Machine learning algorithms have been shown to enhance the accuracy of protein structure prediction in bioinformatics. Traditional methods for protein structure prediction rely on energy minimization and molecular dynamics simulations, which can be computationally expensive and time-consuming. Machine learning algorithms can be used to predict protein structure more efficiently and accurately by learning from large datasets of known protein structures and their corresponding sequences

Machine learning algorithms can be used to predict protein structure by analyzing the relationships between amino acid sequences and protein structures. These algorithms can identify patterns in the data and use them to predict the structure of unknown proteins. Machine learning algorithms can also be used to predict the stability of protein structures and to identify potential drug targets

https://researchoutreach.org/articles/protein-structure-prediction-machine-learning/

https://calla.rnet.missouri.edu/cheng/ieee_review.pdf