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# What Structural Biology Tells Us About the Mode of Action and Detection of Toxicants

Albane Le Maire, William Bourguet

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Albane Le Maire, William Bourguet. What Structural Biology Tells Us About the Mode of Action and Detection of Toxicants. Annual Review of Pharmacology and Toxicology, In press, 10.1146/annurev-pharmtox-061724-080642. hal-04707527

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# What Structural Biology Tells Us About the Mode of Action and Detection of Toxicants

Albane le Maire and William Bourguet

CBS (Centre de Biologie Structurale), Univ Montpellier, CNRS, Inserm, Montpellier, France

Albane le Maire: albane.lemaire@cbs.cnrs.fr; ORCID 0000-0003-3336-2158

William Bourguet: william.bourguet@cbs.cnrs.fr; ORCID 0000-0002-0643-7719

Corresponding author: William Bourguet
Centre de Biologie Structurale
29 rue de Navacelles
34090 Montpellier, France

Posted with permission from the Annual Review of Pharmacology and Toxicology, Volume 65© by
Annual Reviews, http://www.annualreviews.org/. Original version prior to review and revision.
**Keywords**

endocrine disrupting chemicals, nuclear receptors, aryl hydrocarbon receptor, three-dimensional structures, structure-based prediction methods

**Abstract**

Study of the adverse effects of chemical substances on living organisms is an old and intense field of research. However, toxicological and environmental health sciences have long been dominated by descriptive approaches that enable associations or correlations, but relatively few robust causal links and molecular mechanisms. Recent achievements have shown that structural biology approaches can bring this added value to the field. By providing atomic-level information, structural biology appears as a powerful tool to decipher the mechanisms by which toxicants bind to and alter the normal function of essential cell components, causing adverse effects. Here, using endocrine disrupting chemicals as illustrative examples, we describe recent advances in the structure-based understanding of their modes of action and how this knowledge can be exploited to develop computational tools aimed at predicting properties of large collections of compounds.
## INTRODUCTION

There is increasing evidence that genetic factors explain only a limited fraction of the etiology of many chronic diseases and environmental exposures are therefore thought to play a significant role in disease onset and progression (1, 2). External chemicals (aka xenobiotics), whether of natural origin or produced by human activities, are essential components of our daily environment, and one can estimate to tens of thousands the number of man-made chemicals (aka anthropogenic chemicals) currently in use worldwide. Therefore, humans are chronically and simultaneously exposed to hundreds of these contaminants that may affect different physiological functions and trigger the development of a number of pathological conditions (3). Identifying the molecular pathways involved in toxicants action is therefore crucial for devising effective strategies to mitigate their adverse effects.

To gain such a comprehensive understanding of the mode of action of toxicants, modern toxicology employs multidisciplinary approaches that combine advanced experimental and computational techniques, such as *in vitro* cell culture models and cell-based assays, high-throughput screenings, various omics technologies, organoids, animal and epidemiological studies or various *in silico* modeling. Although still under-used in the fields of toxicology and environmental sciences, structural biology and related methods can make a novel contribution to understanding the molecular mechanisms of contaminants by providing unique atomic-level information on the details of their interaction with their biological targets.

Modern structural biology, also referred to as integrative structural biology, involves the combination of information obtained from high-resolution structural biology techniques such as X-ray crystallography, nuclear magnetic resonance (NMR) or cryogenic electron microscopy (cryo-EM) and other low/medium resolution methods like native or cross-linking mass spectrometry (nMS, XL-MS), hydrogen/deuterium exchange coupled to mass spectrometry (HDX-MS), small angle X-ray scattering (SAXS), Forster resonance energy transfer (FRET), correlated light and electron microscopy (CLEM) or cryo-electron tomography (cryo-ET), to name a few (4). More generally, any kind of data with extra information could, in principle, be integrated to provide a more complete picture at different structural scales. These techniques have allowed in the past decades to determine a huge number of protein structures, most often made publicly available in the Protein Data Bank (http://www.rcsb.org/) (5).
Visualizing with atomic precision the three-dimensional architecture of biological macromolecule assemblies (proteins, nucleic acids, etc.) and of their complexes with small regulatory compounds (e.g. endogenous ligands, enzyme cofactors, etc.) sheds light on their functions and regulation, with obvious repercussions and applications in the field of human health. For instance, structural studies are widely used in drug discovery because of their unique ability to reveal the atomic details of protein-small compound interactions, and guide the rational design of novel therapeutics (6, 7). In the same line, the potential of structural biology approaches in elucidating the binding mode of toxicants to their cellular targets and dissecting the mechanisms by which they disrupt essential cellular processes is evident. In addition to providing fundamental knowledge, such structural information can also be used to inspire the rational synthesis of safer chemicals with reduced off-target binding, or help the development of computer aided methods for high-throughput chemical-target interaction affinity prediction.

