Protein Adaptive Plasticity and Night Vision

TL;DR

This paper demonstrates that the molecular properties of rhodopsin, related to night vision, can be effectively analyzed using a scale based on self-organized network criticality, revealing insights into adaptive plasticity across species.

Contribution

It introduces a novel application of the Moret-Zebende hydropathicity scale to quantify species-specific protein properties, surpassing traditional sequence similarity methods.

Findings

Long-range adaptive plasticity enhances molecular functionality.

Hydropathicity scale provides species-specific insights.

Results suggest universal applicability for protein analysis.

Abstract

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.