Computational Approaches to Biofoundry-based Protein Engineering and Synthetic Biology

Abstract

This thesis explores the integration of computational approaches with biofoundry-based protein engineering and synthetic biology to advance the design and optimization of novel biological systems. Biofoundries—automated laboratories equipped with high-throughput capabilities—are transforming the landscape of synthetic biology by enabling the rapid construction and testing of genetic circuits and engineered proteins. However, the complexity of biological systems, including non-linear gene interactions, cellular variability, and metabolic feedback, presents significant challenges in predicting and controlling engineered behaviors. In this context, we offer offer critical solutions by providing predictive models, optimizing genetic designs, and computational tools for automating iterative design-build-test cycles.

The work presented in this thesis focuses on the development and application of computational methodologies to enhance protein engineering efforts within the biofoundry framework. A key aspect of this research involves the integration of experimental data with computational models to iteratively refine and validate design predictions spceifically in the context of protein engineering. Through case studies and practical applications, the synergy between computational approaches and biofoundry automation to accelerate the development of synthetic biological systems is demonstrated.

The findings of this thesis highlight the potential of computational methods to address the inherent challenges of protein engineering and synthetic biology, providing a pathway toward more rational, scalable, and predictable design strategies. The research is consisely packaged as a SynBio stack called High-throughput AI-based protein engineering, which comprises of the relevant computational tools and experimental protocols to replicate the engineering processs for a target protein (or even a bio-part).Ultimately, this work contributes to the growing field of computational synthetic biology and biofoundry research, with implications for industrial biotechnology, biomanufacturing, and the broader application of engineered biological systems.