International Journal of Peptide Research and Therapeutics https://doi.org/10.1007/s10989-018-9695-8
Investigation of the Skin Anti-photoaging Potential of Swertia chirayita Secoiridoids Through the AP-1/Matrix Metalloproteinase Pathway by Molecular Modeling Pathomwat Wongrattanakamon1 · Piyarat Nimmanpipug2 · Busaban Sirithunyalug3 · Wantida Chaiyana3 · Supat Jiranusornkul1 Accepted: 27 January 2018 © Springer Science+Business Media, LLC, part of Springer Nature 2018
Abstract Secoiridoids are bioactive compounds, which are present in plants and exhibit anti-inflammatory activity. In this work, to understand the structural basis of five secoiridoids; amarogentin, amaroswerin, gentiopicrin, sweroside, and swertiamarin for potent inhibitors of the target proteins associated with the collagen degradation pathway, namely MMP-1, MMP-3, MMP-9 and transcription factor AP-1, molecular docking, binding mode modeling, and MD simulations were carried out. The binding inhibitory effects of the secoiridoids were screened on these proteins. The obtained results in terms of binding conformation, binding free energy, protein–ligand interaction profile, structural flexibility, and binding energy decomposition of the secoiridoid inhibitors were elucidated. The molecular modeling clarified inhibitory effect on account of the five secoiridoids towards all three Matrix metalloproteinases (MMPs). Moreover, amarogentin and gentiopicrin may interfere with gene expression via binding to AP-1. Among all screened secoiridoids, amarogentin and gentiopicrin exhibited an interesting binding affinity to the MMPs and AP-1. The results suggest that amarogentin has the highest potential for application as an anti-aging agent with the MMP inhibitory and anti-transcriptional activities, even though further studies are needed to determine the anti-aging effect in vitro, in vivo and by clinical evaluation. Keywords Anti-aging · Matrix metalloproteinases · Molecular docking · Molecular dynamics simulation · Photoaging · Secoiridoids · Swertia chirayita
Introduction
* Pathomwat Wongrattanakamon
[email protected] * Supat Jiranusornkul
[email protected] 1
Laboratory for Molecular Design and Simulation (LMDS), Department of Pharmaceutical Sciences, Faculty of Pharmacy, Chiang Mai University, Chiang Mai 50200, Thailand
2
Computational Simulation and Modelling Laboratory (CSML), Department of Chemistry, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
3
Department of Pharmaceutical Sciences, Faculty of Pharmacy, Chiang Mai University, Chiang Mai 50200, Thailand
Skin aging processes can be classified as (1) chronological (intrinsic) aging and (2) photoaging (extrinsic aging), both of which ordinarily increase wrinkling, sagging, and laxity. The chronological aging arises from the aging process and is greatly correlated with genetic determinants (Jung et al. 2014; Kim et al. 2011). Among solar ultraviolet (UV) radiation, only UVA (long wave; 320–400 nm) and UVB (midwave; 280–320 nm) are harmful to our skin that induces hyperpigmentation, premature aging, edema, erythema, hyperplasia, and skin cancer. UVA constitutes < 90% of the total UV radiation reaching people. This ray is constant the whole year round, but UVB photons are one thousand times more competent of leading to sunburn than the UVA and escalate greatly in the summer (Pérez-Sánchez et al. 2014). Photoaging, on the other hand, is primarily caused by repeated exposure of skin to UVB and is characterized by sunburn, sun tanning, pigmented spots, pigmentary changes,
13
Vol.:(0123456789)
severe wrinkling, and collagen degradation, and accelerates aging of skin (Jung et al. 2014; Kim et al. 2011; PérezSánchez et al. 2014). The synthesis of matrix metalloproteinases (MMPs) in fibroblasts is induced by UV irradiation that leads to observable alterations in skin collagenous tissues because of the breakdown of dermal collagen (a major component of the extracellular matrix (ECM), which likewise comprises collagen I, fibronectin, proteoglycans, and elastin) during UVinduced skin aging. The disarrangement and fragmentation of these proteins by the irradiation advance the skin aging process. The irradiation likewise induces the generation of reactive oxygen species (ROS) and activates cell surface receptors that up-regulates the mitogen-activated protein kinase (MAPK) cascades and proinflammatory cytokine gene products such as IL-1β, TNF-α, IL-6, and IL-8, which in turn trigger expression of c-Fos and c-Jun that together form a nuclear transcription factor complex; activator protein-1 (AP-1) including nuclear factor kappa B (NF-κB) that stimulate the expression and secretion of matrix-degrading enzymes such as metalloproteinases (MMPs), namely MMP-1 (collagenase), MMP-3 (stromelysin-1) and MMP-9 (92-kD gelatinase) in human skin (both keratinocytes and fibroblasts) and inhibits type-I procollagen (Jung et al. 2014; Kim et al. 2011; Park et al. 2013). MMPs, a family of zinc-dependent endoproteinases, play a key role in remodeling ECM structures in dermal photoaging, wound healing, and several pathological conditions such as inflammation and carcinogenesis (Hu et al. 2007; Kim et al. 2011). For example, MMP-1 starts fibrillar collagen cleavage (collagen I and III in skin) at a single site within its central triple helix. Once cleaved by this enzyme, collagen is henceforth degraded by the raised activities of MMP-3 and MMP-9 (Kim et al. 2011). A function of MMPs and their regulation mechanisms (via AP-1) are vastly investigated in an effort to modulate UV-induced photoaging as well as skin wound and inflammation (Park et al. 2013; Singh et al. 2015). Directly (competitively) inhibiting MMP as well as AP-1 activity may be a rational therapeutic approach, particularly for UV-induced photoaging. In recent years, the number of obtainable high resolution X-ray crystal structures of MMP–inhibitor complexes has dramatically raised assisting in the potential inhibitor design in the beginning of a lead generation stage. Molecules having high affinity toward Z n2+ effectively would hinder the binding of the polypeptide to MMPs and therefore are considered to act as MMP inhibitors (Singh et al. 2015). The catalytic domain of the zinc containing enzymes; MMPs is characterized by an ellipsoidal shape with a small active site cleft which is composed of the catalytic Z n2+, coordinated by the three histidines, which is necessary for catalytic reaction. Apart from the catalytic site, the metalloproteinases have certain of subsites assigned as unprimed and primed
13
International Journal of Peptide Research and Therapeutics
S, for example, S1, S2, S3 and S1′, S2′, S3′. The S1′ pocket provides selective inhibition for the zinc containing enzymes on account of variation in size and depth and has gotten considerable interest in the design of MMP inhibitors (Rudra et al. 2013). Swertia chirayita (Roxb. ex Fleming) H. Karst. (also mentioned in the literature as Swertia chirata Buch.-Ham. ex Wall.), belonging to the family Gentianaceae, a well-known medicinal herb originating naturally in the temperate Himalayas. The whole plant is largely utilized by native people for the treatment of digestive, inflammatory, and hepatitis diseases. It is accounted to have a wide spectrum of pharmacological properties such as antidiabetic, antioxidant, anticancer, antibacterial, antifungal, antiviral, and antiinflammatory activities that are attributed to the possession of some bioactive compounds, for example, secoiridoids. Swertiamarin is one of the major secoiridoids found in this plant. It has anticancer, anti-atherosclerotic, and antiarthritic properties (Joshi and Dhawan 2005; Kumar and Van Staden 2016; Suryawanshi et al. 2006). The recent studies suggest that S. chirayita might be useful in prevention of UV-induced skin aging, particularly its secoiridoids, they might be an effective anti-photoaging agent against UVB irradiation, but the molecular target(s) including inhibitory mechanism(s) of these compounds involved in UVB-induced photoaging remain ambiguous. Molecular docking and calculation of binding affinities of metalloproteinase inhibitors to MMPs still keeps a challenge (Singh et al. 2015). Addressing these challenges, in this study, molecular docking, followed by molecular dynamics (MD) simulations on MMP/AP-1–secoiridoid complexes (the secoiridoids namely amarogentin, amaroswerin, gentiopicrin, sweroside, and swertiamarin as inhibitors of the proteins), and a post analysis of the obtained MD trajectories to gauge binding free energies, interaction types and hotspot amino acid residues associated with formations of the MMP/AP-1–secoiridoid complexes were combined. The ability to effectively predict the affinities and binding modes of the herbal inhibitors of these zinc containing enzymes and transcription factor computationally can be of maximal importance in screening very selective clinically relevant inhibitors. The present study has led to the identification of hotspot residues in MMP-1, 3, 9 and AP1, as well as formulation of a few design principles and henceforward new herbal molecules with high affinity and specificity for inhibiting all MMP-1, 3, and 9, and including suppressing expression of the MMPs through the direct repression of AP-1 activity that lead to decelerating in UV-induced skin aging.