By far the most studied class of toxic substances from a structural perspective is that of endocrine disrupting chemicals (EDCs). EDCs form a chemically heterogeneous family of environmental compounds that are not identified by their chemical structure, but rather by their mode of action (8, 9). This group contains substances as chemically different as plasticizers (e.g. bisphenols and phthalate), preservatives (e.g. parabens), surfactants (e.g. alkylphenols and perfluoroalkyls), byproducts of industrial processes (e.g. dioxins and polychlorinated biphenyls), biocides (e.g. organotins and organochlorine pesticides), UV filters (e.g. benzophenones), flame retardants (e.g. halogenated bisphenols) and natural compounds such as the phytoestrogen genistein, or the mycoestrogen α-zearalanol. Human exposure to EDCs occurs via ingestion of food and drinks, inhalation of dust and other air particles or through skin contact. As their name suggests, EDCs were originally defined as compounds that can mimic or antagonize the action of endogenous hormones involved in key endocrine functions regulated by the estrogen (ERα and ERβ) and the androgen (AR) receptors that belong to the nuclear receptor (NR) family of transcription factors (Figure 1a). However, later studies have shown that xenobiotics can alter the function of many more NRs, including those that do not display an endocrine mode of action like, for example, the constitutively active estrogen-related receptor γ (ERRγ), the fatty acid-binding peroxisome proliferator activated receptors (PPARs), the
xenobiotic receptors pregnane X receptor (PXR) and the constitutive androstane receptor (CAR) or the
retinoid X receptors (RXRs). Although this is not strictly correct, all NR disrupting chemicals are by
extension classified as EDCs (10). The range of toxicological effects induced by EDCs is, just like
their chemical heterogeneity, extremely broad and includes developmental, reproductive, metabolic,
immune or neurologic disorders as well as cancers, depending on the NR target (8, 9, 11), and
transgenerational toxicity through epigenetic modifications has also been demonstrated (12, 13).

In this review, we provide a concise overview of different EDC receptors, including various NRs
and the NR-related aryl hydrocarbon receptor (AHR), another front-line target of environmental
contaminants whose ligand-bound structures were reported only recently (Figure 1a). We focus on the
structural details of various toxicant binding modes and discuss how the ever expanding amount of
three-dimensional data can help the detection of new toxicant-protein interactions thanks to structure-
based *in silico* methods.

NUCLEAR RECEPTOR DISRUPTING CHEMICALS

Human NRs belong to a 48-membered family of proteins that mostly comprises ligand-dependent
transcription factors responding to small hydrophobic endogenous compounds like thyroid hormone,
steroids, retinoic acid or fatty acids (14–16). NRs regulate cognate gene networks involved in key
physiological functions such as cell growth and differentiation, development, organ homeostasis,
immune function, reproduction or metabolism. As a consequence, dysfunctional NR signaling often
leads to proliferative, reproductive, or metabolic diseases, including cancers, infertility, obesity, and
diabetes (17–20). In the absence of their cognate ligands, some NRs (e.g. retinoic acid receptors,
RARα, β and γ) are located in the nucleus bound to DNA response elements located in the promoter
region of their target genes and to corepressor complexes, generally in the form of heterodimers with
retinoid X receptors (RXRα, β and γ) (Figure 1a). In contrast, others (e.g. steroid hormone receptors)
are sequestered in the cytoplasm in an inactive complex with chaperone proteins. Ligand binding
induces major structural alterations of the receptor ligand-binding domains (LBDs) leading to the
destabilization of corepressor interfaces or to exposure of nuclear localization signals to allow nuclear
translocation and binding of NRs to DNA as homo- or heterodimers (Figure 1a). The subsequent
recruitment of coactivator complexes triggers gene transcription through chromatin remodeling and
activation of the general transcription machinery. Note that beside their nuclear localization, a few
percent of NR molecules are membrane-bound (mbNRs) and mediate some rapid non genomic effects
through multiple kinase cascades activation, as previously shown for several steroid receptors (21, 22)
(Figure 1a). NRs are modular proteins composed of several functional domains, most notably a
disordered and poorly conserved N-terminal transactivation domain containing the ligand-independent
transcriptional activation function AF-1, a highly conserved zinc-finger DNA- binding domain (DBD)
and a moderately conserved LBD hosting a ligand- dependent transcriptional activation function
(AF- 2) (Figure 1b) (23, 24). The LBD of NRs is organized as an antiparallel α-helical sandwich with
12 conserved α-helices (H1-H12) arranged in three layers (Figure 2a). The C-terminal helix H12 (also
termed activation or AF-2 helix) is flexible and can adopt various conformations and dynamics
depending on the presence or absence of ligand, or the type of bound ligand. This LBD architecture
generates a ligand-binding pocket (LBP) of variable size, primarily made up of hydrophobic residues
from helices H3, H5, H7, H11, H12 and a β-sheet (S1, S2) segment. Slight variations in the number of
α-helices or β-sheets can be observed from one receptor to another. Because of their confined and
predominantly hydrophobic LBP, NRs are the targets of many external chemicals, acting as EDCs,
which compete with endogenous ligands and therefore interfere with the highly regulated
physiological signaling pathways of NRs. In addition to the body's ability to metabolize and eliminate
a large part of xenobiotics, the binding affinities and environmental concentrations of EDCs are
generally rather low so that chemicals are assumed to be innocuous and not harmful to human health
in these conditions. However, several mechanisms including, but not limited to, chronic exposure,
bioaccumulation, metabolic activation, critical exposure windows (e.g. developmental stages), or the
so-called cocktail effect that is cumulative and interactive effects of multiple chemicals, may account
for the deleterious impact of xenobiotics at environmental doses. Below, we provide a selection of
structural mechanisms by which EDCs bind to NRs and interfere with their signaling pathways.
## Endogenous ligand mimicry

