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The Journal of General Physiology, Vol 107, 271-291, Copyright © 1996 by The Rockefeller University Press
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SQ Liu, FY Law and PA Knauf
Department of Biophysics, University of Rochester School of Medicine and Dentistry, New York, USA.
To test the hypothesis that amino acid residues in band 3 with titratable positive charges play a role in the binding of anions to the outside-facing transport site, we measured the effects of changing external pH (pH(O)) on the dissociation constant for binding of external iodide to the transport site, K(O)(I). K(O)(I) increased with increasing pH(O), and a significant increase was seen even at pH(O) values as low as 9.9. The dependence of K(O)(I) on pH(O) can be explained by a model with one titratable site with pK 9.5 +/- 0.2 (probably lysine), which increases anion affinity for the external transport site when it is in the positively charged form. A more complex model, analogous to one recently proposed by Bjerrum (1992), with two titratable sites, one with pK 9.3 +/- 0.3 (probably lysine) and another with pK > 11 (probably arginine), gives a slightly better fit to the data. Thus, titratable positively charged residues seem to be functionally important for the binding of substrate anions to the outward-facing anion transport site. In addition, analysis of Dixon plot slopes for L inhibition of Cl- exchange at different pH 0 values, coupled with the assumption that pH(O) has parallel effects on external I- and Cl- binding, indicates that k', the rate-constant for inward translocation of the complex of Cl- with the extracellular transport site, decreases with increasing pH(O). The data are compatible with a model in which titration of the pK 9.3 residue decreases k to 14 +/- 10% of its value at neutral pH(O). This result, however, together with Bjerrum's (1992) observation that the maximum flux J(M)) increases 1.6- fold when this residue is deprotonated, makes quantitative predictions that raise significant questions about the adequacy of the two titratable site ping-pong model or the assumptions used in analyzing the data.
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