Molecular docking studies on the inhibitory selectivity of cytochrome P450 2C9 by natural anti-arthritic compounds

doi:10.21203/rs.3.rs-2354931/v1

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Molecular docking studies on the inhibitory selectivity of cytochrome P450 2C9 by natural anti-arthritic compounds

https://doi.org/10.21203/rs.3.rs-2354931/v1

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Five natural anti-arthritic compounds, diacerein, rhein, glucosamines (glucosamine 3-sulfate, G3S, and glucosamine 6-sulfate, G6S), and chondroitin disaccharide Δdi-4S (C4S) were docked individually to the defined binding site in CYP2C9 based on published crystal structure (PDB code: 1R9O) in this study. All investigated ligands bound deep in the active site pocket in close proximity to the heme. Except for chondroitin, all ligands bonded to residues found in critical secondary structures that formed the boundary of active site cavity including B-C loop, F helix, F-G loop and I helix. A total of 12 amino acids were involved in the binding and all were critical residues located in four out of six substrate recognition sites (SRSs) that have been identified as important substrate binding and catalysis regions in other CYP isoforms. The relatively more potent binding (lower CDOCKER interaction energy) observed for diacerein and rhein compared to glucosamines and C4S are likely due to two main factors: higher number of bonds between ligand molecule and CYP2C9 active site residues (14 versus 0–4), and direct hydrophobic interaction with the heme moiety. The binding residues identified in both diacerein and rhein were the residues that also bonded with sulfaphenazole, the specific and potent CYP2C9 inhibitor. Collectively, the in silico data from this study have provided insights into structural features of CYP2C9 critical for inhibition, and formed basis for further exploration of structural determinants for potency and specificity of some commonly used natural anti-arthritic compounds in CYP2C9 inhibition.

Cytochrome P450 2C9

anti-arthritic compounds

inhibition

molecular docking

Cytochrome P450 2C9 (CYP2C9) is one of three human microsomal CYPs in subfamily 2C that contribute extensively to the hepatic metabolism of therapeutic drugs. Representative CYP2C9 substrates include the nonsteroidal anti-inflammatory agents such as diclofenac and celecoxib, antidiabetic gliclazide, antihypertensive losartan, anticancer cyclophosphamide and antidepressant amitriptyline. Some of the substrates have a narrow therapeutic index, such as warfarin and phenytoin [Niwa and Yamazaki, 2012]. In addition, CYP2C9 is inhibited by many drugs, such as the antifungal fluconazole, antiarrhythmic amiodarone, antibacterial sulfaphenazole, and anti-inflammatory phenylbutazone. Drug-drug interactions can arise when a patient takes CYP2C9 substrates with inducers or inhibitors. For example, gastrointestinal tract bleeding has been reported in patients taking nonsteroidal anti-inflammatory drug and warfarin due to over anticoagulant action of the latter as a result of reduced metabolism [Cheetham et al., 2009].

Osteoarthritis (OA), also known as degenerative arthritis or degenerative joint disease, is a common, chronic disease that affects about 15% of the world’s population [Hunter and Bierma-Zeinstra, 2019]. Glucosamine, chondroitin and diacerein are three naturally derived compounds used in the treatment of OA. Glucosamine and chondroitin, both natural constituents of the cartilaginous matrix, are commonly available as dietary supplements, or nutraceuticals [Simental-Mendia et al., 2018]. Diacerein is a symptomatic slow acting drug for OA. It is an anthraquinone compound of vegetal origin, obtained from extraction products of aloe or senna leaves. Prior to entering systemic circulation, diacerein is entirely converted to its deacetylated active metabolite, rhein, in liver [Debord et al 1994]. Several studies on the efficacy and safety of diacerein in the treatment of OA have suggested the symptom- and structure-modifying effects of this compound in patients with OA (Panova and Jones, 2015; Rintelen et al., 2006).

