Next Article in Journal
GhERF.B4-15D: A Member of ERF Subfamily B4 Group Positively Regulates the Resistance against Verticillium dahliae in Upland Cotton
Next Article in Special Issue
Recent Advances in Molecular and Cellular Functions of S100A10
Previous Article in Journal
Genomics of Wolfram Syndrome 1 (WFS1)
Previous Article in Special Issue
An Extracellular/Membrane-Bound S100P Pool Regulates Motility and Invasion of Human Extravillous Trophoblast Lines and Primary Cells
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Interaction of S100A6 Protein with the Four-Helical Cytokines

by
Alexey S. Kazakov
1,
Evgenia I. Deryusheva
1,
Victoria A. Rastrygina
1,
Andrey S. Sokolov
1,
Maria E. Permyakova
1,
Ekaterina A. Litus
1,
Vladimir N. Uversky
1,2,3,*,
Eugene A. Permyakov
1 and
Sergei E. Permyakov
1,*
1
Pushchino Scientific Center for Biological Research of the Russian Academy of Sciences, Institute for Biological Instrumentation, Institutskaya str., 7, Pushchino, Moscow Region 142290, Russia
2
Department of Molecular, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
3
USF Health Byrd Alzheimer’s Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
*
Authors to whom correspondence should be addressed.
Biomolecules 2023, 13(9), 1345; https://doi.org/10.3390/biom13091345
Submission received: 27 July 2023 / Revised: 19 August 2023 / Accepted: 31 August 2023 / Published: 4 September 2023

Abstract

:
S100 is a family of over 20 structurally homologous, but functionally diverse regulatory (calcium/zinc)-binding proteins of vertebrates. The involvement of S100 proteins in numerous vital (patho)physiological processes is mediated by their interaction with various (intra/extra)cellular protein partners, including cell surface receptors. Furthermore, recent studies have revealed the ability of specific S100 proteins to modulate cell signaling via direct interaction with cytokines. Previously, we revealed the binding of ca. 71% of the four-helical cytokines via the S100P protein, due to the presence in its molecule of a cytokine-binding site overlapping with the binding site for the S100P receptor. Here, we show that another S100 protein, S100A6 (that has a pairwise sequence identity with S100P of 35%), specifically binds numerous four-helical cytokines. We have studied the affinity of the recombinant forms of 35 human four-helical cytokines from all structural families of this fold to Ca2+-loaded recombinant human S100A6, using surface plasmon resonance spectroscopy. S100A6 recognizes 26 of the cytokines from all families of this fold, with equilibrium dissociation constants from 0.3 nM to 12 µM. Overall, S100A6 interacts with ca. 73% of the four-helical cytokines studied to date, with a selectivity equivalent to that for the S100P protein, with the differences limited to the binding of interleukin-2 and oncostatin M. The molecular docking study evidences the presence in the S100A6 molecule of a cytokine-binding site, analogous to that found in S100P. The findings argue the presence in some of the promiscuous members of the S100 family of a site specific to a wide range of four-helical cytokines. This unique feature of the S100 proteins potentially allows them to modulate the activity of the numerous four-helical cytokines in the disorders accompanied by an excessive release of the cytokines.

1. Introduction

S100 is an evolutionary young family of structurally similar, but functionally diversified regulatory Ca2+-binding proteins of the EF-hand superfamily (for reviews, see [1,2,3,4]). The classical Ca2+-binding motif of the ‘EF-hand’ type (PROSITE [5] entry PDOC00018) is composed of a 12-residue Ca2+-coordinating loop located between two α-helices [6,7,8]. S100 proteins consist of a low-affinity non-classical N-terminal EF-hand motif, and a high-affinity classical C-terminal EF-hand, which are linked by a flexible ‘hinge’ [7,9]. Certain S100 proteins possess distinct Zn2+/Cu2+/Mn2+-binding sites [9,10]. S100 proteins are generally (homo/hetero)dimeric proteins (except for monomeric S100G), whereas some of them tend to form higher-order oligomers [2,11]. With the exception of the S100 fused-type proteins, the human S100 family consists of 21 members (78–113 residues; the pairwise sequence identity evaluated via Clustal Omega 2.1 [12] ranges from 16% to 61%), each of which has a unique set of functional activities, together covering nearly all vital processes [1,2,3]. Some S100 proteins are linked to the progression of oncological, autoimmune, inflammatory, neurodegenerative, cardiovascular, pulmonary, and liver diseases, are used for diagnostic and prognostic purposes, and are considered as promising therapeutic targets [13,14,15,16,17,18,19,20,21]. The dysregulation of most S100 proteins in cancer is related to the fact that most of their genes are located in the epidermal differentiation complex on chromosome 1 (locus 1q21), which undergoes frequent rearrangement in cancer [22,23]. These S100 proteins are designated by Arabic numbers placed behind the ‘S100A’, while the names of the S100 proteins encoded by other chromosomes carry the symbol ‘S100’ followed by ‘B’, ‘G’, ‘P’, or ‘Z’ [23,24]. The multifunctionality of S100 proteins is determined by their cell-/tissue-specific expression, ability to localize in the nucleus/cytosol/extracellular space, metal-binding properties, post-translational modifications, and propensity to recognize a wide range of targets, including enzymes, transcription factors, receptor/membrane proteins, lipids, and nucleic acids [1,2,3,25,26].
Despite the lack of a leader sequence, some of the S100 proteins are secreted via the endoplasmic reticulum (ER)/Golgi pathway, or several unconventional passive and active mechanisms [2,27,28]. When they are released into the extracellular space, certain S100 proteins exert a cytokine-like action, due to interaction with specific cell surface receptors, such as RAGE, TLR4, ErbB1, ErbB3, ErbB4, IL-10R, integrin β1, neuroplastin-β, 5-HT1B, 4-HT4, SIRL-1, ALCAM, EMMPRIN, CD33, CD36, CD68, CD69, or CD146 [2,25,29,30,31,32,33,34,35,36]. Moreover, some of the released S100 proteins interact with cytokines. For instance, S100A4 binds ErbB1/ErbB4 ligands [35,37], S100A13 interacts with IL1α/FGF1 [38,39], S100B binds FGF2 [40,41], and S100A11/A12/A13 interact with the soluble form of TNF [42]. Several S100 proteins recognize four-helical cytokines: S100A2/A6/P bind EPO [43], S100A1/A4/A6/B/P interact with IFN-β [25,44,45], and distinct subsets of S100A1/A6/B/P bind to specific IL-6 family cytokines (IL-11, OSM, CNTF, CT-1, and CLCF1 [46]), whereas S100P binds 29 four-helical cytokines [47]. The S100 binding has been shown to affect the cytokine signaling in some cases: S100A4 enhanced the amphiregulin-mediated proliferation of embryonic fibroblasts [37]; S100B inhibited an FGF2-induced increase in the proliferation of MCF-7 and MDA-MB468 cells [40], but favored the FGF2-medited activation of FGFR1 in myoblasts [41,48]; S100A12/A13 rescued Huh-7 cells from the cytotoxic effect of soluble TNF [42]; and the S100A1/A4/B/P proteins suppressed the IFN-β-induced inhibition of viability in MCF-7 cells [25,44,45]. Moreover, S100-cytokine interactions can promote the non-classical secretion of the cytokines, as demonstrated by S100A13–IL1α/FGF1 interactions [38,39].
The vast majority of the established S100–cytokine interactions correspond to cytokines belonging to the superfamily of four-helical cytokines (SCOP [49] ID: 3001717), which is subdivided into three families: ‘Short-chain cytokines’ (SCOP ID 4000852), ‘Long-chain cytokines’ (SCOP ID 4000851), and ‘Interferons/interleukin-10 (IL-10)’ (SCOP ID 4000854). We have previously shown that the S100P oncoprotein is poorly selective towards the four-helical cytokines of all structural families, interacting with 71% of them (29 out of the 41 cytokines studied), with the equilibrium dissociation constants, Kd, in the 1 nM–3 µM range (below the Kd value for S100P binding to the V domain of RAGE) [47]. Using mutagenesis, we confirmed the presence of a cytokine-binding site in the S100P molecule, overlapping with its RAGE-specific site. The ability of S100P to recognize multiple cytokines reflects its promiscuous nature, well established for certain members of the S100 family, which readily share their binding partners [50,51]. Therefore, the specificity to many four-helical cytokines is also expected for other promiscuous representatives of the S100 family. To explore this possibility, in this work, we test the affinity of another promiscuous S100 oncoprotein [50,51], S100A6 (also known as calcyclin; it has a pairwise sequence identity to S100P of 35% [52,53]), specific to the six four-helical cytokines shown in Table 1, to 35 four-helical cytokines from all their structural families (Table S1). Our findings greatly expand the long list of known extracellular target proteins of S100A6, which may be of value for deciphering its role in the progression of many cancers, neurodegenerative disorders, myocardial infarction, acute coronary syndrome, chronic renal disease, primary biliary cholangitis, pulmonary fibrosis, systemic sclerosis of the lung, endometriosis, osteoarthritis, various eye pathologies, and other disorders (reviewed in [54,55,56]).

2. Materials and Methods

2.1. Materials

The human S100A6 protein was expressed in E. coli, and purified as described in [44]. The samples of human cytokines are presented in Table S1. The protein concentrations were determined according to [57].
The HEPES and sodium chloride were from PanReac AppliChem (Darmstadt, Germany). The CaCl2, Tween 20, and EDTA were purchased from Sigma Aldrich Co. (Burlington, MA, USA).

2.2. Surface Plasmon Resonance Studies

SPR studies of S100A6 binding to the cytokines immobilized on the sensor chip surface (S100A6 was used as an analyte, and the cytokines served as ligands) were performed at 25 °C, mainly according to [47]. The cytokine (0.03–0.05 mg/ml) was immobilized on the ProteOn™ GLH sensor chip surface of the ProteOn™ XPR36 instrument (Bio-Rad Laboratories, Inc. Hercules, CA, USA) via amine coupling (up to 10,000–17,000 RUs). The running buffer was 10 mM HEPES, 150 mM NaCl, 1 mM CaCl2, and 0.05% Tween 20, pH 7.4. The S100A6 (63 nM–8 µM) solution in the running buffer was passed over the chip surface for 300 s. The dissociation of the ligand–analyte complex was triggered by the passage of the running buffer for 1200–2400 s. The SPR sensograms were described via a single-site binding scheme (S100A6-IL-2 interaction) or a heterogeneous ligand model (1). The latter suggests the presence of two populations of the ligand (L1 and L2) independently binding an analyte molecule (A):
L 1 + A k d 1 K d 1 k a 1 L 1 A L 2 + A k d 2 K d 2 k a 2 L 2 A
Here, k and K refer to the kinetic and equilibrium association (‘a’) and dissociation (‘d’) constants, respectively. The Kd and kd values were calculated for several S100A6 concentrations. The resulting values are the average of 3–5 estimates. The ligand was regenerated using 20 mM EDTA pH 8.0 solution for 100 s. The free energy change in the reaction was estimated using the equation: ΔGi = −RT ln(55.3/Kdi), i=1,2.

2.3. Structural Classification of Cytokines

The cytokines investigated in this study were classified according to the SCOP 2 database (https://scop2.mrc-lmb.cam.ac.uk [49], build 1.0.6, updated on 06-29-2022, accessed on 1 June 2023) as belonging to the ‘All alpha proteins’ structural class, ‘4-helical cytokines’ fold (SCOP ID 2001054), ‘4-helical cytokines’ superfamily (SCOP ID 3001717). This superfamily comprises three families, namely ‘Short-chain cytokines’ (SCOP ID 4000852), ‘Long-chain cytokines’ (SCOP ID 4000851), and ‘Interferons/interleukin-10 (IL-10)’ (SCOP ID 4000854). CLCF1 and CT-1 were classified as long-chain cytokines, according to [58].

2.4. Structural Modeling of The S100A6–Cytokine Complexes

The ClusPro docking server [59] was used to generate the models of the tertiary structures of the S100A6–cytokine complexes, according to [43,47]. The tertiary structure of the Ca2+-bound S100A6 dimer was taken from PDB [60] entry 1K9K (X-ray, chains A and B [61]), while the structures of the cytokines were either extracted from PDB, or predicted via AlphaFold2 (https://alphafold.ebi.ac.uk/; accessed on 1 June 2023 [62]) (Table S2). Ten docking models were generated for each S100A6–cytokine complex. The contact residues included in at least five models were considered as the residues of the binding site. The distributions of the contact residues of S100A6 over its amino acid sequence within the models of the complexes were calculated as described in [43]. The models were visualized using PyMOL v.2.5.0 (https://pymol.org/2/; accessed on 1 June 2023) software.

3. Results and Discussion

3.1. Selectivity of S100A6 Binding to The Four-Helical Cytokines

We have studied the affinity of the Ca2+-loaded (1 mM CaCl2) recombinant human S100A6 protein to the panel of 35 recombinant human four-helical cytokines (including the panel used in [47], extended with Flt3L, SCF, and IL-19), which covers all structural families in this fold (Table S1). The cytokines were immobilized on the surface of the SPR sensor chip via amine coupling, and 61 nM–8 µM solutions of S100A6 were passed over the surface at 25 °C. Whereas nine cytokines (Table S3) did not reveal noticeable effects in response to the S100A6, the SPR sensograms for 26 cytokines showed the S100A6 concentration-dependent effects, characteristic of association–dissociation processes (Figure 1, Figure 2, Figure 3 and Figure 4). The kinetic SPR data were adequately described within the heterogeneous ligand model (1) (Figure 1, Figure 2, Figure 3 and Figure 4, Table 2), which was earlier successfully used for the description of the S100–cytokine interactions [25,43,44,45,46,47,63,64]. The data for IL-2 were described via the one-site binding scheme. The respective equilibrium dissociation constants, Kd, range from 0.3 nM (in the case of THPO, similarly to S100P [47]) to 12 µM (for IL-2) (Table 2). For comparison, the reported SPR estimates of the Kd values for the complexes of Ca2+-bound S100A6 with various extracellular fragments of its receptor, RAGE, are within the range from 28 nM to 13 µM [65,66], whereas the Kd value for the V domain of RAGE measured via isothermal calorimetry is 3 µM [67]. An analysis of the free energy changes upon the S100A6–cytokine interactions (Figure 5), ΔG, shows that the average S100A6 affinities for the cytokines of different SCOP families in the fold decrease in the following order: short-chain cytokines > long-chain cytokines > interferons/IL-10 (ΔG of −49.8 kJ/mol < −47.1 kJ/mol < −46.8 kJ/mol). The same tendency was observed previously for the S100P protein [47].
The S100A6–cytokine complexes easily dissociated upon the removal of Ca2+ via the passage over the SPR chip of 20 mM EDTA solution, pH 8.0, which evidences the importance of the Ca2+-induced structural rearrangement within the S100A6 molecule for efficient interaction with the cytokines. As Ca2+ binding induces the solvent exposure of S100A6 residues of helices α2 and α3 and the ‘hinge’ between them [61], this region is likely involved in the cytokine recognition.
As the equilibrium homodimer dissociation constant for the Ca2+-loaded S100A6 does not exceed 0.5 µM [44], our estimates of its affinities to the cytokines (Table 2) mostly correspond to the dimeric state of S100A6. Meanwhile, serum S100A6 concentrations may be as low as 0.2 pM [68] (Table S4), which indicates that, in serum, S100A6 may exist in a monomeric form.
As the affinities of the S100P monomer to the four-helical cytokines IL-11 and IFN-β exceed those of the S100P dimer by 1.4–2.2 orders of magnitude [25,64,69], S100A6 monomerization is likely to improve its affinity to the four-helical cytokines. In this case, the Kd values for some of the S100A6–cytokine interactions (Flt3L, IL-3, IL-5, IL-9, IL-13, IL-15, IL-21, SCF, THPO; G-CSF, GH, GH-V, IL-31, PRL; IL-19, IL-20, IL-26) may reach the nanomolar level or below (Figure 5), which is enough for efficient cytokine binding to S100A6 which concentrations in serum reach the nanomolar level [68,70,71,72] (Table S4). Moreover, the local levels of extracellular S100A6 in damaged tissues expressing S100A6 should be even higher, further facilitating S100A6–cytokine interactions.
Overall, S100A6 interacts with ca. 73% of the four-helical cytokines studied to date (32 of the 44 cytokines, see Table 1, Table 2 and Table S3). The selectivity of S100A6 binding to the cytokines is equivalent to that of S100P [47], except for the interactions with IL-2 and OSM, which are specific only to S100A6 and S100P, respectively. Importantly, the revealed S100A6–cytokine interactions (Table 2) are non-redundant, as the S100A6-specific cytokines are mostly evolutionary distant from each other; the pairwise sequence identities within each of their SCOP families, calculated using Clustal Omega 2.1 (implemented in the EMBL-EBI service [12]), ranges from 3% to 44% (the exception is the GH–GH-V pair, with a pairwise sequence identity of 93%). According to the IntAct [73] and BioGRID [74] databases, so far, only the S100P protein has been described as a soluble non-receptor extracellular target protein for the following cytokines specific to S100A6 (Table 2): IL-3, IL-5, IL-9, IL-13, IL-21, THPO, and IL-22. Except for IL-22, they are short-chain four-helical cytokines, with the highest average affinity to S100A6 (Figure 5).

