Brief literature review and comprehensive bioinformatics analytics unravel the potential mechanism of curcumin in the treatment of periodontitis.

OBJECTIVE: Periodontitis is a chronic oral disease prevalent worldwide, and natural products are recommended as adjunctive therapy due to their minor side effects. Curcumin, a widely used ancient compound, has been reported to possess therapeutic effects in periodontitis. However, the exact mechanism underlying its activity remains unclear. In this context, the present study aimed to conduct computational simulations to uncover the potential mechanism of action of Curcumin in the treatment of periodontitis. MATERIALS AND METHODS: Single-cell analysis was conducted using a dataset (i.e., GSE164241) curated from the Gene Expression Omnibus (GEO) database through an R package "Seurat package." Bulk RNA sequencing data were curated from GSE10334 and GSE16134 and processed by R package "Limma." Then, the marker genes in the single-cell transcriptome and differentially expressed genes (DEGs) in the bulk transcriptome were integrated. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were also carried out to reveal their functionalities. Key targets were mined from their protein-protein interaction (PPI) network topologically. Afterward, molecular docking was performed. The top-ranked pose was subjected to molecular dynamics simulations to investigate the stability of the docking result. RESULTS: FOS, CXCL1, CXCL8, and IL1B, were filtered after a series of selected processes. The results of molecular modeling suggested that except for IL1B, the Vena Scores of the rest exceeded -5 kcal/mol. Furthermore, the molecular dynamic simulation indicated that the binding of the CXCL8-Curcumin complex was stable over the entire 100 ns simulation. CONCLUSION: The present study unlocked the binding modes of CXCL1, FOS, and CXCL8 with the Curcumin molecule, which were relatively stable, especially for CXCL8, hindering its promising potential to serve as the critical targets of Curcumin in periodontitis treatment.

Mechanistic insight of the potential of geraniol against Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) as a neurodegenerative disease occupies 3/5-4/5 cases among patients with dementia, yet its pathogenetic mechanism remains unclear. Geraniol, on the other hand, is a well-known extract from essential oils of aromatic plants and has been proven that it has outstanding neuroprotective effects as well as ameliorating influence in memory impairment. Therefore, the present study aims to elucidate the potential of geraniol against AD by network pharmacology-based approach combined with molecular modeling study. MATERIALS AND METHODS: Firstly, we evaluated the druggability of geraniol by ADME method. Then, we obtained the geraniol targets and AD-related targets from multiple open data sources. Afterward, we calculated the intersection through a Venn diagram to find common targets, and via Panther classification system to categorize them. In order to gain a macroscopic understanding of these common targets, we carried out GO terms and KEGG pathways enrichment analyses, according to which we constructed a compound-target-pathway-disease network. In addition, we built a preliminary PPI network which was further analyzed both functionally and topologically. Consequently, five hub targets were sorted out. Finally, we conducted molecular docking and molecular dynamic simulation to validate our findings. RESULTS: In the present study, the pharmacological properties of geraniol were assessed according to ADME and Lipinski's rule, which demonstrate promising druggability. Then, from 10,972 AD-related targets and 33 geraniol targets, 29 common targets were identified, among which 38.1% of them are metabolite interconversion enzymes, 23.8% are protein modifying enzymes, 33.3% are transmembrane receptors, and the rest are transporters. Enrichment analyses hint that geraniol is involved in cholinergic synapse, serotonergic synapse, and neuroactive ligand-receptor interaction. We also built a preliminary PPI network to investigate the interplay between these targets and their extensive interactions. Then, by functionally clustering the preliminary PPI network, we gained a cluster of proteins which formed a subnetwork with score of 8.476, and 22 nodes. Its results of GO terms and KEGG pathways enrichment analyses once again suggests that geraniol actively participates in cholinergic synapse, serotonergic synapse, and neuroactive ligand-receptor interaction, which are believed to be strongly associated with AD pathogenesis. Besides, topological analyses of the preliminary PPI network helped find 5 hub targets (i.e., CHRM3, PRKCA, PRKCD, JAK1, JAK2). To verify their interaction with geraniol molecule, we conducted molecular docking, and found that CHRM3 possesses the highest affinity in binding, indicating that geraniol molecules are closely bound to each hub target, and CHRM3 may serve as a key target of geraniol against AD. It was then further confirmed by molecular dynamic simulation, the result of which supports our hypothesis. CONCLUSION: The present study shares a mechanistic insight of the potential of geraniol against AD, giving a reference to future experimental studies.

Network Pharmacology-Based Approach Combined with Bioinformatic Analytics to Elucidate the Potential of Curcumol against Hepatocellular Carcinoma.

PURPOSE: Modern, open-source databases provide an unprecedented wealth of information to help drug development. By combining data available in these databases with the proper bioinformatical tools, we can elucidate the molecular targets of natural compounds. One such molecule is curcumol, a guaiane-type sesquiterpenoid hemiketal isolated from Rhizoma Curcumae, which is used for a broad range of diseases in traditional Chinese and Indian medicine. It has been reported to exert anti-tumor activity, but the intrinsic molecular mechanism in hepatocellular carcinoma (HCC) is unclear. Therefore, the present study was designed to reveal the predictive targets and biological mechanisms of curcumol against HCC via a network pharmacology-based approach combined with bioinformatic analytics and to provide proof of concept for further similar investigations. METHODS: Data available from open-source databases (Traditional Chinese Medicine Systems Pharmacology, Comparative Toxicogenomic Database, The Cancer Genome Atlas, the Human Protein Atlas project) was processed with the help of a variety of open-source tools (SwissADME, SwissTargetPrediction, JVenn, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, GeneMANIA, Cytoscape). RESULTS: In the present study, the potential of curcumol against HCC was unraveled by network pharmacology-based elucidation. It suggests that curcumol shows exciting druggability with 44 potent homo sapiens biotargets against HCC. The GO terms and KEGG pathways enrichment analyses, curcumol-targets-pathways-HCC network, PPI network, and corresponding in-depth topological analyses, as well as survival analysis, molecular docking simulation indicate that the potential mechanism of curcumol against HCC is complicated, as it may act in various ways, mainly by inducing apoptosis and modulating the inflammatory response, increasing presentation of HCC-specific protein. CONCLUSION: The present study highlights the potential of curcumol against HCC, giving reference to further experimental study. It also presents a roadmap that can be followed to conduct in silico prescreening of other compounds of interest.