Despite their widespread use in treatment of OA, research on the ability of glucosamine, chondroitin or diacerein to modulate cytochrome P450 enzymes in humans is relatively scarce. Only a handful of studies have been carried out to-date in investigating the modulatory effects of these compounds on CYP enzymatic activity. Persiani and colleagues, in an in vitro study using cryopreserved human hepatocytes and recombinant human CYPs, did not find crystalline glucosamine sulfate to be able to induce or inhibit the catalytic activity of the tested CYPs up to a concentration of 3 mM, the concentration which was hundred folds higher than peak plasma concentrations observed in human (~ 10 µM) [Persiani et al., 2009]. Another study demonstrated that chronic administration of chondroitin sulfate did not affect the protein expression and activity of rabbit CYP1A2 and CYP3A6, both in vivo and in vitro [Iovu et al., 2012]. A more recent study by Yokotani and co-researchers has found that both chondroitin sulfate and glucosamine sulfate did not induce or inhibit mice hepatic CYPs, including CYP1A1, CYP1A2, CYP2B, CYP2C, CYP3A [Yokotani et al., 2014]. The same study also suggested no interactions of these two compounds with the anticoagulation activity of warfarin in mice models. An in vitro study using rhein, the major diacerein metabolite, has detected different degrees of inhibition on several CYP isoforms in rats, with the inhibition potency in the following order: CYP2E1 > CYP3A > CYP2C9 > CYP1A2 > CYP2D6 [Tang et al., 2009]. Based on the inhibition of recombinant human CYP3A4 and CYP2D6 by the ethanol extracts from Aloe vera juice, another recent study has proposed the involvement of rhein (a constituent of Aloe vera although its concentration in the juice extracts was not determined) in inhibiting the activity of these two CYP isoforms [Djuv and Nilsen, 2012].

Recently, we have published a study investigating the inhibitory magnitude of glucosamine, chondroitin, diacerein and rhein on CYP2C9 using in vitro inhibition assay and molecular docking [Tan et al., 2018]. Utilizing valsartan hydroxylase assay as probe, all forms of glucosamine and chondroitin exhibited negligible inhibition toward CYP2C9 whereas diacerein and rhein showed moderate to relatively strong degree of inhibition. The in silico data from the study correlated well with in vitro experimental data where both diacerein and rhein have shown lower binding free energy than glucosamine and chondroitin, with interactions dominated by hydrogen and hydrophobic bondings. In the present study, we have expanded the docking simulation to include elucidation of residue interaction, critical residues responsible for inhibitor binding, as well as the nature of the bonding interactions. The obtained results have provided insights into structural features of CYP2C9 critical for inhibition at the atomic level and may form basis for future research in designing anti-arthritic compounds with reduced drug interaction or inhibition liability.

2.1 Molecular docking

The pdb file for the crystal structure of human CYP2C9 complexed with flurbiprofen (EC: 1.14.13, 1R9O.pdb) was obtained from the RCSB protein data bank (http://www.pdb.org). The molecular docking procedure was performed by using CDOCKER protocol for receptor-ligand interactions section of Discovery Studio 4.5 (DS 4.5) (Accelrys Software Inc., San Diego, USA). CDOCKER is an implementation of a CHARMm based molecular docking tool using a rigid receptor [Wu et al., 2003]. The CDOCKER algorithm adopts a strategy involving the generation of several initial ligand orientations in the active site of target protein followed by molecular dynamics (MD)-based simulated annealing, and final refinement by energy minimization. The annealing schedule engages a series of heating and cooling stages and is implemented as a set of scripts for the CHARMm package using its replica feature.

Initially both the ligands and the enzyme were pretreated. For ligand preparation, the 3D structures of all the anti-arthritic compounds were generated with ChemBioDraw Ultra 13.0 (CambridgeSoft, Perkin Elmer, USA) and optimized with AM1 method. For enzyme preparation, the hydrogen atoms were added with the pH of the protein in the range of 6.5–8.5. The water molecules in the crystal structure were removed with DS 4.5, and the ferrous ion in heme was charged to coordinate with physiological state, and finally the protein was refined with CHARMm. The active site of CYP2C9 was auto-searched with DS 4.5 and selected according to the relevant references. A series of ligand conformations were generated using high temperature MD with different random seeds. Random orientations of the conformations were generated by translating the center of the ligand to a specified position within the receptor active site, and making a series of random rotations. A softened energy was calculated, and the orientation was kept when it is less than a specified limit. This process repeated until either the desired number of low-energy orientations was obtained, or the test times of bad orientations reached the maximum number. Each orientation was subjected to simulated annealing MD. The temperature was heated up to a high temperature then cooled to the target temperature. A final energy minimization of the ligand in the rigid receptor using non-softened potential was performed. For each of the final pose, the CHARMm energy (interaction energy plus ligand strain) and the interaction energy alone were determined. The poses are sorted according to CHARMm energy and the top scoring (most negative, thus favorable to binding) poses were retained. After end of molecular docking, the types of interactions of the docked enzyme with ligand were analyzed. Ten molecular docking poses saved for each ligand were ranked according to their dock score function. The pose with the highest CDOCKER interaction energy (in negative scale) was chosen as the most suitable pose. Only the ligand and amino acid residues within 6.0 Å were allowed during the analysis. A docking without any output pose was considered as a failure. All the poses were displayed as 3D and 2D representations. The 2D representations were generated using the 2D diagram function of the CDOCKER protocol for receptor-ligand interactions.

