Terzoli Sara, Tiana Guido
Department of Physics and Center for Complexity and Biosystems, Universitá degli Studi di Milano and INFN, via Celoria 16, Milano 20133, Italy.
J Phys Chem B. 2020 May 21;124(20):4079-4088. doi: 10.1021/acs.jpcb.0c01671. Epub 2020 May 6.
Studying the conformations involved in the dimerization of cadherins is highly relevant to understand the development of tissues and its failure, which is associated with tumors and metastases. Experimental techniques, like X-ray crystallography, can usually report only the most stable conformations, missing minority states that could nonetheless be important for the recognition mechanism. Computer simulations could be a valid complement to the experimental approach. However, standard all-atom protein models in explicit solvent are computationally too demanding to search thoroughly the conformational space of multiple chains composed of several hundreds of amino acids. To reach this goal, we resorted to a coarse-grained model in implicit solvent. The standard problem with this kind of model is to find a realistic potential to describe its interactions. We used coevolutionary information from cadherin alignments, corrected by a statistical potential, to build an interaction potential, which is agnostic about the experimental conformations of the protein. Using this model, we explored the conformational space of multichain systems and validated the results comparing with experimental data. We identified dimeric conformations that are sequence specific and that can be useful to rationalize the mechanism of recognition between cadherins.
研究钙黏着蛋白二聚化所涉及的构象对于理解组织发育及其功能障碍（这与肿瘤和转移相关）具有高度相关性。诸如X射线晶体学等实验技术通常只能报告最稳定的构象，而遗漏了可能对识别机制很重要的少数状态。计算机模拟可以成为实验方法的有效补充。然而，在显式溶剂中的标准全原子蛋白质模型在计算上要求过高，无法彻底搜索由数百个氨基酸组成的多条链的构象空间。为了实现这一目标，我们采用了隐式溶剂中的粗粒度模型。这类模型的标准问题是找到一个现实的势来描述其相互作用。我们利用来自钙黏着蛋白比对的协同进化信息，并通过统计势进行校正，以构建一个相互作用势，该势与蛋白质的实验构象无关。使用这个模型，我们探索了多链系统的构象空间，并与实验数据比较验证了结果。我们确定了具有序列特异性的二聚体构象，这些构象有助于阐明钙黏着蛋白之间的识别机制。
