Protein Side Chains Facilitate Mg/Al Exchange in Model Protein Binding Sites

ChemPhysChem ◽  
2007 ◽  
Vol 8 (14) ◽  
pp. 2119-2124 ◽  
Author(s):  
Elixabete Rezabal ◽  
Jose M. Mercero ◽  
Xabier Lopez ◽  
Jesus M. Ugalde
2016 ◽  
Vol 45 (30) ◽  
pp. 12206-12214 ◽  
Author(s):  
Marco Caterino ◽  
Ariel A. Petruk ◽  
Alessandro Vergara ◽  
Giarita Ferraro ◽  
Daniela Marasco ◽  
...  

Mass spectrometry, Raman microspectroscopy, circular dichroism and X-ray crystallography have been used to investigate the reaction of CO-releasing molecule Cs2IrCl5CO with the model protein RNase A.


2010 ◽  
Vol 53 (8) ◽  
pp. 3086-3094 ◽  
Author(s):  
A.W. Edith Chan ◽  
Roman A. Laskowski ◽  
David L. Selwood

1971 ◽  
Vol 68 (1_Suppl) ◽  
pp. S223-S246 ◽  
Author(s):  
C. R. Wira ◽  
H. Rochefort ◽  
E. E. Baulieu

ABSTRACT The definition of a RECEPTOR* in terms of a receptive site, an executive site and a coupling mechanism, is followed by a general consideration of four binding criteria, which include hormone specificity, tissue specificity, high affinity and saturation, essential for distinguishing between specific and nonspecific binding. Experimental approaches are proposed for choosing an experimental system (either organized or soluble) and detecting the presence of protein binding sites. Techniques are then presented for evaluating the specific protein binding sites (receptors) in terms of the four criteria. This is followed by a brief consideration of how receptors may be located in cells and characterized when extracted. Finally various examples of oestrogen, androgen, progestagen, glucocorticoid and mineralocorticoid binding to their respective target tissues are presented, to illustrate how researchers have identified specific corticoid and mineralocorticoid binding in their respective target tissue receptors.


2019 ◽  
Author(s):  
Andrea N. Bootsma ◽  
Analise C. Doney ◽  
Steven Wheeler

<p>Despite the ubiquity of stacking interactions between heterocycles and aromatic amino acids in biological systems, our ability to predict their strength, even qualitatively, is limited. Based on rigorous <i>ab initio</i> data, we have devised a simple predictive model of the strength of stacking interactions between heterocycles commonly found in biologically active molecules and the amino acid side chains Phe, Tyr, and Trp. This model provides rapid predictions of the stacking ability of a given heterocycle based on readily-computed heterocycle descriptors. We show that the values of these descriptors, and therefore the strength of stacking interactions with aromatic amino acid side chains, follow simple predictable trends and can be modulated by changing the number and distribution of heteroatoms within the heterocycle. This provides a simple conceptual model for understanding stacking interactions in protein binding sites and optimizing inhibitor binding in drug design.</p>


1989 ◽  
Vol 264 (31) ◽  
pp. 18707-18713 ◽  
Author(s):  
K Matsuno ◽  
C C Hui ◽  
S Takiya ◽  
T Suzuki ◽  
K Ueno ◽  
...  

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