International Journal of Peptide Research and Therapeutics
Materials and Methods Preparing of Molecular Structures Three protein data bank (PDB) files of the crystal structures of photoaging-related proteins namely human MMP-1 [PDB accession code: 966C at 1.9 Å resolution (Lovejoy et al. 1999)], MMP-3 [PDB accession code: 1G4K at 2.0 Å resolution (Dunten et al. 2001)], MMP-9 [PDB accession code: 2OW0 at 2.0 Å resolution (Tochowicz et al. 2007)], and Jun–Fos (AP-1)–DNA complex [PDB accession code: 1FOS at 3.05 Å resolution (Glover and Harrison 1995)] were used. Towards the protein setup using Discovery Studio Client 2.5, A chains were selected for further docking in each MMP case. For docking of Jun–Fos (AP-1) complex, E and F chains were selected. The co-crystallized inhibitors and water molecules of the crystal structures were removed. All MMPs and AP-1 complex were minimized their energies with the CHARMm forcefeld. They were then converted to PDBQT file format applying AutoDockTools version 1.5.6 and define as ‘macromolecule’. Gasteiger and + 2 charges were assigned to the macromolecules and zinc atoms in the MMP catalytic sites (and including the surrounding calcium atoms) respectively. Five 2D structures of secoiridoids; amarogentin, amaroswerin, gentiopicrin, sweroside, and swertiamarin including four of other herbal compounds as positive controls (reference compounds) viz., styraxjaponoside B for MMP-1 (Kim et al. 2004), chicoric acid for MMP-3 (Segueni et al. 2011), plantamajoside for MMP-9 (Pei et al. 2015), and curcumin for AP-1 (Sagar et al. 2014) (Fig. 1) were constructed utilizing ChemBioDraw Ultra version 11.0 and afterwards changed to 3D molecules applying ChemBio3D Ultra version 11.0. The 3D structure was minimized its energy using the ‘Minimization protocol’ of Discovery Studio Client 2.5 which was performed by applying the Chemistry at Harvard Macromolecular mechanics (CHARMm) forcefeld. After this process, the molecule was utilized as a ligand for the in silico molecular docking calculation.
Molecular Docking In order to perform each of the docking, the program AutoDock version 4.2.6 was applied to dock all secoiridoids (as well as all positive controls). These ligands were docked to the targets (MMP-1, MMP-3, MMP-9 and transcription factor AP-1) using the whole protein structures as blind docking that was applied in order to identify possible binding site, correct binding conformation, and binding
affinity (the estimated free energy of binding value) of each ligand. Hydrogen atoms of the crystal structures, and Gasteiger charges were added with the aid of the AutoDockTools. Energies for each atom type in the ligand were computed at each grid point applying AutoGrid. All grid boxes were set to enclose the entire proteins with the 126 × 126 × 126 Å grid (0.375 Å between the grid points) centered on MMP-1, MMP-3, and MMP-9 as well as AP-1 [that the entire basic DNA-binding sequence including nearby leucine zipper domain of the transcription factor (Kumar and Bora 2012; Sagar et al. 2014) was covered by the box]. These computed energies were afterward utilized to estimate binding energies for each ligand. Prior to operate the molecular docking, parameters were set. Number of genetic algorithm (GA) runs was 100. A population size was set to 250 with 2,500,000 evaluations (medium). And a maximum of 27,000 generations per GA run were applied. Conformational searching was operated applying the Lamarckian genetic algorithm. Ligand orientations were clustered into groups with a 1 Å cutoff. A final docked delegate of the potential binding mode of the ligand was selected based on selection of the conformation corresponding to the lowest calculated free energy of binding (kcal/mol) within the most populated cluster of the lowest possible energy.
MD Simulation In this analysis of the dynamical parameters, the selected docked complexes of secoiridoid candidates and positive controls were produced by MD simulations. Every simulation was carried out applying the Amber simulation program version 14. Force field parameters for bonds and angles for the ligand were generated by the Antechamber program in the AMBER package. The complexes were intensively prepared before running the structural and energetic analyses. The xleap (program within AMBER) was operated to prepare the complex prior to simulation. The AP-1 protein and nucleic acid parameters were measured utilizing leaprc.ff03. r1 (the standard AMBER force field) (Duan et al. 2003) to create the topologies and parameters of the AP-1 complexes, with Joung and Cheatham (2008) adjustments for ions in TIP3P water model (frcmod.ionsjc_tip3p). A minimum number of ions (Na+/Cl−) were put around the complex to keep the system’s neutrality. The entire system was solvated in the truncated octahedral periodic box of explicit TIP3P water molecules with a minimum solute-wall distance of 10 Å. PMEMD.CUDA from AMBER14 was applied to run all simulations. The MD simulations were operated applying a two femtosecond time step. A potential energy for non-bonding interactions was computed within the cut-off of 10 Å. The long range molecular interactions were speculated applying
13
International Journal of Peptide Research and Therapeutics
Fig. 1 2D structures of the docked secoiridoid compounds, namely a amarogentin, b amaroswerin, c gentiopicrin, d sweroside, and e swertiamarin, and the known positive controls, namely f styraxjaponoside B, g chichoric acid, h plantamajoside, and i curcumin
a periodic boundary condition which is on the basis of the PME technique. The SHAKE and Langevin dynamics algorithms were applied to constrain a bond associating H atom, together with handle the system temperature, respectively.
13
The simulation protocol was similar to previously published method in explicit solvent study (Wongrattanakamon et al. 2017). The VMD 1.9.2 (Humphrey et al. 1996) was applied to visualize and methodically examine the resulting
International Journal of Peptide Research and Therapeutics
simulation trajectory. Structural properties as well as intermolecular interactions of the complex were analyzed from the trajectory of 20,000 ps. Dynamics conformational changes of the trajectory were examined by monitoring an equilibration of quantity; root mean square deviation (RMSD) values of protein backbone (Cα, C, N) atoms throughout the 20,000 ps simulation with respect to the initial structure that deviation in 3D molecular structure during the MD simulation process as a function of the coordinates of the initial position were admeasured applying the CPPTRAJ utility in Amber Tools 15 (Roe and Cheatham 2013). The binding energies of the herbal compounds (secoiridoids and positive control) with respect to AP-1 including AP-1–DNA recognition were evaluated from molecular mechanics–Poisson–Boltzmann surface area/generalized born surface area (MM–PBSA/GBSA) approaches, implemented in AMBER14 package. The equidistant 2000 snapshots from the 20 ns simulations of AP-1 were utilized to compute the binding energy (kcal/mol). Applying the MM–GBSA decomposition method of the MMPBSA. py module of the package (Miller et al. 2012), the protein–ligand interaction energy data was generated via decomposing the total free energy of binding into pairs of residue–residue interaction.
location in blue. The important protein–secoiridoid interaction images (2D and 3D) were generated by the program.
