# \donttest{
# Download a CIF file and process it without saving
pdb_file <- get_pdb_file(pdb_id = "4HHB", filetype = "cif")
# Download a PDB file, save it, and remove alternate location records
pdb_file <- get_pdb_file(pdb_id = "4HHB", filetype = "pdb", save = TRUE, path = tempdir())
# Understanding the tertiary structure of proteins is
# crucial for elucidating their functional mechanisms,
# especially in the context of ligand binding, enzyme catalysis,
# and protein-protein interactions.
# The tertiary structure refers to the three-dimensional arrangement
# of all atoms within a protein,
# including its secondary structure elements like alpha helices
# and beta sheets, and how these elements
# are organized in space. Using the get_pdb_file function
# to retrieve the PDB file and the r3dmol
# package for visualization, researchers can gain insights
# into the overall 3D structure of a protein.
# The following example demonstrates how to visualize the
# ltertiary structure of a protein using the
# PDB entry 1XYZ:
library(r3dmol)
# Retrieve and parse a PDB structure
pdb_path <- get_pdb_file("1XYZ", filetype = "pdb", save = TRUE)
# Visualize the tertiary structure using r3dmol
viewer <- r3dmol() %>%
m_add_model(pdb_path$path, format = "pdb") %>% # Load the PDB file
m_set_style(style = m_style_cartoon()) %>% # Cartoon representation
m_zoom_to()
# Display the molecular viewer
viewer
# In this example, the protein structure is represented
# in a cartoon style, which is particularly
# effective for visualizing the overall fold of the protein,
# including the orientation and interaction
# of its secondary structure elements.
#. To further enhance the analysis,
# it is often important to
# highlight specific regions of interest,
# such as potential ligand-binding sites.
# These sites can be identified based on prior knowledge,
# experimental data, or computational predictions.
# The following code snippet demonstrates
# how to highlight potential ligand-binding sites in the
# protein structure:
# Highlight potential ligand-binding sites
# Note: Manually define residues of interest based
# on prior knowledge or external analysis
binding_sites <- c(45, 60, 85) # Example residue numbers
viewer <- viewer %>%
m_set_style(
sel = m_sel(resi = binding_sites),
style = m_style_sphere(color = "red", radius = 1.5)
)
# Display the updated viewer with highlighted binding sites
viewer
# In this step, specific residues that are
# hypothesized to participate in ligand binding are
#highlighted using a spherical representation.
# The residues are selected manually based on either
# experimental data or computational predictions.
# By highlighting these sites, researchers can
# visually inspect the spatial relationship between
# these residues and other parts of the protein,
# which may provide insights into the
# protein's functional mechanisms.
# This visualization approach offers a powerful
# way to explore and communicate the 3D structure
# of proteins, making it easier to hypothesize about their function and
# interaction with other molecules.
# }
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