Mechanism of RGD-conjugated nanodevice binding to its target protein integrin αVß3 by atomistic molecular dynamics and machine learning.

Active targeting strategies have been proposed to enhance the selective uptake of nanoparticles (NPs) by diseased cells, and recent experimental findings have proven the effectiveness of this approach. However, no mechanistic studies have yet revealed the atomistic details of the interactions between ligand-activated NPs and integrins. As a case study, here we investigate, by means of advanced molecular dynamics simulations (MD) and machine learning methods (namely equilibrium MD, binding free energy calculations and training of self-organized maps), the interaction of a cyclic-RGD-conjugated PEGylated TiO2 NP (the nanodevice) with the extracellular segment of integrin αVß3 (the target), the latter experimentally well-known to be over-expressed in several solid tumors. Firstly, we proved that the cyclic-RGD ligand binding to the integrin pocket is established and kept stable even in the presence of the cumbersome realistic model of the nanodevice. In this respect, the unsupervised machine learning analysis allowed a detailed comparison of the ligand/integrin binding in the presence and in the absence of the nanodevice, which unveiled differences in the chemical features. Then, we discovered that unbound cyclic RGDs conjugated to the NP largely contribute to the interactions between the nanodevice and the integrin. Finally, by increasing the density of cyclic RGDs on the PEGylated TiO2 NP, we observed a proportional enhancement of the nanodevice/target binding. All these findings can be exploited to achieve an improved targeting selectivity and cellular uptake, and thus a more successful clinical outcome.

The AhR Signaling Mechanism: A Structural Point of View.

The Aryl hydrocarbon Receptor (AhR) is a well-known sensor of xenobiotics; moreover, it is considered a promising drug target as it is involved in the regulation of many patho-physiological processes. For these reasons the study of its ligand-activated transcription mechanism has stimulated several studies for over twenty years. In this review we highlight the key role of molecular structural information in understanding the different steps of the signaling mechanism. The architecture of the AhR cytosolic complex, encompassing the hsp90 chaperone protein and the XAP2 and p23 co-chaperones, has become available in the last year thanks to Cryo-EM experiments. The structure of the AhR ligand-binding (PAS-B) domain has remained elusive for a long time; it has been predicted by homology modelling, based on known PAS systems, and its ligand-bound forms were modelled through ligand molecular docking. Although very recently some structural information on this domain has become available, considerable efforts are still needed to determine the binding geometries of the AhR key ligands by experimental high-resolution studies. On the other hand, the dimeric structure of AhR with the ARNT protein, bound to the specific DNA responsive element, was partially determined by X-ray crystallography and it was completed by homology modelling. On the whole the current structural knowledge of the main protein complexes that form over the AhR mechanism opens the way to confirm and further investigate the main steps of the proposed ligand-activated transcription mechanism of the AhR.

Molecular Dynamics for the Optimal Design of Functionalized Nanodevices to Target Folate Receptors on Tumor Cells.

Atomistic details on the mechanism of targeting activity by biomedical nanodevices of specific receptors are still scarce in the literature, where mostly ligand/receptor pairs are modeled. Here, we use atomistic molecular dynamics (MD) simulations, free energy calculations, and machine learning approaches on the case study of spherical TiO2 nanoparticles (NPs) functionalized with folic acid (FA) as the targeting ligand of the folate receptor (FR). We consider different FA densities on the surface and different anchoring approaches, i.e., direct covalent bonding of FA γ-carboxylate or through polyethylene glycol spacers. By molecular docking, we first identify the lowest energy conformation of one FA inside the FR binding pocket from the X-ray crystal structure, which becomes the starting point of classical MD simulations in a realistic physiological environment. We estimate the binding free energy to be compared with the existing experimental data. Then, we increase complexity and go from the isolated FA to a nanosystem decorated with several FAs. Within the simulation time framework, we confirm the stability of the ligand-receptor interaction, even in the presence of the NP (with or without a spacer), and no significant modification of the protein secondary structure is observed. Our study highlights the crucial role played by the spacer, FA protonation state, and density, which are parameters that can be controlled during the nanodevice preparation step.

Drug Design in the Exascale Era: A Perspective from Massively Parallel QM/MM Simulations.

