  Proteins appear to be the most dramatic natural example of self-organized
network criticality (SONC), a concept that explains many otherwise apparently
exponentially unlikely phenomena. Adaptive plasticity is a term which has
become much more specific as a result of recent physiological and genetic
studies. Here we show that the molecular properties of rhodopsin, the
transmembrane protein associated with night vision, can be quantified species
by species using the Moret-Zebende hydropathicity scale based on SONC. The
results show that long-range adaptive plasticity optimizes proximate species
molecular functionality far more effectively than one would infer using only
standard amino acid sequence (local similarity) tools such as BLAST for
multiple alignments. These results should be universal, and they suggest new
paths for analyzing and predicting protein functionality from amino acid
sequences alone.
