Optimizing Efficiency for Steered Molecular Dynamics Simulations of Protein Unfolding

Steered Molecular Dynamics (SMD) simulations represent an important computational approach for uncovering the mechanistic behaviors of bio-macromolecules under mechanical forces, closely resembling experimental techniques such as single-molecule force spectroscopy for protein unfolding. Despite its widespread application, the computational intensity of simulating large molecular systems has traditionally constrained the scope of such studies. Recent technological advancements in computer hardware have now enabled more extensive and economically viable simulations. This study investigates the unfolding of Interleukin-6 (IL-6) to determine the optimal hardware configurations for SMD simulations using GROMACS. Our findings highlight that a configuration of eight CPU cores to one GPU yields the most efficient performance. Moreover, CPUs with higher clock speeds and GPUs with greater full precise float 32 calculation ability directly enhance simulation outcomes. We also examined the impact of atom count on simulation efficiency. Additionally, we identified the most suitable hardware for SMD simulation by analyzing the cost-effectiveness of the hardware involved in this article. Our research not only elucidates the optimal hardware setup for SMD simulations of protein unfolding but also extends the feasibility of such detailed molecular investigations to a broader research community, offering a pathway to more accessible and insightful mechanistic studies at the molecular level. This also provided an important foundation for understanding and studying the mechanical mechanisms of more complex polymer unfolding in the future.