The initial phases of drug discovery - in silico drug design - could benefit from first principle Quantum Mechanics/Molecular Mechanics (QM/MM) molecular dynamics (MD) simulations in explicit solvent, yet many applications are currently limited by the short time scales that this approach can cover. Developing scalable first principle QM/MM MD interfaces fully exploiting current exascale machines - so far an unmet and crucial goal - will help overcome this problem, opening the way to the study of the thermodynamics and kinetics of ligand binding to protein with first principle accuracy. Here, taking two relevant case studies involving the interactions of ligands with rather large enzymes, we showcase the use of our recently developed massively scalable Multiscale Modeling in Computational Chemistry (MiMiC) QM/MM framework (currently using DFT to describe the QM region) to investigate reactions and ligand binding in enzymes of pharmacological relevance. We also demonstrate for the first time strong scaling of MiMiC-QM/MM MD simulations with parallel efficiency of ∼70% up to >80,000 cores. Thus, among many others, the MiMiC interface represents a promising candidate toward exascale applications by combining machine learning with statistical mechanics based algorithms tailored for exascale supercomputers.

TCDD-Induced Allosteric Perturbation of the AhR:ARNT Binding to DNA.

The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that mediates the biological and toxicological effects of structurally diverse chemicals, including halogenated aromatic hydrocarbons. In this work, we investigate the effects of the binding of the AhR prototypical ligand, TCDD, on the stability of the AhR:ARNT complex, as well as the mechanisms by which ligand-induced perturbations propagate to the DNA recognition site responsible for gene transcription. To this aim, a reliable structural model of the overall quaternary structure of the AhR:ARNT:DRE complex is proposed, based on homology modelling. The model shows very good agreement with a previous one and is supported by experimental evidence. Moreover, molecular dynamics simulations are performed to compare the dynamic behaviour of the AhR:ARNT heterodimer in the presence or absence of the TCDD. Analysis of the simulations, performed by an unsupervised machine learning method, shows that TCDD binding to the AhR PASB domain influences the stability of several inter-domain interactions, in particular at the PASA-PASB interface. The inter-domain communication network suggests a mechanism by which TCDD binding allosterically stabilizes the interactions at the DNA recognition site. These findings may have implications for the comprehension of the different toxic outcomes of AhR ligands and drug design.

Metadynamics simulations for the investigation of drug loading on functionalized inorganic nanoparticles.

Inorganic nanoparticles show promising properties that allow them to be efficiently used as drug carriers. The main limitation in this type of application is currently the drug loading capacity, which can be overcome with a proper functionalization of the nanoparticle surface. In this study, we present, for the first time, a computational approach based on metadynamics to estimate the binding free energy of the doxorubicin drug (DOX) to a functionalized TiO2 nanoparticle under different pH conditions. On a thermodynamic basis, we demonstrate the robustness of our approach to capture the overall mechanism behind the pH-triggered release of DOX due to environmental pH changes. Notably, binding free energy estimations align well with what is expected for a pH-sensitive drug delivery system. Based on our results, we envision the use of metadynamics as a promising computational tool for the rational design and in silico optimization of organic ligands with improved drug carrier properties.

Aryl Hydrocarbon Receptor-Dependent and -Independent Pathways Mediate Curcumin Anti-Aging Effects.

The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor whose activity can be modulated by polyphenols, such as curcumin. AhR and curcumin have evolutionarily conserved effects on aging. Here, we investigated whether and how the AhR mediates the anti-aging effects of curcumin across species. Using a combination of in vivo, in vitro, and in silico analyses, we demonstrated that curcumin has AhR-dependent or -independent effects in a context-specific manner. We found that in Caenorhabditis elegans, AhR mediates curcumin-induced lifespan extension, most likely through a ligand-independent inhibitory mechanism related to its antioxidant activity. Curcumin also showed AhR-independent anti-aging activities, such as protection against aggregation-prone proteins and oxidative stress in C. elegans and promotion of the migratory capacity of human primary endothelial cells. These AhR-independent effects are largely mediated by the Nrf2/SKN-1 pathway.

PathDetect-SOM: A Neural Network Approach for the Identification of Pathways in Ligand Binding Simulations.

