key: cord-264489-h1n9ywbd
authors: Roy, Urmi
title: Insight into the Structures of Interleukin-18 Systems
date: 2020-07-31
journal: Comput Biol Chem
DOI: 10.1016/j.compbiolchem.2020.107353
sha: 
doc_id: 264489
cord_uid: h1n9ywbd

Structure-based molecular designs play a critical role in the context of next generation drug development. Besides their fundamental scientific aspects, the findings established in this approach have significant implications in the expansions of target-based therapies and vaccines. Interleukin-18 (IL-18), also known as interferon gamma (IFN-γ) inducing factor, is a pro-inflammatory cytokine. The IL-18 binds first to the IL-18α receptor and forms a lower affinity complex. Upon binding with IL-18β a hetero-trimeric complex with higher affinity is formed that initiates the signal transduction process. The present study, including structural and molecular dynamics simulations, takes a close look at the structural stabilities of IL-18 and IL-18 receptor-bound ligand structures as functions of time. The results help to identify the conformational changes of the ligand due to receptor binding, as well as the structural orders of the apo and holo IL-18 protein complexes.

Immunologically relevant proteins are critical for the functioning of cellular pathways.

Therefore, in the general contexts of target-based therapies and drug designs, it is necessary to fully understand how these proteins and their variants participate in the progressions of inflammatory, autoimmune and infectious human diseases (Kabat 1968; Voit 2014; Taylor et al. 2017 ; Gupta et al. 2019; Huang et al. 2019; Jang et al. 2019) . The task of gathering detailed knowledge about this topic can be aided to a large extent with residue-level structural analyses of immunologically significant proteins and their interaction with receptors (Moczydlowski 2013; Xiao et al. 2018; Yao et al. 2019) . This investigative approach assists in the proper identifications of therapeutic-targets, their structural-assemblies and consistent ligand-receptor interfacial interactions, and thus, plays a vital role in the development of new, innovative medicines (Freudenberg et al. 2002; Asbury et al. 2010; Haydarlou et al. 2016; Mariethoz et al. 2016; Janwa et al. 2019) . The present study of molecular dynamics (MD) simulation (Ho and Hamelberg 2018; Jin et al. 2020; Weako et al. 2020) , focusing on Interleukin-18 (IL-18), falls in this category of computational structural immunology. The main goal of this study is to explore the essential structural and conformational aspects of IL-18 ligand and ligand bound receptor systems.

IL-18, also known as interferon gamma (IFN-) inducing factor, is a pro-inflammatory cytokine. IL-18 induces T helper (TH) cells 1 and 2 responses, and IL-18 signal transduction J o u r n a l P r e -p r o o f cascade can also activate nuclear factor kappa beta (NF) (Mak and Saunders 2006) . IL-18, a member of interleukin-1 (IL-1) family, is similar to interleukin-12 , and is important for supporting the host defense (Dinarello 1999; Gracie et al. 2003) . IL-18 bridges the gap between innate and adaptive immune responses and is responsible for various inflammatory, autoimmune and physiological conditions, such as inflammatory bowel disease, psoriasis, sepsis, myocardial infarction, Crohn's disease, arthritis and cancer. The IL-18 first binds to the IL-18 receptor (IL-18R and forms a lower affinity complex. Upon binding with IL-18 receptor (IL-18Ra hetero-trimeric complex with higher affinity is formed, which initiates the signal transduction process and, triggers the NF-κβ, leading to a downstream transcription through mitogen-activated protein kinase (MAPK) signaling cascades (Kato et al. 2003; Ohnishi et al. 2012; Tsutsumi et al. 2014) . As reported by previous authors, IL-1Rrp, the main IL-18R, binds to IL-18, but not to IL-1β (Nakamura et al. 2000) . Kato et al. have described the first solution structure of IL-18 ligand (Kato et al. 2003) . This apo version of IL-18 is further modified by Tsutsumi et al. (Tsutsumi et al. 2014) . The ligand bound holo forms of IL-18/IL-18R are also elucidated by binding protein (IL-18BP) is a cell surface receptor that binds to and eventually leads to IL-18 neutralization (Dinarello et al. 2013) . A recent study by Krumm et al. has identified the conserved IL-18BP interfacial binding-region on human IL-18 (Krumm et al. 2008 ).

