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Exploration of natural product ingredients as inhibitors of human HMG-CoA reductase through structure-based virtual screening.

Lin SH, Huang KJ, Weng CF, Shiuan D - Drug Des Devel Ther (2015)

Bottom Line: HMG-CoA (3-hydroxy-3-methylglutaryl coenzyme A) reductase is the key enzyme in the cholesterol biosynthesis pathway, and the statin-like drugs are inhibitors of human HMG-CoA reductase (hHMGR).The results indicated that curcumin and salvianolic acid C can effectively inhibit hHMGR, with IC50 (half maximal inhibitory concentration) values of 4.3 µM and 8 µM, respectively.The present study also demonstrated the feasibility of discovering new drug candidates through structure-based virtual screening.

View Article: PubMed Central - PubMed

Affiliation: Department of Life Science and Institute of Biotechnology, National Dong Hwa University, Hualien, Taiwan, Republic of China.

ABSTRACT
Cholesterol plays an important role in living cells. However, a very high level of cholesterol may lead to atherosclerosis. HMG-CoA (3-hydroxy-3-methylglutaryl coenzyme A) reductase is the key enzyme in the cholesterol biosynthesis pathway, and the statin-like drugs are inhibitors of human HMG-CoA reductase (hHMGR). The present study aimed to virtually screen for potential hHMGR inhibitors from natural product to discover hypolipidemic drug candidates with fewer side effects and lesser toxicities. We used the 3D structure 1HWK from the PDB (Protein Data Bank) database of hHMGR as the target to screen for the strongly bound compounds from the traditional Chinese medicine database. Many interesting molecules including polyphenolic compounds, polisubstituted heterocyclics, and linear lipophilic alcohols were identified and their ADMET (absorption, disrtibution, metabolism, excretion, toxicity) properties were predicted. Finally, four compounds were obtained for the in vitro validation experiments. The results indicated that curcumin and salvianolic acid C can effectively inhibit hHMGR, with IC50 (half maximal inhibitory concentration) values of 4.3 µM and 8 µM, respectively. The present study also demonstrated the feasibility of discovering new drug candidates through structure-based virtual screening.

No MeSH data available.


Related in: MedlinePlus

The 2D structures of the selected top ten compounds.Abbreviation: 2D, two dimensional.
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f3-dddt-9-3313: The 2D structures of the selected top ten compounds.Abbreviation: 2D, two dimensional.

Mentions: Since one of the primary factors that cause drug attrition is the poor ADMET properties, the 278 compounds with higher docking scores were evaluated in silico using the DSSTox and the ADMET prediction tools of DS 3.5. These predictions were based on certain animal and cell models and the results serve as a good reference before performing further experiments. Surprisingly, among the 278 compounds, only 51 compounds received favorable ADMET characteristics, indicating that they are both nonmutagenic and noncarcinogenic (data not shown, Table S1). Taking together the ADMET predictions and –PMF scores, ten compounds were chosen for further analysis. The ten compounds include: 1) Sal C, 2) quercetin-3-O-(6′-malonyl) glucoside, 3) curcumin, 4) ampelopsisin, 5) epigallocatechin-3-gallate, 6) Z-ligustilide-SG1a, 7) tenellin, 8) docosanol, 9) tetracosanol, and 10) folic acid. As shown in Table 2, they have similar molecular weights (MWs), but their –PMF scores span a wide range (from 70 up to 146), and their physicochemical properties are varied. The ADMET predictions of the ten selected compounds and the six statin molecules have been included in the supplementary materials. Quite different from the statins which carry a side chain similar to HMG-CoA, the ten compounds display a wide spectrum of structural features (Figure 3). Among them, compounds 1–5 possess polyphenolic moieties; compounds 1, 2, 6, and 10 are carboxylic acids with various heterocyclic branches. Policosanols, the long-chain alcohols, such as compounds 8 and 9 are also included.


