The Nuclear Receptor Ligand-Binding Domain: A Family-Based Structure Analysis

Folkertsma, Simon; Noort, Paula I. van; Brandt, Ralph; Bettler, Emmanuel; Vriend, Gerrit; Vlieg, Jacob de

doi:10.2174/0929867053764699

Cited by 23 publications

(19 citation statements)

References 49 publications

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“…The similarity between the coactivator sites of the NR3 and NR5 family has been discussed in the literature. 13 The two NR4s are separate (III) from the other large clusters as they have do not share the canonical coactivator site of the other NRs having an opposite charge clamp and different polar residues in the binding groove.…”

Section: Comparison Of Coactivator Site Fieldsmentioning

confidence: 99%

“…Structure-based approaches to functional analysis of the nuclear receptor family have been performed using structure-based alignments and comparison of ligand interactions in combination with literature data. [11][12][13] In this article we present another type of structure-based analysis of the nuclear receptor family, which is focused on essential molecular interaction fields within important functional regions like binding sites for regulating ligands or coactivators. Unlike residue-based comparisons, the effects from several parts of the binding sites are considered by this method in an additive and subtractive manner.…”

Section: Introductionmentioning

confidence: 99%

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Field‐based comparison of ligand and coactivator binding sites of nuclear receptors

2009

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A structure-based comparison of the ligand-binding domains of 35 nuclear receptors from five different subfamilies is presented. Their ligand and coactivator binding sites are characterized using knowledge-based contact preference fields for hydrophobic and hydrophilic interactions implemented in the MOE modeling environment. Additionally, for polar knowledge-based field points the preference for negative or positive electrostatic interactions is estimated using the Poisson-Boltzmann equation. These molecular-interaction fields are used to cluster the nuclear receptor family based on similarities of their binding sites. By analyzing the similarities and differences of hydrophobic and polar fields in binding pockets of related receptors it is possible to identify conserved interactions in ligand and coactivator binding pockets, which support e.g. design of specific ligands during lead optimization or virtual screening as docking filter. Examples of remarkable similarities between ligand binding sites of members from phylogenetically different nuclear receptor families (RXR, RAR, HNF4, NR5) and differences between closely related subtypes (LXR, RAR, TR) are discussed in more detail. Significant similarities and differences of coactivator binding sites are shown for NR3Cs, LXRs and PPARs.

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Section: Comparison Of Coactivator Site Fieldsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Field‐based comparison of ligand and coactivator binding sites of nuclear receptors

2009

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“…A few examples are aspartic proteases, serine protease and cysteine proteases and pseudopeptide inhibitors [31], nuclear hormone receptors [32] and steroid agonists [33][34][35], and certain members of Gprotein coupled receptors and catecholamine agonists [35]. Based on such a relationship, multiple libraries were designed and molecular docking was conducted against three members of serine protease family [36].…”

Section: Exploiting the Correlation Between Protein Families And Ligamentioning

confidence: 99%

Increasing the Odds of Drug Hit Identification by Screening Against Receptor Homologs?

Wang³

et al. 2006

LDDD

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The odds of drug hit identification in screening are closely related to the diversity of libraries or the availability of focused libraries. There are no truly diverse libraries and it is difficult to design focused libraries without sufficient information. Hence alternative approaches need to be explored for enhancing the odds of hit discovery from existing libraries. Protein homologs have been used collectively targeted in inhibitor design and other discovery applications by exploiting the correlation between protein homologs and their ligands from specific compound classes. A receptor-homolog-based screening scheme may be derived as a strategy to potentially increase the odds of hit identification.

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“…This is due to a major extent to the large plethora of protein-protein interactions between nuclear receptors and their many cofactors [1,2]. Binding of a ligand results in a change of the conformation of the LBD and with that it influences the dimerization of the nuclear receptor with other proteins [4]. There are several hundreds of cofactor proteins known, but both the molecular rules for the formation of the nuclear receptorcofactor complexes and the physiological meaning of many of these are often still a mystery [5].…”

Section: Introductionmentioning

confidence: 99%

Targeting the Nuclear Receptor–Cofactor Interaction

Vaz

Möcklinghoff

Brunsveld

2008

Methods and Principles in Medicinal Chemistry

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The developmental and physiological processes regulated by nuclear receptors are the result of the interplay between the receptors, their small-molecule ligands (hormones), their response elements on the DNA and a large set of interacting proteins, the so-called cofactors [1,2]. Up to recently, the modulation of the function of nuclear receptors concentrated mainly on ligands with agonistic, antagonistic or partial (ant)agonistic properties that bind in the binding pocket of the ligand-binding domain (LBD), also occupied by the natural ligands. These types of ligands have proven very beneficial for the treatment of various diseases and the regulation of hormone functioning, as illustrated by many of the chapters in this book. Some of these ligands have even been shown to feature tissue-specific or -selective (ant) agonistic properties, which is often of crucial importance for the separation of the beneficial effects of nuclear receptor stimulation or inhibition from unwanted sideeffects, regulated by the same receptor [2]. Nevertheless, predictability and control over tissue specificity of these classical ligands is difficult. The physiological effects of some of the nuclear receptor ligands are sometimes also altered over a period of time. A typical example of this is the transition of nuclear receptor ligands used for the treatment of specific cancers from an antagonistic profile into an agonistic profile [3]. Interestingly, there are also nuclear receptors for which, up to now, no ligand, neither of natural nor of synthetic origin, has been found. These so-called orphan receptors seem not to be amenable to modulation by classical ligands.The limitations of the current nuclear receptor ligands generate a continuous quest for new ligands with optimized profiles in both industry and academia. The requirements of the effects of these ligands on the level of the organism are usually quite clear; the translation of these requirements to the level of the conformation of the protein and structure of the ligand is, however, usually not evident. This is due to a major extent to the large plethora of protein-protein interactions between nuclear receptors and their many cofactors [1,2]. Binding of a ligand results in a change of the Nuclear Receptors as Drug Targets. Edited by Eckhard Ottow and Hilmar Weinmann

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The Nuclear Receptor Ligand-Binding Domain: A Family-Based Structure Analysis

Cited by 23 publications

References 49 publications

Field‐based comparison of ligand and coactivator binding sites of nuclear receptors

Field‐based comparison of ligand and coactivator binding sites of nuclear receptors

Increasing the Odds of Drug Hit Identification by Screening Against Receptor Homologs?

Targeting the Nuclear Receptor–Cofactor Interaction

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