The role of ligand flexibility in predicting biological activity: Structure–activity relationships for aryl hydrocarbon, estrogen, and androgen receptor binding affinity

Abstract

Recent studies indicate that the potency and agonist or antagonist activity of steroid hormone ligands are dependent, in part, on ligand–receptor binding affinity as well as the conformation of the ligand–receptor complex. The binding of ligands to hormone receptors is thought to involve interactions by which shapes of both the receptor and ligand are modified in the formation of the ligand–receptor complex. As a consequence, it is essential to explore the significance of ligand flexibility in the development of screening‐level structure–activity relationships. In this review, examples are provided of techniques used to generate and screen ligand conformers in the development of quantitative structure–activity relationships and active analogue search algorithms. The biological endpoint modeled was binding affinity of natural ligands and xenobiotics to the aryl hydrocarbon, estrogen, and androgen receptors. These approaches may be useful in future studies to evaluate relationships between ligand structure, receptor binding affinity, and, ultimately, transactivational events associated with receptor interactions with DNA response elements and associated proteins. An improved understanding of ligand–receptor interactions in the context of well‐defined effector systems will enhance the development of credible predictive models that can be used to screen large sets of chemicals for potential agonist or antagonistic activity.

Development of a fish reporter gene system for the assessment of estrogenic compounds and sewage treatment plant effluents

“…Among the more than 100,000 chemicals listed on the European Inventory of Existing Chemical Substances, some are potential estrogenic agonists [3]. The need for screening tools to support human health and ecological risk assessment led to the development of structure‐activity relationship concepts, which predict ligand binding affinity to the ER [4], and several in vivo [1,5] and in vitro [6] assays, which allow the empirical identification of estrogenic compounds. Agreement has been reached during the past years that the most appropriate strategy in the identification and evaluation of environmental estrogens should involve a combination of in vivo and in vitro assays consisting of a suite of endpoints and target organisms [5].…”

Quantitative structure‐activity relationship models for prediction of estrogen receptor binding affinity of structurally diverse chemicals

“…A different approach to 3‐D QSAR modeling of receptor binding was first presented conceptually by Bradbury et al [35,36] and Mekenyan et al [37,38]. Recently, the approach has been more fully evaluated for prediction of ER binding affinity in two companion papers [39,40].…”

“…The rationale for using multiple conformers arises from experimental evidence that the free energy of binding for steroid hormones to receptors is in the range of –10 to –20 kcal/mol [43–45], which can provide the necessary energy to elevate conformers from the low(est) energy state during binding. Conformers selected within this range of ΔΔH are energetically reasonable from a thermodynamic and kinetic perspective [36–38,46]. Conformers of each chemical are considered to be a statistical ensemble, based on Boltz‐man's statistics.…”

“…Reactivity patterns were established for identifying and ranking compounds within a series of binding affinity ranges relative to estradiol binding of 100%, including RBA values of >150%, 100 to 10%, 10 to 1%, and 1 to 0.1%. Local, global, and steric descriptors used in the model were restricted to those hypothesized to be associated with ER binding, based on previous studies with a variety of model receptors [35–38,45,47,48,52–56] (see [39] for computational details). Through the COREPA analysis the authors determined that ER RBA could be predicted based on three parameters: global nucleophilicity (represented by energy of the highest occupied molecular orbital, E HOMO ), interatomic distances between nucleophilic heteroatoms, and electron donor capability of these heteroatoms.…”

“…The modeling approach has also been applied to a more homologous series of chemicals (alkylphenols) with relatively weak binding affinity in order to determine more precise predictors of activity within a confined range and, in this instance, for the more biologically complex endpoint of ER gene activation [13]. The COREPA approach has also been recently extended to the discrimination of ER antagonists from agonists [23] and has also been applied to prediction of ligand affinity to other steroid hormone receptors [36,37,57].…”