Benzosuberene-sulfone analogues synthesis from Cedrus deodara oil and their therapeutic evaluation by computational analysis to treat type 2 diabetes

Active components and molecular mechanisms of Sagacious Confucius' Pillow Elixir to treat cognitive impairment based on systems pharmacology

BACKGROUND

Sagacious Confucius' Pillow Elixir (SCPE) is a common clinical prescription to treat cognitive impairment (CI) in East Asia.

OBJECTIVE

To predict the active components of SCPE, identify the associated signaling pathway, and explore the molecular mechanism using systems pharmacology and an animal study.

METHODS

Systems pharmacology and Python programming language-based molecular docking were used to select and analyze the active components and targets. Senescence-accelerated prone 8 mice were used as a CI model. The molecular mechanism was evaluated using the water maze test, neuropathological observation, cerebrospinal fluid microdialysis, and Western blotting.

RESULTS

Thirty active components were revealed by screening relevant databases and performing topological analysis. Additionally, 376 differentially expressed genes for CI were identified. Pathway enrichment analysis, protein-protein interaction (PPI) network analysis and molecular docking indicated that SCPE played a crucial role in modulating the PI3K/Akt/mTOR signaling pathway, and 23 SCPE components interacted with it. In the CI model, SCPE improved cognitive function, increased the levels of the neurotransmitter 5-hydroxytryptamine (5-HT) and metabolite 5-hydroxyindole acetic acid (5-HIAA), ameliorated pathological damage and regulated the PI3K/AKT/mTOR signaling pathway. SCPE increased the LC3-II/LC3-I, p-PI3K p85/PI3K p85, p-AKT/AKT, and p-mTOR/mTOR protein expression ratios and inhibited P62 expression in the hippocampal tissue of the CI model.

CONCLUSION

Our study revealed that 23 active SCPE components improve CI by increasing the levels of the neurotransmitter 5-HT and metabolite 5-HIAA, suppressing pathological injury and regulating the PI3K/Akt/mTOR signaling pathway to improve cognitive function.

Molecular modeling and dynamics studies of the synthetic small molecule agonists with GPR17 and P2Y1 receptor

The human Guanine Protein coupled membrane Receptor 17 (hGPR17), an orphan receptor that activates uracil nucleotides and cysteinyl leukotrienes is considered as a crucial target for the neurodegenerative diseases. Yet, the detailed molecular interaction of potential synthetic ligands of GPR17 needs to be characterized. Here, we have studied a comparative analysis on the interaction specificity of GPR17-ligands with hGPR17 and human purinergic G protein-coupled receptor (hP2Y1) receptors. Previously, we have simulated the interaction stability of synthetic ligands such as T0510.3657, AC1MLNKK, and MDL29951 with hGPR17 and hP2Y1 receptor in the lipid environment. In the present work, we have comparatively studied the protein-ligand interaction of hGPR17-T0510.3657 and P2Y1-MRS2500. Sequence analysis and structural superimposition of hGPR17 and hP2Y1 receptor revealed the similarities in the structural arrangement with the local backbone root mean square deviation (RMSD) value of 1.16 Å and global backbone RMSD value of 5.30 Å. The comparative receptor-ligand interaction analysis between hGPR17 and hP2Y1 receptor exposed the distinct binding sites in terms of geometrical properties. Further, the molecular docking of T0510.3657 with the hP2Y1 receptor have shown non-specific interaction. The experimental validation also revealed that Gi-coupled activation of GPR17 by specific ligands leads to the adenylyl cyclase inhibition, while there is no inhibition upon hP2Y1 activation. Overall, the above findings suggest that T0510.3657-GPR17 binding specificity could be further explored for the treatment of numerous neuronal diseases. Communicated by Ramaswamy H. Sarma.

Comprehensive Network Analysis Reveals the Targets and Potential Multitarget Drugs of Type 2 Diabetes Mellitus

Type 2 diabetes mellitus (T2DM) is a metabolic disease with increasing prevalence and mortality year by year. The purpose of this study was to explore new therapeutic targets and candidate drugs for multitargets by single-cell RNA expression profile analysis, network pharmacology, and molecular docking. Single-cell RNA expression profiling of islet β cell samples between T2DM patients and nondiabetic controls was conducted to identify important subpopulations and the marker genes. The potential therapeutic targets of T2DM were identified by the overlap analysis of insulin-related genes and diabetes-related genes, the construction of protein-protein interaction network, and the molecular complex detection (MCODE) algorithm. The network distance method was employed to determine the potential drugs of the target. Molecular docking and molecular dynamic simulations were carried out using AutoDock Vina and Gromacs2019, respectively. Eleven cell clusters were identified by single-cell RNA sequencing (scRNA-seq) data, and three of them (C2, C8, and C10) showed significant differences between T2DM samples and normal samples. Eight genes from differential cell clusters were found from differential cell clusters to be associated with insulin activity and T2DM. The MCODE algorithm built six key subnetworks, with five of them correlating with inflammatory pathways and immune cell infiltration. Importantly, CCR5 was a gene within the key subnetworks and was differentially expressed between normal samples and T2DM samples, with the highest area under the ROC curve (AUC) of 82.5% for the diagnosis model. A total of 49 CCR5-related genes were screened, and DB05494 was identified as the most potential drug with the shortest distance to CCR5-related genes. Molecular docking illustrated that DB05494 stably bound with CCR5 (-8.0 kcal/mol) through multiple hydrogen bonds (LYS26, TYR37, TYR89, CYS178, and GLN280) and hydrophobic bonds (TRP86, PHE112, ILE198, TRP248, and TYR251). This study identified CCR5 as a potential therapeutic target and screened DB05494 as a potential drug for T2DM treatment.