3.1 Molecular docking simulations

The structure of human CYP2C9 co-crystallized with flurbiprofen (PDB code: 1R9O) was selected as the protein template for the ligand docking simulation. The model has been energy-minimized and validated as reported previously [Tan et al., 2018]. The model exhibited a root mean square deviation (RMSD) value of 1.8 Å for the docked flurbiprofen (docked ligand) which was well below the cut-off value of 2, indicating adequate validation and acceptable quality of reproduction of our docking protocol (Hevener et al., 2009). The energy-optimzed sulfaphenazole, diacerein, rhein, glucosamines (both glucosamine 3-sulfate [G3S] and glucosamine 6-sulfate [G6S]), and chondroitin disaccharide Δdi-4S (C4S) were docked individually to the defined binding site in CYP2C9. Figure 1 shows the 3D and 2D representations of the docking of each ligand within CYP2C9 binding site. The pose with the lowest CDOCKER interaction energy was selected as the most favorable pose for each ligand. As illustrated in Fig. 1, all ligands accommodated the same hydrophobic cleft as flurbiprofen (in the original crystallographic structure) and bonded in close proximity to the heme. The number and type of bonding between ligand molecules and CYP2C9 binding cavity residues, the bond distance, together with the binding interaction energy and IC₅₀ values from the in vitro inhibition assay reported previously [Tan et al 2018], are listed in Table 1. The number of bonds displayed in the table differs from that of the earlier study [Tan et al., 2018] because we aimed to illustrate the full details of the bonding for each residue involved whereas in the previous study, the bonding was reported based on the residues per se without taking into account the number of bonding for each residue.

