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PathGennie: Rapid Generation of Rare Event Pathways via Direction-Guided Adaptive Sampling Using Ultrashort Monitored

Dibyendu Maity1, Shaheerah Shahid1, Suman Chakrabarty1

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PathGennie rapidly generates molecular transition pathways using adaptive sampling, accelerating simulations of rare events like protein folding and ligand unbinding without external forces. This method enhances the efficiency of molecular dynamics simulations.

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Area of Science:

  • Computational chemistry
  • Molecular dynamics simulations
  • Biophysics

Background:

  • Simulating rare molecular events (e.g., ligand unbinding, protein folding) is computationally challenging.
  • Traditional methods often require extensive sampling or external biasing, which can distort dynamics.

Purpose of the Study:

  • To present PathGennie, a novel framework for efficient generation of transition pathways.
  • To overcome limitations of existing methods in simulating rare molecular events.

Main Methods:

  • PathGennie employs direction-guided adaptive sampling with swarms of ultrashort, unbiased trajectories.
  • It selectively propagates trajectories progressing towards a defined goal in collective variable space.
  • The framework avoids external biasing forces and thermal perturbation.

Main Results:

  • PathGennie successfully identified multiple competing unbinding pathways for small molecules (benzene, imatinib) and folding/unfolding transitions for proteins (Trp-cage, Protein G).
  • Physically meaningful pathways were generated on a picosecond timescale (10-100 ps).
  • Pathways generated by PathGennie significantly accelerated convergence in subsequent weighted ensemble (WE) simulations.

Conclusions:

  • PathGennie offers an efficient and broadly applicable method for generating transition pathways in molecular dynamics.
  • The framework accelerates the study of rare molecular events and improves the efficiency of path sampling methods.
  • The PathGennie software is freely available to the research community.