Predictive classification-based read-across for diverse functional vitiligo-linked chemical exposomes (ViCE): A new approach for the assessment of chemical safety for the vitiligo disease in humans

Abstract

We have explored a new approach using a similarity measure-based read-across derived hypothesis to address the precise risk assessment of vitiligo active chemicals. In this analysis, we initially prepared a data set by combining vitiligo active compounds taken from the previous literature with non-vitiligo chemicals, which are non-skin sensitizers reported in another literature. Afterward, we performed the manual curation process to obtain a curated dataset. Furthermore, the optimum similarity measure was identified from a validation set using a pool of 47 descriptors from the analysis of the most discriminating features. The identified optimum similarity measure (i.e., Euclidean distance-based similarity along with seven close source compounds) has been utilized in the read-across derived similarity-based classification studies on close source congeners concerning target compounds. In this study, we identified the positive and negative contributing features toward the assessment of vitiligo potential as well, including the estimation of target chemicals with better accuracy. The applicability domain status of the reported compounds was also studied, and the outliers were identified. As there are no comparative studies in this regard to the best of our knowledge, we can further affirm that it is the first report on the in-silico identification of potential vitiligo-linked chemical exposomes (ViCE) based on the similarity measure of the read-across.