Computational chemistry allows researchers to experiment in sillico: by running a computer simulations of a biological or chemical processes of interest. Molecular dynamics with molecular mechanics model of interactions simulates N-body problem of atoms$-$it computes movements of atoms according to Newtonian physics and empirical descriptions of atomic electrostatic interactions. These simulations require high performance computing resources, as evaluations within each step are computationally demanding and billions of steps are needed to reach interesting timescales. Current methods decompose the spatial domain of the problem and calculate on parallel/distributed infrastructures. Even the methods with the highest strong scaling hit the limit at half a million cores: they are not able to cut the time to result if provided with more processors. At the dawn of exascale computing with massively parallel computational resources, we want to increase the level of parallelism by incorporating parallel-in-time computation to molecular dynamics simulations. Calculation of results in several successive time points simultaneously without a priori knowledge has been examined with no major success. We will study and implement a novel combinations of methods that according to our theoretical analyses should achieve promising speed-up compared to sequential-in-time calculation.