Definition and Classification of Parkinsonian Drugs

Mizuno, Yoshikuni

doi:10.1007/978-3-030-62059-2_213

Cited by 2 publications

(1 citation statement)

References 187 publications

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“…Specifically, for a given disease, if Meta-DEP predicts a higher score for the combined drug efficacy than for any individual drug within the combination, it would deduce that the concurrent administration of these drugs could potentiate the therapeutic outcome for that particular disease. The findings revealed that Meta-DEP accurately discerned 65 pairs of drug combinations (Figure 3A, Additional file 1), including the combined usage of Acetaminophen and Acetylsalicylic acid for treating Migraine Disorders [40,41], the combined usage of Vildagliptin and Nateglinide for type 2 diabetes mellitus [42], Entacapone and Carbidopa, in combination with Droxidopa, are used for the treatment of Parkinson's Disease [43,44]. (Figure 3B-D).…”

Section: Exploring Drug Combination Predictions With Meta-depmentioning

confidence: 99%

Meta-path-based drug efficacy prediction model for active natural compound discovery from Traditional Chinese medicine

Li,

Shen,

Cai

et al. 2024

Preprint

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Identifying the active nature compounds remains a challenge for drug discovery, and new algorithms need to be developed to predict active ingredients from complex natural products. Here, we proposed Meta-DEP, a Meta-paths-based Drug Efficacy Prediction based on drug-protein-disease heterogeneity network, where Meta-paths contains all the shortest paths between drug targets and disease-related proteins in the network and drug efficacy is measured by a predictive score according to drug disease network proximity. Experiments show that Meta-DEP performs better than traditional network topology analysis on drug-disease interaction prediction task. Further investigations demonstrate that the key targets identified by Meta-DEP for drug efficacy are consistent with clinical pharmacological evidence. To prove that Meta-DEP can be used to discover active nature compounds, we apply it to predict the relationship between the monomeric components of traditional Chinese medicine included in the TCMSP database and diseases. Results indicate that Meta-DEP can accurately predict most of the drug-disease pairs included in the TCMSP database. In addition, biological experiments are directly used to demonstrate that the natural compound mined by Meta-DEP from traditional Chinese medicine has a protective effect against myocardial ischemia. Overall, the model developed in this study provides new impetus for driving the nature compound into innovative lead molecule. Code and data are available at https://github.com/t9lex/Meta-DEP.

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