3.2. Structural Modeling of The S100A6–Cytokine Complexes

The docking models of the complexes between the Ca2+-loaded S100A6 dimer and the S100A6-specific four-helical cytokines shown in Table 1 and Table 2 (excluding the heterodimeric IL-27/IL-35) were generated using the ClusPro docking server [59], and analyzed as previously described [43,47]. The residues predicted to be involved in the interaction for five or more of the ten docking models are listed in Table S5.
The S100A6 residues predicted to be key in the recognition of the four-helical cytokines (for at least half of the cytokines) are I44 (16 cytokines out of 30) of the ‘hinge’ loop region between helices α2 and α3, R55 and D59 of helix α3 (17 cytokines), and I83 (21 cytokines) and Y84 (18 cytokines) of helix α4 (Figure 6A). An analysis of the distribution of the predicted contact residues of the S100A6 dimer along its amino acid sequence within the models of its complexes with the four-helical cytokines (Figure 6B) shows that cytokines of the different structural families share the contact surfaces of S100A6, including N- and C-termini, helix α1, the ‘hinge’ region, and helices α3 and α4. These regions of the S100A6 dimer form a well-defined cytokine-binding site located between its subunits (Figure 6A), which is remarkably similar to that previously predicted for S100P interaction with the four-helical cytokines [47]. The qualitative difference between the predicted behavior of the S100A6 and S100P proteins is the more complete involvement in cytokine recognition of the helix α3 and the N-terminal half of helix α4 of S100A6. In this sense, the predicted pattern in the contact residues of S100A6 is more reminiscent of that described in S100 proteins, with frequent involvement in the target recognition of helix α1, the ‘hinge’, and helices α3 and α4 [75]. Importantly, only 4 of the 11 residues of S100A6 previously shown to interact with the V domain of RAGE using NMR [67] are predicted to interact with some of the cytokines (4 out of 30): R62 (GH-V, IL-11, IFN-β, IL-20), N63 (IL-11, IFN-β), K64 (IFN-β), and N69 (IL-11) (Table S5). The RAGE-binding site of S100A6 reported in [76] is even more distinct from the predicted cytokine-specific site. Thus, the latter is notably different from the RAGE-binding site.
The molecular docking analysis indicates that the long-chain cytokines preferentially bind the Ca2+-bound S100A6 dimer via the residues of the N-terminus and helices α1 and α3 (Figure 7B). The cytokines of the interferon/IL-10 family are predicted to bind the S100A6 dimer via the residues of the C-terminus and helices α2 and α3 (Figure 7C). However, the predicted locations of the contact residues for the short-chain cytokines do not reveal clear regularities (Figure 7A).
Furthermore, unlike other families of cytokines, this family tends to interact with only one chain of the S100A6 dimer. Therefore, similarly to the S100P binding to the four-helical cytokines [47], the putative location of the S100A6-binding site in the cytokines varies, depending on the structural family of the cytokine, and the particular cytokine. At the same time, analysis of the contact residues (Table S5) indicates that arginines are most vastly involved in S100A6 binding, regardless of the cytokine family (14–22% of the contact residues).
The cytokine residues predicted to interact with S100A6 for some of the short-chain cytokines (GM-CSF, IL-3, IL-13, IL-21, THPO), long-chain cytokines (GH, GH-V, IL-31, PRL), and cytokines of the interferon/IL-10 family (IFN-ω1, IL-10, IL-20, IL-22, and IL-24) overlap by more than 50% with the residues similarly predicted for interaction with the S100P protein [47]. On the contrary, the putative S100A6-binding sites of specific short-chain cytokines (EPO, IL-5, IL-15), long-chain cytokines (LEP), and cytokines of the interferon/IL-10 family (IFN-β, IL-26) do not intersect with the sites predicted for S100P binding [43,47]. Thus, despite the nearly identical selectivity of the S100A6 and S100P proteins with regard to the binding of the four-helical cytokines, and the similar putative locations of their cytokine-binding sites, they could be recognized by the cytokines quite differently.
As some of the predicted S100A6-binding residues of the specific four-helical cytokines (EPO, GM-CSF, IL-2, IL-3, IL-5, IL-13, IL-15, IL-21, GH, IFN-ω1, IL-20, IL-22, and IL-24) have previously been shown to participate in the recognition of their respective receptors (Table S5), S100A6 binding is potentially able to affect the cytokine signaling, as demonstrated via the inhibition of IFN-β signaling in MCF-7 cells by S100A1/A4/B/P [25,44,45], the suppression of the cytotoxic activity of soluble TNF against Huh-7 cells by S100A12/A13 [42], the inhibition of the FGF2-induced increase in the proliferation of MCF-7/MDA-MB468 cells by S100B [40], the FGF2-medited activation of FGFR1 by S100B in myoblasts [41,48], and the S100A4 stimulation of the amphiregulin-mediated proliferation of embryonic fibroblasts [37].
Of note, the presented structural predictions based on the molecular docking suffer from their inability to take into consideration the structural flexibility inherent to the four-helical cytokines, as evidenced by the experimentally confirmed disorder in IL-15, THPO, G-CSF, LEP, and IL-10, and the theoretical predictions described in [47].

3.3. Potential Physiological Significance of the S100A6 Interactions with the Four-Helical Cytokines

To get an insight into the possible relative in vivo concentrations of S100A6 and the S100A6-specific cytokines (Table 1 and Table 2), we collected data from the literature on their concentrations in physiological fluids under normal and pathological conditions (Tables S4 and S6). An examination of the concentration ranges reported for S100A6 and the S100A6-specific cytokines in the blood serum/plasma (Figure 8) highlights several regularities. Firstly, there is an overlap in the concentration ranges for both interaction partners, which indicates the possibility of the mutual regulation of the activity of one of the partners due to an excess of the other partner. The binding of S100A6 could alter the cytokine signaling, as previously shown for IFN-β signaling in MCF-7 cells inhibited by S100A1/A4/B/P [25,44,45], and in other cases [37,40,42]. Alternatively, an excess of the S100A6-specific cytokine over the S100A6 protein could affect its interaction with RAGE [66], integrin β1 [29], and/or other receptors. Secondly, with a few exceptions, there is a trend towards increased cytokine concentrations in pathological conditions, which should promote the formation of the S100A6–cytokine complex. The most favorable conditions for that are expected for GH, GH-V, LEP, PRL, and IL-26, which demonstrate the highest blood levels, exceeding 1 nM (Figure 8). As mentioned above, although the experimental estimates of the equilibrium dissociation constants (Table 2 and Figure 5), Kd, are low enough for efficient S100A6 binding only for THPO, S100A6 monomerization could decrease the Kd values by 1.4–2.2 orders of magnitude, which was earlier shown for the S100P interaction with IL-11 and IFN-β [25,64,69]. In this case, many other cytokines could bind S100A6 in vivo, at concentrations as high as several nM [70] (Table S4).
The binding of S100A6 to the cytokines may also promote their non-canonical secretion, as previously reported for S100A13 binding to IL-1α and FGF1 [38,39] and for CLCF1, which requires CRLF1 binding for efficient secretion [77]. Considering that the sharing of interaction partners is inherent to many S100 proteins, including S100A6 and S100P [50,51], the revealed multiple interactions of the four-helical cytokines with S100A6/S100P, and other members of the S100 family [25,43,44,45,46,47,63,64], could serve as a common mechanism for the non-canonical secretion of the cytokines.

4. Conclusions

In this work, we have extended the list of the four-helical cytokines studied, with regard to their affinity to the promiscuous S100A6 protein [50,51], from nine (see references to Table 1) to forty-four (see also Table S1) cytokines, covering all structural families of this fold. Only 12 out of the 44 cytokines studied using SPR spectroscopy lack a notable specificity to S100A6 (Table S3). The absence of detectable interactions implies that the respective equilibrium dissociation constants, Kd, exceed 10−4 M. Thus, about 73% of the cytokines are specific to the Ca2+-loaded S100A6 dimer, with Kd values in the range from 0.3 nM to 12 µM (Table 2), which intersect with the Kd estimates for the complexes of Ca2+-bound S100A6 with extracellular RAGE fragments from 28 nM to 13 µM [65,66,67]. The fraction of the cytokines specific to S100A6 may be even higher, given the possibility that S100A6 monomerization promotes its interaction with the cytokines. The similarly high percentage of the four-helical cytokines specific to the S100P protein of 71% [47] cannot be attributed to the high homology between S100A6 and S100P, as their pairwise sequence identity is only 35%.
The promiscuous binding of S100A6 and S100P to a wide range of the four-helical cytokines belonging to all structural families of this fold can be partly explained via the molecular docking analysis, which revealed that both S100 proteins have a nearly identical cytokine-binding site formed by helices α1, α3 and α4, and the ‘hinge’ (Figure 6A, [47]). The involvement of the ‘hinge’ and helix α4 in the cytokine recognition was previously confirmed via S100P mutagenesis [47]. This site overlaps with the RAGE-binding site of S100P, but differs markedly from that of S100A6. Meanwhile, the structural modeling shows that the S100-specific four-helical cytokines lack a conserved S100-binding site (Figure 7, [47]). Instead, the location of the putative S100A6/S100P-binding sites of the cytokines is variable, and depends on the particular cytokine. Importantly, the modelling reveals distinct differences in the cytokine regions putatively involved in the recognition of the S100A6 or S100P proteins, which explains some differences in their selectivity to the cytokines (limited to the recognition of IL-2 and OSM). Nevertheless, similarly to the putative S100P-binding sites of the four-helical cytokines [47], some of their predicted S100A6-specific regions are involved in binding of the corresponding receptors. This fact raises the possibility that the interaction of some cytokines with extracellular S100A6/S100P may interfere with the formation of the cytokine-receptor complexes, thereby inhibiting proper signaling (see, for instance, [25,40,42,44,45]). The same effect is expected for other promiscuous members of the S100 family, capable of interaction with multiple common binding partners [50,51]. In this case, the promiscuous S100 proteins are potentially able to serve as universal inhibitors of the signaling of the four-helical cytokines. This unique feature of the S100 family could be used to reduce the severity of the disorders associated with an excessive release of the cytokines, including cytokine storm. Another possibility is the S100-binding induced activation of cytokine signaling, as demonstrated via the FGF2-medited stimulation of FGFR1 by S100B in myoblasts [41,48], and the enhancement of the amphiregulin-induced proliferation of embryonic fibroblasts by S100A4 [37]. Moreover, the cytokine binding could modulate the extracellular activity of the promiscuous S100 proteins in response to the pathological conditions that are accompanied by elevated levels of some four-helical cytokines. Finally, the binding of intracellular S100 proteins could facilitate the non-canonical secretion of certain cytokines [38,39,77].

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/biom13091345/s1, Table S1: The cytokine samples studied with regard to their affinity to Ca2+-loaded S100A6 in the present work; Table S2: The PDB entries or AlphaFold2 predictions used for the structural modelling of the complexes of the Ca2+-loaded human S100A6 dimer (chains A and B of PDB entry 1K9K) with the four-helical cytokines using the ClusPro docking server; Table S3: The samples of the four-helical cytokines lacking specificity to S100A6, as evidenced via SPR experiments, using cytokine as a ligand; Table S4: The serum levels of S100A6 under normal and pathological conditions, according to the literature data; Table S5: The contact residues for the S100A6–cytokine complexes, predicted using the ClusPro docking server (the numbering is according to the PDB entries); Table S6: The literature data on the concentrations of the S100A6-specific four-helical cytokines in the physiological fluids under normal and pathological conditions; Table S7: The concentration ranges of the S100A6-specific cytokines in physiological fluids under normal and pathological conditions, extracted from the literature data collected in Table S6. [47,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234] is mentioned in the Supplementary Materials.

Author Contributions

Conceptualization, S.E.P.; validation, A.S.K., E.I.D., V.A.R., V.N.U., E.A.P. and S.E.P.; formal analysis, A.S.K., E.I.D., V.A.R. and S.E.P.; investigation, A.S.K., E.I.D., V.A.R., A.S.S., M.E.P. and E.A.L.; data curation, A.S.K., E.I.D., V.A.R. and S.E.P.; writing—original draft preparation, A.S.K., E.I.D., V.A.R. and S.E.P.; writing—review and editing, A.S.K., E.I.D., V.A.R., V.N.U., E.A.P. and S.E.P.; supervision, E.A.P. and S.E.P.; project administration, S.E.P.; funding acquisition, S.E.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Russian Science Foundation, grant number 19-14-00289-П to S.E.P.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data present in the current study are available from the corresponding authors on reasonable request.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

CHO, Chinese hamster ovary cells; CLCF1, cardiotrophin-like cytokine factor 1; CNTF, ciliary neurotrophic factor; CT-1, cardiotrophin-1; EDTA, ethylenediaminetetraacetic acid; EPO, erythropoietin; FGF, fibroblast growth factor; ER, endoplasmic reticulum; Flt3L, Fms-related tyrosine kinase 3 ligand; G-CSF, granulocyte colony-stimulating factor; GH, growth hormone; GH-V, growth hormone variant; GM-CSF, granulocyte–macrophage colony-stimulating factor; HEK293, human embryonic kidney 293 cells; HEPES, 4-(2-hydroxyethyl)piperazine-1-ethanesulfonic acid; IFN, interferon; IL, interleukin; LEP, leptin; LIF, leukemia inhibitory factor; M-CSF, macrophage colony-stimulating factor 1; NMR, nuclear magnetic resonance; OSM, oncostatin M; PDB, Protein Data Bank [60]; PL, chorionic somatomammotropin hormone 1; PRL, prolactin; RAGE, receptor for advanced glycation end products; RU, resonance unit; SCF, stem cell factor, soluble form; SCOP, Structural Classification of Proteins [49]; SPR, surface plasmon resonance; THPO, thrombopoietin; TNF, tumor necrosis factor; TSLP, thymic stromal lymphopoietin.

