Artificial Neural Networks for the Rapid Prediction of Possible Ferroptosis Inducers Using the GPx4 Enzyme

Alvarado-Huayhuaz J.A.; Silva M.A.S.; Peña E.M.J.; Maraví J.C.R.; Cordova-Muñoz A.M.; Dos Santos MacHado K. · 21st IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2024 (2024) · DOI: 10.1109/cibcb58642.2024.10702169

Resumen

Cancer affects 20 million people worldwide; therefore, accelerated and urgent pathways are needed for the search for new drugs. The reactivation of cell death induced by the accumulation of iron-dependent lipid peroxides (Ferroptosis) is a potential mechanism for cancer treatment. One pathway to trigger Ferroptosis involves the inactivation of the glutathione-dependent peroxidase (GPx4) protein. Molecules with high affinity for iron are also being studied against cancer through chelation therapy. Therefore, the rapid detection of such molecules in molecular databases is of interest. Catechols exhibit a high iron-chelating power and can be synthesized by microorganisms as a chemical strategy for acquiring Fe3+. They can also be found in natural products. Recently, the natural product database in Peru (PeruNPDB) has been published where we found catechols; however, these have not yet been studied in GPx4. To expedite the search for catechols with affinity for the active site of GPx4, in large databases, we have developed a prediction model for scoring based on artificial neural networks. Our initial database consisted of the 83 catechols and 1,024 molecular descriptors. The target is the docking score obtained by ligand-receptor GPx4 coupling with the Autodock Vina software. Emphasizing the application of recursive feature elimination to improve the model's performance and provides both the model and the procedure to be applied and improved by the scientific community. Our program enables the experimenter to rapidly filter molecules with high affinity specifically for the active site of GPx4, in the search for potential inhibitors.

Instituciones: Universidad Nacional Mayor de San Marcos; Universidad Nacional de Trujillo; Universidad Nacional Agraria La Molina; Universidad Nacional de Ingeniería