Multisite Phosphorylation and Binding Alter Conformational Dynamics of the 4E-BP2 Protein

Intrinsically disordered proteins (IDPs) play critical roles in regulatory protein interactions, but detailed structural/dynamics characterization of their ensembles remain challenging, both in isolation and they form dynamic fuzzy complexes. Such is the case for mRNA cap-dependent translation initiation, which is regulated by the interaction of the predominantly folded eukaryotic initiation factor 4E (eIF4E) with the intrinsically disordered eIF4E binding proteins (4E-BPs) in a phosphorylation-dependent manner. Single-molecule Forster resonance energy transfer showed that the conformational changes of 4E-BP2 induced by binding to eIF4E are non-uniform along the sequence; while a central region containing both motifs that bind to eIF4E expands and becomes stiffer, the C-terminal region is less affected. Fluorescence anisotropy decay revealed a nonuniform segmental flexibility around six different labelling sites along the chain. Dynamic quenching of these fluorescent probes by intrinsic aromatic residues measured via fluorescence correlation spectroscopy report on transient intra- and inter-molecular contacts on nanosecond-microsecond timescales. Upon hyperphosphorylation, which induces folding of ~40 residues in 4E-BP2, the quenching rates decreased at labelling sites closest to the phosphorylation sites and within the folded domain, and increased at the other sites. The chain dynamics around sites in the C-terminal region far away from the two binding motifs were significantly reduced upon binding to eIF4E, suggesting that this region is also involved in the highly dynamic 4E-BP2:eIF4E complex. Our time-resolved fluorescence data paint a sequence-level rigidity map of three states of 4E-BP2 differing in phosphorylation or binding status and distinguish regions that form contacts with eIF4E. This study adds complementary structural and dynamics information to recent studies of 4E-BP2, and it constitutes an important step towards a mechanistic understanding of this important IDP via integrative modelling.

A targeted bioinformatics approach identifies highly variable cell surface proteins that are unique to Glomeromycotina

Diversity in arbuscular mycorrhizal fungi (AMF) contributes to biodiversity and resilience in natural environments and healthy agricultural systems. Functional complementarity exists among species of AMF in symbiosis with their plant hosts, but the molecular basis of this is not known. We hypothesise this is in part due to the difficulties that current sequence assembly methodologies have assembling sequences for intrinsically disordered proteins (IDPs) due to their low sequence complexity. IDPs are potential candidates for functional complementarity because they often exist as extended (non-globular) proteins providing additional amino acids for molecular interactions. Rhizophagus irregularis arabinogalactan-protein-like proteins (AGLs) are small secreted IDPs with no known orthologues in AMF or other fungi. We developed a targeted bioinformatics approach to identify highly variable AGLs/IDPs in RNA-sequence datasets. The approach includes a modified multiple k-mer assembly approach (Oases) to identify candidate sequences, followed by targeted sequence capture and assembly (mirabait-mira). All AMF species analysed, including the ancestral family Paraglomeraceae, have small families of proteins rich in disorder promoting amino acids such as proline and glycine, or glycine and asparagine. Glycine- and asparagine-rich proteins also were found in Geosiphon pyriformis (an obligate symbiont of a cyanobacterium), from the same subphylum (Glomeromycotina) as AMF. The sequence diversity of AGLs likely translates to functional diversity, based on predicted physical properties of tandem repeats (elastic, amyloid, or interchangeable) and their broad pI ranges. We envisage that AGLs/IDPs could contribute to functional complementarity in AMF through processes such as self-recognition, retention of nutrients, soil stability, and water movement.

Competing interactions give rise to two-state behavior and switch-like transitions in charge-rich intrinsically disordered proteins

