Molecular dynamics (MD) is a widely adopted method to study physical and chemical processes at an atomistic level in a number of fields ranging from biophysics to chemistry to materials science . Quantum mechanical (QM) simulations allow the geometries and energies to be predicted accurately by solving the Schrödinger's equation. However, the computational complexity and cost of the QM based methods make them only viable for simulating small systems for rather short periods of timeframes. Molecular dynamics (MD) simulations, on the other hand, enable the study of large systems for relatively long timeframes through a number of approximations. In this approach, atomic nucleus together with its electrons is treated as a unit particle and interactions between atoms are governed by a force field (FF), which is essentially a set of parameterized mathematical equations aimd at capturing well-known atomic interactions such as bonds, valence angles, torsion, van der Waals, and Coulomb interactions. These simplifications greatly reduce the overall computational cost, but an important measure of the predictive power of force fields is their fidelity, i.e., how well they can reproduce the results of QM calculations and experimental studies. Development of high fidelity force fields relies heavily on optimization of various force field parameters based on carefully selected quantum-chemical and experimental reference data. With the help of these approximations and careful training, MD methods have proven to be successful in atomistic simulations with billions of degrees of freedom .