This mode of binding can be best illustrated by estrogen receptors (ERs) and their environmental ligands. ERα and ERβ are major targets of EDCs. They are receptors for the sex hormone 17β-estradiol (E2) that plays important roles in many tissues and organs throughout the body such as the mammary gland, uterus, ovary, bone, lung, liver, kidney, brain or the cardiovascular system (25, 26). Importantly, endogenous estrogens or exogenous estrogen-like compounds (i.e. xenoestrogens) are key activators of hormone-dependent breast, endometrial and ovarian cancer growth, and exposure to xenoestrogens can also lead to several ER-related disorders such as neurodegenerative, inflammatory, immune, cardiovascular and metabolic diseases (27, 28). E2 is a high affinity ligand of ERs with dissociation constant (Kd) in the sub-nanomolar range. The hormone-binding pockets of ERs comprise mainly hydrophobic amino acids that interact with the steroid scaffold, and three polar residues located at both ends of the pockets, namely E353 from H3, R394 in H5 and H524 from H11 (ERα numbering), forming hydrogen bonds with the phenolic and hydroxyl groups of E2 (Figure 2b).

Xenoestrogens exhibit a large structural diversity and vary both in size and chemical features. For example, the well-characterized natural mycoestrogen α-zearalenol (α-ZA), the phytoestrogens genistein and ferutinin, the pharmaceutical diethylstilbestrol (DES) or the man-made chemicals DDE and HPTE (metabolites of pesticides DDT and methoxychlore, respectively), and the bisphenol-A (BPA) bind to ERs with a large range of affinities. All of them bind to the same binding site as E2 and engage in different sets of ligand/protein interactions according to their size and chemical structures.

The smallest compounds making fewer contacts with the receptor cavity are generally associated with lower binding affinities whereas larger compounds adopting a binding mode reminiscent of that used by the endogenous ligand are characterized by higher interaction capacities. This is for example the case of DES that recapitulates most of the interaction made by E2 (Figure 2c) and acts as a sub-nanomolar ER agonist (29). By losing one important hydrogen bond with R394, α-ZA only partially mimics the E2 binding mode (Figure 2d) so that it binds to and activates ERs at slightly higher nanomolar concentrations (30). Finally, the emblematic pollutant BPA is a smaller compound engaged in fewer van der Waals contacts with LBP residues. In addition, the two phenolic groups of BPA are not optimally positioned to engage in the hydrogen bond network seen with E2 or DES (Figure 2e).
As a consequence, BPA binds to and activates ERs with EC50 values (half maximal effective concentration) around 0.5 µM (31).

