Exploring therapeutic targets and drug candidates for obesity: a combined network pharmacology, bioinformatics approach

The remarkably high prevalence of obesity in Saudi Arabia reflects a global epidemic demanding urgent attention due to its associated health risks. The integration of traditional medicine, a vital cultural aspect, involves the use of medicinal plants to address various diseases, including obesity. This research merges network pharmacology (NP) and bioinformatics to innovate obesity treatment by identifying effective phytochemicals from native plants in the Taif valley. Focusing on six indigenous plants-Senna alexandrina, Capsicum annuum, Zingiber officinale, Curcuma longa, Trigonella foenum-graecum, and Foeniculum vulgare-we conducted preliminary screenings for potential bioactive compounds. We systematically compiled compound data from public databases and reviewed literature, revealing active compounds like apigenin, kaempferol, moupinamide, cyclocurcumin, chrysoeriol, isorhamnetin, rheinanthrone, cyclocurcumin, and riboflavin.Constructing a compound-target genes-obesity network unveiled their significant impact on metabolic regulation and fat accumulation, interacting notably with key proteins AKT1 and PTGS2. Molecular docking and 100 ns Molecular Dynamic (MD) simulations demonstrated robust binding affinity and stability at the docking site. Employing adipocytes as a cellular model, we gauged their viability and response to obesity-related stressors post-treatment with these native plant compounds.In conclusion, Saudi Arabia's indigenous plants hold promise as natural solutions for obesity treatment. This research opens new avenues in the battle against this pervasive health crisis by incorporating the potential of native botanicals.Communicated by Ramaswamy H. Sarma.

Therapeutic effects of Crataegus monogyna inhibitors against breast cancer

Breast cancer is a silent killer disorder among women and a serious economic burden in healthcare management. Every 19 s, a woman is diagnosed with breast cancer, and every 74 s, a woman worldwide passes away from the disease. Despite the increase in progressive research, advanced treatment approaches, and preventive measures, breast cancer rates continue to increase. This study provides a combination of data mining, network pharmacology, and docking analysis that surely could revolutionize cancer treatment by exploiting prestigious phytochemicals. Crataegus monogyna is a small, rounded deciduous tree with glossy, deeply lobed leaves and flat sprays of cream flowers, followed by dark red berries in autumn. Various studies demonstrated that C. monogyna is therapeutically effective against breast cancer. However, the particular molecular mechanism is still unknown. This study is credited for locating bioactive substances, metabolic pathways, and target genes for breast cancer treatment. According to the current investigation, which examined compound-target genes-pathway networks, it was found that the bioactive compounds of C. monogyna may operate as a viable solution against breast cancer by altering the target genes implicated in the disease pathogenesis. The expression level of target genes was analyzed using GSE36295 microarray data. Docking analysis and molecular dynamic simulation studies further strengthened the current findings by validating the effective activity of the bioactive compounds against putative target genes. In summary, we propose that six key compounds, luteolin, apigenin, quercetin, kaempferol, ursolic acid, and oleanolic acid, contributed to the development of breast cancer by affecting the MMP9 and PPARG proteins. Integration of network pharmacology and bioinformatics revealed C. monogyna's multitarget pharmacological mechanisms against breast cancer. This study provides convincing evidence that C. monogyna might partially alleviate breast cancer and ultimately lays a foundation for further experimental research on the anti-breast cancer activity of C. monogyna.

Molecular dynamics simulation analysis of the beta amyloid peptide with docked inhibitors

Beta amyloid peptide is widely studied due to its association with Alzheimer disease (AD). Various study reported that the accumulation of beta amyloid in brain cells leads to Alzheimer disease. Hence, Beta amyloid peptide could be a potential target of anti-AD therapy. Hence, it is of interest to develop potent inhibitors for Beta amyloid peptide in the context of Alzheimer disease (AD). We report the binding features of Ascorbic acid, Cysteine, Dithioerythriol, Dithiothreitol, Malic acid and α-Tocopherol with beta amyloid having binding energy values of -6.7, -6.5, -6.0, -6.5, -6.7 and - 7.0 kcal/mol respectively. The molecular docking of top-scoring compounds with beta amyloid suggests that amino acids such as ASP23, GLU22, Phe19, are crucial in binding. Molecular dynamics simulation study showed steady-state interaction of compounds with beta amyloid for further consideration.