Liquid–Liquid Phase Separation at the Plasma Membrane–Cytosol Interface: Common Players in Adhesion,Motility, and Synaptic Function

Networks of scaffold proteins and enzymes assemble at the interface between the cytosol and specific sites of the plasma membrane, where these networks guide distinct cellular functions. Some of these plasma membrane–associated platforms (PMAPs) include shared core components that are able to establish specific protein–protein interactions, to produce distinct supramolecular assemblies regulating dynamic processes as diverse as cell adhesion and motility, or the formation and function of neuronal synapses. How cells organize such dynamic networks is still an open question. In this review we introduce molecular networks assembling at the edge of migrating cells, and at pre– and postsynaptic sites, which share molecular players that can drive the assembly of biomolecular condensates. Very recent experimental evidence has highlighted the emerging role of some of these multidomain/scaffold proteins belonging to the GIT, liprin-α and ELKS/ERC families as drivers of liquid–liquid phase separation (LLPS). The data point to an important role of LLPS: (i) in the formation of PMAPs at the edge of migrating cells, where LLPS appears to be involved in promoting protrusion and the turnover of integrin–mediated adhesions, to allow forward cell translocation; (ii) in the assembly of the presynaptic active zone and of the postsynaptic density deputed to the release and reception of neurotransmitter signals, respectively. The recent results indicate that LLPS at cytosol–membrane interfaces is suitable not only for the regulation of active cellular processes, but also for the continuous spatial rearrangements of the molecular interactions involved in these dynamic processes.     

Dynamic Autoinhibition of the HMGB1 Protein via Electrostatic Fuzzy Interactions of Intrinsically Disordered Regions

Highly negatively charged segments containing only aspartate or glutamate residues (“D/E repeats”) are found in many eukaryotic proteins. For example, the C-terminal 30 residues of the HMGB1 protein are entirely D/E repeats. Using nuclear magnetic resonance (NMR), fluorescence, and computational approaches, we investigated how the D/E repeats causes the autoinhibition of HMGB1 against its specific binding to cisplatin-modified DNA. By varying ionic strength in a wide range (40–900 mM), we were able to shift the conformational equilibrium between the autoinhibited and uninhibited states toward either of them to the full extent. This allowed us to determine the macroscopic and microscopic equilibrium constants for the HMGB1 autoinhibition at various ionic strengths. At a macroscopic level, a model involving the autoinhibited and uninhibited states can explain the salt concentration-dependent binding affinity data. Our data at a microscopic level show that the D/E repeats and other parts of HMGB1 undergo electrostatic fuzzy interactions, each of which is weaker than expected from the macroscopic autoinhibitory effect. This discrepancy suggests that the multivalent nature of the fuzzy interactions enables strong autoinhibition at a macroscopic level despite the relatively weak intramolecular interaction at each site. Both experimental and computational data suggest that the D/E repeats interact preferentially with other intrinsically disordered regions (IDRs) of HMGB1. We also found that mutations mimicking post-translational modifications relevant to nuclear export of HMGB1 can moderately modulate DNA-binding affinity, possibly by impacting the autoinhibition. This study illuminates a functional role of the fuzzy interactions of D/E repeats.     

Deciphering Spatial Protein–Protein Interactions in Brain Using Proximity Labeling

Cellular biomolecular complexes including protein–protein, protein–RNA, and protein–DNA interactions regulate and execute most biological functions. In particular in brain, protein–protein interactions (PPIs) mediate or regulate virtually all nerve cell functions, such as neurotransmission, cell–cell communication, neurogenesis, synaptogenesis, and synaptic plasticity. Perturbations of PPIs in specific subsets of neurons and glia are thought to underly a majority of neurobiological disorders. Therefore, understanding biological functions at a cellular level requires a reasonably complete catalog of all physical interactions between proteins. An enzyme-catalyzed method to biotinylate proximal interacting proteins within 10 to 300 nm of each other is being increasingly used to characterize the spatiotemporal features of complex PPIs in brain. Thus, proximity labeling has emerged recently as a powerful tool to identify proteomes in distinct cell types in brain as well as proteomes and PPIs in structures difficult to isolate, such as the synaptic cleft, axonal projections, or astrocyte–neuron junctions. In this review, we summarize recent advances in proximity labeling methods and their application to neurobiology.     

