Literature DB >> 24361687

Local motifs involved in the canonical structure of the ligand-binding domain in the nuclear receptor superfamily.

Motonori Tsuji1.   

Abstract

Structural and sequence alignment analyses have revealed the existence of class-dependent and -independent local motifs involved in the overall fold of the ligand-binding domain (LBD) in the nuclear receptor (NR) superfamily. Of these local motifs, three local motifs, i.e., AF-2 fixed motifs, were involved in the agonist conformation of the activation function-2 (AF-2) region of the LBD. Receptor-agonist interactions increased the stability of these AF-2 fixed motifs in the agonist conformation. In contrast, perturbation of the AF-2 fixed motifs by a ligand or another protein molecule led the AF-2 architecture to adopt an antagonist conformation. Knowledge of this process should provide us with novel insights into the 'agonism' and 'antagonism' of NRs.
Copyright © 2013 Elsevier Inc. All rights reserved.

Keywords:  Agonism; Antagonism; Charge–dipole interaction; Local motif; Nuclear receptor ligand-binding domain; Signal amino acid

Mesh:

Substances:

Year:  2013        PMID: 24361687     DOI: 10.1016/j.jsb.2013.12.007

Source DB:  PubMed          Journal:  J Struct Biol        ISSN: 1047-8477            Impact factor:   2.867


  4 in total

1.  Antagonist-perturbation mechanism for activation function-2 fixed motifs: active conformation and docking mode of retinoid X receptor antagonists.

Authors:  Motonori Tsuji
Journal:  J Comput Aided Mol Des       Date:  2017-05-22       Impact factor: 3.686

2.  Docking simulations suggest that all-trans retinoic acid could bind to retinoid X receptors.

Authors:  Motonori Tsuji; Koichi Shudo; Hiroyuki Kagechika
Journal:  J Comput Aided Mol Des       Date:  2015-09-18       Impact factor: 3.686

3.  Identifying the receptor subtype selectivity of retinoid X and retinoic acid receptors via quantum mechanics.

Authors:  Motonori Tsuji; Koichi Shudo; Hiroyuki Kagechika
Journal:  FEBS Open Bio       Date:  2017-02-05       Impact factor: 2.693

4.  A unified solution for different scenarios of predicting drug-target interactions via triple matrix factorization.

Authors:  Jian-Yu Shi; An-Qi Zhang; Shao-Wu Zhang; Kui-Tao Mao; Siu-Ming Yiu
Journal:  BMC Syst Biol       Date:  2018-12-31
  4 in total

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