Self-Organized Criticality: A Guide to Water-Protein Landscape Evolution

TL;DR

This paper investigates the water-protein landscape evolution using a hydropathic elastic roughening tool, revealing species-specific water film properties and estimating the human eye's color discrimination capacity.

Contribution

It introduces a hydropathic metric based on atomic coordinates to analyze water film roughness and evolutionary differences in water-protein landscapes across species.

Findings

Humans have the smoothest water films in rhodopsin blue rods.

Cats and elephants have optimized water films in red cone opsins.

Estimated human color discrimination capacity is between 10^6 and 10^7 shades.

Abstract

We focus here on the scaling properties of small interspecies differences between red cone opsin transmembrane proteins, using a hydropathic elastic roughening tool previously applied to the rhodopsin rod transmembrane proteins. This tool is based on a non-Euclidean hydropathic metric realistically rooted in the atomic coordinates of 5526 protein segments, which thereby encapsulates universal non-Euclidean long-range differential geometrical features of water films enveloping globular proteins in the Protein Data Bank. Whereas the rhodopsin blue rod water films are smoothest in humans, the red cone opsins' water films are optimized in cats and elephants, consistent with protein species landscapes that evolve differently in different contexts. We also analyze red cone opsins in the chromatophore-containing family of chameleons, snakes, zebrafish and goldfish, where short- and long-range (BLAST and hydropathic) aa correlations are found with values as large as 97-99%. We use hydropathic amino acid (aa) optimization to estimate the maximum number Nmax of color shades that the human eye can discriminate, and obtain 10^6 < Nmax < 10^7, in good agreement with experiment.