Various computational strategies have been employed to detect cryptic or "transient" locations, considering protein dynamics ( ). For example, Markov state models on molecular dynamics simulations detect cryptic sites that effectively reveal the hidden locations of two β-lactamases ( ). In their study, Gao et al. successfully produced bound conformations in lengthy microsecond molecular dynamics (MD) simulations employing unbound initial structures for a mere 8 out of the 39 systems under investigation ( ). Also, Oleinkovas et al. did not identify hidden locations for three systems using microsecond-length molecular dynamics simulations. As a result, they devised a method to improve sampling by utilising scaled Hamiltonians to sample water interfaces based on replica exchange molecular dynamics ( ). Moreover, Cimermancic et al. ( ) uncovered a set of proteins with cryptic sites for their web server, Cryptosite, which predicts binding sites. The term "cryptic" was used to describe a site that could not be identified using FPocket ( ) when utilising the unbound structure.