A computational model for understanding the oligomerization mechanisms of TNF receptor superfamily

Visual analysis on ferroptosis and its cross-talk to coronavirus disease 2019 (COVID-19)

Background

Ferroptosis is a new type of programmed cell death. Although ferroptosis has been studied in various aspects, there has been no visual analysis of ferroptosis in coronavirus disease 2019 (COVID-19) to date. It is still a global health concern of the COVID-19 pandemic worldwide, three years after its outbreak. Yet the emergence of the mutant strain Omicron has caused a fourth wave of infections in many countries. The pathogenesis of COVID-19 is still undergoing extensive exploration, which holds paramount importance in mitigating future epidemics.

Methods

For this study, CiteSpace 6.2 R4 software was used for bibliometric and visual atlas analysis of ferroptosis-related research, and the Genecards database was used to mine ferroptosis and COVID-19-related genes.

Results

We found increasing studies about ferroptosis. China and the United States have demonstrated robust scientific innovation over recent years, with extensive collaboration between their institutions and authors. Ferroptosis and COVID-19 were seen to have 13 shared genes, which may be new targets for the treatment of COVID-19 in the future. Most of the shared genes are enriched in tumor necrosis factor (TNF) pathways. The majority of those genes are up-regulated under the cellular response to oxidative stress. Genes including Tumour necrosis factor (TNF), RELA proto-oncogene (RELA), Activating transcription factor 4 (ATF4), Cytochrome b-245 beta chain (CYBB), Jun proto-oncogene (JUN), Mitogen-activated protein kinase 1 (MAPK1) and Heme oxygenase 1 (HMOX1), maybe a breakthrough for ferroptosis and COVID-19. Whilst previous research has shown there to be a relationship between ferroptosis and COVID-19, the specific role of ferroptosis remained unclear. Our study aimed to analyze the research status of ferroptosis and its relationship with COVID-19, to provide a useful reference for further prevention and treatment of COVID-19. Overall, uncovering the role of ferroptosis in SARS-CoV-2 infection is important for the development of new treatment strategies for COVID-19.

Inflammation in Development and Aging: Insights from the Zebrafish Model

Zebrafish are an emergent animal model to study human diseases due to their significant genetic similarity to humans, swift development, and genetic manipulability. Their utility extends to the exploration of the involvement of inflammation in host defense, immune responses, and tissue regeneration. Additionally, the zebrafish model system facilitates prompt screening of chemical compounds that affect inflammation. This study explored the diverse roles of inflammatory pathways in zebrafish development and aging. Serving as a crucial model, zebrafish provides insights into the intricate interplay of inflammation in both developmental and aging contexts. The evidence presented suggests that the same inflammatory signaling pathways often play instructive or beneficial roles during embryogenesis and are associated with malignancies in adults.

How does the same ligand activate signaling of different receptors in TNFR superfamily: a computational study

TNFα is a highly pleiotropic cytokine inducing inflammatory signaling pathways. It is initially presented on plasma membrane of cells (mTNFα), and also exists in a soluble variant (sTNFα) after cleavage. The ligand is shared by two structurally similar receptors, TNFR1 and TNFR2. Interestingly, while sTNFα preferentially stimulates TNFR1, TNFR2 signaling can only be activated by mTNFα. How can two similar receptors respond to the same ligand in such a different way? We employed computational simulations in multiple scales to address this question. We found that both mTNFα and sTNFα can trigger the clustering of TNFR1. The size of clusters induced by sTNFα is constantly larger than the clusters induced by mTNFα. The systems of TNFR2, on the other hand, show very different behaviors. Only when the interactions between TNFR2 are very weak, mTNFα can trigger the receptors to form very large clusters. Given the same weak binding affinity, only small oligomers were obtained in the system of sTNFα. Considering that TNF-mediated signaling is modulated by the ligand-induced clustering of receptors on cell surface, our study provided the mechanistic foundation to the phenomenon that different isoforms of the ligand can lead to highly distinctive signaling patterns for its receptors.

