利用 MELD×MD 预测蛋白质二聚体结构。
Predicting Protein Dimer Structures Using MELD × MD.
机构信息
Laufer Center for Physical and Quantitative Biology , Stony Brook University , Stony Brook , New York 11794-5252 , United States.
Department of Applied Mathematics and Statistics , Stony Brook University , Stony Brook , New York 11794-3600 , United States.
出版信息
J Chem Theory Comput. 2019 May 14;15(5):3381-3389. doi: 10.1021/acs.jctc.8b01208. Epub 2019 Apr 5.
Abstract
It is challenging to predict the docked conformations of two proteins. Current methods are susceptible to errors from treating proteins as rigid bodies and from an inability to compute relative Boltzmann populations of different docked conformations. Here, we show that by using the ClusPro server as a front end to generate possible protein-protein contacts, and using Modeling Employing Limited Data (MELD) accelerated molecular dynamics (MELD × MD) as a back end for atomistic simulations, we can find 16/20 native dimer structures of small proteins as those having the lowest free energy, starting from good-bound-backbone structures. We show that atomistic MD free energies can be used to identify native protein dimer structures.
摘要
预测两个蛋白质的对接构象具有挑战性。当前的方法容易受到将蛋白质视为刚体以及无法计算不同对接构象的相对玻尔兹曼种群的错误的影响。在这里，我们表明，通过使用 ClusPro 服务器作为生成可能的蛋白质-蛋白质接触的前端，并使用使用有限数据的建模（MELD）加速分子动力学（MELD×MD）作为原子模拟的后端，我们可以从良好的结合骨架结构开始，找到 20 个小分子蛋白质中的 16 个天然二聚体结构，这些结构具有最低的自由能。我们表明，原子 MD 自由能可用于鉴定天然蛋白质二聚体结构。
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