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Efficient High-Throughput DNA Breathing Features Generation Using Jax-EPBD.

Toki Tahmid Inan1,2, Anowarul Kabir1,2, Kim Rasmussen1

  • 1Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM.

Biorxiv : the Preprint Server for Biology
|December 23, 2024
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Summary
This summary is machine-generated.

JAX-EPBD accelerates DNA breathing dynamics simulations by 30x, improving transcription factor binding predictions and revealing sequence-specific bubble dynamics linked to gene regulation.

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Area of Science:

  • Computational Biology
  • Molecular Dynamics
  • Genomics

Background:

  • DNA breathing dynamics, transient base-pair openings, are crucial for DNA-templated processes.
  • Existing models like EPBD face computational limits for analyzing long DNA sequences.

Purpose of the Study:

  • Introduce JAX-EPBD, a GPU-accelerated framework for high-throughput DNA breathing simulations.
  • Enhance the scalability and speed of analyzing DNA dynamics for genome-scale applications.

Main Methods:

  • Developed JAX-EPBD using JAX for GPU acceleration, enabling Langevin molecular dynamics.
  • Achieved up to 30x speedup and improved scalability over traditional C-based EPBD.
  • Applied JAX-EPBD to predict transcription factor binding affinity and analyze promoter dynamics.

Main Results:

  • JAX-EPBD efficiently captures time-dependent DNA breathing behaviors like bubble lifetimes and base flipping kinetics.
  • Incorporating DNA breathing features improved transcription factor binding affinity predictions.
  • Observed sequence-specific bubble dynamics in the AAV P5 promoter correlating with transcriptional activity.

Conclusions:

  • JAX-EPBD is a powerful, scalable tool for studying DNA breathing dynamics.
  • The framework facilitates understanding DNA breathing's role in gene regulation and TF binding.
  • Enables genome-scale analyses of DNA dynamics for biological insights.