Hydropathic self-organized criticality: a magic wand for protein physics

Area of Science:

• Computational Biology
• Biophysics
• Protein Science

Background:

• Self-organized criticality (SOC) is characterized by power-law scaling in observable properties.
• Protein-water interactions are crucial and can be described by water-accessible interfacial area.
• Understanding evolutionary trends in protein sequences is vital for biological research.

Purpose of the Study:

• To connect short-range amino acid sequence similarities to long-range hydropathic properties using SOC.
• To develop a method for analyzing evolutionary trends in water-membrane protein interactions.
• To simplify complex protein sequence-structure-function relationships.

Main Methods:

• Utilized hydropathic power-law exponents derived from SOC.
• Defined a non-Euclidean metric based on atomic coordinates of protein segments.
• Applied the method to analyze sequence differences in proteins, including rhodopsin.

Main Results:

• Connected standard Web-based (BLAST) short-range amino acid similarities to long-range hydropathic roughening form factors.
• Demonstrated that hydropathic exponents encapsulate universal non-Euclidean geometrical features of the Protein Data Bank.
• Achieved 96% success in correlating sequence properties for humans and other species' rhodopsin.

Conclusions:

• The application of SOC with hydropathic exponents offers a novel approach to protein analysis.
• This method simplifies the understanding of complex protein sequence-structure-function problems.
• The findings have implications for studying evolutionary relationships and protein behavior.