AutoSIM: Redesigning and automating umbrella sampling for biomolecular conformational transitions

Umbrella sampling (US) is a widely used biased simulation technique to generate projections of free energy surfaces (FES) of chemical and biomolecular processes along a reaction coordinate (RC). US results are sensitive to the choice and discretization of the RC along which bias is applied as well as simulation lengths. Furthermore, the combination and comparison of FES slices from multiple US runs remains poorly understood. Here, we address these issues through a redefined US scheme based on recent statistical insights in sampling equilibration and convergence of RCs. The scheme is implemented in an algorithm—AutoSIM—that automates US runs based on a non-equilibrated molecular dynamics (MD) trajectory initiated in the native state basin. AutoSIM can generate FES sections associated with functional conformational transitions in biomolecules independent of apriori information on RCs or even the final end state. We validate AutoSIM by comparing FES projections for alanine dipeptide and ubiquitin along the top Principal Components with those from brute-force unbiased simulations. Additionally, we apply AutoSIM to capture the energetics for large scale conformational transitions of HIV-1 protease between open and closed forms of the enzyme.