Directed Evolution

Directed evolution is a powerful technique accelerating the design of improved proteins and other complex systems by mimicking natural selection through iterative cycles of mutation and selection. Current research emphasizes leveraging machine learning, particularly employing advanced models like large language models and Bayesian optimization, to guide the evolutionary process, often incorporating gradient-based methods and novel encoding strategies for efficient search within vast design spaces. This approach significantly reduces the experimental burden associated with traditional directed evolution, leading to faster discovery of optimized molecules with enhanced properties for applications in diverse fields such as biomedicine and materials science.