Results Docking of Secoiridoids with MMP‑1, MMP‑3, and MMP‑9
The docked (pre-MD) and post-MD (20 ns) complexes of the herbal compounds were further examined using LigandScout 4.1 (Wolber and Langer 2005) to generate schematic diagrams of protein–ligand interactions (binding modes). Pharmacophore models were generated that indicate certain amino acid residue atoms in each binding site interacted with ligand atoms. The interactions created by the program were presented as five main features in reference to a ligand, namely HBD (hydrogen bond donors) in green, HBA (hydrogen bond acceptor) in red, H (hydrophobic interactions) in yellow, Ar (aromatic ring) in purple, and zinc binding
For docking validation, the internal ligands; N-hydroxy-2-[4(4-phenoxy-benzenesulfonyl)-tetrahydro-pyran-4-yl]-acetamide, 5-methyl-5-(4-phenoxy-phenyl)-pyrimidine-2,4,6trione, and N-[(4′-iodobiphenyl-4-yl)sulfonyl]-d-tryptophan were extracted from 966C, 1G4K, and 2OW0 respectively. They were then docked back into their original binding sites in the corresponding crystal proteins (re-docking). The calculated RMSD values of re-docking comparing to the crystal structures were regarded as a measurement of the accuracy of the docking outcomes. The obtained best poses of three internal ligands were recognized because their RMSD values were found to be < 3.0 Å (Fig. 2) (Tedasen et al. 2017). If the binding energy (ΔGbinding) of secoiridoid was presented equally or better than the recognized inhibitor, it will be regarded as a potential protein inhibitor. In consideration of docking properties of secoiridoids with the photoaging-related proteins; MMP-1, MMP-3, and MMP-9 (as well as AP-1), the in silico generated ligand of the secoiridoids viz., amarogentin, amaroswerin, gentiopicrin, sweroside, and swertiamarin were chosen for docking. Docking of these compounds with the MMPs (and AP-1) was studied towards (a) ligand-binding conformation, (b) predicted binding energy, and (c) interacting amino acid residue and atom. Towards MMP-1, MMP-3, and MMP-9 the compounds amarogentin, amaroswerin, gentiopicrin, sweroside, and swertiamarin showed successful docking simulations to all MMPs. Docking calculations were carried out and the binding sites for the secoiridoids on all MMPs were found. The ligands were fitted into the S1′-pocket of the catalytic domain
Fig. 2 The matches of the crystallographic (green) and the minimum energy blind re-docked (magenta) conformations of a N-hydroxy2-[4-(4-phenoxy-benzenesulfonyl)-tetrahydro-pyran-4-yl]-acetamide,
b 5-methyl-5-(4-phenoxy-phenyl)-pyrimidine-2,4,6-trione, and c N-[(4′-Iodobiphenyl-4-yl)sulfonyl]-d-tryptophan (PDB codes: 966C, 1G4K, and 2OW0 respectively). (Color figure online)
Structure‑Based Pharmacophore Modeling
13
Table 1 Docking energy against the protein targets of each secoiridoid
International Journal of Peptide Research and Therapeutics Compound
Amarogentin Amaroswerin Gentiopicrin Sweroside Swertiamarin Positive controls
Lowest estimated free energy of binding in cluster (kcal/mol) MMP-1 (PDB 966C)
MMP-3 (PDB 1G4K)
MMP-9 (PDB 2OW0)
AP-1 (PDB 1FOS)
− 9.82 − 7.94 − 8.24 − 7.73 − 7.70 Styraxjaponoside B − 6.99
− 9.90 − 9.25 − 10.05 − 8.01 − 8.71 Chichoric acid − 5.88
− 8.13 − 7.81 − 9.01 − 6.81 − 6.56 Plantamajoside − 5.72
− 5.50 − 4.58 − 4.82 − 3.95 − 4.30 Curcumin − 4.77
of each MMP near the active center binding site. All compounds exhibited strong binding energy values to all MMPs (Table 1); − 9.82, − 7.94, − 8.24, − 7.73, and − 7.70 kcal/ mol respectively for MMP-1; − 9.90, − 9.25, − 10.05, − 8.01, and − 8.71 kcal/mol respectively for MMP-3; − 8.13, − 7.81, − 9.01, − 6.81, and − 6.56 respectively for MMP-9; which are better than their positive controls (styraxjaponoside B, chichoric acid, and plantamajoside respectively). The docking results indicate that all secoiridoids have high affinity for all MMPs. They interacted to the proteins with the similar cavities and amino acid residues to each other and the positive controls (Fig. 3; Tables 2, 3, 4). These results suggest that amarogentin, amaroswerin, gentiopicrin, sweroside, and swertiamarin might inhibit collagen degradation via blocking multiple protein targets in the MMP pathway. The result indicated that every secoiridoid compound interacted with every MMP with high affinity binding forces that signifies the anti-aging activity of these compounds. Tables 2, 3 and 4 summarizes the results of binding mode analysis showing MMPs’ amino acids involved in binding interactions with the screened ligands.
Docking of Secoiridoids with AP‑1 Protein The five natural secoiridoids derived from S. chirayita were docked with AP-1 protein. Two compounds amarogentin and gentiopicrin have greater calculated binding energy values, − 5.50 and − 4.82 kcal/mol respectively (Table 1), than other secoiridoids for AP-1 which are better than the positive control curcumin (− 4.77 kcal/mol). The docking results indicate that amarogentin and gentiopicrin have high affinity for AP-1. They interacted to the protein with the similar site (DNA-binding region) to curcumin (Fig. 4). The secoiridoids amarogentin and gentiopicrin, the two highest affinity ligands to the all docked proteins, can selectively inhibit enzyme activity and gene expression linked to UV-induced photoaging via control many important proteins, along with MMP-1, MMP-3, MMP-9 and especially AP-1. Therefore, AP-1 protein binding of amarogentin and gentiopicrin, and
13
corresponding DNA binding of AP-1 protein were analyzed using the full MD simulation technique.
Structures from MD Simulations The binding affinities and interactions could be more accurately calculated by MD simulations through the flexibility of the protein and ligand. For this reason, this technique was employed to simulate the interaction between amarogentin and gentiopicrin and their protein target AP-1. In this work, MD was run to clarify the interactions between the two active secoiridoids and AP-1 in the MMP pathway network. The two secoiridoid compounds were subjected to 20,000 ps simulations, and the free energies of binding of the snapshots (protein–ligand and protein–DNA binding free energies) were then noted in Tables 5 and 6. Trajectory analysis was seen to have a low fluctuation of the binding site after 12,500 ps (Fig. 5).
