TY - JOUR
T1 - Ligand- and protein-based modeling studies of the inhibitors of human cytochrome P450 2D6 and a virtual screening for potential inhibitors from the Chinese herbal medicine, Scutellaria baicalensis (Huangqin, Baikal Skullcap)
AU - Mo, Sui-Lin
AU - Liu, Wei-Feng
AU - Chen, Yuling
AU - Luo, Hai-Bin
AU - Sun, Lai-Bao
AU - Chen, Xiao-Wu
AU - Zhou, Zhi-Wei
AU - Sneed, Kevin B.
AU - Li, Chun Guang
AU - Du, Yao-Min
AU - Liang, Jun
AU - Zhou, Shu-Feng
PY - 2012
Y1 - 2012
N2 - We have previously examined the binding patterns of various substrates to human cytochrome P450 2D6 (CYP2D6) using a series of molecular modeling methods. In this study, we further explored the binding modes of various types of inhibitors to CYP2D6 using a combination of ligand- and protein-based modeling approaches. Firstly, we developed and validated a pharmacophore model for CYP2D6 inhibitors, which consisted of two hydrophobic features and one hydrogen bond acceptor feature. Secondly, we constructed and validated a quantitative structure-activity relationship (QSAR) model for CYP2D6 inhibitors which gave a poor to moderate prediction accuracy. Thirdly, a panel of CYP2D6 inhibitors were subject to molecular docking into the active site of wild-type and mutated CYP2D6 enzyme. We demonstrated that 8 residues in the active site (Leu213, Glu216, Ser217, Gln244, Asp301, Ser304, Ala305, and Phe483) played an important role in the binding to the inhibitors via hydrogen bond formation and/or π-π stacking interaction. Apparent changes in the binding modes of the inhibitors have been observed with Phe120Ile, Glu216Asp, Asp301Glu mutations in CYP2D6. Finally, we screened for potential binders/inhibitors from the Chinese herbal medicine Scutellaria baicalensis (Huangqin, Baikal Skullcap) using the established pharmacophore model for CYP2D6 inhibitors and molecular docking approach. Overall, 18 out of 40 compounds from S. baicalensis were mapped to the pharmacophore model of CYP2D6 inhibitors and most herbal compounds from S. baicalensis could be docked into the active site of CYP2D6. Our study has provided insights into the molecular mechanisms of interaction of synthetic and herbal compounds with human CYP2D6 and further benchmarking studies are needed to validate our modeling and virtual screening results.
AB - We have previously examined the binding patterns of various substrates to human cytochrome P450 2D6 (CYP2D6) using a series of molecular modeling methods. In this study, we further explored the binding modes of various types of inhibitors to CYP2D6 using a combination of ligand- and protein-based modeling approaches. Firstly, we developed and validated a pharmacophore model for CYP2D6 inhibitors, which consisted of two hydrophobic features and one hydrogen bond acceptor feature. Secondly, we constructed and validated a quantitative structure-activity relationship (QSAR) model for CYP2D6 inhibitors which gave a poor to moderate prediction accuracy. Thirdly, a panel of CYP2D6 inhibitors were subject to molecular docking into the active site of wild-type and mutated CYP2D6 enzyme. We demonstrated that 8 residues in the active site (Leu213, Glu216, Ser217, Gln244, Asp301, Ser304, Ala305, and Phe483) played an important role in the binding to the inhibitors via hydrogen bond formation and/or π-π stacking interaction. Apparent changes in the binding modes of the inhibitors have been observed with Phe120Ile, Glu216Asp, Asp301Glu mutations in CYP2D6. Finally, we screened for potential binders/inhibitors from the Chinese herbal medicine Scutellaria baicalensis (Huangqin, Baikal Skullcap) using the established pharmacophore model for CYP2D6 inhibitors and molecular docking approach. Overall, 18 out of 40 compounds from S. baicalensis were mapped to the pharmacophore model of CYP2D6 inhibitors and most herbal compounds from S. baicalensis could be docked into the active site of CYP2D6. Our study has provided insights into the molecular mechanisms of interaction of synthetic and herbal compounds with human CYP2D6 and further benchmarking studies are needed to validate our modeling and virtual screening results.
UR - http://handle.uws.edu.au:8081/1959.7/528143
M3 - Article
SN - 1386-2073
VL - 15
SP - 36
EP - 80
JO - Combinatorial Chemistry & High Throughput Screening
JF - Combinatorial Chemistry & High Throughput Screening
IS - 1
ER -