write.pca.pdb: PDB and PML file creation for 3D representation of PCA...

In Bios2cor: From Biological Sequences and Simulations to Correlation Analysis

PDB and PML file creation for 3D representation of PCA analysis

Description

Given a PCA structure, creates .pdb and .pml files for 3D visualization with Pymol

Usage

  write.pca.pdb(corr_pca, filepathroot=NULL, trio_comp= c(1:3))

Arguments

corr_pca	An object created by the centered_pca function from a correlation/covariation matrix
filepathroot	The root for the full path name of the output PDB and PML files. Default is NULL (Two PCA_l_m_n.pdb and PCA_l_m_n.pml files are created where l, m, n are the 3 selected components). If not null, '_PCA_l_m_n.pdb' and '_PCA_l_m_n.pml' extensions are added to the root name.
trio_comp	A numeric vector of length 3 indicating the principal components to be displayed. Default is c(1, 2, 3).

Details

This function creates PDB and PML files to visualize the positions of the elements (sequence positions or dihedral angles) in a 3D space corresponding to three selected components of the PCA space. The PDB file can be viewed in any molecular graphics softaware. The PML file allows a nice representation with Pymol (axis, background color, size of points and for GPCRs, color code for helices).

Value

Returns two files: a PDB file which contains three PCA coordinates for each element in PDB format and a PML file for nice visualization with Pymol.

Author(s)

Antoine GARNIER and Marie CHABBERT

Examples

# Example for MSA
  #File path for output files
  wd <- tempdir()
  #wd <-getwd() 
  file <- file.path(wd,"test_seq5") 

  #Importing MSA file
  align <- import.msf(system.file("msa/toy_align.msf", package = "Bios2cor"))

  #Creating OMES correlation object and selecting correlation matrix
  omes <- omes(align, gap_ratio = 0.2)
  cor_omes <- omes$Zscore
 
  #Creating PCA object for selected  matrix 
  pca <- centered_pca(cor_omes, filepathroot = file, filter = NULL, pc = NULL, dec_val = 5)

  #Creating PDB and PML files (open PDB file with Pymol then "File > Run" PML file)
  indices <- c(1,2,3)
  write.pca.pdb(pca, file, indices)


 
### Example for MD
  #File path for output files
  wd <- tempdir()
  #wd <-getwd() 
  file <- file.path(wd,"test_dyn5") 

  #Redaing pdb and dcd files
  pdb <- system.file("rotamer/toy_coordinates.pdb", package= "Bios2cor")
  trj <- system.file("rotamer/toy_dynamics.dcd", package= "Bios2cor")

  #Creating dynamic_structure object for selected frames
  nb_frames_wanted <- 40
  wanted_frames <- seq(from = 5, to= nb_frames_wanted, by = 10)
  dynamic_structure <- dynamic_structure(pdb, trj, wanted_frames)

  #Creating rotamers object
  conversion_file <- system.file("rotamer/dynameomics_rotamers.csv", package= "Bios2cor")
  rotamers <- angle2rotamer(dynamic_structure, conversion_file)
  
  #Creating OMES correlation object and selecting correlation matrix
  wanted_residues <- c("W","Y","F","N")
  omes <- dynamic_omes(dynamic_structure, rotamers, wanted_residues)
  cor_omes <- omes$Zscore_noauto

  #Creating PCA object for selected matrix 
  pca <- centered_pca(cor_omes, file, filter = NULL, pc = NULL, dec_val = 5)

  #Creating PDB and PML files (open PDB file with Pymol then "File > Run" PML file)
  indices <- c(1,2,3)
  write.pca.pdb(pca, file, indices)

Bios2cor documentation built on July 8, 2022, 5:05 p.m.