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协同配体-晶格结合。近似高斯结合分布。

Cooperative ligand-lattice binding. Approximate Gaussian binding distribution.

作者信息

Reiter J, Epstein I R

机构信息

Department of Chemistry, Brandeis University, Waltham, MA 02254.

出版信息

Biophys Chem. 1989 Mar;33(1):1-9. doi: 10.1016/0301-4622(89)80001-8.

Abstract

Nearest-neighbor cooperative binding of a ligand covering n sites and binding with equilibrium constant K and cooperativity factor omega to a large molecule with m binding sites (m much greater than n omega, n/omega) can be approximately described by a Gaussian distribution P(q-qmax), where q is the number of ligands bound and qmax the most probable value of q. The variance of the Gaussian is equal to the derivative dqmax/d ln(L), where L is the free ligand concentration. This variance, sigma 2, is a complicated function of qmax. However, in the limits of very large cooperativity, omega much greater than 1, very large anticooperativity, omega much less than 1, or noncooperativity, omega = 1, simpler expressions for sigma 2 can be given. For qmax = m/(n + 1), where the most probable number of bound ligands equals the number of free binding sites, sigma 2 has a particularly simple form: sigma 2 = 2m omega 1/2/(n + 1)3. The Gaussian and the infinite lattice approximations for the average number of ligands bound are good approximations only if sigma is much smaller than the number of binding sites. The variance may therefore provide an easy check on the validity of the infinite lattice approximation, which is commonly used to analyze experimental binding data.

摘要

一个覆盖(n)个位点、结合平衡常数为(K)且协同因子为(\omega)的配体与具有(m)个结合位点((m)远大于(n\omega)、(n / \omega))的大分子的最近邻协同结合,可以近似用高斯分布(P(q - q_{max}))来描述,其中(q)是结合的配体数量,(q_{max})是(q)的最可能值。高斯分布的方差等于导数(dq_{max} / d\ln(L)),其中(L)是游离配体浓度。这个方差(\sigma^2)是(q_{max})的复杂函数。然而,在协同性非常大((\omega)远大于(1))、反协同性非常大((\omega)远小于(1))或非协同性((\omega = 1))的极限情况下,可以给出(\sigma^2)的更简单表达式。对于(q_{max} = m / (n + 1)),即结合的配体的最可能数量等于游离结合位点的数量时,(\sigma^2)具有特别简单的形式:(\sigma^2 = 2m\omega^{1/2} / (n + 1)^3)。仅当(\sigma)远小于结合位点数量时,高斯分布和无限晶格近似对于结合的配体平均数量才是良好的近似。因此,方差可以很容易地检验无限晶格近似的有效性,无限晶格近似常用于分析实验结合数据。

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