Non Structural Protein

Non-structural proteins are crucial for understanding protein function and are a major focus of current research. Scientists are employing diverse machine learning approaches, including graph neural networks, large language models, and various regression techniques, to predict protein properties, analyze protein-ligand interactions, and design novel proteins with improved functionalities. These efforts leverage multimodal data (sequence, structure, images) and aim to improve the accuracy and efficiency of protein analysis and engineering. The advancements in this field have significant implications for drug discovery, biotechnology, and our fundamental understanding of biological processes.