Binding Free Energy Analysis In order to measure the binding affinity of the two secoiridoids in the AP-1 binding site, the total free energies of binding were estimated by the MM–GBSA approach through the MMPBSA.py module. The components of the binding free energy (kcal/mol) of each AP-1–secoiridoid complex are noted in Table 5. The free energies of binding of amarogentin, gentiopicrin, and the positive control curcumin bound to AP-1 are − 23.4355, − 18.0093, and − 17.1676 kcal/mol, respectively, which are in remarkably good agreement with the docking scores. The obtained results from the above two individual methods demonstrate that the practical binding free energy analysis is reliable. The results showed that amarogentin and gentiopicrin have strong binding interactions with AP-1 (higher negative binding free energy values than the positive control curcumin) that prevent AP-1’s binding to DNA leading to the total loss of constitutive DNAbinding ability when the DNA-binding region was blocked by both compounds (lesser negative AP-1–DNA binding free energy values in amarogentin and gentiopicrin complexes
International Journal of Peptide Research and Therapeutics
Fig. 3 The lowest energy docking models for the protein–ligand recognition between the secoiridoids/reference herbal compounds and catalytic sites of a MMP-1, b MMP-3, and c MMP-9. The docked compounds are amarogentin (green), amaroswerin (blue), gentiopic-
rin (yellow), sweroside (magenta), swertiamarin (cyan), and styraxjaponoside B (a), chichoric acid (b), and plantamajoside (c) (orange). The MMPs are in cartoon–mesh representations and the zinc atoms are displayed in lime green spheres. (Color figure online)
than the positive and negative control complexes; Table 6). Amarogentin is a good high-affinity ligand for AP-1 that binds to the binding site in a relatively low energy conformation. Changes in the ligand RMSD were generally small and stable (Fig. 5b). These results clarify the low RMSD of amarogentin and support the stability of the formed AP-1–amarogentin complex. Jun–Fos dimer of the MAPKs family is another potential drug target for the development of new anti-aging agents. Therefore, the molecular mechanism of the compounds against photoaging might be interpreted.
Pre‑MD and post‑MD Simulation Binding Interaction Analysis Binding modes of the two secoiridoids amarogentin and gentiopicrin including the positive control curcumin were calculated and delineated from pre-MD (docked) and postMD (20,000 ps) structures of the AP-1–amarogentin, gentiopicrin, and curcumin complexes. Significant molecular interactions such as hydrophobic interactions and hydrogen bonds were examined by interaction network visualizing
13
International Journal of Peptide Research and Therapeutics
Table 2 Binding modes of the secoiridoids and positive control against MMP-1 Compound
Residue involved in H-bond formation
Residue involved in hydrophobic interaction Zinc binding location
Amarogentin
OH (donor)–Gly179 OH (donor)–Asn180 O side chain (acceptor)–Leu181 and Ala182 OH (acceptor)–Tyr210 OH (donor)–Glu219 OH (donor)–His222 and His228 O side chain (acceptor)–Tyr240 O side chain (acceptor)–Ala182 OH (acceptor)–Ala184 OH (donor)–Glu219 OH–Pro238 (acceptor) and Ser239 (donor) OH (donor)–Ser239 OH (donor)–Ala234 OH (donor)–Ser239 2O (acceptor)–Ser239 OH (donor)–Thr241 OH (acceptor)–Asn180 OH–Leu181 (donor) and Ala182 (donor and acceptor) OH–Ala182 (acceptor) and Ala184 (donor) OH (donor)–His218 OH (donor)–Ala234 and Ser239 OH (donor)–Thr241 OH (donor)–Asn180
–
–
Aromatic side chain–Leu181
OH–Zn171
Aromatic ring skeleton–Leu181 Aromatic ring skeleton–Val215 Vinyl group–Val215 Vinyl group–Tyr240 –
–
Amaroswerin
Gentiopicrin
Sweroside Swertiamarin Styraxjaponoside B (positive control)
– –
Vinyl group–Leu181 Vinyl group–Ala182 Vinyl group–Val215 Aromatic side chain–Leu235
–
Table 3 Binding modes of the secoiridoids and positive control against MMP-3 Compound
Residue involved in H-bond formation
Residue involved in hydrophobic interaction Residue involved in aromatic interaction
Amarogentin
OH (donor)–Ala165 and His201 OH (acceptor)–Tyr223 O side chain (acceptor)–His224 OH (donor)–Asn162 OH–Ala167 (donor), and Glu202 and His205 (acceptors) OH (donor)–Glu202 OH (donor)–Glu202 OH (donor)–His211
Vinyl group–Leu164 Vinyl group–Ala165 Vinyl group–Val198 Aromatic side chain–Leu164 and Val198 Vinyl group–Leu164
Amaroswerin Gentiopicrin
Sweroside
Swertiamarin
Cichoric acid (positive control)
13
Aromatic ring skeleton–Leu197 Vinyl group–Leu197 Vinyl group–Val198 Aromatic ring skeleton–Leu218 Vinyl group–Leu218 Vinyl group–Tyr223 Vinyl group–Leu164 Vinyl group–Ala165 Vinyl group–Val198
OH (donor)–Asn162 OH (donor)–Asn162 OH–Pro221 (acceptor) and Tyr223 (donor) Vinyl group–Leu164 OH (donor)–Glu202 OH (donor)–Ala217, Leu218, and Tyr220 OH (donor)–His224 OH (donor)–His224 OH (donor)–Arg231 Aromatic side chain–Leu164, Val198, and Tyr223 Aromatic side chain–Leu226 and Phe232
–
Zinc binding location
–
– Aromatic side chain– His201 – OH–Zn301 OH–Zn301
–
–
–
–
International Journal of Peptide Research and Therapeutics Table 4 Binding modes of the secoiridoids and positive control against MMP-9 Compound
Residue involved in H-bond forma- Residue involved in hydrophobic tion interaction
Amarogentin
O side chain (acceptor)–Phe110 O side chain (acceptor)–Leu188 and Ala189 OH (donor)–Ala189 OH (donor)–Ala191 OH–Gln402 (donor) and His405 (acceptor) OH (donor)–Gly186 OH–Ala189 (acceptor) and Gln402 (donor) OH (acceptor)–Gln402 OH (donor)–Pro421 2O (acceptor)–Tyr423 OH (donor and acceptor)–Ala189 OH (donor)–Ala189 OH (acceptor)–Arg424
Amaroswerin
Zinc binding location
Vinyl group–Phe110 Vinyl group–Tyr179 Vinyl group–Leu187 Aromatic side chain–Leu188 and Val398
Aromatic side chain–Zn444 –
Vinyl group–Leu187 Vinyl group–Leu188
–
–
–
–
–
–
–
–
Vinyl group–Leu188 Vinyl group–Ala189 Vinyl group–Val398 Aromatic side chain–Val398 and Tyr423 Vinyl group–Leu188 Sweroside OH (donor)–Gly186 OH–Met422 (acceptor) and Tyr423 Vinyl group–Ala189 Vinyl group–Val398 (donor and acceptor) O side chain (acceptor)–Tyr423 Vinyl group–Leu188 Swertiamarin O side chain (acceptor)–Leu188 Vinyl group–Val398 and Ala189 Vinyl group–Tyr423 OH (donor)–Pro421 O side chain (acceptor)–Tyr423 Plantamajoside OH–Ala189 (acceptor) and Gln402 Vinyl group–Val398 Vinyl group–Tyr423 (Positive control) (donor) OH (acceptor)–Gln402 OH (donor)–Tyr420 OH–Leu418, Tyr420, and Met422 (acceptors) OH (acceptor)–Tyr423
Gentiopicrin
Residue involved in aromatic interaction
Fig. 4 The lowest energy docking model for the protein–ligand recognition between the secoiridoids/reference herbal compound and DNA-binding region of AP-1. The docked compounds are amarogen-
OH–Zn444
tin (green), gentiopicrin (blue), and curcumin (orange). The AP-1 is in a cartoon–mesh and b closed-up surface representations. (Color figure online)
13
International Journal of Peptide Research and Therapeutics
Table 5 Components of the binding free energies (kcal/mol) of amarogentin, gentiopicrin and positive control curcumin as calculated using the MM–GBSA protocol of the MMPBSA.py module Compound
VDWAALS
EEL
EGB
ESURF
Delta Ggas
Delta Gsolv
Delta total
Amarogentin Gentiopicrin Curcumin
− 37.9513 − 29.8826 − 27.5191
− 0.7057 − 4.4986 6.4011
