Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794.
Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794;
Proc Natl Acad Sci U S A. 2017 Mar 28;114(13):E2654-E2661. doi: 10.1073/pnas.1620646114. Epub 2017 Mar 14.
Chaperones are protein complexes that help to fold and disaggregate a cell's proteins. It is not understood how four major chaperone systems of work together in proteostasis: the recognition, sorting, folding, and disaggregating of the cell's many different proteins. Here, we model this machine. We combine extensive data on chaperoning, folding, and aggregation rates with expression levels of proteins and chaperones measured at different growth rates. We find that the proteostasis machine recognizes and sorts a client protein based on two biophysical properties of the client's misfolded state (M state): its stability and its kinetic accessibility from its unfolded state (U state). The machine is energy-efficient (the sickest proteins use the most ATP-expensive chaperones), comprehensive (it can handle any type of protein), and economical (the chaperone concentrations are just high enough to keep the whole proteome folded and disaggregated but no higher). The cell needs higher chaperone levels in two situations: fast growth (when protein production rates are high) and very slow growth (to mitigate the effects of protein degradation). This type of model complements experimental knowledge by showing how the various chaperones work together to achieve the broad folding and disaggregation needs of the cell.
伴侣蛋白是帮助折叠和解聚细胞蛋白质的蛋白复合物。目前尚不清楚四个主要伴侣蛋白系统如何协同作用以维持蛋白质稳态:即细胞内多种不同蛋白质的识别、分拣、折叠和解聚。在这里,我们构建了这个机器模型。我们将伴侣蛋白对蛋白质的折叠和聚集的调控作用,以及在不同生长速率下测量到的蛋白质和伴侣蛋白的表达水平等广泛数据结合起来。我们发现,蛋白质稳态机器基于客户蛋白质错误折叠状态(M 态)的两个生物物理特性来识别和分拣客户蛋白质:其稳定性和从未折叠状态(U 态)的动力学可及性。该机器具有高效节能(病态蛋白质使用最昂贵的 ATP 依赖性伴侣蛋白)、全面(可以处理任何类型的蛋白质)和经济(伴侣蛋白浓度仅需高到足以保持整个蛋白质组的折叠和解聚状态,但不会更高)的特点。细胞在两种情况下需要更高的伴侣蛋白水平:快速生长(当蛋白质产生速率较高时)和非常缓慢的生长(以减轻蛋白质降解的影响)。这种类型的模型通过展示各种伴侣蛋白如何协同工作以满足细胞广泛的折叠和解聚需求,补充了实验知识。