In recent years, inhibitor based therapies have shown great potentials for further developments in the pharma and biotech sectors (Vogt and Hofmann 2012; Boulaki et al. 2013; Zamiri et al. 2014; Gonzalez et al. 2015; Lin et al. 2017; Kwak et al. 2018) . The treatments of IL-18 related diseases may involve the use of selective or potent IL-18 ligand/-receptor inhibitors that would interfere with, or effectively block the targeted functions (Hamasaki et al. 2005;  J o u r n a l P r e -p r o o f Tsutsumi et al. 2019) . In our earlier papers we have described the structures and structure-related functional changes of several physiologically relevant proteins (Roy and Luck 2007; Roy 2016a Roy , 2016b Roy , 2017 Roy , 2019a Roy , 2019b Roy , 2020 . The present simulation study examines the structural stabilities of the ligand-protein, IL-18 and IL-18 receptor (IL-18R) bound ligand structures as functions of time. We analyze here the conformational changes within the ligand-protein, due to receptor binding and, we also identify the possible structurally ordered and disordered region within the apo and holo (ligand-bound) protein complexes.

All protein structures were collected from the Protein Databank (PDB) website (Berman et al. 2000) in the form of standard PDB files. For structural studies, we have used Nuclear Magnetic Resonance (NMR) and X-ray crystallographic structures of the human IL-18 ligand-protein 1J0S.PDB (Kato et al. 2003 ) and 3WO2.PDB, (Tsutsumi et al. 2014) . Additionally 3WO3.PDB and 3WO4.PDB, the X-ray crystallographic structures of IL-18 receptor bound IL-18 and the ternary signaling complex of IL-18 have been utilized (Tsutsumi et al. 2014 ). The 3F62.PDB, an IL-18 complex with IL-18BP of Ectromelia virus has also been briefly mentioned (Krumm et al. 2008 ). The resolution values for the X-ray structures 3WO2, 3WO3, 3WO4 and 3F62 are 2.33 Å, 3.10 Å, 3.10 Å and 2.00 Å respectively.

Nanoscale Molecular Dynamics (NAMD) and Visual Molecular Dynamics (VMD) programs were used for time-based simulations (Humphrey et al. 1996; Phillips et al. 2005) , and the J o u r n a l P r e -p r o o f aligned sequences were studied with Molecular Evolutionary Genetics Analysis (MEGA 7) (Kumar et al. 2016) . IL-18 interactome analyses were performed using the Cytoscope package (Shannon et al. 2003) , and 3D protein graphics were developed with Biovia Discovery Studio Visualizer, v16.1.0.15350 (Dassault Systèmes BIOVIA Discovery Studio Modeling Environment 2015) . The plots were constructed with Origin (OriginLab Corporation 2016).

The experimental simulation setup for IL-18 and IL-18/IL-18R were similar to those reported previously (Roy 2016a (Roy , 2016b (Roy , 2017 (Roy , 2019a (Roy , 2019b (Roy , 2020 . Based on the native/original protein, the protein structure file (PSF) along with a corresponding PDB structure was generated. The NAMD software required both the PSF and the modified PDB files as simulation inputs, and these files were created using the Automatic PSF Builder (autoPSF) graphical user interface (gui) of VMD. The topology file, PSF had all the structural information while the modified PDB file contained the predicted hydrogen atoms coordinates. The solvated and neutralized protein structures were obtained using solvate and ionize gui of VMD, where a 0.15mol/L concentration of NaCl was used for system neutralization.

Energy minimization for the system was performed in 10,000 steps using the NPT ensemble. The final production run was carried out for 20 ns at 298K using the NVT ensemble and employing the CHARMM force field. A combined version of CHARM22/CHARMM27/CMAP force field was used for this purpose. CHARM22 and CHARMM27 provided the necessary parameter files for the proteins as well as the lipids. The proteins were subjected to phi, psi cross term map (CMAP) corrections (a built-in feature of NAMD plugin gui); these force field parameter files were necessary to calculate the energies.

