Center for Bioinformatics, Saarland University, Saarbruecken, Germany.
Comput Biol Chem. 2011 Apr;35(2):96-107. doi: 10.1016/j.compbiolchem.2011.03.002. Epub 2011 Mar 30.
Several computational methods exist for the identification of transmembrane beta barrel proteins (TMBs) from sequence. Some of these methods also provide the transmembrane (TM) boundaries of the putative TMBs. The aim of this study is to (1) derive the propensities of the TM residues to be exposed to the lipid bilayer and (2) to predict the exposure status (i.e. exposed to the bilayer or hidden in protein structure) of TMB residues. Three novel propensity scales namely, BTMC, BTMI and HTMI were derived for the TMB residues at the hydrophobic core region of the outer membrane (OM), the lipid-water interface regions of the OM, and for the helical membrane proteins (HMPs) residues at the lipid-water interface regions of the inner membrane (IM), respectively. Separate propensity scales were derived for monomeric and functionally oligomeric TMBs. The derived propensities reflect differing physico-chemical properties of the respective membrane bilayer regions and were employed in a computational method for the prediction of the exposure status of TMB residues. Based on the these propensities, the conservation indices and the frequency profile of the residues, the transmembrane residues were classified into buried/exposed with an accuracy of 77.91% and 80.42% for the residues at the membrane core and the interface regions, respectively. The correlation of the derived scales with different physico-chemical properties obtained from the AAIndex database are also discussed. Knowledge about the residue propensities and burial status will be useful in annotating putative TMBs with unknown structure.
有几种计算方法可用于从序列中识别跨膜β桶蛋白(TMB)。其中一些方法还提供了假定 TMB 的跨膜(TM)边界。本研究的目的是:(1)推导 TM 残基暴露于脂质双层的倾向;(2)预测 TMB 残基的暴露状态(即暴露于双层或隐藏在蛋白质结构中)。为此,我们分别为外膜(OM)疏水区的 TMB 残基、OM 的油水界面区的 TMB 残基和内膜(IM)油水界面区的螺旋膜蛋白(HMP)残基,推导了三个新的倾向尺度,即 BTMC、BTMI 和 HTMI。分别为单体和功能寡聚 TMB 推导了单独的倾向尺度。推导的倾向反映了相应膜双层区域不同的物理化学性质,并用于计算方法中以预测 TMB 残基的暴露状态。基于这些倾向、保守指数和残基的频率分布,将跨膜残基分为埋藏/暴露状态,对于膜核心和界面区域的残基,分类的准确性分别为 77.91%和 80.42%。还讨论了推导的尺度与从 AAIndex 数据库获得的不同物理化学性质之间的相关性。关于残基倾向和埋藏状态的知识将有助于注释具有未知结构的假定 TMB。