Lella Muralikrishna, Mahalakshmi Radhakrishnan
Molecular Biophysics Laboratory, Department of Biological Sciences , Indian Institute of Science Education and Research Bhopal , Bhopal 462066 , India.
J Phys Chem Lett. 2018 Jun 7;9(11):2967-2971. doi: 10.1021/acs.jpclett.8b00953. Epub 2018 May 21.
Membrane protein aggregation is associated with neurodegenerative diseases. Despite remarkable advances to map protein aggregation, molecular elements that drive the structural transition from functional to amyloidogenic β-sheet polymers remain elusive. Here, we report a simple and reliable reverse-mapping method to identify the molecular elements. We validate our approach by obtaining molecular details of aggregation loci of human β-barrel nanopore ion channels that are vital for cell survival. By coupling bottom-up synthesis with time-resolved aggregation kinetics and high-resolution imaging, we identify molecular elements that switch folded channels to polymeric β-rich aggregates. We prove that intrinsic protein aggregation and amyloidogenicity does not depend on total hydrophobicity but on single residue differences in the primary sequence. Our method offers effective strategies for sequence-based design of aggregation inhibitors in biomedicine for neurodegenerative diseases.
膜蛋白聚集与神经退行性疾病相关。尽管在绘制蛋白质聚集图谱方面取得了显著进展,但驱动从功能性向淀粉样β-折叠聚合物结构转变的分子元件仍不清楚。在此,我们报告一种简单可靠的反向映射方法来识别这些分子元件。我们通过获取对细胞存活至关重要的人β-桶状纳米孔离子通道聚集位点的分子细节来验证我们的方法。通过将自下而上的合成与时间分辨聚集动力学和高分辨率成像相结合,我们识别出将折叠通道转变为富含β-折叠聚合物聚集体的分子元件。我们证明,蛋白质的内在聚集和淀粉样变性并不取决于总疏水性,而是取决于一级序列中的单个残基差异。我们的方法为基于序列设计神经退行性疾病生物医学中的聚集抑制剂提供了有效策略。