Structure and thermodynamics of a 2D Lennard-Jones hexagonal fluid

The thermodynamic and structural properties of the 2D hexagonal soft-sites fluid are examined by integral equation theory benchmarked against extensive Monte Carlo simulations. Hexamers are built of six equal Lennard-Jones segments. Site-site integral equation theory is used to compute site-site correlation functions, excess internal energies and isotherms over a wide range of conditions and compared with results obtained from Monte Carlo simulations. Various approaches for computing the pressure are discussed as well. Satisfactory qualitative agreement between theory and simulations is found with details depending on the applied closure relation.

Understanding the functional role of membrane confinements in TNF-mediated signaling by multiscale simulations

The interaction between TNFα and TNFR1 is essential in maintaining tissue development and immune responses. While TNFR1 is a cell surface receptor, TNFα exists in both soluble and membrane-bound forms. Interestingly, it was found that the activation of TNFR1-mediated signaling pathways is preferentially through the soluble form of TNFα, which can also induce the clustering of TNFR1 on plasma membrane of living cells. We developed a multiscale simulation framework to compare receptor clustering induced by soluble and membrane-bound ligands. Comparing with the freely diffusive soluble ligands, we hypothesize that the conformational dynamics of membrane-bound ligands are restricted, which affects the clustering of ligand-receptor complexes at cell-cell interfaces. Our simulation revealed that only small clusters can form if TNFα is bound on cell surface. In contrast, the clustering triggered by soluble TNFα is more dynamic, and the size of clusters is statistically larger. We therefore demonstrated the impact of membrane-bound ligand on dynamics of receptor clustering. Moreover, considering that larger TNFα-TNFR1 clusters is more likely to provide spatial platform for downstream signaling pathway, our studies offer new mechanistic insights about why the activation of TNFR1-mediated signaling pathways is not preferred by membrane-bound form of TNFα.

EXCESP: A Structure-Based Online Database for Extracellular Interactome of Cell Surface Proteins in Humans

The interactions between ectodomains of cell surface proteins are vital players in many important cellular processes, such as regulating immune responses, coordinating cell differentiation, and shaping neural plasticity. However, while the construction of a large-scale protein interactome has been greatly facilitated by the development of high-throughput experimental techniques, little progress has been made to support the discovery of extracellular interactome for cell surface proteins. Harnessed by the recent advances in computational modeling of protein-protein interactions, here we present a structure-based online database for the extracellular interactome of cell surface proteins in humans, called EXCESP. The database contains both experimentally determined and computationally predicted interactions among all type-I transmembrane proteins in humans. All structural models for these interactions and their binding affinities were further computationally modeled. Moreover, information such as expression levels of each protein in different cell types and its relation to various signaling pathways from other online resources has also been integrated into the database. In summary, the database serves as a valuable addition to the existing online resources for the study of cell surface proteins. It can contribute to the understanding of the functions of cell surface proteins in the era of systems biology.

Computational Simulation of Holin S105 in Membrane Bilayer and Its Dimerization Through a Helix-Turn-Helix Motif

During the final step of the bacteriophage infection cycle, the cytoplasmic membrane of host cells is disrupted by small membrane proteins called holins. The function of holins in cell lysis is carried out by forming a highly ordered structure called lethal lesion, in which the accumulation of holins in the cytoplasmic membrane leads to the sudden opening of a hole in the middle of this oligomer. Previous studies showed that dimerization of holins is a necessary step to induce their higher order assembly. However, the molecular mechanism underlying the holin-mediated lesion formation is not well understood. In order to elucidate the functions of holin, we first computationally constructed a structural model for our testing system: the holin S105 from bacteriophage lambda. All atom molecular dynamic simulations were further applied to refine its structure and study its dynamics as well as interaction in lipid bilayer. Additional simulations on association between two holins provide supportive evidence to the argument that the C-terminal region of holin plays a critical role in regulating the dimerization. In detail, we found that the adhesion of specific nonpolar residues in transmembrane domain 3 (TMD3) in a polar environment serves as the driven force of dimerization. Our study therefore brings insights to the design of binding interfaces between holins, which can be potentially used to modulate the dynamics of lesion formation.

