Structural Biology/Bioinformatics, University of Bayreuth, Universitätsstrasse 30, BGI, 95447 Bayreuth, Germany.
J Phys Chem B. 2010 Feb 11;114(5):1994-2003. doi: 10.1021/jp908926w.
Because of their central importance for understanding enzymatic mechanisms, pK(a) values are of great interest in biochemical research. It is common practice to determine pK(a) values of amino acid residues in proteins from NMR or FTIR titration curves by determining the pH at which the protonation probability is 50%. The pH dependence of the free energy required to protonate this residue is then determined from the linear relationship DeltaG(prot) = RT ln 10 (pH-pK(a)), where R is the gas constant and T the absolute temperature. However, this approach neglects that there can be important electrostatic interactions in the proteins that can shift the protonation energy. Even if the titration curves seem to have a standard sigmoidal shape, the protonation energy of an individual site in a protein may depend nonlinearly on pH. To account for this nonlinear dependence, we show that it is required to introduce pK(a) values for individual sites in proteins that depend on pH. Two different definitions are discussed. One definition is based on a rearranged Henderson-Hasselbalch equation, and the other definition is based on an equation that was used by Tanford and Roxby to approximate titration curves of proteins. In the limiting case of weak interactions, the two definitions lead to nearly the same pK(a) value. We discuss how these two differently defined pK(a) values are related to the free energy change required to protonate a site. Using individual site pK(a) values, we demonstrate on simple model systems that the interactions between protonatable residues in proteins can help to maintain the energy required to protonate a site in the protein nearly constant over a wide pH range. We show with the example of RNase T1 that such a mechanism to keep the protonation energy constant is used in enzymes. The pH dependence of pK(a) values may be an important concept in enzyme catalysis. Neglecting this concept, important features of enzymes may be missed, and the enzymatic mechanism may not be fully understood.
由于它们对理解酶机制至关重要,pK(a) 值在生化研究中具有重要意义。通常情况下,通过从 NMR 或 FTIR 滴定曲线确定质子化概率为 50%时的 pH 值,来确定蛋白质中氨基酸残基的 pK(a) 值。然后,通过线性关系 DeltaG(prot) = RT ln 10 (pH-pK(a)),确定该残基质子化所需的自由能 pH 依赖性,其中 R 是气体常数,T 是绝对温度。然而,这种方法忽略了蛋白质中可能存在重要的静电相互作用,这些相互作用会改变质子化能。即使滴定曲线似乎具有标准的 S 形形状,蛋白质中单个位点的质子化能也可能与 pH 呈非线性关系。为了解释这种非线性依赖性,我们表明需要引入蛋白质中依赖 pH 的单个位点的 pK(a) 值。讨论了两种不同的定义。一种定义基于重新排列的 Henderson-Hasselbalch 方程,另一种定义基于 Tanford 和 Roxby 用于近似蛋白质滴定曲线的方程。在弱相互作用的极限情况下,这两种定义导致几乎相同的 pK(a) 值。我们讨论了这两种不同定义的 pK(a) 值与质子化一个位点所需的自由能变化之间的关系。使用单个位点 pK(a) 值,我们在简单的模型系统上证明,蛋白质中可质子化残基之间的相互作用有助于在宽 pH 范围内使蛋白质中一个位点的质子化所需的能量几乎保持不变。我们以 RNase T1 为例表明,这种保持质子化能恒定的机制在酶中被使用。pK(a) 值的 pH 依赖性可能是酶催化中的一个重要概念。忽略这个概念,可能会错过酶的重要特征,并且可能无法完全理解酶的机制。