Yuan Jintao, Pu Yuepu, Yin Lihong
Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing 210009, China; School of Public Health, Zhengzhou University, Zhengzhou 450001, China.
Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing 210009, China.
Environ Toxicol Pharmacol. 2014 Jul;38(1):1-7. doi: 10.1016/j.etap.2014.04.019. Epub 2014 Apr 28.
Polychlorinated Dibenzodioxins (PCDDs), Dibenzofurans (PCDFs) and Biphenyls (PCBs) are industrial compounds or byproducts that can cause toxic effects after binding to aryl hydrocarbon receptor (AhR). But the mechanism about PCDDs, PCDFs and PCBs binding to AhR is unclear. To study the interaction and significant amino acid residues in binding of PCDDs, PCDFs and PCBs to AhR, a docking-based Comparative Molecular Similarity Indices Analysis (CoMSIA) was performed on a set of structurally diverse PCDDs, PCDFs and PCBs with known binding affinities. The docking-based CoMSIA model (non-cross-validated regression coefficient of 0.942 and cross-validated regression coefficient of 0.768) was developed and compared with previous report, the presented docking-based CoMSIA model showed good robustness and predictive performance. The obtained docking conformations and predictive CoMSIA model could provide clues to understand key residues and interactions between receptor and compounds of interest.
多氯代二苯并二噁英（PCDDs）、二苯并呋喃（PCDFs）和多氯联苯（PCBs）是工业化合物或副产物，它们与芳烃受体（AhR）结合后会产生毒性作用。但PCDDs、PCDFs和PCBs与AhR结合的机制尚不清楚。为了研究PCDDs、PCDFs和PCBs与AhR结合过程中的相互作用及重要氨基酸残基，对一组具有已知结合亲和力、结构多样的PCDDs、PCDFs和PCBs进行了基于对接的比较分子相似性指数分析（CoMSIA）。构建了基于对接的CoMSIA模型（非交叉验证回归系数为0.942，交叉验证回归系数为0.768），并与之前的报告进行比较，结果表明所构建的基于对接的CoMSIA模型具有良好的稳健性和预测性能。获得的对接构象和预测性CoMSIA模型可为理解受体与目标化合物之间的关键残基和相互作用提供线索。
