Author: Liu, Huiqiang ; Li, Ping ; Sun, Hui ; Wang, Xijun ; Chen, Xiangmei ; Yin, Fengting ; Guan, Shihan ; Wang, Mengmeng ; Wang, Yuhang ; Zheng, Ying ; Liu, Chang

ABSTRACTShenhua Tablet (SHT), a Chinese herbal medicine comprising seven crude drugs, is utilized in the treatment of immunoglobulin A nephropathy (IgAN). However, due to its complex composition, the chemical constituents of SHT in vitro are still incompletely known, which has restricted the comprehensive development and utilization of SHT in clinical practice. In the present study based on ultra‐high performance liquid chromatography‐quadrupole‐orbitrap‐linear ion trap mass spectrometry (UHPLC‐Q‐Orbitrap‐LTQ‐MS) in data dependent acquisition mode, combining the accurate mass and structural information, the profiling and characterization of chemical constituents in SHT were carried out. The automated spectral matching (of experimental MS2 spectra against library spectra of mzCloud) method with a high mass accuracy (within 5 ppm) was used for the rapid identification of compounds. A total of 183 compounds, consisting of 64 flavonoids, 52 terpenoids, 37 organic acids, 6 phenylpropanoids, 5 phenols, and 19 other phytochemicals, were successfully characterized. In addition, the fragmentation pathways and characteristic fragments of some representative compounds were elucidated. The results offered clear insights into its chemical profile, thereby facilitating quality control and advancing pharmacological research.

05 Jun 2024·ACS Chemical Neuroscience

Identifying Substructures That Facilitate Compounds to Penetrate the Blood–Brain Barrier via Passive Transport Using Machine Learning Explainer Models

Article

Author: Rosa, Lucca Caiaffa Santos ; Nascimento, Cayque Monteiro Castro ; Pimentel, Andre Silva ; Argolo, Caio Oliveira

The local interpretable model-agnostic explanation (LIME) method was used to interpret two machine learning models of compounds penetrating the blood-brain barrier. The classification models, Random Forest, ExtraTrees, and Deep Residual Network, were trained and validated using the blood-brain barrier penetration dataset, which shows the penetrability of compounds in the blood-brain barrier. LIME was able to create explanations for such penetrability, highlighting the most important substructures of molecules that affect drug penetration in the barrier. The simple and intuitive outputs prove the applicability of this explainable model to interpreting the permeability of compounds across the blood-brain barrier in terms of molecular features. LIME explanations were filtered with a weight equal to or greater than 0.1 to obtain only the most relevant explanations. The results showed several structures that are important for blood-brain barrier penetration. In general, it was found that some compounds with nitrogenous substructures are more likely to permeate the blood-brain barrier. The application of these structural explanations may help the pharmaceutical industry and potential drug synthesis research groups to synthesize active molecules more rationally.

01 Jun 2024·Industrial Crops and Products

Evaluation of lipid and metabolite profiles in tobacco leaves from different plant parts by comprehensive lipidomics and metabolomics analysis

Author: Qin, Lei ; Wu, Han ; Wang, Xusong ; Chai, Ying ; Zhang, Shanlin ; Duan, Xiaojiao ; Hao, Jie ; Huang, Xuhui

Tobacco is an agricultural product with extremely high economic value.Manufacturers have realized that the chem. nature of fresh tobacco leaves influences the flavor properties of tobacco products.To explore the key components that cause the differences in tobacco leaves, high-precision mass spectrometry was employed for multi-omics anal. of three groups (upper, middle, and lower parts) of tobacco leaves.The results showed that the fresh leaves from different parts of Yunyan 87 tobacco plant had significant differences.It was not unique compounds that caused these differences, but more likely variations in shared compoundsThe species of glycerolipids, glycerophospholipids, and fatty acyls were the most numerous, their numbers account for 76.68% of total lipids components.The number of glycerolipids accounted for 70% of the identified key lipid components, with the majority being polyunsaturated glycerolipids.It suggested that the disparities in polyunsaturated glycerolipids were the primary cause of lipids differentiation in fresh leaves from different parts.Glycerolipids are effective storage forms of carbon and energy.Carbohydrates and carbohydrate conjugates are the main products of tobacco photosynthesis.In key components, they had the highest relative abundance in the lower leaves.In addition, terpenoids, and organic oxygen compounds, all exhibit high relative abundances in the lower leaves.Amino acids, peptides, and analogs were more abundant in the upper leaves.Differences in the chem. composition of fresh tobacco will result in different sensory qualities and styles.In addition to providing insights into the differences and diversity of tobacco leaves in various parts of the plant during growth, the results present potentially rewarding information for directional cultivation of tobacco plants, grading of tobacco leaves, and optimization of resource utilization.

100 Deals associated with Levallorphan Tartrate

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