Table 1

The number and type of bonding between ligand molecules and CYP2C9 binding cavity residues, the bond distance, together with the binding interaction energy and IC₅₀ values from the *in vitro* inhibition assay
CYP-ligand (Binding energy, Kcal/mol; IC₅₀, µM)^a	No of bonds	Bond-ing no	Residues involved^b	Bonding category	Type of bonding	Distance (Å)
CYP2C9-rhein (-35.22; 6.08)	14	1	A:ILE205:HN1 - Rhein:O17	Hydrogen Bond	Conventional Hydrogen Bond	2.562197
		2	Rhein:H27 - A:ASP293:O	Hydrogen Bond	Conventional Hydrogen Bond	3.090060
		3	A:ASP293:HA - Rhein:O21	Hydrogen Bond	Carbon Hydrogen Bond	2.804421
		4	A:ALA297:HA - Rhein:O18	Hydrogen Bond	Carbon Hydrogen Bond	2.870330
		5	Rhein:O20 - A:HEM500	Electrostatic	Pi-Anion	4.453505
		6	A:PHE114 – Rhein (ring C)	Hydrophobic	Pi-Pi T-shaped	5.281925
		7	A:GLY296:C,O;ALA297:N – Rhein (ring C)	Hydrophobic	Amide-Pi Stacked	4.010072
		8	Rhein (ring C) - A:VAL113	Hydrophobic	Pi-Alkyl	5.321472
		9	Rhein (ring C) - A:ILE205	Hydrophobic	Pi-Alkyl	5.113695
		10	Rhein (ring C) - A:LEU208	Hydrophobic	Pi-Alkyl	5.201962
		11	Rhein (ring B) - A:VAL113	Hydrophobic	Pi-Alkyl	5.146036
		12	Rhein (ring B) - A:ILE205	Hydrophobic	Pi-Alkyl	5.318006
		13	Rhein (ring B) - A:ALA297	Hydrophobic	Pi-Alkyl	5.331537
		14	Rhein (ring A) - A:LEU366	Hydrophobic	Pi-Alkyl	4.682293
CYP2C9 – diacerein (-39.86; 32.23)	14	1	A:SER209:HN1 - Diacerein:O26	Hydrogen Bond	Conventional Hydrogen Bond	2.903369
		2	A:SER209:HA - Diacerein:O26	Hydrogen Bond	Conventional Hydrogen Bond	2.612144
		3	A:LEU201:HA - Diacerein:O22	Hydrogen Bond	Carbon Hydrogen Bond	2.743063
		4	Diacerein:O17 - A:HEM500	Electrostatic	Pi-Anion	4.831412
		5	A:PHE114 – Diacerein (ring B)	Hydrophobic	Pi-Pi T-shaped	5.611757
		6	A:PHE114 – Diacerein (ring A)	Hydrophobic	Pi-Pi T-shaped	4.960882
		7	A:GLY296:C,O;ALA297:N – Diacerein (ring C)	Hydrophobic	Amide-Pi Stacked	4.812890
		8	A:GLY296:C,O;ALA297:N – Diacerein (ring B)	Hydrophobic	Amide-Pi Stacked	3.823132
		9	A:GLY296:C,O;ALA297:N – Diacerein (ring A)	Hydrophobic	Amide-Pi Stacked	4.320433
		10	Diacerein (ring C) - A:ALA297	Hydrophobic	Pi-Alkyl	4.973498
		11	Diacerein (ring B) - A:VAL113	Hydrophobic	Pi-Alkyl	4.854490
		12	Diacerein (ring B) - A:ILE205	Hydrophobic	Pi-Alkyl	5.201749
		13	Diacerein (ring B) - A:ALA297	Hydrophobic	Pi-Alkyl	5.027617
		14	Diacerein (ring A) - A:VAL113	Hydrophobic	Pi-Alkyl	5.227213
CYP2C9-sulfaphenazole (-36.50; 0.95)	9	1	A:HEM500 - Sulfaphenazole	Hydrophobic	Pi-Pi T-shaped	5.566038
		2	A:GLY296:C,O;ALA297:N – Sulfaphenazole (ring A)	Hydrophobic	Amide-Pi Stacked	4.557513
		3	Sulfaphenazole (ring A) - A:LEU208	Hydrophobic	Pi-Alkyl	5.469036
		4	Sulfaphenazole (ring B) - A:LEU208	Hydrophobic	Pi-Alkyl	4.861211
		5	Sulfaphenazole (ring B) - A:LEU366	Hydrophobic	Pi-Alkyl	5.116724
		6	Sulfaphenazole (ring C) - A:VAL113	Hydrophobic	Pi-Alkyl	5.492285
		7	Sulfaphenazole (ring C) - A:ALA297	Hydrophobic	Pi-Alkyl	4.923605
		8	Sulfaphenazole (ring C) - A:LEU362	Hydrophobic	Pi-Alkyl	5.275490
		9	Sulfaphenazole (ring C) - A:LEU366	Hydrophobic	Pi-Alkyl	4.735068
CYP2C9 – glucosamine 3 sulfate (-25.54; >1000)	4	1	Glucosamine 3-sulphate:H24 - A:LEU208:O	Hydrogen Bond	Conventional Hydrogen Bond	2.158468
		2	A:ALA297:HA – Glucosamine 3-sulphate:O21	Hydrogen Bond	Carbon Hydrogen Bond	2.379240
		3	Glucosamine 3-sulphate:H18 - A:SER209:OG	Hydrogen Bond	Carbon Hydrogen Bond	2.714800
		4	Glucosamine 3-sulphate:N12 - A:PHE114	Electrostatic	Pi-Cation	3.699830
CYP2C9 – glucosamine 6 sulfate (-24.41; >1000)	4	1	A:ARG108:HH22 – Glucosamine 6-sulphate:O21	Hydrogen Bond	Conventional Hydrogen Bond	3.028392
		2	A:GLY296:HA2 – Glucosamine 6-sulphate:O22	Hydrogen Bond	Carbon Hydrogen Bond	2.743366
		3	Glucosamine 6-sulphate:H18 - A:GLY296:O	Hydrogen Bond	Carbon Hydrogen Bond	2.573529
		4	Glucosamine 6-sulphate:S20 - A:PHE114	Other	Pi-Sulfur	5.314108
2C9-chondroitin disaccharide Δdi-4S (-7.59; >1000)	0		‒	‒	‒	‒
^aThe CDOCKER interaction energy and IC₅₀ values were derived from previously published data (Tan et al., 2018); ^bRing labelling were the same as the labels used in Fig. 3

As reported in our previous study (Tan et al., 2018) and listed in Table 1, sulfaphenazole showed the lowest IC₅₀ value (0.95 µM) toward valsartan-4 hydroxylase activity, confirming its status as the specific and potent inhibitor probe for CYP2C9. Rhein and diacerein were the next potent inhibitors demonstrating IC₅₀ values of 6.08 µM and 32.23 µM respectively. G3S, G6S and C4S were found to have IC₅₀ values higher than 1000 µM, indicating negligible inhibition toward CYP2C9. The rank order of binding affinity, based on CDOCKER interaction energy values, was sulfaphenazole/diacerein/rhein > glucosamines and chondroitin. Except for C4S, all ligands were docked and orientated in close proximity to the heme moiety with interactions dominated by hydrogen and hydrophobic bondings. Binding of the docked ligands involved total of 12 active site amino acids. Majority of these residues possess hydrophobic or non-polar side chains (VAL113, PHE114, LEU201, ILE205, LEU208, GLY296, ALA297, LEU362 and LEU366), only one carries neutral (uncharged) side chain (SER209) and another two have polar side chains (ARG108 and ASP293). All these twelve residues have been found forming the boundary of the active site cavity of CYP2C9 crystal structure [Wester et al., 2004]. Of these residues, ARG108, VAL113, PHE114, ILE205, LEU208, ASP293, GLY296, ALA297 and LEU366 were shown to reside within 5 Å of flurbiprofen, the co-crystalized ligand in the crystal structure, indicating their primary roles in ligand binding. All the 12 residues in Table 1 were also residues identified within the substrate recognition sites (SRSs) which have been identified by Gotoh [Gotoh 1992] as regions important for CYP-substrate interaction based on alignment with bacterial CYP101 (P450cam), the substrate binding residues of which have been identified by X-ray crystallography (Fig. 2). Analysis of mutations in experimental studies of numerous CYP isoforms in these SRSs, altogether six sites (SRS1 to SRS6), have been reported to cause altered kinetics for major CYP substrates [Mo et al., 2009]. As listed in Table 1, residues bonded to the various ligands were the amino acids residing in SRS1, SRS2, SRS4 and SRS5 (Fig. 2).

