Intramolecular Cohesion of Coils Mediated by Phenylalanine–Glycine Motifs in the Natively Unfolded Domain of a Nucleoporin

The nuclear pore complex (NPC) provides the sole aqueous conduit for macromolecular exchange between the nucleus and the cytoplasm of cells. Its diffusion conduit contains a size-selective gate formed by a family of NPC proteins that feature large, natively unfolded domains with phenylalanine–glycine repeats (FG domains). These domains of nucleoporins play key roles in establishing the NPC permeability barrier, but little is known about their dynamic structure. Here we used molecular modeling and biophysical techniques to characterize the dynamic ensemble of structures of a representative FG domain from the yeast nucleoporin Nup116. The results showed that its FG motifs function as intramolecular cohesion elements that impart order to the FG domain and compact its ensemble of structures into native premolten globular configurations. At the NPC, the FG motifs of nucleoporins may exert this cohesive effect intermolecularly as well as intramolecularly to form a malleable yet cohesive quaternary structure composed of highly flexible polypeptide chains. Dynamic shifts in the equilibrium or competition between intra- and intermolecular FG motif interactions could facilitate the rapid and reversible structural transitions at the NPC conduit needed to accommodate passing karyopherin–cargo complexes of various shapes and sizes while simultaneously maintaining a size-selective gate against protein diffusion

CHANDRA/VLA Follow-up of TeV J2032+4131, the Only Unidentified TeV Gamma-ray Source

The HEGRA Cherenkov telescope array group recently reported a steady and extended unidentified TeV gamma-ray source lying at the outskirts of Cygnus OB2. This is the most massive stellar association known in the Galaxy, estimated to contain ~2600 OB type members alone. It has been previously argued that the large scale shocks and turbulence induced by the multiple interacting supersonic winds from the many young stars in such associations may play a role in accelerating Galactic cosmic rays. Indeed, Cyg OB2 also coincides with the non-variable MeV-GeV range unidentified EGRET source, 3EG 2033+4118. We report on the near-simultaneous follow-up observations of the extended TeV source region with the CHANDRA X-ray Observatory and the Very Large Array (VLA) radio telescope obtained in order to explore this possibility. Analysis of the CO, HI, and IRAS 100 micron emissions shows that the TeV source region coincides with an outlying sub-group of powerful OB stars which have evacuated or destroyed much of the ambient atomic, molecular and dust material, and which may be related to the very high-energy emissions. An interesting SNR-like structure is also revealed near the TeV source region in the CO, HI and radio emission maps. Applying a numerical simulation which accurately tracks the radio to gamma-ray emission from primary hadrons as well as primary and secondary e+/-, we find that the broadband spectrum of the TeV source region favors a predominantly nucleonic - rather than electronic - origin of the high-energy flux, though deeper X-ray and radio observations are needed to confirm this. A very reasonable, ~0.1%, conversion efficiency of Cyg OB2's extreme stellar wind mechanical luminosity to nucleonic acceleration to ~PeV (10^15 eV) energies is sufficient to explain the multifrequency emissions.Comment: ApJ accepte

Understanding biomolecular motion, recognition, and allostery by use of conformational ensembles

We review the role conformational ensembles can play in the analysis of biomolecular dynamics, molecular recognition, and allostery. We introduce currently available methods for generating ensembles of biomolecules and illustrate their application with relevant examples from the literature. We show how, for binding, conformational ensembles provide a way of distinguishing the competing models of induced fit and conformational selection. For allostery we review the classic models and show how conformational ensembles can play a role in unravelling the intricate pathways of communication that enable allostery to occur. Finally, we discuss the limitations of conformational ensembles and highlight some potential applications for the future

The Effect of a ΔK280 Mutation on the Unfolded State of a Microtubule-Binding Repeat in Tau

Tau is a natively unfolded protein that forms intracellular aggregates in the brains of patients with Alzheimer's disease. To decipher the mechanism underlying the formation of tau aggregates, we developed a novel approach for constructing models of natively unfolded proteins. The method, energy-minima mapping and weighting (EMW), samples local energy minima of subsequences within a natively unfolded protein and then constructs ensembles from these energetically favorable conformations that are consistent with a given set of experimental data. A unique feature of the method is that it does not strive to generate a single ensemble that represents the unfolded state. Instead we construct a number of candidate ensembles, each of which agrees with a given set of experimental constraints, and focus our analysis on local structural features that are present in all of the independently generated ensembles. Using EMW we generated ensembles that are consistent with chemical shift measurements obtained on tau constructs. Thirty models were constructed for the second microtubule binding repeat (MTBR2) in wild-type (WT) tau and a ΔK280 mutant, which is found in some forms of frontotemporal dementia. By focusing on structural features that are preserved across all ensembles, we find that the aggregation-initiating sequence, PHF6*, prefers an extended conformation in both the WT and ΔK280 sequences. In addition, we find that residue K280 can adopt a loop/turn conformation in WT MTBR2 and that deletion of this residue, which can adopt nonextended states, leads to an increase in locally extended conformations near the C-terminus of PHF6*. As an increased preference for extended states near the C-terminus of PHF6* may facilitate the propagation of β-structure downstream from PHF6*, these results explain how a deletion at position 280 can promote the formation of tau aggregates

.Using machine learning to identify important predictors of COVID-19 infection prevention behaviors during the early phase of the pandemic

Before vaccines for coronavirus disease 2019 (COVID-19) became available, a set of infection-prevention behaviors constituted the primary means to mitigate the virus spread. Our study aimed to identify important predictors of this set of behaviors. Whereas social and health psychological theories suggest a limited set of predictors, machine-learning analyses can identify correlates from a larger pool of candidate predictors. We used random forests to rank 115 candidate correlates of infection-prevention behavior in 56,072 participants across 28 countries, administered in March to May 2020. The machine-learning model predicted 52% of the variance in infection-prevention behavior in a separate test sample—exceeding the performance of psychological models of health behavior. Results indicated the two most important predictors related to individuallevel injunctive norms. Illustrating how data-driven methods can complement theory, some of the most important predictors were not derived from theories of health behavior—and some theoretically derived predictors were relatively unimportant