Combinatorial Engineering of Proteins to Enhance Their Folding Stability

Protein folding stability is a fundamental property that determines whether a protein adopts its functional three-dimensional structure or remains unfolded and inactive. The amino acid sequence of a protein dictates how it folds, and even a single amino acid change can dramatically influence folding stability. Despite decades of experimental studies involving thousands of individual mutations, predicting the impact of mutations remains a significant challenge. The same mutation can have stabilizing, neutral, or destabilizing effects depending on the local protein context, underscoring the complexity of the sequence–structure–stability relationship, which is still not fully understood. Gaining a deeper understanding of these nuances is essential for engineering proteins with enhanced stability, enabling rational protein design, and improving the manufacturability of protein-based therapeutics. We are interested in studying the folding stability of chemokine-binding proteins called evasins, due to their high therapeutic potential as anti-inflammatory and anti-cancer agents. The insights gained from this research will directly support the development of next-generation biologics. The cutting-edge techniques used in this project include: • Generation of combinatorial mutant libraries of evasins • Display of evasin mutant libraries on the surface of phage • Selection of stable variants using Phage ELISA • Next-generation sequencing (NGS) • Application of machine learning for stability prediction