How to analyze conformational variability of macromolecules using codimensional PCA
02/04/2023
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We provide an example of application of codimensional PCA to simulated 70S ribosome data. We follow information included in the Supplemental Material of "Identifying conformational states of macromolecules by eigen-analysis of resampled cryo-EM images" by Penczek et al, Structure 19, 1582-1590, 2012. This page includes:
Test data and solution to all tests. Begin from downloading the file codim.tar.gz and unpacking it: gunzip codim.tar.gz; tar -xvf codim.tar; rm codim.tar. In addition to subdirectory data containing PDB files and auxiliary programs, subdirectory codim-test contains precalculated results of most steps of the test example.
Instructions for preparation of a test data Preparation.pdf
Direct analysis of 3D test structures using Principal Component Analysis (PCA) and K-means clustering: 3DPCA.pdf
Proper codimensional PCA, including resampling of structures, PCA, computation of factorial coordinates, K-means clustering of factorial coordinates, calculation of initial structures, multireference alignment of 3D structures. codimPCA-test.pdf
Analysis of Cryo-EM Structure of the T. thermophilus 70S-tRNA-EFTu-GDP-Kirromycin Complex. Penczek, P. A., Kimmel, M., and Spahn, C. M. (2011) Identifying conformational states of macromolecules by eigen-analysis of resampled cryo-EM images, Structure 19, 1582-1590. |
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First eigenvector: Ratchet-like subunit rearrangement of the complex and inward movement of L1 protein |
Third eigenvector: anti-correlated substoichiometry of E-site tRNA and EF-Tu |
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Flexible architecture of IP3R1. Ludtke, S. J., Tran, T. P., Ngo, Q. T., Moiseenkova-Bell, V. Y., Chiu, W., and Serysheva, II. (2011) Structure 19, 1192-1199. |
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