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计算机程序Jamsek结合统计和立体化学规则来预测蛋白质二级结构。

Computer program Jamsek combining statistical and stereochemical rules for the prediction of protein secondary structure.

作者信息

Mrázek J, Kypr J

机构信息

Institute of Biophysics, Czechoslovak Academy of Sciences, Brno.

出版信息

Comput Appl Biosci. 1988 Apr;4(2):297-302. doi: 10.1093/bioinformatics/4.2.297.

DOI:10.1093/bioinformatics/4.2.297
PMID:3167604
Abstract

This article briefly describes our program Jamsek written in FORTRAN for an ICL 2950/10 computer. Jamsek combines statistical and stereochemical rules most frequently encountered in literature to predict protein secondary structure from its sequence, into a single algorithm. The composite algorithm does not work better than the best existing single algorithms of Garnier et al. (J. Mol. Biol., 120, 97-120, 1978) or Lim (J. Mol. Biol., 88, 873-894, 1974) if percentage of residues with a correctly predicted secondary structure is taken as a criterion. However, it is fairly reliable in predicting the total amount of alpha-helices and beta-sheets in proteins, the secondary structure of highly ordered proteins or their parts and identification of long alpha-helices. It surpasses the previous algorithms by providing a possibility to make a notion about confidence of the prediction of the particular secondary structure elements thanks to the simultaneous availability of four independent predictions of the secondary structure and other relevant data (hydrophobic profile and helical wheel representation). The main body of this article is devoted to a demonstration that output data of Jamsek can simply be used for the prediction of protein topological class, identification of globular proteins containing hydrophobic alpha-helices and, as an auxiliary means, to distinguish between protein coding and non-coding nucleotide sequences.

摘要

本文简要介绍了我们用FORTRAN语言为ICL 2950/10计算机编写的程序Jamsek。Jamsek将文献中最常遇到的统计和立体化学规则结合起来,以便从蛋白质序列预测其二级结构,并将其整合到一个单一算法中。如果将正确预测二级结构的残基百分比作为标准,那么这种复合算法并不比Garnier等人(《分子生物学杂志》,120卷,97 - 120页,1978年)或Lim(《分子生物学杂志》,88卷,873 - 894页,1974年)现有的最佳单一算法效果更好。然而,在预测蛋白质中α螺旋和β折叠的总量、高度有序蛋白质或其部分的二级结构以及识别长α螺旋方面,它相当可靠。由于可以同时获得二级结构的四个独立预测结果以及其他相关数据(疏水分布图和螺旋轮表示),它为人们了解特定二级结构元件预测的可信度提供了可能,从而超越了先前的算法。本文的主体部分致力于证明Jamsek的输出数据可简单用于预测蛋白质拓扑类别、识别含有疏水α螺旋的球状蛋白质,并作为一种辅助手段来区分蛋白质编码和非编码核苷酸序列。

相似文献

1
Computer program Jamsek combining statistical and stereochemical rules for the prediction of protein secondary structure.计算机程序Jamsek结合统计和立体化学规则来预测蛋白质二级结构。
Comput Appl Biosci. 1988 Apr;4(2):297-302. doi: 10.1093/bioinformatics/4.2.297.
2
Prediction of surface and interior regions in proteins--Part II: Predicting secondary structure in regions bound by surface exposed regions.
Pept Res. 1991 Nov-Dec;4(6):355-63.
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A simple method for predicting the secondary structure of globular proteins: implications and accuracy.
Comput Appl Biosci. 1988 Aug;4(3):357-65. doi: 10.1093/bioinformatics/4.3.357.
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A secondary structure evaluation of peptides based on statistics and heuristic rules.
Comput Methods Programs Biomed. 1991 Jan;34(1):9-15. doi: 10.1016/0169-2607(91)90077-7.
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Protein secondary structure prediction using logic-based machine learning.基于逻辑的机器学习进行蛋白质二级结构预测。
Protein Eng. 1992 Oct;5(7):647-57. doi: 10.1093/protein/5.7.647.
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How good are predictions of protein secondary structure?蛋白质二级结构的预测准确性如何?
FEBS Lett. 1983 May 8;155(2):179-82. doi: 10.1016/0014-5793(82)80597-8.
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Evaluation of secondary structure predictions in proteins.蛋白质二级结构预测的评估
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Prediction of protein secondary structure and active sites using the alignment of homologous sequences.利用同源序列比对预测蛋白质二级结构和活性位点。
J Mol Biol. 1987 Jun 20;195(4):957-61. doi: 10.1016/0022-2836(87)90501-8.
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Protein topology prediction through constraint-based search and the evaluation of topological folding rules.通过基于约束的搜索和拓扑折叠规则评估进行蛋白质拓扑预测。
Protein Eng. 1991 Oct;4(7):751-60. doi: 10.1093/protein/4.7.751.
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A simple method for predicting transmembrane alpha helices with better accuracy.一种预测跨膜α螺旋的简单方法,其准确性更高。
Protein Eng. 1999 Jul;12(7):557-61. doi: 10.1093/protein/12.7.557.

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