TAF1
塔夫2
二价(发动机)
TAF4
蛋白质亚单位
转录因子ⅡD
化学
转录因子ⅡA
转录因子
细胞生物学
生物
生物化学
发起人
基因
增强子
有机化学
金属
基因表达
作者
Junghyun L. Suh,Brian Watts,Jacob I. Stuckey,Jacqueline L. Norris‐Drouin,Stephanie H. Cholensky,Bradley M. Dickson,Yi An,Sebastian Mathea,E. Salah,Stefan Knapp,Abid Khan,Alex Adams,Brian D. Strahl,Cari A. Sagum,Mark T. Bedford,Lindsey I. James,Dmitri Kireev,Stephen V. Frye
出处
期刊:Biochemistry
[American Chemical Society]
日期:2018-03-20
卷期号:57 (14): 2140-2149
被引量:16
标识
DOI:10.1021/acs.biochem.8b00150
摘要
Multivalent binding is an efficient means to enhance the affinity and specificity of chemical probes targeting multidomain proteins in order to study their function and role in disease. While the theory of multivalent binding is straightforward, physical and structural characterization of bivalent binding encounters multiple technical difficulties. We present a case study where a combination of experimental techniques and computational simulations was used to comprehensively characterize the binding and structure-affinity relationships for a series of Bromosporine-based bivalent bromodomain ligands with a bivalent protein, Transcription Initiation Factor TFIID subunit 1 (TAF1). Experimental techniques-Isothermal Titration Calorimetry, X-ray Crystallography, Circular Dichroism, Size Exclusion Chromatography-Multi-Angle Light Scattering, and Surface Plasmon Resonance-were used to determine structures, binding affinities, and kinetics of monovalent ligands and bivalent ligands with varying linker lengths. The experimental data for monomeric ligands were fed into explicit computational simulations, in which both ligand and protein species were present in a broad range of concentrations, and in up to a 100 s time regime, to match experimental conditions. These simulations provided accurate estimates for apparent affinities (in good agreement with experimental data), individual dissociation microconstants and other microscopic details for each type of protein-ligand complex. We conclude that the expected efficiency of bivalent ligands in a cellular context is difficult to estimate by a single technique in vitro, due to higher order associations favored at the concentrations used, and other complicating processes. Rather, a combination of structural, biophysical, and computational approaches should be utilized to estimate and characterize multivalent interactions.
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