Exploration of natural product ingredients as inhibitors of human HMG-CoA reductase through structure-based virtual screening.

Lin SH, Huang KJ, Weng CF, Shiuan D - Drug Des Devel Ther (2015)

The 2D structures of the selected top ten compounds.Abbreviation: 2D, two dimensional.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4492635&req=5

f3-dddt-9-3313: The 2D structures of the selected top ten compounds.Abbreviation: 2D, two dimensional.
Mentions: Since one of the primary factors that cause drug attrition is the poor ADMET properties, the 278 compounds with higher docking scores were evaluated in silico using the DSSTox and the ADMET prediction tools of DS 3.5. These predictions were based on certain animal and cell models and the results serve as a good reference before performing further experiments. Surprisingly, among the 278 compounds, only 51 compounds received favorable ADMET characteristics, indicating that they are both nonmutagenic and noncarcinogenic (data not shown, Table S1). Taking together the ADMET predictions and –PMF scores, ten compounds were chosen for further analysis. The ten compounds include: 1) Sal C, 2) quercetin-3-O-(6′-malonyl) glucoside, 3) curcumin, 4) ampelopsisin, 5) epigallocatechin-3-gallate, 6) Z-ligustilide-SG1a, 7) tenellin, 8) docosanol, 9) tetracosanol, and 10) folic acid. As shown in Table 2, they have similar molecular weights (MWs), but their –PMF scores span a wide range (from 70 up to 146), and their physicochemical properties are varied. The ADMET predictions of the ten selected compounds and the six statin molecules have been included in the supplementary materials. Quite different from the statins which carry a side chain similar to HMG-CoA, the ten compounds display a wide spectrum of structural features (Figure 3). Among them, compounds 1–5 possess polyphenolic moieties; compounds 1, 2, 6, and 10 are carboxylic acids with various heterocyclic branches. Policosanols, the long-chain alcohols, such as compounds 8 and 9 are also included.

Bottom Line: HMG-CoA (3-hydroxy-3-methylglutaryl coenzyme A) reductase is the key enzyme in the cholesterol biosynthesis pathway, and the statin-like drugs are inhibitors of human HMG-CoA reductase (hHMGR).The results indicated that curcumin and salvianolic acid C can effectively inhibit hHMGR, with IC50 (half maximal inhibitory concentration) values of 4.3 µM and 8 µM, respectively.The present study also demonstrated the feasibility of discovering new drug candidates through structure-based virtual screening.

View Article: PubMed Central - PubMed

Affiliation: Department of Life Science and Institute of Biotechnology, National Dong Hwa University, Hualien, Taiwan, Republic of China.

ABSTRACT
Cholesterol plays an important role in living cells. However, a very high level of cholesterol may lead to atherosclerosis. HMG-CoA (3-hydroxy-3-methylglutaryl coenzyme A) reductase is the key enzyme in the cholesterol biosynthesis pathway, and the statin-like drugs are inhibitors of human HMG-CoA reductase (hHMGR). The present study aimed to virtually screen for potential hHMGR inhibitors from natural product to discover hypolipidemic drug candidates with fewer side effects and lesser toxicities. We used the 3D structure 1HWK from the PDB (Protein Data Bank) database of hHMGR as the target to screen for the strongly bound compounds from the traditional Chinese medicine database. Many interesting molecules including polyphenolic compounds, polisubstituted heterocyclics, and linear lipophilic alcohols were identified and their ADMET (absorption, disrtibution, metabolism, excretion, toxicity) properties were predicted. Finally, four compounds were obtained for the in vitro validation experiments. The results indicated that curcumin and salvianolic acid C can effectively inhibit hHMGR, with IC50 (half maximal inhibitory concentration) values of 4.3 µM and 8 µM, respectively. The present study also demonstrated the feasibility of discovering new drug candidates through structure-based virtual screening.

No MeSH data available.


Related in: MedlinePlus