The Potentiality of Natural Products and Herbal Medicine as Novel Medications for Parkinson's Disease: A Promising Therapeutic Approach.

As the global population ages, the prevalence of Parkinson's disease (PD) is steadily on the rise. PD demonstrates chronic and progressive characteristics, and many cases can transition into dementia. This increases societal and economic burdens, emphasizing the need to find effective treatments. Among the widely recognized causes of PD is the abnormal accumulation of proteins, and autophagy dysfunction accelerates this accumulation. The resultant Lewy bodies are also commonly found in Alzheimer's disease patients, suggesting an increased potential for the onset of dementia. Additionally, the production of free radicals due to mitochondrial dysfunction contributes to neuronal damage and degeneration. The activation of astrocytes and the M1 phenotype of microglia promote damage to dopamine neurons. The drugs currently used for PD only delay the clinical progression and exacerbation of the disease without targeting its root cause, and come with various side effects. Thus, there is a demand for treatments with fewer side effects, with much potential offered by natural products. In this study, we reviewed a total of 14 articles related to herbal medicines and natural products and investigated their relevance to possible PD treatment. The results showed that the reviewed herbal medicines and natural products are effective against lysosomal disorder, mitochondrial dysfunction, and inflammation, key mechanisms underlying PD. Therefore, natural products and herbal medicines can reduce neurotoxicity and might improve both motor and non-motor symptoms associated with PD. Furthermore, these products, with their multi-target effects, enhance bioavailability, inhibit antibiotic resistance, and might additionally eliminate side effects, making them good alternative therapies for PD treatment.

LC-MS/MS Software for Screening Unknown Erectile Dysfunction Drugs and Analogues: Artificial Neural Network Classification, Peak-Count Scoring, Simple Similarity Search, and Hybrid Similarity Search Algorithms.

Screening and identifying unknown erectile dysfunction (ED) drugs and analogues, which are often illicitly added to health supplements, is a challenging analytical task. The analytical technique most commonly used for this purpose, liquid chromatography-tandem mass spectrometry (LC-MS/MS), is based on the strategy of searching the LC-MS/MS spectra of target compounds against database spectra. However, such a strategy cannot be applied to unknown ED drugs and analogues. To overcome this dilemma, we have constructed a standalone software named AI-SIDA (artificial intelligence screener of illicit drugs and analogues). AI-SIDA consists of three layers: LC-MS/MS viewer, AI classifier, and Identifier. In the second AI classifier layer, an artificial neural network (ANN) classification model, which was constructed by training 149 LC-MS/MS spectra (including 27 sildenafil-type, 6 vardenafil-type, 11 tadalafil-type ED drugs/analogues and other 105 compounds), is included to classify the LC-MS/MS spectra of the query compound into four categories: i.e., sildenafil, vardenafil, and tadalafil families and non-ED compounds. This ANN model was found to show 100% classification accuracy for the 187 LC-MS/MS modeling and test data sets. In the third Identifier layer, three search algorithms (pick-count scoring, simple similarity search, and hybrid similarity search) are implemented. In particular, the hybrid similarity search was found to be very powerful in identifying unknown ED drugs/analogues with a single modification from the library ED drugs/analogues. Altogether, the AI-SIDA software provides a very useful and powerful platform for screening unknown ED drugs and analogues.