Understanding the process of ligand-protein recognition is important to unveil biological mechanisms and to guide drug discovery and design. Enhanced-sampling molecular dynamics is now routinely used to simulate the ligand binding process, resulting in the need for suitable tools for the analysis of large data sets of binding events. Here, we designed, implemented, and tested PathDetect-SOM, a tool based on self-organizing maps to build concise visual models of the ligand binding pathways sampled along single simulations or replicas. The tool performs a geometric clustering of the trajectories and traces the pathways over an easily interpretable 2D map and, using an approximate transition matrix, it can build a graph model of concurrent pathways. The tool was tested on three study cases representing different types of problems and simulation techniques. A clear reconstruction of the sampled pathways was derived in all cases, and useful information on the energetic features of the processes was recovered. The tool is available at https://github.com/MottaStefano/PathDetect-SOM.

Metadynamics-Based Approaches for Modeling the Hypoxia-Inducible Factor 2α Ligand Binding Process.

Several methods based on enhanced-sampling molecular dynamics have been proposed for studying ligand binding processes. Here, we developed a protocol that combines the advantages of steered molecular dynamics (SMD) and metadynamics. While SMD is proposed for investigating possible unbinding pathways of the ligand and identifying the preferred one, metadynamics, with the path collective variable (PCV) formalism, is suggested to explore the binding processes along the pathway defined on the basis of SMD, by using only two CVs. We applied our approach to the study of binding of two known ligands to the hypoxia-inducible factor 2α, where the buried binding cavity makes simulation of the process a challenging task. Our approach allowed identification of the preferred entrance pathway for each ligand, highlighted the features of the bound and intermediate states in the free-energy surface, and provided a binding affinity scale in agreement with experimental data. Therefore, it seems to be a suitable tool for elucidating ligand binding processes of similar complex systems.

Reconstruction of ARNT PAS-B Unfolding Pathways by Steered Molecular Dynamics and Artificial Neural Networks.

Several experimental studies indicated that large conformational changes, including partial domain unfolding, have a role in the functional mechanisms of the basic helix loop helix Per/ARNT/SIM (bHLH-PAS) transcription factors. Recently, single-molecule atomic force microscopy (AFM) revealed two distinct pathways for the mechanical unfolding of the ARNT PAS-B. In this work we used steered molecular dynamics simulations to gain new insights into this process at an atomistic level. To reconstruct and classify pathways sampled in multiple simulations, we designed an original approach based on the use of self-organizing maps (SOMs). This led us to identify two types of unfolding pathways for the ARNT PAS-B, which are in good agreement with the AFM findings. Analysis of average forces mapped on the SOM revealed a stable conformation of the PAS-B along one pathway, which represents a possible structural model for the intermediate state detected by AFM. The approach here proposed will facilitate the study of other signal transmission mechanisms involving the folding/unfolding of PAS domains.

NURA: A curated dataset of nuclear receptor modulators.

Nuclear receptors (NRs) are key regulators of human health and constitute a relevant target for medicinal chemistry applications as well as for toxicological risk assessment. Several open databases dedicated to small molecules that modulate NRs exist; however, depending on their final aim (i.e., adverse effect assessment or drug design), these databases contain a different amount and type of annotated molecules, along with a different distribution of experimental bioactivity values. Stemming from these considerations, in this work we aim to provide a unified dataset, NURA (NUclear Receptor Activity) dataset, collecting curated information on small molecules that modulate NRs, to be intended for both pharmacological and toxicological applications. NURA contains bioactivity annotations for 15,247 molecules and 11 selected NRs, and it was obtained by integrating and curating data from toxicological and pharmacological databases (i.e., Tox21, ChEMBL, NR-DBIND and BindingDB). Our results show that NURA dataset is a useful tool to bridge the gap between toxicology- and medicinal-chemistry-related databases, as it is enriched in terms of number of molecules, structural diversity and covered atomic scaffolds compared to the single sources. To the best of our knowledge, NURA dataset is the most exhaustive collection of small molecules annotated for their modulation of the chosen nuclear receptors. NURA dataset is intended to support decision-making in pharmacology and toxicology, as well as to contribute to data-driven applications, such as machine learning. The dataset and the data curation pipeline can be downloaded free of charge on Zenodo at the following DOI: https://doi.org/10.5281/zenodo.3991561.

An aryl hydrocarbon receptor from the caecilian Gymnopis multiplicata suggests low dioxin affinity in the ancestor of all three amphibian orders.

