Thermodynamics of Nath’s 2-ion model for ATP synthesis

IF 1.9 4区 生物学 Q2 BIOLOGY
Lee D. Hansen , Sunil Nath
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引用次数: 0

Abstract

A major finding of studies of organic acid ionization was that substituents on an aliphatic chain attached to a carboxyl group have large effects on the equilibrium constant but very little effect on ΔionizH which is in the range 0 ± 4 kJ/mol for all carboxylic acids of this type. According to Nath’s 2-ion mechanism for ATP synthesis, succinic acid was selected by biological evolution because an acid that could be ionized with no energy input was required, i.e., with ΔionizH near zero. In support of this, ATP synthesis evolved in prokaryotes in a world without oxygen in the atmosphere and consequently catabolic reactions in prokaryotes that are coupled to ATP synthesis generally have small enthalpy changes. ATP synthesis in anaerobes is thus driven by the potential energy in concentration gradients. This potential energy is associated with a probability field quantified by the change in the number of microstates of particle distributions. ATP synthesis is thus powered by a probability field associated with a concentration gradient of ions consistent with Nath’s 2-ion mechanism.
ATP合成的Nath 2离子模型热力学。
有机酸电离研究的一个主要发现是,与羧基连接的脂肪链上的取代基对平衡常数有很大的影响,但对ΔionizH的影响很小,该平衡常数在0±4 kJ/mol范围内。根据Nath的2离子ATP合成机制,琥珀酸是生物进化选择的,因为它不需要能量输入就可以电离,即ΔionizH接近于零。为了支持这一点,原核生物在大气中没有氧气的环境中进化了ATP合成,因此,与ATP合成耦合的原核生物的分解代谢反应通常具有很小的焓变化。因此,厌氧生物的ATP合成是由浓度梯度中的势能驱动的。这个势能与一个由粒子分布的微观状态数目的变化所量化的概率场有关。因此,ATP的合成是由与Nath的2离子机制一致的离子浓度梯度相关的概率场驱动的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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