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Accurate predictions of protein stability have great potential to accelerate progress in computational protein design, yet the correlation of predicted and experimentally determined stabilities remains a significant challenge. To address this problem, we have developed a computational framework based on negative multistate design in which sequence energy is evaluated in the context of both native and non-native backbone ensembles. This framework was validated experimentally with the design of ten variants of streptococcal protein G domain β1 that retained the wild-type fold, and showed a very strong correlation between predicted and experimental stabilities (R² = 0.86). When applied to four different proteins spanning a range of fold types, similarly strong correlations were also obtained. Overall, the enhanced prediction accuracies afforded by this method pave the way for new strategies to facilitate the …