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配体和/或质子与大分子结合的位点亲和常数及协同系数的计算。II. 化学模型与配分函数算法之间的关系。

Calculation of site affinity constants and cooperativity coefficients for binding of ligands and/or protons to macromolecules. II. Relationships between chemical model and partition function algorithm.

作者信息

Fisicaro E, Braibanti A, Lamb J D, Oscarson J L

机构信息

Institute of Applied Physical Chemistry, University of Parma, Italy.

出版信息

Biophys Chem. 1990 May;36(1):15-25. doi: 10.1016/0301-4622(90)85002-n.

Abstract

The relationships between the chemical properties of a system and the partition function algorithm as applied to the description of multiple equilibria in solution are explained. The partition functions ZM, ZA, and ZH are obtained from powers of the binary generating functions Jj = (1 + kappa j gamma j,i[Y])i tau j, where i tau j = p tau j, q tau j, or r tau j represent the maximum number of sites in sites in class j, for Y = M, A, or H, respectively. Each term of the generating function can be considered an element (ij) of a vector Jj and each power of the cooperativity factor gamma ij,i can be considered an element of a diagonal cooperativity matrix gamma j. The vectors Jj are combined in tensor product matrices L tau = (J1) [J2]...[Jj]..., thus representing different receptor-ligand combinations. The partition functions are obtained by summing elements of the tensor matrices. The relationship of the partition functions with the total chemical amounts TM, TA, and TH has been found. The aim is to describe the total chemical amounts TM, TA, and TH as functions of the site affinity constants kappa j and cooperativity coefficients bj. The total amounts are calculated from the sum of elements of tensor matrices Ll. Each set of indices (pj..., qj..., rj...) represents one element of a tensor matrix L tau and defines each term of the summation. Each term corresponds to the concentration of a chemical microspecies. The distinction between microspecies MpjAqjHrj with ligands bound on specific sites and macrospecies MpAqHR corresponding to a chemical stoichiometric composition is shown. The translation of the properties of chemical model schemes into the algorithms for the generation of partition functions is illustrated with reference to a series of examples of gradually increasing complexity. The equilibria examined concern: (1) a unique class of sites; (2) the protonation of a base with two classes of sites; (3) the simultaneous binding of ligand A and proton H to a macromolecule or receptor M with four classes of sites; and (4) the binding to a macromolecule M of ligand A which is in turn a receptor for proton H. With reference to a specific example, it is shown how a computer program for least-squares refinement of variables kappa j and bj can be organized. The chemical model from the free components M, A, and H to the saturated macrospecies MpAQHR, with possible complex macrospecies MpAq and AHR, is defined first.(ABSTRACT TRUNCATED AT 250 WORDS)

摘要

本文解释了系统的化学性质与用于描述溶液中多重平衡的配分函数算法之间的关系。配分函数ZM、ZA和ZH是从二元生成函数Jj = (1 + κjγj,i[Y])iτj的幂次中获得的,其中iτj = pτj、qτj或rτj分别表示j类位点中的最大位点数,Y = M、A或H。生成函数的每一项都可视为向量Jj的一个元素(ij),协同因子γij,i的每一次幂都可视为对角协同矩阵γj的一个元素。向量Jj在张量积矩阵Lτ = (J1)[J2]...[Jj]...中组合,从而表示不同的受体 - 配体组合。配分函数通过对张量矩阵的元素求和得到。已发现配分函数与总化学量TM、TA和TH之间的关系。目的是将总化学量TM、TA和TH描述为位点亲和常数κj和协同系数bj的函数。总量是从张量矩阵Ll的元素总和计算得出的。每组指标(pj...,qj...,rj...)表示张量矩阵Lτ的一个元素,并定义求和的每一项。每一项对应一种化学微物种的浓度。展示了在特定位点结合配体的微物种MpjAqjHrj与对应化学计量组成的宏物种MpAqHR之间的区别。通过一系列复杂度逐渐增加的示例,说明了将化学模型方案的性质转化为配分函数生成算法的过程。所研究的平衡涉及:(1) 一类独特的位点;(2) 具有两类位点的碱的质子化;(3) 配体A和质子H同时与具有四类位点的大分子或受体M结合;(4) 配体A(其本身又是质子H的受体)与大分子M的结合。参照一个具体示例,展示了如何组织用于对变量κj和bj进行最小二乘优化的计算机程序。首先定义了从自由成分M、A和H到饱和宏物种MpAQHR以及可能的复杂宏物种MpAq和AHR的化学模型。(摘要截选至250字)

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