Efficient identification of novel anti-glioma lead compounds by machine learning models

• Published in: European journal of medicinal chemistry 2020-03, Vol.189, p.111981-111981, Article 111981
• Main Authors: Neves, Bruno Junior, Agnes, Jonathan Paulo, Gomes, Marcelo do Nascimento, Henriques Donza, Marcio Roberto, Gonçalves, Rosângela Mayer, Delgobo, Marina, Ribeiro de Souza Neto, Lauro, Senger, Mario Roberto, Silva-Junior, Floriano Paes, Ferreira, Sabrina Baptista, Zanotto-Filho, Alfeu, Andrade, Carolina Horta
• Format: Article
• Language: English
• Subjects: Cancer; Glioblastoma; Machine learning; Orthotopic glioma model; Predictive modeling; Thioredoxin reductase
• ISSN: 0223-5234; 1768-3254
• DOI: 10.1016/j.ejmech.2019.111981

Glioblastoma multiforme (GBM) is the most devastating and widespread primary central nervous system tumor. Pharmacological treatment of this malignance is limited by the selective permeability of the blood-brain barrier (BBB) and relies on a single drug, temozolomide (TMZ), thus making the discovery of new compounds challenging and urgent. Therefore, aiming to discover new anti-glioma drugs, we developed robust machine learning models for predicting anti-glioma activity and BBB penetration ability of new compounds. Using these models, we prioritized 41 compounds from our in-house library of compounds, for further in vitro testing against three glioma cell lines and astrocytes. Subsequently, the most potent and selective compounds were resynthesized and tested in vivo using an orthotopic glioma model. This approach revealed two lead candidates, 4m and 4n, which efficiently decreased malignant glioma development in mice, probably by inhibiting thioredoxin reductase activity, as shown by our enzymological assays. Moreover, these two compounds did not promote body weight reduction, death of animals, or altered hematological and toxicological markers, making then good candidates for lead optimization as anti-glioma drug candidates. [Display omitted] •ML models were developed to predict of anti-glioma activity and BBB penetration.•New hits with antiproliferative activity were identified by virtual screening.•Three hits presented high potency and moderate cytotoxicity.•Compounds were able to inhibit TrxR enzyme.•Two lead compounds stopped the malignant glioma in vivo without promoting toxicity.