Vijay Paramanik1, Harini Krishnan2, Mahendra Kumar Thakur2. 1. Department of Zoology, Cellular and Molecular Neurobiology and Drug Targeting Laboratory, Indira Gandhi National Tribal University, Amarkantak, India. 2. Department of Zoology, Biochemistry and Molecular Biology Laboratory, Banaras Hindu University, Varanasi, India.
Abstract
BACKGROUND: Estrogen receptor (ER)α and ERβ are ligand-activated transcription factors that regulate gene expression by binding to estrogen-responsive elements and interacting with several coregulators through protein-protein interactions. Usually, these coregulators bind to the various conserved and functional domains of the receptor through a consensus LXXLL sequence, although variations can be found. The interaction of receptor domains and the consensus motif can be a possible target for nuclear receptor (NR) pharmacology, since modifications in these are responsible for possible pathogenesis of various diseases. PURPOSE: The present study focuses on the secondary structure and conserved domains of the ERα and ERβ interacting proteins, using bioinformatics tools and their relation to the function of the coregulators. METHODS: Bioinformatics-based prediction tools like STRING, PSIPRED, PROTPARAM and Conserved Domain Database (CDD) were used. The prediction tools utilized in this study basically determines the characteristics of a possible coregulator by using an already existing protein as a template and determines the presence of any conserved consensus sequence. Coregulators have been enlisted with the help of NCBI, STRING and iHOP. The secondary structures were analyzed using PSIPRED and conserved domains were determined using CDD. RESULTS: The analysis of the structure has shown the presence of conserved domains and homology between the various coregulators. Each interacting protein contains conserved domains like the nuclear coactivators' domain, the helix-loop-helix domain and the SRC domain. CONCLUSION: Such studies give the characteristic features of ERα and ERβ interacting proteins and maybe useful to determine their family and uses in NR pharmacology in health and diseases.
BACKGROUND: Estrogen receptor (ER)α and ERβ are ligand-activated transcription factors that regulate gene expression by binding to estrogen-responsive elements and interacting with several coregulators through protein-protein interactions. Usually, these coregulators bind to the various conserved and functional domains of the receptor through a consensus LXXLL sequence, although variations can be found. The interaction of receptor domains and the consensus motif can be a possible target for nuclear receptor (NR) pharmacology, since modifications in these are responsible for possible pathogenesis of various diseases. PURPOSE: The present study focuses on the secondary structure and conserved domains of the ERα and ERβ interacting proteins, using bioinformatics tools and their relation to the function of the coregulators. METHODS: Bioinformatics-based prediction tools like STRING, PSIPRED, PROTPARAM and Conserved Domain Database (CDD) were used. The prediction tools utilized in this study basically determines the characteristics of a possible coregulator by using an already existing protein as a template and determines the presence of any conserved consensus sequence. Coregulators have been enlisted with the help of NCBI, STRING and iHOP. The secondary structures were analyzed using PSIPRED and conserved domains were determined using CDD. RESULTS: The analysis of the structure has shown the presence of conserved domains and homology between the various coregulators. Each interacting protein contains conserved domains like the nuclear coactivators' domain, the helix-loop-helix domain and the SRC domain. CONCLUSION: Such studies give the characteristic features of ERα and ERβ interacting proteins and maybe useful to determine their family and uses in NR pharmacology in health and diseases.
Authors: Hang Li; Jun Che; Mian Jiang; Ming Cui; Guoxing Feng; Jiali Dong; Shuqin Zhang; Lu Lu; Weili Liu; Saijun Fan Journal: Cell Commun Signal Date: 2020-09-17 Impact factor: 5.712