Identification of chemical constituents in Naozhenning granule by UHPLC coupled with hybrid quadrupole-orbitrap MS / 药学学报

Naozhenning granule, which is composed of 11 herbal drugs, is mainly used in the treatment of concussion, cerebral post-traumatic syndrome. As the chemical composition of Naozhenning was complex, the ultrahigh performance liquid chromatography coupled with hybrid quadrupole-orbitrap mass spectrometry was applied to identify the chemical constituents rapidly in the Naozhenning granule. By analyzing the retention behaviors, accurate molecular weight, the fragmentation pathway, and comparison with the MS data from the standards and references, as well as the automatic identification by the Compound Discover 2.0, a total of 161 compounds were identified or tentatively deduced, and the sources of constituents were also confirmed. The compounds identified in Naozhenning granule included 9 iridoids, 8 butylphthalides, 26 flavonoids and flavonoid glycosides, 8 phenolic acids, 8 monoterpenoid glycosides and 9 alkaloids, as well as the common compounds in the herbal drugs, such as organic acids, amino acids, and sugars. The chemical composition of Naozhenning was studied for the first time, which provides a scientific basis for the quality control and document of effective materials of Naozhenning granule.

Using diffusion distances for flexible molecular shape comparison.

BACKGROUND: Many molecules are flexible and undergo significant shape deformation as part of their function, and yet most existing molecular shape comparison (MSC) methods treat them as rigid bodies, which may lead to incorrect shape recognition. RESULTS: In this paper, we present a new shape descriptor, named Diffusion Distance Shape Descriptor (DDSD), for comparing 3D shapes of flexible molecules. The diffusion distance in our work is considered as an average length of paths connecting two landmark points on the molecular shape in a sense of inner distances. The diffusion distance is robust to flexible shape deformation, in particular to topological changes, and it reflects well the molecular structure and deformation without explicit decomposition. Our DDSD is stored as a histogram which is a probability distribution of diffusion distances between all sample point pairs on the molecular surface. Finally, the problem of flexible MSC is reduced to comparison of DDSD histograms. CONCLUSIONS: We illustrate that DDSD is insensitive to shape deformation of flexible molecules and more effective at capturing molecular structures than traditional shape descriptors. The presented algorithm is robust and does not require any prior knowledge of the flexible regions.