For molecular models there are two major computer simulation approaches: Monte Carlo (MC) simulations and Molecular Dynamics (MD). These techniques are used to sample a representative number of states of a model which allows us to study static properties and in the case of MD also dynamic properties of the model.
Molecular dynamics: If we have a particle and knows its position and velocity, and are able to calculate the force that acts on it, then we can integrate its dynamics (e.g. Newtons second law) to derive its trajectory. The same is possible if we have a million of interacting particles.
Monte Carlo: We want to sample representative states with a probability proportional to their Boltzmann probability. MC techniques allows us to do this by generating cleverly crafted trial states that are accepted based on their energy increase or decrease relative to the current state. This method does not provide any dynamical information, but on the other hand can sample conformations without being bound by often painfully slow natural relaxation mechanisms such as reptation in polymers.