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# Conformational and binding mode assessment of the human IL-3 recognition by its alpha receptor

Jade Fogha, Alexandre G de Brevern, Julien Diharce

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Jade Fogha, Alexandre G de Brevern, Julien Diharce. Conformational and binding mode assessment of the human IL-3 recognition by its alpha receptor. Proteins - Structure, Function and Bioinformatics, 2023, 91 (7), 10.1002/prot.26476. hal-05500041

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# Conformational and binding mode assessment of the human IL-3 recognition by its alpha receptor

Jade Fogha ID

Alexandre G. de Brevern ID

Julien Diharce ID

Université Paris Cité and Université des Antilles and Université de la Réunion, INSERM, Biologie Intégrée du Globule Rouge, UMR_S 1134, DSIMB, Paris, France

**Correspondence**

Alexandre G. de Brevern and Julien Diharce, Université Paris Cité, INSERM UMR_S 1134, 8 Rue Maria Helena Vieira da Silva, 75014 Paris, France.

Email: alexandre.debrevern@univ-paris-diderot.fr; julien.diharce@inserm.fr

**Funding information**

CINES; Labex Gr-Ex, Grant/Award Number: ANR-11-LABX-0051; French National Research Agency, Grant/Award Number: ANR-19-CE17-0021; GENCI (Grand Equipement National de Calcul Intensif), Grant/Award Number: A0090711986

**Abstract**

Protein-protein interactions (PPIs) are attractive targets as they are critical in a variety of biological processes and pathologies. As an illustration, the interleukin 3 (IL-3) and its α subunit receptor (IL-3Rα) are two proteins belonging to the cytokine or receptor βc family and are involved in several disorders like inflammatory diseases or hematological malignancies. This PPI exhibits a low binding affinity and a complex formed by a mutant form of IL-3 (superkine) and IL-3Rα have emerged from the literature, with an increase of the affinity. Therefore, in this study, we performed molecular dynamics simulations and binding energy calculation in order to evaluate protein dynamics and to characterize the main interactions between IL-3 and IL-3Rα, considering both wild-type and mutant. First, in the case of IL-3Rα/IL-3 wild-type complex, IL-3Rα can adopt three different conformations essentially driven by NTD domain, including the open and closed conformations, previously observed in crystal structures. Additionally, our results reveal a third conformation that has a distinct interaction profile that the others. Interestingly, these conformational changes are attenuated in IL-3Rα/IL-3 mutant complex. Then, we highlighted the contribution of different residues which interact principally with IL-3 or IL-3Rα conserved region. As for the mutated residue at position 135 of IL-3, other residues such as IL-3 E138, IL-3 D40, IL-3Rα Y279, IL-3Rα K235, or IL-3Rα R277 seem important for a low or a high binding affinity. Altogether these findings yield new information that could be exploited in a drug discovery process.

**KEYWORDS**

binding free energy, MM-PBSA, molecular dynamics simulations, molecular modeling, protein-protein interactions

**Abbreviations:** 3D, tridimensional; AML, acute myeloid leukemia; BPDCN, blastic plasmacytoid dendritic cell neoplasm; CSF, colony stimulating factor; FDA, food and drug administration; GM-CSF, granulocyte-macrophage colony stimulating factor; GMRα, granulocyte-macrophage colony stimulating factor receptor α; IL-3, interleukin-3; IL-3Rα, interleukin-3 receptor α; IL-5, interleukin-5; IL-5Rα, interleukin-5 receptor α; JAK, Janus tyrosine kinase; MM-PBSA, molecular mechanics Poisson-Boltzmann surface area; N<sub>eq</sub>, equivalent number or protein blocks; NTD, N-terminal domain; PB, protein block; PC, principal component; PCA, principal component analysis; PPI, protein-protein interaction; RMSD, root mean square deviation; RMSF, root mean square fluctuation; SASA, solvent accessible surface area; STAT, signal transducers of activated T; WT, wild-type.

## 1 | INTRODUCTION

Multi-colony stimulating factor (CSF), Mast cell growth factor or Multi-lineage growth factor are different names attributed to the interleukin 3 (IL-3) over the years.¹ All these alternatives names reflected its various impact on different lineages of hematopoietic cells, such as mast cells and basophils,²,³ as a growth, differentiation,

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

© 2023 The Authors. *Proteins: Structure, Function, and Bioinformatics* published by Wiley Periodicals LLC.
<figure><img src="image_3.png" /><figcaption>**FIGURE 1** IL-3 and IL-3Rα proteins. 3D structures and schematic representation of (A) human IL-3 and (B) human IL-3Rα both taken from PDB ID: 5UV8. (C) A general view of the IL-3Rα/IL-3 interaction and (D) a zoom over the predicted conserved or hot regions represented with dots. These conserved residues are R128~C, T131~C, and F132~C of IL-3, and S203~C, F232~C and N233~C of IL-3Rα (the “c” character designates a conserved residue). Disulfide bridges are represented using spheres. D2, D3, domains 2 and 3; ECD, extracellular domain; ICD, intracellular domain; NTD, N-terminal domain; SP, signal peptide; TM, transmembrane; α1, A, B, C, and D, α helices. *IL-3 mutated position 135.</figcaption></figure>

activation or survival factor. Beyond the immune system, these cellular functions can be extended to other biological systems like the nervous and vascular ones.⁴ As a cytokine, IL-3 biological activities are mediated by the presence of its receptor, which is expressed on the target cell surface. The IL-3 receptor comprises two different subunits: IL-3 receptor α (IL-3Rα or CD123) and the so-called common β (βc or CD131) receptor.⁵ The presence of two distinct subunits indicated a complex signalization process. In fact, IL-3 firstly binds to IL-3Rα before the recruitment of the βc dimer. These consecutive steps form a multimeric complex, which activate a downstream signalization

through different pathways like Janus tyrosine kinase (JAK)—Signal transducers of activated T (STAT) pathway.⁶

IL-3 and IL-3Rα are members of the βc cytokine family and receptor cytokine family respectively.⁷,⁸ The βc cytokine family is a subfamily of the type I cytokine glycoprotein family, characterized by four helical bundle, namely α-helix A to D (see Figure 1B). It includes also interleukin-5 (IL-5) and granulocyte-macrophage colony stimulating factor (GM-CSF). The associated βc receptor comprises heterodimeric glycoproteins: an α subunit and the shared βc subunit as described earlier.⁵ The α receptor subunit also comprises IL-5Rα or CD125 for
IL-5 and GMRα, CSF2Rα or CD116 for GMCSF. They are transmembrane proteins; their extracellular part is divided into three fibronectin type III (FnIII) domains that formed β-sandwich structures: the N-terminal domain (NTD) followed by the D2 and D3 domains (see Figure 1A). Each domain is made up of β strands (from A to G in Figure 1C). As those βc receptors share a common signal transducing receptor, their biological activities are regulated through a similar mechanism. However, IL-3Rα/IL-3 interaction, the initial step of the signaling process, displays a lower affinity (~100–200 nM) compared to other family complexes (IL-5Rα/IL-5, ~1–2 nM, and GMRα/GM-CSF, ~2–10 nM).⁹ Mutagenesis studies have highlighted a superkine from literature which corresponds to the cytokine with a Lysine to Tryptophan mutation (K135W), resulting in an increased binding affinity for IL-3Rα.¹⁰,¹¹

Recently, the IL-3Rα/IL-3 interaction became an important target in therapeutic research since this protein-protein interaction (PPI) is associated to various human disorders.¹²⁻¹⁴ Indeed, IL-3Rα is overexpressed in hematological malignancies like acute myeloid leukemia (AML) or blastic plasmacytoid dendritic cell neoplasm (BPDCN).¹⁵ IL-3 amplifies inflammation response in murine sepsis and high plasma levels of IL-3 are related to high mortality in human sepsis.¹⁶ IL-3 promotes activation of basophils that are involved in pathogenesis of allergic diseases.¹⁴,¹⁷,¹⁸

Given the relevance of IL-3Rα/IL-3 complex as therapeutic target, different studies have been conducted on this system. Crystal structures of those proteins, alone or in a complex form have been resolved.¹⁹⁻²² The tridimensional (3D) structure of IL-3Rα with the blocking antibody CSL362, reveals that the receptor has a wrench-like conformation with two possible forms: closed and open (Figure S1).¹⁹ In the former, the angle between NTD and D2 is about 55° allowing for instance a van der Waals (vdW) interaction between A72 and F199. The open complex has its NTD and D2 domains more distant (angle about 95°). The 3D structure of IL-3Rα/IL-3 complex shows that the NTD, D2 and D3 domains also have a wrench-like conformation around IL-3 (see Figure 1C). In a preliminary study, we carried out a sequence and structure analysis of IL-3 wild-type (WT) and K135W, IL-3Rα, and others family members through an evolutionary point of view.²³ We pinpointed the high conservation of the cytokine or receptor structural architectures across evolution, using multiple sequence alignments including human and other species, and within the βc family members. Moreover, the IL-3Rα/IL-3 interface has been characterized as a large interface involving the NTD domain in one side, and the D2-D3 domains in the other. Among interfacing residues, only few ones belonging to D2-D3 are evolutionary conserved and can be dispatched into two potential conserved or hot regions (see Figure 1D).

