Green fluorescent proteins (GFPs) are ubiquitous for protein tagging and live-cell imaging. Split-GFPs are widely used to study protein-protein interactions by fusing proteins of interest to split GFP fragments that create a fluorophore upon typically irreversible complementation. Thus, controlled dissociation of the fragments is desirable. Although we have found that split strands can be photodissociated, the quantum efficiency of light-induced photodissociation of split GFPs is low. Traditional protein engineering approaches to increase efficiency, including extensive mutagenesis and screening, have proved difficult to implement. To reduce the search space, key states in the dissociation process are modeled by combining classical and enhanced sampling molecular dynamics with QM/MM calculations, enabling the rational design and engineering of split GFPs with up to 20-fold faster photodissociation rates using non-intuitive amino acid changes. This demonstrates the feasibility of modeling complex molecular processes using state-of-the-art computational methods, and the potential of integrating computational methods to increase the success rate in protein engineering projects.