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Geometry for optimal bistate molecular machines.

efficiency equation on blackboard
emmgeo: 70% efficiency of bistate molecular machines explained by information theory, high dimensional geometry and evolutionary convergence
  Thomas D. Schneider
Nucleic Acids Research (2010) 38: 5995-6006, doi: 10.1093/nar/gkq389

Abstract: The relationship between information and energy is key to understanding biological systems. We can display the information in DNA sequences specifically bound by proteins by using sequence logos, and we can measure the corresponding binding energy. These can be compared by noting that one of the forms of the second law of thermodynamics defines the minimum energy dissipation required to gain one bit of information. Under the isothermal conditions that molecular machines function this is Emin = kB T ln 2 joules per bit (kB is Boltzmann's constant and T is the absolute temperature). Then an efficiency of binding can be computed by dividing the information in a logo by the free energy of binding after it has been converted to bits. The isothermal efficiencies of not only genetic control systems, but also visual pigments are near 70%. From information and coding theory, the theoretical efficiency limit for bistate molecular machines is ln2 = 0.6931. Evolutionary convergence to maximum efficiency is limited by the constraint that molecular states must be distinct from each other. The result indicates that natural molecular machines operate close to their information processing maximum (the channel capacity), and implies that nanotechnology can attain this goal.
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Acceptance Celebration Song: Time machine - Eloi.

This paper is probably my Magnum opus.

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origin: 2010 Apr 30
updated: version = 1.27 of emmgeo.html 2019 Oct 31

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