Controllability of protein-protein interaction phosphorylation-based networks: Participation of the hub 14-3-3 protein family

A statistical mechanics investigation of unfolded protein response across organisms

Living systems rely on coordinated molecular interactions, especially those related to gene expression and protein activity. The Unfolded Protein Response is a crucial mechanism in eukaryotic cells, activated when unfolded proteins exceed a critical threshold. It maintains cell homeostasis by enhancing protein folding, initiating quality control, and activating degradation pathways when damage is irreversible. This response functions as a dynamic signaling network, with proteins as nodes and their interactions as edges. We analyze these protein-protein networks across different organisms to understand their intricate intra-cellular interactions and behaviors. In this work, analyzing twelve organisms, we assess how fundamental measures in network theory can individuate seed proteins and specific pathways across organisms. We employ network robustness to evaluate and compare the strength of the investigated protein-protein interaction networks, and the structural controllability of complex networks to find and compare the sets of driver nodes necessary to control the overall networks. We find that network measures are related to phylogenetics, and advanced network methods can identify main pathways of significance in the complete Unfolded Protein Response mechanism.

Intrinsic structural disorder on proteins is involved in the interactome evolution

New mathematical tools help understand cell functions, adaptability, and evolvability to discover hidden variables to predict phenotypes that could be tested in the future in wet labs. Different models have been successfully used to discover the properties of the protein-protein interaction networks or interactomes. I found that in the hyperbolic Popularity-Similarity model, cellular proteins with the highest contents of structural intrinsic disorder cluster together in many different eukaryotic interactomes and this is not the case for the prokaryotic E. coli, where proteins with high degree of intrinsic disorder are scarce. I also found that the normalized theta variable from the Popularity-Similarity model for orthologues proteins correlate to the complexity of the organisms in analysis.

Systematic identification of recognition motifs for the hub protein LC8

LC8 is a eukaryotic hub protein that interacts with multifarious partners; analysis of more than 100 binding/nonbinding sequences led to an algorithm that predicts LC8 partners with 78% accuracy.

Hub proteins participate in cellular regulation by dynamic binding of multiple proteins within interaction networks. The hub protein LC8 reversibly interacts with more than 100 partners through a flexible pocket at its dimer interface. To explore the diversity of the LC8 partner pool, we screened for LC8 binding partners using a proteomic phage display library composed of peptides from the human proteome, which had no bias toward a known LC8 motif. Of the identified hits, we validated binding of 29 peptides using isothermal titration calorimetry. Of the 29 peptides, 19 were entirely novel, and all had the canonical TQT motif anchor. A striking observation is that numerous peptides containing the TQT anchor do not bind LC8, indicating that residues outside of the anchor facilitate LC8 interactions. Using both LC8-binding and nonbinding peptides containing the motif anchor, we developed the “LC8Pred” algorithm that identifies critical residues flanking the anchor and parses random sequences to predict LC8-binding motifs with ∼78% accuracy. Our findings significantly expand the scope of the LC8 hub interactome.

Do cells use passwords in cell-state transitions? Is cell signaling sometimes encrypted?

Organisms must maintain proper regulation including defense and healing. Life-threatening problems may be caused by pathogens or by a multicellular organism's own cells through cancer or autoimmune disorders. Life evolved solutions to these problems that can be conceptualized through the lens of information security, which is a well-developed field in computer science. Here I argue that taking an information security view of cells is not merely semantics, but useful to explain features of signaling, regulation, and defense. An information security perspective also offers a conduit for cross-fertilization of advanced ideas from computer science and the potential for biology to inform computer science. First, I consider whether cells use passwords, i.e., initiation sequences that are required for subsequent signals to have effects, by analyzing the concept of pioneer transcription factors in chromatin regulation and cellular reprogramming. Second, I consider whether cells may encrypt signal transduction cascades. Encryption could benefit cells by making it more difficult for pathogens or oncogenes to hijack cell networks. By using numerous molecules, cells may gain a security advantage in particular against viruses, whose genome sizes are typically under selection pressure. I provide a simple conceptual argument for how cells may perform encryption through posttranslational modifications, complex formation, and chromatin accessibility. I invoke information theory to provide a criterion of an entropy spike to assess whether a signaling cascade has encryption-like features. I discuss how the frequently invoked concept of context dependency may oversimplify more advanced features of cell signaling networks, such as encryption. Therefore, by considering that biochemical networks may be even more complex than commonly realized we may be better able to understand defenses against pathogens and pathologies.

