129, Arg-176, Arg-177, Cys-191 and Arg-192 are found in the highly conserved amino-terminal and C-terminus regions of PRL. Our predictions agree with previous experimentally tested residues by site-direct mutagenesis and photoaffinity labelling. (C) 2000 Elsevier Science B.V. All rights reserved.