A systems-biology model of the tumor necrosis factor (TNF) interactions with TNF receptor 1 and 2

MOTIVATION

Clustering enables TNF receptors to stimulate intracellular signaling. The differential soluble ligand-induced clustering behavior of TNF receptor 1 (TNFR1) and TNFR2 was modeled. A structured, rule-based model implemented ligand-independent pre-ligand binding assembly domain (PLAD)-mediated homotypic low affinity interactions of unliganded and liganded TNF receptors.

RESULTS

Soluble TNF initiates TNFR1 signaling but not TNFR2 signaling despite receptor binding unless it is secondarily oligomerized. We consider high affinity binding of TNF to signaling-incompetent pre-assembled dimeric TNFR1 and TNFR2 molecules and secondary clustering of liganded dimers to signaling competent ligand-receptor clusters. Published receptor numbers, affinities and measured different activities of clustered receptors validated model simulations for a large range of receptor and ligand concentrations. Different PLAD-PLAD affinities and different activities of receptor clusters explain the observed differences in the TNF receptor stimulating activities of soluble TNF.

AVAILABILITY AND IMPLEMENTATION

All scripts and data are in manuscript and supplement at Bioinformatics online.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Mechanistic dissection of spatial organization in NF-κB signaling pathways by hybrid simulations

The nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) is one of the most important transcription factors involved in the regulation of inflammatory signaling pathways. Inappropriate activation of these pathways has been linked to autoimmunity and cancers. Emerging experimental evidences have been showing the existence of elaborate spatial organizations for various molecular components in the pathways. One example is the scaffold protein tumor necrosis factor receptor associated factor (TRAF). While most TRAF proteins form trimeric quaternary structure through their coiled-coil regions, the N-terminal region of some members in the family can further be dimerized. This dimerization of TRAF trimers can drive them into higher-order clusters as a response to receptor stimulation, which functions as a spatial platform to mediate the downstream poly-ubiquitination. However, the molecular mechanism underlying the TRAF protein clustering and its functional impacts are not well-understood. In this article, we developed a hybrid simulation method to tackle this problem. The assembly of TRAF-based signaling platform at the membrane-proximal region is modeled with spatial resolution, while the dynamics of downstream signaling network, including the negative feedbacks through various signaling inhibitors, is simulated as stochastic chemical reactions. These two algorithms are further synchronized under a multiscale simulation framework. Using this computational model, we illustrated that the formation of TRAF signaling platform can trigger an oscillatory NF-κB response. We further demonstrated that the temporal patterns of downstream signal oscillations are closely regulated by the spatial factors of TRAF clustering, such as the geometry and energy of dimerization between TRAF trimers. In general, our study sheds light on the basic mechanism of NF-κB signaling pathway and highlights the functional importance of spatial regulation within the pathway. The simulation framework also showcases its potential of application to other signaling pathways in cells.

In silico analysis of molecular interactions between HIV-1 glycoprotein gp120 and TNF receptors

