Dataset Information

Spongian diterpenoids inhibit androgen receptor activity.

ABSTRACT: Androgen receptor is a ligand-activated transcription factor and a validated drug target for all stages of prostate cancer. Antiandrogens compete with physiologic ligands for androgen receptor ligand-binding domain (LBD). High-throughput screening of a marine natural product library for small molecules that inhibit androgen receptor transcriptional activity yielded the furanoditerpenoid spongia-13(16),-14-dien-19-oic acid, designated terpene 1 (T1). Characterization of T1 and the structurally related semisynthetic analogues (T2 and T3) revealed that these diterpenoids have antiandrogen properties that include inhibition of both androgen-dependent proliferation and androgen receptor transcriptional activity by a mechanism that involved competing with androgen for androgen receptor LBD and blocking essential N/C interactions required for androgen-induced androgen receptor transcriptional activity. Structure-activity relationship analyses revealed some chemical features of T1 that are associated with activity and yielded T3 as the most potent analogue. In vivo, T3 significantly reduced the weight of seminal vesicles, which are an androgen-dependent tissue, thereby confirming the on-target activity of T3. The ability to create analogues of diterpenoids that have varying antiandrogen activity represents a novel class of chemical compounds for the analysis of androgen receptor ligand-binding properties and therapeutic development.

SUBMITTER: Yang YC

PROVIDER: S-EPMC3729039 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundEndocrine disrupting chemicals (EDCs) are xenobiotics that mimic the interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The prospect of EDCs causing adverse health effects in humans and wildlife has led to the development of scientific and regulatory approaches for evaluating bioactivity. This need is being addressed using high-throughput screening (HTS) in vitro approaches and computational modeling.ObjectivesIn support of the Endocrine Disruptor Screening Program, the U.S. Environmental Protection Agency (EPA) led two worldwide consortiums to virtually screen chemicals for their potential estrogenic and androgenic activities. Here, we describe the Collaborative Modeling Project for Androgen Receptor Activity (CoMPARA) efforts, which follows the steps of the Collaborative Estrogen Receptor Activity Prediction Project (CERAPP).MethodsThe CoMPARA list of screened chemicals built on CERAPP's list of 32,464 chemicals to include additional chemicals of interest, as well as simulated ToxCast™ metabolites, totaling 55,450 chemical structures. Computational toxicology scientists from 25 international groups contributed 91 predictive models for binding, agonist, and antagonist activity predictions. Models were underpinned by a common training set of 1,746 chemicals compiled from a combined data set of 11 ToxCast™/Tox21 HTS in vitro assays.ResultsThe resulting models were evaluated using curated literature data extracted from different sources. To overcome the limitations of single-model approaches, CoMPARA predictions were combined into consensus models that provided averaged predictive accuracy of approximately 80% for the evaluation set.DiscussionThe strengths and limitations of the consensus predictions were discussed with example chemicals; then, the models were implemented into the free and open-source OPERA application to enable screening of new chemicals with a defined applicability domain and accuracy assessment. This implementation was used to screen the entire EPA DSSTox database of ∼875,000 chemicals, and their predicted AR activities have been made available on the EPA CompTox Chemicals dashboard and National Toxicology Program's Integrated Chemical Environment. https://doi.org/10.1289/EHP5580.

Dataset Information

Spongian diterpenoids inhibit androgen receptor activity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets