Access Path to the Ligand Binding Pocket May Play a Role in Xenobiotics Selection by AhR.

Understanding of multidrug binding at the atomic level would facilitate drug design and strategies to modulate drug metabolism, including drug transport, oxidation, and conjugation. Therefore we explored the mechanism of promiscuous binding of small molecules by studying the ligand binding domain, the PAS-B domain of the aryl hydrocarbon receptor (AhR). Because of the low sequence identities of PAS domains to be used for homology modeling, structural features of the widely employed HIF-2alpha and a more recent suitable template, CLOCK were compared. These structures were used to build AhR PAS-B homology models. We performed molecular dynamics simulations to characterize dynamic properties of the PAS-B domain and the generated conformational ensembles were employed in in silico docking. In order to understand structural and ligand binding features we compared the stability and dynamics of the promiscuous AhR PAS-B to other PAS domains exhibiting specific interactions or no ligand binding function. Our exhaustive in silico binding studies, in which we dock a wide spectrum of ligand molecules to the conformational ensembles, suggest that ligand specificity and selection may be determined not only by the PAS-B domain itself, but also by other parts of AhR and its protein interacting partners. We propose that ligand binding pocket and access channels leading to the pocket play equally important roles in discrimination of endogenous molecules and xenobiotics

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Discrimination of xenobiotics from endogenous molecules may be realized by access pathways to the binding pockets, acting as filters.

<p>(A) Based on visual examination of our simulations, two putative ligand entry pores (indicated with arrows) can be identified in the conformations of the AhR PAS B domain. Both of these regions are involved in Hsp90 binding (purple segments) suggesting that Hsp90 can directly influence the accessibility of the pores and potentially participate in ligand selection (cyan segment indicates XAP2 binding residues.) (B, C) A role of access pathways (indicated on the protein structures by blue arrows) in ligand selection has been described for nuclear receptors (B: PXR, PDBID:3R8D) and also for CYPs (C: bacterial CYP101D2, PDBID:3NV6). (D) Similarly, a substrate selective access pathway from the cytoplasmic leaflet of the membrane to the low affinity binding pocket of ABC multidrug transporters localized in the outer membrane leaflet may play a role in xenobiotics recognition (<i>T</i>. <i>maritima</i> TM287/288, PDBID:4Q4J). Blue arrows: ligand/substrate entry pathway; blue circle: location of the ligand binding pocket inside the structure.</p

The contact maps of the homology models based on different templates are similar.

<p>The network of the interacting residues was determined by the Elastic Network Analysis Module of the MDAnalysis toolkit for the HIF-2α (A) and CLOCK (B) X-ray structures and AhR homology models based on the HIF-2α (C) and CLOCK (D) templates. Nodes are colored according to the main secondary structural modules in AhR (cyan: β-sheet, red: α-helix, green: ‘belt’ region, orange: small helices in the ‘belt’ region). On the C and D panels the blue edges represent interactions specific to either AhR_HIF or AhR_CLOCK compared to each other.</p

Melting temperatures of the homology models are between those of the templates.

<p>(A) Melting points as maxima of heat capacity curves were calculated from replica exchange DMD simulations using WHAM. (B) The unfolding events connected to the two peaks were determined and representative AhR_CLOCK conformations observed realized below and above the melting temperatures are shown as examples. The presented conformations are centroids of the largest clusters generated by clustering based on pairwise RMSD of conformations visited at 0.6116, 0.6604, and 0.6862 temperature units (indicated by arrows).</p

Docking to conformational ensembles does not show discriminative differences between binding of agonists with high and low affinity.

<p>Docking of molecules to each conformation from simulations was performed for three ensembles per setup using AutoDock Vina. The number of conformations that could accommodate a given molecule in its binding pocket was counted and depicted for each drug as a colored box with a size of that number. The percentage of these conformations compared to the possible maxima (2,500 and 5,000 in the case of MD and DMD, respectively) is indicated above the bars. Green colors indicate drugs with high affinity, while the other colors depict low affinity ligands or non-binders.</p

The belt region and the loops between secondary structural elements are the most flexible.

<p>Equilibrium simulations were performed using AhR_HIF and AhR_CLOCK models employing GROMOS and CHARMM force fields and discrete molecular dynamics (DMD, 0.53 temperature units). (A, B) Deviation from the starting conformation is characterized by RMSD values. Curves show the average value and colored bands correspond to the standard deviation from 3 independent simulations. (C, D) RMSF is calculated for individual residues for the characterization of protein flexibility.</p

Low and high affinity ligands dock to similar set of frames.

<p>The number of conformations with relevant docking poses was counted in every ensemble, binned, and plotted for one of the MD CHARMM36 AhR_CLOCK simulations as an example. In this simulation the number of the relevant docked poses of low affinity molecules (except Leflunomid) is significantly lower. Green colors indicate drugs with high affinity, while the other colors depict low affinity ligands or non-binders. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0146066#pone.0146066.t002" target="_blank">Table 2</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0146066#pone.0146066.s003" target="_blank">S3 Fig</a> for details on these molecules.</p

The size of the binding pocket is sufficiently large for ligand binding in CHARMM and DMD simulations, while significantly decreased or missing using the GROMOS force field.

<p>Average ligand binding pocket volume calculated for each conformation from 3–3 independent GROMOS, CHARMM, and DMD (0.53 temperature units) simulations are plotted for the HIF-2α (A), CLOCK (B), and AhR models (C, D). The distribution of the volume values are shown on the right of the graphs.</p