The relatively more potent binding (lower CDOCKER interaction energy) observed for sulfaphenazole, diacerein and rhein are likely to be accounted for by two main factors. Firstly, the number of bondings formed in the three ligands were much higher compared to glucosamines and CS4 (9–14 versus 0–4 bondings). Larger number and the different types of bonds have contributed to tighter interaction between the ligands and CYP2C9, hence better affinity. Interestingly, hydrophobic interactions (pi-pi, amide-pi and pi-alkyl) appeared to play a role in better binding for sulfaphenazole, diacerein and rhein as this was not observed for glucosamines where interactions were dominated by hydrogen and electrostatic bondings only. Secondly, the three ligands directly interacted with the heme moiety, forming mostly hydrophobic pi-pi interaction (sulfaphenazole), or electrostatic pi-anion interaction (diacerein and rhein). These direct interaction with heme has probably further enhanced stability of interaction therefore contributing to increased binding affinity observed.

3.2 Docking analysis for each ligand

Rhein, an anthracene compound, has an extended conjugated system with two hydroxyl and a carboxyl moieties (bonded to rings A and C) in addition to the central anthracene functionality (Fig. 3). It was the most potent inhibitor of CYP2C9-mediated valsartan 4-hydroxylation among the natural anti-arthritic compounds investigated and showed low CDOCKER energy (Table 1). Our docking showed that the compound packed next to helix I and above the heme in a hydrophobic cleft that was formed by VAL113 and PHE114 in the SRS 1; ILE205 and LEU208 in SRS 2; ASP293, GLY296, and ALA297 in SRS 4; and LEU366 in SRS 5 (Fig. 1A). These residues formed altogether 14 bonds with various structural moieties of rhein. Both VAL113 and PHE114, forming part of the B-C loop, corresponded to ILE113 and PHE114 amino acids of CYP2C2 that have been shown to be critical for substrate binding in site-directed mutagenesis [Straub et al., 1993; Kronbach et al., 1991]. PHE114 formed pi-pi stacking with ring C of anthracene functionality in rhein in our docking model, consistent with similar pi-pi stacks observed for diclofenac in another CYP2C9 homology modeling study [Lewis, 2003]. This residue has also been shown by site-directed mutagenesis to play an important role in S-warfarin binding [Haining et al., 1999]. Both ILE205 and LEU208 formed pi-alkyl interactions with rhein, and these two residues have been part of hydrophobic side chains along helix F that were involved in interaction with hydrophobic portion of flurbiprofen in CYP2C9 crystal structure, alongside ASN204 which was involved in direct hydrogen bonding with the substrate [Wester et al., 2004]. In our model, ILE205 additionally formed a hydrogen bond with O17 of the carboxylate moiety (attached to ring C) of rhein, further contributing to the relatively high affinity binding of this compound to CYP2C9. ASP293, GLY296, and ALA297, located within SRS 4 (Fig. 2), were all part of the long helix I that forms part of the wall of the heme pocket. ASP293, in particular, was one of the critical residue that formed hydrogen bond with ARG108 in CYP2C9-flurbiprofen crystal structure. Hydrogen bonding of ARG108 with ASP293 and a nearby ASN289 on helix I was demonstrated to stabilize the observed conformation of ARG108 that bonded directly flurbiprofen in the active site. These interactions position the substrate for regioselective oxidation in a relatively large active site cavity and are likely to account for the high catalytic efficiency exhibited by CYP2C9 for the regioselective oxidation of several anionic non-steroidal anti-inflammatory drugs [Wester et al., 2004]. Moreover, ASP293 also exhibited hydrogen bonding interactions that were likely to stabilize the adjacent B-C loop formed by the polypeptide backbone at residues 111–114, including VAL113 and PHE114 described above [Wester et al., 2004]. LEU366, located in the loop region between helix K and β1–4 sheet, resided in SRS 5 region (Fig. 2) where many residues critical for substrate binding and catalysis have been investigated. For instance, ILE359Leu substitution found in CYP2C9*3 have been shown to cause detrimental effect in substrate catalysis, with reported 3.4- to 26.9-fold reduction in intrinsic clearance for a number of substrates [Takanashi et al., 2000]. In addition, LEU366 is also close to LEU363 that interacted directly with diclofenac in CYP2C9-diclofenac homology modeling [Lewis 2003]. It is therefore clear from the discussion above, the high number of bondings and critical locality of the residues involved in direct interaction with rhein, have collectively contributed to high affinity binding of the ligand in our model.

