The thermostabilization of penicillin G acylase (PGA) is a difficult problem due to the large size of the protein and its complex maturation process. We developed a data-driven protein design method that requires fewer homologous sequences than the traditional consensus approach and utilizes structural information to limit the number of variants created. Approximately 50% of our 21 single-point mutants were found experimentally to be more thermostable than the wild-type PGA, two had almost threefold longer half-life at 50 degrees C, with very little effect on activity. An analysis of four programs that predict the thermostability conferred by point mutations shows little agreement between the programs and with the experimental data, emphasizing that the chosen stabilizing mutations are very difficult to predict, but that our data-driven design method should prove useful.