References

  1. Donato, R.; Cannon, B.R.; Sorci, G.; Riuzzi, F.; Hsu, K.; Weber, D.J.; Geczy, C.L. Functions of S100 Proteins. Curr. Mol. Med. 2013, 13, 24–57. [Google Scholar] [CrossRef] [PubMed]
  2. Sreejit, G.; Flynn, M.C.; Patil, M.; Krishnamurthy, P.; Murphy, A.J.; Nagareddy, P.R. S100 family proteins in inflammation and beyond. Adv. Clin. Chem. 2020, 98, 173–231. [Google Scholar] [CrossRef] [PubMed]
  3. Singh, P.; Ali, S.A. Multifunctional Role of S100 Protein Family in the Immune System: An Update. Cells 2022, 11, 2274. [Google Scholar] [CrossRef] [PubMed]
  4. Zimmer, D.B.; Eubanks, J.O.; Ramakrishnan, D.; Criscitiello, M.F. Evolution of the S100 family of calcium sensor proteins. Cell Calcium 2013, 53, 170–179. [Google Scholar] [CrossRef]
  5. Sigrist, C.J.; de Castro, E.; Cerutti, L.; Cuche, B.A.; Hulo, N.; Bridge, A.; Bougueleret, L.; Xenarios, I. New and continuing developments at PROSITE. Nucleic Acids Res. 2013, 41, D344–D347. [Google Scholar] [CrossRef]
  6. Nockolds, C.E.; Kretsinger, R.H.; Coffee, C.J.; Bradshaw, R.A. Structure of a calcium-binding carp myogen. Proc. Natl. Acad. Sci. USA 1972, 69, 581–584. [Google Scholar] [CrossRef]
  7. Gifford, J.L.; Walsh, M.P.; Vogel, H.J. Structures and metal-ion-binding properties of the Ca2+-binding helix-loop-helix EF-hand motifs. Biochem. J. 2007, 405, 199–221. [Google Scholar] [CrossRef]
  8. Kawasaki, H.; Kretsinger, R.H. Structural and functional diversity of EF-hand proteins: Evolutionary perspectives. Protein Sci. 2017, 26, 1898–1920. [Google Scholar] [CrossRef]
  9. Fritz, G.; Heizmann, C.W. 3D Structures of the Calcium and Zinc Binding S100 Proteins. In Handbook of Metalloproteins; John Wiley & Sons: Hoboken, NJ, USA, 2004. [Google Scholar] [CrossRef]
  10. Gilston, B.A.; Skaar, E.P.; Chazin, W.J. Binding of transition metals to S100 proteins. Sci. China Life Sci. 2016, 59, 792–801. [Google Scholar] [CrossRef]
  11. Streicher, W.W.; Lopez, M.M.; Makhatadze, G.I. Modulation of quaternary structure of S100 proteins by calcium ions. Biophys. Chem. 2010, 151, 181–186. [Google Scholar] [CrossRef]
  12. Madeira, F.; Park, Y.M.; Lee, J.; Buso, N.; Gur, T.; Madhusoodanan, N.; Basutkar, P.; Tivey, A.R.N.; Potter, S.C.; Finn, R.D.; et al. The EMBL-EBI search and sequence analysis tools APIs in 2019. Nucleic Acids Res. 2019, 47, W636–W641. [Google Scholar] [CrossRef] [PubMed]
  13. Bresnick, A.R.; Weber, D.J.; Zimmer, D.B. S100 proteins in cancer. Nat. Rev. Cancer 2015, 15, 96–109. [Google Scholar] [CrossRef] [PubMed]
  14. Cristóvão, J.S.; Gomes, C.M. S100 Proteins in Alzheimer’s Disease. Front. Neurosci. 2019, 13, 463. [Google Scholar] [CrossRef] [PubMed]
  15. Holzinger, D.; Tenbrock, K.; Roth, J. Alarmins of the S100-Family in Juvenile Autoimmune and Auto-Inflammatory Diseases. Front. Immunol. 2019, 10, 182. [Google Scholar] [CrossRef]
  16. Sattar, Z.; Lora, A.; Jundi, B.; Railwah, C.; Geraghty, P. The S100 Protein Family as Players and Therapeutic Targets in Pulmonary Diseases. Pulm. Med. 2021, 2021, 5488591. [Google Scholar] [CrossRef]
  17. Gonzalez, L.L.; Garrie, K.; Turner, M.D. Role of S100 proteins in health and disease. Biochim. Biophys. Acta Mol. Cell Res. 2020, 1867, 118677. [Google Scholar] [CrossRef]
  18. Allgower, C.; Kretz, A.L.; von Karstedt, S.; Wittau, M.; Henne-Bruns, D.; Lemke, J. Friend or Foe: S100 Proteins in Cancer. Cancers 2020, 12, 2037. [Google Scholar] [CrossRef]
  19. Bresnick, A.R. S100 proteins as therapeutic targets. Biophys. Rev. 2018, 10, 1617–1629. [Google Scholar] [CrossRef]
  20. Yao, S.; Yang, X.; An, J.; Jin, H.; Wen, G.; Wang, H.; Tuo, B. Role of the S100 protein family in liver disease (Review). Int. J. Mol. Med. 2021, 48, 166. [Google Scholar] [CrossRef]
  21. Xiao, X.; Yang, C.; Qu, S.L.; Shao, Y.D.; Zhou, C.Y.; Chao, R.; Huang, L.; Zhang, C. S100 proteins in atherosclerosis. Clin. Chim. Acta 2020, 502, 293–304. [Google Scholar] [CrossRef]
  22. Engelkamp, D.; Schafer, B.W.; Mattei, M.G.; Erne, P.; Heizmann, C.W. Six S100 genes are clustered on human chromosome 1q21: Identification of two genes coding for the two previously unreported calcium-binding proteins S100D and S100E. Proc. Natl. Acad. Sci. USA 1993, 90, 6547–6551. [Google Scholar] [CrossRef] [PubMed]
  23. Schafer, B.W.; Wicki, R.; Engelkamp, D.; Mattei, M.G.; Heizmann, C.W. Isolation of a YAC clone covering a cluster of nine S100 genes on human chromosome 1q21: Rationale for a new nomenclature of the S100 calcium-binding protein family. Genomics 1995, 25, 638–643. [Google Scholar] [CrossRef] [PubMed]
  24. Marenholz, I.; Lovering, R.C.; Heizmann, C.W. An update of the S100 nomenclature. Biochim. Biophys. Acta 2006, 1763, 1282–1283. [Google Scholar] [CrossRef] [PubMed]
  25. Kazakov, A.S.; Mayorov, S.A.; Deryusheva, E.I.; Avkhacheva, N.V.; Denessiouk, K.A.; Denesyuk, A.I.; Rastrygina, V.A.; Permyakov, E.A.; Permyakov, S.E. Highly specific interaction of monomeric S100P protein with interferon beta. Int. J. Biol. Macromol. 2020, 143, 633–639. [Google Scholar] [CrossRef]
  26. Santamaria-Kisiel, L.; Rintala-Dempsey, A.C.; Shaw, G.S. Calcium-dependent and -independent interactions of the S100 protein family. Biochem. J. 2006, 396, 201–214. [Google Scholar] [CrossRef]
  27. Hsieh, H.L.; Schafer, B.W.; Cox, J.A.; Heizmann, C.W. S100A13 and S100A6 exhibit distinct translocation pathways in endothelial cells. J. Cell Sci. 2002, 115, 3149–3158. [Google Scholar] [CrossRef]
  28. Jurewicz, E.; Wyroba, E.; Filipek, A. Tubulin-dependent secretion of S100A6 and cellular signaling pathways activated by S100A6-integrin beta1 interaction. Cell. Signal. 2018, 42, 21–29. [Google Scholar] [CrossRef]
  29. Jurewicz, E.; Góral, A.; Filipek, A. S100A6 is secreted from Wharton’s jelly mesenchymal stem cells and interacts with integrin β1. Int. Journal. Biochem. Cell Biol. 2014, 55, 298–303. [Google Scholar] [CrossRef]
  30. Rumpret, M.; von Richthofen, H.J.; van der Linden, M.; Westerlaken, G.H.A.; Talavera Ormeno, C.; Low, T.Y.; Ovaa, H.; Meyaard, L. Recognition of S100 proteins by Signal Inhibitory Receptor on Leukocytes-1 negatively regulates human neutrophils. Eur. J. Immunol. 2021, 51, 2210–2217. [Google Scholar] [CrossRef]
  31. Moller, A.; Jauch-Speer, S.L.; Gandhi, S.; Vogl, T.; Roth, J.; Fehler, O. The roles of toll-like receptor 4, CD33, CD68, CD69, or CD147/EMMPRIN for monocyte activation by the DAMP S100A8/S100A9. Front. Immunol. 2023, 14, 1110185. [Google Scholar] [CrossRef]
  32. Ruma, I.M.; Putranto, E.W.; Kondo, E.; Murata, H.; Watanabe, M.; Huang, P.; Kinoshita, R.; Futami, J.; Inoue, Y.; Yamauchi, A.; et al. MCAM, as a novel receptor for S100A8/A9, mediates progression of malignant melanoma through prominent activation of NF-κB and ROS formation upon ligand binding. Clin. Exp. Metastasis 2016, 33, 609–627. [Google Scholar] [CrossRef]
  33. Sakaguchi, M.; Yamamoto, M.; Miyai, M.; Maeda, T.; Hiruma, J.; Murata, H.; Kinoshita, R.; Winarsa Ruma, I.M.; Putranto, E.W.; Inoue, Y.; et al. Identification of an S100A8 Receptor Neuroplastin-beta and its Heterodimer Formation with EMMPRIN. J. Investig. Dermatol. 2016, 136, 2240–2250. [Google Scholar] [CrossRef]
  34. Tomonobu, N.; Kinoshita, R.; Sakaguchi, M. S100 Soil Sensor Receptors and Molecular Targeting Therapy Against Them in Cancer Metastasis. Transl. Oncol. 2020, 13, 100753. [Google Scholar] [CrossRef]
  35. Pankratova, S.; Klingelhofer, J.; Dmytriyeva, O.; Owczarek, S.; Renziehausen, A.; Syed, N.; Porter, A.E.; Dexter, D.T.; Kiryushko, D. The S100A4 Protein Signals through the ErbB4 Receptor to Promote Neuronal Survival. Theranostics 2018, 8, 3977–3990. [Google Scholar] [CrossRef]
  36. Warner-Schmidt, J.L.; Flajolet, M.; Maller, A.; Chen, E.Y.; Qi, H.; Svenningsson, P.; Greengard, P. Role of p11 in cellular and behavioral effects of 5-HT4 receptor stimulation. J. Neurosci. 2009, 29, 1937–1946. [Google Scholar] [CrossRef]
  37. Klingelhofer, J.; Moller, H.D.; Sumer, E.U.; Berg, C.H.; Poulsen, M.; Kiryushko, D.; Soroka, V.; Ambartsumian, N.; Grigorian, M.; Lukanidin, E.M. Epidermal growth factor receptor ligands as new extracellular targets for the metastasis-promoting S100A4 protein. FEBS J. 2009, 276, 5936–5948. [Google Scholar] [CrossRef]
  38. Mohan, S.K.; Yu, C. The IL1alpha-S100A13 heterotetrameric complex structure: A component in the non-classical pathway for interleukin 1alpha secretion. J. Biol. Chem. 2011, 286, 14608–14617. [Google Scholar] [CrossRef]
  39. Carreira, C.M.; LaVallee, T.M.; Tarantini, F.; Jackson, A.; Lathrop, J.T.; Hampton, B.; Burgess, W.H.; Maciag, T. S100A13 is involved in the regulation of fibroblast growth factor-1 and p40 synaptotagmin-1 release in vitro. J. Biol. Chem. 1998, 273, 22224–22231. [Google Scholar] [CrossRef]
  40. Gupta, A.A.; Chou, R.H.; Li, H.C.; Yang, L.W.; Yu, C. Structural insights into the interaction of human S100B and basic fibroblast growth factor (FGF2): Effects on FGFR1 receptor signaling. Bba-Proteins Proteom. 2013, 1834, 2606–2619. [Google Scholar] [CrossRef]
  41. Riuzzi, F.; Sorci, G.; Donato, R. S100B protein regulates myoblast proliferation and differentiation by activating FGFR1 in a bFGF-dependent manner. J. Cell Sci. 2011, 124, 2389–2400. [Google Scholar] [CrossRef]
  42. Kazakov, A.S.; Zemskova, M.Y.; Rystsov, G.K.; Vologzhannikova, A.A.; Deryusheva, E.I.; Rastrygina, V.A.; Sokolov, A.S.; Permyakova, M.E.; Litus, E.A.; Uversky, V.N.; et al. Specific S100 Proteins Bind Tumor Necrosis Factor and Inhibit Its Activity. Int. J. Mol. Sci. 2022, 23, 15956. [Google Scholar] [CrossRef]
  43. Kazakov, A.S.; Deryusheva, E.I.; Sokolov, A.S.; Permyakova, M.E.; Litus, E.A.; Rastrygina, V.A.; Uversky, V.N.; Permyakov, E.A.; Permyakov, S.E. Erythropoietin Interacts with Specific S100 Proteins. Biomolecules 2022, 12, 120. [Google Scholar] [CrossRef] [PubMed]
  44. Kazakov, A.S.; Sofin, A.D.; Avkhacheva, N.V.; Denesyuk, A.I.; Deryusheva, E.I.; Rastrygina, V.A.; Sokolov, A.S.; Permyakova, M.E.; Litus, E.A.; Uversky, V.N.; et al. Interferon Beta Activity Is Modulated via Binding of Specific S100 Proteins. Int. J. Mol. Sci. 2020, 21, 9473. [Google Scholar] [CrossRef] [PubMed]
  45. Kazakov, A.S.; Sofin, A.D.; Avkhacheva, N.V.; Deryusheva, E.I.; Rastrygina, V.A.; Permyakova, M.E.; Uversky, V.N.; Permyakov, E.A.; Permyakov, S.E. Interferon-β Activity Is Affected by S100B Protein. Int. J. Mol. Sci. 2022, 23, 1997. [Google Scholar] [CrossRef]
  46. Kazakov, A.S.; Sokolov, A.S.; Permyakova, M.E.; Litus, E.A.; Uversky, V.N.; Permyakov, E.A.; Permyakov, S.E. Specific cytokines of interleukin-6 family interact with S100 proteins. Cell Calcium 2022, 101, 102520. [Google Scholar] [CrossRef] [PubMed]
  47. Kazakov, A.S.; Deryusheva, E.I.; Permyakova, M.E.; Sokolov, A.S.; Rastrygina, V.A.; Uversky, V.N.; Permyakov, E.A.; Permyakov, S.E. Calcium-Bound S100P Protein Is a Promiscuous Binding Partner of the Four-Helical Cytokines. Int. J. Mol. Sci. 2022, 23, 12000. [Google Scholar] [CrossRef] [PubMed]
  48. Riuzzi, F.; Sorci, G.; Beccafico, S.; Donato, R. S100B engages RAGE or bFGF/FGFR1 in myoblasts depending on its own concentration and myoblast density. Implications for muscle regeneration. PLoS ONE 2012, 7, e28700. [Google Scholar] [CrossRef] [PubMed]
  49. Andreeva, A.; Kulesha, E.; Gough, J.; Murzin, A.G. The SCOP database in 2020: Expanded classification of representative family and superfamily domains of known protein structures. Nucleic Acids Res. 2020, 48, D376–D382. [Google Scholar] [CrossRef]
  50. Simon, M.A.; Ecsedi, P.; Kovacs, G.M.; Poti, A.L.; Remenyi, A.; Kardos, J.; Gogl, G.; Nyitray, L. High-throughput competitive fluorescence polarization assay reveals functional redundancy in the S100 protein family. FEBS J. 2020, 287, 2834–2846. [Google Scholar] [CrossRef]
  51. Simon, M.A.; Bartus, É.; Mag, B.; Boros, E.; Roszjár, L.; Gógl, G.; Travé, G.; Martinek, T.A.; Nyitray, L. Promiscuity mapping of the S100 protein family using a high-throughput holdup assay. Sci. Rep. 2022, 12, 5904. [Google Scholar] [CrossRef]
  52. Donato, R.; Sorci, G.; Giambanco, I. S100A6 protein: Functional roles. Cell. Mol. Life Sci. 2017, 74, 2749–2760. [Google Scholar] [CrossRef] [PubMed]
  53. Lesniak, W.; Wilanowski, T.; Filipek, A. S100A6 - focus on recent developments. Biol. Chem. 2017, 398, 1087–1094. [Google Scholar] [CrossRef] [PubMed]
  54. Lesniak, W.; Filipek, A. S100A6 Protein-Expression and Function in Norm and Pathology. Int. J. Mol. Sci. 2023, 24, 1341. [Google Scholar] [CrossRef]