19.9181 20.4557 7.9619
− 4.6965 − 4.0838 − 4.0115
− 38.6571 − 34.3812 − 21.1180
15.2216 16.3719 3.9504
− 23.4355 − 18.0093 − 17.1676
Table 6 Components of the AP-1–DNA binding free energies (kcal/mol) in amarogentin, gentiopicrin, and positive and negative control complexes as calculated using the MM–PBSA protocol through the Perl script
Method
MM
PBSA
Contribution
ELE VDW INT GAS PBSUR PBCAL PBSOL PBELE PBTOT
AP-1–DNA interaction energy in each contribution (kcal/mol) Amarogentin
Gentiopicrin
Curcumin
Negative control
− 13384.78 − 47.50 132.19 − 13300.09 − 22.51 13256.84 13234.33 − 127.94 − 65.75
− 13879.24 − 62.53 130.88 − 13810.90 − 25.37 13758.27 13732.90 − 120.97 − 78.00
− 13684.92 − 55.14 130.68 − 13609.39 − 23.26 13549.02 13525.76 − 135.90 − 83.62
− 13906.69 − 58.86 131.52 − 13834.04 − 23.69 13759.81 13736.13 − 146.88 − 97.91
ELE non-bonded electrostatic energy, VDW non-bonded van der Waals energy, INT internal energies (bond, angle, dihedral energies), GAS: MM energies = ELE + VDW + INT, PBSUR: non-polar contribution to solvation, PBCAL polar contribution of solvation, P BSOL = PBSUR + PBCAL, PBELE = PBCAL + ELE, PBTOT: total binding free energy calculated by the MM–PBSA method = PBSOL + GAS
applying the LigandScout program. After simulation, position of each secoiridoid was by some means very slightly shifted when compared to the initial docked mode in the binding site on the DNA-binding region of AP-1, and well positioned into the site with hydrophobic and electrostatic interactions. The pre- and post-MD simulation binding modes for three AP-1–secoiridoid complex conformations are shown in Fig. 6. Furthermore, in order to delineate into the mechanism of protein–ligand recognition and to explore the contributions of essential amino acid residues involving the binding interactions, the free energy of binding of each AP-1–secoiridoid complex was decomposed on essential residues in the binding site. For this reason, decomposed energies on a pairwise per-residue basis were admeasured. Generally, a residue is considered to be an essential amino acid residue in molecular recognition of a ligand for stabilization within a binding site if the molecular interaction energy between the amino acid residue and ligand is lower than − 1 kcal/mol (Zhang et al. 2017). The result shows the energy decomposition values for the identified key amino acid residues in the binding site of amarogentin, gentiopicrin, and curcumin (Table 7). In case of amarogentin, the initial binding of the ligand (the docked complex) (Fig. 6a), the oxygen-atom and hydroxyl side chains of the compound participated in forming hydrogen bonds with Ser278 and Arg279. The vinyl
13
group and aromatic side chain performed as the hydrophobic parts of the molecule forming hydrophobic interactions with two hydrophobic amino acid residues, Ala151 and Leu283 respectively in the binding site. In the stable stage (Fig. 6b), new hydrogen bond between the hydroxyl side chain of the ligand and Lys282 was formed and only the hydrophobic bond between the aromatic side chain and Leu283 was remained. From the per-residue binding energy decomposition analysis (Table 7), the result supports the pharmacophore modeling of the AP-1–amarogentin complex that Arg279 and Lys282 contributed to the total binding free energy in which amarogentin formed the hydrogen bonds with them (in the initial binding and reorientation processes for Arg279, and in the reorientation process and stable stage for Lys282). Leu283 was also identified by the decomposition analysis and pharmacophore modeling that this residue contributed the hydrophobic interaction with the aromatic side chain of the ligand from the beginning until the stable stage. Towards gentiopicrin, the initial binding of the ligand (the docked complex) (Fig. 6c), the oxygen atom of the glycosidic bond participated in forming a hydrogen bond with Ser154. The aromatic ring skeleton performed as the hydrophobic part of the molecule forming a hydrophobic interaction with the hydrophobic amino acid residue, Leu283 in the binding site. In the stable stage (Fig. 6d), gentiopicrin
International Journal of Peptide Research and Therapeutics
to each other and curcumin (Fig. 6; Table 7). These results suggest that amarogentin and gentiopicrin might inhibit collagen degradation via suppressing MMP-associated gene expression by blocking the AP-1–DNA interaction involving the MMP pathway.
Discussion
Fig. 5 Plot of RMSD values versus time (ps) obtained over 20,000 ps production for the backbone atoms (Cα, N, C) of the a DNA-binding region–ligand parts and b ligands
slightly shifted from its initial binding residues to the adjacent residues. The hydrogen bond was lost and a new hydrophobic bond was formed. Figure 6d shows that gentiopicrin interacts with the binding site by hydrophobic interactions between the vinyl group of the ligand and the residues Thr162 and Ile286 of the DNA-binding region. The result from the energy decomposition analysis (Table 7) supports the pharmacophore modeling of the AP-1–gentiopicrin complex that Leu283 contributed to the total binding free energy in which gentiopicrin formed the hydrophobic bond with the residue (in the initial binding and reorientation processes). Moreover, Thr162 and Ile286 were also identified by the decomposition analysis and pharmacophore modeling that these residues contributed the hydrophobic interactions with the vinyl group of the ligand from the reorientation process until the stable stage. The pharmacophore modeling and per-residue binding energy decomposition results indicate that amarogentin and gentiopicrin have the strong and stable interactions between their molecules and the DNA-binding region of AP-1 the same as the positive control curcumin. They interacted to the protein with the similar site and key amino acid residues
MAPK signaling pathway is realized to be one of the considerable signal transduction pathways activated by exposure of UVB. This pathway is a significant transmitter of extracellular signals to the cell nucleus. In human dermal fibroblasts, increased ROS production on account of UVB exposure activates the pathway (dose dependent manner). In consequence of the activation, MAPK downstream targets, for example, JNK, ERK and p38 are phosphorylated and pivotal transcription factors, for example, AP-1 are activated, which simultaneously encourage expression of the zinc-containing enzymes; MMPs leading to subsequent escalating collagen degradation (Cavinato and Jansen-Dürr 2017). Small compound inhibitors are the majority of MMP inhibitors tested in many clinical trials. They were designed to interfere specifically with their catalytic domains (Kessenbrock et al. 2015). There are several subsites (designated by unprimed and primed S, e.g., S1, S2, S3 and S1′, S2′, S3′) present in the MMPs which interact with substrate or inhibitor molecules. The S1′-pocket of the catalytic domain of each MMP has played a significant role in the design of their inhibitors. The determination of inhibitor affinity and the MMP catalytic domain is mainly based on ligand–S1′ interaction (Gupta and Patil 2012). The present docking studies revealed that secoiridoids could inhibit MMP catalytic domains by binding at the S1′-pocket similar to