The purpose of this study was to use chemical similarity evaluations, transcriptional profiling, in vitro toxicokinetic data, and physiologically based pharmacokinetic (PBPK) models to support read-across for a series of branched carboxylic acids using valproic acid (VPA), a known developmental toxicant, as a comparator. The chemicals included 2-propylpentanoic acid (VPA), 2-ethylbutanoic acid, 2-ethylhexanoic acid (EHA), 2-methylnonanoic acid, 2-hexyldecanoic acid, 2-propylnonanoic acid (PNA), dipentyl acetic acid or 2-pentylheptanoic acid, octanoic acid (a straight chain alkyl acid), and 2-ethylhexanol. Transcriptomics was evaluated in 4 cell types (A549, HepG2, MCF7, and iCell cardiomyocytes) 6 h after exposure to 3 concentrations of the compounds, using the L1000 platform. The transcriptional profiling data indicate that 2- or 3-carbon alkyl substituents at the alpha position of the carboxylic acid (EHA and PNA) elicit a transcriptional profile similar to the one elicited by VPA. The transcriptional profile is different for the other chemicals tested, which provides support for limiting read-across from VPA to much shorter and longer acids. Molecular docking models for histone deacetylases, the putative target of VPA, provide a possible mechanistic explanation for the activity cliff elucidated by transcriptomics. In vitro toxicokinetic data were utilized in a PBPK model to estimate internal dosimetry. The PBPK modeling data show that as the branched chain increases, predicted plasma Cmax decreases. This work demonstrates how transcriptomics and other mode of action-based methods can improve read-across.
By Shengde Wu, Corie Ellison, Jorge Naciff, Michael Karb, Cindy Obringer, Gang Yan, Yuqing Shan, Alex Smith, Xiaohong Wang & George P Daston