The aryl hydrocarbon receptor (AHR) plays pleiotropic roles in the development and physiology of vertebrates in conjunction with xenobiotic and endogenous ligands. It is best known for mediating the toxic effects of dioxin-like pollutants such as 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). While most vertebrates possess at least one AHR that binds TCDD tightly, amphibian AHRs bind TCDD with very low affinity. Previous analyses of AHRs from Xenopus laevis (a frog; order Anura) and Ambystoma mexicanum (a salamander; order Caudata) identified three amino acid residues in the ligand-binding domain (LBD) that underlie low-affinity binding. In X. laevis AHR1ß, these are A354, A370, and N325. Here we extend the analysis of amphibian AHRs to the caecilian Gymnopis multiplicata, representing the remaining extant amphibian order, Gymnophiona. G. multiplicata AHR groups with the monophyletic vertebrate AHR/AHR1 clade. The LBD includes all three signature residues of low TCDD affinity, and a structural homology model suggests that its architecture closely resembles those of other amphibians. In transactivation assays, the EC50 for reporter gene induction by TCDD was 17.17 nM, comparable to X. laevis AhR1ß (26.23 nM) and Ambystoma AHR (34.09 nM) and dramatically higher than mouse AhR (0.13 nM), a trend generally reflected in direct measures of TCDD binding. These shared properties distinguish amphibian AHRs from the high-affinity proteins typical of both vertebrate groups that diverged earlier (teleost fish) and those that appeared more recently (other tetrapods). These findings suggest the hypothesis that AHRs with low TCDD affinity represent a characteristic that evolved in a common ancestor of all three extant amphibian groups.

The Cellular and Molecular Determinants of Naphthoquinone-Dependent Activation of the Aryl Hydrocarbon Receptor.

1,2-naphthoquinone (1,2-NQ) and 1,4-naphthoquinone (1,4-NQ) are clinically promising biologically active chemicals that have been shown to stimulate the aryl hydrocarbon receptor (AhR) signaling pathway, but whether they are direct or indirect ligands or activate the AhR in a ligand-independent manner is unknown. Given the structural diversity of AhR ligands, multiple mechanisms of AhR activation of gene expression, and species differences in AhR ligand binding and response, we examined the ability of 1,2-NQ and 1,4-NQ to bind to and activate the mouse and human AhRs using a series of in vitro AhR-specific bioassays and in silico modeling techniques. Both NQs induced AhR-dependent gene expression in mouse and human hepatoma cells, but were more potent and efficacious in human cells. 1,2-NQ and 1,4-NQ stimulated AhR transformation and DNA binding in vitro and was inhibited by AhR antagonists. Ligand binding analysis confirmed the ability of 1,2-NQ and 1,4-NQ to competitively bind to the AhR ligand binding cavity and the molecular determinants for interactions were predicted by molecular modeling methods. NQs were shown to bind distinctly differently from that of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and differences were also observed between species. Mutation of amino acid residues (F289, M334, and M342) involved in critical NQ:AhR binding interactions, decreased NQ- and AhR-dependent gene expression, consistent with a role for these residues in binding and activation of the AhR by NQs. These studies provide insights into the molecular mechanism of action of NQs and contribute to the development of emerging NQ-based therapeutics.

Transitional States in Ligand-Dependent Transformation of the Aryl Hydrocarbon Receptor into Its DNA-Binding Form.

The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that mediates the biological and toxicological effects of an AhR lacking the entire PASB structurally diverse chemicals, including halogenated aromatic hydrocarbons. Ligand-dependent transformation of the AhR into its DNA binding form involves a ligand-dependent conformational change, heat shock protein 90 (hsp90), dissociation from the AhR complex and AhR dimerization with the AhR nuclear translocator (ARNT) protein. The mechanism of AhR transformation was examined using mutational approaches and stabilization of the AhR:hsp90 complex with sodium molybdate. Insertion of a single mutation (F281A) in the hsp90-binding region of the AhR resulted in its constitutive (ligand-independent) transformation/DNA binding in vitro. Mutations of AhR residues within the Arg-Cys-rich region (R212A, R217A, R219A) and Asp371 (D371A) impaired AhR transformation without a significant effect on ligand binding. Stabilization of AhR:hsp90 binding with sodium molybdate decreased transformation/DNA binding of the wild type AhR but had no effect on constitutively active AhR mutants. Interestingly, transformation of the AhR in the presence of molybdate allowed detection of an intermediate transformation ternary complex containing hsp90, AhR, and ARNT. These results are consistent with a stepwise transformation mechanism in which binding of ARNT to the liganded AhR:hsp90 complex results in a progressive displacement of hsp90 and conversion of the AhR into its high affinity DNA binding form. The available molecular insights into the signaling mechanism of other Per-ARNT-Sim (PAS) domains and structural information on hsp90 association with other client proteins are consistent with the proposed transformation mechanism of the AhR.