their co-crystallized inhibitors and positive controls with similar interactions at the same sites. Secoiridoids including amarogentin, amaroswerin, gentiopicrin, sweroside, and swertiamarin have the higher affinity for all MMPs because they bind with lowest binding energy, formed number of hydrogen, hydrophobic, and chelate bonds with the catalytic site residues as compared to styraxjaponoside B (MMP-1), chicoric acid (MMP-3), and plantamajoside (MMP-9) inhibitors. The binding modes of all selected secoiridoids within MMP-1, MMP-3, and MMP-9 were studied. Various key features of plausible molecular interactions can be derived. According to Fig. 3 and the 2D structure-based pharmacophore models of the five secoiridoids (data not shown), the ligands are able to possess three subpockets, namely S1, S1′ and S3′ of the MMPs. They subsequently generate hydrogen bonds by their oxygen atoms and hydroxyl groups, chelate bonds through their hydroxyl groups and zinc ions, pi–pi interaction through the aromatic rings, and cation–pi interaction through the aromatic ring and zinc ion of the ligands and
13
International Journal of Peptide Research and Therapeutics
Fig. 6 Structure-based pharmacophore models illustrate molecular interactions of AP-1: a, b amarogentin, c, d gentiopicrin, and e, f curcumin; a, c, e pre-MD interactions and b, d, f post (20,000 ps)-MD interactions
13
International Journal of Peptide Research and Therapeutics
Fig. 6 (continued)
13
International Journal of Peptide Research and Therapeutics
Table 7 Relative decomposed free energies during 20,000 ps of important amino acid residues of AP-1 interacting with amarogentin and gentiopicrin Important residue
Amarogentin (kcal/mol)
Gentiopicrin
Curcumin
Ser154 Arg155 Arg158 Arg159 Thr162 Arg279 Lys280 Lys282 Leu283 Glu284 Arg285 Ile286 Ala287
– − 1.23602 − 6.01571 – − 1.04623 − 3.33651 – − 5.34837 − 7.07407 – − 2.06485 − 2.23457 –
– − 2.15184 − 4.13501 − 2.33869 − 1.09656 − 2.67836 – − 3.93569 − 3.32504 – − 1.94521 − 1.01882 –
− 1.00594 − 1.52629 − 3.10230 – – − 3.42715 − 1.30485 − 1.34136 − 4.60647 − 1.07855 – − 1.88948 − 1.15142
protein. In addition to electrostatic interaction, it pointed out that, in the S1′ cavity, the hydrophobic interaction is likewise essential for the MMP inhibitory activity (Yuan et al. 2013). In the S1′ and S3′ pockets, the secoiridoids were likewise stabilized by hydrophobic interactions. With regard to the S1′ cavity, the aromatic rings and vinyl groups of the compounds made hydrophobic contacts with residues Val215, Leu235, and Tyr240 of MMP-1, Leu197, Val198, Leu218, and Tyr223 of MMP-3, and Val398 and Tyr423 of MMP9. Moreover, these ligand parts made hydrophobic contacts with residues Leu181 of MMP-1, and Leu187 and Leu188 of MMP-9 in the S3′ pocket. The other parts extend toward the S1 pockets, binding by a hydrophobic interaction, the vinyl group of swertiamarin made the interaction with Ala182 of MMP-1, the aromatic rings and vinyl groups of amarogentin, amaroswerin, sweroside, and swertiamarin made the hydrophobic interactions with Leu164 and Ala165 of MMP-3, and the vinyl groups of gentiopicrin and sweroside made the hydrophobic interactions with Ala189 of MMP-9. The cupped secoiridoid inhibitor conformations predicted fit the shape and size of the MMP catalytic positions well, so these make the compounds combine with MMP-1, MMP-3, and MMP-9 closely, which could be corresponding with the high potency against the enzymes. The study of Yuan et al. (2013) revealed herbal compound methyl rosmarinate as an inhibitor of MMP-1 (experimental IC50 of 14.7 mM). Its binding modes clarified by molecular docking between the compound and MMP-1 were shown that, from the caffeic acid group, the phenyl ring inserted into the S1′ cavity, which made hydrophobic interactions with the amino acid residues His218 and Tyr240 that are similar to the hydroxyl group of swertiamarin (hydrogen
13
bond with His218), the oxygen atom of amarogentin (hydrogen bond with Tyr240), and the vinyl group of gentiopicrin (hydrophobic interaction with Tyr240). Some polar interactions occurred in the binding interactions between methyl rosmarinate and MMP-1. The carbonyl group of the ligand formed a chelate bond with the MMP zinc atom (similar to the hydroxyl group of amaroswerin). Another carbonyl group in the middle of methyl rosmarinate made ionic interactions with the polar nitrogen atom of the residue Ala182 that are similar to the oxygen atoms and hydroxyl groups of amarogentin, amaroswerin, and sweroside (hydrogen bonds), and the vinyl group of swertiamarin (hydrophobic interaction). Moreover the hydroxyl groups of the two terminal aryl rings which locate in methyl rosmarinate made hydrogen bonds with the polar atoms of the amino acid residues Ala234, Thr241 in the S1′ cavity and the residue Asn180 in the S3′ cavity, respectively that are similar to the hydroxyl groups of gentiopicrin and swertiamarin which formed hydrogen bonds with Ala234 and Thr241, and the hydroxyl groups of amarogentin and sweroside which formed hydrogen bonds with Asn180. The present MMP-1 docking result was similar as reported by Yuan et al. (2013) that validated the accuracy of the present MMP-1 docking study. Hence, when methyl rosmarinate is bound to MMP-1, the protein is in consequence inactivated due to high affinity between methyl rosmarinate and the enzyme and when the secoiridoids are bound to MMP-1, the MMP also could be in consequence inactivated by reason of the same interactions. The study of Amin and Welsh (2006) revealed 2-phthalimidinoglutaric acid analogues as MMP-3 inhibitors. The two carbonyls of the high potency ligand chelated the catalytic zinc atom that is similar to the hydroxyl groups of gentiopicrin. Amide nitrogen of this analogue formed a critical hydrogen bond with Glu202 in the S1′ pocket that is similar to the hydroxyl groups of amaroswerin, gentiopicrin, and swertiamarin. Another two analogues exhibited high predicted activities, with SO2 moieties that engaged in hydrogen bonding with Leu164 and Ala165 in the S1 pocket that is similar to the hydroxyl group of amarogentin which formed hydrogen bond with Ala165. Moreover, the vinyl groups and aromatic ring of amarogentin, amaroswerin, sweroside, and swertiamarin also formed hydrophobic interactions with Leu164 and Ala165. Kumar and Patnaik (2017) found that withanolide G (the phytochemical extracted from Withania somnifera) is an MMP-9 inhibitor. The compound formed hydrogen bonds to His405, His411, Pro421, Tyr423, and zinc atom. Moreover, it formed hydrophobic contacts with Phe110, Glu111, Gly186, Leu187, Leu188, Ala189, His190, Glu402, Tyr420, Met422, and Val398 residues of the MMP-9 catalytic domain. These important residues conform to the residues identified in the present study that amarogentin formed hydrogen bond to His405, amaroswerin and swertiamarin formed hydrogen bonds to Pro421, and amaroswerin,
International Journal of Peptide Research and Therapeutics
