Can ML Algorithms Simplify The Process Of Protein Engineering?

Machine learning algorithms aid in protein engineering by decreasing the experimental burden associated with techniques like directed evolution, which entails several rounds of mutagenesis and high-throughput screening. Although numerous machine learning techniques exist, only a few utilise the target protein's evolutionary history. This is where the Evolutionary Context-integrated Neural Network (ECNet) algorithm, a type of deep learning, comes into play. Huimin Zhao, the Steven L. Miller Chair of Chemical and Biomolecular Engineering, is also the Director of the National Science Foundation-funded Molecule Maker Lab Institute. He stated that "Using ECNet, we can examine the target protein and all of its homologs to determine which residues are connected together and hence critical for