From structure to function: the convergence of structure based models and co-evolutionary information.

Area of Science:

• Biophysics
• Computational Biology
• Molecular Biology

Background:

• Protein folding and function are central to biological research, often studied using energy landscape theory and structure-based models (SBMs).
• SBMs are limited by the availability of structural information for various functional states.
• Amino acid co-evolution analysis offers insights into residue-residue interactions, complementing structural data.

Purpose of the Study:

• To develop and apply a novel computational method combining SBMs and co-evolutionary analysis to investigate protein folding and function.
• To explore the mechanistic aspects of protein translocation in the integral membrane protease FtsH.

Main Methods:

• Dual basin-SBM simulations utilizing open and closed states of the FtsH hexameric motor.
• Direct Coupling Analysis (DCA) to predict residue-residue interactions.
• Integration of experimental structural information with co-evolutionary couplings.

Main Results:

• A functionally important paddling motion was identified in the catalytic cycle of FtsH.
• DCA predicted crucial physical contacts between AAA and peptidase domains, facilitating the open-to-close transition.
• The combined method successfully explored the functional landscape of FtsH, overcoming limitations of purely structure-dependent methods.

Conclusions:

• The integrated SBM and co-evolutionary analysis approach provides a powerful framework for studying complex biomolecular mechanisms.
• This methodology enhances the characterization of functional landscapes in large biomolecular assemblies, even with limited experimental structural data.