Researchers have developed a new algorithm to improve the performance of enzymes by introducing mutations based on the evolutionary history of the enzyme. This approach is a departure from the traditional random mutation method, which can lead to a loss of enzyme activity. By using the algorithm, researchers were able to introduce up to 84 mutations into the amino acid sequence of an enzyme called beta-lactamase, resulting in improved activity and stability at higher temperatures.
The study, published in Nature Communications, focused on the beta-lactamase enzyme, which plays a crucial role in various industrial applications and human health. By carefully selecting mutations based on the enzyme’s evolutionary history, researchers were able to enhance the enzyme’s functional performance without disrupting its 3D structure. This new approach holds promise for the development of more efficient enzymes for a variety of applications, including food production, plastic degradation, and disease treatment.
One of the key findings of the study was the discovery that coordinated changes in multiple amino acids can efficiently stabilize the 3D structure of enzymes, leading to improved activity. Despite changes to 30% of the amino acids in the beta-lactamase enzyme, the overall structure remained identical to the wild-type enzyme. This insight into the relationship between amino acid changes and enzyme stability could have far-reaching implications for enzyme engineering and protein design.
The research team, led by Dr. Amir Khan from Trinity College Dublin, utilized a scoring function that analyzed thousands of beta-lactamase sequences from diverse organisms to identify potential mutations for improving enzyme performance. The algorithm allowed researchers to make targeted changes to the amino acid sequence, resulting in significant enhancements in enzyme activity and stability. The success of this approach highlights the potential for rational enzyme engineering in various industries.
One of the key contributors to the study was Eve Napier, a second-year PhD student at Trinity College Dublin, who determined the 3D experimental structure of the engineered beta-lactamase enzyme using X-ray crystallography. Her findings confirmed that the engineered enzyme maintained its 3D structure despite multiple amino acid changes, demonstrating the effectiveness of the rational engineering approach. These results provide a foundation for future research and development in enzyme design and optimization.
The implications of this research are significant for industries that rely on enzyme-based processes, such as food production and healthcare. The ability to enhance enzyme activity and stability through targeted mutations opens up new possibilities for improving existing processes and developing novel applications. By leveraging the evolutionary history of enzymes and employing advanced algorithms, researchers can achieve better outcomes in enzyme engineering, paving the way for innovation and advancement in various fields.