The ugly,bad, and good stories of large-scale biomolecular simulations

Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranous nano-constructs, and key pieces of the genetic machinery. We present three unifying biophysical themes that emanate from some of the most recent multi-million atom simulation endeavors. Despite connecting molecular changes with phenotypic outcomes, the quality measures of these simulations remain questionable. We discuss the existing and upcoming strategies for constructing representative ensembles of large systems, how new computing technologies will boost this area, and make a point that integrative modeling guided by experimental data is the future of biomolecular computations.     

Negatively Charged Disordered Regions are Prevalent and Functionally Important Across Proteomes

Intrinsically disordered regions (IDRs) of proteins are often characterized by a high fraction of charged residues, but differ in their overall net charge and in the organization of the charged residues. The function-encoding information stored via IDR charge composition and organization remains elusive. Here, we aim to decipher the sequence–function relationship in IDRs by presenting a comprehensive bioinformatic analysis of the charge properties of IDRs in the human, mouse, and yeast proteomes. About 50% of the proteins comprise at least a single IDR, which is either positively or negatively charged. Highly negatively charged IDRs are longer and possess greater net charge per residue compared with highly positively charged IDRs. A striking difference between positively and negatively charged IDRs is the characteristics of the repeated units, specifically, of consecutive Lys or Arg residues (K/R repeats) and Asp or Glu (D/E repeats) residues. D/E repeats are found to be about five times longer than K/R repeats, with the longest found containing 49 residues. Long stretches of consecutive D and E are found to be more prevalent in nucleic acid-related proteins. They are less common in prokaryotes, and in eukaryotes their abundance increases with genome size. The functional role of D/E repeats and the profound differences between them and K/R repeats are discussed.     

TAPASS: Tool for annotation of protein amyloidogenicity in the context of other structural states

Numerous studies have demonstrated that the propensity of a protein to form amyloids or amorphous aggregates is encoded by its amino acid sequence. This led to the emergence of several computational programs to predict amyloidogenicity from amino acid sequences. However, a growing number of studies indicate that an accurate prediction of the protein aggregation can only be achieved when also accounting for the overall structural context of the protein, and the likelihood of transition between the initial state and the aggregate. Here, we describe a computational pipeline called TAPASS, which was designed to do just that. The pipeline assigns each residue of a protein as belonging to a structured region or an intrinsically disordered region (IDR). For this purpose, TAPASS uses either several state-of-the-art programs for prediction of IDRs, of transmembrane regions and of structured domains or the artificial intelligence program AlphaFold. In the next step, this assignment is crossed with amyloidogenicity prediction. As a result, TAPASS allows the detection of Exposed Amyloidogenic Regions (EARs) located within intrinsically disordered regions (IDRs) and carrying high amyloidogenic potential. TAPASS can substantially improve the prediction of amyloids and be used in proteome-wide analysis to discover new amyloid-forming proteins. Its results, combined with clinical data, can create individual risk profiles for different amyloidoses, opening up new opportunities for personalised medicine. The architecture of the pipeline is designed so that it makes it easy to add new individual predictors as they become available. TAPASS can be used through the web interface (https://bioinfo.crbm.cnrs.fr/index.php?route=tools&tool=32).     

Metabolite assemblies: A surprising extension to the amyloid hypothesis

The realization of the ability of metabolites to form self-assembled amyloid-like nanostructures was a surprising phenomenon. This discovery paved the way towards understanding the pathophysiology of the inborn error of metabolism disorders from a new perspective, relating them to amyloid-associated diseases that are characterized by the aggregation of proteins and polypeptides. Hence, a ‘generic amyloid hypothesis’ can be proposed. This theory implies that the formation of amyloid-like structures is a general phenomenon not limited to proteins and reflects a common etiology for both age-related amyloid-associated diseases and inborn error of metabolism disorders. Here, we present a comprehensive survey of the recent research related to metabolite amyloids including their structure formation through self-association, propagation, interactions, transmission, and their role in metabolic disorders and neurodegenerative diseases and their applications for the fabrication of novel materials which implicate metabolite assemblies as a surprising extension to the amyloid scheme.     