  55. Filipek, A.; Lesniak, W. S100A6 and Its Brain Ligands in Neurodegenerative Disorders. Int. J. Mol. Sci. 2020, 21, 3979. [Google Scholar] [CrossRef] [PubMed]
  56. Yang, F.; Ma, J.; Zhu, D.; Wang, Z.; Li, Y.; He, X.; Zhang, G.; Kang, X. The Role of S100A6 in Human Diseases: Molecular Mechanisms and Therapeutic Potential. Biomolecules 2023, 13, 1139. [Google Scholar] [CrossRef]
  57. Pace, C.N.; Vajdos, F.; Fee, L.; Grimsley, G.; Gray, T. How to measure and predict the molar absorption coefficient of a protein. Protein Sci. 1995, 4, 2411–2423. [Google Scholar] [CrossRef]
  58. Brocker, C.; Thompson, D.; Matsumoto, A.; Nebert, D.W.; Vasiliou, V. Evolutionary divergence and functions of the human interleukin (IL) gene family. Hum. Genom. 2010, 5, 30–55. [Google Scholar] [CrossRef]
  59. Desta, I.T.; Porter, K.A.; Xia, B.; Kozakov, D.; Vajda, S. Performance and Its Limits in Rigid Body Protein-Protein Docking. Structure 2020, 28, 1071–1081. [Google Scholar] [CrossRef] [PubMed]
  60. Berman, H.M.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T.N.; Weissig, H.; Shindyalov, I.N.; Bourne, P.E. The Protein Data Bank. Nucleic Acids Res. 2000, 28, 235–242. [Google Scholar] [CrossRef]
  61. Otterbein, L.R.; Kordowska, J.; Witte-Hoffmann, C.; Wang, C.L.; Dominguez, R. Crystal structures of S100A6 in the Ca(2+)-free and Ca(2+)-bound states: The calcium sensor mechanism of S100 proteins revealed at atomic resolution. Structure 2002, 10, 557–567. [Google Scholar] [CrossRef]
  62. Jumper, J.; Evans, R.; Pritzel, A.; Green, T.; Figurnov, M.; Ronneberger, O.; Tunyasuvunakool, K.; Bates, R.; Zidek, A.; Potapenko, A.; et al. Highly accurate protein structure prediction with AlphaFold. Nature 2021, 596, 583–589. [Google Scholar] [CrossRef] [PubMed]
  63. Kazakov, A.S.; Sokolov, A.S.; Vologzhannikova, A.A.; Permyakova, M.E.; Khorn, P.A.; Ismailov, R.G.; Denessiouk, K.A.; Denesyuk, A.I.; Rastrygina, V.A.; Baksheeva, V.E.; et al. Interleukin-11 binds specific EF-hand proteins via their conserved structural motifs. J. Biomol. Struct. Dyn. 2017, 35, 78–91. [Google Scholar] [CrossRef] [PubMed]
  64. Kazakov, A.S.; Sokolov, A.S.; Rastrygina, V.A.; Solovyev, V.V.; Ismailov, R.G.; Mikhailov, R.V.; Ulitin, A.B.; Yakovenko, A.R.; Mirzabekov, T.A.; Permyakov, E.A.; et al. High-affinity interaction between interleukin-11 and S100P protein. Biochem. Biophys. Res. Commun. 2015, 468, 733–738. [Google Scholar] [CrossRef]
  65. Leclerc, E. Measuring binding of S100 proteins to RAGE by surface plasmon resonance. Methods Mol. Biol. 2013, 963, 201–213. [Google Scholar] [CrossRef] [PubMed]
  66. Leclerc, E.; Fritz, G.; Weibel, M.; Heizmann, C.W.; Galichet, A. S100B and S100A6 differentially modulate cell survival by interacting with distinct RAGE (receptor for advanced glycation end products) immunoglobulin domains. J. Biol. Chem. 2007, 282, 31317–31331. [Google Scholar] [CrossRef]
  67. Mohan, S.K.; Gupta, A.A.; Yu, C. Interaction of the S100A6 mutant (C3S) with the V domain of the receptor for advanced glycation end products (RAGE). Biochem. Biophys. Res. Commun. 2013, 434, 328–333. [Google Scholar] [CrossRef]
  68. Loosen, S.H.; Benz, F.; Niedeggen, J.; Schmeding, M.; Schuller, F.; Koch, A.; Vucur, M.; Tacke, F.; Trautwein, C.; Roderburg, C.; et al. Serum levels of S100A6 are unaltered in patients with resectable cholangiocarcinoma. Clin. Transl. Med. 2016, 5, 39. [Google Scholar] [CrossRef]
  69. Permyakov, S.E.; Denesyuk, A.I.; Denessiouk, K.A.; Permyakova, M.E.; Kazakov, A.S.; Ismailov, R.G.; Rastrygina, V.A.; Sokolov, A.S.; Permyakov, E.A. Monomeric state of S100P protein: Experimental and molecular dynamics study. Cell Calcium 2019, 80, 152–159. [Google Scholar] [CrossRef]
  70. Guzel, C.; van den Berg, C.B.; Duvekot, J.J.; Stingl, C.; van den Bosch, T.P.P.; van der Weiden, M.; Steegers, E.A.P.; Steegers-Theunissen, R.P.M.; Luider, T.M. Quantification of Calcyclin and Heat Shock Protein 90 in Sera from Women with and without Preeclampsia by Mass Spectrometry. PROTEOMICS–Clin. Appl. 2019, 13, e1800181. [Google Scholar] [CrossRef]
  71. Wang, T.; Liang, Y.; Thakur, A.; Zhang, S.; Yang, T.; Chen, T.; Gao, L.; Chen, M.; Ren, H. Diagnostic significance of S100A2 and S100A6 levels in sera of patients with non-small cell lung cancer. Tumour Biol. 2016, 37, 2299–2304. [Google Scholar] [CrossRef]
  72. Cai, X.Y.; Lu, L.; Wang, Y.N.; Jin, C.; Zhang, R.Y.; Zhang, Q.; Chen, Q.J.; Shen, W.F. Association of increased S100B, S100A6 and S100P in serum levels with acute coronary syndrome and also with the severity of myocardial infarction in cardiac tissue of rat models with ischemia-reperfusion injury. Atherosclerosis 2011, 217, 536–542. [Google Scholar] [CrossRef] [PubMed]
  73. Orchard, S.; Ammari, M.; Aranda, B.; Breuza, L.; Briganti, L.; Broackes-Carter, F.; Campbell, N.H.; Chavali, G.; Chen, C.; del-Toro, N.; et al. The MIntAct project--IntAct as a common curation platform for 11 molecular interaction databases. Nucleic Acids Res. 2014, 42, D358–D363. [Google Scholar] [CrossRef] [PubMed]
  74. Oughtred, R.; Rust, J.; Chang, C.; Breitkreutz, B.J.; Stark, C.; Willems, A.; Boucher, L.; Leung, G.; Kolas, N.; Zhang, F.; et al. The BioGRID database: A comprehensive biomedical resource of curated protein, genetic, and chemical interactions. Protein Sci. 2021, 30, 187–200. [Google Scholar] [CrossRef] [PubMed]
  75. Permyakov, S.E.; Ismailov, R.G.; Xue, B.; Denesyuk, A.I.; Uversky, V.N.; Permyakov, E.A. Intrinsic disorder in S100 proteins. Mol. Biosyst. 2011, 7, 2164–2180. [Google Scholar] [CrossRef]
  76. Yatime, L.; Betzer, C.; Jensen, R.K.; Mortensen, S.; Jensen, P.H.; Andersen, G.R. The Structure of the RAGE:S100A6 Complex Reveals a Unique Mode of Homodimerization for S100 Proteins. Structure 2016, 24, 2043–2052. [Google Scholar] [CrossRef]
  77. Rousseau, F.; Gauchat, J.F.; McLeod, J.G.; Chevalier, S.; Guillet, C.; Guilhot, F.; Cognet, I.; Froger, J.; Hahn, A.F.; Knappskog, P.M.; et al. Inactivation of cardiotrophin-like cytokine, a second ligand for ciliary neurotrophic factor receptor, leads to cold-induced sweating syndrome in a patient. Proc. Natl. Acad. Sci. USA 2006, 103, 10068–10073. [Google Scholar] [CrossRef] [PubMed]
  78. Zhang, J.; Zhang, K.; Jiang, X. S100A6 as a potential serum prognostic biomarker and therapeutic target in gastric cancer. Dig. Dis. Sci. 2014, 59, 2136–2144. [Google Scholar] [CrossRef]
  79. Grote Beverborg, N.; Verweij, N.; Klip, I.T.; van der Wal, H.H.; Voors, A.A.; van Veldhuisen, D.J.; Gansevoort, R.T.; Bakker, S.J.; van der Harst, P.; van der Meer, P. Erythropoietin in the general population: Reference ranges and clinical, biochemical and genetic correlates. PLoS ONE 2015, 10, e0125215. [Google Scholar] [CrossRef]
  80. Szuber, N.; Lavu, S.; Mudireddy, M.; Nicolosi, M.; Penna, D.; Vallapureddy, R.R.; Lasho, T.L.; Finke, C.; Hanson, C.A.; Ketterling, R.P.; et al. Serum erythropoietin levels in essential thrombocythemia: Phenotypic and prognostic correlates. Blood Cancer J. 2018, 8, 118. [Google Scholar] [CrossRef]
  81. Davidovic, S.; Babic, N.; Jovanovic, S.; Barisic, S.; Grkovic, D.; Miljkovic, A. Serum erythropoietin concentration and its correlation with stage of diabetic retinopathy. BMC Ophthalmol. 2019, 19, 227. [Google Scholar] [CrossRef]
  82. Mannello, F.; Fabbri, L.; Ciandrini, E.; Tonti, G.A. Increased levels of erythropoietin in nipple aspirate fluid and in ductal cells from breast cancer patients. Anal. Cell. Oncol. 2008, 30, 51–61. [Google Scholar] [CrossRef]
  83. Varda, M.M.; Tomassetti, S. Erythropoietin Levels in Patients with Polycythemia Vera and Secondary Erythrocytosis. Blood 2022, 140, 12181–12182. [Google Scholar] [CrossRef]
  84. Tas, F.; Oguz, H.; Argon, A.; Duranyildiz, D.; Camlica, H.; Yasasever, V.; Topuz, E. The value of serum levels of IL-6, TNF-alpha, and erythropoietin in metastatic malignant melanoma: Serum IL-6 level is a valuable prognostic factor at least as serum LDH in advanced melanoma. Med. Oncol. 2005, 22, 241–246. [Google Scholar] [CrossRef]
  85. Lyman, S.D.; Seaberg, M.; Hanna, R.; Zappone, J.; Brasel, K.; Abkowitz, J.L.; Prchal, J.T.; Schultz, J.C.; Shahidi, N.T. Plasma/serum levels of flt3 ligand are low in normal individuals and highly elevated in patients with Fanconi anemia and acquired aplastic anemia. Blood 1995, 86, 4091–4096. [Google Scholar] [CrossRef]
  86. Zwierzina, H.; Anderson, J.E.; Rollinger-Holzinger, I.; Torok-Storb, B.; Nuessler, V.; Lyman, S.D. Endogenous FLT-3 ligand serum levels are associated with disease stage in patients with myelodysplastic syndromes. Leukemia 1999, 13, 553–557. [Google Scholar] [CrossRef]
  87. Peterlin, P.; Gaschet, J.; Guillaume, T.; Garnier, A.; Eveillard, M.; Le Bourgeois, A.; Cherel, M.; Debord, C.; Le Bris, Y.; Theisen, O.; et al. FLT3 ligand plasma levels in acute myeloid leukemia. Haematologica 2019, 104, e240–e243. [Google Scholar] [CrossRef]
  88. Tobon, G.J.; Saraux, A.; Gottenberg, J.E.; Quartuccio, L.; Fabris, M.; Seror, R.; Devauchelle-Pensec, V.; Morel, J.; Rist, S.; Mariette, X.; et al. Role of Fms-like tyrosine kinase 3 ligand as a potential biologic marker of lymphoma in primary Sjogren’s syndrome. Arthritis Rheum. 2013, 65, 3218–3227. [Google Scholar] [CrossRef]
  89. Papagoras, C.; Tsiami, S.; Chrysanthopoulou, A.; Mitroulis, I.; Baraliakos, X. Serum granulocyte-macrophage colony-stimulating factor (GM-CSF) is increased in patients with active radiographic axial spondyloarthritis and persists despite anti-TNF treatment. Arthritis Res. Ther. 2022, 24, 195. [Google Scholar] [CrossRef]
  90. Riccio, A.; De Caterina, M.; Natale, D.; Grimaldi, E.; Pronesti, G.; Montagnani, S.; Postiglione, L. Serum Levels of Granulocyte Macrophage Colony Stimulating Factor (GM-CSF) in a Group of Patients with Systemic Sclerosis. Int. J. Immunopathol. Pharmacol. 1996, 9, 9–12. [Google Scholar] [CrossRef]
  91. Balleari, E.; Bason, C.; Visani, G.; Gobbi, M.; Ottaviani, E.; Ghio, R. Serum levels of granulocyte-macrophage colony-stimulating factor and granulocyte colony-stimulating factor in treated patients with chronic myelogenous leukemia in chronic phase. Haematologica 1994, 79, 7–12. [Google Scholar]
  92. Fiehn, C.; Wermann, M.; Pezzutto, A.; Hufner, M.; Heilig, B. Plasma GM-CSF concentrations in rheumatoid arthritis, systemic lupus erythematosus and spondyloarthropathy. Z. Rheumatol. 1992, 51, 121–126. [Google Scholar]
  93. Carrieri, P.B.; Provitera, V.; De Rosa, T.; Tartaglia, G.; Gorga, F.; Perrella, O. Profile of cerebrospinal fluid and serum cytokines in patients with relapsing-remitting multiple sclerosis: A correlation with clinical activity. Immunopharmacol. Immunotoxicol. 1998, 20, 373–382. [Google Scholar] [CrossRef]
  94. Kleiner, G.; Marcuzzi, A.; Zanin, V.; Monasta, L.; Zauli, G. Cytokine levels in the serum of healthy subjects. Mediators Inflamm. 2013, 2013, 434010. [Google Scholar] [CrossRef] [PubMed]
  95. Huan, X.; Zhao, R.; Song, J.; Zhong, H.; Su, M.; Yan, C.; Wang, Y.; Chen, S.; Zhou, Z.; Lu, J.; et al. Increased serum IL-2, IL-4, IL-5 and IL-12p70 levels in AChR subtype generalized myasthenia gravis. BMC Immunol. 2022, 23, 26. [Google Scholar] [CrossRef] [PubMed]
  96. Li, B.; Guo, Q.; Wang, Y.; Su, R.; Gao, C.; Zhao, J.; Li, X.; Wang, C. Increased Serum Interleukin-2 Levels Are Associated with Abnormal Peripheral Blood Natural Killer Cell Levels in Patients with Active Rheumatoid Arthritis. Mediat. Inflamm. 2020, 2020, 6108342. [Google Scholar] [CrossRef] [PubMed]
  97. Kasumagic-Halilovic, E.; Cavaljuga, S.; Ovcina-Kurtovic, N.; Zecevic, L. Serum Levels of Interleukin-2 in Patients with Alopecia Areata: Relationship with Clinical Type and Duration of the Disease. Skin. Appendage Disord. 2018, 4, 286–290. [Google Scholar] [CrossRef]
  98. Ceyhan, B.B.; Enc, F.Y.; Sahin, S. IL-2 and IL-10 levels in induced sputum and serum samples of asthmatics. J. Investig. Allergol. Clin. Immunol. 2004, 14, 80–85. [Google Scholar]
  99. Kutukculer, N.; Vergin, C.; Cetingul, N.; Kavakli, K.; Caglayan, S.; Oztop, S.; Nisli, G. Plasma interleukin-3 (IL-3) and IL-7 concentrations in children with homozygous beta-thalassemia. J. Trop. Pediatr. 1997, 43, 366–367. [Google Scholar] [CrossRef]
