Evidence for the sequential folding mechanism in RNase H from an ensemble-based model

Area of Science:

• Biochemistry
• Computational Biology
• Protein Dynamics

Background:

• Protein folding mechanisms are complex and influenced by protein size, sequence, and stability.
• Conventional experiments often mask the intricate folding landscape due to their ensemble nature.
• Recent hydrogen-exchange mass spectrometry (HX-MS) suggests a hierarchical folding pathway for RNase H.

Purpose of the Study:

• To provide computational evidence for the unique folding mechanism of RNase H.
• To model the folding landscape and identify intermediate states computationally.
• To gain structural and energetic insights into RNase H folding stages.

Main Methods:

• Structure-based statistical mechanical modeling calibrated with equilibrium measurements.
• Explicit solvent molecular simulations of helical units.
• Electrostatic calculations.

Main Results:

• The computational model predicts multiple intermediate states in RNase H folding, consistent with experimental findings.
• A simplified landscape representation captures folding complexity and suggests a defined sequence of events.
• Simulations and calculations offer insights into early/late folding stages and the frustrated nature of the landscape.

Conclusions:

• Computational evidence supports a unique, hierarchical folding pathway for RNase H.
• The folding landscape of RNase H is complex but can be adequately represented by simplified models.
• The study provides a deeper understanding of protein folding mechanisms and the factors influencing them.