<p>In the second cycle, our journey with OpenMM led to a deeper understanding of forcefield design, partial charge assignment, and simulation optimization. We learned valuable lessons about fine-tuning parameters and the importance of meticulous adjustments to achieve meaningful and reliable results in molecular simulations. We also learned how simulations can be inaccurate based on how accurate the information being fed to them is, i.e. forcefields. And forcefields in their own right are hard to develop and even harder to get right, so considering the fact that some info in the forcefield could be incorrect, the data returned to us made sense to us, and though some outputs were completely out of the question such as a negative box volume, it was just a simple error! We incorrectly stored the data for that column, causing a slight confusion. We also learned that the ensemble average of a property (like temperature) calculated over multiple simulation trajectories should converge to the expected macroscopic value. In other words, if your simulated system was big enough to stick a real thermometer into it (like a protein in a buffer on your lab bench), the temperature is converged to a single, macroscopic value that is read out on your thermometer device. However, at the level of a simulation, a single trajectory is just one possible realization of the system's behavior over time. Fluctuations in any single trajectory are expected due to the inherent statistical nature of the system. Over multiple trajectories or a long enough time, the average of these fluctuations should converge to the expected value.</p>