  100. Biancotto, A.; Wank, A.; Perl, S.; Cook, W.; Olnes, M.J.; Dagur, P.K.; Fuchs, J.C.; Langweiler, M.; Wang, E.; McCoy, J.P. Baseline levels and temporal stability of 27 multiplexed serum cytokine concentrations in healthy subjects. PLoS ONE 2013, 8, e76091. [Google Scholar] [CrossRef]
  101. Xiu, M.H.; Lin, C.G.; Tian, L.; Tan, Y.L.; Chen, J.; Chen, S.; Tan, S.P.; Wang, Z.R.; Yang, F.D.; Chen, D.C.; et al. Increased IL-3 serum levels in chronic patients with schizophrenia: Associated with psychopathology. Psychiatry Res. 2015, 229, 225–229. [Google Scholar] [CrossRef]
  102. Vasiliades, G.; Kopanakis, N.; Vasiloglou, M.; Zografos, G.; Margaris, H.; Masselou, K.; Kokosi, E.; Liakakos, T. Role of the hematopoietic cytokines SCF, IL-3, GM-CSF and M-CSF in the diagnosis of pancreatic and ampullary cancer. Int. J. Biol. Markers 2012, 27, e186–e194. [Google Scholar] [CrossRef]
  103. Lee, H.L.; Jang, J.W.; Lee, S.W.; Yoo, S.H.; Kwon, J.H.; Nam, S.W.; Bae, S.H.; Choi, J.Y.; Han, N.I.; Yoon, S.K. Inflammatory cytokines and change of Th1/Th2 balance as prognostic indicators for hepatocellular carcinoma in patients treated with transarterial chemoembolization. Sci. Rep. 2019, 9, 3260. [Google Scholar] [CrossRef] [PubMed]
  104. Lee, Y.C.; Lee, K.H.; Lee, H.B.; Rhee, Y.K. Serum levels of interleukins (IL)-4, IL-5, IL-13, and interferon-gamma in acute asthma. J. Asthma 2001, 38, 665–671. [Google Scholar] [CrossRef] [PubMed]
  105. Joseph, J.; Benedict, S.; Safa, W.; Joseph, M. Serum interleukin-5 levels are elevated in mild and moderate persistent asthma irrespective of regular inhaled glucocorticoid therapy. BMC Pulm. Med. 2004, 4, 2. [Google Scholar] [CrossRef] [PubMed]
  106. Dimitrova, D.; Youroukova, V.; Ivanova-Todorova, E.; Tumangelova-Yuzeir, K.; Velikova, T. Serum levels of IL-5, IL-6, IL-8, IL-13 and IL-17A in pre-defined groups of adult patients with moderate and severe bronchial asthma. Respir. Med. 2019, 154, 144–154. [Google Scholar] [CrossRef]
  107. Perret, J.; McDonald, C.; Apostolopoulos, V. Elevated serum interleukin-5 levels in severe chronic obstructive pulmonary disease. Acta Biochim. Biophys. Sin. 2017, 49, 560–563. [Google Scholar] [CrossRef]
  108. Fischer, M.; Bijman, M.; Molin, D.; Cormont, F.; Uyttenhove, C.; van Snick, J.; Sundstrom, C.; Enblad, G.; Nilsson, G. Increased serum levels of interleukin-9 correlate to negative prognostic factors in Hodgkin’s lymphoma. Leukemia 2003, 17, 2513–2516. [Google Scholar] [CrossRef]
  109. Dantas, A.T.; Marques, C.D.L.; da Rocha Junior, L.F.; Cavalcanti, M.B.; Gonçalves, S.M.C.; Cardoso, P.R.G.; Mariz, H.d.A.; Rego, M.J.B.d.M.; Duarte, A.L.B.P.; Pitta, I.d.R.; et al. Increased Serum Interleukin-9 Levels in Rheumatoid Arthritis and Systemic Lupus Erythematosus: Pathogenic Role or Just an Epiphenomenon? Dis. Markers 2015, 2015, 519638. [Google Scholar] [CrossRef]
  110. Huang, Y.; Cao, Y.; Zhang, S.; Gao, F. Association between low expression levels of interleukin-9 and colon cancer progression. Exp. Ther. Med. 2015, 10, 942–946. [Google Scholar] [CrossRef]
  111. Erpenbeck, V.J.; Hohlfeld, J.M.; Volkmann, B.; Hagenberg, A.; Geldmacher, H.; Braun, A.; Krug, N. Segmental allergen challenge in patients with atopic asthma leads to increased IL-9 expression in bronchoalveolar lavage fluid lymphocytes. J. Allergy Clin. Immunol. 2003, 111, 1319–1327. [Google Scholar] [CrossRef]
  112. Mahdaviani, S.A.; Eskian, M.; Khorasanizadeh, M.; Bashardoost, B.; Tashayoie Nejad, S.; Jamaati, H.R.; Rezaei, A.; Sadr, M.; Aryan, Z.; Rezaei, N. Interleukin 9 serum level and single nucleotide polymorphism in patients with asthma. Acta Biomed. 2021, 92, e2021206. [Google Scholar] [CrossRef] [PubMed]
  113. Defendenti, C.; Sarzi-Puttini, P.; Saibeni, S.; Bollani, S.; Bruno, S.; Almasio, P.L.; Declich, P.; Atzeni, F. Significance of serum Il-9 levels in inflammatory bowel disease. Int. J. Immunopathol. Pharmacol. 2015, 28, 569–575. [Google Scholar] [CrossRef] [PubMed]
  114. Lv, X.; Feng, L.; Ge, X.; Lu, K.; Wang, X. Interleukin-9 promotes cell survival and drug resistance in diffuse large B-cell lymphoma. J. Exp. Clin. Cancer Res. 2016, 35, 106. [Google Scholar] [CrossRef]
  115. Ciprandi, G.; De Amici, M.; Castellazzi, A.M.; Tosca, M.A.; Marseglia, G. Serum IL-9 levels depend on allergen exposure: Preliminary study. Int. Arch. Allergy Immunol. 2011, 154, 246–248. [Google Scholar] [CrossRef]
  116. Yanaba, K.; Yoshizaki, A.; Asano, Y.; Kadono, T.; Sato, S. Serum interleukin 9 levels are increased in patients with systemic sclerosis: Association with lower frequency and severity of pulmonary fibrosis. J. Rheumatol. 2011, 38, 2193–2197. [Google Scholar] [CrossRef] [PubMed]
  117. Martínez-Reyes, C.P.; Gómez-Arauz, A.Y.; Torres-Castro, I.; Manjarrez-Reyna, A.N.; Palomera, L.F.; Olivos-García, A.; Mendoza-Tenorio, E.; Sánchez-Medina, G.A.; Islas-Andrade, S.; Melendez-Mier, G.; et al. Serum Levels of Interleukin-13 Increase in Subjects with Insulin Resistance but Do Not Correlate with Markers of Low-Grade Systemic Inflammation. J. Diabetes Res. 2018, 2018, 7209872. [Google Scholar] [CrossRef]
  118. Nabavi, M.; Arshi, S.; Bahrami, A.; Aryan, Z.; Bemanian, M.H.; Esmaeilzadeh, H.; Jalali, F.; Pousti, S.B.; Rezaei, N. Increased level of interleukin-13, but not interleukin-4 and interferon-γ in chronic rhinosinusitis with nasal polyps. Allergol. Immunopathol. 2014, 42, 465–471. [Google Scholar] [CrossRef]
  119. Cingu, A.K.; Turkcu, F.M.; Aktas, S.; Sahin, A.; Ayyildiz, O. Serum IL-4, IL-12, IL-13, IL-27, and IL-33 levels in active and inactive ocular Behcet’s disease. Int. Ophthalmol. 2020, 40, 3441–3451. [Google Scholar] [CrossRef]
  120. Spadaro, A.; Rinaldi, T.; Riccieri, V.; Valesini, G.; Taccari, E. Interleukin 13 in synovial fluid and serum of patients with psoriatic arthritis. Ann. Rheum. Dis. 2002, 61, 174–176. [Google Scholar] [CrossRef]
  121. Versace, A.G.; Bitto, A.; Ioppolo, C.; Aragona, C.O.; La Rosa, D.; Roberts, W.N.; D’Angelo, T.; Cinquegrani, A.; Cirmi, S.; Irrera, N.; et al. IL-13 and IL-33 Serum Levels Are Increased in Systemic Sclerosis Patients With Interstitial Lung Disease. Front. Med. 2022, 9, 825567. [Google Scholar] [CrossRef]
  122. Mielnik, P.; Chwalinska-Sadowska, H.; Wiesik-Szewczyk, E.; Maslinski, W.; Olesinska, M. Serum concentration of interleukin 15, interleukin 2 receptor and TNF receptor in patients with polymyositis and dermatomyositis: Correlation to disease activity. Rheumatol. Int. 2012, 32, 639–643. [Google Scholar] [CrossRef] [PubMed]
  123. Kaibe, M.; Ohishi, M.; Ito, N.; Yuan, M.; Takagi, T.; Terai, M.; Tatara, Y.; Komai, N.; Rakugi, H.; Ogihara, T. Serum Interleukin-15 Concentration in Patients With Essential Hypertension*. Am. J. Hypertens. 2005, 18, 1019–1025. [Google Scholar] [CrossRef] [PubMed]
  124. Jang, G.-C.; Kim, H.-Y.; Ahn, S.-Y.; Kim, D.-S. Raised serum interleukin 15 levels in Kawasaki disease. Ann. Rheum. Dis. 2003, 62, 264–266. [Google Scholar] [CrossRef]
  125. Mengus, C.; Le Magnen, C.; Trella, E.; Yousef, K.; Bubendorf, L.; Provenzano, M.; Bachmann, A.; Heberer, M.; Spagnoli, G.C.; Wyler, S. Elevated levels of circulating IL-7 and IL-15 in patients with early stage prostate cancer. J. Transl. Med. 2011, 9, 162. [Google Scholar] [CrossRef] [PubMed]
  126. Rentzos, M.; Cambouri, C.; Rombos, A.; Nikolaou, C.; Anagnostouli, M.; Tsoutsou, A.; Dimitrakopoulos, A.; Triantafyllou, N.; Vassilopoulos, D. IL-15 is elevated in serum and cerebrospinal fluid of patients with multiple sclerosis. J. Neurol. Sci. 2006, 241, 25–29. [Google Scholar] [CrossRef]
  127. Fehniger, T.A.; Caligiuri, M.A. Interleukin 15: Biology and relevance to human disease. Blood 2001, 97, 14–32. [Google Scholar] [CrossRef]
  128. Lauw, F.N.; Simpson, A.J.H.; Prins, J.M.; Smith, M.D.; Kurimoto, M.; van Deventer, S.J.H.; Speelman, P.; Chaowagul, W.; White, N.J.; van der Poll, T. Elevated Plasma Concentrations of Interferon (IFN)-γ and the IFN-γ—Inducing Cytokines Interleukin (IL)-18, IL-12, and IL-15 in Severe Melioidosis. J. Infect. Dis. 1999, 180, 1878–1885. [Google Scholar] [CrossRef]
  129. Vivanco-Cid, H.; Maldonado-Renteria, M.J.; Sanchez-Vargas, L.A.; Izaguirre-Hernandez, I.Y.; Hernandez-Flores, K.G.; Remes-Ruiz, R. Dynamics of interleukin-21 production during the clinical course of primary and secondary dengue virus infections. Immunol. Lett. 2014, 161, 89–95. [Google Scholar] [CrossRef]
  130. de Oliveira, P.S.; Cardoso, P.R.; Lima, E.V.; Pereira, M.C.; Duarte, A.L.; Pitta Ida, R.; Rego, M.J.; Pitta, M.G. IL-17A, IL-22, IL-6, and IL-21 Serum Levels in Plaque-Type Psoriasis in Brazilian Patients. Mediat. Inflamm. 2015, 2015, 819149. [Google Scholar] [CrossRef]
  131. Bae, Y.J.; Kim, M.H.; Lee, H.Y.; Uh, Y.; Namgoong, M.K.; Cha, B.H.; Chun, J.K. Elevated Serum Levels of IL-21 in Kawasaki Disease. Allergy Asthma Immunol. Res. 2012, 4, 351–356. [Google Scholar] [CrossRef]
  132. Bono, P.; Krause, A.; von Mehren, M.; Heinrich, M.C.; Blanke, C.D.; Dimitrijevic, S.; Demetri, G.D.; Joensuu, H. Serum KIT and KIT ligand levels in patients with gastrointestinal stromal tumors treated with imatinib. Blood 2004, 103, 2929–2935. [Google Scholar] [CrossRef] [PubMed]
  133. Makowska, J.S.; Cieslak, M.; Kowalski, M.L. Stem cell factor and its soluble receptor (c-kit) in serum of asthmatic patients- correlation with disease severity. BMC Pulm. Med. 2009, 9, 27. [Google Scholar] [CrossRef] [PubMed]
  134. Kalmarzi, R.N.; Foroutan, A.; Abdi, M.; Ataee, P.; Jalili, A.; Babaei, E.; Kashefi, H.; Mohamadi, S.; Sigari, N.; Kooti, W. Serum level of stem cell factor and its soluble receptor in aspirin-exacerbated respiratory disease. Immunotherapy 2019, 11, 1283–1291. [Google Scholar] [CrossRef]
  135. Mashayekhi, F.; Shabani, S.; Sasani, S.T.; Salehi, Z. The association of stem cell factor and soluble c-Kit (s-cKit) receptor serum concentrations with the severity and risk prediction of autism spectrum disorders. Metab. Brain Dis. 2022, 37, 619–624. [Google Scholar] [CrossRef]
  136. Leyhe, T.; Hoffmann, N.; Stransky, E.; Laske, C. Increase of SCF plasma concentration during donepezil treatment of patients with early Alzheimer’s disease. Int. J. Neuropsychopharmacol. 2009, 12, 1319–1326. [Google Scholar] [CrossRef]
  137. Temel, T.; Cansu, D.U.; Temel, H.E.; Ozakyol, A.H. Serum thrombopoietin levels and its relationship with thrombocytopenia in patients with cirrhosis. Hepat. Mon. 2014, 14, e18556. [Google Scholar] [CrossRef] [PubMed]
  138. Usuki, K.; Tahara, T.; Iki, S.; Endo, M.; Osawa, M.; Kitazume, K.; Kato, T.; Miyazaki, H.; Urabe, A. Serum thrombopoietin level in various hematological diseases. Stem Cells 1996, 14, 558–565. [Google Scholar] [CrossRef]
  139. Ballmaier, M.; Schulze, H.; Strauβ, G.; Cherkaoui, K.; Wittner, N.; Lynen, S.; Wolters, S.; Bogenberger, J.; Welte, K. Thrombopoietin in Patients With Congenital Thrombocytopenia and Absent Radii: Elevated Serum Levels, Normal Receptor Expression, But Defective Reactivity to Thrombopoietin. Blood 1997, 90, 612–619. [Google Scholar] [CrossRef]
  140. Tsukishiro, S.; Suzumori, N.; Nishikawa, H.; Arakawa, A.; Suzumori, K. Preoperative serum thrombopoietin levels are higher in patients with ovarian cancer than with benign cysts. Eur. J. Obstet. Gynecol. Reprod. Biol. 2008, 140, 67–70. [Google Scholar] [CrossRef]
  141. Makar, R.S.; Zhukov, O.S.; Sahud, M.A.; Kuter, D.J. Thrombopoietin levels in patients with disorders of platelet production: Diagnostic potential and utility in predicting response to TPO receptor agonists. Am. J. Hematol. 2013, 88, 1041–1044. [Google Scholar] [CrossRef] [PubMed]
  142. Chebotareva, N.; Vinogradov, A.; Cao, V.; Gindis, A.; Berns, A.; Alentov, I.; Sergeeva, N. Serum levels of plasminogen activator urokinase receptor and cardiotrophin-like cytokine factor 1 in patients with nephrotic syndrome. Clin. Nephrol. 2022, 97, 103–110. [Google Scholar] [CrossRef] [PubMed]
  143. Muller-Deile, J.; Sarau, G.; Kotb, A.M.; Jaremenko, C.; Rolle-Kampczyk, U.E.; Daniel, C.; Kalkhof, S.; Christiansen, S.H.; Schiffer, M. Novel diagnostic and therapeutic techniques reveal changed metabolic profiles in recurrent focal segmental glomerulosclerosis. Sci. Rep. 2021, 11, 4577. [Google Scholar] [CrossRef] [PubMed]
  144. Robak, T.; Gladalska, A.; Stepien, H.; Robak, E. Serum levels of interleukin-6 type cytokines and soluble interleukin-6 receptor in patients with rheumatoid arthritis. Mediat. Inflamm. 1998, 7, 347–353. [Google Scholar] [CrossRef]
