Mutation goals in the vitamin D receptor predicted by computational methods. Issue 183 (October 2018)

• Record Type: Journal Article
• Authors: Sicinska, Wanda; Gront, Dominik; Sicinski, Kamil
• Is Part Of: Journal of steroid biochemistry and molecular biology. Issue 183(2018)
• Page Start: 210
• Page End: 220
• Publication Date: 2018-10
• Subjects: VD vitamin D -- VDR vitamin D receptor -- 1, 25D 1α, 25-(OH)2D3 -- LBP ligand binding pocket -- RXR retinoid X receptor -- VDRRE vitamin D receptor response element (DNA-DR3) -- VDRR vitamin D-resistant rickets -- SRC steroid receptor coactivator -- DRIP vitamin D receptor interacting protein -- TIF transcriptional intermediary factor -- TAF a specific TATA binding protein associated factor -- SFR structure function relationship -- HDX-MS hydrogen deuterium exchange - mass spectrometry -- SKIP SKI oncoprotein interacting with VDR; Vitamin D receptor active sites -- Vitamin D -- Vitamin D analogs -- Computational analysis -- holoVDR crystal complexes; Steroid hormones -- Periodicals; Biochemistry -- Periodicals; Hormones -- Periodicals; Molecular Biology -- Periodicals; Hormones stéroïdes -- Périodiques; Steroid hormones; Periodicals; 572.579
• DOI: 10.1016/j.jsbmb.2018.06.016
• Languages: English
• ISSNs: 0960-0760

Abstract

Graphical abstract: Highlights: Computational method for identifying biologically active amino acids is proposed. Application to the vitamin D receptor is discussed. Relevance of identified amino acids is verified using experimental and genomic data. Method can be used to identify promising mutation targets in nuclear receptors. Abstract: The mechanism through which nuclear receptors respond differentially to structurally distinct agonists is a poorly understood process. We present a computational method that identifies nuclear receptor amino acids that are likely involved in biological responses triggered by ligand binding. The method involves tracing how structural changes spread from the ligand binding pocket to the sites on the receptor surface, which makes it a good tool for studying allosteric effects. We employ the method to the vitamin D receptor and verify that the identified amino acids are biologically relevant using a broad range of experimental data and a genome browser. We infer that surface vitamin D receptor residues K141, R252, I260, T280, T287 and L417 are likely involved in cell differentiation and antiproliferation, whereas P122, D149, K321, E353 and Q385 are linked to carcinogenesis.