Proinflammatory microenvironmental is crucial for the Human Immunodeficiency Virus Type 1 (HIV-1) pathogenesis. The viral glycoprotein 120 (gp120) must interact with the CD4+ T cell chemokine receptor (CCR5) and a co-receptor C-X-C chemokine receptor type 4 (CXCR4) to let the virus entry into the host cells. However, the interaction of the viral particle with other cell surface receptors is mandatory for its attachment and subsequently entry. Tumor Necrosis Factor receptor type I (TNFR1), type II (TNFR2) and Fas are a superfamily of transmembrane proteins involved in canonical inflammatory pathway and cell death by apoptosis as responses against viral pathogens. In our study, we performed an in silico evaluation of the molecular interactions between viral protein gp120 and TNF receptors (TNFR1, TNFR2 and Fas). Protein structures were retrieved from Protein Databank (PDB), and Molecular Docking and dynamics were performed using ClusPro 2.0 server and GROMACS software, respectively. We observed that gp120 is able to bind TNFR1, TNFR2 and Fas receptors, although only the TNFR2-gp120 complex demonstrated to produce a stable and durable binding. Our findings suggest that gp120 may act as an agonist to TNF-α and also function as an attachment factor in HIV-1 entry process. These molecular interaction by gp120 may be the key to HIV-1 immunopathogenesis. In conclusion, gp120 may stimulate pro-inflammatory and apoptotic signaling transduction pathways mediated by TNFR2 and may act as an attachment factor retaining HIV-1 viral particles on the host cell surface.

A multiscale study on the mechanisms of spatial organization in ligand-receptor interactions on cell surfaces

The binding of cell surface receptors with extracellular ligands triggers distinctive signaling pathways, leading into the corresponding phenotypic variation of cells. It has been found that in many systems, these ligand-receptor complexes can further oligomerize into higher-order structures. This ligand-induced oligomerization of receptors on cell surfaces plays an important role in regulating the functions of cell signaling. The underlying mechanism, however, is not well understood. One typical example is proteins that belong to the tumor necrosis factor receptor (TNFR) superfamily. Using a generic multiscale simulation platform that spans from atomic to subcellular levels, we compared the detailed physical process of ligand-receptor oligomerization for two specific members in the TNFR superfamily: the complex formed between ligand TNFα and receptor TNFR1 versus the complex formed between ligand TNFβ and receptor TNFR2. Interestingly, although these two systems share high similarity on the tertiary and quaternary structural levels, our results indicate that their oligomers are formed with very different dynamic properties and spatial patterns. We demonstrated that the changes of receptor’s conformational fluctuations due to the membrane confinements are closely related to such difference. Consistent to previous experiments, our simulations also showed that TNFR can preassemble into dimers prior to ligand binding, while the introduction of TNF ligands induced higher-order oligomerization due to a multivalent effect. This study, therefore, provides the molecular basis to TNFR oligomerization and reveals new insights to TNFR-mediated signal transduction. Moreover, our multiscale simulation framework serves as a prototype that paves the way to study higher-order assembly of cell surface receptors in many other bio-systems.

A computational study of co-inhibitory immune complex assembly at the interface between T cells and antigen presenting cells

The activation and differentiation of T-cells are mainly directly by their co-regulatory receptors. T lymphocyte-associated protein-4 (CTLA-4) and programed cell death-1 (PD-1) are two of the most important co-regulatory receptors. Binding of PD-1 and CTLA-4 with their corresponding ligands programed cell death-ligand 1 (PD-L1) and B7 on the antigen presenting cells (APC) activates two central co-inhibitory signaling pathways to suppress T cell functions. Interestingly, recent experiments have identified a new cis-interaction between PD-L1 and B7, suggesting that a crosstalk exists between two co-inhibitory receptors and the two pairs of ligand-receptor complexes can undergo dynamic oligomerization. Inspired by these experimental evidences, we developed a coarse-grained model to characterize the assembling of an immune complex consisting of CLTA-4, B7, PD-L1 and PD-1. These four proteins and their interactions form a small network motif. The temporal dynamics and spatial pattern formation of this network was simulated by a diffusion-reaction algorithm. Our simulation method incorporates the membrane confinement of cell surface proteins and geometric arrangement of different binding interfaces between these proteins. A wide range of binding constants was tested for the interactions involved in the network. Interestingly, we show that the CTLA-4/B7 ligand-receptor complexes can first form linear oligomers, while these oligomers further align together into two-dimensional clusters. Similar phenomenon has also been observed in other systems of cell surface proteins. Our test results further indicate that both co-inhibitory signaling pathways activated by B7 and PD-L1 can be down-regulated by the new cis-interaction between these two ligands, consistent with previous experimental evidences. Finally, the simulations also suggest that the dynamic and the spatial properties of the immune complex assembly are highly determined by the energetics of molecular interactions in the network. Our study, therefore, brings new insights to the co-regulatory mechanisms of T cell activation.