gentiopicrin, sweroside, and swertiamarin formed hydrogen bonds to Tyr423 (gentiopicrin and swertiamarin also formed hydrophobic interactions to this residue). Moreover, towards hydrophobic binding, Phe110 contributed a hydrophobic interaction (including hydrogen bond formation) with amarogentin. Leu187 contributed hydrophobic interactions with amarogentin and amaroswerin. Leu188 contributed hydrophobic interactions with all ligands (including hydrogen bond formations with amarogentin and swertiamarin). Ala189 contributed hydrophobic interactions with gentiopicrin and sweroside (including hydrogen bond formations with amarogentin, amaroswerin, gentiopicrin, and swertiamarin). Val398 contributed hydrophobic interactions with amarogentin, gentiopicrin, sweroside, and swertiamarin. Hence, when these secoiridoids are bound to MMP-3 and MMP9, the enzymes could be inactivated by reason of the same interactions as observed in the previous studies. An overall analysis of residues involved in the AP-1–secoiridoid modeling revealed the implication of Ala, Ile, Leu, Ser, Thr, Arg, Lys, and Glu as most common amino acids at the significant binding site, signifying their roles in determining the binding strength and relative contribution in the formation of electrostatic and hydrophobic bonds. The results, according to the pharmacophore modeling (Fig. 6) and the energy components of the free energies of binding (Table 5) indicate that the non-bond van der Waals energy of the AP-1–secoiridoid (as well as—curcumin) complex gives the highest contribution to the binding free energy (high negative values for ΔEvdw), which confirms that the hydrophobic interaction is dominant for the secoiridoids interacting with AP-1. This may due to the favorite interaction between the ligand and identified hydrophobic key amino acid residues Ala, Ile, and Leu. In addition to these hydrophobic residues, Thr, Arg, Lys, and Glu also play a key role for the intermolecular hydrophobic bond formation. Some hydrophobic interactions in the reorientation process and stable stage may be contributed by these key hydrophilic residues due to the fact that the hydrophobic interactions may occur between the hydrophobic part(s) of each ligand and the (1) Thr methyl group (Zhang and Laursen 1998) (2) Arg aliphatic portion (Legault et al. 1998) (3) Lys (Oh et al. 1980) and (4) Glu (Li et al. 2007) hydrophobic –(CH2)n– portions (methylene spacers). With the contributions from these abovementioned key hydrophilic amino acids along with the key hydrophobic residues, allowing the ligands to occupy and strongly bind to the DNA-binding region of AP-1 may then result in inhibition of the protein binding to DNA. These results also point out that the raise of the hydrophobicity of these molecules may lead to a raise in the binding affinity of these inhibitors in the AP-1 DNAbinding region. Moreover, the docking study of curcumin as an AP-1 inhibitor performed by Kumar and Bora (2012) clarified that Lys282 and Leu283 are the important amino
acid residues of the binding site responsible for polar and hydrophobic interactions respectively with the ligand. These key residues corresponded to the present docking identified interacting residues that Lys282 formed a hydrogen bond and Leu283 contributed a hydrophobic interaction with curcumin as well as amarogentin and gentiopicrin in the initial binding interaction. The chemical characteristics of polyphenol–protein interactions are generally involved: (1) the hydrophobicity of the aromatic nuclei of polyphenols and (2) the availability of multiple phenolic hydroxyl groups that allow hydrogen bonding (Fraga et al. 2009). It is noted that the hydrophobic portions (aromatic rings/the presence of a double bond between C5 and C6 of the secoiridoid skeleton, as in gentiopicrin, increases the hydrophobicity, and vinyl groups) as well as the hydrophilic portions (oxygen atoms and hydroxyl groups) of the secoiridoids (including the all control natural phenolic compounds) are very important for hydrophobic contacts, hydrogen and chelate bonds, and pi–pi and cation–pi interactions with the key amino acid residues to hold the ligands tightly into the binding sites inside the MMPs and on the AP-1 surface in the ligand binding process.
Conclusions The present integrated molecular docking, pharmacophore modeling, and MD simulations study provides significant evidence and insights into the inhibition of (1) activity of the photoaging-related proteins MMP-1, MMP-3, and MMP-9, and (2) Jun–Fos–DNA complex formation by secoiridoids that may confer skin protection in the UV-induced skin aging. These computational techniques were successful in modeling reliable binding conformation, binding modes, binding energy, and type of interaction of a secoiridoid compound in the MMP and AP-1 binding sites. Five secoiridoids (amarogentin, amaroswerin, gentiopicrin, sweroside, and swertiamarin) exhibit high affinity for the MMP-1, MMP3, and MMP-9. Every ligand bound to the S1′-pocket residues with the lowest binding energy than every reference inhibitor. Based on the modeling, the binding locations of secoiridoids in the MMP pockets and AP-1 surface as well as the corresponding key amino acid residues and ligand pharmacophores are important for their inhibitory activities. The MM–GBSA binding energy of AP-1–ligand complexes suggests that the van der Waals interaction exhibits a greater contribution to the binding of the secoiridoids on the AP-1 DNA-binding region than the electrostatic interaction. All of the compounds were predicted to be more potent than the known MMP inhibitors like styraxjaponoside B, chichoric acid, and plantamajoside. Amarogentin was predicted to be the most potent inhibitor among all the natural secoiridoids tested which may inhibit all the MMP and AP-1 proteins.
13
Therefore, the results obtained from the present study can facilitate the further preclinical in vitro and in vivo models, and clinical trial in regard to skin protective potential against UV-induced skin aging. Acknowledgements The authors would like to thank Inte:Ligand Software-Entwicklungs und Consulting GmbH for providing an academic free license for LigandScout 4.1.
Compliance with Ethical Standards Conflict of interest Every author declares no conflict of interest. Research Involving Human and Animal Rights This article does not contain any study with human or animal subjects performed by any of the authors.
References Amin EA, Welsh WJ (2006) A preliminary in silico lead series of 2-phthalimidinoglutaric acid analogues designed as MMP-3 inhibitors. J Chem Inf Model 46:2104–2109. https: //doi.org/10.1021/ ci0601362 Cavinato M, Jansen-Dürr P (2017) Molecular mechanisms of UVBinduced senescence of dermal fibroblasts and its relevance for photoaging of the human skin. Exp Gerontol 94:78–82. https:// doi.org/10.1016/j.exger.2017.01.009 Duan Y et al (2003) A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations. J Comput Chem 24:1999–2012. https:// doi.org/10.1002/jcc.10349 Dunten P, Kammlott U, Crowther R, Levin W, Foley LH, Wang P, Palermo R (2001) X-ray structure of a novel matrix metalloproteinase inhibitor complexed to stromelysin. Protein Sci 10:923– 926. https://doi.org/10.1110/ps.48401 Fraga CG, Celep GS, Galleano M (2009) Biochemical actions of plant phenolics compounds: thermodynamic and kinetic aspects. In Plant phenolics and human health. Wiley, New York, pp 91–106. https://doi.org/10.1002/9780470531792.ch3 Glover JNM, Harrison SC (1995) Crystal structure of the heterodimeric bZIP transcription factor c-Fos-c-Jun bound to. DNA Nat 373:257–261 Gupta SP, Patil VM (2012) Specificity of binding with matrix metalloproteinases. In Matrix metalloproteinase inhibitors, vol 103. Springer, Basel, pp 35–56. https : //doi. org/10.1007/978-3-0348-0364-9_2 Hu J, Van den Steen PE, Sang Q-XA, Opdenakker G (2007) Matrix metalloproteinase inhibitors as therapy for inflammatory and vascular diseases. Nat Rev Drug Discov 6:480–498 http://www.natur e.com/nrd/journal/v6/n6/suppinfo/nrd2308_S1.html Humphrey W, Dalke A, Schulten K (1996) VMD: visual molecular dynamics. J Mol Grap 14:33–38 Joshi P, Dhawan V (2005) Swertia chirayita: an overview. Curr Sci 89:635–640 Joung IS, Cheatham TE (2008) Determination of alkali and halide monovalent ion parameters for use in explicitly solvated biomolecular simulations. J Phys Chem B 112:9020–9041. https://doi. org/10.1021/jp8001614 Jung H-Y, Shin J-C, Park S-M, Kim N-R, Kwak W, Choi B-H (2014) Pinus densiflora extract protects human skin fibroblasts against UVB-induced photoaging by inhibiting the expression of MMPs
