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首页> 外文期刊>Journal of Bioinformatics and Computational Biology >Prediction of the exposure status of transmembrane beta barrel residues from protein sequence
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Prediction of the exposure status of transmembrane beta barrel residues from protein sequence

机译：从蛋白质序列预测跨膜β桶残基的暴露状态

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We present BTMX (Beta barrel TransMembrane eXposure), a computational method tonpredict the exposure status (i.e. exposed to the bilayer or hidden in the protein structure)nof transmembrane residues in transmembrane beta barrel proteins (TMBs). BTMXnpredicts the exposure status of known TM residues with an accuracy of 84.2% over 2225nresidues and provides a confidence score for all predictions. Predictions made are in concertnwith the fact that hydrophobic residues tend to be more exposed to the bilayer. Thenbiological relevance of the input parameters is also discussed. The highest predictionnaccuracy is obtained when a sliding window comprising of three residues with similarnCα−Cβ vector orientations is employed. The prediction accuracy of the BTMX methodnon a separate unseen non-redundant test data set is 78.1%. By employing out-pointingnresidues that are exposed to the bilayer, we have identified various physico-chemical propertiesnthat show statistically significant differences between the beta strands located atnthe oligomeric interfaces compared to the non-oligomeric strands. The BTMX web serverngenerates colored, annotated snake-plots as part of the prediction results and is availablenunder the BTMX tab at http://service.bioinformatik.uni-saarland.de/tmx-site/. Exposurenstatus prediction of TMB residues may be useful in 3D structure prediction ofnTMBs
机译：我们介绍了BTMX（Beta桶状跨膜eXposure），一种计算方法可以预测跨膜β桶状蛋白（TMBs）中跨膜残基的暴露状态（即暴露于双层或隐藏在蛋白质结构中）。 BTMXn预测已知TM残留物的暴露状态，相对于2225n个残基的准确度为84.2％，并为所有预测提供可信度得分。做出的预测与疏水残基倾向于更暴露于双层的事实相一致。然后还讨论了输入参数的生物学相关性。当使用包含三个具有相似Cα-Cβ矢量方向的残基的滑动窗口时，可以获得最高的预测精度。 BTMX方法的预测准确性（未单独看到的非冗余测试数据集）为78.1％。通过使用暴露在双层中的外向残基，我们已经鉴定了各种理化性质，与非低聚链相比，它们显示出位于低聚界面的β链之间的统计学显着差异。 BTMX Web服务器生成彩色的带注释的蛇形图作为预测结果的一部分，可在BTMX选项卡下找到，网址为http://service.bioinformatik.uni-saarland.de/tmx-site/。 TMB残基的暴露状态预测可能对nTMB的3D结构预测有用

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