Artificial Intelligence in Decrypting Cytoprotective Activity under Oxidative Stress from Molecular Structure

Autor: Damian Nowak, Karolina Babijczuk, La Ode Irman Jaya, Rafał Adam Bachorz, Lucyna Mrówczyńska, Beata Jasiewicz, Marcin Hoffmann
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: International Journal of Molecular Sciences, Vol 24, Iss 14, p 11349 (2023)
Druh dokumentu: article
ISSN: 1422-0067
1661-6596
DOI: 10.3390/ijms241411349
Popis: Artificial intelligence (AI) is widely explored nowadays, and it gives opportunities to enhance classical approaches in QSAR studies. The aim of this study was to investigate the cytoprotective activity parameter under oxidative stress conditions for indole-based structures, with the ultimate goal of developing AI models capable of predicting cytoprotective activity and generating novel indole-based compounds. We propose a new AI system capable of suggesting new chemical structures based on some known cytoprotective activity. Cytoprotective activity prediction models, employing algorithms such as random forest, decision tree, support vector machines, K-nearest neighbors, and multiple linear regression, were built, and the best (based on quality measurements) was used to make predictions. Finally, the experimental evaluation of the computational results was undertaken in vitro. The proposed methodology resulted in the creation of a library of new indole-based compounds with assigned cytoprotective activity. The other outcome of this study was the development of a validated predictive model capable of estimating cytoprotective activity to a certain extent using molecular structure as input, supported by experimental confirmation.
Databáze: Directory of Open Access Journals
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