The periodic boundary condition with "Langevin on" control was applied in each case, with an "active" setting of particle mesh ewald (PME). The Langevin Damping was set to 1. The time steps were set to 1 femtosecond (fs), with 20 steps per cycle selected.

For the basic dynamics, the dielectric value was set to 1.0. The periodic cell basis and periodic cell center were selected according to the PDB coordinates. The time frames of each system were saved as "DCD" files. The output parameters, like DCD/XST output frequency, energy output frequency and restart file frequency, were chosen according to system specifications. Most of these parameters were kept at their default values incorporated in the NAMD gui. This simulation approach is based on the conformational sampling of the predominant (especially early-stage) structural changes of the four systems studied here (Chhatbar et al. 2019; Dimić et al. 2020 ). The computational protocol was designed to obtain the basic frameworks for the IL-18 ligand and the ligand bound holo structures. Additional computational details of the present work have been described elsewhere (Roy 2016a (Roy , 2016b (Roy , 2017 (Roy , 2019a (Roy , 2019b (Roy , 2020 . Table S1 has been included in the Supplementary Data (SD) to list the abbreviations of Fig.1 .

The PPI is one of the most valuable tools for identifying the ligand-receptor interactions and signaling cascades (Jiang et al. 2015; Wang et al. 2018 ). The results have been generated by Cytoscape, on the basis of experimental data, as well as manually curated results obtained using the Mentha database (Calderone et al. 2013) . Mentha compiles the proteins' key interaction data J o u r n a l P r e -p r o o f collected by International Molecular Exchange (IMEx) databases (Orchard et al. 2012 ) and

analyzes the experimental data with a thorough annotation. The interactions considered here are dominated by physical association (as those studied in affinity chromatography, two hybrid array and two hybrid prey pooling), direct interactions (pull down, cross-linking/molecular sieving/Xray crystallography/enzymatic study and two hybrid), physical interactions (biochemical) and

antitag co-immunoprecipitation. The confidence scores are based on a scale of 0 to 1 where these values reflect the number of functional PPIs curated by experimental procedures as well as based on data from scientific literature. Nonetheless there is always a possibility that a few interactions may be absent. The score between IL-18 and IL-18R1 interaction is 0.539, which is slightly higher than the usual upper bound of a "medium" range. The score near the range of 1 denotes many PPIs as published in scientific literature whereas lower range represents fewer experimental processes. The PPIs identified between IL-18 and IL-18R1 are primarily of physical/biochemical origins. The high affinity signaling complex IL-18/IL-18R initially activates toll like receptor (TLR) domains, which, via the recruitment of certain adaptor and recruiter molecules, ultimately trigger the NF and MAPK dependent pathways. Binding of IL-18BP to IL-18 leads to neutralization, and the IL-18/IL-18R signaling cascades are no longer induced (Kimura et al. 2008; Krumm et al. 2008; Dinarello et al. 2013) .

The biological sequence alignment between IL-18/IL-1 and IL-18R1/IL-1R type 1 and 2 are (Kato et al. 2003; Yamamoto et al. 2004; Tsutsumi et al. 2014 ). The alignment schemes presented here (Figs. S1 and S2) follow the format used by them. These multiple sequence alignments are generated using the clustal omega (clustalW) algorithm (Sievers et al. 2011 ) of MEGA software, (Kumar et al. 2016 ) along with the incorporation of the Blocks Substitution Matrix (BLOSUM) (Henikoff and Henikoff 1992 (Yamamoto et al. 2004 ). In IL-1 the S-glutathionylation of a highly conserved Cys residue is considered as a therapeutic target (Zhang et al. 2017) . At this time, the possibility of utilizing the conserved IL-18 or IL-18R

Cys residues as potential drug targets for various infectious or chronic diseases remains a subject of future investigations. ligand-protein (Kato et al. 2003) . This is a single subunit protein that mostly contains sheets.

The undefined loop structure in 1J0S consists of residues 34-42. Fig. 4A (Kato et al. 2003 ). These residues have been highlighted in a "green stick" mode within the primary interactions site of IL-18 and the IL-18 bound receptor structures.

3WO2 is the X ray crystal structure of wildtype (wt) IL-18 ligand-protein (Tsutsumi et al. 2014 SD Table S3 .

The X ray crystal structure of the IL-18 signaling complex, 3WO4, is displayed in Fig. 4D (Tsutsumi et al. 2014 ). This core signaling complex consists of a ternary structure of IL-18 4D . These primary site III residues have also been highlighted accordingly in SD Table S4 .

3F62, an IL-18 complex with the IL-18 binding protein (IL-18BP) of Ectromelia virus is displayed in Fig. 4F . This structure of 3F62 has been described by Krumm et al. (Krumm et al. 2008 ). Part of the IL-18R resembles IL-18BP and thus, the binding of IL-18BP with IL-18 blocks the interactions between IL-18 and IL-18R (Krumm et al. 2008 Buried Cys residues play a leading role in determining the protein's structural stability, since buried Cys residues are usually embedded within a protein's hydrophobic core. Being surrounded by various hydrophobic and aromatic residues they form hydrophobic and other nonbonded interactions and thus make the protein structure more compact and stable. In 3WO3/3WO4, most of the Cys residues and disulfide bridges of IL-18 and IL-18R receptor chains are buried, and hence, are subject to the aforesaid stability criterion. In the 3WO4: IL-18Rsubunit, however, the Cys residues and some of the disulfide bridges are mostly surfaceexposed. In our previous paper, we have addressed the Cys residue stability resulting from metal binding or structural effects (Roy and Luck 2011) . Here, our goal is to examine how disulfide connectivity increases the overall stability in a protein complex. Previous authors explored the possibility of mutating Cys (SH) to increase the overall stability of a protein (Yamamoto et al. 2004 ).

To check the overall efficacy of the 3D models, the initial protein structures were assessed.

Ramachandran plots for the initial structures used in MD simulation are depicted in SD Fig S3. These plots illustrate the favored, allowed and disfavored distributions of phi (φ)/psi (ψ) dihedral angles. The structural evaluations of these figures ensure that most residues are within the J o u r n a l P r e -p r o o f favored and allowed region (Lovell et al. 2003) . Overall, these plots indicate the effectiveness of the 3D structures; further details are explained in the SD. greater (3.16Å) than 3WO2 (2.47Å). The first 0.6 ns of the simulation was skipped for averaging as initial sampling indicated a steep rise owing to the process of protein-unfolding. These observations gathered from plot 6A lead us to conclude that, apo ligand 3WO2 is more stable than 1J0S. The undefined loop structure and Cys (-SH) residues in 1J0S make this structure less stable. Four Cys (-SH) residues also exist in 3WO2, where the Cys76 and Cys127 species support sulfur-pi interactions with Tyr120 and Phe134, respectively. These sulfur-pi interactions are absent in 1J0S. Though the Cys127-Phe134 pair involves pi-alkyl interactions in both cases.

Although some minor variations are observed in 3WO2 loop, overall it maintains a stable nature.

The partial conversion of turns into -helices in 3WO2 strengthens and stabilizes this structure.

The undefined loop region in 1J0S is relatively less stable. For the ligand bound ternary structure 3WO4, the  receptor exhibit strong RMSD variations compared to those of the ligand and receptor structures (data not shown). The larger interfacial regions of the  receptor (both with ligand and the  receptor) most likely boost the latter's stability, because the stronger inter-subunit interactions operate in these regions. The existence of three Cys residues in the  receptor could be attributed to the latter's unstable nature. The presence of surface exposed Cys in the IL-18R receptor chain may also be accountable for the -chain's higher instability. It is possible that, these fluctuations in the  J o u r n a l P r e -p r o o f receptor (Fig. 6B ) cause the overall instability of the ligand bound receptor's trimeric structure (Fig. 6A) . SD Fig. S5 shows the superposed Cys and the disulfides within the IL-18 systems. A change from 3-10 helices to turn is observed around residues 41-44, within the ligand bound form of the 3WO3 ligand. Like the case of 3WO2, in the 3WO3 ligand, the residues around 76-81 also persistently change from 3-10 helical structure to turn. Aside from this, no other major changes are observed in this case, and overall the ligand in 3WO3 seems slightly more stable than that of 3WO2. The receptor residues 256-261 and 282-295 in the linker-turn region of 3WO3 show a few changes from turn to coils and 3-10 helices respectively.

