Membrane contact probability: An essential and predictive character for the structural and functional studies of membrane proteins.
Membrane contact probability: An essential and predictive character for the structural and functional studies of membrane proteins.
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膜接触概率：膜蛋白结构和功能研究的基本特征和预测特征
DOI：
10.1371/journal.pcbi.1009972
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发表时间：
2022-03
影响因子：
4.3
通讯作者：
中科院分区：
文献类型：
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作者：
膜蛋白的一个独特特征是，其疏水氨基酸的很大一部分暴露在脂双层的疏水核心，而不是嵌入到蛋白质内部，这通常在蛋白质结构和功能预测中没有被明确考虑。在这里，我们提出了一个特征和预测量，膜接触概率(MCP)，来描述给定序列的氨基酸与脂质分子的酰基链直接接触的可能性。我们发现，在表征膜蛋白外表面方面，MCP是对溶剂可及性的补充，并且可以利用从MemProtMD提取的训练数据集，使用基于机器学习的方法对任何给定的序列进行预测，MemProtMD是一个通过分子动力学模拟生成的具有已知结构的膜蛋白的数据库。作为众多潜在应用中的第一个，我们证明了MCP可以用来系统地提高蛋白质接触图和结构的预测精度。蛋白质表面残基的分布在很大程度上取决于周围环境。对于可溶性蛋白质来说，外表面的残基大多是亲水性的，人们用溶剂可及性量来描述和预测这些表面残基。相比之下，对于包埋在脂质双层中的膜蛋白来说，它们的许多表面残基是疏水的和与膜接触的，但还没有一个被广泛接受的量来描述或预测这一特性。在这里，我们提出了一个新的量，称为膜接触概率(MCP)，它可以用来描述和预测蛋白质与膜接触的表面残基。我们还提出了一种基于机器学习的方法，利用基于物理的计算机模拟产生的数据集，从蛋白质序列中预测MCP。我们证明，像MCP这样的量有助于蛋白质结构的预测，我们相信它将在膜蛋白的结构和功能研究中得到广泛的应用。
One of the unique traits of membrane proteins is that a significant fraction of their hydrophobic amino acids is exposed to the hydrophobic core of lipid bilayers rather than being embedded in the protein interior, which is often not explicitly considered in the protein structure and function predictions. Here, we propose a characteristic and predictive quantity, the membrane contact probability (MCP), to describe the likelihood of the amino acids of a given sequence being in direct contact with the acyl chains of lipid molecules. We show that MCP is complementary to solvent accessibility in characterizing the outer surface of membrane proteins, and it can be predicted for any given sequence with a machine learning-based method by utilizing a training dataset extracted from MemProtMD, a database generated from molecular dynamics simulations for the membrane proteins with a known structure. As the first of many potential applications, we demonstrate that MCP can be used to systematically improve the prediction precision of the protein contact maps and structures. The distribution of residues on protein surfaces is largely determined by the surrounding environment. For soluble proteins, most of the residues on the outer surface are hydrophilic, and people use the quantity “solvent accessibility” to describe and predict these surface residues. In contrast, for membrane proteins that are embedded in a lipid bilayer, many of their surface residues are hydrophobic and membrane-contacting, but there is yet a widely-accepted quantity for the description or prediction of this characteristic property. Here, we propose a new quantity termed “membrane contact probability (MCP)”, which can be used to describe and predict the membrane-contacting surface residues of proteins. We also propose a machine learning-based method to predict MCP from protein sequences, utilizing the dataset generated by physics-based computer simulations. We demonstrate that a quantity such as MCP is helpful for protein structure prediction, and we believe that it will find broad applications in the structure and function studies of membrane proteins.
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DOI：
10.1093/bioinformatics/btx781
发表时间：
2018-05-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Adhikari B;Hou J;Cheng J
通讯作者：
Cheng J
影响因子：
3
作者：
Illergård K;Callegari S;Elofsson A
通讯作者：
Elofsson A
影响因子：
5.8
作者：
Dunn, S. D.;Wahl, L. M.;Gloor, G. B.
通讯作者：
Gloor, G. B.
影响因子：
5.5
作者：
de Jong, Djurre H.;Singh, Gurpreet;Marrink, Siewert J.
通讯作者：
Marrink, Siewert J.
影响因子：
15
作者：
Bond PJ;Sansom MS
通讯作者：
Sansom MS