The most commonly occurring intrinsically disordered proteins (IDPs) are polyampholytes, which are defined by the duality of low net charge per residue and high fractions of charged residues. Recent experiments have uncovered surprises regarding sequence-ensemble relationships of model polyampholytic IDPs. These include differences in conformational preferences for sequences with lysine vs. arginine, and the suggestion that well-mixed sequences either form globules or conformations with ensemble averages that are reminiscent of ideal chains wherein intra-chain and chain-solvent interactions are counterbalanced. Here, we explain these observations by analyzing results from atomistic simulations. We find that polyampholytic IDPs generally sample two distinct stable states, namely globules and self-avoiding walks. Globules are favored by electrostatic attractions between oppositely charged residues, whereas self-avoiding walks are favored by favorable free energies of hydration of charged residues. We find sequence-specific temperatures of bistability at which globules and self-avoiding walks can coexist. At these temperatures, ensemble averages over coexisting states give rise to statistics that resemble ideal chains without there being an actual counterbalancing of intra-chain and chain-solvent interactions. At equivalent temperatures, arginine-rich sequences tilt the preference toward globular conformations whereas lysine-rich sequences tilt the preference toward self-avoiding walks. This stems from intrinsic differences in free energies of hydration between arginine and lysine. We also identify differences between aspartate and glutamate containing sequences, whereby the shorter aspartate sidechain engenders preferences for metastable, necklace-like conformations. Finally, although segregation of oppositely charged residues within the linear sequence maintains the overall two-state behavior, compact states are highly favored by such systems.

Multivalency enables unidirectional switch-like competition between intrinsically disordered proteins

Intrinsically disordered proteins must compete for binding to common regulatory targets to carry out their biological functions. Previously, we showed that the activation domains of two disordered proteins, the transcription factor HIF-1α and its negative regulator CITED2, function as a unidirectional, allosteric molecular switch to control transcription of critical adaptive genes under conditions of oxygen deprivation. These proteins achieve transcriptional control by competing for binding to the TAZ1 domain of the transcriptional coactivators CREB-binding protein (CBP) and p300 (CREB: cyclic-AMP response element binding protein). To characterize the mechanistic details behind this molecular switch, we used solution NMR spectroscopy and complementary biophysical methods to determine the contributions of individual binding motifs in CITED2 to the overall competition process. An N-terminal region of the CITED2 activation domain, which forms a helix when bound to TAZ1, plays a critical role in initiating competition with HIF-1α by enabling formation of a ternary complex in a process that is highly dependent on the dynamics and disorder of the competing partners. Two other conserved binding motifs in CITED2, the LPEL motif and an aromatic/hydrophobic motif that we term ϕC, function synergistically to enhance binding of CITED2 and inhibit rebinding of HIF-1α. The apparent unidirectionality of competition between HIF-1α and CITED2 is lost when one or more of these binding regions is altered by truncation or mutation of the CITED2 peptide. Our findings illustrate the complexity of molecular interactions involving disordered proteins containing multivalent interaction motifs and provide insight into the unique mechanisms by which disordered proteins compete for occupancy of common molecular targets within the cell.

Do Molecular Dynamics Force Fields Accurately Model Ramachandran Distributions of Amino Acid Residues in Water?

Molecular dynamics (MD) is a powerful tool for studying intrinsically disordered proteins, however, its reliability depends on the accuracy of the force field. We here assess Amber ff14SB, Amber ff14SB,...

Determinants for Intrinsically Disordered Protein Recruitment into Phase-Separated Protein Condensates

Multivalent interactions between amino acid residues of intrinsically disordered proteins (IDPs) drive phase separation of these proteins into liquid condensates, forming various membrane-less organelles in cells. These interactions between often...

Computational Prediction of Intrinsically Disordered Proteins Based on Protein Sequences and Convolutional Neural Networks

Intrinsically disordered proteins (IDPs) possess at least one region that lacks a single stable structure in vivo, which makes them play an important role in a variety of biological functions. We propose a prediction method for IDPs based on convolutional neural networks (CNNs) and feature selection. The combination of sequence and evolutionary properties is used to describe the differences between disordered and ordered regions. Especially, to highlight the correlation between the target residue and adjacent residues, multiple windows are selected to preprocess the protein sequence through the selected properties. The shorter windows reflect the characteristics of the central residue, and the longer windows reflect the characteristics of the surroundings around the central residue. Moreover, to highlight the specificity of sequence and evolutionary properties, they are preprocessed, respectively. After that, the preprocessed properties are combined into feature matrices as the input of the constructed CNN. Our method is training as well as testing based on the DisProt database. The simulation results show that the proposed method can predict IDPs effectively, and the performance is competitive in comparison with IsUnstruct and ESpritz.