Agonist and antagonist binding to the nuclear vitamin D receptor: dynamics, mutation effects and functional implications

Deciphering the importance of MD descriptors in designing Vitamin D Receptor agonists and antagonists using machine learning

The Vitamin D Receptor (VDR) ligand-binding domain undergoes conformation change upon the binding of VDR agonists/antagonists. Helix 12 ((H)12) is one of the important helices at VDR ligand binding and its conformational changes are controlled by the binding of agonists and antagonists molecules. Various molecular modeling studies are available to explain the agonistic and antagonistic activity of vitamin D analogs. In this work, for the first time, we attempted to generate a machine learning model with fingerprints, 2D, 3D and MD descriptors that are specific to Vitamin D analogs and VDR. Initially, 2D and 3D descriptors and fingerprints of 1003 vitamin D analogs were calculated using CDK and RDKit. The machine learning model was generated using descriptors and fingerprints. Further, 80 Vitamin D analogs (40 VDR agonists + 40 VDR antagonists) were docked in the VDR active site. 50ns MD simulation was performed for each protein-ligand complex. Different MD descriptors such as Solvent Accessible Surface Area (SASA), radius of gyration, PC1 and PC2 were calculated and considered along with CDK and RDKit descriptors as features for machine learning calculations. A few other descriptors that are related to VDR conformational changes such as conformation of the (H)12, the angle at kink were considered for machine learning model generation. It was observed that the descriptors calculated from VDR conformational changes i) were able to distinguish between agonists and antagonists ii) provide key and comprehensive information about the unique binding characteristics of agonists and antagonists iii) provide a strong basis for the machine learning model generation. Overall, this study attempts the utilization of descriptors that are specific to a protein conformation will be helpful for the generation of an efficient machine learning model.

Review of in silico studies dedicated to the nuclear receptor family: Therapeutic prospects and toxicological concerns

Being in the center of both therapeutic and toxicological concerns, NRs are widely studied for drug discovery application but also to unravel the potential toxicity of environmental compounds such as pesticides, cosmetics or additives. High throughput screening campaigns (HTS) are largely used to detect compounds able to interact with this protein family for both therapeutic and toxicological purposes. These methods lead to a large amount of data requiring the use of computational approaches for a robust and correct analysis and interpretation. The output data can be used to build predictive models to forecast the behavior of new chemicals based on their in vitro activities. This atrticle is a review of the studies published in the last decade and dedicated to NR ligands in silico prediction for both therapeutic and toxicological purposes. Over 100 articles concerning 14 NR subfamilies were carefully read and analyzed in order to retrieve the most commonly used computational methods to develop predictive models, to retrieve the databases deployed in the model building process and to pinpoint some of the limitations they faced.

Mechanism of Vitamin D Receptor Ligand-Binding Domain Regulation Studied by gREST Simulations

The vitamin D receptor ligand-binding domain (VDR-LBD) undergoes conformational changes upon ligand binding. In this nuclear receptor family, agonistic or antagonistic activities are controlled by the conformation of the helix (H)12. However, all crystal structures of VDR-LBD reported to date correspond to the active H12 conformation, regardless of agonist/antagonist binding. To understand the mechanism of VDR-LBD regulation structurally, conformational samplings of agonist- and antagonist-bound rat VDR-LBD were performed using the generalized replica exchange with solute tempering (gREST) method. The gREST simulations demonstrated different structural responses of rat VDR-LBD to agonist or antagonist binding, whereas in conventional molecular dynamics simulations, the conformation was the same as that of the crystal structures, regardless of agonist/antagonist binding. In the gREST simulations, a spontaneous conformational change of H12 was observed only for the antagonist complex. The different responses to agonist/antagonist binding were attributed to hydrophobic core formation at the ligand-binding pocket and cooperative rearrangements of H11. The gREST method can be applied to the examination of structure-activity relationships for multiple VDR-LBD ligands.

Ligand-based pharmacophore modeling and docking studies on vitamin D receptor inhibitors

In recent years, pharmacophore modeling and molecular docking approaches have been extensively used to characterize the structural requirements and explore the conformational space of a ligand in the binding pocket of the selected target protein. Herein, we report a pharmacophore modeling and molecular docking of 45 compounds comprising of the indole scaffold as vitamin D receptor (VDR) inhibitors. Based on the selected best hypothesis (DRRRR.61), an atom-based three-dimensional quantitative structure-activity relationships model was developed to rationalize the structural requirement of biological activity modulating components. The developed model predicted the binding affinity for the training set and test set with R² _(training)  = 0.8869 and R² _(test)  = 0.8139, respectively. Furthermore, molecular docking and dynamics simulation were performed to understand the underpinning of binding interaction and stability of selected VDR inhibitors in the binding pocket. In conclusion, the results presented here, in the form of functional and structural data, agreed well with the proposed pharmacophores and provide further insights into the development of novel VDR inhibitors with better activity.

