Development of a hierarchical support vector regression-based in silico model for the prediction of the cysteine depletion in DPRA

In this study, a quantitative structure-activity relationship (QSAR) model was developed using the innovative hierarchical support vector regression (HSVR) scheme. The aim was to quantitatively predict the potential for skin sensitization by analyzing the percent of cysteine depletion in Direct Peptide Reactivity Assay (DPRA). The results demonstrated accurate, consistent, and robust predictions in the training set, test set, and outlier set. Consequently, this model can be employed to estimate skin sensitization potential of novel or virtual compounds.PMID:38307191 | DOI:10.1016/j.tox.2024.153739

Source: Toxicology - February 2, 2024 Category: Toxicology Authors: Giang H Ta Ching-Feng Weng Max K Leong Source Type: research