How to analyze conformational variability of macromolecules using codimensional PCA



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:

  1. 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.

  2. Instructions for preparation of a test data Preparation.pdf

  3. Direct analysis of 3D test structures using Principal Component Analysis (PCA) and K-means clustering: 3DPCA.pdf

  4. 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.

First eigenvector: Ratchet-like subunit rearrangement of the complex and inward movement of L1 protein EIG1_142027877.gif

Third eigenvector: anti-correlated substoichiometry of E-site tRNA and EF-Tu EIG3_142129885.gif

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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