ProAl: A Powerful Protein Structure Prediction Software

ProAl is a protein structure prediction software that uses a combination of machine learning algorithms and structural bioinformatics tools to predict the three-dimensional structure of proteins from their amino acid sequence. It was developed by the University of California, San Diego and is widely used in the field of protein structure prediction.

ProAl uses a two-stage approach to protein structure prediction. In the first stage, it uses a machine learning algorithm called "profile-based" to predict the secondary structure (i.e., the local arrangements of amino acids) of the protein. In the second stage, it uses a different machine learning algorithm called "template-based" to predict the tertiary structure (i.e., the overall 3D shape) of the protein based on the predicted secondary structure.

ProAl can be used to predict the structures of both soluble and membrane proteins, and it has been applied to a wide range of protein systems, including enzymes, receptors, and viral proteins. It is a useful tool for researchers studying protein function and dynamics, as well as for drug discovery and development.