Literature DB >> 30460461

Exploring the binding properties of agonists interacting with glucocorticoid receptor: an in silico approach.

Samith Rathnayake1, Samantha Weerasinghe2.   

Abstract

The glucocorticoid receptors (GR) are members of the nuclear receptor superfamily that regulate growth, development, and many of the biological functions, including metabolism and inflammation, in a ligand dependent behavior. Thus, GRs are vital as therapeutic targets with steroid hormones and steroidal analogues, especially including the glucocorticoids. Studying the molecular mechanism of binding between GR and ligands is fundamentally important to develop applications in the pharmacological industry. The present study was carried out via molecular docking and molecular dynamic (MD) simulations of three GR-ligand complexes formed between the ligand binding domain (LBD) of GR with cortisol (a natural steroid), dexamethasone (a well-known synthetic steroid drug), and chonemorphine (a steroid virtually screened from the "Sri Lankan Flora" web-based information system). The investigation was mainly carried out in terms of macroscopic properties of the ligand-protein interactions and conformational fluctuations of the protein. The results indicated greater stability and a similar behavior of the GR protein in the chonemorphine-GR complex, compared to the other two complexes, GR-dexamethasone and GR-cortisol, in an aqueous medium. The integrity of the protein-substrate complexes was preserved by strong hydrogen bonds formed between the amino acid residues of the binding site of the proteins and ligands. The findings revealed that chonemorphine is a promising agonist to GR and may produce a pharmacological effect like that produced by glucocorticoids. Thus, the obtained knowledge could lead to further investigations of the pharmaceutical potential of chonemorphine and biological functions of GR in vivo.

Entities:  

Keywords:  Glucocorticoid receptors; Ligand-protein complex formations; Molecular docking; Molecular dynamic simulations; Sri Lankan Flora web based information system; Steroid drugs

Mesh:

Substances:

Year:  2018        PMID: 30460461     DOI: 10.1007/s00894-018-3879-1

Source DB:  PubMed          Journal:  J Mol Model        ISSN: 0948-5023            Impact factor:   1.810


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