Abstract
Fine-tuning has received much attention in physics, and it states that the fundamental constants of physics are finely tuned to precise values for a rich chemistry and life permittance. It has not yet been applied in a broad manner to molecular biology. However, in this paper we argue that biological systems present fine-tuning at different levels, e.g. functional proteins, complex biochemical machines in living cells, and cellular networks. This paper describes molecular fine-tuning, how it can be used in biology, and how it challenges conventional Darwinian thinking. We also discuss the statistical methods underpinning fine-tuning and present a framework for such analysis.
Highlights
Fine-tuning has obtained much attention in physics, and many studies have been accomplished since Brandon Carter presented his first results at the conference honoring Copernicus’s 500th birthday (Carter, 1974)
We focus on the topic of fine-tuning in the present paper and address the following questions: Is it possible to recognize fine-tuning in biological systems at the levels of functional proteins, protein groups and cellular networks? Can fine-tuning in molecular biology be formulated using state of the art statistical methods, or are the arguments just ‘‘in the eyes of the beholder”?
We have elaborated on basic information from DNA sequences, proteins, protein complexes, signaling pathways and networks, using the prevalence PðAÞ of an observed event A of fine-tuning, which corresponds to a Shannon information of Àlog2PðAÞ
Summary
Fine-tuning has obtained much attention in physics, and many studies have been accomplished since Brandon Carter presented his first results at the conference honoring Copernicus’s 500th birthday (Carter, 1974). Luke Barnes has published a good review paper on the fine-tuning of the universe (Barnes, 2012), and Lewis and Barnes wrote an up to date book (2016). This naturally raises the question whether it is appropriate to introduce and address fine-tuning in biology as well. The term fine-tuning is used to characterize sensitive dependences of functions or properties on the values of certain parameters (cf Friederich, 2018). While technological devices are fine-tuned products of actual engineers and manufacturers who designed and built them, only sensitivity with respect to the values of certain parameters or initial conditions are considered sufficient in the present paper.
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