  145. Laaksovirta, H.; Soinila, S.; Hukkanen, V.; Roytta, M.; Soilu-Hanninen, M. Serum level of CNTF is elevated in patients with amyotrophic lateral sclerosis and correlates with site of disease onset. Eur. J. Neurol. 2008, 15, 355–359. [Google Scholar] [CrossRef] [PubMed]
  146. Druzhkova, T.A.; Yakovlev, A.A.; Rider, F.K.; Zinchuk, M.S.; Guekht, A.B.; Gulyaeva, N.V. Elevated Serum Cortisol Levels in Patients with Focal Epilepsy, Depression, and Comorbid Epilepsy and Depression. Int. J. Mol. Sci. 2022, 23. [Google Scholar] [CrossRef]
  147. Shpak, A.A.; Guekht, A.B.; Druzhkova, T.A.; Kozlova, K.I.; Gulyaeva, N.V. Ciliary neurotrophic factor in patients with primary open-angle glaucoma and age-related cataract. Mol. Vis. 2017, 23, 799–809. [Google Scholar]
  148. Brondino, N.; Rocchetti, M.; Fusar-Poli, L.; Damiani, S.; Goggi, A.; Chiodelli, G.; Corti, S.; Visai, L.; Politi, P. Increased CNTF levels in adults with autism spectrum disorders. World J. Biol. Psychiatry 2019, 20, 742–746. [Google Scholar] [CrossRef]
  149. Perugini, J.; Di Mercurio, E.; Giuliani, A.; Sabbatinelli, J.; Bonfigli, A.R.; Tortato, E.; Severi, I.; Cinti, S.; Olivieri, F.; le Roux, C.W.; et al. Ciliary neurotrophic factor is increased in the plasma of patients with obesity and its levels correlate with diabetes and inflammation indices. Sci. Rep. 2022, 12, 8331. [Google Scholar] [CrossRef]
  150. Wang, K.; Chu, C.; Hu, J.; Wang, Y.; Zheng, W.; Lv, Y.; Yan, Y.; Ma, Q.; Mu, J. Effect of Salt Intake on the Serum Cardiotrophin-1 Levels in Chinese Adults. Ann. Nutr. Metab. 2018, 73, 302–309. [Google Scholar] [CrossRef]
  151. Cakir, I.; Uluhan, M. Cardiotrophin-1 and leptin as cardiovascular risk markers in male patients with obstructive sleep apnea syndrome. Arch. Med. Sci. Atheroscler. Dis. 2018, 3, e123–e128. [Google Scholar] [CrossRef]
  152. Calabro, P.; Limongelli, G.; Riegler, L.; Maddaloni, V.; Palmieri, R.; Golia, E.; Roselli, T.; Masarone, D.; Pacileo, G.; Golino, P.; et al. Novel insights into the role of cardiotrophin-1 in cardiovascular diseases. J. Mol. Cell. Cardiol. 2009, 46, 142–148. [Google Scholar] [CrossRef]
  153. Monserrat, L.; Lopez, B.; Gonzalez, A.; Hermida, M.; Fernandez, X.; Ortiz, M.; Barriales-Villa, R.; Castro-Beiras, A.; Diez, J. Cardiotrophin-1 plasma levels are associated with the severity of hypertrophy in hypertrophic cardiomyopathy. Eur. Heart J. 2011, 32, 177–183. [Google Scholar] [CrossRef] [PubMed]
  154. Kawakami, M.; Tsutsumi, H.; Kumakawa, T.; Abe, H.; Hirai, M.; Kurosawa, S.; Mori, M.; Fukushima, M. Levels of serum granulocyte colony-stimulating factor in patients with infections. Blood 1990, 76, 1962–1964. [Google Scholar] [CrossRef]
  155. Bordbar, E.; Malekzadeh, M.; Ardekani, M.T.; Doroudchi, M.; Ghaderi, A. Serum levels of G-CSF and IL-7 in Iranian breast cancer patients. Asian Pac. J. Cancer Prev. 2012, 13, 5307–5312. [Google Scholar] [CrossRef] [PubMed]
  156. Pauksen, K.; Elfman, L.; Ulfgren, A.K.; Venge, P. Serum levels of granulocyte-colony stimulating factor (G-CSF) in bacterial and viral infections, and in atypical pneumonia. Br. J. Haematol. 1994, 88, 256–260. [Google Scholar] [CrossRef]
  157. Morozumi, K.; Namiki, S.; Kudo, T.; Aizawa, M.; Ioritani, N. Serum G-CSF May Be a More Valuable Biomarker than Image Evaluation in G-CSF-Producing Urothelial Carcinoma: A Case Report. Case Rep. Oncol. 2017, 10, 377–382. [Google Scholar] [CrossRef] [PubMed]
  158. Galvan, S.T.; Flores-Lopez, M.; Romero-Sanchiz, P.; Requena-Ocana, N.; Porras-Perales, O.; Nogueira-Arjona, R.; Mayoral, F.; Araos, P.; Serrano, A.; Muga, R.; et al. Plasma concentrations of granulocyte colony-stimulating factor (G-CSF) in patients with substance use disorders and comorbid major depressive disorder. Sci. Rep. 2021, 11, 13629. [Google Scholar] [CrossRef] [PubMed]
  159. Watari, K.; Asano, S.; Shirafuji, N.; Kodo, H.; Ozawa, K.; Takaku, F.; Kamachi, S. Serum granulocyte colony-stimulating factor levels in healthy volunteers and patients with various disorders as estimated by enzyme immunoassay. Blood 1989, 73, 117–122. [Google Scholar] [CrossRef]
  160. Gross-Weege, W.; Dumon, K.; Dahmen, A.; Schneider, E.M.; Röher, H.D. Granulocyte colony-stimulating factor (G-CSF) serum levels in surgical intensive care patients. Infection 1997, 25, 213–216. [Google Scholar] [CrossRef]
  161. Triantafillidis, J.K.; Merikas, E.; Govosdis, V.; Konstandellou, E.; Cheracakis, P.; Barbatzas, C.; Tzourmakliotis, D.; Peros, G. Increased fasting serum levels of growth hormone and gastrin in patients with gastric and large bowel cancer. Hepatogastroenterology 2003, 50 (Suppl. S2), cclvi–cclx. [Google Scholar]
  162. Elkarow, M.H.; Hamdy, A. A Suggested Role of Human Growth Hormone in Control of the COVID-19 Pandemic. Front. Endocrinol. 2020, 11, 569633. [Google Scholar] [CrossRef] [PubMed]
  163. Akirov, A.; Masri-Iraqi, H.; Dotan, I.; Shimon, I. The Biochemical Diagnosis of Acromegaly. J. Clin. Med. 2021, 10. [Google Scholar] [CrossRef]
  164. Ishikawa, M.; Yokoya, S.; Tachibana, K.; Hasegawa, Y.; Yasuda, T.; Tokuhiro, E.; Hashimoto, Y.; Tanaka, T. Serum levels of 20-kilodalton human growth hormone (GH) are parallel those of 22-kilodalton human GH in normal and short children. J. Clin. Endocrinol. Metab. 1999, 84, 98–104. [Google Scholar] [CrossRef]
  165. Christiansen, M. Placental growth hormone and growth hormone binding protein are first trimester maternal serum markers of Down syndrome. Prenat. Diagn. 2009, 29, 1249–1255. [Google Scholar] [CrossRef] [PubMed]
  166. Mittal, P.; Espinoza, J.; Hassan, S.; Kusanovic, J.P.; Edwin, S.S.; Nien, J.K.; Gotsch, F.; Than, N.G.; Erez, O.; Mazaki-Tovi, S.; et al. Placental growth hormone is increased in the maternal and fetal serum of patients with preeclampsia. J. Matern. Fetal Neonatal Med. 2007, 20, 651–659. [Google Scholar] [CrossRef] [PubMed]
  167. Wu, J.; Chen, J.; Lv, X.; Yang, Q.; Yao, S.; Zhang, D. Clinical value of serum and exhaled breath condensate inflammatory factor IL-11 levels in non-small cell lung cancer: Clinical value of IL-11 in non-small cell lung cancer. Int. J. Biol. Markers 2021, 36, 64–76. [Google Scholar] [CrossRef]
  168. Ye, J.; Wang, Z.; Ye, D.; Wang, Y.; Wang, M.; Ji, Q.; Huang, Y.; Liu, L.; Shi, Y.; Shi, L.; et al. Increased Interleukin-11 Levels Are Correlated with Cardiac Events in Patients with Chronic Heart Failure. Mediat. Inflamm. 2019, 2019, 1575410. [Google Scholar] [CrossRef]
  169. Trontzas, P.; Kamper, E.F.; Potamianou, A.; Kyriazis, N.C.; Kritikos, H.; Stavridis, J. Comparative study of serum and synovial fluid interleukin-11 levels in patients with various arthritides. Clin. Biochem. 1998, 31, 673–679. [Google Scholar] [CrossRef]
  170. Ren, C.; Chen, Y.; Han, C.; Fu, D.; Chen, H. Plasma interleukin-11 (IL-11) levels have diagnostic and prognostic roles in patients with pancreatic cancer. Tumour Biol. 2014, 35, 11467–11472. [Google Scholar] [CrossRef]
  171. Wu, P.; Lin, B.; Huang, S.; Meng, J.; Zhang, F.; Zhou, M.; Hei, X.; Ke, Y.; Yang, H.; Huang, D. IL-11 Is Elevated and Drives the Profibrotic Phenotype Transition of Orbital Fibroblasts in Thyroid-Associated Ophthalmopathy. Front. Endocrinol. 2022, 13, 846106. [Google Scholar] [CrossRef]
  172. Hassan, W.A.; Hamaad, G.A.; Sayed, E.A.; El Behisy, M.M.; Gomaa, M.K. Clinical significance of interleukin 27 serum concentration in patients with systemic sclerosis: Relation to clinical, laboratory and radiological parameters. Egypt. Rheumatol. Rehabil. 2019, 46, 101–107. [Google Scholar] [CrossRef]
  173. Swaminathan, S.; Hu, Z.; Rupert, A.W.; Higgins, J.M.; Dewar, R.L.; Stevens, R.; Chen, Q.; Rehm, C.A.; Metcalf, J.A.; Baseler, M.W.; et al. Plasma Interleukin-27 (IL-27) Levels Are Not Modulated in Patients with Chronic HIV-1 Infection. PLoS ONE 2014, 9, e98989. [Google Scholar] [CrossRef] [PubMed]
  174. Hassan, T.; Abdel Rahman, D.; Raafat, N.; Fathy, M.; Shehab, M.; Hosny, A.; Fawzy, R.; Zakaria, M. Contribution of interleukin 27 serum level to pathogenesis and prognosis in children with immune thrombocytopenia. Medicine 2022, 101, e29504. [Google Scholar] [CrossRef]
  175. Jafarzadeh, A.; Nemati, M.; Rezayati, M.T. Serum levels of interleukin (IL)-27 in patients with ischemic heart disease. Cytokine 2011, 56, 153–156. [Google Scholar] [CrossRef] [PubMed]
  176. Yan, A.; You, H.; Zhang, X. Levels of Interleukin 27 and Interleukin 35 in the Serum and Vitreous of Patients with Proliferative Diabetic Retinopathy. Ocul. Immunol. Inflamm. 2018, 26, 273–279. [Google Scholar] [CrossRef]
  177. Lukawska-Tatarczuk, M.; Franek, E.; Czupryniak, L.; Joniec-Maciejak, I.; Pawlak, A.; Wojnar, E.; Zielinski, J.; Mirowska-Guzel, D.; Mrozikiewicz-Rakowska, B. Sirtuin 1, Visfatin and IL-27 Serum Levels of Type 1 Diabetic Females in Relation to Cardiovascular Parameters and Autoimmune Thyroid Disease. Biomolecules 2021, 11. [Google Scholar] [CrossRef]
  178. Forrester, M.A.; Robertson, L.; Bayoumi, N.; Keavney, B.D.; Barker, R.N.; Vickers, M.A. Human interleukin-27: Wide individual variation in plasma levels and complex inter-relationships with interleukin-17A. Clin. Exp. Immunol. 2014, 178, 373–383. [Google Scholar] [CrossRef]
  179. Ezzat, M.H.; Hasan, Z.E.; Shaheen, K.Y. Serum measurement of interleukin-31 (IL-31) in paediatric atopic dermatitis: Elevated levels correlate with severity scoring. J. Eur. Acad. Dermatol. Venereol. 2011, 25, 334–339. [Google Scholar] [CrossRef]
  180. Ginaldi, L.; De Martinis, M.; Ciccarelli, F.; Saitta, S.; Imbesi, S.; Mannucci, C.; Gangemi, S. Increased levels of interleukin 31 (IL-31) in osteoporosis. BMC Immunol. 2015, 16, 60. [Google Scholar] [CrossRef]
  181. Mohd Ashari, N.S.; Syuhada Mohd Amin, S.N.; Wan Abdul Hamid, W.Z.; Musa, M.; Rahman, A.A.; Mohamad, I. Determination of interleukin 31 (IL-31) serum levels in allergic rhinitis patients. Int. J. Pediatr. Adolesc. Med. 2014, 1, 69–72. [Google Scholar] [CrossRef]
  182. Rosine, N.; Etcheto, A.; Hendel-Chavez, H.; Seror, R.; Briot, K.; Molto, A.; Chanson, P.; Taoufik, Y.; Wendling, D.; Lories, R.; et al. Increase In Il-31 Serum Levels Is Associated With Reduced Structural Damage In Early Axial Spondyloarthritis. Sci. Rep. 2018, 8, 7731. [Google Scholar] [CrossRef] [PubMed]
  183. Swierczynska, K.; Krajewski, P.K.; Nowicka-Suszko, D.; Bialynicki-Birula, R.; Krajewska, M.; Szepietowski, J.C. The Serum Level of IL-31 in Patients with Chronic Kidney Disease-Associated Pruritus: What Can We Expect? Toxins 2022, 14. [Google Scholar] [CrossRef] [PubMed]
  184. Raap, U.; Wichmann, K.; Bruder, M.; Stander, S.; Wedi, B.; Kapp, A.; Werfel, T. Correlation of IL-31 serum levels with severity of atopic dermatitis. J. Allergy Clin. Immunol. 2008, 122, 421–423. [Google Scholar] [CrossRef]
  185. Zeng, X.; Zhang, Z.; Gao, Q.Q.; Wang, Y.Y.; Yu, X.Z.; Zhou, B.; Xi, M.R. Clinical Significance of Serum Interleukin-31 and Interleukin-33 Levels in Patients of Endometrial Cancer: A Case Control Study. Dis. Markers 2016, 2016, 9262919. [Google Scholar] [CrossRef] [PubMed]
  186. Lu, Y.; Yuan, Y. Serum level of interleukin-17 and interleukin-35 as a biomarker for diagnosis of thyroid cancer. J. Cancer Res. Ther. 2015, 11 Suppl. 2, C209–C211. [Google Scholar] [CrossRef]
  187. Ahmed, H.A.; Maklad, A.M.; Khaled, S.A.; Elyamany, A. Interleukin-27 and interleukin-35 in de novo acute myeloid leukemia: Expression and significance as biological markers. J. Blood Med. 2019, 10, 341–349. [Google Scholar] [CrossRef]
  188. Su, Y.; Feng, S.; Luo, L.; Liu, R.; Yi, Q. Association between IL-35 and coronary arterial lesions in children with Kawasaki disease. Clin. Exp. Med. 2019, 19, 87–92. [Google Scholar] [CrossRef]
  189. Mann, H.; Krystufkova, O.; Zamecnik, J.; Hacek, J.; Hulejova, H.; Filkova, M.; Vencovsky, J.; Senolt, L. Interleukin-35 in idiopathic inflammatory myopathies. Cytokine 2021, 137, 155350. [Google Scholar] [CrossRef]
  190. Li, W.; Gao, R.; Xin, T.; Gao, P. Different expression levels of interleukin-35 in asthma phenotypes. Respir. Res. 2020, 21, 89. [Google Scholar] [CrossRef]
  191. Zhang, N.; Dai, H.; Dong, X.; Liu, W.; Jiang, H.; Zhao, Q.; Gao, Y.; Feng, Z.; Dong, Z.; Hu, Y.; et al. Level of interleukin-35 in patients with idiopathic membranous nephropathy and its predictive value for remission time. Front. Immunol. 2022, 13, 926368. [Google Scholar] [CrossRef]
