Direct coupling analysis of epistasis in allosteric materials.

Area of Science:

• Biophysics
• Computational Biology
• Protein Science

Background:

• Allosteric proteins regulate distant active sites via ligand binding.
• Inferring allosteric pathways from sequence data is crucial for drug design.
• Current methods yield conflicting results on long-range evolutionary couplings.

Purpose of the Study:

• To resolve the conundrum of inferring long-range allosteric pathways.
• To investigate epistasis and its inference in silico evolved models.
• To evaluate the performance of Direct Coupling Analysis (DCA) in capturing allosteric interactions.

Main Methods:

• In silico evolution of an allosteric material model for a mechanical task.
• Analysis of four types of epistasis (Synergistic, Sign, Antagonistic, Saturation).
• Application and evaluation of Direct Coupling Analysis (DCA).

Main Results:

• Identified four types of epistasis with mechanical interpretations, occurring at short and long ranges.
• DCA accurately predicts point mutation costs but is a poor generative model.
• DCA successfully predicts short-range epistasis but fails to capture long-range epistasis.

Conclusions:

• DCA's failure to capture long-range epistasis aligns with empirical findings.
• This failure is likely generic when protein subparts must cooperate for function.
• Alternative methods may be better suited for capturing long-range allosteric effects.