## Covalent coupling

Covalent ligand binding to proteins has been widely studied (32, 33), and affinity labeling, in which a known ligand is chemically modified to irreversibly bind to the active site of a protein, has been instrumental in identifying, characterizing and purifying NRs (34). Covalent binding displays several advantages, including low dissociation rates, higher binding affinity and prolonged activity. Therefore, covalent pharmacological ligands have been developed for NRs that represent an important family of drug targets (35). Note that, since covalent binding is a two-step process involving proper ligand positioning within the binding cavity through non-covalent interactions followed by covalent bond formation, the confined LBP of NRs appears to offer a particularly well-suited environment allowing a residence time long enough to let the chemical reaction to occur. Later, it was discovered that endogenous compounds such as prostaglandins (e.g. 15d-PGJ2, etc.) and polyunsaturated fatty acids (e.g. 4-oxo-DHA, 6-oxo-OTE etc.) acted as covalent ligands of certain NRs (36–38). Most of them were found to bind to PPARs, and more specifically PPARγ that is highly expressed in adipocytes where it plays key roles in regulating lipid storage and adipogenesis (39). While the special characteristics of covalent bonds can be of benefit in the development of therapeutic ligands, the situation is different when they boost the interaction with environmental contaminants. The first characterized EDC acting through covalent bonding is the organotin tributyltin (TBT). Organotins form a large family of tin derivatives ubiquitously found in the environment due to their widespread use in many industrial and agricultural processes (40). TBT was found to be a nanomolar agonist of PPARγ and of its heterodimeric partner RXRs (41–43), and organotins were classified as potential environmental obesogens due to their ability to induce adipogenesis via a potent activation of the RXR-PPARγ heterodimer (41, 43). Structural studies revealed that TBT binds covalently to both heterodimer subunits (44, 45). Covalent coupling is generally mediated by a nucleophilic attack of the sulfur atom of a cysteine residue on a reactive electrophilic group of the ligand. In the case of TBT, the covalent attachment involves the tin atom of the organotin and the sulfur atom of C432 in helix
H11 of RXRα or C285 in helix H3 of PPARγ (Figure 3a, b). Interestingly, RXRα C432 places TBT in close proximity to the AF-2 helix, stabilizing it in an active conformation, whereas in PPARγ, the organotin is located at a distance of the activation helix H12, in line with its weaker PPARγ agonistic activity (44). Nevertheless, binding of one organotin molecule to each subunit is probably a key feature accounting for the strong activity of TBT on the RXR-PPARγ heterodimer. In addition to organotins, a number of bioactive compounds display reactive chemical groups that can form covalent bonds with cysteine residues. Recent structural studies (46) have shown that the herbicide pretilachlor or the insecticide fipronil (Figure 3c) bind covalently to two different cysteines present in the LBP of PXR. Hence, one can hypothesize that a significant part of the endocrine disrupting effects of environmental chemicals can be attributed to their covalent coupling with the fifteen NRs displaying at least one cysteine residue in their LBP. Moreover, as exemplified by the differential response of RXRs and PPARγ following TBT binding, the position of the reactive cysteine within the LBD appears as a good predictor of compound activity.

## Multiple ligand binding and cooperativity

Although ligand binding to NRs occurs predominantly in a 1:1 molar ratio, it has been observed that multiple compounds can bind simultaneously to the receptors and, sometimes, in a cooperative fashion. PPARγ harbors a large and conformable LBP with a volume ranging from 1,200 to 1,500 Å³ depending on the bound ligand (47). Hence, the first description of cobinding to a NR was provided by the observation that PPARγ can accommodate two copies of the synthetic ligand N-(9-fluorenylmethyloxycarbonyl)-L-Leucine (48). Subsequent crystal structures revealed that dietary medium chain fatty acids (MCFAs) and endogenous long chain unsaturated fatty acids (UFAs) can bind to PPARγ in up to three copies of the same molecule (49). Other structural studies demonstrated binding of two equivalents of non-fatty acid ligands to PPARγ such as, for example, the plant-derived natural compound magnolol (50), the non-steroidal anti-inflammatory drugs indomethacin and sulindac sulfide (51, 52), or the mono(ethylhexyl)phthalate (MEHP), a metabolite of the plasticizer di-2-ethyhexyl phthalate (DEHP) (Figure 4a) (53). The PPARγ LBP extends from helix H12 on one side to the β-sheet on the other side. Based on structural and functional data, it has been shown that
formation of a hydrogen bond between the ligand and H12 Y473 is required for stabilization of the transcriptionally active conformation and full receptor activation. With one of the two molecules hydrogen bonded to Y473, the binding modes of indomethacin, sulindac sulfide and MEHP (Figure 4a) are in full agreement with *in vitro* cell-based assays showing that all three compounds act as full human PPARγ agonists. As revealed by the structure of PPARγ in complex with the serotonin metabolite 5-methoxy-indole acetate and the fatty acid 15-oxo-ETE, fatty acids and non-fatty acid compounds can coexist within the binding pocket (51). This was subsequently confirmed with the observation that 9-carbon MCFAs, copurified during protein bacterial expression, are present in many synthetic ligand-bound PPARγ LBD crystal structures solved previously, including with the antidiabetic drug rosiglitazone (54). Because cotreatment with synthetic ligands and fatty acids was shown to synergistically enhance coactivator interaction and PPARγ transcriptional activity in cells, it has been hypothesized that such cobinding with MCFAs, that are essential components of mammalian food, could be an integral part of the binding mechanism of many chemicals to PPARγ (54).

In some instances, it has been shown that chemicals not only bind simultaneously to a receptor, but they do so cooperatively, that is, binding of one molecule enhances the binding affinity of the second one. A direct consequence of this phenomenon is the lowering of the concentrations at which compounds may alter NR function. This binding mode has been best described for the xenobiotic receptor PXR which plays a key role in the body's defense against a wide variety of foreign substances. Upon ligand binding, PXR regulates the expression of a number of genes coding for metabolic enzymes and transporters involved in the elimination of adverse chemicals (55). On the other hand, sustained activation of PXR is known to provoke undesirable effects, including drug interactions, resistance to cancer therapy, defects in the homeostasis of endogenous hormones, increased cell proliferation and tumor aggressiveness as well as increased risk of cardiovascular and metabolic diseases (56–59). PXR harbors a large (~1,300 Å³) balloon-shaped LBP made up of several sub-pockets to which different kinds of small compounds can bind according to their size and chemical structure (46). Other features of the LBP accounting for the ligand binding promiscuity of PXR are (1) the presence of a F/W/Y aromatic triad generating a π-cage deeply buried in the LBP and trapping aromatic/aliphatic groups, and (2) a highly malleable and adaptive loop segment in the H2'
C-terminal region (Figure 4b). Thanks to these unique features, crystal structures have shown that PXR can accommodate two compounds simultaneously, each of them binding to a specific sub-pocket. Notably, synthetic (17α-ethinylestradiol, EE2) or endogenous (17α-estradiol, E2) estrogens and organochlorine pesticides such as *trans*-nonachlor (TNC) or *cis*-chlordane (CC), that exhibit low individual potency, were shown to bind cooperatively to PXR and activate the receptor in a synergistic fashion (Figure 4b, c). Biophysical and cell-based analyses showed that each ligand enhances the binding affinity of the other, so the binary mixtures bind 10 to 100-fold more avidly to PXR than their individual components, and induce a biological response at concentrations where the compounds are individually inactive (46, 60). Note that, in addition to this cooperative cobinding to PXR LBP, coincubation with a third environmental ligand targeting the heterodimerization partner RXR was shown to increase further transcriptional activation through cooperative recruitment of coactivators to both RXR-PXR heterodimer subunits, as previously demonstrated using combinations of pharmacological receptor ligands (16).

## ARYL HYDROCARBON RECEPTOR AS A TARGET OF THE CHEMICAL EXPOSOME

Also referred to as an 'exposome receptor' (61), AHR is one of the crucial chemosensory proteins involved in a wide range of physiological and pathological processes in response to hundreds of natural and chemical substances (62). First identified in 1976 as a dioxin-binding protein (63), it was later cloned in 1992 (64) and found to be an ubiquitously expressed ligand-dependent transcription factor belonging to the basic helix-loop-helix (bHLH) PER-ARNT-SIM (PAS) protein family (65, 66). AHR shares many similarities with NRs such as a molecular organization in functional domains, the interaction with small regulatory ligands, the binding to DNA response elements upon interaction with an heterodimerization partner, and the regulation of target genes transcription *via* the dynamic association with a common set of transcriptional coactivators (67, 68). AHR consists in an N-terminal bHLH domain involved in DNA binding and dimerization, followed by a bipartite PAS domain involved in dimerization (PAS-A, PAS-B) and ligand binding (PAS-B), and a C-terminal transactivation domain (Figure 1c). In the absence of cognate ligand, AHR is found in the cytoplasm complexed with the chaperone Hsp90 (heat shock protein 90) and the co-chaperones XAP2 (X-
associated protein-2) and p23 (Figure 1a). Upon ligand binding, the full complex migrates to the nucleus where AHR dissociates from the chaperone complex and associates with ARNT (AHR nuclear translocator, also member of the bHLH/PAS protein family) to bind to dioxin response DNA elements (DRE), in the form of an AHR-ARNT heterodimer.

