Flexible Backbone Assembly and Refinement of Symmetrical Homomeric Complexes

Area of Science:

• Structural biology
• Computational biochemistry
• Bioinformatics

Background:

• Symmetrical homomeric proteins are vital across all life domains, but their large size challenges experimental structure determination.
• Accurate protein structure modeling is crucial for understanding protein function.
• Existing computational docking algorithms struggle with backbone inaccuracies in homology-modeled monomers.

Purpose of the Study:

• To present Rosetta SymDock2, an advanced computational tool for modeling symmetrical protein complexes.
• To improve the accuracy and physical realism of modeling large, symmetrical protein structures.

Main Methods:

• Rosetta SymDock2 employs a broad search of symmetrical conformational space using a six-dimensional coarse-grained score function.
• An all-atom flexible-backbone refinement step is integrated for physically realistic modeling.
• The method was tested on a benchmark set of complexes with varying point symmetries, starting from homology-modeled monomers.

Main Results:

• Rosetta SymDock2 successfully docked 17 out of 31 cyclic complexes and 3 out of 12 dihedral complexes.
• The definition of successful docking involved predicting three near-native structures within the top five scoring models.
• The all-atom flexible-backbone refinement was demonstrated as essential for modeling tightly packed complexes.

Conclusions:

• Rosetta SymDock2 offers a significant advancement in modeling symmetrical protein complexes, particularly those derived from homology models.
• The computational approach provides a viable alternative for structure determination when experimental methods are intractable.
• This tool aids in deciphering the function of ubiquitous symmetrical protein structures.