Similar to rhein, diacerein was shown to locate within the putative active site of CYP2C9 where again a combination of pi-pi stacking and hydrogen bondings orientated the ligand in close proximity to the heme. Docking of diacerein showed hydrogen bondings between the oxygen atom of the two acetyl functions (O22 and O26 respectively) with LEU201 and SER209. Hydrophobic pi-stacking interactions were observed for the aromatic rings of diacerein (rings A, B and C) including the pi-pi interaction with the hydrophobic PHE114, and the amide-pi bonding with GLY296 and ALA297, along with additional pi-alkyl interactions with the hydrophobic residues VAL113, ILE205 and ALA297. Additional bonding included a direct pi-anion interaction with the heme (see Table 1 and Fig. 1B). Diacerein was however positioned in opposite orientation than the docked pose of rhein whereby ring C of the rhein was orientated to point toward proximal end of I helix and B-C loop with its carboxyl moiety pointing upward away from the heme (Fig. 1A). In the case of diacerein, the ring C was positioned closer to I helix distal end, pointing away from B-C loop with its carboxyl moiety pointing downward to the heme (Fig. 1B). Nevertheless, both ligands showed the same number of bondings with CYP2C9 and formed the same hydrophobic interaction with VAL113, PHE114, ILE205, GLY296 and ALA297 at the binding site, along with the pi-anion interaction with the heme. Due to this different docking orientation, structural moieties from the two anti-athritic compounds interacting with active site residues were therefore different. As an example, heme interacted with oxygen atom (O17) of carboxylate attached to ring C for diacerein whereas oxygen atom (O20) of the hydroxyl function of ring A was the interacting atom with the heme in rhein (Fig. 1 and Fig. 3). From the docked pose of diacerein in our model (Fig. 1B), it is evident that LEU201 and SER209, located in F helix and F-G loop respectively and observed only in diacerein but not in rhein, have played crucial role in interacting with the two reactive acetyl moieties of diacerein (via hydrogen bond), and this has probably played a critical part in the observed opposite docking mode of diacerein (to that of rhein) in CYP2C9 cavity. It is therefore apparent that having a unique set of interacting residues (LEU201 and SER209 in diacerein, and LEU208, Asp293 and LEU366 in the case for rhein), together with the opposite orientation of the ligand molecule within the active site, appear to have resulted in different binding affinity and potency as reflected by different CDOCKER interaction energy and IC₅₀ values for these two anti-arthritic compounds.

Sulfaphenazole, in our docking model, demonstrated mainly hydrophobic interaction with a number of active site residues. Benzene ring (ring A) interacted with GLY296, ALA297 and LEU208 via pi-pi, amide-pi and pi-alkyl bondings respectively. Pyrazole ring (ring B), on the other hand, bonded to LEU208 and LEU366 via pi-alkyl interaction. N-phenyl ring (ring C), which is orientated closer to heme, formed pi-alkyl bonds with VAL113, ALA297, LEU362 and LEU366, and also a direct pi-pi stacking with the heme (Fig. 1C and Fig. 3). As discussed above, all these residues have been shown to be important in ligand binding and catalysis for CYP2C9 and were also the residues found in the binding of rhein and diacerein described above. These common interacting residues identified in all three ligands indicate their critical role in ligand docking, consistent with the low CDOCKER interaction energy values, as well as the relatively low IC₅₀ values in the in vitro inhibition assay reported in our previous study (Tan et al., 2018).

