Qin Sanbo, Hicks Alan, Dey Souvik, Prasad Ramesh, Zhou Huan-Xiang
Department of Chemistry, University of Illinois at Chicago, Chicago, IL 60607, USA.
Department of Physics, University of Illinois at Chicago, Chicago, IL 60607, USA.
Membranes (Basel). 2022 Aug 11;12(8):773. doi: 10.3390/membranes12080773.
The functional processes of many proteins involve the association of their intrinsically disordered regions (IDRs) with acidic membranes. We have identified the membrane-association characteristics of IDRs using extensive molecular dynamics (MD) simulations and validated them with NMR spectroscopy. These studies have led to not only deep insight into functional mechanisms of IDRs but also to intimate knowledge regarding the sequence determinants of membrane-association propensities. Here we turned this knowledge into a web server called ReSMAP, for predicting the residue-specific membrane-association propensities from IDR sequences. The membrane-association propensities are calculated from a sequence-based partition function, trained on the MD simulation results of seven IDRs. Robustness of the prediction is demonstrated by leaving one IDR out of the training set. We anticipate there will be many applications for the ReSMAP web server, including rapid screening of IDR sequences for membrane association.
许多蛋白质的功能过程涉及到其内在无序区域(IDR)与酸性膜的结合。我们通过广泛的分子动力学(MD)模拟确定了IDR的膜结合特性,并用核磁共振光谱对其进行了验证。这些研究不仅使我们对IDR的功能机制有了深入了解,还让我们对膜结合倾向的序列决定因素有了详尽认识。在此,我们将这些知识转化为一个名为ReSMAP的网络服务器,用于从IDR序列预测残基特异性的膜结合倾向。膜结合倾向是根据基于序列的配分函数计算得出的,该函数是基于七个IDR的MD模拟结果进行训练的。通过将一个IDR排除在训练集之外,证明了预测的稳健性。我们预计ReSMAP网络服务器将有许多应用,包括快速筛选与膜结合的IDR序列。