A dual controllability analysis of influenza virus-host protein-protein interaction networks for antiviral drug target discovery

BACKGROUND

Host factors of influenza virus replication are often found in key topological positions within protein-protein interaction networks. This work explores how protein states can be manipulated through controllability analysis: the determination of the minimum manipulation needed to drive the cell system to any desired state. Here, we complete a two-part controllability analysis of two protein networks: a host network representing the healthy cell state and an influenza A virus-host network representing the infected cell state. In this context, controllability analyses aim to identify key regulating host factors of the infected cell's progression. This knowledge can be utilized in further biological analysis to understand disease dynamics and isolate proteins for study as drug target candidates.

RESULTS

Both topological and controllability analyses provide evidence of wide-reaching network effects stemming from the addition of viral-host protein interactions. Virus interacting and driver host proteins are significant both topologically and in controllability, therefore playing important roles in cell behavior during infection. Functional analysis finds overlap of results with previous siRNA studies of host factors involved in influenza replication, NF-kB pathway and infection relevance, and roles as interferon regulating genes. 24 proteins are identified as holding regulatory roles specific to the infected cell by measures of topology, controllability, and functional role. These proteins are recommended for further study as potential antiviral drug targets.

CONCLUSIONS

Seasonal outbreaks of influenza A virus are a major cause of illness and death around the world each year with a constant threat of pandemic infection. This research aims to increase the efficiency of antiviral drug target discovery using existing protein-protein interaction data and network analysis methods. These results are beneficial to future studies of influenza virus, both experimental and computational, and provide evidence that the combination of topology and controllability analyses may be valuable for future efforts in drug target discovery.

Intrinsic disorder associated with 14-3-3 proteins and their partners

Protein-protein interactions (PPIs) mediate a variety of cellular processes and form complex networks, where connectivity is achieved owing to the "hub" proteins whose interaction with multiple protein partners is facilitated by the intrinsically disordered protein regions (IDPRs) and posttranslational modifications (PTMs). Universal regulatory proteins of the eukaryotic 14-3-3 family nicely exemplify these concepts and are the focus of this chapter. The extremely wide interactome of 14-3-3 proteins is characterized by high levels of intrinsic disorder (ID) enabling protein phosphorylation and consequent specific binding to the well-structured 14-3-3 dimers, one of the first phosphoserine/phosphothreonine binding modules discovered. However, high ID enrichment also challenges structural studies, thereby limiting the progress in the development of small molecule modulators of the key 14-3-3 PPIs of increased medical importance. Besides the well-known structural flexibility of their variable C-terminal tails, recent studies revealed the strong and conserved ID propensity hidden in the N-terminal segment of 14-3-3 proteins (~40 residues), normally forming the α-helical dimerization region, that may have a potential role for the dimer/monomer dynamics and recently reported moonlighting chaperone-like activity of these proteins. We review the role of ID in the 14-3-3 structure, their interactome, and also in selected 14-3-3 complexes. In addition, we discuss approaches that, in the future, may help minimize the disproportion between the large amount of known 14-3-3 partners and the small number of 14-3-3 complexes characterized with atomic precision, to unleash the whole potential of 14-3-3 PPIs as drug targets.

Small-Molecule-Induced and Cooperative Enzyme Assembly on a 14-3-3 Scaffold

Scaffold proteins regulate cell signalling by promoting the proximity of putative interaction partners. Although they are frequently applied in cellular settings, fundamental understanding of them in terms of, amongst other factors, quantitative parameters has been lagging behind. Here we present a scaffold protein platform that is based on the native 14-3-3 dimeric protein and is controllable through the action of a small-molecule compound, thus permitting study in an in vitro setting and mathematical description. Robust small-molecule regulation of caspase-9 activity through induced dimerisation on the 14-3-3 scaffold was demonstrated. The individual parameters of this system were precisely determined and used to develop a mathematical model of the scaffolding concept. This model was used to elucidate the strong cooperativity of the enzyme activation mediated by the 14-3-3 scaffold. This work provides an entry point for the long-needed quantitative insights into scaffold protein functioning and paves the way for the optimal use of reengineered 14-3-3 proteins as chemically inducible scaffolds in synthetic systems.