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Background:Although rare,relapsed/refractory (R/R) B-cell non-Hodgkin lymphoma (B-NHL) in children, adolescents, and young adults is an area of high unmet need, with 1-year overall survival rates of <30% and complete remission (CR) rates of 27% after treatment with R-ICE (rituximab, ifosfamide, carboplatin, and etoposide) chemoimmunotherapy (Burke et al. Leukemia 2020). New treatment regimens are urgently needed (Woessmann et al. Blood 2020; Burkhardt et al. Cancers (Basel) 2021). T-cell engagers have been identified as medicinal products with the greatest probability of being beneficial for the pediatric population (Pearson et al. Eur J Cancer 2019).

The LXR model has been added in the VirtualToxLab, a fully automated technology that allows for the identification of the endocrine‐disrupting potential of drugs, chemicals and natural products. This protocol has then been applied to screen a series of 161 natural compounds probing their binding to the LXR. The results of the simulation were compared with experimental data (where available) and suggest that the LXR model can be applied to predict the binding affinity of existing or hypothetical compounds for screening purposes. The binding of 52 ligands towards the liver X receptors (LXRs) was identified trough docking to the three‐dimensional protein structure and quantified by multidimensional QSAR (mQSAR), an approach referred to as ‘mixed‐model QSAR’. The model was validated by the prediction of 17 external compounds (oxysterols) present neither in the training nor in the test set. The robustness of the model was verified by consensus scoring using a conceptually different methodology, and chance correlation was ruled out by a series of scramble tests.