Reminiscent of PXR, AHR has been originally considered as a xenobiotic receptor involved in the
metabolism and clearance of external chemicals through the regulation of the expression of
xenobiotic-metabolizing enzymes (59). AHR is historically known as the receptor for numerous
xenobiotics such as halogenated aromatic hydrocarbons (HAHs, e.g. 2,3,7,8-tetrachlorodibenzo-p-
dioxin also known as dioxin or TCDD), polycyclic aromatic hydrocarbons (PAHs, e.g.
benzo[a]pyrene, B[a]P), polychlorinated biphenyls (PCBs, e.g. PCB-81), pharmaceuticals and other
environmental contaminants. However, in addition to promoting their elimination, AHR is also known
to act as a mediator of the toxicity of certain chemicals through various mechanisms. A well-
characterized example is B[a]P, a byproduct formed in various combustion processes, including
burning of fossil fuels, wood, and other organic materials, that is present in high levels in cigarette
smoke, diesel exhaust, smoked and grilled food products. Binding of B[a]P to AHR results in its
biotransformation by AHR-induced cytochrome P450s into the carcinogenic metabolite B[a]P-7,8-
diol-9,10-epoxide that binds covalently to DNA, thus leading to erroneous replication and mutagenesis
(69). A sustained activation of the receptor by metabolically resistant AHR ligands (e.g. TCDD) has
also been suggested as a possible mechanism of AHR-mediated toxicity (70). In addition, it has been
shown that AHR can act as a mediator of endocrine disruption by increasing the metabolism of
endogenous hormones mediated by the ligand-induced expression of metabolizing enzymes such as
CYP1A1/1B1 (67, 71), competitively sequestering away common coactivators used by AHR and NRs
(68, 72) or acting as an E3 ubiquitin ligase that induces ubiquitination and proteasome-driven
degradation of a number of NRs (73). In addition to its detoxification function, AHR plays an integral
role in various cellular processes including cell growth, differentiation, immune response and barrier
function through its modulation by many natural compounds like microbiome metabolites, natural
products and endogenous molecules (74).
Because the mammalian AHR ligand binding PAS-B domain is unstable and prone to aggregation, many attempts at solving the structure of full-length AHR or of its isolated PAS-B domain have failed for thirty years. It is only very recently that the first experimental visualizations of AHR PAS-B domains have been reported following different methodological approaches to circumvent protein instability issues. On one hand, reconstitution of the core AHR cytosolic complex allowed to solve the cryo-EM structures of the indirubin- and B[a]P-bound human AHR-Hsp90-XAP2 (75, 76), and of the unliganded mouse AHR-Hsp90-XAP2-p23 (77) complexes. On the other hand, crystal structures of the fruit fly AHR PAS-B domain were obtained thanks to the screening of the recombinant expression of PAS-B homologs from ten different species, revealing that only fruit fly PAS-B could be produced in a soluble form (78). Structures of the AHR cytosolic complex revealed the concerted action of the (co)chaperones to maintain the receptor in a stable and functional form, with the Hsp90 dimer and XAP2 forming extensive interaction sites with the PAS-B domain (Figure 5a). The ligand binding PAS-B domain of AHR exhibits the canonical PAS fold comprising a five-stranded antiparallel β-sheet (Aβ, Bβ, Gβ, Hβ and Iβ) flanked by four consecutive α-helices of variable lengths (Cα, Dα, Eα and Fα), plus two additional short α-helices (Jα and Kα) at the carboxy-terminus (Figure 5b). At the center of the domain, a mostly hydrophobic LBP of around 680 Å³ in human AHR takes a form of an elongated channel extending perpendicularly between helices Cα and Fα (Figure 5c). The structures showed that indirubin and B[a]P use a common binding site that is located close to helix Fα, as illustrated with B[a]P in Figure 5c. Both compounds are small-sized, aromatic in nature, and display a planar shape, three characteristics that are shared by most AHR ligands. Their binding modes involve primarily a number of aromatic and aliphatic residues engaged in π-π and C-H/π interactions, respectively, and two additional hydrogen bonds between the polar atoms of indirubin and AHR S365 and Q383 account for its roughly two orders of magnitude higher affinity compared to B[a]P (76). The compounds occupy approximately half of the binding pocket, suggesting how AHR can accommodate larger compounds by exploiting the empty space near Cα. Thus, the structures revealed that human AHR PAS-B holds a bipartite LBP comprising (1) a sterically constrained primary binding site controlling ligand binding specificity and affinity through a mix of aromatic/aliphatic residues and a few polar amino acids with the potential to form tight π interactions and hydrogen bonds, respectively,
and (2) a less geometrically constrained secondary binding site, more permissive in terms of ligand three-dimensional hindrance, and contributing to the binding promiscuity of the receptor (Figure 5c).

Interestingly, comparison of AHR and PXR structures revealed how ligand binding promiscuity can be achieved through different mechanisms. Both receptors bind hundreds of substances but whereas PXR harbors a balloon-shaped binding pocket of about 1,300 Å³ accommodating chemically unrelated compounds with binding affinities in the micromolar range, AHR displays a more restrained elongated binding pocket (around 700 Å³) with a marked preference for planar aromatic compounds and binding affinities in the high nanomolar to picomolar range. Apart from their size, a major difference between the two LBPs is that the PAS-B primary binding site, which plays a critical role in controlling AHR binding specificity and affinity, doesn't exist in PXR, thus explaining the greater chemical heterogeneity of PXR ligands.

## STRUCTURE-BASED DETECTION OF TOXICANT-RECEPTOR INTERACTIONS

The development of *in silico* testing strategies aimed at facilitating the accurate prediction of potential interactions between known or putative chemicals and various molecular targets, as well as associated adverse effects, is ongoing for several decades and remains a significant challenge. Applications of these computational tools range from compounds prioritization in order to reduce the time, cost and animal use associated with the experimental evaluation of a large number of compounds, to help in the rational design of safer compounds. Historically, a number of methods for predicting chemical toxicity or activity have been developed on the basis of quantitative structure-activity relationship (QSAR) models (79). However, these ligand-based approaches require a high chemical similarity between target chemicals and reference compounds and thus can often fail for molecules with significantly different scaffolds. To overcome this limitation, protein structure-based methods, also called target-based methods, have been developed, benefiting from the availability of three-dimensional structures of cellular targets. Indeed, the ever-expanding number of structures of toxicant targets available in the PDB, such as NR LBDs in both their unbound and bound forms, provides a wealth of information on molecular recognition events, instrumental for predicting their interactions with chemicals. A plethora of computational methods aiming at modeling ligand-protein complexes based on experimentally
determined structures have been developed (80, 81), and have been applied to toxicological profiling of chemical compounds (79, 82, 83). These approaches include molecular docking, molecular dynamics (MD) simulations, and to a minor extent Monte Carlo (MC) simulations. Because of their own limitations and to take advantage of their complementarity, these methods are often used in combination and/or integrated with ligand-based methods to enhance overall predictive capabilities (84–86). Being less computationally demanding, molecular docking strategy is the most widely used in virtual high-throughput screening. For instance, it has been applied for endocrine disruption prediction of thousands of chemicals with potential for human exposure on various NRs (87–89). A number of docking servers have also been implemented into user-friendly tools for predicting the toxic potential of drugs, chemicals and natural products. The OpenVirtualToxLab (http://www.virtualtoxlab.org) is intended to predict the toxic effects on 16 biological targets, including NRs involved in endocrine and metabolic disruption (90), while the Endocrine Disruptome (http://endocrinedisruptome.ki.si) is an open-source project allowing users to assess the endocrine-disrupting potential of compounds against 14 NRs involved in several biological processes (91). The server EDMon (Endocrine Disruptor Monitoring, http://edmon.cbs.cnrs.fr) has been developed to screen EDCs against different NRs by modeling their complexes and estimating binding affinities (31, 92).

Although molecular docking approaches yield reasonable predictions, some impediments limiting their accuracy still remains, including the difficulty to predict conformational changes upon ligand binding or the inherent dynamics of proteins that remains difficult to manage in high-throughput docking campaigns. The ability to address the dynamic conformational changes of the protein target occurring upon ligand binding has been one of the most relevant and challenging issues in molecular modeling since early times (93). To take this fourth dimension into consideration, docking procedures using structure ensembles instead of single conformations have been developed. For example, the EARDB server (http://eardb.schanglab.org.cn/) employs a multiple conformation-based docking approach using all complex structures of ERs and AR available in the PDB, allowing exploring conformational diversity and thus enhancing docking accuracy (94). Similarly, an optimized structure-based virtual screening method using multiple functional states of PPARγ has been proposed to screen
and prioritize potential EDCs against this NR (95). Alternatively, MD simulations offer a valuable means to explore the conformational diversity of biomolecules, capturing key motions related to ligand binding and significantly improving docking accuracy. For instance, MD simulations allowed generating non-crystallized conformations of AR, thereby improving virtual screening and toxicology predictions (96). MD simulations have also been used to study the interaction mechanism of different bisphenol derivatives with various human NRs (97, 98), or to identify new potential thyroid hormone disrupting chemicals from the Tox21 inventory whose activities were subsequently validated through *in vitro* experiments (99). In addition to the accurate evaluation of protein dynamics, other weaknesses of current computational predictive tools are the lack of knowledge regarding the proper assessment of protein-ligand interactions involving “exotic” atoms such as halogens or metals that are often present in toxicants, or the failure to take into account the possibility for simultaneous binding of several molecules, in a cooperative and/or allosteric fashion. More experimental structures will be necessary to reflect the conformational landscape of the target receptors in a more comprehensive manner and to help in training new dedicated docking tools. Finally, deep learning-based protein structure prediction procedures, such as AlphaFold2 (https://alphafold.ebi.ac.uk/) (100) and RoseTTAfold (https://robetta.bakerlab.org/) (101), have been proposed as new powerful tools to predict the three-dimensional structure of proteins with high accuracy on a large scale. The development of protocols exploiting machine learning and artificial intelligence based models are ongoing for the prediction of protein-ligand interactions (102–106).

