Reinterpretation of Jagendorf's classic experiment on photophosphorylation

IF 1.9 4区 生物学 Q2 BIOLOGY
Gabi Drochioiu
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引用次数: 0

Abstract

Photophosphorylation is an anoxygenic process of ATP production, and here we provide relevant insights from recent literature with respect to multiple observations from classical experiments with chloroplasts, archaeal cells, or reconstituted vesicles. Since new and significant information on photophosphorylation has been accumulated, there is a strong necessity to reevaluate the experimental data obtained by Jagendorf, Racker, and other researchers, which were interpreted exclusively in light of the chemiosmotic hypothesis developed by Peter Mitchell. Although unsupported experimentally, the chemiosmotic hypothesis had the merit of proposing a molecular mechanism for the production of ATP molecules in mitochondria, which stimulated further biochemical research. Meanwhile, improved alternatives to the chemiosmotic concept have been advanced, as well as new theories based on recent experimental data. Therefore, it is desirable to carefully evaluate the advantages and drawbacks of these approaches.
重新诠释詹根多夫关于光磷酸化的经典实验。
光磷酸化是一个ATP生产的无氧过程,在这里,我们从最近的文献中提供了有关叶绿体,古细菌细胞或重构囊泡的经典实验的多个观察结果的相关见解。由于积累了关于光磷酸化的新的和重要的信息,因此非常有必要重新评估jengorf, Racker和其他研究人员获得的实验数据,这些数据完全是根据Peter Mitchell提出的化学渗透假说来解释的。虽然没有实验支持,但化学渗透假说的优点是提出了线粒体中ATP分子产生的分子机制,从而刺激了进一步的生化研究。与此同时,人们提出了化学渗透概念的改进替代方案,以及基于最新实验数据的新理论。因此,需要仔细评估这些方法的优点和缺点。
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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