Modeling the binding of diverse ligands within the Ah receptor ligand binding domain.

The Ah receptor (AhR) is a ligand-dependent transcription factor belonging to the basic helix-loop-helix Per-Arnt-Sim (bHLH-PAS) superfamily. Binding to and activation of the AhR by a variety of chemicals results in the induction of expression of diverse genes and production of a broad spectrum of biological and toxic effects. The AhR also plays important roles in several physiological responses, which has led it to become a novel target for the development of therapeutic drugs. Differences in the interactions of various ligands within the AhR ligand binding domain (LBD) may contribute to differential modulation of AhR functionality. We combined computational and experimental analyses to investigate the binding modes of a group of chemicals representative of major classes of AhR ligands. On the basis of a novel computational approach for molecular docking to the homology model of the AhR LBD that includes the receptor flexibility, we predicted specific residues within the AhR binding cavity that play a critical role in binding of three distinct groups of chemicals. The prediction was validated by site-directed mutagenesis and evaluation of the relative ligand binding affinities for the mutant AhRs. These results provide an avenue for understanding ligand modulation of the AhR functionality and for rational drug design.

Computational prediction and in vitro validation of VEGFR1 as a novel protein target for 2,3,7,8-tetrachlorodibenzo-p-dioxin.

The toxic manifestations of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), an environmental contaminant, primarily depend on its ability to activate aryl hydrocarbon receptor (AhR), which is a ligand-dependent transcription factor belonging to the superfamily of basic-helix-loop-helix DNA-binding proteins. In the present study, we aimed to identify novel protein receptor targets for TCDD using computational and in vitro validation experiments. Interestingly, results from computational methods predicted that Vascular Endothelial Growth Factor Receptor 1 (VEGFR1) could be one of the potential targets for TCDD in both mouse and humans. Results from molecular docking studies showed that human VEGFR1 (hVEGFR1) has less affinity towards TCDD compared to the mouse VEGFR1 (mVEGFR1). In vitro validation results showed that TCDD can bind and phosphorylate hVEGFR1. Further, results from molecular dynamic simulation studies showed that hVEGFR1 interaction with TCDD is stable throughout the simulation time. Overall, the present study has identified VEGFR1 as a novel target for TCDD, which provides the basis for further elucidating the role of TCDD in angiogenesis.

Exploring the PXR ligand binding mechanism with advanced Molecular Dynamics methods.

The Pregnane X Receptor (PXR) is a ligand-activated transcription factor belonging to the nuclear receptor family. PXR can bind diverse drugs and environmental toxicants with different binding modes, making it an intriguing target for drug discovery. Here we investigated the binding mechanism of the SR12813 ligand to elucidate the significant steps, from the ligand entrance pathway into the binding cavity, to the ligand-induced conformational changes, and to the exploration of its alternative binding geometries. We used the advanced Molecular Dynamics-based methods implemented in the BiKi suite and developed specific methodological approaches to overcome the complexity induced by the buried and flexible binding cavity. The adopted methods provided a full dynamic description of the binding event and allowed rationalization of the observed multiple binding modes. These results suggest that the same approach could be exploited for the study of other binding processes with similar characteristics.

Comparative In Vitro and In Silico Analysis of the Selectivity of Indirubin as a Human Ah Receptor Agonist.

The aryl hydrocarbon receptor (AhR) is a ligand-dependent transcription factor that modulates gene expression following its binding and activation by structurally diverse chemicals. Species differences in AhR functionality have been observed, with the mouse AhR (mAhR) and human AhR (hAhR) exhibiting significant differences in ligand binding, coactivator recruitment, gene expression and response. While the AhR agonist indirubin (IR) is a more potent activator of hAhR-dependent gene expression than the prototypical ligand 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), it is a significantly less potent activator of the mAhR. DNA binding analysis confirmed the greater potency/efficacy of IR in stimulating transformation/DNA binding of the hAhR in vitro and domain-swapping experiments demonstrated that the enhanced response to IR was primarily due to the hAhR ligand binding domain (LBD). Site-directed mutagenesis and functional analysis studies revealed that mutation of H326 and A349 in the mAhR LBD to the corresponding residues in the hAhR LBD significantly increased the potency of IR. Since these mutations had no significant effect on ligand binding, these residues likely contribute to an enhanced efficiency of transformation/DNA binding by IR-bound hAhR. Molecular docking to mAhR LBD homology models further elucidated the different roles of the A375V mutation in TCDD and IR binding, as revealed by [³H]TCDD competitive binding results. These results demonstrate the differential binding of structurally diverse ligands within the LBD of a given AhR and confirm that amino acid differences within the LBD of AhRs contribute to significant species differences in ligand response.