In this study, we pursued the investigation of IL-3Rα/IL-3 interaction focusing on protein dynamics and the understanding of binding affinity, by using molecular dynamics (MD) approaches to go beyond structure and sequence. To achieve our goal, classical MD simulations were performed on the human IL-3Rα/IL-3 complex as well as the unbound human IL-3Rα and IL-3. The impact of the superkine

(K135W mutation on IL-3) and therefore, of the binding affinity enhancement, was explored.

## 2 | MATERIALS AND METHODS

### 2.1 | Simulation systems

In this study, we were interested in various systems surrounding IL-3 and its receptor IL-3Rα. Therefore, we evaluated the human IL-3Rα/IL-3 complex as well as the mutated complex human IL-3Rα/IL-3 K135W. We also considered apo state of these different complexes. For MD simulations, initial coordinates of these proteins, human IL-3 (PDB ID: 1JLI,²⁴ human IL-3Rα/IL-3 wild-type complex (PDB ID: 5UV8⁹), human IL-3Rα/IL-3 K135W complex (PDB ID: 5UWC⁹) were retrieved from the Protein Data Bank (PDB)²⁵ (www.rcsb.org–Table S1).

Some refinements were realized for the study based on UniProt reference sequences (Table S1). First, protein sequences in all crystal structures were renumbered to fit the numbering of the reference sequence. It is important to notice that a different sequence enumeration may be found in literature, since the mutated position 135 might be 116. Engineered mutations found in crystal structure (Table S1) were reverted, thanks to SCWRL tool²⁶ in PyMOL.²⁷ An exception was made for the K135W mutation present in the chain I of the human IL-3 Rα/IL-3 K135W complex (PDB ID: 5UWC) as this mutation enhanced receptor binding affinity.¹⁰,¹¹ In order to complete the structure of non-solved residues and fill the gaps in structures, unresolved residues were rebuilt with Modeler 9.17.²⁸

### 2.2 | System preparation

pK values of ionizable groups were calculated at a pH of 7.4 and hydrogen atoms were added to the different structures using H⁺ system version 3.2 (http://biophysics.cs.vt.edu/H⁺).²⁹ Then, structures were prepared with the solution builder tool of CHARMM-GUI webserver (https://www.charmm-gui.org/).³⁰ During this preparation, proteins were solvated in a rectangular box of explicit TIP3P water molecules with edges at least 10 Å from the protein. Na⁺ and Cl⁻ ions at 0.15 M were added to neutralize the system.

### 2.3 | MD simulations

Classical MD simulations were carried out on the different systems using GROMACS software version 2019.1³¹ with the CHARMM36m force field.³² Initially, the energy of solvated structures was minimized during 10 000 cycles of steepest descend algorithm that was dismissed when the overall force was lower than 1000 kJ mol⁻¹ nm⁻¹. The equilibration stage was performed in different steps. Firstly, the
minimized system was heated to 300 K and then equilibrated with a timestep of 2 fs during 100 ps under NVT conditions (constant volume and temperature). Positional restraints of 400 kJ mol⁻¹ nm⁻¹ on backbone and 40 kJ mol⁻¹ nm⁻¹ on side chain atoms were applied. In the following step, the same equilibration step was applied but under NPT conditions (constant pressure and temperature). Then, in four NPT equilibration steps, positional restraints were gradually decreased until they were canceled. The Nosé-Hoover temperature coupling was used to maintain a constant temperature. The pressure was set to 1 bar using a Parrinello-Rahman barostat with a coupling constant of 5 ps and a compressibility of 4.5 e-05 bar⁻¹. All bonds involving hydrogen atoms were restrained using LINear Constraint Solver (LINCS) algorithm. Long range electrostatic interactions were computed using the Particle-Mesh Ewald (PME) method with a cut-off about 12 Å. At the same time, the vdW energies were smoothly switched to zero between 10 and 12 Å. Trajectories were saved during 1 µs production stage under NPT conditions with a timestep of 2 fs. Three independent production runs with random initial velocities were performed for each system.

## 2.4 | Analysis of MD trajectories

For all systems, trajectories were centered in the periodic box and concatenated to reach a total of 3 µs of simulation (30 000 frames), using standard GROMACS tools.

Root mean square deviation (RMSD) and root mean square fluctuation (RMSF) were computed along 30 000 frames using python scripts with MDAnalysis library version 1.0³³ RMSDs on Cα atoms of the overall protein or specific protein domains were computed. Fluctuations of Cα atoms were also evaluated through RMSF.

Protein Blocks (PBs) were also used for analysis purpose. PBs are structural elements for the description of local structures of proteins.³⁴,³⁵ There are 16 independent PBs (from a to p), each assigned to a structure type like central α-helix, terminal α-helix, or coil. The PBxplor tool³⁶ were used to compute a density map of PBs along protein sequences and the equivalent number of PBs (Neq) which is a local measurement of deformability or local flexibility.²⁷ Neq allows a fine description of local protein dynamics as follow: rigid (Neq of 1.0), flexible (Neq of 4.0), high flexible (Neq of 6.0) and disorder (Neq of 8.0 and higher).³⁷

Principal components analysis (PCA) was performed using MDA-analysis library version 1.0 in Python version 3.4 and trajectory containing 3000 over the initial 30 000 snapshots were projected onto the principal component 1 and 2 (PC1 and PC2).

Contacts displayed during the simulation were analyzed using CONAN tool.³⁸ Contact maps were generated for all systems with a stride of 1 ns and three different cutoff values have been selected. A main cut-off distance value of 12 Å beyond which any residue pair is ignored. An “inter” cut-off value of 5 Å under which interactions are formed and a “high inter” cut-off of 10 Å that marked the disruption of interactions. k-medoid clustering of the trajectories based on the RMSD between contact maps were also carried out.

## 2.5 | Binding energy

Binding free energy for the WT IL-3 and K135W systems were estimated using the Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) approach with the tool gmx_MMPBSA version 1.4.3.³⁹,⁴⁰ To better represented closed, open and alternative-open conformations, different trajectories were selected according to the distance variation between contact patches (A72-F199, A72-R146—Figure S2) obtained previously during contact analyses of NTD and D2 IL-3Rα domains. Then, for the WT, MM-PBSA based analysis was performed on a first trajectory from 1450 to 1650 ns (closed), a second from 2250 to 2450 ns (open) and a last one from 2800 to 3000 ns (alternative-open), each of them with a time step of 1 ns (that always correspond to 200 frames). Additionally, MM-PBSA based analysis was performed from 1800 to 2000 ns for the IL-3Rα/IL-3 K135W system representing a closed conformation. In theory, binding free energy of protein-protein interaction can be expressed as follow:

$$ \Delta G_{binding} = G_{complex} - (G_{protein1} + G_{protein2}) $$

where the total free energies of the complex as well as the isolated proteins are considered. Each individual entity can have a free energy determined by:

$$ G_x = E_{MM} + G_{solvation} - TS $$

$E_{MM}$ is the molecular mechanics potential energy in vacuum. As we used a single trajectory approach, bonded interactions are taken to zero and then molecular mechanics components only consider the nonbonded interactions van der Waals and electrostatic ($E_{vdW} + E_{elec}$). $G_{solvation}$ refer to the free energy of solvation which is divided into the polar solvation ($G_{polar}$) and non-polar solvation ($G_{non-polar}$) terms. The polar or electrostatic term is estimated by solving the Poisson-Boltzmann equation with the dielectric constant of solute and solvent set to 2 and 80, respectively, and 0.5 Å grid resolution. The non-polar or non-electrostatic solvation term was calculated using the solvent accessible surface area (SASA) model as $γ(SASA) + b$, with the coefficient related to surface tension of the solvent or $γ = 0.00542 \text{ kcal mol}^{-1} \text{ Å}^{-2}$, the fitting parameter $b = 0.92 \text{ kcal mol}^{-1}$ and the water probe size of $1.4 \text{ Å}$.⁴¹ The energy contribution of residues to the binding were also estimated including residues that are less than 6 Å between the receptor and the cytokine or superkine. We consider a residue to be important to the interaction if it contributes $≤ -2 \text{ kcal mol}^{-1}$. One must note that we decide here to not take into account the entropic term of the calculation, since our goal is to extract insights of residues of importance for the interaction. By consequent, our $ΔG_{binding}$ from above is in fact similar to the enthalpic term $ΔH$.

