Spectrum-effect relationship of immunologic activity of Ganoderma lucidum by UPLC-MS/MS and component knock-out method

Abstract

This study was designed to elucidate the immunoregulation of Ganoderma lucidum. HPLC fingerprint and spectrum-effect relationship of G. lucidum were established to predict the active compounds and BP neural network model was established to predict the efficacy. Then the target compounds were identified by high resolution mass spectrometry. The results indicated that there are both enhanced immunity and immunosuppressive components in G. lucidum. BP neural network was trained with the common peak area and immune efficacy index of G. lucidum fingerprint as samples, and a combined evaluation system of G. lucidum fingerprint efficacy was established. The correlation coefficient R of BP network model was 0.986 43, and the error of pharmacodynamic prediction results was in the ideal range. Eight compounds were identified by high resolution mass spectrometry. The compounds related to immune activity in G. lucidum were determined in this study.

Keywords

• Ganoderma lucidum
• RAW 264.7 cell
• Spectrum-effect relationships
• Component knock-out
• BP neural network