scholarly journals The influence of pH on the equilibrium distribution of iron between the metal-binding sites of human transferrin

1981 ◽  
Vol 193 (3) ◽  
pp. 717-727 ◽  
Author(s):  
N D Chasteen ◽  
J Williams
Keyword(s):  
Metal Binding ◽  
Binding Sites ◽  
Equilibrium Distribution ◽  
Polyacrylamide Gel Electrophoresis ◽  
Ph Titration ◽  
Metal Binding Sites ◽  
Titration Curves ◽  
Diferric Transferrin ◽  
Differential Properties ◽  
Influence Of Ph

The dependence of the metal-binding properties of transferrin on pH in the pH 6–9 range was investigated by urea/polyacrylamide-gel electrophoresis. Equations are presented for calculating the relative values of the four conditional site constants for the stepwise binding of iron to the two sites of transferrin and for calculating the equilibrium distribution of the protein among the four principal forms, apotransferrin, the C-terminal and N-terminal monoferric transferrins and diferric transferrin. The relative affinity of iron for the two sites and the co-operativity of iron-binding follow characteristic ‘pH titration’ curves. A mathematical model that can account for the former behaviour is presented. In both cases the metal-binding sites are affected by the ionization of functional groups with apparent pKa values near physiological pH approx. 7.4. There is strong positive co-operatively in the release of protons from these groups. The results indicate that pH must be accurately controlled in studies of the differential properties of the two sites of the transferrin molecule.

scholarly journals The distribution of iron between the metal-binding sites of transferrin human serum

1980 ◽  
Vol 185 (2) ◽  
pp. 483-488 ◽  
Author(s):  
J Williams ◽  
K Moreton
Keyword(s):  
Human Serum ◽  
Metal Binding ◽  
Binding Sites ◽  
Gel Electrophoresis ◽  
Polyacrylamide Gel Electrophoresis ◽  
Iron Binding ◽  
Metal Binding Sites ◽  
Fresh Serum ◽  
Marked Preference ◽  
Terminal Site

The Makey & Seal [(1976) Biochim. Biophys. Acta 453, 250-256] method of polyacrylamide-gel electrophoresis in buffer containing 6 M-urea was used to determine the distribution of iron between the N-terminal and C-terminal iron-binding sites of transferrin in human serum. In fresh serum the two sites are unequally occupied; there is preferential occupation of the N-terminal site. On incubation of the serum at 37 degrees C the preference of iron for the N-terminal site becomes more marked. On storage of serum at −15 degrees C the iron distribution changes so that there is a marked preference for the C-terminal site. Dialysis of serum against buffer at pH 7.4 also causes iron to be bound much more strongly by the C-terminal than by the N-terminal site. The original preference for the N-terminal site can be resroted to the dialysed serum by addition of the diffusible fraction.

scholarly journals Rational design of metal-binding sites in domain-swapped myoglobin dimers

2021 ◽  
Vol 217 ◽  
pp. 111374
Author(s):  
Satoshi Nagao ◽  
Ayaka Idomoto ◽  
Naoki Shibata ◽  
Yoshiki Higuchi ◽  
Shun Hirota
Keyword(s):  
Metal Binding ◽  
Binding Sites ◽  
Rational Design ◽  
Metal Binding Sites

scholarly journals Electron transfer pathways in photoexcited lanthanide(III) complexes of picolinate ligands

2021 ◽  
Author(s):  
Daniel Kovacs ◽  
Daniel Kocsi ◽  
Jordann A. L. Wells ◽  
Salauat R. Kiraev ◽  
Eszter Borbas
Keyword(s):  
Electron Transfer ◽  
Metal Binding ◽  
Binding Sites ◽  
Secondary Amide ◽  
Metal Binding Sites ◽  
Electron Transfer Pathways

A series of luminescent lanthanide(III) complexes consisting of 1,4,7-triazacyclononane frameworks and three secondary amide-linked carbostyril antennae were synthesised. The metal binding sites were augmented with two pyridylcarboxylate donors yielding octadentate...

scholarly journals Machine learning differentiates enzymatic and non-enzymatic metals in proteins

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ryan Feehan ◽  
Meghan W. Franklin ◽  
Joanna S. G. Slusky
Keyword(s):  
Machine Learning ◽  
Metal Binding ◽  
Binding Sites ◽  
Active Sites ◽  
De Novo ◽  
Enzyme Design ◽  
Metal Binding Sites ◽  
Ensemble Machine Learning ◽  
Machine Learning Model ◽  
Physicochemical Features

AbstractMetalloenzymes are 40% of all enzymes and can perform all seven classes of enzyme reactions. Because of the physicochemical similarities between the active sites of metalloenzymes and inactive metal binding sites, it is challenging to differentiate between them. Yet distinguishing these two classes is critical for the identification of both native and designed enzymes. Because of similarities between catalytic and non-catalytic  metal binding sites, finding physicochemical features that distinguish these two types of metal sites can indicate aspects that are critical to enzyme function. In this work, we develop the largest structural dataset of enzymatic and non-enzymatic metalloprotein sites to date. We then use a decision-tree ensemble machine learning model to classify metals bound to proteins as enzymatic or non-enzymatic with 92.2% precision and 90.1% recall. Our model scores electrostatic and pocket lining features as more important than pocket volume, despite the fact that volume is the most quantitatively different feature between enzyme and non-enzymatic sites. Finally, we find our model has overall better performance in a side-to-side comparison against other methods that differentiate enzymatic from non-enzymatic sequences. We anticipate that our model’s ability to correctly identify which metal sites are responsible for enzymatic activity could enable identification of new enzymatic mechanisms and de novo enzyme design.

The metal-binding sites of glycose phosphates

2009 ◽  
pp. 7934 ◽  
Author(s):  
Kathrin Gilg ◽  
Tobias Mayer ◽  
Natascha Ghaschghaie ◽  
Peter Klüfers
Keyword(s):  
Metal Binding ◽  
Binding Sites ◽  
Metal Binding Sites

scholarly journals Developing Remote Metal Binding Sites in Heteropolymolybdates

2003 ◽  
Vol 2003 (13) ◽  
pp. 2406-2412 ◽  
Author(s):  
Pierre R. Marcoux ◽  
Bernold Hasenknopf ◽  
Jacqueline Vaissermann ◽  
Pierre Gouzerh
Keyword(s):  
Metal Binding ◽  
Binding Sites ◽  
Metal Binding Sites
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