Computational Insights into Ligand Selectivity of Estrogen Receptors from Pharmacophore Modeling

Abstract

Estrogen receptors (ERs) belong to the nuclear receptor superfamily, which play crucial roles in the human body. To date, two subtypes, ERα and ERβ, have been identified. The function and expression of both subtypes are various, stimulating the interest for discovering subtype selective ligands. However, ERα and ERβ are highly homologous. They share 56 % sequence identity in the ligand binding domain and only two pairs of residues differ in the ligand binding pocket. In this study, pharmacophore models were built for both subtypes based on 23 ERα and 24 ERβ selective ligands, respectively. It was found from these pharmacophore models that hydrophobic and hydrogen bonding interactions were essential for the subtype selectivity. The hydrogen bond donor feature in the phenol part was a favorable contribution to ERβ selectivity, whereas the one in the benzopyran part of the ligand was important for ERα selectivity. Furthermore, simulated virtual screening was performed with both subtype specific pharmacophore models. The results confirmed the reliability and discrimination ability of both models. These findings could not only be helpful for the understanding of a possible mechanism underlying ligand selectivity of ERs, but could also pave a new avenue for the discovery of novel selective ER ligands.

Estrogen receptor‐based multi‐residue screening of bisphenol compounds in urine

“…). Apparently, the hydrogen bonding and hydrophobic interactions were significant for ERα affinity, which was consistent with the results of previous experimental analysis . The molecule structures and their interactions with the pharmacophore can be visualized to further understand how feature mapping relates to CR results.…”

Insight Analysis of Promiscuous Estrogen Receptor α-Ligand Binding by a Novel Machine Learning Scheme

“…Furthermore, it can be discovered from Figure 13, which exhibits the interactions between ERα-E 2 by LigPlot + (available at http://www.ebi.ac.uk/thornton-srv/software/ LigPlus/) based on the ERα-E 2 co-complex structure (PDB code: 1YIN), that both hydroxyl groups of E 2 can bind with ERα by hydrogen bonds, indicating the necessity of both interactions to exert the ERα-ligand interactions. Consequently, the predictive models proposed by Brogi et al, 41 Fang et al, 42 and Islam et al 76 unanimously adopted one HBA and one HBD chemical features. However, 5, 87, and 88, which only have one hydroxyl group, are strong ERα binders, suggesting that only one hydrogen-bond interaction is sufficient enough to establish strong binding with ERα that, actually, is totally consistent with the postulation made by Katzenellenbogen.…”

“…The predictive hypothesis built by Brogi et al 41 selected 2 HPAs and 1 HP, whereas the ones proposed by Fang et al 42 and Islam et al 76 adopted 3HPs. Furthermore, Hypo A and Hypo B included 2 HPs and 1 RA as well as 2 HPs and 1 HPA, respectively.…”

Discovery of Inhibitors To Block Interactions of HIV-1 Integrase with Human LEDGF/p75 via Structure-Based Virtual Screening and Bioassays

“…1 We have previously confirmed the reliability of this process. 2,3 Firstly, commercial compound were retrieved from database-Specs (http://www.specs.net/) and filtered by rule of 5. Secondly, with the "find diverse molecules" protocol, 10,000 diverse compounds were chosen from the 70,624 molecules.…”