Computational study demonstrates sequence-free ruggedness estimation improves search outcomes across protein fitness landscapes, highlighting better control for directed evolution.
Key Points
To develop a sequence-free computational framework (SLIDE) that quantifies fitness landscape ruggedness from phenotypic data and guides experimental parameters in directed evolution.
Formulated SLIDE to calculate landscape ruggedness using population-level phenotypic distributions and estimated mutation rates without requiring sequence data.
Evaluated the optimization framework across theoretical NK fitness landscapes and experimental data from four real-world protein fitness landscapes.
Accurately inferred landscape ruggedness metrics using solely bulk phenotypic measurements and mutation rates.
Enhanced directed evolution search efficiency compared with standard selection protocols, providing the largest performance gains on highly rugged fitness landscapes.