Two new benzyl dihydroflavones phelligrins A and B were isolated from the fruit body of Phellinus igniarius. Their structrues were identified as 5, 7, 4-trihydroxy-6-O-hydroxybenzyl -dihydroflavone and 5, 7, 4-trihyd...Two new benzyl dihydroflavones phelligrins A and B were isolated from the fruit body of Phellinus igniarius. Their structrues were identified as 5, 7, 4-trihydroxy-6-O-hydroxybenzyl -dihydroflavone and 5, 7, 4-trihydroxy-8-O-hydroxybenzyldihydroflavone, respectively, by means of spectral methods.展开更多
From the bioassay tests, 14 neuraminidase inhibitors （NIs） flavones and dihydroflavones derivatives from natural plants displayed different degree of inhibitory activities. Further- more, compounds No. 8 and 14 show...From the bioassay tests, 14 neuraminidase inhibitors （NIs） flavones and dihydroflavones derivatives from natural plants displayed different degree of inhibitory activities. Further- more, compounds No. 8 and 14 showed good inhibitory activity against influenza A virus with IC50 = 835.4 and 860.6 μg/mL. Then, to investigate interactions between NIs and neuraminidase （NA）, molecular docking was performed. Docking results indicated that Arg118, Asp151, Arg292 and Arg371 were the key residues in the active pocket of 2ht8. Main influencing factors of interactions between NIs and NA were hydrogen bond and electrostatic, then hydrophobic factor. Moreover, experimental activities of NIs were consistent with total scores of the docking. In order to understand the chemical-biological interactions governing their activities toward NA, QSAR models of 14 NIs were developed. The obtained HQSAR （hologram quantitative structure activity relationship）, PLS （partial least squares） and SRA （stepwise regression analysis） models were robust and had good exterior predictive capabilities. Moreover, squared multiple correlation coefficients （R2） and squared cross-validated correlation coefficients （Q2） of HQSAR and PLS models based on descriptors by Gaussian and Sarchitect were 0.832 and 0.721, 0.925 and 0.688, 0.892 and 0.692, respectively. R2 and SE （standard error） of SRA model based on descriptors by Gaussian were 0.922 and 0.072. Therefore, these models may be further used to design and evaluate the bioactivity of new compounds.展开更多
基金The authors are grateful to professor Ablez zeper Institute of Materia Medica,Chinese Academy of Medical Sciences,for mass spectra measurements,and financial support from National“863”program of China(Grant No.2001AA234021).
文摘Two new benzyl dihydroflavones phelligrins A and B were isolated from the fruit body of Phellinus igniarius. Their structrues were identified as 5, 7, 4-trihydroxy-6-O-hydroxybenzyl -dihydroflavone and 5, 7, 4-trihydroxy-8-O-hydroxybenzyldihydroflavone, respectively, by means of spectral methods.
基金supported by the National Natural Science Foundation of China(No.21202110)
文摘From the bioassay tests, 14 neuraminidase inhibitors （NIs） flavones and dihydroflavones derivatives from natural plants displayed different degree of inhibitory activities. Further- more, compounds No. 8 and 14 showed good inhibitory activity against influenza A virus with IC50 = 835.4 and 860.6 μg/mL. Then, to investigate interactions between NIs and neuraminidase （NA）, molecular docking was performed. Docking results indicated that Arg118, Asp151, Arg292 and Arg371 were the key residues in the active pocket of 2ht8. Main influencing factors of interactions between NIs and NA were hydrogen bond and electrostatic, then hydrophobic factor. Moreover, experimental activities of NIs were consistent with total scores of the docking. In order to understand the chemical-biological interactions governing their activities toward NA, QSAR models of 14 NIs were developed. The obtained HQSAR （hologram quantitative structure activity relationship）, PLS （partial least squares） and SRA （stepwise regression analysis） models were robust and had good exterior predictive capabilities. Moreover, squared multiple correlation coefficients （R2） and squared cross-validated correlation coefficients （Q2） of HQSAR and PLS models based on descriptors by Gaussian and Sarchitect were 0.832 and 0.721, 0.925 and 0.688, 0.892 and 0.692, respectively. R2 and SE （standard error） of SRA model based on descriptors by Gaussian were 0.922 and 0.072. Therefore, these models may be further used to design and evaluate the bioactivity of new compounds.