## CONCLUDING REMARKS

Understanding the mode of action of toxicants is crucial for devising effective strategies to alleviate their adverse effects on living organisms. Structural biology can play a central role in this effort by allowing visualization of the atomic details of their intricate interactions with molecular targets within cells. This three-dimensional information can be extremely useful in guiding the rational design of safer alternatives with reduced interference with biological targets or in helping the development of *in silico* alternative detection and characterization methods. The examples outlined in this review highlight advances in our understanding of the mode of action of EDCs through binding to their
primary targets AHR and NRs. The application of structure-based studies in toxicology and
environmental sciences extends well beyond the investigation of these receptors, yet, while structures
are available for multiple NR-toxicant complexes, such structural data for other potential toxicant
targets are scarce. Recent advances in cryo-EM instruments and image processing algorithms have
revolutionized the field of structural biology, allowing for the determination of high-resolution
structures of numerous protein targets that were historically challenging to crystallize, including
membrane proteins or large macromolecular assemblies. Notably, recent cryo-EM studies on ion-
channels (e.g. ryanodine and nicotinic acetylcholine receptors) in complex with insecticides have shed
light on their mechanisms of action, providing accurate templates for structure-based insecticide
screening and the rational design of selective molecules less detrimental to non-targeted living
organisms (107, 108). As technologies continue to advance, from biological sample preparation to
instrumentation, computational resources and artificial intelligence, we can anticipate that structural
biology approaches will be more easily and systematically applied to a higher number of biological
targets, thus providing a solid framework for understanding, predicting and combating the impact of
environmental toxicants on human health and ecosystems.

DISCLOSURE STATEMENT

The authors are not aware of any affiliations, memberships, funding, or financial holdings that might
be perceived as affecting the objectivity of this review.

ACKNOWLEDGEMENTS

This work was supported by the National Center for Scientific Research (CNRS), the National
Institute of Health and Medical Research (Inserm) and the University of Montpellier.
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<figure><img src="image_3.png" /><figcaption>**Figure 1:** Canonical signaling routes of toxicant targets discussed in this review. (a) Classical signaling pathways of NRs and AHR. Functional organization of NRs (b) and AHR (c). Both receptors contain a DNA-binding domain (DBD or bHLH), a ligand-binding domain (LBD or PAS-B) and transactivation domains (AF-1 and AF-2, activation function 1 and 2 in NRs). AKT: protein kinase B; Cav-1: caveolin-1; PI3K: phosphoinositide-3-kinase; Src: sarcoma tyrosine kinase; TG: target gene.</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>**Figure 2:** Endogenous estrogens and xenoestrogens use diverse binding modes. **a.** Overall structure of ERα LBD bound to estradiol (blue sticks) and a coactivator-derived peptide (green helix) showing the active position of helix H12 (orange helix). **b-e.** Close-up views of the ligand-binding pocket of ERα in complex with estradiol (E2) (**b**), diethylstilbestrol (DES) (**c**), α-zearalenol (αZA) (**d**) and bisphenol-A (BPA) (**e**). Hydrogen bonds with key residues are displayed in dashed lines.</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>**Figure 3: Covalent binding of various EDCs to NRs.** Close-up views of the ligand-binding pockets of RXRα (a) and PPARγ (b) in complex with tributyltin (TBT), and of PXR bound to fipronil (FIP) (c). The ligands and cysteine residues involved in covalent bonds are shown as sticks.</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>**Figure 4: Multiple ligand binding and cooperativity in NRs.** Close-up views of the ligand-binding pockets of PPARγ (a) and PXR (b) in complex with two molecules of phthalate MEHP and a mixture of 17α-ethinylestradiol (EE2) and *trans*-nonachlor (TNC), respectively. In (b), residues F288, W299 and Y306 forming the aromatic π-trap in PXR are shown as sticks. (c) Transactivation assay showing synergistic PXR activation by a mixture of EE2 and TNC.</figcaption></figure>
<figure><img src="image_7.png" /></figure>

**Figure 5: AHR structure.** (a) Overall structure of the AHR-Hsp90-XAP2 cytosolic complex. (b)

Overall structure of the ligand-binding PAS-B domain in complex with B[a]P (green sticks). (c)

Close-up view of the B[a]P binding site. Amino acid residues in contact with the ligand are shown as sticks. Dashed lines depict aromatic π-bonds. The grey zone delimits the bipartite ligand-binding pocket with a primary binding site with B[a]P bound, and an empty secondary binding site close to helix Cα.