Missense Variants Reveal Functional Insights Into the Human ARID Family of Gene Regulators

Missense variants are alterations to protein coding sequences that result in amino acid substitutions. They can be deleterious if the amino acid is required for maintaining structure or/and function, but are likely to be tolerated at other sites. Consequently, missense variation within a healthy population can mirror the effects of negative selection on protein structure and function, such that functional sites on proteins are often depleted of missense variants. Advances in high-throughput sequencing have dramatically increased the sample size of available human variation data, allowing for population-wide analysis of selective pressures. In this study, we developed a convenient set of tools, called 1D-to-3D, for visualizing the positions of missense variants on protein sequences and structures. We used these tools to characterize human homologues of the ARID family of gene regulators. ARID family members are implicated in multiple cancer types, developmental disorders, and immunological diseases but current understanding of their mechanistic roles is incomplete. Combined with phylogenetic and structural analyses, our approach allowed us to characterise sites important for protein-protein interactions, histone modification recognition, and DNA binding by the ARID proteins. We find that comparing missense depletion patterns among paralogs can reveal sub-functionalization at the level of domains. We propose that visualizing missense variants and their depletion on structures can serve as a valuable tool for complementing evolutionary and experimental findings.     

Synthesis,biological evaluation and anti-proliferative mechanism of fluorine-containing proguanil derivatives

Proguanil, a member of biguanide family, has excellent anti-proliferative activities. Fluorine-containing compounds have been demonstrated to have super biological activities including enhanced binding interactions, metabolic stability, and reduced toxicity. In this study, based on the intermediate derivatization methods, we synthesized 13 new fluorine-containing proguanil derivatives, and found that 7a,7d and 8e had much lower IC₅₀ than proguanil in 5 human cancerous cell lines. The results of clonogenic and scratch wound healing assays revealed that the inhibitory effects of derivatives 7a,7d and 8e on proliferation and migration of human cancer cell lines were much better than proguanil as well. Mechanistic study based on representative derivative 7a indicated that this compound up-regulates AMPK signal pathway and downregulates mTOR/4EBP1/p70S6K. In conclusion, these new fluorine-containing derivatives show potential for the development of cancer chemotherapeutic drugs.     

Structure-based analyses of gut microbiome-related proteins by neural networks and molecular dynamics simulations

An imbalance in the gut microbiome is linked to immune disorders, such as autoimmune, allergic, and chronic inflammatory disorders. Elucidation of disease mechanisms is a matter of urgency. It requires precise elucidation of the structure-based mechanisms of protein interactions involved in disease onset. In addition, an understanding of the protein dynamics is vital because these fluctuations affect the function and interaction of disease-associated proteins. Experimental evaluation of not only protein interactions, functions, and structures but also the dynamics are time-consuming; therefore, computational predictions are necessary to elucidate disease mechanisms. Here, we introduce recent studies on structure-based analyses of proteins using computational approaches, particularly artificial intelligence (AI) and molecular dynamics (MD) simulations.     

PARP–nucleic acid interactions: Allosteric signaling,PARP inhibitor types,DNA bridges,and viral RNA surveillance

PARP enzymes create ADP-ribose modifications to regulate multiple facets of human biology, and some prominent PARP family members are best known for the nucleic acid interactions that regulate their activities and functions. Recent structural studies have highlighted PARP interactions with nucleic acids, in particular for PARP enzymes that detect and respond to DNA strand break damage. These studies build on our understanding of how DNA break detection is linked to the catalysis of ADP-ribose modifications, provide insights into distinct modes of DNA interaction, and shed light on the mechanisms of PARP inhibitor action. PARP enzymes have several connections to RNA biology, including the detection of the genomes of RNA viruses, and recent structural work has highlighted how PARP13/ZAP specifically targets viral genomes enriched in CG dinucleotides.     

