Interactions between their transmembrane domains (TMDs) frequently support the assembly of single-pass membrane proteins to non-covalent complexes. Yet, the TMD-TMD interactome remains largely uncharted. With a view to predicting homotypic TMD-TMD interfaces from primary structure, we performed a systematic analysis of their physical and evolutionary properties. To this end, we generated a dataset of 50 self-interacting TMDs. This dataset contains interfaces of nine TMDs from bitopic human proteins (Ire1, Armcx6, Tie1, ATP1B1, PTPRO, PTPRU, PTPRG, DDR1, and Siglec7) that were experimentally identified here and combined with literature data. We show that interfacial residues of these homotypic TMD-TMD interfaces tend to be more conserved, coevolved and polar than non-interfacial residues. Further, we suggest for the first time that interface positions are deficient in β-branched residues, and likely to be located deep in the hydrophobic core of the membrane. Overrepresentation of the GxxxG motif at interfaces is strong, but that of (small)xxx(small) motifs is weak. The multiplicity of these features and the individual character of TMD-TMD interfaces, as uncovered here, prompted us to train a machine learning algorithm. The resulting prediction method, THOIPA (www.thoipa.org), excels in the prediction of key interface residues from evolutionary sequence data.

它们的跨膜结构域 (TMD) 之间的相互作用经常支持单程膜蛋白组装成非共价复合物。然而，TMD-TMD 相互作用组在很大程度上仍然未知。为了从初级结构预测同型 TMD-TMD 界面，我们对其物理和进化特性进行了系统分析。为此，我们生成了一个包含 50 个自交互 TMD 的数据集。该数据集包含来自双位人类蛋白质（Ire1、Armcx6、Tie1、ATP1B1、PTPRO、PTPRU、PTPRG、DDR1 和 Siglec7）的九个 TMD 的接口，这些接口在此处通过实验确定并与文献数据相结合。我们表明这些同型 TMD-TMD 界面的界面残基比非界面残基更保守、共同进化和极性。更远，我们首次提出界面位置缺乏β-分支残基，并且可能位于膜的疏水核心深处。GxxxG 基序在界面上的过度表达很强，但（小）xxx（小）基序的表达很弱。这些特征的多样性和 TMD-TMD 接口的个性，正如这里所揭示的，促使我们训练机器学习算法。由此产生的预测方法 THIOPA (www.thoipa.org) 在从进化序列数据中预测关键界面残基方面表现出色。这些特征的多样性和 TMD-TMD 接口的个性，正如这里所揭示的，促使我们训练机器学习算法。由此产生的预测方法 THIOPA (www.thoipa.org) 在从进化序列数据中预测关键界面残基方面表现出色。这些特征的多样性和 TMD-TMD 接口的个性，正如这里所揭示的，促使我们训练机器学习算法。由此产生的预测方法 THIOPA (www.thoipa.org) 在从进化序列数据中预测关键界面残基方面表现出色。