  Protein circular permutations are crucial for understanding protein evolution
and functionality. Traditional detection methods, sequence-based or
structure-based, struggle with accuracy and computational efficiency, the
latter also limited by treating proteins as rigid bodies. The plmCP method,
utilizing a protein language model, not only speeds up the detection process
but also enhances the accuracy of identifying circular permutations,
contributing significantly to protein research and engineering by acknowledging
structural flexibility.