13
International Journal of Peptide Research and Therapeutics and increasing type I procollagen expression. Toxicol Rep 1:658– 666. https://doi.org/10.1016/j.toxrep.2014.08.010 Kessenbrock K, Wang C-Y, Werb Z (2015) Matrix metalloproteinases in stem cell regulation and cancer. Matrix Biol 44–46:184–190. https://doi.org/10.1016/j.matbio.2015.01.022 Kim M-R, Moon H-I, Chung JH, Moon YH, Hahm K-S, Woo E-R (2004) Matrix Metalloproteinase-1 Inhibitor from the Stem Bark of Styrax japonica S. et Z. Chem Pharm Bull 52:1466–1469. https ://doi.org/10.1248/cpb.52.1466 Kim J et al (2011) Inhibition effect of Gynura procumbens extract on UV-B-induced matrix-metalloproteinase expression in human dermal fibroblasts. J Ethnopharmacol 137:427–433. https://doi. org/10.1016/j.jep.2011.04.072 Kumar A, Bora U (2012) In silico inhibition studies of Jun–Fos-DNA complex formation by curcumin derivatives. Int J Med Chem 2012:8. https://doi.org/10.1155/2012/316972 Kumar G, Patnaik R (2017) Inhibition of gelatinases (MMP-2 and MMP-9) by Withania somnifera phytochemicals confers neuroprotection in stroke: an in silico analysis. Interdisc Sci Comput Life Sci. https://doi.org/10.1007/s12539-017-0231-x Kumar V, Van Staden J (2016) A Review of Swertia chirayita (Gentianaceae) as a traditional medicinal. Plant Front Pharmacol 6 https ://doi.org/10.3389/fphar.2015.00308 Legault P, Li J, Mogridge J, Kay LE, Greenblatt J (1998) NMR structure of the bacteriophage λ N peptide/boxB RNA complex: recognition of a GNRA fold by an arginine-Rich Motif. Cell 93:289– 299. https://doi.org/10.1016/S0092-8674(00)81579-2 Li W-S, Jia X-R, Wang B-B, Ji Y, Wei Y (2007) Glycine and l-glutamic acid-based dendritic gelators. Tetrahedron 63:8794–8800. https:// doi.org/10.1016/j.tet.2007.06.028 Lovejoy B et al (1999) Crystal structures of MMP-1 and -13 reveal the structural basis for selectivity of collagenase inhibitors. Nat Struct Biol 6:217–221 Miller BR III, McGee TD Jr, Swails JM, Homeyer N, Gohlke H, Roitberg AE (2012) MMPBSA.py: an efficient program for end-state free energy calculations. J Chem Theory Comput 8:3314–3321. https://doi.org/10.1021/ct300418h Oh HI, Hoff JE, Armstrong GS, Haff LA (1980) Hydrophobic interaction in tannin-protein complexes. J Agric Food Chem 28:394–398. https://doi.org/10.1021/jf60228a020 Park M, Han J, Lee CS, Heung Soo B, Lim K-M, Ha H (2013) Carnosic acid, a phenolic diterpene from rosemary, prevents UVinduced expression of matrix metalloproteinases in human skin fibroblasts and keratinocytes. Exp Dermatol 22:336–341. https:// doi.org/10.1111/exd.12138 Pei S, Yang X, Wang H, Zhang H, Zhou B, Zhang D, Lin D (2015) Plantamajoside, a potential anti-tumor herbal medicine inhibits breast cancer growth and pulmonary metastasis by decreasing the activity of matrix metalloproteinase-9 and -2. BMC Cancer 15:965. https://doi.org/10.1186/s12885-015-1960-z Pérez-Sánchez A, Barrajón-Catalán E, Caturla N, Castillo J, BenaventeGarcía O, Alcaraz M, Micol V (2014) Protective effects of citrus and rosemary extracts on UV-induced damage in skin cell model and human volunteers. J Photochem Photobiol B 136:12–18. https ://doi.org/10.1016/j.jphotobiol.2014.04.007 Roe DR, Cheatham TE (2013) PTRAJ and CPPTRAJ: software for processing and analysis of molecular dynamics trajectory data. J Chem Theory Comput 9:3084–3095. https://doi.org/10.1021/ ct400341p Rudra DS, Pal U, Maiti NC, Reiter RJ, Swarnakar S (2013) Melatonin inhibits matrix metalloproteinase-9 activity by binding to its active site. J Pineal Res 54:398–405. https://doi.org/10.1111/ jpi.12034 Sagar M, Pathak RK, Pandey RK, Singh DB, Pandey N, Gupta MK (2014) Binding affinity analysis and ADMET prediction of epigallocatechine gallate (EGCG) derivatives for AP-1 protein: a drug
International Journal of Peptide Research and Therapeutics target for liver cancer. Netw Model Anal Health Inform Bioinform 3:66. https://doi.org/10.1007/s13721-014-0066-x Segueni N et al (2011) Inhibition of stromelysin-1 by caffeic acid derivatives from a propolis sample from. Algeria Planta Med 77:999–1004. https://doi.org/10.1055/s-0030-1270713 Singh T, Adekoya OA, Jayaram B (2015) Understanding the binding of inhibitors of matrix metalloproteinases by molecular docking, quantum mechanical calculations, molecular dynamics simulations, and a MMGBSA/MMBappl study. Mol Biosyst 11:1041– 1051. https://doi.org/10.1039/C5MB00003C Suryawanshi S, Mehrotra N, Asthana RK, Gupta RC (2006) Liquid chromatography/tandem mass spectrometric study and analysis of xanthone and secoiridoid glycoside composition of Swertia chirata, a potent antidiabetic. Rapid Commun Mass Spectrom 20:3761–3768. https://doi.org/10.1002/rcm.2795 Tedasen A, Choomwattana S, Graidist P, Tipmanee V (2017) Structure-guided cancer blockade between bioactive bursehernin and proteins: molecular docking and molecular dynamics study. J Mol Graph Model 74:215–224. https: //doi.org/10.1016/j. jmgm.2017.04.021 Tochowicz A et al (2007) Crystal structures of MMP-9 complexes with five inhibitors: contribution of the flexible Arg424 side-chain to selectivity. J Mol Biol 371:989–1006. https://doi.org/10.1016/j. jmb.2007.05.068
Wolber G, Langer T (2005) LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters. J Chem Inf Model 45:160–169. https: //doi.org/10.1021/ci049 885e Wongrattanakamon P, Nimmanpipug P, Sirithunyalug B, Jiranusornkul S (2017) Molecular modeling elucidates the cellular mechanism of synaptotagmin-SNARE inhibition: a novel plausible route to anti-wrinkle activity of botox-like cosmetic active molecules. Mol Cell Biochem. https://doi.org/10.1007/s11010-017-3196-5 Yuan H et al (2013) Synthesis of derivatives of methyl rosmarinate and their inhibitory activities against matrix metalloproteinase-1 (MMP-1). Eur J Med Chem 62:148–157. https: //doi.org/10.1016/j. ejmech.2012.09.047 Zhang W, Laursen RA (1998) Structure-function relationships in a type I antifreeze polypeptide. The role of threonine methyl and hydroxyl groups in antifreeze activity. J Biol Chem 273:34806–34812 Zhang C et al (2017) Discovery of novel phosphodiesterase-2A inhibitors by structure-based virtual screening, structural optimization, and bioassay. J Chem Inf Model 57:355–364. https://doi. org/10.1021/acs.jcim.6b00551
13