Improving Protein Optimization with Smoothed Fitness Landscapes: A Novel Approach for Protein Engineering

The authors propose a novel method of smoothing fitness landscapes to optimize protein engineering, leading to significant improvements in protein fitness. By utilizing graph-based smoothing and Gibbs sampling, they demonstrate state-of-the-art results in GFP and AAV benchmarks.