  192. Chen, B.; Liu, Y.N.; Ji, L.; Liu, P.L.; He, J.; Gan, Y.Y.; Ji, G.J.; Zhu, S.Y.; Zhang, W.H. Elevated levels of interleukin-35 and interleukin-37 in adult patients with obstructive sleep apnea. J. Clin. Lab. Anal. 2021, 35, e23790. [Google Scholar] [CrossRef] [PubMed]
  193. Szczepankiewicz, D.; Sobkowiak, P.; Narozna, B.; Wojsyk-Banaszak, I.; Breborowicz, A.; Szczepankiewicz, A. Leptin gene polymorphism affects leptin level in childhood asthma. World J. Pediatr. 2018, 14, 601–606. [Google Scholar] [CrossRef]
  194. Kvistad, S.S.; Myhr, K.M.; Holmoy, T.; Benth, J.S.; Wergeland, S.; Beiske, A.G.; Bjerve, K.S.; Hovdal, H.; Midgard, R.; Sagen, J.V.; et al. Serum levels of leptin and adiponectin are not associated with disease activity or treatment response in multiple sclerosis. J. Neuroimmunol. 2018, 323, 73–77. [Google Scholar] [CrossRef]
  195. Fahmi, R.M.; Kamel, A.E.; Elsayed, D.A.; Zidan, A.A.; Sarhan, N.T. Serum levels of leptin and adiponectin in patients with multiple sclerosis. Egypt. J. Neurol. Psychiatry Neurosurg. 2021, 57, 114. [Google Scholar] [CrossRef]
  196. Demiray, G.; Degirmencioglu, S.; Ugurlu, E.; Yaren, A. Effects of Serum Leptin and Resistin Levels on Cancer Cachexia in Patients With Advanced-Stage Non-Small Cell Lung Cancer. Clin. Med. Insights Oncol. 2017, 11, 1179554917690144. [Google Scholar] [CrossRef]
  197. Duan, D.M.; Jhang, J.Y.; Wu, S.; Teng, M.S.; Hsu, L.A.; Ko, Y.L. Modification effect of sex and obesity on the correlation of LEP polymorphisms with leptin levels in Taiwanese obese women. Mol. Genet. Genom. Med. 2020, 8, e1113. [Google Scholar] [CrossRef] [PubMed]
  198. Ko, B.J.; Lee, M.; Park, H.S.; Han, K.; Cho, G.J.; Hwang, T.G.; Kim, J.H.; Lee, S.H.; Lee, H.Y.; Kim, S.M. Elevated vaspin and leptin levels are associated with obesity in prepubertal Korean children. Endocr. J. 2013, 60, 609–616. [Google Scholar] [CrossRef]
  199. Juhasz, E.; Kiss, E.; Simonova, E.; Patocs, A.; Reismann, P. Serum prolactin as a biomarker for the study of intracerebral dopamine effect in adult patients with phenylketonuria: A cross-sectional monocentric study. Eur. J. Med. Res. 2016, 21, 22. [Google Scholar] [CrossRef]
  200. Jacobi, A.M.; Rohde, W.; Ventz, M.; Riemekasten, G.; Burmester, G.R.; Hiepe, F. Enhanced serum prolactin (PRL) in patients with systemic lupus erythematosus: PRL levels are related to the disease activity. Lupus 2001, 10, 554–561. [Google Scholar] [CrossRef]
  201. Keen, M.A.; Hassan, I. Serum prolactin levels in psoriasis and its association with disease activity: A case-control study. Indian J. Dermatol. 2014, 59, 562–566. [Google Scholar] [CrossRef]
  202. Cohen, A.D.; Cohen, Y.; Maislos, M.; Buskila, D. Prolactin serum level in patients with breast cancer. Isr. Med. Assoc. J. 2000, 2, 287–289. [Google Scholar] [PubMed]
  203. Al-Nami, M.S.; Al-Kuraishy, H.M.; Al-Gareeb, A.I.; Al-Mamoori, F. Metabolic profile and prolactin serum levels in men with type 2 diabetes mellitus: Old-new rubric. Int. J. Crit. Illn. Inj. Sci. 2019, 9, 120–126. [Google Scholar] [CrossRef] [PubMed]
  204. Pech Torres, R.E.; Cedillo Rivera, R.M.; Lorono Pino, M.A.; Sanchez Burgos, G.G. Serum levels of IFN-beta are associated with days of evolution but not with severity of dengue. J. Med. Virol. 2016, 88, 395–399. [Google Scholar] [CrossRef] [PubMed]
  205. Cheng, C.W.; Tang, K.T.; Fang, W.F.; Lee, T.I.; Lin, J.D. Differential serum interferon-beta levels in autoimmune thyroid diseases. Arch. Med. Sci. 2022, 18, 1231–1240. [Google Scholar] [CrossRef]
  206. Liao, A.P.; Salajegheh, M.; Nazareno, R.; Kagan, J.C.; Jubin, R.G.; Greenberg, S.A. Interferon beta is associated with type 1 interferon-inducible gene expression in dermatomyositis. Ann. Rheum. Dis. 2011, 70, 831–836. [Google Scholar] [CrossRef] [PubMed]
  207. Gonzalez-Garza, M.T.; Elva Cruz-Vega, D.; Maldonado-Bernal, C. IL10 as Cancer Biomarker. Transl. Res. Cancer 2021. [Google Scholar] [CrossRef]
  208. Sobhan, M.R.; Farshchian, M.; Hoseinzadeh, A.; Ghasemibasir, H.R.; Solgi, G. Serum Levels of IL-10 and IL-22 Cytokines in Patients with Psoriasis. Iran. J. Immunol. 2016, 13, 317–323. [Google Scholar]
  209. Della Bella, C.; Antico, A.; Panozzo, M.P.; Capitani, N.; Benagiano, M.; Petrone, L.; Azzurri, A.; Pratesi, S.; D’Elios, S.; Cianchi, F.; et al. Elevated IL-19 Serum Levels in Patients With Pernicious Anemia and Autoimmune Gastritis. Front. Immunol. 2022, 13, 887256. [Google Scholar] [CrossRef]
  210. Saleh, H.M.; Deif, M.A.; El-Husseiny, R.M. Assessment of serum interleukin-19 in acne vulgaris patients of different clinical severities. J. Cosmet. Dermatol. 2021, 20, 3034–3040. [Google Scholar] [CrossRef]
  211. Konrad, R.J.; Higgs, R.E.; Rodgers, G.H.; Ming, W.; Qian, Y.W.; Bivi, N.; Mack, J.K.; Siegel, R.W.; Nickoloff, B.J. Assessment and Clinical Relevance of Serum IL-19 Levels in Psoriasis and Atopic Dermatitis Using a Sensitive and Specific Novel Immunoassay. Sci. Rep. 2019, 9, 5211. [Google Scholar] [CrossRef]
  212. Rong, B.; Liu, Y.; Li, M.; Fu, T.; Gao, W.; Liu, H. Correlation of serum levels of HIF-1alpha and IL-19 with the disease progression of COPD: A retrospective study. Int. J. Chron. Obstruct. Pulmon. Dis. 2018, 13, 3791–3803. [Google Scholar] [CrossRef] [PubMed]
  213. Dumycz, K.; Kunkiel, K.; Stelmaszczyk-Emmel, A.; Józefczuk, P.; Ambrozej, D.; Feleszko, W. The role and association of plasma level of IL-19 and pro-inflammatory cytokines (IL-17A, IL-4 and IL-1β) with severity of atopic dermatitis in children. World Allergy Organ. J. 2020, 13, 100217. [Google Scholar] [CrossRef]
  214. Saheb Sharif-Askari, F.; Saheb Sharif-Askari, N.; Hafezi, S.; Goel, S.; Ali Hussain Alsayed, H.; Ansari, A.W.; Mahboub, B.; Al-Muhsen, S.; Temsah, M.H.; Hamid, Q.; et al. Upregulation of interleukin-19 in saliva of patients with COVID-19. Sci. Rep. 2022, 12, 16019. [Google Scholar] [CrossRef] [PubMed]
  215. Hussien, D.T.; Shabana, A.A.; Hassan, A.S.; Elmarghany, E.B. Assessment of serum interleukin-20 level in rheumatoid arthritis patients: Relation to disease activity and ultrasound measures. Egypt. Rheumatol. 2022, 44, 181–186. [Google Scholar] [CrossRef]
  216. Michalak-Stoma, A.; Bartosinska, J.; Kowal, M.; Juszkiewicz-Borowiec, M.; Gerkowicz, A.; Chodorowska, G. Serum levels of selected Th17 and Th22 cytokines in psoriatic patients. Dis. Markers 2013, 35, 625–631. [Google Scholar] [CrossRef] [PubMed]
  217. Hsu, Y.H.; Li, H.H.; Hsieh, M.Y.; Liu, M.F.; Huang, K.Y.; Chin, L.S.; Chen, P.C.; Cheng, H.H.; Chang, M.S. Function of interleukin-20 as a proinflammatory molecule in rheumatoid and experimental arthritis. Arthritis Rheum. 2006, 54, 2722–2733. [Google Scholar] [CrossRef]
  218. Naumnik, W.; Naumnik, B.; Niklińska, W.; Ossolińska, M.; Chyczewska, E. Clinical Implications of Hepatocyte Growth Factor, Interleukin-20, and Interleukin-22 in Serum and Bronchoalveolar Fluid of Patients with Non-Small Cell Lung Cancer. In Advancements in Clinical Research; Pokorski, M., Ed.; Springer International Publishing: Cham, Switzerland, 2016; pp. 41–49. [Google Scholar]
  219. Kragstrup, T.W.; Otkjaer, K.; Holm, C.; Jorgensen, A.; Hokland, M.; Iversen, L.; Deleuran, B. The expression of IL-20 and IL-24 and their shared receptors are increased in rheumatoid arthritis and spondyloarthropathy. Cytokine 2008, 41, 16–23. [Google Scholar] [CrossRef] [PubMed]
  220. Valentina, M.; Jan, F.; Peder, N.L.; Bo, Z.; Hongjie, D.; Pernille, K. Cytokine detection and simultaneous assessment of rheumatoid factor interference in human serum and synovial fluid using high-sensitivity protein arrays on plasmonic gold chips. BMC Biotechnol. 2015, 15, 73. [Google Scholar] [CrossRef]
  221. Aydogdu, E.; Pamuk, O.N.; Donmez, S.; Pamuk, G.E. Decreased interleukin-20 level in patients with systemic sclerosis: Are they related with angiogenesis? Clin. Rheumatol. 2013, 32, 1599–1603. [Google Scholar] [CrossRef]
  222. Wang, T.; Zhang, Z.; Xing, H.; Wang, L.; Zhang, G.; Yu, N.; Wang, J.; Guo, W.; Jiang, J. Elevated Th22 cells and related cytokines in patients with epithelial ovarian cancer. Medicine 2017, 96, e8359. [Google Scholar] [CrossRef]
  223. Tsirakis, G.; Pappa, C.A.; Kolovou, A.; Kokonozaki, M.; Neonakis, I.; Alexandrakis, M.G. Clinical significance of interleukin-22 in multiple myeloma. Hematology 2015, 20, 143–147. [Google Scholar] [CrossRef] [PubMed]
  224. Souza, J.M.; Matias, B.F.; Rodrigues, C.M.; Murta, E.F.; Michelin, M.A. IL-17 and IL-22 serum cytokine levels in patients with squamous intraepithelial lesion and invasive cervical carcinoma. Eur. J. Gynaecol. Oncol. 2013, 34, 466–468. [Google Scholar] [PubMed]
  225. Abdullah, H.N.; Abdulwahid, A.G. Expression of Serum IL-22, IL-23, and TLR9 as Tumor Markers in Untreated Breast Cancer Patients. J. Drug Deliv. 2020, 10, 472–476. [Google Scholar] [CrossRef]
  226. Thomas-Dupont, P.; Remes-Troche, J.M.; Izaguirre-Hernández, I.Y.; Sánchez-Vargas, L.A.; Maldonado-Rentería, M.d.J.; Hernández-Flores, K.G.; Torre, A.; Bravo-Sarmiento, E.; Vivanco-Cid, H. Elevated circulating levels of IL-21 and IL-22 define a cytokine signature profile in type 2 autoimmune hepatitis patients. Ann. Hepatol. 2016, 15, 550–558. [Google Scholar]
  227. Khoshroo, M.; Yazdanpanah, M.J.; Yasrebi, S. Serum Interleukin-24 Levels in Gastric and Breast Cancers and Non-cancerous Inflammations. Middle East J. of Cancer 2021, 12, 183–189. [Google Scholar] [CrossRef]
  228. Li, R.C.; Guo, J.; Su, L.C.; Huang, A.F. Elevated levels of IL-24 in systemic lupus erythematosus patients. Lupus 2019, 28, 748–754. [Google Scholar] [CrossRef] [PubMed]
  229. Brilland, B.; Bach-Bunner, M.; Gomes, C.N.; Larochette, V.; Foucher, E.; Plaisance, M.; Saulnier, P.; Costedoat-Chalumeau, N.; Ghillani, P.; Belizna, C.; et al. Serum Interleukin-26 Is a New Biomarker for Disease Activity Assessment in Systemic Lupus Erythematosus. Front. Immunol. 2021, 12, 663192. [Google Scholar] [CrossRef] [PubMed]
  230. Shen, Y.; Dong, X.; Liu, J.; Lv, H.; Ge, Y. Serum Interleukin-26 is a Potential Biomarker for the Differential Diagnosis of Neurosyphilis and Syphilis at Other Stages. Infect. Drug Resist. 2022, 15, 3693–3702. [Google Scholar] [CrossRef]
  231. Louhaichi, S.; Mlika, M.; Hamdi, B.; Hamzaoui, K.; Hamzaoui, A. Sputum IL-26 Is Overexpressed in Severe Asthma and Induces Proinflammatory Cytokine Production and Th17 Cell Generation: A Case-Control Study of Women. J. Asthma Allergy 2020, 13, 95–107. [Google Scholar] [CrossRef]
  232. Kaabachi, W.; Bouali, E.; Berraïes, A.; Dhifallh, I.B.; Hamdi, B.; Hamzaoui, K.; Hamzaoui, A. Interleukin-26 is overexpressed in Behçet’s disease and enhances Th17 related −cytokines. Immunol. Lett. 2017, 190, 177–184. [Google Scholar] [CrossRef]
  233. Pinero, P.; Juanola, O.; Gutierrez, A.; Zapater, P.; Gimenez, P.; Steinert, A.; Sempere, L.; Gonzalez-Navajas, J.M.; Niess, J.H.; Frances, R. IL26 modulates cytokine response and anti-TNF consumption in Crohn’s disease patients with bacterial DNA. J. Mol. Med. 2017, 95, 1227–1236. [Google Scholar] [CrossRef] [PubMed]
  234. Corvaisier, M.; Delneste, Y.; Jeanvoine, H.; Preisser, L.; Blanchard, S.; Garo, E.; Hoppe, E.; Barre, B.; Audran, M.; Bouvard, B.; et al. IL-26 is overexpressed in rheumatoid arthritis and induces proinflammatory cytokine production and Th17 cell generation. PLoS Biol. 2012, 10, e1001395. [Google Scholar] [CrossRef]
Figure 1. SPR spectroscopy data on the kinetics of association/dissociation of the complexes of Ca2+-bound S100A6 with the short-chain four-helical cytokines (see Table 2) immobilized on the sensor chip surface via amine coupling, at 25 °C: (A) Flt3L, (B) GM-CSF, (C) IL-2, (D) IL-3, (E) IL-5, (F) IL-9. The association phase is marked by the vertical dotted lines. The micromolar concentrations of S100A6 are indicated for the sensograms. The experimental curves (grey) are described via the heterogeneous ligand model (1) or the one-site binding model (black curves) (see Table 2).
Figure 1. SPR spectroscopy data on the kinetics of association/dissociation of the complexes of Ca2+-bound S100A6 with the short-chain four-helical cytokines (see Table 2) immobilized on the sensor chip surface via amine coupling, at 25 °C: (A) Flt3L, (B) GM-CSF, (C) IL-2, (D) IL-3, (E) IL-5, (F) IL-9. The association phase is marked by the vertical dotted lines. The micromolar concentrations of S100A6 are indicated for the sensograms. The experimental curves (grey) are described via the heterogeneous ligand model (1) or the one-site binding model (black curves) (see Table 2).
