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TMBpro: secondary structure, beta-contact and tertiary structure prediction of transmembrane beta-barrel proteins

机译:TMBpro:跨膜β-桶蛋白的二级结构,β-接触和三级结构预测

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Motivation: Transmembrane beta-barrel (TMB) proteins are embedded in the outer membranes of mitochondria, Gram-negative bacteria and chloroplasts. These proteins perform critical functions, including active ion-transport and passive nutrient intake. Therefore, there is a need for accurate prediction of secondary and tertiary structure of TMB proteins. Traditional homology modeling methods, however, fail on most TMB proteins since very few non-homologous TMB structures have been determined. Yet, because TMB structures conform to specific construction rules that restrict the conformational space drastically, it should be possible for methods that do not depend on target-template homology to be applied successfully. Results: We develop a suite (TMBpro) of specialized predictors for predicting secondary structure (TMBpro-SS), beta-contacts (TMBpro-CON) and tertiary structure (TMBpro-3D) of transmembrane beta-barrel proteins. We compare our results to the recent state-of-the-art predictors transFold and PRED-TMBB using their respective benchmark datasets, and leave-one-out cross-validation. Using the transFold dataset TMBpro predicts secondary structure with perresidue accuracy (Q(2)) of 77.8%, a correlation coefficient of 0.54, and TMBpro predicts beta-contacts with precision of 0.65 and recall of 0.67. Using the PRED-TMBB dataset, TMBpro predicts secondary structure with Q2 of 88.3% and a correlation coefficient of 0.75. All of these performance results exceed previously published results by 4% or more. Working with the PRED-TMBB dataset, TMBpro predicts the tertiary structure of transmembrane segments with RMSD 56.0A for 9 of 14 proteins. For 6 of 14 predictions, the RMSD is 55.0A, with a GDT_TS score greater than 60.0.
机译:动机:跨膜β-桶(TMB)蛋白嵌入线粒体,革兰氏阴性细菌和叶绿体的外膜中。这些蛋白质执行关键功能,包括主动离子转运和被动营养摄入。因此,需要准确预测TMB蛋白的二级和三级结构。然而,由于已经确定了极少数的非同源TMB结构,因此传统的同源建模方法对大多数TMB蛋白均无效。但是,由于TMB结构符合严格限制构象空间的特定构造规则,因此不依赖目标模板同源性的方法应能成功应用。结果:我们开发了一套专门的预测因子(TMBpro),用于预测跨膜β-桶蛋白的二级结构(TMBpro-SS),β-接触(TMBpro-CON)和三级结构(TMBpro-3D)。我们将其结果与最近的最新预测因子transFold和PRED-TMBB进行比较,并使用它们各自的基准数据集,并留出了一次交叉验证。使用transFold数据集,TMBpro预测的残基精度(Q(2))为77.8%,相关系数为0.54,二级结构,TMBpro预测β-接触的精度为0.65,召回率为0.67。使用PRED-TMBB数据集,TMBpro预测二级结构的Q2为88.3%,相关系数为0.75。所有这些性能结果都比以前发布的结果高出4%或更多。使用PRED-TMBB数据集,TMBpro预测14种蛋白质中的9种蛋白质的RMSD 56.0A跨膜片段的三级结构。对于14个预测中的6个,RMSD为55.0A,GDT_TS得分大于60.0。

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