Molecular dynamics

Molecular dynamics is a simulation method that calculates how interacting atoms move over time by numerically integrating their equations of motion.

Interatomic potential: A mathematical function that assigns potential energy to an arrangement of atoms. Its energy gradient supplies the forces that drive each simulated trajectory.
Classical mechanics: The framework describing motion through forces, positions, and momenta. Most molecular dynamics simulations use its equations to evolve atoms.
Protein folding: The process by which a protein chain adopts a three-dimensional structure. Simulations probe folding motions and the stability of candidate protein structures.
Monte Carlo method: A computational method that uses random sampling to estimate properties of probability distributions. Monte Carlo samples configurations without generating physical time trajectories.
Enhanced sampling: Methods that help simulations explore configurations rarely reached in ordinary thermal sampling. Biomolecular transitions often occur too rarely for straightforward trajectories to capture.
Newton's laws of motion: Classical laws relating an object's motion to the forces acting on it. Classical molecular dynamics advances atomic positions by applying these laws.
Statistical mechanics: The framework connecting microscopic states to macroscopic thermodynamic properties. It explains how trajectory averages estimate measurable quantities.
Molecular docking: A computational method for predicting how one molecule binds within another molecule's site. Dynamics can refine docked poses and reveal motions absent from static docking.
Brownian dynamics: A simulation method for particle motion dominated by friction and stochastic forces. It replaces explicit fast solvent motion with stochastic dynamics.
Sampling problem: The difficulty of drawing enough representative configurations from a complex probability distribution. Long-lived metastable states can leave molecular dynamics averages underconverged.

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