a open book
mmoptimal
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.
To look up the terms marked above,
1. click this link to the glossary of terms to launch a new window with the glossary in it.
2. Click any term above to control the location shown in the glossary window. If you already have clicked on a term above first, close that window and go to step 1.

Background Papers

Works that depend on this work


Acceptance Celebration Song: Time machine - Eloi.

This paper is probably my Magnum opus.

Permanent links Tinyurl for this page: http://tinyurl.com/emmgeo points to https://alum.mit.edu/www/toms/papers/emmgeo/ which points to the current web location.

color bar Small icon for Theory of Molecular Machines: physics,
chemistry, biology, molecular biology, evolutionary theory,
genetic engineering, sequence logos, information theory,
electrical engineering, thermodynamics, statistical
mechanics, hypersphere packing, gumball machines, Maxwell's
Daemon, limits of computers


Schneider Lab

origin: 2010 Apr 30
updated: version = 1.28 of emmgeo.html 2024 Feb 12

color bar