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Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
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Related Experiment Video

Updated: May 25, 2026

Realistic Membrane Modeling Using Complex Lipid Mixtures in Simulation Studies
07:31

Realistic Membrane Modeling Using Complex Lipid Mixtures in Simulation Studies

Published on: September 1, 2023

Force fields for homology modeling.

Andrew J Bordner1

  • 1Mayo Clinic, Scottsdale, AZ, USA. bordner.andrew@mayo.edu

Methods in Molecular Biology (Clifton, N.J.)
|February 11, 2012
PubMed
Summary

Accurate all-atom energy functions are essential for predicting protein structures. This review covers physics-based force fields and knowledge-based potentials, including solvation models, for precise protein modeling.

Area of Science:

  • Computational biology
  • Biophysics
  • Structural biology

Background:

  • Accurate all-atom energy functions are critical for high-resolution protein structure prediction.
  • Protein modeling relies on both physics-based force fields and knowledge-based potentials.
  • Understanding protein energetics requires detailed consideration of various energy components and force field complexities.

Purpose of the Study:

  • To review physics-based force fields and knowledge-based potentials for protein modeling.
  • To discuss different components of energy functions and their representation in force fields.
  • To describe aqueous and membrane solvation models relevant to protein energetics.

Main Methods:

  • Review of existing literature on physics-based force fields and knowledge-based potentials.

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Last Updated: May 25, 2026

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  • Discussion of Cartesian and torsion angle representations of protein geometry.
  • Description of solvation models for protein simulations.

    • Main Results:

    • Comprehensive overview of force fields and potentials used in protein structure prediction.
    • Analysis of different energy components and their impact on accuracy.
    • Inclusion of various solvation models for aqueous and membrane environments.

    Conclusions:

    • Accurate energy functions are fundamental for successful protein structure prediction.
    • The choice of force field representation and solvation model impacts simulation accuracy.
    • Recent advancements in force fields are improving protein structure refinement.