Numerical solution of compartment-based reaction/diffusion models with DABOSS algorithm.

Area of Science:

• Biophysics
• Computational Biology
• Biochemistry

Background:

• Intracellular molecular transport is crucial for cellular function.
• Modeling diffusive movement with buffering chelators often uses compartmental approaches.
• Existing models face challenges with accuracy and computational efficiency for complex systems.

Purpose of the Study:

• To present a novel algorithm for solving time-dependent differential equations governing intracellular diffusion with buffering.
• To introduce the Dynamic and Balanced Operator Splitting Scheme (DABOSS) for improved simulation accuracy and efficiency.
• To demonstrate the algorithm's applicability to systems requiring high spatial resolution.

Main Methods:

• Developed the Dynamic and Balanced Operator Splitting Scheme (DABOSS).
• Combined dynamic time stepping to minimize steps and bound errors.
• Employed balanced operator splitting to efficiently solve diffusion and reaction components while preserving steady-state behavior.

Main Results:

• DABOSS demonstrates near-linear scaling with the number of compartments.
• The algorithm maintains accuracy over extended simulation durations.
• DABOSS shows efficiency in modeling nanometer-sized compartments with flux sources.

Conclusions:

• DABOSS provides an accurate and efficient method for simulating intracellular diffusion with buffering.
• The algorithm's scalability and efficiency make it suitable for complex biological systems.
• DABOSS enables higher spatial resolution in modeling molecular transport, advancing computational biology.