Chronic obstructive pulmonary disease (COPD) is a chronic obstructive lung disease and is frequently found in well-developed countries due to the issue of aging populations. Not all forms of medical treatment are unable to return a patient's limited pulmonary function back to normal and eventually they could require a lung transplant. At this time, COPD is the leading cause of death in the world. Studies surveying I-kappa-B-kinase beta (IKK2) are very relevant to the occurrence and deterioration of the condition COPD. The sinapic acid-4-O-sulfate, kaempferol, and alpha-terpineol were found to be IKK2 inhibitors and helped prevent COPD occurrence and worsening according to a screening of the traditional Chinese medicine (TCM) database. The protein-ligand interaction of these three compounds with regard to IKK2 was also done by molecular dynamics. The docking poses, hydrogen bond variation, and hydrophobic interactions found Asp103 and Lys106 are crucial to IKK2 binding areas for IKK2 inhibition. Finally, we found the three compounds that have an equally strong effect in terms of IKK2 binding proven by the TCM database and perhaps these may be an alternative treatment for COPD in the future.
COPD, a chronic obstructive pulmonary disease, can lead to the restriction of lung function [
IKK2 activation is related to many inflammatory diseases, severe immune compromise diseases [
Utilizing a computational simulation technique could efficiently help identify suitable drugs for IKK2 inhibition through the use of computer-aided drug design (CADD) which can help to structure the best drug candidates and predict biological activity. CADD is a very efficient way to treat any specific disease with appropriate drugs targeting [
Traditional Chinese medicine (TCM) has been used in China, Taiwan, Korea, and Japan for thousands of years. The largest traditional Chinese medicine database thus far is the TCM Database@Taiwan (
Based on recent study, a possible lead compound for COPD treatment has been identified by the TCM Database@Taiwan in this study. The docking screening of selected COPD ligands is done by utilizing computational techniques and confirming the molecular dynamics (MD) for protein-ligand interactions affected the most regarding IKK2 inhibitions in COPD.
Molecular simulations were performed by Accelrys Discovery Studio 2.5 (DS 2.5) system. There were 61,000 TCM compounds downloaded from TCM database (
LigandFit [
Disorder region was predicted according to protein structure and docking site by the Database of Protein Disorder (DisProt,
The surveyed ligands prepared for further MD simulation were supported by SwissParam (
The top 3 TCM compounds were selected (Table
Scoring functions of top high ranking candidates from docking results.
Name | Dock Score | -PLP1 | -PLP2 | -PMF |
---|---|---|---|---|
Sinapic acid-4-O-sulfate | 189.61 | 62 | 60.93 | 48.9 |
Kaempferol | 174.852 | 54 | 47.17 | 44.31 |
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157.438 | 39 | 33.49 | 25.96 |
Geranial | 150.458 | 42 | 43.71 | 22.91 |
3-(2-Carboxyphenyl)-4(3H)-quinazolinone | 147.919 | 54 | 46.9 | 33.24 |
Arctigenin | 145.065 | 71 | 72.46 | 85.33 |
Notoginsenoside G | 143.481 | 54 | 49.1 | 38.14 |
*Staurosporine |
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The candidate compounds and control structure were selected after screening the TCM database (Figure
The scaffold of top three TCM compounds and control: (a) sinapic acid-4-O-sulfate (b), kaempferol (c), alpha-terpineol (d), and staurosporine.
The ligands and poses of docking site for IKK2 and its docking site crystal structure: (a) sinapic acid-4-O-sulfate, (b) kaempferol, (c) alpha-terpineol, and (d) staurosporine.
The Ligplot plus [
Protein-ligand interactions by Ligplot plus: (a) sinapic acid-4-O-sulfate, (b) kaempferol, (c) alpha-terpineol, and (d) staurosporine. The high frequency hydrophobic interactions, ligands’ interactions, were showed by deep red color spots.
There were important amino acids nearby the docking site for IKK2 docking which include the Asp103, Leu21, Cys99, Glu149, Val29, Ile165, Val152, Gly102, and Gly22. They were considered as active ATP binding sites in IKK2. Staurosporine can inhibit IKK2 by these regions through the binding of targets and as a reference to other compounds. Disorder prediction shows that the binding residues 21 to 165 are all located in ordered region below 0.5 disorder disposition as showed in Figure
PONDR-FIT prediction of IKK2 active binding domain, value of disorder disposition below 0.5 indicated order residues.
The trajectory of protein-ligand complexes were calculated during MD simulation (Figure
Trajectories of (a) complex RMSD, (b) SASA, and (c) gyrate.
In stability analysis of each residue on the binding region over MD simulation, the major binding regions are located on 21 to 149 residues (Figure
The variation of staurosporine and IKK2 complex in RMSF MD simulation: (a) sinapic acid-4-O-sulfate, (b) kaempferol, (c) alpha-terpineol, and (d) staurosporine.
The MD simulation showed the binding energy variation of top three compounds and control to IKK2 complex: (a) sinapic acid-4-O-sulfate, (b) kaempferol, (c) alpha-terpineol, and (d) staurosporine.
We calculated distance for pair of each residue during all simulation time; there is no significant difference between all protein-ligand complexes, indicating that complexes remain stable during the simulation time (Figure
The residue index of bindings distances change: (a) sinapic acid-4-O-sulfate, (b) kaempferol, (c) alpha-terpineol, and (d) staurosporine.
