Center for Bioinformatics and Quantitative Biology and Richard and Loan Hill Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL, USA.
Computational Biology Research Lab and Department of Computing, National University of Computer and Emerging Sciences, Islamabad, Pakistan.
Methods Mol Biol. 2023;2627:321-328. doi: 10.1007/978-1-0716-2974-1_17.
β-barrel membrane proteins (βMPs), found in the outer membrane of gram-negative bacteria, mitochondria, and chloroplasts, play important roles in membrane anchoring, pore formation, and enzyme activities. However, it is often difficult to determine their structures experimentally, and the knowledge of their structures is currently limited. We have developed a method to predict the 3D architectures of βMPs. We can accurately construct transmembrane domains of βMPs by predicting their strand registers, from which full 3D atomic structures are derived. Using 3D Beta-barrel Membrane Protein Predictor (3D-BMPP), we can further accurately model the extended beta barrels and loops in non-TM regions with overall greater structure prediction coverage. 3DBMPP is a general technique that can be applied to protein families with limited sequences as well as proteins with novel folds. Applications of 3DBMPP can be broadly applied to genome-wide βMPs structure prediction.
β-桶膜蛋白（βMPs）存在于革兰氏阴性菌的外膜、线粒体和叶绿体中，在膜锚定、孔形成和酶活性中发挥重要作用。然而，βMPs 的结构通常很难通过实验确定，目前对其结构的了解也很有限。我们开发了一种预测 βMPs 三维结构的方法。我们可以通过预测其链寄存器来准确构建 βMPs 的跨膜结构域，由此可以推导出完整的三维原子结构。使用 3D Beta-barrel Membrane Protein Predictor（3D-BMPP），我们可以进一步准确地模拟非 TM 区域中的扩展β桶和环，从而具有更高的整体结构预测覆盖率。3DBMPP 是一种通用技术，适用于序列有限的蛋白质家族以及具有新颖折叠的蛋白质。3DBMPP 的应用可以广泛应用于全基因组 βMPs 结构预测。
