Better understanding the phenotypic effects of drugs through shared targets in genetic disease networks
Elena Díaz-Santiago, Aurelio A. Moya-García, Jesús Pérez-García, Raquel Yahyaoui, Christine Orengo, Florencio Pazos, James R. Perkins, Juan A. G. Ranea · 2025
Read Better understanding the phenotypic effects of drugs through shared targets in genetic disease networks by Elena Díaz-Santiago, Aurelio A. Moya-García, Jesús Pérez-García, Raquel Yahyaoui, Christine Orengo, Florencio Pazos, James R. Perkins, Juan A. G. Ranea (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11794328.txt.
Description
Most drugs fail in testing, often because their side effects are not understood early enough. Elena Diaz-Santiago and co-authors present a network method to predict drug effects in this 2025 paper, with the journal record listing twenty twenty-four. The method links drugs to the body proteins they hit, and those proteins to disease traits.
The team found links for more than one hundred and forty thousand drugs and thousands of traits. Checked against known side effect lists, the method scored far above chance, and it also matched drug effects drawn from papers at a high rate. Using protein parts as well as whole proteins sharpened the results. Earlier warnings about side effects could cut failures and make drug testing cheaper and safer.
Catalog record
| CREATOR | Elena Díaz-Santiago, Aurelio A. Moya-García, Jesús Pérez-García, Raquel Yahyaoui, Christine Orengo, Florencio Pazos, James R. Perkins, Juan A. G. Ranea |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 51 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |