本頁只刊出中文翻譯與中文說明；英文原文請見下方原文連結。
原文連結
論文資訊
- 類型：已發表論文
- 日期：2021-11-10
摘要
More than a hundred 蛋白質s in yeast reversibly aggregate and phase-separate in response to various stressors, such as nutrient depletion and heat shock. We know little about the 蛋白質 sequence and structural features behind this ability, which has not been characterized on a proteome-wide level. To identify the distinctive features of aggregation-prone 蛋白質 regions, we apply 機器學習 algorithms to 基因組scale limited proteolysis-mass spectrometry (LiP-MS) data from yeast 蛋白質s. LiP-MS data reveals that 96 蛋白質s show significant structural changes upon heat shock. We find that in these 蛋白質s the propensity to phase separate cannot be solely driven by disordered regions, because their aggregation-prone regions (APRs) are not significantly disordered. Instead, the phase separation of these 蛋白質s requires con
※ 此為已發表論文，全文需透過期刊付費取得