The activation of a T cell can be regulated by the receptors on its surface, such as CTLA-4 and PD-1. People used to think that these two receptors inhibit T cell activation through distinct pathways. However, recent experiments discovered that the ligands of these two receptors, B7 and PD-L1, can interact with each other on the same surface of antigen presenting cells. Here we utilized computational simulations to investigate functional roles of this newly discovered interaction in T cell coregulation. The specific environment of interface between T cell and antigen presenting cell has been taken into account of our model. Ligand and receptors randomly diffuse within this interface area. They further involve in different types of interactions, with each other from the same side or the opposite side of cell surface. Using this method, we found ligands and receptors can not only form complexes, but also aggregate into large-scale clusters. We also demonstrated that the engagement between B7 and PD-L1 can reduce the interactions with their corresponding receptors. This study, therefore, offers new insights to our understanding of signal regulation in T cells.

Understanding the impacts of cellular environments on ligand binding of membrane receptors by computational simulations

Binding of cell surface receptors with their extracellular ligands initiates various intracellular signaling pathways. However, our understanding of the cellular functions of these receptors is very limited due to the fact that in vivo binding between ligands and receptors has only been successfully measured in a very small number of cases. In living cells, receptors are anchored on surfaces of the plasma membrane, which undergoes thermal undulations. Moreover, it has been observed in various systems that receptors can be organized into oligomers prior to ligand binding. It is not well understood how these cellular factors play roles in regulating the dynamics of ligand-receptor interactions. Here, we tackled these problems by using a coarse-grained kinetic Monte Carlo simulation method. Using this method, we demonstrated that the membrane undulations cause a negative effect on ligand-receptor interactions. We further found that the preassembly of membrane receptors on the cell surface can not only accelerate the kinetics of ligand binding but also reduce the noises during the process. In general, our study highlights the importance of membrane environments in regulating the function of membrane receptors in cells. The simulation method can be potentially applied to specific receptor systems involved in cell signaling.

A Systematic Test of Receptor Binding Kinetics for Ligands in Tumor Necrosis Factor Superfamily by Computational Simulations

Ligands in the tumor necrosis factor (TNF) superfamily are one major class of cytokines that bind to their corresponding receptors in the tumor necrosis factor receptor (TNFR) superfamily and initiate multiple intracellular signaling pathways during inflammation, tissue homeostasis, and cell differentiation. Mutations in the genes that encode TNF ligands or TNFR receptors result in a large variety of diseases. The development of therapeutic treatment for these diseases can be greatly benefitted from the knowledge on binding properties of these ligand–receptor interactions. In order to complement the limitations in the current experimental methods that measure the binding constants of TNF/TNFR interactions, we developed a new simulation strategy to computationally estimate the association and dissociation between a ligand and its receptor. We systematically tested this strategy to a comprehensive dataset that contained structures of diverse complexes between TNF ligands and their corresponding receptors in the TNFR superfamily. We demonstrated that the binding stabilities inferred from our simulation results were compatible with existing experimental data. We further compared the binding kinetics of different TNF/TNFR systems, and explored their potential functional implication. We suggest that the transient binding between ligands and cell surface receptors leads into a dynamic nature of cross-membrane signal transduction, whereas the slow but strong binding of these ligands to the soluble decoy receptors is naturally designed to fulfill their functions as inhibitors of signal activation. Therefore, our computational approach serves as a useful addition to current experimental techniques for the quantitatively comparison of interactions across different members in the TNF and TNFR superfamily. It also provides a mechanistic understanding to the functions of TNF-associated cell signaling pathways.