Biomolecules 13 01345 g001
Figure 2. SPR spectroscopy data on the kinetics of association/dissociation of the complexes of Ca2+-bound S100A6 with the short-chain four-helical cytokines (see Table 2) immobilized on the sensor chip surface via amine coupling at 25 °C: (A) IL-13, (B) IL-15, (C) IL-21, (D) SCF, (E) THPO. The experimental curves (grey) are described via the heterogeneous ligand model (1) (black curves) (see Table 2). For other designations, refer to the caption to Figure 1.
Figure 2. SPR spectroscopy data on the kinetics of association/dissociation of the complexes of Ca2+-bound S100A6 with the short-chain four-helical cytokines (see Table 2) immobilized on the sensor chip surface via amine coupling at 25 °C: (A) IL-13, (B) IL-15, (C) IL-21, (D) SCF, (E) THPO. The experimental curves (grey) are described via the heterogeneous ligand model (1) (black curves) (see Table 2). For other designations, refer to the caption to Figure 1.
Biomolecules 13 01345 g002
Figure 3. SPR spectroscopy data on the kinetics of association/dissociation of the complexes of Ca2+-loaded S100A6 with the long-chain four-helical cytokines (see Table 2) immobilized on the sensor chip surface via amine coupling, 25 °C: (A) G-CSF, (B) GH, (C) GH-V, (D) IL-27, (E) IL-31, (F) IL-35, (G) LEP, (H) PRL. The experimental curves (grey) are described via the heterogeneous ligand model (1) (black curves) (see Table 2). For other designations, refer to the caption to Figure 1.
Figure 3. SPR spectroscopy data on the kinetics of association/dissociation of the complexes of Ca2+-loaded S100A6 with the long-chain four-helical cytokines (see Table 2) immobilized on the sensor chip surface via amine coupling, 25 °C: (A) G-CSF, (B) GH, (C) GH-V, (D) IL-27, (E) IL-31, (F) IL-35, (G) LEP, (H) PRL. The experimental curves (grey) are described via the heterogeneous ligand model (1) (black curves) (see Table 2). For other designations, refer to the caption to Figure 1.
Biomolecules 13 01345 g003
Figure 4. SPR spectroscopy data on the kinetics of association/dissociation of the complexes of Ca2+-bound S100A6 with the interferons/IL-10 four-helical cytokines (see Table 2) immobilized on the sensor chip surface via amine coupling at 25 °C: (A) IFN-ω1, (B) IL-10, (C) IL-19, (D) IL-20, (E) IL-22, (F) IL-24, (G) IL-26. The experimental curves (grey) are described via the heterogeneous ligand model (1) (black curves) (see Table 2). For other designations, refer to the caption to Figure 1.
Figure 4. SPR spectroscopy data on the kinetics of association/dissociation of the complexes of Ca2+-bound S100A6 with the interferons/IL-10 four-helical cytokines (see Table 2) immobilized on the sensor chip surface via amine coupling at 25 °C: (A) IFN-ω1, (B) IL-10, (C) IL-19, (D) IL-20, (E) IL-22, (F) IL-24, (G) IL-26. The experimental curves (grey) are described via the heterogeneous ligand model (1) (black curves) (see Table 2). For other designations, refer to the caption to Figure 1.
Biomolecules 13 01345 g004
Figure 5. The free energy changes upon the binding of Ca2+-loaded S100A6 to the four-helical cytokines of short-chain (panel A), long-chain (B), or interferon/IL-10 (C) families at 25 °C, estimated from the SPR data shown in Table 2. The scale of Kd values is indicated.
Figure 5. The free energy changes upon the binding of Ca2+-loaded S100A6 to the four-helical cytokines of short-chain (panel A), long-chain (B), or interferon/IL-10 (C) families at 25 °C, estimated from the SPR data shown in Table 2. The scale of Kd values is indicated.
Biomolecules 13 01345 g005
Figure 6. (A) The cytokine-binding site predicted for the Ca2+-loaded S100A6 dimer (PDB entry 1K9K) using the ClusPro docking server [59] and the tertiary structures listed in Table S2. The chains A and B are highlighted in cyan and grey, respectively. The α-helices are labeled as α1–α4, and the Ca2+-binding loops are yellow-colored. The S100A6 residues predicted to recognize at least 10 out of the 30 four-helical cytokines (I44, E52, R55, D59, I83, Y84, E86, A87, and K89 of chain A, and A2 and D6 of chain B) are marked as an orange mesh surface, whereas the residues predicted to interact with at least half of the cytokines (I44, R55, D59, I83, and Y84) are shown as red balls and sticks. (B) Distributions of the predicted contact residues of S100A6 over its amino acid sequence, within the docking models of S100A6 complexes with the four-helical cytokines shown in Table S2 (10 models per each S100A6–cytokine pair). The boundaries of the α-helices α1–α4 are extracted from PDB entry 1K9K; the residues I44, R55, D59, I83, and Y84 of chain A are marked in red.
Figure 6. (A) The cytokine-binding site predicted for the Ca2+-loaded S100A6 dimer (PDB entry 1K9K) using the ClusPro docking server [59] and the tertiary structures listed in Table S2. The chains A and B are highlighted in cyan and grey, respectively. The α-helices are labeled as α1–α4, and the Ca2+-binding loops are yellow-colored. The S100A6 residues predicted to recognize at least 10 out of the 30 four-helical cytokines (I44, E52, R55, D59, I83, Y84, E86, A87, and K89 of chain A, and A2 and D6 of chain B) are marked as an orange mesh surface, whereas the residues predicted to interact with at least half of the cytokines (I44, R55, D59, I83, and Y84) are shown as red balls and sticks. (B) Distributions of the predicted contact residues of S100A6 over its amino acid sequence, within the docking models of S100A6 complexes with the four-helical cytokines shown in Table S2 (10 models per each S100A6–cytokine pair). The boundaries of the α-helices α1–α4 are extracted from PDB entry 1K9K; the residues I44, R55, D59, I83, and Y84 of chain A are marked in red.
Biomolecules 13 01345 g006
Figure 7. The S100A6-binding sites (orange-colored; see Table S5) predicted for the four-helical cytokines of the short-chain (A), long-chain (B), and interferon/IL-10 (C) families, using the ClusPro docking server [59], and the tertiary structures listed in Table S2. Only one subunit of IL-5 is shown. The N-terminus of each cytokine is located in the lower left corner. The analogous predictions for the S100P protein are presented in [47].
Figure 7. The S100A6-binding sites (orange-colored; see Table S5) predicted for the four-helical cytokines of the short-chain (A), long-chain (B), and interferon/IL-10 (C) families, using the ClusPro docking server [59], and the tertiary structures listed in Table S2. Only one subunit of IL-5 is shown. The N-terminus of each cytokine is located in the lower left corner. The analogous predictions for the S100P protein are presented in [47].
Biomolecules 13 01345 g007
Figure 8. The concentration ranges of the S100A6-specific cytokines in the blood serum or plasma under normal (blue bars) and pathological (red bars) conditions, extracted from the literature data (see Table S7). The blue and red dotted lines correspond to the upper limits of S100A6 serum levels in health and disease, respectively, according to the literature data (see Table S4).
Figure 8. The concentration ranges of the S100A6-specific cytokines in the blood serum or plasma under normal (blue bars) and pathological (red bars) conditions, extracted from the literature data (see Table S7). The blue and red dotted lines correspond to the upper limits of S100A6 serum levels in health and disease, respectively, according to the literature data (see Table S4).
Biomolecules 13 01345 g008
Table 1. The literature data on the equilibrium dissociation constants for the complexes between Ca2+-loaded S100A6 and four-helical cytokines at 25 °C. The SPR spectroscopy data (the amine coupling of the cytokine on the SPR chip surface) are described using the heterogeneous ligand model (1).
Table 1. The literature data on the equilibrium dissociation constants for the complexes between Ca2+-loaded S100A6 and four-helical cytokines at 25 °C. The SPR spectroscopy data (the amine coupling of the cytokine on the SPR chip surface) are described using the heterogeneous ligand model (1).
CytokineKd1, MKd2, MReference
Short-chain cytokines
EPO(1.5 ± 0.3) × 10−7(6.5 ± 2.6) × 10−7[43]
Long-chain cytokines
CLCF1(1.1 ± 0.8) × 10−6(3.7 ± 0.8) × 10−6[46]
CNTF(1.1 ± 1.0) × 10−7(2.07 ± 0.08) × 10−6[46]
CT-1(1.6 ± 0.5) × 10−6(1.2 ± 0.4) × 10−5[46]
IL-11(8.3 ± 1.9) × 10−6(7.9 ± 2.1) × 10−6[46]
Interferons/IL-10
IFN-β(8.2 ± 2.4) × 10−8
(0.70 ± 0.03) × 10−9 *
(2.67 ± 0.57) × 10−7
(2.81 ± 0.49) × 10−7 *
[44]
* S100A6 serves as a ligand.
Table 2. The parameters of the interactions between Ca2+-bound S100A6 and the specific four-helical cytokines shown in Table S1 at 25 °C, derived from the SPR spectroscopy data (Figure 1, Figure 2, Figure 3 and Figure 4), using the heterogeneous ligand model (1).
Table 2. The parameters of the interactions between Ca2+-bound S100A6 and the specific four-helical cytokines shown in Table S1 at 25 °C, derived from the SPR spectroscopy data (Figure 1, Figure 2, Figure 3 and Figure 4), using the heterogeneous ligand model (1).
Cytokinekd1, s−1Kd1, Mkd2, s−1Kd2, M
Short-chain cytokines
Flt3L(8.83 ± 2.54) × 10−4(1.22 ± 0.27) × 10−7(8.32 ± 4.05) × 10−4(1.25 ± 0.46) × 10−7
GM-CSF(7.92 ± 4.02) × 10−4(2.26 ± 1.18) × 10−6(1.76 ± 0.49) × 10−2(3.63 ± 1.14) × 10−6
IL-2 *(4.97 ± 0.78) × 10−3(1.20 ± 0.04) × 10−5n/an/a
IL-3(2.71 ± 0.78) × 10−4(6.11 ± 2.19) × 10−9(7.28 ± 0.65) × 10−3(4.02 ± 2.03) × 10−7
IL-5(2.47 ± 0.45) × 10−4(1.16 ± 0.52) × 10−8(5.07 ± 0.20) × 10−3(3.23 ± 0.73) × 10−8
IL-9(5.97 ± 2.79) × 10−3(1.69 ± 0.90) × 10−7(5.85 ± 2.72) × 10−3(2.71 ± 2.42) × 10−7
IL-13(2.64 ± 0.98) × 10−4(1.97 ± 1.50) × 10−7(1.36 ± 0.06) × 10−2(1.91 ± 1.07) × 10−6
IL-15(1.62 ± 0.24) × 10−4(5.70 ± 0.46) × 10−8(6.29 ± 0.26) × 10−3(2.15 ± 1.32) × 10−7
IL-21(1.88 ± 1.33) × 10−4(4.57 ± 1.30) × 10−8(5.68 ± 0.34) × 10−3(3.87 ± 0.86) × 10−7
SCF(2.57 ± 0.92) × 10−4(8.72 ± 4.95) × 10−9(4.51 ± 1.52) × 10−3(1.90 ± 1.45) × 10−6
THPO(6.00 ± 3.29) × 10−5(2.89 ± 1.83) × 10−10(4.47 ± 2.46) × 10−3(3.96 ± 2.65) × 10−9
Long-chain cytokines
G-CSF(7.72 ± 0.31) × 10−4(3.91 ± 2.06) × 10−9(1.04 ± 0.04) × 10−2(1.68 ± 1.29) × 10−6
GH(3.73 ± 2.36) × 10−4(3.42 ± 2.85) × 10−7(5.87 ± 1.16) × 10−3(4.16 ± 2.65) × 10−7
GH-V(7.92 ± 3.35) × 10−5(4.62 ± 2.41) × 10−8(3.06 ± 1.27) × 10−3(1.78 ± 0.92) × 10−6
IL-27 #(9.61 ± 4.18) × 10−4(1.16 ± 0.63) × 10−6(1.47 ± 0.62) × 10−2(2.80 ± 0.85) × 10−6
IL-31(4.64 ± 0.13) × 10−4(1.06 ± 0.96) × 10−7(1.11 ± 0.12) × 10−2(2.56 ± 1.95) × 10−7
IL-35 #(2.59 ± 0.81) × 10−3(2.34 ± 1.26) × 10−6(3.91 ± 1.55) × 10−2(4.65 ± 2.42) × 10−6
LEP(3.18 ± 2.17) × 10−3(3.25 ± 1.92) × 10−7(2.87 ± 1.00) × 10−4(3.85 ± 1.06) × 10−7
PRL(1.59 ± 0.23) × 10−4(8.40 ± 0.58) × 10−8(1.55 ± 0.82) × 10−2(6.35 ± 0.96) × 10−7
Interferons/IL-10
IFN-ω1(4.71 ± 0.22) × 10−4(2.28 ± 0.64) × 10−7(1.29 ± 0.55) × 10−2(1.11 ± 0.63) × 10−6
IL-10(3.98 ± 0.28) × 10−4(3.61 ± 1.09) × 10−7(1.50 ± 0.37) × 10−2(2.13 ± 0.67) × 10−6
IL-19(6.28 ± 0.86) × 10−4(1.47 ± 1.08) × 10−7(2.77 ± 1.69) × 10−2(4.96 ± 4.04) × 10−7
IL-20(3.08 ± 0.86) × 10−4(4.51 ± 1.12) × 10−8(9.14 ± 2.51) × 10−3(3.85 ± 0.59) × 10−7
IL-22(3.57 ± 2.56) × 10−3(5.93 ± 0.84) × 10−7(3.26 ± 2.67) × 10−2(1.31 ± 0.49) × 10−6
IL-24(5.73 ± 0.85) × 10−4(2.39 ± 0.94) × 10−7(7.79 ± 1.72) × 10−3(6.01 ± 1.57) × 10−7
IL-26(5.98 ± 2.92) × 10−4(2.78 ± 2.31) × 10−7(2.56 ± 1.39) × 10−3(6.00 ± 2.63) × 10−7
* a single-site binding model is used; #, heterodimeric cytokines; n/a, not applicable.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Kazakov, A.S.; Deryusheva, E.I.; Rastrygina, V.A.; Sokolov, A.S.; Permyakova, M.E.; Litus, E.A.; Uversky, V.N.; Permyakov, E.A.; Permyakov, S.E. Interaction of S100A6 Protein with the Four-Helical Cytokines. Biomolecules 2023, 13, 1345. https://doi.org/10.3390/biom13091345

AMA Style

Kazakov AS, Deryusheva EI, Rastrygina VA, Sokolov AS, Permyakova ME, Litus EA, Uversky VN, Permyakov EA, Permyakov SE. Interaction of S100A6 Protein with the Four-Helical Cytokines. Biomolecules. 2023; 13(9):1345. https://doi.org/10.3390/biom13091345

Chicago/Turabian Style

Kazakov, Alexey S., Evgenia I. Deryusheva, Victoria A. Rastrygina, Andrey S. Sokolov, Maria E. Permyakova, Ekaterina A. Litus, Vladimir N. Uversky, Eugene A. Permyakov, and Sergei E. Permyakov. 2023. "Interaction of S100A6 Protein with the Four-Helical Cytokines" Biomolecules 13, no. 9: 1345. https://doi.org/10.3390/biom13091345

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop