Intrinsically disordered proteins (IDPs) and regions (IDRs) constitute over 50% of the eukaryotic proteome and exhibit dynamic conformational ensembles rather than adopting a single stable structure. Unlike structured proteins, where short- and long-range interactions define a singular 3D folded structure, IDP/Rs rely on complex fluctuation between the ensemble of conformations to perform their biological functions. Understanding the link between IDPs’ amino acid sequence and these structural ensembles’ statistical properties is critical to elucidate their roles in cellular processes. Our studies focus on neurofilament (NF) proteins, key neuronal cytoskeleton components containing extensive IDRs. We investigate the molecular mechanisms that govern their function by examining their behavior across multiple length scales, from nanoscopic to macroscopic. Employing small-angle X-ray scattering, time-resolved spectroscopy, electron microscopy, and coarse-grained polymer physics models, we successfully approximate the structural ensembles of NFs. Our results reveal that sequence-specific motifs and contextual factors are essential for fully capturing the conformational complexity of these proteins in solution. Motivated by clinical studies linking point-mutations in NFL’s IDR tail domain to Charcot-Marie-Tooth (CMT) disease, we will show how such mutations compact NFL hydrogel networks, disrupt nematic order, and reduce water retention. Our findings demonstrate the utility of advanced statistical physics, bioinformatics, and recently developed deep-learning models in predicting the ensemble behavior of IDPs and highlight their potential for modeling their functions and dysfunctions, particularly in the context of neurodegenerative diseases.
Roy Beck (Sun,) studied this question.