Virtual screening of potentially endocrine-disrupting chemicals against nuclear receptors and its application to identif
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Virtual screening of potentially endocrine‑disrupting chemicals against nuclear receptors and its application to identify PPARγ‑bound fatty acids Chaitanya K. Jaladanki1,2 · Yang He3 · Li Na Zhao1 · Sebastian Maurer‑Stroh1,2 · Lit‑Hsin Loo1,2 · Haiwei Song3 · Hao Fan1 Received: 2 July 2020 / Accepted: 27 August 2020 © The Author(s) 2020
Abstract Nuclear receptors (NRs) are key regulators of energy homeostasis, body development, and sexual reproduction. Xenobiotics binding to NRs may disrupt natural hormonal systems and induce undesired adverse effects in the body. However, many chemicals of concerns have limited or no experimental data on their potential or lack-of-potential endocrine-disrupting effects. Here, we propose a virtual screening method based on molecular docking for predicting potential endocrine-disrupting chemicals (EDCs) that bind to NRs. For 12 NRs, we systematically analyzed how multiple crystal structures can be used to distinguish actives and inactives found in previous high-throughput experiments. Our method is based on (i) consensus docking scores from multiple structures at a single functional state (agonist-bound or antagonist-bound), (ii) multiple functional states (agonist-bound and antagonist-bound), and (iii) multiple pockets (orthosteric site and alternative sites) of these NRs. We found that the consensus enrichment from multiple structures is better than or comparable to the best enrichment from a single structure. The discriminating power of this consensus strategy was further enhanced by a chemical similarity-weighted scoring scheme, yielding better or comparable enrichment for all studied NRs. Applying this optimized method, we screened 252 fatty acids against peroxisome proliferator-activated receptor gamma (PPARγ) and successfully identified 3 previously unknown fatty acids with Kd = 100–250 μM including two furan fatty acids: furannonanoic acid (FNA) and furanundecanoic acid (FUA), and one cyclopropane fatty acid: phytomonic acid (PTA). These results suggested that the proposed method can be used to rapidly screen and prioritize potential EDCs for further experimental evaluations. Keywords Virtual screening · In silico toxicity prediction · Nuclear receptors · EDC · ToxCast · Furan fatty acid
Chaitanya K. Jaladanki and Yang He contributed equally to this work. Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00204-020-02897-x) contains supplementary material, which is available to authorized users.
Abbreviations NR Nuclear receptor AR Androgen receptor ER Estrogen receptor GR Glucocorticoid receptor PPAR Peroxisome proliferator-activated receptor PR Progesterone receptor
* Haiwei Song [email protected]‑star.edu.sg * Hao Fan [email protected]‑star.edu.sg 1
Bioinformatics Institute (BII), Agency for Science, Technology, and Research (A*STAR), 30 Biopolis Street, Matrix No. 07‑01, Singapore 138671, Singapore
Toxicity Mode‑of‑Action Discovery (ToxMAD) Platform, Innovations in Food and Chemical Safety Programme,
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