Multiscale modeling of biological functions

Area of Science:

• Computational Biology
• Biophysics
• Computational Chemistry

Background:

• Computational power has surged, enabling more complex all-atom simulations in biology and chemistry.
• However, computational time remains a limitation, and many significant problems were solved prior to current computational capabilities.

Purpose of the Study:

• To provide a historical overview of multiscale simulations in biology.
• To present key developments in multiscale simulation methodologies.
• To highlight instances where simplified, physically sound models surpass brute-force simulations.

Main Methods:

• Review of historical and recent literature on multiscale simulations.
• Analysis of case studies demonstrating the efficacy of multiscale approaches.
• Discussion of simulation methodologies and their physical underpinnings.

Main Results:

• Multiscale simulations have a rich history and have seen significant advancements.
• Physically sound simplifications in simulations can yield superior results compared to exhaustive methods.
• The review identifies specific examples where multiscale simulations were crucial.

Conclusions:

• Multiscale simulations are a vital tool in computational biology and chemistry, offering efficient solutions to complex problems.
• The strategic use of simplification is often more effective than purely brute-force computational approaches.
• Future directions in multiscale simulation techniques hold significant promise for scientific discovery.