In Molecular Dynamics, the accuracy of the results of your simulation depends entirely on the quality of the model that you are using. This means that the equations and the parameters describing how the system behaves needs to be of a high quality within the model that you are using. These equations and parameters are what makes up the Force Field. 

 A Force Field consists of two main parts: the mathematical function (equation) which estimates potential energy (like how atoms bond or repel each other) and the parameters used within those functions. These methods fall under molecular mechanics because they only take into account the positions of atomic nuclei, ignoring the more complex behaviour of electrons and such simplification makes the Force Field simulations much faster than quantum mechanical ones, yet producing impressively accurate and precise results.

There are a number of Force Fields out there, but none of them are a one-size-fits all kind of Force Field. Therefore, we have different Force Fields designed for different purposes such as if we want to simulate small organic molecules, proteins, lipids or polymers, or different environments such as water, membranes or vacuum. Terms such as all-atom (AA), united atom (UA) and coarse-grained (CG) Force Fields denote the level of detail that the Force Field works with. AA Force Fields simulate every single atom, giving you fine detail but at a higher computational cost. UA Force Fields on the other hand simplify things by grouping aliphatic hydrogens with their carbons therefore reducing the total number of particles, while CG Force Fields takes it a step further by grouping several atoms together (e.g., three carbon atoms and their hydrogens) into what’s called a single “bead” or superatom. 

Going from AA to UA to CG what you’ll do is that you will lose the detail but on the other hand gain huge improvements in computational power, therefore making CG methods especially useful when dealing with large systems. Such systems could be simulating the behaviour of thousands of molecules, each with hundreds of atoms, making running a detailed AA simulation impractical. 

There are plenty of Force Fields to choose from and popular ones include OPLS-AA, OPLS-UA, AMBER, CHARMM, MARTINI and COGITO just to name a few. Which one to go for very much depends on your system, your goal and how long you would like to wait for the results. 

Given that no one Force Field can work for everything. Some are more versatile than others, but in most cases you will need to test and validate your chosen Force Field, ideally by checking whether it can reproduce known experimental results before diving into your full simulations. 

In the end a Force Field is a powerful, yet simplified tool. Even when using basic models such as for instance bond stretching with Hooke’s law, it can still provide a surprisingly accurate picture of the real system. One of the key strengths of a good Force Field is transferability. This means that the Force Field should not only perform well on specific molecules it was built for but also on related or larger systems. This is what makes a good Force Field a valuable cornerstone of molecular simulation.