Kitsas Ilias K, Hadjileontiadis Leontios J, Panas Stavros M
Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki GR-54124, Greece.
Comput Biol Med. 2008 Aug;38(8):867-80. doi: 10.1016/j.compbiomed.2008.05.003. Epub 2008 Jun 30.
Prediction of the transmembrane (TM) helices is important in the study of membrane proteins. A novel method to predict the location and length of both single and multiple TM helices in human proteins is presented. The proposed method is based on a combination of hydrophobicity and higher-order statistics, resulting in a TM prediction tool, namely K(4)HTM. A training dataset of 117 human single TM proteins and two test-datasets containing 499 and 484 human single and multiple TM proteins, respectively, were drawn from the SWISS-PROT public database and used for the optimisation and evaluation of K(4)HTM. Validation results showed that K(4)HTM correctly predicts the entire topology for 99.68% and 93.08% of the sequences in the single and multiple test-datasets, respectively. These results compare favourably with existing methods, such as SPLIT4, TMHMM2, WAVETM and SOSUI, constituting an alternative approach to the TM helix prediction problem.
跨膜（TM）螺旋的预测在膜蛋白研究中至关重要。本文提出了一种预测人类蛋白质中单个和多个TM螺旋的位置及长度的新方法。该方法基于疏水性和高阶统计量的结合，产生了一种TM预测工具，即K(4)HTM。从SWISS-PROT公共数据库中提取了一个包含117个人类单TM蛋白的训练数据集以及两个分别包含499个和484个人类单TM和多TM蛋白的测试数据集，用于K(4)HTM的优化和评估。验证结果表明，K(4)HTM分别正确预测了单测试数据集和多测试数据集中99.68%和93.08%的序列的完整拓扑结构。这些结果与现有方法（如SPLIT4、TMHMM2、WAVETM和SOSUI）相比具有优势，构成了一种解决TM螺旋预测问题的替代方法。