Computational insights into the interaction mechanisms of estrogen-related receptor alpha with endogenous ligand cholesterol

Estrogen-related receptor alpha (ERRα) has attracted increasing concerns. ERRα, orphan nuclear receptor, plays important roles in energy metabolism. Therefore, small molecule agonists of ERRα could be a potential therapeutic strategy in the treatment of metabolic diseases such as diabetes. Recently, Wei et al. identified cholesterol as the endogenous agonist of ERRα. However, the detailed molecular mechanism of cholesterol bound with ERRα remains ambiguous. Thus, in this study molecular docking and molecular dynamics (MD) simulations were performed to characterize how cholesterol affects the behavior of ERRα. Based on the results, we found that a proven residue Phe232 and others including Leu228, Glu235, Arg276, and Phe399 were key residues to ligand binding. A hydrogen-bonding interaction between cholesterol and Glu235 ensured the orientation of the ligand in the binding pocket, while hydrophobic interactions between cholesterol and the above-mentioned residues promoted the stability of ERRα-cholesterol complex. In the presence of the proliferator-activated receptor γ coactivator 1α (PGC-1α), the cholesterol-ERRα interaction became more stable. Interestingly, we observed that cholesterol facilitated the binding of ERRα with its coactivator PGC-1α via stabilizing the conformation of helix 12 and the interaction surface of ERRα/PGC-1α. Overall, these findings would be valuable for the future rational design of novel ERRα agonists.

The conformational dynamics of H2-H3n and S2-H6 in gating ligand entry into the buried binding cavity of vitamin D receptor

Crystal structures of holo vitamin D receptor (VDR) revealed a canonical conformation in which the ligand is entrapped in a hydrophobic cavity buried in the ligand-binding domain (LBD). The mousetrap model postulates that helix 12 is positioned away from the domain to expose the interior cavity. However, the extended form of helix 12 is likely due to artifacts during crystallization. In this study, we set out to investigate conformational dynamics of apo VDR using molecular dynamics simulation on microsecond timescale. Here we show the neighboring backbones of helix 2-helix 3n and beta strand 2-helix 6 of LBD, instead of the helix 12, undergo large-scale motion, possibly gating the entrance of ligand to the ligand binding domain. Docking analysis to the simulated open structure of VDR with the estimated free energy of -37.0 kJ/mol, would emphasise the role of H2-H3n and S2-H6 in facilitating the entrance of calcitriol to the LBD of VDR.

The identification of nuclear receptors associated with hepatic steatosis to develop and extend adverse outcome pathways

The development of adverse outcome pathways (AOPs) is becoming a key component of twenty-first century toxicology. AOPs provide a conceptual framework that links the molecular initiating event to an adverse outcome through organized toxicological knowledge, bridging the gap from chemistry to toxicological effect. As nuclear receptors (NRs) play essential roles for many physiological processes within the body, they are used regularly as drug targets for therapies to treat many diseases including diabetes, cancer and neurodegenerative diseases. Due to the heightened development of NR ligands, there is increased need for the identification of related AOPs to facilitate their risk assessment. Many NR ligands have been linked specifically to steatosis. This article reviews and summarizes the role of NR and their importance with links between NR examined to identify plausible putative AOPs. The following NRs are shown to induce hepatic steatosis upon ligand binding: aryl hydrocarbon receptor, constitutive androstane receptor, oestrogen receptor, glucocorticoid receptor, farnesoid X receptor, liver X receptor, peroxisome proliferator-activated receptor, pregnane X receptor and the retinoic acid receptor. A preliminary, putative AOP was formed for NR binding linked to hepatic steatosis as the adverse outcome.

Relationship of structure and function of DNA-binding domain in vitamin D receptor

While the structure of the DNA-binding domain (DBD) of the vitamin D receptor (VDR) has been determined in great detail, the roles of its domains and how to bind the motif of its target genes are still under debate. The VDR DBD consists of two zinc finger modules and a C-terminal extension (CTE), at the end of the C-terminal of each structure presenting α-helix. For the first zinc finger structure, N37 and S-box take part in forming a dimer with 9-cis retinoid X receptor (RXR), while V26, R50, P-box and S-box participate in binding with VDR response elements (VDRE). For the second zinc finger structure, P61, F62 and H75 are essential in the structure of the VDR homodimer with the residues N37, E92 and F93 of the downstream of partner VDR, which form the inter-DBD interface. T-box of the CTE, especially the F93 and I94, plays a critical role in heterodimerization and heterodimers-VDRE binding. Six essential residues (R102, K103, M106, I107, K109, and R110) of the CTE α-helix of VDR construct one interaction face, which packs against the DBD core of the adjacent symmetry mate. In 1,25(OH)2D3-activated signaling, the VDR-RXR heterodimer may bind to DR3-type VDRE and ER9-type VDREs of its target gene directly resulting in transactivation and also bind to DR3-liked nVDRE of its target gene directly resulting in transrepression. Except for this, 1α,25(OH)2D3 ligand VDR-RXR may bind to 1αnVDRE indirectly through VDIR, resulting in transrepression of the target gene. Upon binding of 1α,25(OH)2D3, VDR can transactivate and transrepress its target genes depending on the DNA motif that DBD binds.