Research Keyword: systems pharmacology

The molecular mechanisms through which psilocybin prevents suicide: evidence from network pharmacology and molecular docking analyses

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Researchers used computer-based analysis to understand how psilocybin, a compound found in certain mushrooms, might help prevent suicide. They identified four key proteins that psilocybin interacts with and found that it works through serotonin and calcium signaling pathways in the brain, which are known to be involved in depression and suicidal behavior. While these findings are promising, more research is needed to confirm these effects in humans before psilocybin can be used clinically for suicide prevention.

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Screening of active components of Ganoderma lucidum and decipher its molecular mechanism to improve learning and memory disorders

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Researchers used computer analysis and laboratory experiments to understand how a medicinal mushroom called Ganoderma lucidum (reishi) helps improve memory and learning problems. They identified ten key active ingredients in the mushroom that work together to reduce inflammation in the brain and protect nerve cells. The most important ingredient appears to be a compound called β-sitosterol, which helps prevent memory loss similar to effects seen in Alzheimer’s disease.

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Synergistic target network construction and dynamic simulation analysis based on a prospective systems pharmacology strategy

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Researchers used computer-based methods to study how Sang Huang, a traditional medicinal fungus, might help treat type 2 diabetes. They identified 17 active compounds in the fungus and found that a key component called estradiol dipropionate could improve insulin sensitivity and glucose control by activating specific protein pathways. The study suggests Sang Huang could be a promising natural treatment for diabetes, though more laboratory and animal testing is needed.

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