The variation of secondary structural changes during binding process showed by MD simulation of top candidates to IKK2: (a) sinapic acid-4-O-sulfate and (b) kaempferol.
The variation of secondary structural changes during binding process showed by MD simulation of top candidate and control to IKK2: (c) alpha-terpineol and (d) staurosporine.
In addition, the distance of H-bond affecting the occupancy of H-bond was also calculated during MD (Table
H-bond occupancy among all MD simulations.
Compound name | Atoms of H-bonds | Occupancy | Compound name | Atoms of H-bonds | Occupancy |
---|---|---|---|---|---|
Sinapic acid-4-O-sulfate | O14:LIG—NZ:LYS106 | 10.76% | Kaempferol | HZ3:LYS106—O14:LIG | 18.33% |
HZ3:LYS106—O15:LIG | 42.23% | HZ3:LYS106—O15:LIG | 59.76% | ||
O7:LIG—N:GLY22 | 0.40% | HN:ASP103—O15:LIG | 48.21% | ||
HN:GLY22—O17:LIG | 0.40% | HH:TYR98—O14:LIG | 59.36% | ||
O18:LIG—N:GLY22 | 5.58% | H27:LIG—O:LEU21 | 23.51% | ||
HN:GLY22—O20:LIG | 12.35% | H27:LIG—OD1:ASP103 | 74.90% | ||
— | — | H27:LIG—OD2:ASP103 | 47.01% | ||
— | — | H27:LIG—OE2:GLU149 | 9.16% | ||
— | — | H27:LIG—O:GLU149 | 14.34% | ||
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HG1:THR23—O13:LIG | 29.48% | Staurosporine | O25:LIG—N:THR23 | 0.00% |
HG1:THR23—O14:LIG | 51.00% | HN:THR23—O1:LIG | 59.36% | ||
HH22:ARG20—O13:LIG | 63.35% | O:GLU97—O6:LIG | 0.00% | ||
HH22:ARG20—O14:LIG | 54.58% | — | — | ||
HH12:ARG20—O13:LIG | 55.38% | — | — | ||
HH12:ARG20—O14:LIG | 47.01% | — | — | ||
HE:ARG20—O13:LIG | 2.79% | — | — | ||
HE:ARG20—O14:LIG | 4.38% | — | — | ||
H30:LIG—OD1:ASP103 | 3.98% | — | — | ||
H30:LIG—OD2:ASP103 | 3.19% | — | — | ||
H22:LIG—OE1:GLU149 | 15.54% | — | — | ||
H22:LIG—OE2:GLU149 | 16.33% | — | — |
After that, we clustered all MD structures using linkage algorithm to identify represented conformation for interaction analysis. All MD frames of four complexes with docked ligand were clustered to different groups (Figure
Time of middle frames in each cluster.
Cluster | Time of middle frame (ps) | |||
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Sinapic acid-4-O-sulfate | Kaempferol |
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Staurosporine | |
1 | 200 | 0 | 0 | 0 |
2 | 380 | 20 | 780 | 20 |
3 | 1900 | 140 | 2840 | 520 |
4 | — | 1320 | 4940 | 1280 |
5 | — | 3620 | — | 2460 |
6 | — | 4920 | — | 3140 |
7 | — | — | — | 3960 |
8 | — | — | — | 3540 |
Further clustering analysis of the hit component for further IKK2 binding MD survey.
Snapshots of initial conformation and represented structures: (a) sinapic acid-4-O-sulfate, (b) kaempferol, (c) alpha-terpineol, and (d) staurosporine.
For docking pose of kaempferol in Figure
Prediction of ligand channels of the hit component during MD simulation.
By TCM targeting IKK2 when drug screening, we found the three compounds from Chinese medicine to treat the COPD and believe that this may help clinicians select potent medicine to prevent patients from having COPD in the future or to assist in the area of disease control for COPD. This identification method can also be useful for many other infectious or inflammatory diseases in terms of selecting the proper drugs for difficult treating diseases.
Based on the above discussion, we identified the top 3 TCM compounds, sinapic acid-4-O-sulfate, kaempferol, and alpha-terpineol, which can have an effect on IKK2 inhibition and prevent exacerbation and disease progression with regards to COPD. Asp103, Leu21, Cys99, Glu149, Cal29, Val152, Gly22, and Gly102 108 present their crucial effect on IKK2 inhibition through H-bond formation and hydrophobic interaction. The Asp103 and Lys106 are very important residues in IKK2 binding. These top three compounds can bind to the IKK2 ATP binding site and cause IKK2 inhibition by phosphorylation and may be used in future considerations in the development of novel therapies for COPD.
The authors reaffirm that there is no conflict of interests to declare.
Yung-An Tsou, Hung-Jin Huang, and Wesley Wen-Yang Lin contributed equally to this paper.
The research was supported by grants from the National Science Council of Taiwan (NSC102-2325-B039-001, NSC102-2221-E-468-027, and NSC101-2314-B-039-013-MY3), from Asia University (ASIA100-CMU-2, ASIA101-CMU-2, and 102-ASIA-07), and from China Medical University Hospital (DMR-102-003, DMR-103-025, DMR-103-058, DMR-103-001, and DMR-103-096). This study is also supported in part by Taiwan Department of Health Clinical Trial and Research Center of Excellence (DOH102-TD-B-111-004) and Taiwan Department of Health Cancer Research Center of Excellence (MOHW103-TD-B-111-03), and CMU under the Aim for Top University Plan of the Ministry of Education, Taiwan.