Discovery of diverse thyroid hormone receptor antagonists by  high-throughput docking

Schapira, Matthieu; Raaka, Bruce M.; Das, Sharmistha; Fan, Li; Totrov, Maxim; Zhou, Zhiguo; Wilson, Stephen R.; Abagyan, Ruben; Samuels, Herbert H.

doi:10.1073/pnas.1131854100

Cited by 160 publications

(115 citation statements)

References 38 publications

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“…Furthermore, there was a good correlation between docking scores and relative specificity across nuclear receptors for 78 known nuclear receptor ligands (17). We also identified antagonists to two nuclear receptors, retinoic acid receptor (17,18) and thyroid hormone receptor (19), by using predicted antagonist-bound models.…”

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confidence: 99%

Discovery of antiandrogen activity of nonsteroidal scaffolds of marketed drugs

Bisson

Cheltsov

Bruey-Sédano

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

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Finding good drug leads de novo from large chemical libraries, real or virtual, is not an easy task. High-throughput screening is often plagued by low hit rates and many leads that are toxic or exhibit poor bioavailability. Exploiting the secondary activity of marketed drugs, on the other hand, may help in generating drug leads that can be optimized for the observed side-effect target, while maintaining acceptable bioavailability and toxicity profiles. Here, we describe an efficient computational methodology to discover leads to a protein target from safe marketed drugs. We applied an in silico ''drug repurposing'' procedure for identification of nonsteroidal antagonists against the human androgen receptor (AR), using multiple predicted models of an antagonist-bound receptor. The library of marketed oral drugs was then docked into the best-performing models, and the 11 selected compounds with the highest docking score were tested in vitro for AR binding and antagonism of dihydrotestosterone-induced AR transactivation. The phenothiazine derivatives acetophenazine, fluphenazine, and periciazine, used clinically as antipsychotic drugs, were identified as weak AR antagonists. This in vitro biological activity correlated well with endocrine side effects observed in individuals taking these medications. Further computational optimization of phenothiazines, combined with in vitro screening, led to the identification of a nonsteroidal antiandrogen with improved AR antagonism and marked reduction in affinity for dopaminergic and serotonergic receptors that are the primary target of phenothiazine antipsychotics.androgen receptor ͉ drug design ͉ prostate cancer C urrent approaches for discovery of novel chemical leads against a molecular target rely heavily on high-throughput screening (HTS) and to a lesser extent on virtual ligand screening (VLS) techniques. HTS has provided rapid lead identification for numerous drug targets (1-8); however, HTS also has major drawbacks, including a significant level of false positives and false negatives and low hit rates for many targets (9). Successful leads from HTS can also suffer from poor bioavailability and unwanted toxicity profiles of compounds. These problems result partially from the nature of the chemical libraries used for HTS. Furthermore, because the pharmacological properties of most compound libraries are largely unknown, there is an additional high risk that optimization of hits identified with HTS will not be sufficient for their evolution into real drugs.In contrast, retrospective analysis of marketed drugs reveals that their physicochemical and structural properties are clustered around preferred values and scaffolds (10). In addition, some chemical motifs are associated with high biological activity and often confer activity against more than one target/receptor (11-16). These motifs have been referred to as ''privileged structures'' (11). These observations lead to an assumption that the chemical space of potential drugs is limited. Consequently, currently marketed...

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confidence: 99%

Discovery of antiandrogen activity of nonsteroidal scaffolds of marketed drugs

Bisson

Cheltsov

Bruey-Sédano

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

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“…Prior functional and structural analyses of ligand-bound receptor provided the groundwork for understanding TR regulation by agonist and antagonist ligands: (1) the receptor exists in different conformations when it is complexed with agonists or antagonists, (2) the 2 ligand types bind to TR at the same site, and with similar affinities (Schapira et al, 2003). Therefore, SPR technology and molecular docking were further applied to study the binding features of the pesticides to hTRb.…”

Section: Discussionmentioning

confidence: 99%

Editor’s Highlight: Structure-Based Investigation on the Binding and Activation of Typical Pesticides With Thyroid Receptor

Xiang

Han

Yao

et al. 2017

Toxicological Sciences

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A broad range of pesticides have been reported to interfere with the normal function of the thyroid endocrine system. However, the precise mechanism(s) of action has not yet been thoroughly elucidated. In this study, 21 pesticides were assessed for their binding interactions and the potential to disrupt thyroid homeostasis. In the GH3 luciferase reporter gene assays, 5 of the pesticides tested had agonistic effects in the order of procymidone > imidacloprid > mancozeb > fluroxypyr > atrazine. 11 pesticides inhibited luciferase activity of T3 to varying degrees, demonstrating their antagonistic activity. And there are 4 pesticides showed mixed effects when treated with different concentrations. Surface plasmon resonance (SPR) biosensor technique was used to directly measure the binding interactions of these pesticides to the human thyroid hormone receptor (hTR). 13 pesticides were observed to bind directly with TR, with a KD ranging from 4.80E-08 M to 9.44E-07 M. The association and disassociation of the hTR/pesticide complex revealed 2 distinctive binding modes between the agonists and antagonists. At the same time, a different binding mode was displayed by the pesticides showed mix agonist and antagonist activity. In addition, the molecular docking simulation analyses indicated that the interaction energy calculated by CDOCKER for the agonists and antagonists correlated well with the KD values measured by the surface plasmon resonance assay. These results help to explain the differences of the TR activities of these tested pesticides.

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“…Based on the crystal structure of the target protein and highthroughput molecular docking using compound database, virtual screening allows for scanning a large number of compounds with reasonable accuracy and speed. It has been used to identify RAR and TR antagonists [14,15] and to screen for selective estrogen receptor (ER) modulators [16]. Computer-aided high throughput docking provides a rapid and economic approach for orphan nuclear receptor ligand screening and proves to be a valuable tool for drug discovery.…”

Section: Ligand Identification For Orphan Nuclear Receptorsmentioning

confidence: 99%

Orphan nuclear receptors in drug discovery

Shi

2007

Drug Discovery Today

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SummaryOrphan nuclear receptors provide a unique resource for uncovering novel regulatory systems that impact human health and provide excellent drug targets for a variety of human diseases. Ligands of nuclear receptors have been used in a number of important therapeutic areas, such as breast cancers, skin disorders, and diabetes. Orphan nuclear receptors, therefore, represent a tremendous opportunity in understanding and treating human diseases. This review highlights advances and potentials of using orphan nuclear receptors, in particular PPARs, Nurr1, RORs, and TLX as targets for drug discovery in diabetes and obesity, neurodegenerative diseases, and other related disorders.

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Discovery of diverse thyroid hormone receptor antagonists by high-throughput docking

Cited by 160 publications

References 38 publications

Discovery of antiandrogen activity of nonsteroidal scaffolds of marketed drugs

Discovery of antiandrogen activity of nonsteroidal scaffolds of marketed drugs

Editor’s Highlight: Structure-Based Investigation on the Binding and Activation of Typical Pesticides With Thyroid Receptor

Orphan nuclear receptors in drug discovery

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