In vitro toxicity and in silico docking analysis of two novel selective AH-receptor modulators.

The mediator of dioxin toxicity, aryl hydrocarbon receptor (AHR), has also important physiological functions. Selective AHR modulators (SAHRMs) share some effects of dioxins, except for their marked toxicity. We recently characterised toxicologically two novel SAHRMs, prodrugs IMA-08401 and IMA-07101 in rats, demonstrating that they are far less deleterious than the most toxic AHR-agonist, TCDD. Here, we analysed the in vitro toxicity and in silico AHR binding of the respective active, deacetylated metabolites, IMA-06201 (N-ethyl-N-phenyl-5-chloro-1,2-dihydro-4-hydroxy-1-methyl-2-oxo-quinoline-3-carboxamide) and IMA-06504 (N-(4-trifluoromethylphenyl)-1,2-dihydro-4-hydroxy-5-methoxy-1-methyl-2-oxo-quinoline-3-carboxamide). In H4IIE rat hepatoma cells, IMA-06201 and IMA-06504 induced CYP1A1 with comparable potencies and efficacies to those of TCDD. They had little effect on cell viability as assessed by LDH leakage and MTT reduction assays, and were not mutagenic in the Ames test, but IMA-06504 elicited a maximally 2.7-fold increase in micronuclei. Molecular docking simulations showed that similar to TCDD, they occupy the central region of AHR ligand binding cavity. Hence, while showing low to negligible in vitro toxicity, these novel SAHRMs bind to the AHR qualitatively in a similar fashion to TCDD, and appear comparably powerful AHR agonists. Combined with our earlier results demonstrating that they seem considerably less toxic in vivo than TCDD, these compounds are thus highly interesting new SAHRMs.

Ligand-induced perturbation of the HIF-2α:ARNT dimer dynamics.

Hypoxia inducible factors (HIFs) are transcription factors belonging to the basic helix-loop-helix PER-ARNT-SIM (bHLH-PAS) protein family with a role in sensing oxygen levels in the cell. Under hypoxia, the HIF-α degradation pathway is blocked and dimerization with the aryl hydrocarbon receptor nuclear translocator (ARNT) makes HIF-α transcriptionally active. Due to the common hypoxic environment of tumors, inhibition of this mechanism by destabilization of HIF-α:ARNT dimerization has been proposed as a promising therapeutic strategy. Following the discovery of a druggable cavity within the PAS-B domain of HIF-2α, research efforts have been directed to identify artificial ligands that can impair heterodimerization. Although the crystallographic structures of the HIF-2α:ARNT complex have elucidated the dimer architecture and the 0X3-inhibitor placement within the HIF-2α PAS-B, unveiling the inhibition mechanism requires investigation of how ligand-induced perturbations could dynamically propagate through the structure and affect dimerization. To this end, we compared evolutionary features, intrinsic dynamics and energetic properties of the dimerization interfaces of HIF-2α:ARNT in both the apo and holo forms. Residue conservation analysis highlighted inter-domain connecting elements that have a role in dimerization. Analysis of domain contributions to the dimerization energy demonstrated the importance of bHLH and PAS-A of both partners and of HIF-2α PAS-B domain in dimer stabilization. Among quaternary structure oscillations revealed by Molecular Dynamics simulations, the hinge-bending motion of the ARNT PAS-B domain around the flexible PAS-A/PAS-B linker supports a general model for ARNT dimerization in different heterodimers. Comparison of the HIF-2α:ARNT dynamics in the apo and 0X3-bound forms indicated a model of inhibition where the HIF-2α-PAS-B interfaces are destabilised as a result of water-bridged ligand-protein interactions and these local effects allosterically propagate to perturb the correlated motions of the domains and inter-domain communication. These findings will guide the design of improved inhibitors to contrast cell survival in tumor masses.