As listed in Table 1, both G3S and G6S were involved in lower number of bondings with CYP2C9 compared to rhein, diacerein and sulfaphenazole (4 versus 9–14). The interacting residues in the two glucosamine molecules were also the residues involved in binding of rhein, diacerein and sulfaphenazole. The involved residues were PHE114, LEU208, SER209, GLY296 and ALA297 (Fig. 1D and Fig. 1E). The only exception was ARG108 which was hydrogen bonded to G6S in our model. Interestingly, ARG108 has been demonstrated to be involved in charge-charge interaction with carboxylate moiety of flurbiprofen in CYP2C9 crystal structure [Wester et al., 2004], and shown in site-directed mutagenesis studies to be important in substrate recognition of substrates such as S-warfarin and diclofenac [Ridderström et al., 2000; Dickmann et al., 2004]. Despite the importance of ARG108 in ligand binding and catalysis, the lesser number of interacting bonds in both G3S and G6S, has likely accounted for the lesser affinity for binding as evidenced by higher CDOCKER interaction energy values and negligible inhibition observed in our previous in vitro inhibition study (Tan et al., 2018).

Chondroitin sulfate, our last anti-athritic compound investigated in the docking study, is a natural polymer of disaccharide units with high molecular weight. Docking of this long chain of molecules was not successful in our initial attempts and hence, it was substituted with the smaller disaccharide C4S. Our docking data showed no interaction with the residues at the binding site even though there was a number of residues located nearby C4S molecule (see 2D diagram in Fig. 1F). This was consistent with the high interaction energy (-7.59 kcal/mol) and the experimentally determined IC₅₀ (> 1000 µM) values.

In the present study, we have successfully docked five natural anti-arthritic compounds, diacerein, rhein, glucosamines (G3S and G6S), and C4S to the defined active site of CYP2C9. All ligands bound deep in the active site pocket in close proximity to the heme. Except for chondroitin, all ligands bonded to residues found in critical secondary structures that formed the boundary of active site cavity as reported in the published crystal structure [Wester et al., 2004], including B-C loop, F helix, F-G loop and I helix. A total of 12 amino acids were involved in the binding and all were critical residues located in four out of six SRSs that have been identified as important substrate binding and catalysis regions in many other CYP isoforms. The better binding efficiency (lower CDOCKER interaction energy) observed for diacerein and rhein compared to glucosamines and C4S are likely due to two main factors: higher number of bonds between ligand molecule and CYP2C9 active site residues (14 versus 0–4), and direct hydrophobic interaction with the heme moiety. The binding residues identified in both diacerein and rhein were the residues that also bonded with sulfaphenazole, the specific and potent CYP2C9 inhibitor, confirming their pivotal role in ligand docking. In summary, the in silico data from this study have provided insights into structural features of CYP2C9 critical for inhibition, and formed basis for further exploration of structural determinants for potency and specificity of some commonly used natural anti-arthritic compounds in CYP2C9 inhibition.

Author contribution statement

NA, CEO, IO and YP designed, organized the project and all analysis. BHT, NA, UDP, BCY and CEO performed the analysis and the experimental study. BHT, NA and CEO drafted and edited the manuscript. YP, UDP, IO and BCY read and approved the final manuscript.

CoNFLICT OF Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This work was supported by the Monash University Seed Grant (grant no BCHH-SS-4-02-2010) and the Science Fund (project code 02-02-10-SF0077) of the Malaysian Ministry of Science, Technology and Innovation.

