Disassembly orders of protein complexes by coarse-grained simulations with dynamic native contacts

Area of Science:

• Structural biology
• Computational biophysics
• Biochemistry

Background:

• Protein complexes are essential for biological functions, but their assembly and disassembly dynamics are poorly understood.
• Current experimental methods for determining assembly/disassembly order are costly and time-consuming.
• Existing computational models often neglect crucial residue-specific interactions.

Purpose of the Study:

• To develop a cost-effective computational method for predicting the disassembly order of protein complexes.
• To improve coarse-grained (CG) models by incorporating residue-specific native contact information.
• To provide insights into protein complex assembly mechanisms.

Main Methods:

• Utilized all-atom molecular dynamics simulations to analyze native contacts in protein complexes.
• Developed a residue-specific re-parametrization strategy for coarse-grained (CG) models.
• Employed cyclic multitemperature CG simulations with reweighted native contact strengths to predict disassembly pathways.

Main Results:

• The novel computational approach successfully predicted the correct disassembly order for 14 out of 21 tested protein complexes.
• Partially correct disassembly orders were predicted for an additional six complexes.
• The method demonstrated the importance of residue-specific native contacts in modeling complex dynamics.

Conclusions:

• The proposed computational method offers a reliable and efficient alternative to experimental techniques for determining protein complex disassembly order.
• This approach enhances the accuracy of coarse-grained (CG) models by integrating detailed residue-level information.
• The findings facilitate advancements in protein engineering, drug design, and understanding fundamental biological processes.