PocketAnalyzerPCA is approach combines a grid-based pocket detection algorithm with PCA and clustering to predict dominant binding-site deformation modes within an ensemble of protein structures/conformations. The principal component (PC) eigenvectors and their associated scores derived from this analysis provide a characterization and visualization of the pocket conformational distributions which can be used to identify relevant binding-site conformations in proteins.
The software is available under an open-source license here.
Craig et al. J. Chem. Inf. Model. (2011)
Last Modified: 01.06.2022