Timing of TolA and TolQ Recruitment at the Septum Depends on the Functionality of the Tol-Pal System

Efficient cell division of Gram-negative bacteria requires the presence of the Tol-Pal system to coordinate outer membrane (OM) invagination with inner membrane invagination (IM) and peptidoglycan (PG) remodeling. The Tol-Pal system is a trans-envelope complex that connects the three layers of the cell envelope through an energy-dependent process. It is composed of the three IM proteins, TolA, TolQ and TolR, the periplasmic protein TolB and the OM lipoprotein Pal. The proteins of the Tol-Pal system are dynamically recruited to the cell septum during cell division. TolA, the central hub of the Tol-Pal system, has three domains: a transmembrane helix (TolA₁), a long second helical periplasmic domain (TolA₂) and a C-terminal globular domain (TolA₃). The TolQR complex uses the PMF to energize TolA, allowing its cyclic interaction via TolA₃ with the OM TolB-Pal complex. Here, we confirm that TolA₂ is sufficient to address TolA to the site of constriction, whereas TolA₁ is recruited by TolQ. Analysis of the protein localization as function of the bacterial cell age revealed that TolA and TolQ localize earlier at midcell in the absence of the other Tol-Pal proteins. These data suggest that TolA and TolQ are delayed from their septal recruitment by the multiple interactions of TolA with TolB-Pal in the cell envelope providing a new example of temporal regulation of proteins recruitment at the septum.     

Optimisation of estrogen receptor subtype-selectivity of a 4-Aryl-4H-chromene scaffold previously identified by virtual screening

4-Aryl-4H-Chromene derivatives have been previously shown to exhibit anti-proliferative, apoptotic and anti-angiogenic activity in a variety of tumor models in vitro and in vivo generally via activation of caspases through inhibition of tubulin polymerisation. We have previously identified by Virtual Screening (VS) a 4-aryl-4H-chromene scaffold, of which two examples were shown to bind Estrogen Receptor α and β with low nanomolar affinity and <20-fold selectivity for α over β and low micromolar anti-proliferative activity in the MCF-7 cell line. Thus, using the 4-aryl-4H-chromene scaffold as a starting point, a series of compounds with a range of basic arylethers at C-4 and modifications at the C3-ester substituent of the benzopyran ring were synthesised, producing some potent ER antagonists in the MCF-7 cell line which were highly selective for ERα (compound 35; 350-fold selectivity) or ERβ (compound 42; 170-fold selectivity).     

Towards the Molecular Mechanism of Pulmonary Surfactant Protein SP-B: At the Crossroad of Membrane Permeability and Interfacial Lipid Transfer

Pulmonary surfactant is a lipid-protein complex that coats the alveolar air-liquid interface, enabling the proper functioning of lung mechanics. The hydrophobic surfactant protein SP-B, in particular, plays an indispensable role in promoting the rapid adsorption of phospholipids into the interface. For this, formation of SP-B ring-shaped assemblies seems to be important, as oligomerization could be required for the ability of the protein to generate membrane contacts and to mediate lipid transfer among surfactant structures. SP-B, together with the other hydrophobic surfactant protein SP-C, also promotes permeability of surfactant membranes to polar molecules although the molecular mechanisms underlying this property, as well as its relevance for the surface activity of the protein, remain undefined. In this work, the contribution of SP-B and SP-C to surfactant membrane permeability has been further investigated, by evaluation of the ability of differently-sized fluorescent polar probes to permeate through giant vesicles with different lipid/protein composition. Our results are consistent with the generation by SP-B of pores with defined size in surfactant membranes. Furthermore, incubation of surfactant with an anti-SP-B antibody not only blocked membrane permeability but also affected lipid transfer into the air-water interface, as observed in a captive bubble surfactometer device. Our findings include the identification of SP-C and anionic phospholipids as modulators required for maintaining native-like permeability features in pulmonary surfactant membranes. Proper permeability through membrane assemblies could be crucial to complement the overall role of surfactant in maintaining alveolar equilibrium, beyond its biophysical function in stabilizing the respiratory air-liquid interface.