Comprehensive understanding about the binding of estrogen-related receptor alpha (ERR-α) to inverse agonists with the first-principles based theoretical methods

Albany State University, Albany GA

Investigators

Abstract

Comprehensive understanding about the binding of estrogen-related receptor alpha (ERR-α) to inverse agonists with the first-principles based theoretical methods ERR is one of three estrogen-related receptors (ERRs: ERR,- and -) that act as ligand-dependent transcription factors and share common target genes. Substantial expression of ERR was found in a few types of breast cancers, and ERR has thus been identified as a new target for breast cancer therapy. Breast cancers have become the most common cancers diagnosed in the United States and one of the leading cause of cancer deaths in women. Therefore, it is urgent to develop targeted therapy approaches for breast cancer treatment. A few classes of ERR inverse agonists were reported to inhibit tumor development and progression by disrupting the interaction of ERR with their coactivators (PGC-1 and PGC-1). The crystal structure for the complex ERR and an inverse agonist compound 1 (1-p-tolyl-1H-indol-3-ylmethyl- amine, the most studied inverse agonist) reveals the conformation change as compared with active apo-ERR in the absence of compound 1, and illustrates the major residues in the ligand binding pocket (LBP). However, the quantitative binding affinities for the key residues with the inverse agonist are unknown, and the binding free energy for ERR/compound 1 predicted by previous theoretical methods is far from the experimental one. Although the inverse agonist (thiadiazoleacrylamide, XCT790) and a few others also show strong inhibitory effects on the transcriptional activity of ERR, the crystal structures for the complexes of these inverse agonists with ERRα are still unavailable, which considerably limits an understanding about the mechanism by which these inverse agonists bind to ERRα, and inhibit the coactivation of ERRα and PGC-1. Overall, the binding mechanism of ERR to the potential inverse agonists has not been well understood in terms of binding modes and thermodynamics, and the hot spot residues that play an important role in the binding have not been well defined. On the basis of our preliminary study we hypothesized that a) a potential inverse agonist needs to strongly interact with the residues of H3, H5, H6/H7 loop, and H11 helix in the ligand binding domain (LBD) through hydrophobic and hydrogen bonding. b) it is essential for an effective inverse agonist to strongly bind with the aromatic ring cluster consisting of Phe328(H3), Phe495(H11), and Phe382(H5/H6 loop) as well as Leu500. The first-principles-based theoretical methods such as molecular dynamics (MD) simulation and binding affinity calculations are able to provide meaningful insights into the binding mechanism of ERR to the inverse agonists. Using large scale MD simulation with the updated force fields and a robust binding free energy strategy, the major goal of the project therefore is to gain a comprehensive understanding about the binding between ERR and a few inverse agonists in terms of binding modes and binding thermodynamics. To test our hypothesis and gain a comprehensive understanding the specific aims are 1) Aim 1. To explore the binding mode and binding free energy of ERRα to inverse agonists with the new force fields and more robust method, alchemical binding free energy in AMBER22. Large scale MD trajectory will be used to analyze the binding modes with 3- D PyMol and 2-D LigPlot visualization software, and to calculate binding affinity with MM/PB(GB)SA approaches. Besides the standard MM/PB(GB)SA calculation for binding affinity, conformation change of unbound ligand and protein will be taken into account through separate MD simulations. Before applying to other inverse agonists, the employed theoretical methods and force fields will be carefully validated by comparing the theoretical results (binding modes, and binding free affinity) with the available experimental data for the binding of ERRα and compound 1. 2) Aim 2. To provide more accurate binding thermodynamics by developing a quantum mechanics based hierarchical approach and using Alchemical binding free energy strategy Predicting protein-ligand binding affinities is a major objective of structure-based drug design. In order to provide more accurate thermodynamics for the binding of ERR to the inverse agonists, a hierarchical approach will be developed on the basis of the first-principles based theoretical methods such as dispersion-corrected density functional theory (DFT-D) and quantum mechanics/molecular mechanics (QM/MM) like 3-layer ONIOM scheme. DFT-D and QM/MM will provide accurate binding affinity for ligand-residue pairs and ligand-protein, respectively. Accurate binding thermodynamics are essential to identify the hot spot residues for the complexes of ERR/inverse agonists. 3) Aim 3. To identify hot spot residues of ERR and the essential ( operational) groups of the inverse agonists The validated theoretical methods will be extended to a few more systems such as ERRα/XCT790 and ERR α/compounds 3-4 including large scale MD simulation and binding free energy calculation with new force fields. Accurate binding affinity per residue basis from DFT-D and binding pocket analysis with AlphaSpace will help identify the hot spot residues. The relative binding free affinities for different inverse agonists from Alchemical binding free energy (BFE) will be used to analyse the essential (operational) groups of the inverse agonists, which play the predominant role in the binding of ERR with the inverse agonists.