Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, USA.
National Research Council, U.S. Environmental Protection Agency, Duluth, Minnesota 55804, USA.
Toxicol Sci. 2021 Apr 12;180(2):212-223. doi: 10.1093/toxsci/kfab004.
Predictive toxicology is increasingly reliant on innovative computational methods to address pressing questions in chemicals assessment. Of importance is the evaluation of contaminant impact differences across species to inform ecosystem protection and identify appropriate model species for human toxicity studies. Here we evaluated 2 complementary tools to predict cross-species differences in binding affinity between per- and polyfluoroalkyl substances (PFAS) and the liver fatty acid-binding protein (LFABP): the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool and molecular dynamics (MD). SeqAPASS determined that the structure of human LFABP, a key determinant of PFAS bioaccumulation, was conserved in the majority of vertebrate species, indicating these species would have similar PFAS bioaccumulation potentials. Level 3 SeqAPASS evaluation identified several potentially destabilizing amino acid differences across species, which were generally supported by DUET stability change predictions. Nine single-residue mutations and 7 whole species sequences were selected for MD evaluation. One mutation (F50V for PFNA) showed a statistically significant difference with stronger affinity than wild-type human LFABP. Predicted binding affinities for 9 different PFAS across 7 species showed human, rat, chicken, and rainbow trout had similar binding affinities to one another for each PFAS, whereas Japanese medaka and fathead minnow had significantly weaker LFABP-binding affinity for some PFAS. Based on these analyses, the combined use of SeqAPASS and MD provides rapid screening for potential species differences with deeper structural insight. This approach can be easily extended to other important biological receptors and potential ligands.
预测毒理学越来越依赖于创新的计算方法来解决化学品评估中的紧迫问题。重要的是评估污染物对不同物种的影响差异,以告知生态系统保护,并确定适合人类毒性研究的模型物种。在这里,我们评估了两种互补的工具,以预测持久性有机污染物和多氟烷基物质(PFAS)与肝脂肪酸结合蛋白(LFABP)之间的结合亲和力的跨物种差异:序列比对预测跨物种易感性(SeqAPASS)工具和分子动力学(MD)。SeqAPASS 确定,人类 LFABP 的结构是 PFAS 生物累积的关键决定因素,在大多数脊椎动物物种中是保守的,这表明这些物种将具有相似的 PFAS 生物累积潜力。三级 SeqAPASS 评估在跨物种水平上确定了几个潜在的不稳定氨基酸差异,这些差异通常得到 DUET 稳定性变化预测的支持。选择了 9 个单残基突变和 7 个全物种序列进行 MD 评估。一个突变(对于 PFNA 的 F50V)显示出与野生型人类 LFABP 相比具有更强亲和力的统计学显著差异。对 7 个物种的 9 种不同 PFAS 的预测结合亲和力表明,人类、大鼠、鸡和虹鳟鱼彼此之间具有相似的 PFAS 结合亲和力,而日本青鳉和黑头呆鱼对某些 PFAS 的 LFABP 结合亲和力明显较弱。基于这些分析,SeqAPASS 和 MD 的联合使用提供了快速筛选潜在物种差异的方法,同时具有更深入的结构洞察力。这种方法可以很容易地扩展到其他重要的生物受体和潜在的配体。