Complexity of Guanine Quadruplex Unfolding Pathways Revealed by Atomistic Pulling Simulations

Area of Science:

• Biophysics
• Molecular Biology
• Computational Chemistry

Background:

• Guanine quadruplexes (GQs) are non-canonical nucleic acid structures crucial for various biological processes.
• Understanding the mechanochemical properties of GQs is vital as they often require unwinding by cellular machinery.
• Human telomeric GQs serve as a model system for studying these structures.

Purpose of the Study:

• To investigate the unfolding mechanisms of human telomeric GQs using steered molecular dynamics simulations.
• To identify factors influencing GQ unfolding pathways under different pulling conditions.
• To assess the impact of pulling velocity and force direction on GQ structural dynamics.

Main Methods:

• Steered molecular dynamics (SMD) simulations were employed to mimic mechanical unfolding.
• Simulations were conducted under four distinct pulling regimes, including conditions relevant to high-speed atomic force microscopy.
• Analysis focused on identifying unfolding mechanisms, intermediates, and the influence of external forces.

Main Results:

• The direction of applied force significantly influences the unfolding pathway: perpendicular force favors base unzipping, while parallel force promotes GQ opening.
• Strand slippage is a possible unfolding mechanism for GQs with an all-anti pattern.
• Slower pulling velocities reveal richer structural dynamics, including intermediate states and partial refolding events.
• Unfolding can occur after a force drop below previously withstood forces.
• Different unfolding intermediates may exhibit similar end-to-end distances, complicating structural interpretation.

Conclusions:

• The unfolding mechanism of human telomeric GQs is highly sensitive to the applied force direction and pulling velocity.
• Computational simulations provide detailed insights into GQ mechanochemistry, revealing complex unfolding pathways.
• The study highlights potential limitations in interpreting single-molecule experimental data based solely on chain end-to-end distances.