Molecular simulations of enzymes can provide a wealth of knowledge to explain and characterize these uniquely complex and beautiful molecular machines. However, the vast majority of the most interesting properties of enzymes depend on what are called "rare events" – statistically rare molecular transformations such as reactions – that cannot be observed using entirely unbiased simulations. Conversely, injection of too much bias into a simulation can mask the real mechanics of the system and

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... to incorrect results. In this annotated compilation of manuscripts – one describing the rationalization of a known mechanism; the next a discovery of an unknown mechanism; and the last describing a novel software tool for automated enhanced sampling – we explore enzymatic mechanisms through simulations, relying on the minimum possible bias while capturing as complete a transition pathway perspective as possible. We also discuss the appropriate role of researcher "intuition" or general chemical knowledge in studying such complex mechanisms as are present in enzymes. Special attention is given to glycoactive enzymes, as well as to strategies for generalizing the lessons learned from studying especially unusual mechanisms or events.