Accelerating Rare Dissociative Processes in Biomolecules Using Selectively Scaled MD Simulations.

Area of Science:

• Computational Chemistry
• Molecular Dynamics Simulations
• Biophysics

Background:

• Molecular dynamics (MD) simulations are valuable for studying ligand unbinding.
• Biologically relevant dissociation events often occur on timescales longer than typical MD simulations.
• Enhanced sampling methods are needed to overcome timescale limitations in MD.

Purpose of the Study:

• To implement and apply a novel enhanced sampling method for accelerating dissociative processes in MD simulations.
• To utilize selectively scaled molecular dynamics (ssMD) to expedite ligand unbinding events.
• To enable realistic estimation of unbinding times and free energy changes from simulation data.

Main Methods:

• Developed and applied a selectively scaled molecular dynamics (ssMD) approach.
• Selective scaling of specific energy terms, particularly ligand-water interactions, to accelerate dissociation.
• Employed Kramers'-based rate extrapolation and a novel free energy extrapolation method.

Main Results:

• ssMD successfully accelerated ligand unbinding in cyclin-dependent kinase-inhibitor complexes, with events occurring in as little as 2 ns.
• Realistic estimates of initial unbinding times (τ_unbind^sim) were obtained.
• Accurate estimations of the free energy change (ΔG^sim) associated with inhibitor unbinding were achieved.

Conclusions:

• The ssMD method effectively accelerates complex dissociative processes like ligand unbinding.
• ssMD allows for timely estimation of key kinetic and thermodynamic parameters.
• This general and easily deployable ssMD approach has broad applicability for modeling other dissociative events.