Estimating computational limits on theoretical descriptions of biological cells

Area of Science:

• Computational Biology
• Theoretical Biology
• Biophysics

Background:

• Recent advances in molecular-level simulations aim for first-principles modeling of whole cells.
• The immense complexity of cells poses a significant challenge to achieving whole-cell simulations.

Purpose of the Study:

• To establish approximate equations for estimating computation times for cell simulations.
• To define limits on cellular complexity addressable by molecular dynamics and molecular kinetics.
• To develop foundational concepts for biological uncertainty relations in molecular cell models.

Main Methods:

• Developing approximate equations to estimate computational time.
• Analyzing simulation requirements for molecular dynamics calculations.
• Analyzing simulation requirements for solving molecular kinetic equations.

Main Results:

• Derived equations provide estimates for computation times for simplified cell models.
• Established theoretical limits on the complexity of cells that can be simulated.
• Identified that molecular kinetics may soon allow simulation of the simplest bacterial cell.

Conclusions:

• Computational simulation of whole cells is constrained by cellular complexity.
• Complex multicellular systems like the human brain are unlikely to be simulated for decades, even with quantum computing.
• The study provides a framework for understanding the limits of theoretical biological modeling.