Nevertheless, within the receptor structure, the prominent loop region 207-215 seems rather stable. It is likely that, the protein-protein inter-subunit interactions act to stabilize this loop.

From the structure of 3WO3 it is also clear that the IL-18 fits very well within the typical ligand binding pocket by surrounding receptor domains. Certain accommodative arrangements taking place between the ligand and the receptor's three different domains may make the corresponding region further stable.

It is also evident from Fig. 8 that, the ligand is a bit more stable in the receptor bound form of 3WO3, as compared to the corresponding case of the apo structure 3WO2. The secondary structure of 3WO4 ligand has an approximately comparable or marginally higher stability with respect to that of the 3WO3 ligand. However, the 3WO4 ligand residues 66-71

show some additional variability from -sheets to turns. Nevertheless, the changes that are observed around residue 56 in 3WO3 ligand are absent here. The secondary structural changes of the ligand within the ligand bound receptors are plotted in SD Fig. S8 . From Figs. 8 and S8, it is evident that, the ligand is more stable within the receptor-bound forms than in its apo form, and that correspondingly, fewer conformational changes occur within the ligand of 3WO4 upon receptor binding. The IL-18 in 3WO4 is somewhat more stable than 3WO3, even though the overall stability in 3WO3 is higher than that of 3WO4; the relatively higher interfacial intersubunit interactions present in 3WO4 ligand may be responsible for this higher stability.

The maximum changeability in the secondary structure is observable in the C subunit Furthermore, along with several other cytokines, IL-18 can be used as adjuvants with HIV and several other vaccines (Bradney et al. 2002) . In recent years, due to outbreak of SARS-CoV-2 pandemic, considerable attentions have been directed towards the immunity development against viral pathogens. The present paper demonstrates that, IL-18 itself is a structurally steady protein and that it can retain this stability over a relatively extended time-scale. This observation points at the potential use of IL-18 as an adjuvant for antibody generation and immune enhancement, which, in turn could facilitate future strategies to develop novel treatments for communicable viral diseases.

The computational results presented in this work describe a set of residue-level analyses of the IL-18 systems based on their published structures. This investigation also explores the PPIs between the IL-18/IL-18R and the IL-18/IL-18BP systems, and notes the relevance of the findings. The time-based structural stabilities of IL-18, in both its apo and ligand bound holo forms have been measured using MD simulation. The results show that, the ligand is somewhat more stable in its receptor bound structures. The ligand bound receptor monomer 3WO3 has been found to be somewhat more stable than the ligand bound receptor dimer 3WO4. The immunological significance of IL-18 signaling is rooted in the fact that, IL-18 is related to numerous autoimmune and inflammatory diseases, and that the interruption of IL-18/IL-18R signaling cascades impact the development of anti-inflammatory drugs/drug-targets.

Additionally, IL-18 upregulates Fas ligand and interferon gamma (IFN-) leading to the process J o u r n a l P r e -p r o o f of apoptosis or cell death. IL-18 biologics may be relevant also in the contexts of immunity enhancement approaches. Thus the detailed identification of the ligand/receptor interfaces of this protein, and subsequent identification of targeted-therapy based on computer modeling efforts, as those discussed in this paper, could be helpful in the development of predictive immunotherapy and precision bio-therapeutics.

The author has attached all high resolution figures (Figs 1 to 9 and graphical abstract) as Zip files.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

The author declares no conflict of interest. (residues 35-40) that turned into a helical structure has been shown in a different color, grey. E.

highlight the main interacting residues, the secondary structures in Fig. 4 have been are presented in the line diagrams. 

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