The digital nature of biology is crucial to its functioning as an
information system, as well in building hierarchical components.
We attempt to explain how protein systems can function as discrete
components, despite the importance of non-specific forces due to
the hydrophobic effect. We address the question of why proteins
bind to other proteins predictably and not in a continuous
distribution of places, the way grease forms into blobs.
We explain how the differences in hydrophobicity in sidechains
cause the modulation of the dielectric effect in the vicinity of
proteins. This in turn has a significant effect on the strength
and stability of certain electrostatic bonds, which in turn guide
the interaction of proteins and ligands.
We will give a detailed description of how data mining in the
PDB can give clues to how proteins interact. This work makes
precise the notion of hydrophobic interaction in certain cases.
It provides an understanding of how molecular recognition and
signaling can evolve. This work also introduces a new model of
electrostatics for protein-solvent systems that presents
significant computational challenges. We give an example of the
use of our ideas in drug design.
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