An important class of biological molecules—proteins called ionic channels—conduct ions (like Na+ , K+ , Ca2+ , and Cl− ) through a narrow tunnel of fixed charge (‘doping’). Ionic channels control the movement of electric charge and current across biological membranes and so play a role in biology as significant as the role of transistors in computers: a substantial fraction of all drugs used by physicians act on channels. Channels can be studied in the tradition of physical science because the ions near and in channels form an ionic liquid, a plasma in both the biological and physical meaning of the word. Poisson-Drift diffusion equations familiar in physics (called the PNP or Poisson Nernst Planck equations in biophysics) form can be extended to describe ‘chemical’ phenomena like selectivity with some success by including correlations produced by the finite size of the ions. Complex phenomena of selectivity in this reduced model comes from the balance of simple attractive (mostly electrostatic) and repulsive (mostly excluded volume) forces. Preformed structures and chemical bonds like cation-π interactions play no role in these models. Two parameters (volume and dielectric coefficient) set to invariant values are enough to predict the selectivity of DEEA calcium channels in a wide range of solutions. The same model and parameters predict the very different properties of the DEKA sodium channel, including selectivity for Na+ vs. K+ in a wide variety of solutions. The same reduced model accounts for the properties of the RyR channel in some 100 solutions, and predicted several complex experimental results before they were observed. Nonselective bacterial channels have been mutated into selective calcium channels as predicted by the model and selective nanoholes in plastic have been made. In these models, the structure of ‘side chains’ is an output of the model, in marked contrast to the usual view of crystallographic structures. We are unaware of other models — crystallographic or computational — that deal successfully with selectivity phenomena over a range of concentrations, mutations and channel types.
The Network for Computational Nanotechnology
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