Cheetham TC, Levy G, Niu F, Bixler F. Gastrointestinal safety of nonsteroidal anti-inflammatory drugs and selective cyclooxygenase-2 inhibitors in patients on warfarin. Ann Pharmacother 2009; 43: 1765–73.
Debord P, Louchahi K, Tod M, Cournot A, Perret G, Petitjean O. Influence of renal function on the pharmacokinetics of diacerein after a single oral dose. Eur J Drug Metab Pharmacokinet 1994; 19:13-9.
Dickmann LJ, Locuson CW, Jones JP, Rettie AE. Differential roles of Arg97, Asp293, and Arg108 in enzyme stability and substrate specificity of CYP2C9. Mol Pharmacol 2004; 65: 842-50.
Djuv A1, Nilsen OG. Aloe vera juice: IC₅₀ and dual mechanistic inhibition of CYP3A4 and CYP2D6. Phytother Res 2012; 26: 445-51.
Gotoh O. Substrate recognition sites in cytochrome P450 family 2 (CYP2) proteins inferred from comparative analyses of amino acid and coding nucleotide sequences. J Biol Chem 1992; 267: 83-90.
Haining RL, Jones JP, Henne KR, Fisher MB, Koop DR, Trager WF, Rettie AE. Enzymatic determinants of the substrate specificity of CYP2C9: role of B'-C loop residues in providing the pi-stacking anchor site for warfarin binding. Biochemistry. 1999; 38: 3285-92.
Hevener KE, Zhao W, Ball DM, Babaoglu K, Qi J, White SW, Lee RE. Validation of molecular docking programs for virtual screening against dihydropteroate synthase. J Chem Inf Model 2009; 49: 444-60.
Hunter DJ, Bierma-Zeinstra S. Osteoarthritis. Lancet 2019; 393: 1745-1759
Iovu MO1, Héroux L, Vergés J, Montell E, Paiement J, du Souich P. Effect of chondroitin sulfate on turpentine-induced down-regulation of CYP1A2 and CYP3A6. Carbohydr Res 2012; 355: 63-8.
Kronbach T, Kemper B, Johnson EF. A hypervariable region of P450IIC5 confers progesterone 21-hydroxylase activity to P450IIC1. Biochemistry 1991; 30: 6097-102.
Lewis DF. Essential requirements for substrate binding affinity and selectivity toward human CYP2 family enzymes. Arch Biochem Biophys 2003; 409: 32-44.
Mo SL, Zhou ZW, Yang LP, Wei MQ, Zhou SF. New insights into the structural features and functional relevance of human cytochrome P450 2C9. Part I. Curr Drug Metab 2009; 10: 1075-126.
Niwa T, Yamazaki H. Comparison of cytochrome P450 2C subfamily members in terms of drug oxidation rates and substrate inhibition. Curr Drug Metab 2012; 13: 1145-59.
Panova E, Jones G. Benefit-risk assessment of diacerein in the treatment of osteoarthritis. Drug Saf 2015; 38: 245-52.
Persiani S, Canciani L, Larger P, Rotini R, Trisolino G, Antonioli D, Rovati LC. In vitro study of the inhibition and induction of human cytochromes P450 by crystalline glucosamine sulfate. Drug Metabol Drug Interact 2009; 24: 195-209.
Ridderström M, Masimirembwa C, Trump-Kallmeyer S, Ahlefelt M, Otter C, Andersson TB. Arginines 97 and 108 in CYP2C9 are important determinants of the catalytic function. Biochem Biophys Res Commun 2000; 270: 983-7.
Rintelen B, Neumann K, Leeb BF. A meta-analysis of controlled clinical studies with diacerein in the treatment of osteoarthritis. Arch Intern Med 2006; 166: 1899-906.
Simental-Mendía M, Sánchez-García A, Vilchez-Cavazos F, Acosta-Olivo CA, Peña-Martínez VM, Simental-Mendía LE. Effect of glucosamine and chondroitin sulfate in symptomatic knee osteoarthritis: a systematic review and meta-analysis of randomized placebo-controlled trials. Rheumatol Int 2018; 38: 1413-1428.
Straub P, Johnson EF, Kemper B. Hydrophobic side chain requirements for lauric acid and progesterone hydroxylation at amino acid 113 in cytochrome P450 2C2, a potential determinant of substrate specificity. Arch Biochem Biophys 1993; 306: 521-7.
Takanashi K, Tainaka H, Kobayashi K, Yasumori T, Hosakawa M, Chiba K. CYP2C9 Ile359 and Leu359 variants: enzyme kinetic study with seven substrates. Pharmacogenetics 2000; 10: 95-104.
Tan BH, Ahemad N, Pan Y, Palanisamy UD, Othman I, Yiap BC, Ong CE. Cytochrome P450 2C9-natural antiarthritic interactions: Evaluation of inhibition magnitude and prediction from in vitro data. Biopharm Drug Dispos 2018; 39: 205-17.
Tang JC1, Yang H, Song XY, Song XH, Yan SL, Shao JQ, Zhang TL, Zhang JN. Inhibition of cytochrome P450 enzymes by rhein in rat liver microsomes. Phytother Res 2009; 23: 159-64.
Wester MR, Yano JK, Schoch GA, Yang C, Griffin KJ, Stout CD, Johnson EF. The structure of human cytochrome P450 2C9 complexed with flurbiprofen at 2.0-A resolution. J Biol Chem 2004; 279: 35630-7.
Wu G, Robertson DH, Brooks CL 3rd, Vieth M. Detailed analysis of grid-based molecular docking: A case study of CDOCKER-A CHARMm-based MD docking algorithm. J Comput Chem 2003; 24: 1549-62.
Yokotani K, Nakanishi T, Chiba T, Sato Y, Umegaki K. Glucosamine and chondroitin sulfate do not enhance anticoagulation activity of warfarin in mice in vivo. Shokuhin Eiseigaku Zasshi 2014; 55: 183-7.

No competing interests reported.

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Molecular docking studies on the inhibitory selectivity of cytochrome P450 2C9 by natural anti-arthritic compounds

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1. Introduction

2. Materials And Methods

2.1 Molecular docking

3. Results And Discussion

3.1 Molecular docking simulations

3.2 Docking analysis for each ligand

4. Conclusion

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