## 2.6 | Graphic generation

Visualization and graphics were made using VMD version 1.9.4⁴² and PyMOL version 2.3.4 programs. Data plots were generated with Matplotlib library version 3.3 in Python version 3.8.
3 | RESULTS

3.1 | The structural architecture of IL-3Rα/IL-3

IL-3 and IL-3Rα are proteins that present structural specificities. The cytokine has four principal α helices A to D with an additional one, named α1, between A and B helices. The extracellular part of IL-3Rα is mainly constituted by β-strands arranged into NTD, D2, and D3 domains (see Figure 1). These three domains are separated by hinge regions with loops and a disulfide bond is present between C76 of NTD and C195 of D2. MD simulations were performed on these two apo proteins and their complex form, wild-type (WT) and mutated (K135W) (Figure S3, Table S1). To evaluate the protein local structure sampled during the simulation, the equivalent number of PBs (N<sub>eq</sub>) were employed. N<sub>eq</sub> described a rigid (N<sub>eq</sub> of 1.0), flexible (N<sub>eq</sub> of 4.0), high flexible (N<sub>eq</sub> of 6.0) and disorder (N<sub>eq</sub> of 8.0 and higher) local

structure.³⁷ In the case of IL-3 apo, flexible regions were detected in loop between C and D helices (loop C-D) and high flexible to disorder regions were found between A and α1 helices (Figures 2D and S4). Regarding IL-3Rα apo, except for the C-terminal, high N<sub>eq</sub> are not found, although NTD contains the largest number of flexible residues (N<sub>eq</sub> around 3 or 4—see Figure 2). These observations are also found using the root mean square fluctuation (RMSF) (Figures 2C and S4,S5).

The complex formed by IL-3 and IL-3Rα has been crystallized (PDB ID 5UV8). High B-factor values are observed at IL-3Rα and IL-3 protein extremities (see Figure 2B) and are associated to flexible atoms or regions. Elevated B-factors are also observed in loop C-D of IL-3 and in many NTD and D3 residues of IL-3Rα. To confirm those results, N<sub>eq</sub> and RMSF analyses were performed on MD simulations of this complex. Once again, protein extremities are the most flexible regions and other residues of both proteins scarcely reach a N<sub>eq</sub> value

<figure><img src="image_4.png" /><figcaption>**FIGURE 2** Mobility and flexibility of IL-3Rα/IL-3 complexes. (A) The equivalent number of protein blocks (N<sub>eq</sub>), average values computed for the 3 replicates of MD simulations. 3D structures of human IL-3Rα/IL-3 complex taken from PDB ID: 5UV8 represented via (B) B-factor, (C) RMSF, and (D) N<sub>eq</sub>. Values are ranked from the lowest (blue and thin tube) to the highest one (red and thick tube). D2, D3, domains 2 and 3; IL-3Rα apo, unbound IL-3Rα; IL-3Rα “WT,” IL-3Rα bound to IL-3 wild-type; IL-3Rα “K135W,” IL-3Rα bound to the mutated IL-3α1; NTD, N-terminal domain; A, B, C, and D, α helices.</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>**FIGURE 3** NTD and D2 contacts on IL-3Rα/IL-3. (A) IL-3Rα structure oriented towards NTD and D2 domains shows the different contact patches named i (loop A-B of NTD), ii (loop E-F of NTD), i' (from β-strand C to β-strand D of D2), ii' (β-strand F of D2), iii' (β-strand G of D2). (B) Contact maps of the total interaction existence time between NTD and D2 domains. Contact patches are also indicated. Secondary structure labels are underlined. D2 and D3, domains 2 and 3; NTD, N-terminal domain.</figcaption></figure>

of 4 (see Figures 2A,D and S2,S5). The IL-3Rα NTD contains the largest number of flexible residues ($N_{eq}$ value around 3 and 4—see Figure 2A,D) and appear to be a mobile domain (RMSF values can be above 8 Å— Figures 2B and S5).

Finally, the helices and strands that form protein fold are generally rigid in IL-3 apo, IL-3Rα apo and in IL-3Rα/IL-3 complex, except in NTD domain in which there are strong fluctuations along the trajectory. IL-3Rα apo and IL-3Rα in complex have similar RMSF and $N_{eq}$ simulation profiles (see Figures 2A and S5). However, the NTD mobility seems amplified in the unbound receptor (IL-3Rα apo—Figure S5). The comparison of IL-3 apo and IL-3 in complex highlighted that the binding of IL-3 to its receptor attenuated the fluctuation of the region between A and α1 helices.

## 3.2 | Conformational changes on IL-3Rα/IL-3

In the literature, two different IL-3Rα conformations have been described based on crystal structure of the IL-3Rα complexed with the CSL362 antibody: open and closed.⁹,¹⁹ These conformations were defined by the presence or absence of interaction between the loop

E-F of NTD and β-strand G of D2, in particular, a hydrogen bond between S74 of NTD and D197 of D2, and vdW interaction between A72 of NTD and F199 of D2 (see Figures 3A and S1). In order to analyze conformational changes into the IL-3Rα/IL-3 complex during MD simulations, contacts between the flexible NTD domain and the D2 domain were analyzed. These results based on contact analysis are consistent with the literature, meaning that we retrieved the open and closed forms described by the crystal structures. Indeed, during 3 µs (i.e., the concatenation of all three trajectories), contact numbers between Cα atoms of these two domain residues changed considerably (Figure S6). The number of contacts between NTD and D2 ranged from 15 to 20 in one stage of the simulation and fall to 0–5 in another. Analysis of the interaction existence time between NTD and D2 (see Figure 3) pinpointed different patches in the structure, which could be added to complete the definition of the open and closed conformation of IL-3Rα. In NTD, two regions can be distinguished: (i) the loop between the β-strand A and B or loop A-B (residues 32–38); (ii) the loop E-F (residues 70–80). On the opposite side, we observed three D2 regions: (i') the β-strand C and the loop C-D (residues 136–150); (ii') the β-strand F (residues 180–188); and (iii') the β-strand G with a part of the loop F-G (residues 191–200).
<figure><img src="image_6.png" /><figcaption>**FIGURE 4** NTD motions along MD simulations. (A) Global NTD motions of IL-3Rα/IL-3 complex taken from PDB ID: 5UV8 and illustrated by 150 snapshots from 3 µs MD simulations corresponding to the total of the 3 independent runs. NTD allowed the receptor opening and shutting on the left side and described a perpendicular movement on the right side. (B) Cluster analysis of trajectories based on NTD and D2 contacts over the simulation. Each cluster was related to a conformational state (open, closed, or alternative-open) and the cluster population was mentioned in term of percentage. Center or representative structures of the different clusters were also shown. Disulfide bond residues and contact patches are represented with spheres. Cα distances are mentioned in Å. (C) Distance evolution of Cα contact patches of IL-3Rα/IL-3 WT (PDB ID: 5UV8) complex over 3 µs simulation trajectory. (D) Distance evolution of Cα contact patches of IL-3Rα/IL-3 K135W (PDB ID: 5UWC) complex over 3 µs simulation trajectory. The dotted lines mark the separation for the three independent runs.</figcaption></figure>
Contacts between the loop E-F of NTD (ii) and β-strands F and G of D2 (ii' and iii' respectively), including the disulfide bond between NTD C76 and D2 C195, are more persistent during all the simulation (80%–100%), while others (i-i', i-ii', and ii-i' contacts in Figure 3B) are occasional (20%–40%–see Figure 3). Thus, due to the loss of certain contacts between the two domains, NTD can be near (closed conformation) or distant to D2 (open conformation).

According to simulations, motions of IL-3Rα are not restraint to the opening and closing of the NTD regarding D2. Intriguingly, as seen in Figure 4A, in addition to the opening and closing (left side), another global motion is recorded (right side) that is perpendicular to the first one. The projection of concatenated trajectories along principal component 1 and 2 (PC1 and PC2) during a dimensionality reduction analysis (principal component analysis or PCA) shows three distinct groups of conformations; PC1 and PC2 explaining about 68% of the variance (Figure S7).

Furthermore, cluster analyses (see Figures 4B and S8) indicate that IL-3Rα taken from the complex can be divided in three types of conformations depending on NTD-D2 contacts and their two principal motions during the simulations illustrated in Figure 4A. As presumed, the cluster 1 in Figure 4B indicates that the loop E-F of NTD (or patch ii) and β-strand G of D2 (or patch iii') are close while in cluster 0, they are distant. Indeed, the Cα distance between A72 (patch ii of NTD) and F199 (patch iii' of D2), vary along the simulation as the two residues can be at a distance less than 10 Å or higher than 12 Å (Figure 4C). In open conformations, only the disulfide bond remained as contact between NTD and D2. One can notice that in crystal structure of the IL-3Rα/CSL362 complex, the Cα distances between A72 and F199 are 6.6 Å and 12.9 Å for closed and open forms respectively (Figure S1). We also found cluster (see cluster 2 in Figure 4B) in which the patch ii of NTD is far away from the patch iii' of D2, except for the disulfide bond, but get closer to another contact patch, i' or the loop C-D of D2. For instance, from 2600 to 3000 ns in Figure 4C, the Cα distance between A72 (patch ii of NTD) and R146 (patch i' of D2) is generally lower to 10 Å. At the same simulation period, the Cα distance between A72 (patch ii of NTD) and F199 (patch iii' of D2) is up to 12 Å. Neither the open crystal structure of the IL-3Rα/CSL362 complex, nor the closed one, has this contact between A72 and R146 (14.9 Å and 15.3 Å for the closed and open forms respectively– Figure S1). Therefore, according to MD simulations of complex systems, IL-3Rα adopts open and closed conformations (~22% and ~37% respectively) but also a third one which we refer as an “alternative-open” conformation, in a greater proportion (~39%). Closed conformations are defined by the proximity between the loop E-F of NTD (A72) and the β-strand G of D2 (F199). In open conformations, the two contact patches are partially far away as well as the loop E-F of NTD (A72) and the loop C-D of D2 (R146). In alternative-open conformations, the loop E-F of NTD (A72) drift to nullify contacts with a part of the β-strand G of D2 (F199) and to establish new ones with the loop C-D of D2 (R146). As our simulations always starts with closed conformation, we observed that the receptor can conserve this conformation (run 2 in Figure 4C) or adopt the open conformation followed by the alternative-open one (runs 1 and 3 in Figure 4C). Even

starting with an open form complex, IL-3Rα finally switches to an alternative-open conformation (Figure S14). Interestingly, a conformation of IL-3Rα/IL-3 complex with a contact pattern consistent with the alternative-open conformation can persist for 1 µs of simulation (Figure S13), suggesting that we are facing a potential conformational state that can be located in a free energy basin.

Those motions between NTD and D2 have an impact on the binding of IL-3Rα and IL-3. We have previously determined that NTD binds to IL-3 through different interaction, such as a hydrogen bond between the main chain of A72 (loop E-F or patch i of NTD) and a residue of α1 helix of IL-3 conserved during evolution (E62c—the “c” character designates a conserved residue in the manuscript).<sup>23</sup> This interaction is only maintained when IL-3Rα adopts a closed conformation (Figure 4B,C).

Moreover, as noticed above, the mobility of NTD in IL-3Rα/IL-3 complex is still observable in the unbound receptor and even accentuated. As expected, the three conformational states are found in IL-3Rα apo trajectories but with a different distribution comparing to the complex (Figure S9). Alternative-open conformations were largely represented (more than 60%) followed by open ones. Closed conformations only represented conformations from the very beginning of simulations but are not retrieved once the other conformations are reached.

## 3.3 | Molecular basis of IL-3Rα/IL-3 binding

IL-3 cytokine binds to its α subunit receptor with a low affinity and in our study, this interaction, and especially the contribution of each interfacing residues to the binding, was evaluated with free energy calculation using the MM-PBSA method and considering the different conformations of the receptor. Hence, three different parts of the trajectories (always computed with 200 snapshots), that best represent the three different conformational states, were selected (see Materials and Methods section). The changes of binding energies between the different states were reported in Table 1. Surprisingly, alternative-open conformation seems more favorable to the complex formation with a $ΔG_{binding}$ of about –129.4 kcal mol$^{-1}$. The closed conformation is about –102.7 kcal mol$^{-1}$ while the open conformation has a decreased value (–94 kcal mol$^{-1}$). These variations are driven by molecular mechanics energies (vdW and electrostatic). Following this observation, the alternative-open conformation displays the most interactions, notably hydrogen bonds and salt bridges according to the interactions observed at the interface of the different states (Table S3).

According to energy terms in Table 1, total non-polar interactions (vdW and non-polar solvation) are major part of the binding energy, apparently the highest in alternative-open conformation followed by closed one. Even though the electrostatic contribution in vacuum is significant, it is offset by a greater polar solvation contribution. The polar interactions (electrostatic and polar solvation) introduced an energetical penalty which is less important in open conformation.
<figure><img src="image_7.png" /><figcaption>TABLE 1 Binding energies components (in kcal mol⁻¹) for the different conformations.</figcaption></figure>

<table><thead><tr><th></th><th>IL-3Rα/IL-3 WT (C)</th><th>IL-3Rα/IL-3 WT (O)</th><th>IL-3Rα/IL-3 WT (AO)</th><th>IL-3Rα/IL-3 K135W (C)</th></tr></thead><tbody><tr><td>ΔE<sub>vdW</sub></td><td>-102.9 ± 9.9</td><td>-88 ± 16.7</td><td>-126.3 ± 9.9</td><td>-133.6 ± 10.7</td></tr><tr><td>ΔE<sub>Elec</sub></td><td>-285.3 ± 50.8</td><td>-277.7 ± 65.5</td><td>-311.8 ± 33.9</td><td>-292.6 ± 32.8</td></tr><tr><td>ΔG<sub>Polar</sub></td><td>302.8 ± 44.4</td><td>285.7 ± 61.6</td><td>327.6 ± 30.5</td><td>324.1 ± 28.2</td></tr><tr><td>ΔG<sub>non-Polar</sub></td><td>-17.2 ± 1.1</td><td>-13.9 ± 2.4</td><td>-18.9 ± 1</td><td>-19.9 ± 1</td></tr><tr><td>ΔG<sub>gas</sub></td><td>-388.3 ± 48.3</td><td>-365.7 ± 78.7</td><td>-438.2 ± 36.8</td><td>-426.2 ± 31.8</td></tr><tr><td>ΔG<sub>solv</sub></td><td>285.6 ± 44.6</td><td>271.7 ± 59.6</td><td>308.7 ± 30</td><td>304.1 ± 28.2</td></tr><tr><td>ΔG<sub>binding</sub></td><td>-102.7 ± 8.6</td><td>-94 ± 21.1</td><td>-129.4 ± 10.1</td><td>-122 ± 9.1</td></tr></tbody></table>

Abbreviations: AO, alternative-open conformation; C, closed conformation; elec, electrostatic; O, open conformation; solv, solvation; vdW, van der Waals.

<figure><img src="image_8.png" /><figcaption>FIGURE 5 Per-residue decompositions of the binding energies. (A) IL-3Rα residues of the D2, D3 domains and their hinge region. (B) IL-3 residues. Only residues that are less than 6 Å between the receptor and the cytokine were reported. c, conserved residues; D2, D3: NTD domains D2 and D3; p, partners residues of conserved regions; α1, A, B, C, and D, α helices.</figcaption></figure>

For further insights into the binding mechanism, contributions of IL-3Rα/IL-3 interfacial residues to the global binding energy for the three conformations were evaluated. Excluding the NTD mobile domain in order to have a right comparison between the three conformations, IL-3Rα/IL-3 interaction is mediated by a site oriented towards D2-D3 of IL-3Rα which interacts with A, D helices of IL-3. In

addition, we have previously highlighted few conserved residues during evolution. These conserved residues, located at the complex interface, are arranged in two distinct regions in IL-3Rα or IL-3 (see Figure 1D).²³ Surprisingly, these conserved residues are not part of the strongest contribution of the binding as seen in Figure 5 as their values scarcely reach a ΔG<sub>binding</sub> of −2 kcal mol<sup>−1</sup>. An exception may
<figure><img src="image_9.png" /><figcaption>**FIGURE 6** IL-3Rα/IL-3 binding site. Representative structures of the different conformational states oriented towards (A) IL-3Rα conserved region and (B) IL-3 conserved region. For each protein, the conserved region has two types of residues highlighted on protein surfaces: (1) Conserved residues are represented in yellow (R128<sub>c</sub>, T131<sub>c</sub>, F132<sub>c</sub>, I39<sub>c</sub> for IL-3, and S203<sub>c</sub>, F232<sub>c</sub>, N233<sub>c</sub> for IL-3Rα) and the residues, on the opposite side, interacting with these conserved regions are in stick; (2) The partners of conserved residues from the other side or protein are in green.</figcaption></figure>

be made for IL-3Rα residue N233<sub>c</sub> with a low contribution of around –8 kcal mol<sup>−1</sup> only in open and alternative-open conformations, and IL-3 residue F132<sub>c</sub> with a lower contribution (~ –2.3, –2.1, and – 1.9 kcal mol<sup>−1</sup>, in closed, open and alternative-open states respectively).

The conserved IL-3Rα residues S203<sub>c</sub>, F232<sub>c</sub>, N233<sub>c</sub>, are spatially close to each other and located in the D2-D3 linker and the D3 domain. At the opposite site, IL-3 residues F132<sub>c</sub>, K135, E138 and

N139 in the α-helix D, pointed towards this IL-3Rα conserved region (Figure 6A). Among these partner residues, only E138 have a strong and favorable energetical contribution (~ –47.7 kcal mol<sup>−1</sup> for closed, –31.4 kcal mol<sup>−1</sup> for open and – 33.2 kcal mol<sup>−1</sup> for alternative-open conformation) and can establish interactions with residues that surrounded the conserved ones. In every conformation, E138 interacts with the main chain of R234 or K235 through hydrogen bonds. K135 scarcely contributes to the binding energy in open and alternative-
open conformations (~ -1.4 and -1.9 kcal mol⁻¹) or can be unfavor-
able for the complex formation in closed one (~ 5.1 kcal mol⁻¹). In
the different conformations, it can establish hydrogen bond with
N233c or a salt bridge with E276. In closed conformations, we
observed cation-π interaction with Y279. N139, that have a low con-
tribution in all states (~ -5.4, -5.4, and -7.5 kcal mol⁻¹ respectively
for closed, open and alternative-open conformations), can interacts
with IL-3Rα residues H231, F232c, and Q178. As noticed earlier,
F132c has a low contribution and is surrounded by IL-3Rα residues
Y279 and V201. Other IL-3 residues contribute significantly
(ΔGbinding < -20 kcal mol⁻¹) in all conformations, but they are distant
from the subpocket formed by IL-3Rα conserved residues. Among
them, D40 follows I39c in the α-helix A of IL-3. Its largest contribution
is due to the interaction between the negative charged residue and a
set of IL-3Rα positive charged residues like R255 or K235.

The conserved IL-3 residues R128c, T131c, F132c, and I39c con-
stituted an extended subpocket located in helices A and D. V201,
K235, R237, E276, R277, V278, Y279, E280 located in the D2-D3
hinge region and the D3 domain, are potential partners of IL-3 con-
served residues (see Figure 6B). IL-3Rα partner residues V201, V278,
and Y279 are anchored in the IL-3 subpocket and principally form
hydrophobic interactions with F132c or I39c. Although a relatively
modest contribution to the binding energy, the three residues have a
similar contribution in all states: around -2 kcal mol⁻¹ for V201,
around -5 kcal mol⁻¹ for V278 and around -2 kcal mol⁻¹ for Y279.
Interestingly, Y279 displays the largest non-polar contribution (vdW
interaction and non-polar solvation) of IL-3Rα residues (see
Figure S11). The remaining partner residues contributed to the inter-
action in varying degrees (medium to high) and interact principally
with residues surrounding the conserved IL-3 subpocket. K235
appears to have the most important contribution for IL-3Rα (~ -49.7,
-39.2, and -42.6 kcal mol⁻¹ respectively for closed, open and
alternative-open conformation). It always establishes hydrogen bond
with the main chain of E138 which is located at the edge of the IL-3
subpocket. In open and alternative-open states, it approaches IL-3
residue D40, another border residue on E138 opposite side. A cation-
pi interaction can also be observed between IL-3Rα K235 and IL-3
border residue W32, in closed and open conformations. The binding
energy of R277 has a medium contribution (~ -20.6, -18.9, and
-13.7 kcal mol⁻¹ for closed, open and alternative-open states respec-
tively) and it forms salt bridge with border residue D40 in closed con-
formations. R237 is favorable in all conformations (~ -17.2, -15.7,
and -18.5 kcal mol⁻¹ for closed, open and alternative-open respec-
tively) and can form salt bridge with the IL-3 border residue D40 only
in alternative-open conformations. E276 is favorable to the complex
formation and as previously mentioned, it forms salt bridge with K135
in all states. E280 establishes salt bridge with IL-3 surrounding residue
K47 in all states and with R127 only in alternative-open one. Beyond
IL-3 conserved area, IL-3Rα residues R255 account for a significant
contribution, principally in alternative-open conformation (~
-26.7 kcal mol⁻¹). In this state, we observed that R255 can form salt
bridge with D40. In open state, R255 switches interaction to D41. In

closed state, the residue seems to lose IL-3 interaction and is mostly
exposed to the solvent.

In summary, different residues could play an important role in the IL-3Rα/IL-3 binding. In all conformations, we detected residues, considered as key residues important to the binding energy of the complex. Evolutionary conserved residues are unlikely to make the greatest energetic contribution, although IL-3Rα residue N233c appear to be relevant in all states. Per-residue contributions highlight other IL-3Rα residues, K235 and Y279 in all states. Concerning the contribution of cytokine, the importance of E138 belonging to helix D and D40 from helix A is revealed. We can observe also that newly formed salt bridges, exclusively present in the alternative-open form, can explain why the binding energy seems higher for this conformational state.

3.4 | Impact of a single mutation in IL-3Rα/IL-3

Several years ago, mutational studies resulted in the development of a
"superkine": the IL-3 K135W mutant, with an increased biological and
binding activities.<sup>10,11,43</sup> Therefore, in this study, the difference
between IL-3Rα/IL-3 wild-type (WT) and IL-3Rα/IL-3 K135W were
studied through MD simulations.

Firstly, we identify some conformational differences between
complexes involving IL-3 WT and IL-3 K135W. In complex, the cyto-
kine and the superkine did not present major differences in terms of
RMSF and N<sub>eq</sub> and the mutated position is rigid (see Figures 2A and
S5). An exception is made in the IL-3 region between helices A and
α1, where the mutation appears to cause slight local flexibilities (N<sub>eq</sub>
between 3 and 4–Figure S5). However, the most noticeable effect
concerns the NTD domain of IL-3Rα bound to the mutated IL-3
(noted IL-3Rα “K135W” in the study). The latter still display the most
RMSF values among domains, but this mobility is attenuated in IL-3Rα
“K135W” comparing to IL-3Rα “WT” (see Figure 2A). The NTD
domain of IL-3Rα “K135W” is then more rigid than IL-3Rα apo or IL-
3Rα “WT” in our simulations and presents a different behavior related
to its D2 domain. Indeed, Cα contacts cluster analysis indicate that
NTD and D2 are mainly close during the simulation (about 87% over
the trajectory of 3 µs–Figure S10). As seen in Figure 4D, contact
patch A72 (i) is mainly close to F199 (patch iii') over simulations. As
the result of the mutation, the IL-3Rα/IL-3 K135W complex preferen-
tially adopts a closed conformation.

Secondly, the mutation of the charged lysine into an aromatic res-
idue has considerable impact in the binding. Binding energy computa-
tion on trajectories representing closed conformations of IL-3Rα/IL-3
K135W indicate a correlation with literature. Indeed, IL-3Rα/IL-3
K135W has the strongest binding energy (-122 kcal mol⁻¹) compar-
ing to IL-3Rα/IL-3 WT regardless of its conformations (see Table 1).
An exception is made for alternative-open conformation. The binding
energy of IL-3Rα/IL-3 K135W is still dominated by the total non-polar
interactions but the mutation increases the penalty coming from polar
interactions. As expected, non-polar interactions in IL-3Rα/IL-3
<figure><img src="image_10.png" /><figcaption>**FIGURE 7** IL-3Rα/IL-3 K135W interaction. Binding energy contribution of (A) IL-3Rα “K135W” residues and (B) IL-3 K135W residues, compared with residues of the wild-type (WT) complex in the closed form. Representative structures of the closed state oriented towards (C) IL-3Rα “K135W” conserved region and (D) IL-3 K135W conserved region. For each protein, the conserved region has two types of residues highlighted in lines: (1) Conserved residues are represented in yellow (R128<sub>c</sub>, T131<sub>c</sub>, F132<sub>c</sub>, I39<sub>c</sub> for IL-3 K135W and, S203<sub>c</sub>, F232<sub>c</sub>, and N233<sub>c</sub> for IL-3Rα “K135W”) and the residues, on the opposite side, interacting with these conserved regions are in stick; (2) The partners of conserved residues from the other side or protein are in green.</figcaption></figure>

K135W are higher than in alternative-open conformations (IL-3Rα/IL-3 WT) probably due to an increased number of vdW interactions (see Tables 1 and S3).

Finally, the receptor/superkine interaction presents some particu-
larities at a residue level. In our previous study, we have suggested
that W135 in the IL-3 K135W is anchored in the IL-3Rα evolutionary
conserved region forming a π-stacking network with surrounding resi-
dues Y279, F281 (IL-3Rα residues), F132<sub>c</sub>, and F56 (IL-3).<sup>23</sup> Indeed,

the representative closed conformation of IL-3Rα/IL-3 K135W shows
that W135 establishes a parallel π-stacking with Y279, which is also
near the IL-3 residue F132c. Not surprisingly, the binding energy anal-
ysis reveals that the K135 position of IL-3 WT does not contribute to
the IL-3Rα/IL-3 complex formation in every state (see Figure 5B).
Conversely, in IL-3 K135W, we noticed a beneficial switch of the
W135 energetic contribution (~ -9.9 kcal mol⁻¹—see Figure 6B).
Moreover, W135 is the largest total non-polar contribution for IL-3
residues as well as its partner Y279 for IL-3Rα “K135W” residues (Figure S12). It is also important to notice that IL-3Rα residues N233c and E276, which interacts with K135, lost their contributions or became unfavorable to the binding in the case of W135. Comparing to IL-3Rα/IL-3 WT closed form, or others (see Figure 6), we observed a displacement of IL-3 K135W residue E138 for which the lateral chain is not completely anchored in the conserved IL-3Rα “K135W” subpocket (see Figure 7C). Thus, IL-3Rα E138 moves away from the 135 position to form salt bridge with IL-3Rα “K135W” R277 or K255, residues surrounding the subpocket. As for IL-3 WT, E138 of the superkine has a significant impact on the binding and even higher compared to the WT. Its IL-3Rα “K135W” partner residue R277 has an increased contribution while K255 has a decreased one. Hence, this high affinity complex IL-3Rα/IL-3 K135W seems governed principally by IL-3Rα residues Y279, K235 and IL-3 residues E138, D40 as for IL-3Rα/IL-3 WT, even with variable binding contributions. As IL-3 residue W135, IL-3Rα residue R277 also distinguishes the two complexes since it has the strongest IL-3Rα contribution in IL-3Rα/IL-3 K135W complex.

## 4 | DISCUSSION

As a PPI complex, the human IL-3Rα/IL-3 has a large interface that can be divided into two distinct sites commonly called site 1a and 1b. The site 1b is composed of the IL-3 helix α1 and loop C-D on one side and the IL-3Rα NTD domain on the other. According to MD simulations, this NTD domain maintained its β-sandwich structure principally formed by β-strands. However, NTD depicts motions that induce a variation in contacts with D2 and/or IL-3. Hence, the mobility of NTD residues is related to the existence of three different conformations: (1) a closed conformation with various contacts with D2, (2) an open conformation with reduced contacts with D2, and (3) an alternative-open conformation also having reduced contacts with D2 but different from the open one. As the first two conformations have been reported in the literature, the alternative-open state appears to be a novelty for this system. Moreover, the pattern of contact we identified in this new conformation seems to be maintained during long simulations, meaning that structures alike alternative-open state could be a stable one of the IL-3Rα. Interestingly, NTD residues display different behavior depending on the presence or absence of ligand. The NTD residue fluctuation is accentuated in the apo form of IL-3Rα with a large representation of the alternative-open state during simulations. Conversely, the interaction with IL-3 leads to conformational changes with a more homogenous distribution of states. In the case of an interaction with the superkine (the mutated cytokine with an increased affinity), NTD is more rigid, and the closed state is more favored. Researchers have studied the role of the IL-3Rα NTD domain and suggested that it is not important for the IL-3 recognition.⁹,¹⁹,⁴⁴ Once IL-3 has bound IL-3Rα, NTD might facilitate its locking and the recruitment of βc receptor. Only closed conformations allow interactions between NTD and IL-3 and we suggest that this form promotes the IL-3 clamping by NTD. Moreover, NTD could be important to

prevent a premature heterodimerization of IL-3Rα and βc without IL-3.⁹ This prevention role could be associated with the alternative-open conformation that is predominant for the unbound receptor. In other words, in apo form, IL-3Rα could adopt an alternative-open form that could be exclusively suitable for the recognition of the cytokine and not the βc receptor.

In the site 1a, IL-3Rα D2 and D3 domains interact with helices A, D, and loop A-α1 of IL-3. This site has been referred to as the recognition site for the IL-3Rα/IL-3 binding in literature.⁹,¹⁹ In a previous study, we have detected conserved regions in both receptor and cytokine that could play a role in the binding.²³ However, these conserved regions are not among the most energetical contributors to the interaction. They formed shallow binding clefts or sub-pockets in which key residues or hot spots that seem important to the binding are anchored. Considering IL-3Rα interface, the interaction is centered at the IL-3 α-helix D and taking the residue at position 132 as a starting point (iᵗʰ), the residue positions i + 3rd and i + 7th, altogether are in the same face of the α-helix and projected into the IL-3Rα conserved subpocket. Those α-helix positions are commonly involved in a specific and/or selective binding in PPIs.⁴⁵ The only hydrophobic residue corresponds to the iᵗʰ position that is also conserved across evolution (F132c).²³ At i + 3rd and i + 7th positions are respectively located K135 and N139, two hydrophilic residues. Moreover, a supplementary position (i + 6th) has one of the most important residues in terms of binding energy contribution, E138. In IL-3, E138 side chain, in the vicinity of K135, is also projected into the subpocket. Remarkably, a hydrophobic residue is inserted at the i + 3rd position (135) of the superkine, resulting in a reorientation of E138 main chain which is no longer located at the same face than the others (iᵗʰ, i + 3rd, and i + 7th). Coming from another IL-3 α-helix (A), D40 seems to have an important energetical contribution but this residue is not anchored into the conserved cleft and its contribution is reduced due to the mutation. Mutagenesis studies have revealed the importance of F132c and D40 as essential to the binding association.¹¹,⁴⁶ Nevertheless, the most impressive role concerns the residue K135 or W135 (in the case of low or high affinity for the receptor respectively). The K135W mutation facilitates binding association and reduces the dissociation.⁴⁶ Considering IL-3 interface, the PPI is mediated through residues on IL-3Rα D3. V201, V278 and Y279 side chains are anchored into the conserved subpocket and display a moderate energetical contribution. Focusing on the total non-polar contribution, those residues could play a role in the binding, especially Y279 which has the strongest contribution regardless of the conformation. In agreement with our observations, mutagenesis studies on IL-3Rα have demonstrated that V201 and Y279 have respectively a moderate and a high impact on the IL-3Rα/IL-3 binding affinity. On contrary, V278 mutation has no effect on the binding,¹⁹ albeit the mutation into another hydrophobic residue, alanine, may explain this finding. K235, the greatest IL-3Rα polar contribution in the low affinity complex, became somewhat less relevant in the high affinity complex since the contribution is dispatched to R277 residue.

As reported in Figure 8, our results provided an interpretation for the binding mechanisms of the cytokine and the superkine.
<figure><img src="image_11.png" /><figcaption>**FIGURE 8** A hypothesis for the IL-3Rα/IL-3 binding mechanism considering wild-type (yellow) and mutant (green). Dashed arrows indicate the uncertainty about the direction of changes.</figcaption></figure>

Unbounded, IL-3Rα may adopt the predominant alternative-open state until it binds the ligand: cytokine or superkine. The interaction with ligand induces conformational changes that could lead to different conformations (open, closed or alternative-open) in the case of cytokine or a closed-like conformation for the superkine.

Several years ago, differences between cytokine and superkine binding mechanism have been attributed to their binding kinetics which assigned a slow association and fast dissociation rates to IL-3 WT whereas IL-3 K135W has the reverse.⁴⁶ Hence, the cytokine could rapidly leave the α subunit receptor and it is difficult to precise in which conformation at this point, though open conformation is less advantageous to the binding than the others in terms of binding free energies. Otherwise, the interaction with the superkine leads to the formation of a stable closed conformation with a suitable presentation of key residues at the interface and increased vdW interactions. In that case, the NTD domain clamps the superkine and reduced its release. Finally, both binary complexes are able to recruit the βc receptor and the signalization process. Our proposed hypothesis is of great importance regarding the therapeutic interest of this system. This biological mechanism, especially conformational changes derived from our sampling could be more explore using enhanced simulations techniques to confirm these conformational states and determine their transition pathways and characterize more deeply the energetic landscape and the molecular mechanisms associated to the complex formation. In addition, our findings could be relevant for any drug design approaches targeting the IL-3Rα/IL-3 axe since it can use multiple receptor conformations or potential hotspots for hit identification to lead optimization.

## 5 | CONCLUSION

Previously, structural and evolutionary analyses have been carried out on the interaction between human IL-3 and the α subunit of its receptor IL-3Rα. These analyses revealed a conserved structural integrity and conserved regions that could be important for the binding. In this study, through dynamics studies, we noticed that the structural architecture of human IL-3 and the different domains of human IL-3Rα are still conserved. However, motions of NTD causes notable conformational changes that could vary depending on the presence or absence of cytokine or superkine. Hence, our results put forward an open and closed conformation, already described in the literature and a supplementary one called alternative-open, which appears to be predominant in our simulations of the WT complex. By consequence, these three different states need to be considered in the biological process starting from IL-3 recognition to the signalization pathways following the βc recruitment. Moreover, analyses highlighted different key residues that could play a role in the low or high binding affinity. Surprisingly, residues conserved across evolution are generally excluded from these key residues but constituted binding clefts in which lateral chains of key residues are anchored. Regarding the importance of IL-3 and IL-3Rα in therapeutic research, these structural outcomes could represent a promising starting point for the PPI modulation.

## AUTHOR CONTRIBUTIONS

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.
## ACKNOWLEDGMENTS

The research was supported by the French National Research Agency with grant ANR-19-CE17-0021 (BASIN) for Jade Fogha, Julien Diharce, & Alexandre G. de Brevern, the Laboratory of Excellence GR-Ex, reference ANR-11-LABX-0051, and the programme "Investissements d'avenir" of the French National Research Agency, reference ANR-11-IDEX-0005-02 for Jade Fogha, Julien Diharce, & Alexandre G. de Brevern. The simulations were performed on the high-performance resource OCCIGEN computer at the "Centre Informatique National de l'Enseignement Supérieur" (CINES) under grants n A0090711986, funded by the GENCI (Grand Equipement National de Calcul Intensif).

## CONFLICT OF INTEREST STATEMENT

The authors declare no conflict of interest. The funding bodies have no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

## DATA AVAILABILITY STATEMENT

The three starting structures from our calculations are all available on the RCSB database: www.rcsb.org, with PDB ID 1JLI, 5UV8 and 5UWC. All software used for this study are publicly available: Modeler (https://salilab.org/modeller/), PyMOL (https://pymol.org/2/), CHARMM-GUI (https://www.charmm-gui.org/), H++ (http://biophysics.cs.vt.edu/H++), Gromacs (https://www.gromacs.org/), CONAN (https://github.com/HITS-MBM/conan), MDAnalysis (https://www.mdanalysis.org/) and gmx_MMPBSA (https://valdes-tresanco-ms.github.io/gmx_MMPBSA/). The following files are available free of charge below. RMSF, RMSD, PBs, PCA and clusters analyses, per-residue decomposition of energy binding, sequence, structure, and interaction information (PDF).

## ORCID

Jade Fogha ID https://orcid.org/0000-0001-5512-544X

Alexandre G. de Brevern ID https://orcid.org/0000-0001-7112-5626

Julien Diharce ID https://orcid.org/0000-0002-6400-927X

## REFERENCES

1. Frendl G. Interleukin 3: from Colony-stimulating factor to pluripotent immunoregulatory cytokine. *Int J Immunopharmacol.* 1992;14(3):421-430. doi:10.1016/0192-0561(92)90172-H

2. Dahl C, Hoffmann HJ, Saito H, Schiøtz PO. Human mast cells express receptors for IL-3, IL-5 and GM-CSF; a partial map of receptors on human mast cells cultured in vitro. *Allergy*. 2004;59(10):1087-1096. doi:10.1111/j.1398-9995.2004.00606.x

3. Hercus TR, Dhagat U, Kan WLT, et al. Signalling by the Bc family of cytokines. *Cytokine Growth Factor Rev.* 2013;24:189-201. doi:10.1016/j.cytogfr.2013.03.002

4. Luo X, Li M, Huang L, et al. The interleukin 3 gene (IL3) contributes to human brain volume variation by regulating proliferation and survival of neural progenitors. *PLoS One*. 2012;7(11):e50375. doi:10.1371/journal.pone.0050375

5. Kitamura T, Sato N, Arai K-I, Miyajima A. Expression cloning of the human IL-3 receptor CDNA reveals a shared β subunit for the human IL-3 and GM-CSF receptors. *Cell*. 1991;66(6):1165-1174. doi:10.1016/0092-8674(91)90039-2

6. Lopez AF, Hercus TR, Ekert P, et al. Molecular basis of cytokine receptor activation. *IUBMB Life*. 2010;10:509-518. doi:10.1002/ibu.350

7. Wang X, Lupardus P, LaPorte SL, Garcia KC. Structural biology of shared cytokine receptors. *Annu Rev Immunol.* 2009;27(1):29-60. doi: 10.1146/annurev.immunol.24.021605.090616

8. Broughton SE, Nero TL, Dhagat U, et al. The Bc receptor family—structural insights and their functional implications. *Cytokine*. 2015;74:247-258. doi:10.1016/j.cyto.2015.02.005

9. Broughton SE, Hercus TR, Nero TL, et al. A dual role for the N-terminal domain of the IL-3 receptor in cell Signalling. *Nat Commun.* 2018;9(1):386. doi:10.1038/s41467-017-02633-7

10. Lopez AF, Shannon MF, Barry S, et al. A human interleukin 3 analog with increased biological and binding activities. *Proc Natl Acad Sci U S A.* 1992;89(24):11842-11846. doi:10.1073/pnas.89.24.11842

11. Klein BK, Feng Y, McWherter CA, Hood WF, Paik K, McKearn JP. The receptor binding site of human Interleukin-3 defined by mutagenesis and molecular modeling. *J Biol Chem.* 1997;272(36):22630-22641. doi:10.1074/jbc.272.36.22630

12. Hercus TR, Kan WLT, Broughton SE, et al. Role of the β common (Bc) family of cytokines in health and disease. *Cold Spring Harb Perspect Biol.* 2018;10(6):a028514. doi:10.1101/cshperspect.a028514

13. Borriello F, Galdiero MR, Varricchi G, Loffredo S, Spadaro G, Marone G. Innate immune modulation by GM-CSF and IL-3 in health and disease. *Int. J. Mol. Sci.* 2019;2:834. doi:10.3390/ijms20040834

14. Varricchi G, Poto R, Marone G, Schroeder JT. IL-3 in the development and function of basophils. *Semin Immun.* 2021;29:101510. doi:10.1016/j.smim.2021.101510

15. Testa Pelosi; Castelli. CD123 as a therapeutic target in the treatment of hematological malignancies. *Cancers (Basel)*. 2019;11(9):1358. doi: 10.3390/cancers11091358

16. Weber GF, Chousterman BG, He S, et al. Interleukin-3 amplifies acute inflammation and is a potential therapeutic target in sepsis. *Science*. 2015;347(6227):1260-1265. doi:10.1126/science.aaa4268

17. Siracusa MC, Kim BS, Spergel JM, Artis D. Basophils and allergic inflammation. *J Allergy Clin Immunol.* 2013;132(4):789-801. doi:10.1016/j.jaci.2013.07.046

18. Schroeder JT, Chichester KL, Bieneman AP. Human basophils secrete IL-3: evidence of autocrine priming for phenotypic and functional responses in allergic disease. *J Immunol.* 2009;182(4):2432-2438. doi: 10.4049/JIMMUNOL.0801782

19. Broughton SE, Hercus TR, Hardy MP, et al. Dual mechanism of Interleukin-3 receptor blockade by an anti-cancer antibody. *Cell Rep.* 2014;8(2):410-419. doi:10.1016/j.celrep.2014.06.038

20. Yao S, Young IG, Norton RS, Murphy JM. Murine Interleukin-3: structure, dynamics, and conformational heterogeneity in solution. *Biochemistry.* 2011;50(13):2464-2477. doi:10.1021/bi101810f

21. Patino E, Kotzsch A, Saremba S, et al. Structure analysis of the IL-5 ligand-receptor complex reveals a wrench-like architecture for IL-5Rα. *Structure*. 2011;19(12):1864-1875. doi:10.1016/j.str.2011.08.015

22. Broughton SE, Hercus TR, Nero TL, et al. Conformational changes in the GM-CSF receptor suggest a molecular mechanism for affinity conversion and receptor signaling. *Structure*. 2016;24(8):1271-1281. doi:10.1016/j.str.2016.05.017

23. Fogha J, Bayry J, Diharce J, de Brevern AG. Structural and evolutionary exploration of the IL-3 family and its alpha subunit receptors. *Amino Acids*. 2021;53(8):1211-1227. doi:10.1007/s00726-021-03026-3

24. Feng Y, Klein BK, McWherter CA. Three-dimensional solution structure and backbone dynamics of a variant of human Interleukin-3. *J Mol Biol.* 1996;259(3):524-541. doi:10.1006/jmbi.1996.0337

25. Berman HM, Westbrook J, Feng Z, et al. The protein data bank. *Nucleic Acids Res.* 2000;28(1):235-242.
26. Krivov GG, Shapovalov MV, Dunbrack RL. Improved prediction of protein side-chain conformations with SCWRL4. *Proteins: Struct Funct Genet.* 2009;77(4):778-795. doi:10.1002/prot.22488

27. Schrödinger, L. L. C. The {PyMOL} molecular graphics system, version~1.8. 2015.

28. Šali A, Blundell TL. Comparative protein modelling by satisfaction of spatial restraints. *J Mol Biol.* 1993;234(3):779-815. doi:10.1006/jmbi. 1993.1626

29. Anandakrishnan R, Aguilar B, Onufriev AV. H++ 3.0: automating PK prediction and the preparation of biomolecular structures for atomis- tic molecular modeling and simulations. *Nucleic Acids Res.* 2012;40 (Web Server issue), W537-W541. doi:10.1093/NAR/GKS375

30. Jo S, Kim T, Iyer VG, Im W. CHARMM-GUI: a web-based graphical user interface for CHARMM. *J Comput Chem.* 2008;29(11):1859-1865. doi:10.1002/jcc.20945

31. Berendsen HJC, van der Spoel D, van Drunen R. GROMACS: a message-passing parallel molecular dynamics implementation. *Comput Phys Commun.* 1995;91(1-3):43-56. doi:10.1016/0010-4655(95) 00042-E

32. Huang J, Rauscher S, Nawrocki G, et al. CHARMM36m: an improved force field for folded and intrinsically disordered proteins. *Nat Methods.* 2016;14(1):71-73. doi:10.1038/nmeth.4067

33. Michaud-Agrawal N, Denning EJ, Woolf TB, Beckstein O. MDAnaly- sis: a toolkit for the analysis of molecular dynamics simulations. *J Comput Chem.* 2011;32(10):2319-2327. doi:10.1002/JCC.21787

34. De Brevern AG, Etchebest C, Hazout S. Bayesian probabilistic approach for predicting backbone structures in terms of protein blocks. *Proteins: Struct Funct Genet.* 2000;41(3):271-287. doi: 10.1002/1097-0134(20001115)41:3<271::AID-PROT10>3.0.CO;2-Z

35. Etchebest C, Benros C, Hazout S, Brevern AG d. A structural alphabet for local protein structures: improved prediction methods. *Proteins: Struct Funct Genet.* 2005;59(4):810-827. doi:10.1002/PROT.20458

36. Barnoud J, Santuz H, Craveur P, et al. PBxplore: a tool to analyze local protein structure and deformability with protein blocks. *PeerJ*. 2017; 1:136408. doi:10.1101/136408

37. Akhila MV, Narwani TJ, Floch A, et al. A structural entropy index to analyse local conformations in intrinsically disordered proteins. *J Struct Biol.* 2020;210. doi:10.1016/j.jsb.2020.107464

38. Mercadante D, Gräter F, Daday C. CONAN: a tool to decode dynami- cal information from molecular interaction maps. *Biophys J.* 2018; 114(6):1267-1273. doi:10.1016/j.bpj.2018.01.033

39. Valdés-Tresanco MS, Valdés-Tresanco ME, Valiente PA, Moreno E. Gmx_MMPBSA: a new tool to perform end-state free energy calcula- tions with GROMACS. *J Chem Theory Comput.* 2021;17(10):6281-6291. doi:10.1021/acs.jctc.1c00645

40. Miller BR, McGee TD, Swails JM, Homeyer N, Gohlke H, Roitberg AEMMPBSA. Py: an efficient program for end-state free energy calculations. *J Chem Theory Comput.* 2012;8(9):3314-3321. doi:10.1021/CT300418H

41. Wang C, Greene D, Xiao L, Qi R, Luo R. Recent developments and applications of the MMPBSA method. *Front Mol Biosci.* 2018;4:87. doi:10.3389/fmolb.2017.00087

42. Humphrey W, Dalke A, Schulten K. VMD: visual molecular dynamics. *J Mol Graph.* 1996;14(1):33-38. doi:10.1016/0263-7855(96)00018-5

43. Klein BK, Olins PO, Bauer SC, et al. Use of combinatorial mutagenesis to select for multiply substituted human Interleukin-3 variants with improved pharmacologic properties. *Exp Hematol.* 1999;27(12):1746-1756. doi:10.1016/S0301-472X(99)00118-6

44. Barry SC, Korpelainen E, Sun Q, et al. Roles of the N and C terminal domains of the Interleukin-3 receptor α chain in receptor function. *Blood.* 1997;89(3):842-852. doi:10.1182/blood.v89.3.842

45. Edwards TA, Wilson AJ. Helix-mediated protein-protein interactions as targets for intervention using foldamers. *Amino Acids.* 2011;41(3): 743-754. doi:10.1007/s00726-011-0880-8

46. Klein BK, Shieh J-JJ, Grabbe E, Li X, Welply JK, Mckearn JP. Receptor binding kinetics of human IL-3 variants with altered proliferative activity. *Biochem Biophys Res Commun.* 2001;288(5):1244-1249. doi: 10.1006/bbrc.2001.5907

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How to cite this article: Fogha J, de Brevern AG, Diharce J. Conformational and binding mode assessment of the human IL-3 recognition by its alpha receptor. *Proteins.* 2023;91(7): 904-919. doi:10.1002/prot.26476